Spatial and Temporal Analysis of Industrial Forest Clearcuts in the Conterminous United States

NASA Astrophysics Data System (ADS)

Huo, L. Z.; Boschetti, L.

2015-12-01

Remote sensing has been widely used for mapping and characterizing changes in forest cover, but the available remote sensing forest change products are not discriminating between deforestation (permanent transition from forest to non forest) and industrial forest management (logging followed by regrowth, with no land cover/ land use class change) (Hansen et al, 2010). Current estimates of carbon-equivalent emissions report the contribution of deforestation as 12% of total anthropogenic carbon emissions (van der Werf et al., 2009), but accurate monitoring of forest carbon balance should discriminate between land use change related to forest natural disturbances, and forest management. The total change in forest cover (Gross Forest Cover Loss, GFLC) needs to be characterized based on the cause (natural/human) and on the outcome of the change (regeneration to forest/transition to non/forest)(Kurtz et al, 2010). This paper presents the methodology used to classify the forest loss detected by the University of Maryland Global Forest Change product (Hansen, 2013) into deforestation, disturbances (fires, insect outbreaks) and industrial forest clearcuts. The industrial forest clearcuts were subsequently analysed by converting the pixel based detections into objects, and applying patch level metrics (e.g. size, compactness, straightness of boundaries) and contextual measures. The analysis is stratified by region and by dominant forest specie, to highlight changes in the rate of forest resource utilization in the 2003-2013 period covered by the Maryland Forest Cover Change Product. References Hansen, M.C., Stehman, S.V., & Potapov, P.V. (2010). Reply to Wernick et al.: Global scale quantification of forest change. Proceedings of the National Academy of Sciences, 107, E148-E148 Hansen, M.C., Potapov, P.V., Moore, R et al., (2013), "High resolution Global Maps for the 21stCentury Forest Cover Change", Science 342: 850-853 Kurz, W.A. (2010). An ecosystem context for global gross forest cover loss estimates. Proceedings of the National Academy of Sciences, 107, 9025-9026 van der Werf, G.R., Morton, D.C., DeFries, R.S., Olivier, J.G., Kasibhatla, P.S., Jackson, R.B., Collatz, G.J., & Randerson, J. (2009). CO2 emissions from forest loss. Nature Geoscience, 2, 737-738

A statistical power analysis of woody carbon flux from forest inventory data

Treesearch

James A. Westfall; Christopher W. Woodall; Mark A. Hatfield

2013-01-01

At a national scale, the carbon (C) balance of numerous forest ecosystem C pools can be monitored using a stock change approach based on national forest inventory data. Given the potential influence of disturbance events and/or climate change processes, the statistical detection of changes in forest C stocks is paramount to maintaining the net sequestration status of...

A Multi-Index Integrated Change detection method for updating the National Land Cover Database

USGS Publications Warehouse

Jin, Suming; Yang, Limin; Xian, George Z.; Danielson, Patrick; Homer, Collin G.

2010-01-01

Land cover change is typically captured by comparing two or more dates of imagery and associating spectral change with true thematic change. A new change detection method, Multi-Index Integrated Change (MIIC), has been developed to capture a full range of land cover disturbance patterns for updating the National Land Cover Database (NLCD). Specific indices typically specialize in identifying only certain types of disturbances; for example, the Normalized Burn Ratio (NBR) has been widely used for monitoring fire disturbance. Recognizing the potential complementary nature of multiple indices, we integrated four indices into one model to more accurately detect true change between two NLCD time periods. The four indices are NBR, Normalized Difference Vegetation Index (NDVI), Change Vector (CV), and a newly developed index called the Relative Change Vector (RCV). The model is designed to provide both change location and change direction (e.g. biomass increase or biomass decrease). The integrated change model has been tested on five image pairs from different regions exhibiting a variety of disturbance types. Compared with a simple change vector method, MIIC can better capture the desired change without introducing additional commission errors. The model is particularly accurate at detecting forest disturbances, such as forest harvest, forest fire, and forest regeneration. Agreement between the initial change map areas derived from MIIC and the retained final land cover type change areas will be showcased from the pilot test sites.

Detecting and Quantifying Forest Change: The Potential of Existing C- and X-Band Radar Datasets.

PubMed

Tanase, Mihai A; Ismail, Ismail; Lowell, Kim; Karyanto, Oka; Santoro, Maurizio

2015-01-01

This paper evaluates the opportunity provided by global interferometric radar datasets for monitoring deforestation, degradation and forest regrowth in tropical and semi-arid environments. The paper describes an easy to implement method for detecting forest spatial changes and estimating their magnitude. The datasets were acquired within space-borne high spatial resolutions radar missions at near-global scales thus being significant for monitoring systems developed under the United Framework Convention on Climate Change (UNFCCC). The approach presented in this paper was tested in two areas located in Indonesia and Australia. Forest change estimation was based on differences between a reference dataset acquired in February 2000 by the Shuttle Radar Topography Mission (SRTM) and TanDEM-X mission (TDM) datasets acquired in 2011 and 2013. The synergy between SRTM and TDM datasets allowed not only identifying changes in forest extent but also estimating their magnitude with respect to the reference through variations in forest height.

Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2014-01-01

A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

Soil Carbon Variability and Change Detection in the Forest Inventory Analysis Database of the United States

NASA Astrophysics Data System (ADS)

Wu, A. M.; Nater, E. A.; Dalzell, B. J.; Perry, C. H.

2014-12-01

The USDA Forest Service's Forest Inventory Analysis (FIA) program is a national effort assessing current forest resources to ensure sustainable management practices, to assist planning activities, and to report critical status and trends. For example, estimates of carbon stocks and stock change in FIA are reported as the official United States submission to the United Nations Framework Convention on Climate Change. While the main effort in FIA has been focused on aboveground biomass, soil is a critical component of this system. FIA sampled forest soils in the early 2000s and has remeasurement now underway. However, soil sampling is repeated on a 10-year interval (or longer), and it is uncertain what magnitude of changes in soil organic carbon (SOC) may be detectable with the current sampling protocol. We aim to identify the sensitivity and variability of SOC in the FIA database, and to determine the amount of SOC change that can be detected with the current sampling scheme. For this analysis, we attempt to answer the following questions: 1) What is the sensitivity (power) of SOC data in the current FIA database? 2) How does the minimum detectable change in forest SOC respond to changes in sampling intervals and/or sample point density? Soil samples in the FIA database represent 0-10 cm and 10-20 cm depth increments with a 10-year sampling interval. We are investigating the variability of SOC and its change over time for composite soil data in each FIA region (Pacific Northwest, Interior West, Northern, and Southern). To guide future sampling efforts, we are employing statistical power analysis to examine the minimum detectable change in SOC storage. We are also investigating the sensitivity of SOC storage changes under various scenarios of sample size and/or sample frequency. This research will inform the design of future FIA soil sampling schemes and improve the information available to international policy makers, university and industry partners, and the public.

Spatial Analysis for Monitoring Forest Health

Treesearch

Francis A. Roesch

1994-01-01

A plan for the spatial analysis for the sample design for the detection monitoring phase in the joint USDA Forest Service/EPA Forest Health Monitoring Program (FHM) in the United States is discussed. The spatial analysis procedure is intended to more quickly identify changes in forest health by providing increased sensitivity to localized changes. The procedure is...

Estimating forestland area change from inventory data

Treesearch

Paul Van Deusen; Francis Roesch; Thomas Wigley

2013-01-01

Simple methods for estimating the proportion of land changing from forest to nonforest are developed. Variance estimators are derived to facilitate significance tests. A power analysis indicates that 400 inventory plots are required to reliably detect small changes in net or gross forest loss. This is an important result because forest certification programs may...

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, J.; Smoot, J.; Kuper, P.

2011-12-01

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of a web-based national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. The FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each of our forest change products in FCAV is based on current versus historical 24 day composites of NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI for a given 24 day period. Change products are computed according to previous year, previous 3 year and previous 8 year historical baselines. The use of multiple baselines enables apparent forest disturbance anomalies to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service constructed and maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to view and monitor forest hazards at regional scales throughout the year and across the nation.

Change detection for soil carbon in the forest inventory and analysis

Treesearch

An-Min Wu; Edward A. Nater; Charles H. Perry; Brent J. Dalzell; Barry T. Wilson

2015-01-01

Estimates of carbon stocks and stock changes in the U.S. Department of Agriculture Forest Service’s Forest Inventory and Analysis (FIA) Program are reported as the official United States submission to the UN Framework Convention on Climate Change. Soil, as a critical component of the forest carbon stocks, has been sampled in about 10-year intervals in FIA with the re-...

Aerial detection surveys in the United States

Treesearch

E. W. Johnson; D. Wittwer

2006-01-01

Aerial detection surveys, also known as aerial sketchmapping, is a remote sensing technique of observing forest change events from an aircraft and documenting them manually onto a map. Data from aerial surveys have become an important component of the Forest Health Monitoring, a national program designed to determine the status, changes, and trends in indicators of...

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Glasser, Jerry; Kuper, Philip D.

2011-01-01

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Forest land cover change (1975-2000) in the Greater Border Lakes region

Treesearch

Peter T. Wolter; Brian R. Sturtevant; Brian R. Miranda; Sue M. Lietz; Phillip A. Townsend; John Pastor

2012-01-01

This document and accompanying maps describe land cover classifications and change detection for a 13.8 million ha landscape straddling the border between Minnesota, and Ontario, Canada (greater Border Lakes Region). Land cover classifications focus on discerning Anderson Level II forest and nonforest cover to track spatiotemporal changes in forest cover. Multi-...

Comprehensive methods for earlier detection and monitoring of forest decline

Treesearch

Jennifer Pontius; Richard Hallett

2014-01-01

Forested ecosystems are threatened by invasive pests, pathogens, and unusual climatic events brought about by climate change. Earlier detection of incipient forest health problems and a quantitatively rigorous assessment method is increasingly important. Here, we describe a method that is adaptable across tree species and stress agents and practical for use in the...

The Detection and Characterization of Urbanization, Industrialization, and Longwall Mining Impacts on Forest Ecosystems Through the Use of GiS and Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Pfeil-McCullough, Erin Kathleen

Urbanization has far reaching and significant effects on forest ecosystems, directly through urban development and indirectly through supportive processes such as coal mining and agriculture. Urban processes modify the landscape leading to altered hillslope hydrology, increased disturbance, and the introduction of non-native forest pathogens. This dissertation addresses several challenges in our ability to detect these urbanization impacts on forests via geospatial analyses. The role of forests in urban hydrological processes has been extensively studied, but the impacts of urbanized hydrology on forests remain poorly examined. This dissertation documented impacts to hydrology and forests at variety of temporal and spatial scales: 1) A geospatial comparison of the historic and contemporary forests of Allegheny County, Pennsylvania revealed substantial shifts in tree species, but less change in the species soil moisture preference. These results document additional evidence that increased heterogeneity in urban soil moisture alters forest structure. 2) To examine soil moisture changes, impacts of longwall mine subsidence were assessed by using a Landsat based canopy moisture index and hot spot analysis tools at the forest patch scale. Declines in forest canopy moisture were detected over longwall mines as mining progressed through time, and results contradicted assumptions that the hydrological impacts overlying LMS recover within 4-5 years following subsidence of undermined land. 3) Utilizing a landslide susceptibility model (SINMAP), increases in landslide susceptibility were predicted in Pittsburgh, PA based on several scenarios of ash tree loss to the emerald ash borer (EAB), a bark beetle that rapidly kills ash trees. This model provides a tool to predict changes in landslide susceptibility following tree loss, increasing the understanding of urban forest function and its role in slope stability. Detecting how urbanized hydrology impacts forest health, function, and development is fundamental to sustaining the services forests provide. Results from this dissertation will ultimately allow improvements in the management and protection of both trees and water resources in urban systems and beyond.

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

USGS Publications Warehouse

Shermeyer, Jacob S.; Haack, Barry N.

2015-01-01

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Tree migration detection through comparisons of historic and current forest inventories

Treesearch

Christopher W. Woodall; Christopher M. Oswalt; James A. Westfall; Charles H. Perry; Mark N. Nelson

2009-01-01

Changes in tree species distributions are a potential impact of climate change on forest ecosystems. The examination of tree species shifts in forests of the eastern United States largely has been limited to modeling activities with little empirical analysis of long-term forest inventory datasets. The goal of this study was to compare historic and current spatial...

Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

Monitoring tropical forest degradation using time series analysis of Landsat and Sentinel-2 data

NASA Astrophysics Data System (ADS)

Bullock, E.; Woodcock, C. E.

2017-12-01

Tropical forest loss is expected to be contribute 5 to 15% of anthropogenic carbon emissions in the coming century. The wide range of expected emissions is indicative of the large uncertainties that exist in the terrestrial carbon cycle. Total carbon loss from forest conversion consists of loss from deforestation plus loss from degradation. There have been significant improvements in the ability to relate plot-level estimates of carbon stocks to remote sensing-derived calculations of deforestation to estimate total carbon emissions from forest loss. These approaches, however, have been limited in their ability to assess the magnitude, extent, and overall impact of forest degradation. The causes of tropical degradation include selective logging, fuel wood collection, fires, and the development of forest plantations. This study demonstrates a newly developed methodology for detecting subtle changes in forest structure and condition using time series analysis of Landsat and Sentinel-2 data. The research shows how the ability to detect small changes in forest biomass, in addition to changes in forest composition, can be improved by incorporating historical context and multi-sensor data fusion. Results are demonstrated from two climatically unique tropical forests in Thailand and Brazil.

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, J.; Smoot, J.; Kuper, P.

2010-01-01

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009,. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornadoes, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, J.; Smoot, J.; Kuper, P.

2010-12-01

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service’s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornados, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

Optimal use of land surface temperature data to detect changes in tropical forest cover

NASA Astrophysics Data System (ADS)

van Leeuwen, Thijs T.; Frank, Andrew J.; Jin, Yufang; Smyth, Padhraic; Goulden, Michael L.; van der Werf, Guido R.; Randerson, James T.

2011-06-01

Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the buildup of atmospheric CO2. Here we examined different ways to use land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05° × 0.05° Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of LST and Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10° × 10° included the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (˜1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pantropical deforestation classifiers. Combined with the normalized difference vegetation index, a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES.

The power of FIA Phase 3 Crown-Indicator variables to detect change

Treesearch

William Bechtold; KaDonna Randolph; Stanley Zarnoch

2009-01-01

The goal of Phase 3 Detection Monitoring as implemented by the Forest Inventory and Analysis Program is to identify forest ecosystems where conditions might be deteriorating in subtle ways over large areas. At the relatively sparse sampling intensity of the Phase 3 plot network, a rough measure of success for the forest health indicators developed for this purpose is...

Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Moran, Emilio

2009-01-01

Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM image. A rule-based approach was used to classify the TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and post-classification comparison was used to detect vegetation change trajectories. This research indicates promising vegetation change techniques, especially for vegetation gain and loss, even if very limited reference data are available. PMID:19789721

TEMPORAL CHANGE IN FOREST FRAGMENTATION AT MULTIPLE SCALES

EPA Science Inventory

Previous studies of temporal changes in fragmentation have focused almost exclusively on patch and edge statistics, which might not detect changes in the spatial scale at which forest occurs in or dominates the landscape. We used temporal land-cover data for the Chesapeake Bay r...

An Online 3D Database System for Endangered Architectural and Archaeological Heritage in the South-Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Abate, D.; Avgousti, A.; Faka, M.; Hermon, S.; Bakirtzis, N.; Christofi, P.

2017-10-01

This study compares performance of aerial image based point clouds (IPCs) and light detection and ranging (LiDAR) based point clouds in detection of thinnings and clear cuts in forests. IPCs are an appealing method to update forest resource data, because of their accuracy in forest height estimation and cost-efficiency of aerial image acquisition. We predicted forest changes over a period of three years by creating difference layers that displayed the difference in height or volume between the initial and subsequent time points. Both IPCs and LiDAR data were used in this process. The IPCs were constructed with the Semi-Global Matching (SGM) algorithm. Difference layers were constructed by calculating differences in fitted height or volume models or in canopy height models (CHMs) from both time points. The LiDAR-derived digital terrain model (DTM) was used to scale heights to above ground level. The study area was classified in logistic regression into the categories ClearCut, Thinning or NoChange with the values from the difference layers. We compared the predicted changes with the true changes verified in the field, and obtained at best a classification accuracy for clear cuts 93.1 % with IPCs and 91.7 % with LiDAR data. However, a classification accuracy for thinnings was only 8.0 % with IPCs. With LiDAR data 41.4 % of thinnings were detected. In conclusion, the LiDAR data proved to be more accurate method to predict the minor changes in forests than IPCs, but both methods are useful in detection of major changes.

ALOS-PALSAR multi-temporal observation for describing land use and forest cover changes in Malaysia

NASA Astrophysics Data System (ADS)

Avtar, R.; Suzuki, R.; Ishii, R.; Kobayashi, H.; Nagai, S.; Fadaei, H.; Hirata, R.; Suhaili, A. B.

2012-12-01

The establishment of plantations in carbon rich peatland of Southeast Asia has shown an increase in the past decade. The need to support development in countries such as Malaysia has been reflected by having a higher rate of conversion of its forested areas to agricultural land use in particular oilpalm plantation. Use of optical data to monitor changes in peatland forests is difficult because of the high cloudiness in tropical region. Synthetic Aperture Radar (SAR) based remote sensing can potentially be used to monitor changes in such forested landscapes. In this study, we have demonstrated the capability of multi-temporal Fine-Beam Dual (FBD) data of Phased Array L-band Synthetic Aperture Radar (PALSAR) to detect forest cover changes in peatland to other landuse such as oilpalm plantation. Here, the backscattering properties of radar were evaluated to estimate changes in the forest cover. Temporal analysis of PALSAR FBD data shows that conversion of peatland forest to oilpalm can be detected by analyzing changes in the value of σoHH and σoHV. This is characterized by a high value of σoHH (-7.89 dB) and σoHV (-12.13 dB) for areas under peat forests. The value of σoHV decreased about 2-4 dB due to the conversion of peatland to a plantation area. There is also an increase in the value of σoHH/σoHV. Changes in σoHV is more prominent to identify the peatland conversion than in the σoHH. The results indicate the potential of PALSAR to estimate peatland forest conversion based on thresholding of σoHV or σoHH/σoHV for monitoring changes in peatland forest. This would improve our understanding of the temporal change and its effect on the peatland forest ecosystem.

Waveform LiDAR across forest biomass gradients

NASA Astrophysics Data System (ADS)

Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

2011-12-01

Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (< 50Mg/ha) AGB. We relate field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

NASA Astrophysics Data System (ADS)

Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

2017-01-01

Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

PubMed Central

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions. PMID:24717283

A practical and automated approach to large area forest disturbance mapping with remote sensing.

PubMed

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.

Exploring the association of the Minnesota Department of Natural Resources' satellite-detected change with the Forest Inventory and Analysis system of observed removals and mortality

Treesearch

Dale D. Gormanson; Timothy J. Aunan; Mark H. Hansen; Michael Hoppus

2009-01-01

Since 2001, the Minnesota Department of Natural Resources (MN-DNR) has mapped forest change annually by comparison of Landsat satellite image pairs. Over the same timeframe, 1,761 U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) plots in Minnesota have been remeasured on a 5-year cycle, providing field data on growth, removals, and...

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, J.; Norman, S. P.

2013-12-01

Forest threats across the US have become increasingly evident in recent years. These include regionally extensive disturbances (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and result in extensive forest mortality. In addition, forests can be subject to ephemeral, sometimes yearly defoliation from various insects and types of storm damage. After prolonged severe disturbance, signs of forest recovery can vary in terms of satellite-based Normalized Difference Vegetation Index (NDVI) values. The increased extent and threat of forest disturbances in part led to the enactment of the 2003 Healthy Forest Restoration Act, which mandated that a national forest threat Early Warning System (EWS) be deployed. In response, the US Forest Service collaborated with NASA, DOE Oak Ridge National Laboratory, and the USGS Eros Data Center to build the near real time ForWarn forest threat EWS for monitoring regionally evident forest disturbances, starting on-line operations in 2010. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines used with current NDVI to derive a suite of six nationwide 'weekly' forest change products. ForWarn uses daily 232 meter MODIS Aqua and Terra satellite NDVI data, including MOD13 products for deriving historical baseline NDVIs and eMODIS products for compiling current NDVI. Separately pre-processing the current and historical NDVIs, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally reduce noise, fuse, and aggregate MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of forest change products per year. The 24 day compositing interval typically enables new disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. ForWarn's three standard forest change products compare current NDVI to that from the previous year, previous 3 years, and all previous years since 2000. Other forest change products added in 2013 include one for quicker disturbance detection and two others that adjust for seasonal fluctuations in normal vegetation phenology. This product suite and ForWarn's geospatial data viewer allow end users to view and assess disturbance dynamics for many regionally evident biotic and abiotic forest disturbances throughout a given current year. ForWarn's change products are also being used for forest change trend analysis and for developing regional forest overstory mortality products. They are used to alert forest health specialists about new regional forest disturbances. Such alerts also typically consider available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances for multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn provides forest change products that could be combined with other geospatial data on forest biomass to help assess forest disturbance carbon impacts within the conterminous US.

Satellite change detection of forest damage near the Chernobyl accident

DOE Office of Scientific and Technical Information (OSTI.GOV)

McClellan, G.E.; Anno, G.H.

1992-01-01

A substantial amount of forest within a few kilometers of the Chernobyl nuclear reactor station was badly contaminated with radionuclides by the April 26, 1986, explosion and ensuing fire at reactor No. 4. Radiation doses to conifers in some areas were sufficient to cause discoloration of needles within a few weeks. Other areas, receiving smaller doses, showed foliage changes beginning 6 months to a year later. Multispectral imagery available from Landsat sensors is especially suited for monitoring such changes in vegetation. A series of Landsat Thematic Mapper images was developed that span the 2 yr following the accident. Quantitative dosemore » estimation for the exposed conifers requires an objective change detection algorithm and knowledge of the dose-time response of conifers to ionizing radiation. Pacific-Sierra Research Corporation's Hyperscout{trademark} algorithm is based on an advanced, sensitive technique for change detection particularly suited for multispectral images. The Hyperscout algorithm has been used to assess radiation damage to the forested areas around the Chernobyl nuclear power plant.« less

Monitoring Forest Degradation for a Case Study in Cambodia: Comparison of Landsat 8 and Sentinel-2 Imagery

NASA Astrophysics Data System (ADS)

Langner, Andreas; Miettinen, Jukka; Stibig, Hans-Jurgen

2016-08-01

We use a Normalized Burned Ratio (NBR) differential approach for detecting forest canopy disturbance caused by selective logging in evergreen tropical moist forests of central Cambodia. The general disturbance pattern obtained from Landsat 8 (30 m) imagery is largely compatible to Sentinel-2 (10 m), showing good conformity to high resolution RapidEye reference data. However, the 10 m spatial resolution of Sentinel-2 provides notably higher spatial detail and purer pixel values, increasing the potential for detecting fine and subtle forest canopy changes as indicators for potential forest degradation. We can expect further improvement for detecting short-lived disturbance signals in tropical forest canopies due to an increased revisit frequency (5 days) after the Sentinel-2B launch.

Forest health monitoring indicators and their interpretability: a Lithuanian case study

Treesearch

Romualdas Kuknys; Algirdas Augustaitis

1998-01-01

Growth and productivity of forests are important indicators for understanding the general condition and health of forests. It is very important that indicators detected during monitoring procedures afford an opportunity for direct or indirect evaluation of forest productivity and its natural and anthropogenic changes. Analysis of the U.S. Forest Health Monitoring (FHM...

Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD.

PubMed

Mitchell, Anthea L; Rosenqvist, Ake; Mora, Brice

2017-12-01

Forest degradation is a global phenomenon and while being an important indicator and precursor to further forest loss, carbon emissions due to degradation should also be accounted for in national reporting within the frame of UN REDD+. At regional to country scales, methods have been progressively developed to detect and map forest degradation, with these based on multi-resolution optical, synthetic aperture radar (SAR) and/or LiDAR data. However, there is no one single method that can be applied to monitor forest degradation, largely due to the specific nature of the degradation type or process and the timeframe over which it is observed. The review assesses two main approaches to monitoring forest degradation: first, where detection is indicated by a change in canopy cover or proxies, and second, the quantification of loss (or gain) in above ground biomass (AGB). The discussion only considers degradation that has a visible impact on the forest canopy and is thus detectable by remote sensing. The first approach encompasses methods that characterise the type of degradation and track disturbance, detect gaps in, and fragmentation of, the forest canopy, and proxies that provide evidence of forestry activity. Progress in these topics has seen the extension of methods to higher resolution (both spatial and temporal) data to better capture the disturbance signal, distinguish degraded and intact forest, and monitor regrowth. Improvements in the reliability of mapping methods are anticipated by SAR-optical data fusion and use of very high resolution data. The second approach exploits EO sensors with known sensitivity to forest structure and biomass and discusses monitoring efforts using repeat LiDAR and SAR data. There has been progress in the capacity to discriminate forest age and growth stage using data fusion methods and LiDAR height metrics. Interferometric SAR and LiDAR have found new application in linking forest structure change to degradation in tropical forests. Estimates of AGB change have been demonstrated at national level using SAR and LiDAR-assisted approaches. Future improvements are anticipated with the availability of next generation LiDAR sensors. Improved access to relevant satellite data and best available methods are key to operational forest degradation monitoring. Countries will need to prioritise their monitoring efforts depending on the significance of the degradation, balanced against available resources. A better understanding of the drivers and impacts of degradation will help guide monitoring and restoration efforts. Ultimately we want to restore ecosystem service and function in degraded forests before the change is irreversible.

Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2014-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in forest vegetation cover for areas burned by wildfires in the Sierra Nevada Mountains of California between the periods of 1975- 79 and 1995-1999. Results for areas burned by wildfire between 1995 and 1999 confirmed the importance of regrowing forest vegetation over 17% of the combined burned areas. A notable fraction (12%) of the entire 5-km (unburned) buffer area outside the 1995-199 fires perimeters showed decline in forest cover, and not nearly as many regrowing forest areas, covering only 3% of all the 1995-1999 buffer areas combined. Areas burned by wildfire between 1975 and 1979 confirmed the importance of disturbed (or declining evergreen) vegetation covering 13% of the combined 1975- 1979 burned areas. Based on comparison of these results to ground-based survey data, the LEDAPS methodology should be capable of fulfilling much of the need for consistent, low-cost monitoring of changes due to climate and biological factors in western forest regrowth following stand-replacing disturbances.

Volumetric Forest Change Detection Through Vhr Satellite Imagery

NASA Astrophysics Data System (ADS)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.

Optimal use of land surface temperature data to detect changes in tropical forest cover

NASA Astrophysics Data System (ADS)

Van Leeuwen, T. T.; Frank, A. J.; Jin, Y.; Smyth, P.; Goulden, M.; van der Werf, G.; Randerson, J. T.

2011-12-01

Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the build up of atmospheric CO2. Here we examined different ways to use remotely sensed land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05×0.05 degree Terra MODerate Resolution Imaging Spectroradiometer (MODIS) observations of LST and PRODES (Program for the Estimation of Deforestation in the Brazilian Amazon) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10×10 degree included most of the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (~1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pan-tropical deforestation classifiers. Combined with the normalized difference vegetation index (NDVI), a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST difference decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES. The use of day-night LST differences may be particularly valuable for use with satellites that do not have spectral bands that allow for the estimation of NDVI or other vegetation indices.

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Gasser, Gerald

2013-01-01

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.

Optical remote sensing for forest area estimation

Treesearch

Randolph H. Wynne; Richard G. Oderwald; Gregory A. Reams; John A. Scrivani

2000-01-01

The air photo dot-count method is now widely and successfully used for estimating operational forest area in the USDA Forest Inventory and Analysis (FIA) program. Possible alternatives that would provide for more frequent updates, spectral change detection, and maps of forest area include the AVHRR calibration center technique and various Landsat TM classification...

Using forest health monitoring data to integrate above and below ground carbon information

Treesearch

Barbara L. Conkling; Coeli M. Hoover; William D. Smith; Craig J. Palmer

2002-01-01

The national Forest Health Monitoring (FHM) program conducted a remeasurement study in 1999 to evaluate the usefulness and feasibility of collecting data needed for investigating carbon budgets in forests. This study indicated that FHM data are adequate for detecting a 20% change over 10 years (2% change per year) in percent total carbon and carbon content (MgC/ha)...

Quantifying Structural and Compositional Changes in Forest Cover in NW Yunnan, China

NASA Astrophysics Data System (ADS)

Hakkenberg, C.

2012-12-01

NW Yunnan, China is a region renowned for high levels of biodiversity, endemism and genetically distinct refugial plant populations. It is also a focal area for China's national reforestation efforts like the Natural Forest Protection Program (NFPP), intended to control erosion in the Upper Yangtze watershed. As part of a larger project to investigate the role of reforestation programs in facilitating the emergence of increasingly species-rich forest communities on a previously degraded and depauperate land mosaic in montane SW China, this study uses a series of Landsat TM images to quantify the spatial pattern and rate of structural and compositional change in forests recovering from medium to large-scale disturbances in the area over the past 25 years. Beyond the fundamental need to assess the outcomes of one of the world's largest reforestation programs, this research offers approaches to confronting two critical methodological issues: (1) techniques for characterizing subtle changes in the nature of vegetation cover, and (2) reducing change detection uncertainty due to persistent cloud cover and shadow. To address difficulties in accurately assessing the structure and composition of vegetative regrowth, a biophysical model was parameterized with over 300 ground-truthed canopy cover assessment points to determine pattern and rate of long-term vegetation changes. To combat pervasive shadow and cloud cover, an interactive generalized additive model (GAM) model based on topographic and spatial predictors was used to overcome some of the constraints of satellite image analysis in Himalayan regions characterized by extreme topography and extensive cloud cover during the summer monsoon. The change detection is assessed for accuracy using ground-truthed observations in a variety of forest cover types and topographic positions. Results indicate effectiveness in reducing the areal extent of unclassified regions and increasing total change detection accuracy. In addition to quantifying forest cover change in this section of NW Yunnan, the analysis attempts to qualify that change - distinguishing among distinct disturbance histories and post-recovery successional pathways.

Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black Sea region--a case study.

PubMed

Coban, Huseyin Oguz; Koc, Ayhan; Eker, Mehmet

2010-01-01

Previous studies have been able to successfully detect changes in gently-sloping forested areas with low-diversity and homogeneous vegetation cover using medium-resolution satellite data such as landsat. The aim of the present study is to examine the capacity of multi-temporal landsat data to identify changes in forested areas with mixed vegetation and generally located on steep slopes or non-uniform topography landsat thematic mapper (TM) and landsat enhanced thematic mapperplus (ETM+) data for the years 1987-2000 was used to detect changes within a 19,500 ha forested area in the Western Black sea region of Turkey. The data comply with the forest cover type maps previously created for forest management plans of the research area. The methods used to detect changes were: post-classification comparison, image differencing, image rationing and NDVI (Normalized Difference Vegetation Index) differencing methods. Following the supervised classification process, error matrices were used to evaluate the accuracy of classified images obtained. The overall accuracy has been calculated as 87.59% for 1987 image and as 91.81% for 2000 image. General kappa statistics have been calculated as 0.8543 and 0.9038 for 1987 and 2000, respectively. The changes identified via the post-classification comparison method were compared with other change detetion methods. Maximum coherence was found to be 74.95% at 4/3 band rate. The NDVI difference and 3rd band difference methods achieved the same coherence with slight variations. The results suggest that landsat satellite data accurately conveys the temporal changes which occur on steeply-sloping forested areas with a mixed structure, providing a limited amount of detail but with a high level of accuracy. Moreover it has been decided that the post-classification comparison method can meet the needs of forestry activities better than other methods as it provides information about the direction of these changes.

Forest health monitoring in the Ngangao Forest, Taita Tills, Kenya: A five year assessment of change

Treesearch

Paul C. Rogers; Barbara O' Connell; James Mwang' ombe; Seif Madoffe; Gerard Hertel

2008-01-01

Forest Health Monitoring (FHM) provides a standardized detection-level survey of forest and tree characteristics for large forested areas. We have adopted FHM methods from this temperate-based program to tropical forests in the Eastern Arc Mountains (EAM) of Kenya and Tanzania. This paper reports the first assessment of trend data in the EAM over a period from 2001 to...

Forest genetic monitoring: an overview of concepts and definitions.

PubMed

Fussi, Barbara; Westergren, Marjana; Aravanopoulos, Filippos; Baier, Roland; Kavaliauskas, Darius; Finzgar, Domen; Alizoti, Paraskevi; Bozic, Gregor; Avramidou, Evangelia; Konnert, Monika; Kraigher, Hojka

2016-08-01

Safeguarding sustainability of forest ecosystems with their habitat variability and all their functions is of highest priority. Therefore, the long-term adaptability of forest ecosystems to a changing environment must be secured, e.g., through sustainable forest management. High adaptability is based on biological variation starting at the genetic level. Thus, the ultimate goal of the Convention on Biological Diversity (CBD) to halt the ongoing erosion of biological variation is of utmost importance for forest ecosystem functioning and sustainability. Monitoring of biological diversity over time is needed to detect changes that threaten these biological resources. Genetic variation, as an integral part of biological diversity, needs special attention, and its monitoring can ensure its effective conservation. We compare forest genetic monitoring to other biodiversity monitoring concepts. Forest genetic monitoring (FGM) enables early detection of potentially harmful changes of forest adaptability before these appear at higher biodiversity levels (e.g., species or ecosystem diversity) and can improve the sustainability of applied forest management practices and direct further research. Theoretical genetic monitoring concepts developed up to now need to be evaluated before being implemented on a national and international scale. This article provides an overview of FGM concepts and definitions, discusses their advantages and disadvantages, and provides a flow chart of the steps needed for the optimization and implementation of FGM. FGM is an important module of biodiversity monitoring, and we define an effective FGM scheme as consisting of an assessment of a forest population's capacity to survive, reproduce, and persist under rapid environmental changes on a long-term scale.

Forest health and global change.

PubMed

Trumbore, S; Brando, P; Hartmann, H

2015-08-21

Humans rely on healthy forests to supply energy, building materials, and food and to provide services such as storing carbon, hosting biodiversity, and regulating climate. Defining forest health integrates utilitarian and ecosystem measures of forest condition and function, implemented across a range of spatial scales. Although native forests are adapted to some level of disturbance, all forests now face novel stresses in the form of climate change, air pollution, and invasive pests. Detecting how intensification of these stresses will affect the trajectory of forests is a major scientific challenge that requires developing systems to assess the health of global forests. It is particularly critical to identify thresholds for rapid forest decline, because it can take many decades for forests to restore the services that they provide. Copyright © 2015, American Association for the Advancement of Science.

Monitoring 2009 Forest Disturbance Across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

NASA Technical Reports Server (NTRS)

Spruce, J.; Hargrove, W. W.; Gasser, G.; Smoot, J. C.; Kuper, P.

2009-01-01

This case study shows the promise of computing current season forest disturbance detection products at regional to CONUS scales. Use of the eMODIS expedited product enabled a NRT CONUS forest disturbance detection product, a requirement for an eventual, operational forest threat EWS. The 2009 classification product from this study can be used to quantify the areal extent of forest disturbance across CONUS, although a quantitative accuracy assessment still needs to be completed. However, the results would not include disturbances that occurred after July 27, such as the Station Fire. While not shown here, the project also produced maximum NDVI products for the June 10-July 27 period of each year of the 2000-2009 time frame. These products could be applied to compute forest change products on an annual basis. GIS could then be used to assess disturbance persistence. Such follow-on work could lead to attribution of year in which a disturbance occurred. These products (e.g., Figures 6 and 7) may also be useful for assessing forest change associated with climate change, such as carbon losses from bark beetle-induced forest mortality in the Western United States. Other MODIS phenological products are being assessed for aiding forest monitoring needs of the EWS, including cumulative NDVI products (Figure 10).

Uncertainties in detecting decadal change in extractable soil elements in Northern Forests

NASA Astrophysics Data System (ADS)

Bartlett, O.; Bailey, S. W.; Ducey, M. J.

2016-12-01

Northern Forest ecosystems have been or are being impacted by land use change, forest harvesting, acid deposition, atmospheric CO2 enrichment, and climate change. Each of these has the potential to modify soil forming processes, and the resulting chemical stocks. Horizontal and vertical variations in concentrations complicate determination of temporal change. This study evaluates sample design, sample size, and differences among observers as sources of uncertainty when quantifying soil temporal change over regional scales. Forty permanent, northern hardwood, monitoring plots were established on the White Mountain National Forest in central New Hampshire and western Maine. Soil pits were characterized and sampled by genetic horizon at plot center in 2001 and resampled again in 2014 two-meters on contour from the original sampling location. Each soil horizon was characterized by depth, color, texture, structure, consistency, boundaries, coarse fragments, and roots from the forest floor to the upper C horizon, the relatively unaltered glacial till parent material. Laboratory analyses included pH in 0.01 M CaCl2 solution and extractable Ca, Mg, Na, K, Al, Mn, and P in 1 M NH4OAc solution buffered at pH 4.8. Significant elemental differences were identified by genetic horizon from paired t-tests (p ≤ 0.05) indicate temporal change across the study region. Power analysis, 0.9 power (α = 0.05), revealed sampling size was appropriate within this region to detect concentration change by genetic horizon using a stratified sample design based on topographic metrics. There were no significant differences between observers' descriptions of physical properties. As physical properties would not be expected to change over a decade, this suggests spatial variation in physical properties between the pairs of sampling pits did not detract from our ability to detect temporal change. These results suggest that resampling efforts within a site, repeated across a region, to quantify elemental change by carefully described genetic horizons is an appropriate method of detecting soil temporal change in this region. Sample size and design considerations from this project will have direct implications for future monitoring programs to characterize change in soil chemistry.

Long-term fragmentation effects on the distribution and dynamics of canopy gaps in a tropical montane forest

Treesearch

Nicholas R. Vaughn; Gregory P. Asner; Christian P. Giardina

2015-01-01

Fragmentation alters forest canopy structure through various mechanisms, which in turn drive subsequent changes to biogeochemical processes and biological diversity. Using repeated airborne LiDAR (Light Detection and Ranging) mappings, we investigated the size distribution and dynamics of forest canopy gaps across a topical montane forest landscape in Hawaii naturally...

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

NASA Technical Reports Server (NTRS)

Freeman, A.; Kramer, C.; Alves, M.; Chapman, B.

1994-01-01

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

NASA Astrophysics Data System (ADS)

Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

2013-05-01

In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2017-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2016-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Evaluation of methodology for detecting/predicting migration of forest species

Treesearch

Dale S. Solomon; William B. Leak

1996-01-01

Available methods for analyzing migration of forest species are evaluated, including simulation models, remeasured plots, resurveys, pollen/vegetation analysis, and age/distance trends. Simulation models have provided some of the most drastic estimates of species changes due to predicted changes in global climate. However, these models require additional testing...

Utilization of ALOS PALSAR-2 Data for Mangrove Detection Using OBIA Method Approach

NASA Astrophysics Data System (ADS)

Anggraini, N.; Julzarika, A.

2017-12-01

Mangroves have an important role for climate change mitigation. This is because mangroves have high carbon stock potential. The ability of mangroves to absorb carbon is very high and it is estimated that the mangrove carbon stock reaches 1023 Mg C. The current problem is the area of mangrove forest is decreasing due to land conversion. One technology that can be used to detect changes in the area of mangrove forest is by utilizing ALOS PALSAR-2 satellite imagery. The purpose of this research is to detect mangrove forest area from ALOS PALSAR-2 data by using object-based image analysis (OBIA) method. The location of the study is Taman Nasional Sembilang in Banyuasin Regency of South Sumatra. The data used are ALOS PALSAR-2 dualpolarization (HH and HV), recording year 2015. The calculation of mangrove forest area in Sembilang National Park has ∼ 82% accuracy. The results of this study can be used for various applications and mapping activities.

Vulnerability of island tropical montane cloud forests to climate change, with special reference to East Maui, Hawaii

USGS Publications Warehouse

Loope, Lloyd L.; Giambelluca, Thomas W.

1998-01-01

Island tropical montane cloud forests may be among the most sensitive of the world's ecosystems to global climate change. Measurements in and above a montane cloud forest on East Maui, Hawaii, document steep microclimatic gradients. Relatively small climate-driven shifts in patterns of atmospheric circulation are likely to trigger major local changes in rainfall, cloud cover, and humidity. Increased interannual variability in precipitation and hurricane incidence would provide additional stresses on island biota that are highly vulnerable to disturbance-related invasion of non-native species. Because of the exceptional sensitivity of these microclimates and forests to change, they may provide valuable ‘listening posts’ for detecting the onset of human-induced global climate change.

Current and emerging operational uses of remote sensing in Swedish forestry

Treesearch

Hakan Olsson; Mikael Egberth; Jonas Engberg; Johan E.S. Fransson; Tina Granqvist Pahlen; < i> et al< /i>

2007-01-01

Satellite remote sensing is being used operationally by Swedish authorities in applications involving, for example, change detection of clear felled areas, use of k-Nearest Neighbour estimates of forest parameters, and post-stratification (in combination with National Forest Inventory plots). For forest management planning of estates, aerial...

Dynamics of change in Alaska's boreal forests: resilience and vulnerability in response to climate warming

Treesearch

A. David McGuire; F.S. Chapin; R.W. Ruess

2010-01-01

Long-term research by the Bonanza Creek (BNZ) Long Term Ecological Research (LTER) program has documented natural patterns of interannual and successional variability of the boreal forest in interior Alaska against which we can detect changes in system behavior. Between 2004 and 2010 the BNZ LTER program focused on understanding the dynamics of change through studying...

Temporal change in forest fragmentation at multiple scales

Treesearch

J.D. Wickham; K.H. Riitters; T.G. Wade; J.W. Coulston

2007-01-01

Previous studies of temporal changes in fragmentation have focused almost exclusively on patch and edge statistics, which might not detect changes in the spatial scale at which forest occurs in or dominates the landscape. We used temporal land-cover data for the Chesapeake Bay region and the state of New Jersey to compare patch-based and area–density scaling measures...

Vegetation change detection and quantification: linking Landsat imagery and LIDAR data

USGS Publications Warehouse

Peterson, Birgit E.; Nelson, Kurtis J.

2009-01-01

Measurements of the horizontal and vertical structure of vegetation are helpful for detecting and monitoring change or disturbance on the landscape. Lidar has a unique ability to capture the three-dimensional structure of vegetation canopies. In this preliminary study, we present the results of a series of exploratory data analyses that tested our assumptions about the links between the structural data obtainable from lidar and the change detection products derived from Landsat imagery. Our study area is located in the Sierra National Forest in the Sierra Nevada Mountains of California and covers a wide range of vegetation types. The lidar data used in this study were collected by the Laser Vegetation Imaging System (LVIS) (Blair et al., 1999). LVIS is a largefootprint lidar system optimized to measure canopy structure characteristics. A series of Landsat scenes from 1984 through 2008 was collected for the study area (Path 42, Row 34) and processed to generate maps of disturbance. The preliminary results described here indicate that even simple metrics of height can be useful in assessing changes in structure brought about by disturbance in forest canopies. For example, canopy height values for 2008 were higher on average than those measured for 1999 in undisturbed forest, whereas this trend is not clearly observable for the disturbed forest patches.

Detecting change in advance tree regeneration using forest inventory data: the implications of type II error

Treesearch

James A. Westfall; William H. McWilliams

2012-01-01

Achieving adequate and desirable forest regeneration is necessary for maintaining native tree species and forest composition. Advance tree seedling and sapling regeneration is the basis of the next stand and serves as an indicator of future composition. The Pennsylvania Regeneration Study was implemented statewide to monitor regeneration on a subset of Forest Inventory...

Tracking the health of trees over time on forest health monitoring plots

Treesearch

Jim Steinman

2000-01-01

The Forest Health Monitoring (FHM) Program was initiated in 1990 as a cooperative effort between the USDA Forest Service and the National Association of State Foresters. Program efforts include detecting changes in tree health from a national grid of one-sixth acre permanent sample plots. Tree data have been collected in various states since 1991, and include species,...

Tracking the health of trees over time on Forest Health Monitoring plots

Treesearch

Jim Steinman

2000-01-01

The Forest Health Monitoring (FHM) Program was initiated in 1990 as a cooperative effort between the USDA Forest Service and the National Association of State Foresters. Program efforts include detecting changes in tree health from a national grid of one-sixth acre permanent sample plots. Tree data have been collected in various States since 1991, and include species...

Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection.

Treesearch

Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Olga N. Krankina

2005-01-01

Landsat satellite data has become ubiquitous in regional-scale forest disturbance detection. The Tasseled Cap (TC) transformation for Landsat data has been used in several disturbance-mapping projects because of its ability to highlight relevant vegetation changes. We used an automated composite analysis procedure to test four multi-date variants of the TC...

Detecting forest canopy change due to insect activity using Landsat MSS

NASA Technical Reports Server (NTRS)

Nelson, R. F.

1983-01-01

Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William W.; Gasser, Gerald

2013-01-01

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Varying effects of geomorphic change on floodplain inundation and forest communities

NASA Astrophysics Data System (ADS)

Keim, R.; Johnson, E. L.; Edwards, B. L.; King, S. L.; Hupp, C. R.

2015-12-01

Overbank flooding in floodplains is an important control on vegetation, but effects of changing flooding are difficult to predict because sensitivities of plant communities to multidimensional flooding (frequency, depth, duration, and timing) are not well understood. We used HEC-RAS to model the changing flooding regime in the lower White River floodplain, Arkansas, in response to rapid incision of the Mississippi River in the 1930s, and quantified flood frequency, depth, and duration by forest community type. Incision has decreased flooding especially in terms of frequency, which is one of the most important variables for ecological processes. Modeled depth-duration curves varied more among floodplain reaches than among forest communities within the same reach, but forest communities are now arranged in accordance with new flood regimes in place after river incision. Forest responses to subtle geomorphic change are slower than other vegetation communities, so detection of the full ramifications of ecohydrologic change may require decades.

Forest fuel treatment detection using multi-temporal airborne Lidar data and high resolution aerial imagery ---- A case study at Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Su, Y.; Guo, Q.; Collins, B.; Fry, D.; Kelly, M.

2014-12-01

Forest fuel treatments (FFT) are often employed in Sierra Nevada forest (located in California, US) to enhance forest health, regulate stand density, and reduce wildfire risk. However, there have been concerns that FFTs may have negative impacts on certain protected wildlife species. Due to the constraints and protection of resources (e.g., perennial streams, cultural resources, wildlife habitat, etc.), the actual FFT extents are usually different from planned extents. Identifying the actual extent of treated areas is of primary importance to understand the environmental influence of FFTs. Light detection and ranging (Lidar) is a powerful remote sensing technique that can provide accurate forest structure measurements, which provides great potential to monitor forest changes. This study used canopy height model (CHM) and canopy cover (CC) products derived from multi-temporal airborne Lidar data to detect FFTs by an approach combining a pixel-wise thresholding method and a object-of-interest segmentation method. We also investigated forest change following the implementation of landscape-scale FFT projects through the use of normalized difference vegetation index (NDVI) and standardized principle component analysis (PCA) from multi-temporal high resolution aerial imagery. The same FFT detection routine was applied on the Lidar data and aerial imagery for the purpose of comparing the capability of Lidar data and aerial imagery on FFT detection. Our results demonstrated that the FFT detection using Lidar derived CC products produced both the highest total accuracy and kappa coefficient, and was more robust at identifying areas with light FFTs. The accuracy using Lidar derived CHM products was significantly lower than that of the result using Lidar derived CC, but was still slightly higher than using aerial imagery. FFT detection results using NDVI and standardized PCA using multi-temporal aerial imagery produced almost identical total accuracy and kappa coefficient. Both methods showed relatively limited capacity to detect light FFT areas, and had higher false detection rate (recognized untreated areas as treated areas) compared to the methods using Lidar derived parameters.

Evaluation of Landsat-7 SLC-off image products for forest change detection

USGS Publications Warehouse

Wulder, Michael A.; Ortlepp, Stephanie M.; White, Joanne C.; Maxwell, Susan

2008-01-01

Since July 2003, Landsat-7 ETM+ has been operating without the scan line corrector (SLC), which compensates for the forward motion of the satellite in the imagery acquired. Data collected in SLC-off mode have gaps in a systematic wedge-shaped pattern outside of the central 22 km swath of the imagery; however, the spatial and spectral quality of the remaining portions of the imagery are not diminished. To explore the continued use of Landsat-7 ETM+ SLC-off imagery to characterize change in forested environments, we compare the change detection results generated from a reference image pair (a 1999 Landsat-7 ETM+ image and a 2003 Landsat-5 TM image) with change detection results generated from the same 1999 Landsat-7 ETM+ image coupled with three different 2003 Landsat-7 SLC-off products: unremediated SLC-off (i.e., with gaps); histogram-based gap-filled; and segment-based gap-filled. The results are compared on both a pixel and polygon basis; on a pixel basis, the unremediated SLC-off product missed 35% of the change identified by the reference data, and the histogram- and segment-based gap-filled products missed 23% and 21% of the change, respectively. When using forest inventory polygons as a context for change (to reduce commission error), the amount of change missed was 31%, 14%, and 12% for the each of the unremediated, histogram-based gap-filled, and segment-based gap-filled products, respectively. Our results indicate that over the time period considered, and given the types and spatial distribution of change events within our study area, the gap-filled products can provide a useful data source for change detection in forested environments. The selection of which product to use is, however, very dependent on the nature of the application and the spatial configuration of change events. ?? 2008 Government of Canada.

Satellite inventory of Minnesota forest resources

NASA Technical Reports Server (NTRS)

Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.

1993-01-01

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

Satellite data based method for general survey of forest insect disturbance in British Columbia

NASA Astrophysics Data System (ADS)

Ranson, J.; Montesano, P.

2008-12-01

Regional forest disturbances caused by insects are important to monitor and quantify because of their influence on local ecosystems and the global carbon cycle. Local damage to forest trees disrupts food supplies and shelter for a variety of organisms. Changes in the global carbon budget, its sources and its sinks affect the way the earth functions as a whole, and has an impact on global climate. Furthermore, the ability to detect nascent outbreaks and monitor the spread of regional infestations helps managers mitigate the damage done by catastrophic insect outbreaks. While detection is needed at a fine scale to support local mitigation efforts, detection at a broad regional scale is important for carbon flux modeling on the landscape scale, and needed to direct the local efforts. This paper presents a method for routinely detecting insect damage to coniferous forests using MODIS vegetation indices, thermal anomalies and land cover. The technique is validated using insect outbreak maps and accounts for fire disturbance effects. The range of damage detected may be used to interpret and quantify possible forest damage by insects.

Forests and Phenology: Designing the Early Warning System to Understand Forest Change

NASA Astrophysics Data System (ADS)

Pierce, T.; Phillips, M. B.; Hargrove, W. W.; Dobson, G.; Hicks, J.; Hutchins, M.; Lichtenstein, K.

2010-12-01

Vegetative phenology is the study of plant development and changes with the seasons, such as the greening-up and browning-down of forests, and how these events are influenced by variations in climate. A National Phenology Data Set, based on Moderate Resolution Imaging Spectroradiometer satellite images covering 2002 through 2009, is now available from work by NASA, the US Forest Service, and Oak Ridge National Laboratory. This new data set provides an easily interpretable product useful for detecting changes to the landscape due to long-term factors such as climate change, as well as finding areas affected by short-term forest threats such as insects or disease. The Early Warning System (EWS) is a toolset being developed by the US Forest Service and the University of North Carolina-Asheville to support distribution and use of the National Phenology Data Set. The Early Warning System will help research scientists, US Forest Service personnel, forest and natural resources managers, decision makers, and the public in the use of phenology data to better understand unexpected change within our nation’s forests. These changes could have multiple natural sources such as insects, disease, or storm damage, or may be due to human-induced events, like thinning, harvest, forest conversion to agriculture, or residential and commercial use. The primary goal of the Early Warning System is to provide a seamless integration between monitoring, detection, early warning and prediction of these forest disturbances as observed through phenological data. The system consists of PC and web-based components that are structured to support four user stages of increasing knowledge and data sophistication. Building Literacy: This stage of the Early Warning System educates potential users about the system, why the system should be used, and the fundamentals about the data the system uses. The channels for this education include a website, interactive tutorials, pamphlets, and other technology transfer methodologies. Achieving Context and Meaning: To provide deeper meaning and knowledge about the Early Warning System to users, this stage of the Early Warning System provides more information about specific examples of disturbances seen in the phenological data, as well the spatial and temporal context to these disturbances. The main components of this stage are specific case studies of forest disturbances. Accessing Data: This component of the Early Warning System includes products for research scientists, the aerial detection survey sketch mapper community, and others who will access and analyze the Early Warning System and phenological data. Products and data will be available through online GIS mashups and WMS and KML downloads. Utilizing Services: The final stage of the Early Warning System supports the analysis of phenological data and serves the results to those end users, including forest managers, the forest industry, and the public, who need to locate past, present, and potential forest disturbances. The main components of this stage include data-driven web tools, automated analysis processes, and end user training programs.

Agricultural land change in the Carpathian ecoregion after the breakdown of socialism and expansion of the European Union

NASA Astrophysics Data System (ADS)

Griffiths, Patrick; Müller, Daniel; Kuemmerle, Tobias; Hostert, Patrick

2013-12-01

Widespread changes of agricultural land use occurred in Eastern Europe since the collapse of socialism and the European Union’s eastward expansion, but the rates and patterns of recent land changes remain unclear. Here we assess agricultural land change for the entire Carpathian ecoregion in Eastern Europe at 30 m spatial resolution with Landsat data and for two change periods, between 1985-2000 and 2000-2010. The early period is characterized by post-socialist transition processes, the late period by an increasing influence of EU politics in the region. For mapping and change detection, we use a machine learning approach (random forests) on image composites and variance metrics which were derived from the full decadal archive of Landsat imagery. Our results suggest that cropland abandonment was the most prevalent change process, but we also detected considerable areas of grassland conversion and forest expansion on non-forest land. Cropland abandonment was most extensive during the transition period and predominantly occurred in marginal areas with low suitability for agriculture. Conversely, we observed substantial recultivation of formerly abandoned cropland in high-value agricultural areas since 2000. Hence, market forces increasingly adjust socialist legacies of land expansive production and agricultural land use clusters in favorable areas while marginal lands revert to forest.

Gulf Coast Disaster Management: Forest Damage Detection and Carbon Flux Estimation

NASA Astrophysics Data System (ADS)

Maki, A. E.; Childs, L. M.; Jones, J.; Matthews, C.; Spindel, D.; Batina, M.; Malik, S.; Allain, M.; Brooks, A. O.; Brozen, M.; Chappell, C.; Frey, J. W.

2008-12-01

Along the Gulf Coast and Eastern Seaboard, tropical storms and hurricanes annually cause defoliation and deforestation amongst coastal forests. After a severe storm clears, there is an urgent need to assess impacts on timber resources for targeting state and national resources to assist in recovery. It is important to identify damaged areas following the storm, due to their increased probability of fire risk, as well as the effect upon the carbon budget. Better understanding and management of the immediate and future effects on the carbon cycle in the coastal forest ecosystem is especially important. Current methods of detection involve assessment through ground-based field surveys, aerial surveys, computer modeling of meteorological data, space-borne remote sensing, and Forest Inventory and Analysis field plots. Introducing remotely-sensed data from NASA and NASA-partnered Earth Observation Systems (EOS), this project seeks to improve the current methodology and focuses on a need for methods that are more synoptic than field surveys and more closely linked to the phenomenology of tree loss and damage than passive remote sensing methods. The primary concentration is on the utilization of Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) data products to detect changes in forest canopy height as an indicator of post-hurricane forest disturbances. By analyzing ICESat data over areas affected by Hurricane Katrina, this study shows that ICESsat is a useful method of detecting canopy height change, though further research is needed in mixed forest areas. Other EOS utilized in this study include Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and the NASA verified and validated international Advanced Wide Field Sensor (AWiFS) sensor. This study addresses how NASA could apply ICESat data to contribute to an improved method of detecting hurricane-caused forest damage in coastal areas; thus to pinpoint areas more susceptible to fire damage and subsequent loss of carbon sequestration.

ForWarn: A Cross-Cutting Forest Resource Management and Decision Support System Providing the Capacity to Identify and Track Forest Disturbances Nationally

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Norman, S.; Christie, W.; Hoffman, F. M.

2012-12-01

The Eastern Forest Environmental Threat Assessment Center and Western Wildland Environmental Assessment Center of the USDA Forest Service have collaborated with NASA Stennis Space Center to develop ForWarn, a forest monitoring tool that uses MODIS satellite imagery to produce weekly snapshots of vegetation conditions across the lower 48 United States. Forest and natural resource managers can use ForWarn to rapidly detect, identify, and respond to unexpected changes in the nation's forests caused by insects, diseases, wildfires, severe weather, or other natural or human-caused events. ForWarn detects most types of forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, and landslides. It also detects drought, flood, and temperature effects, and shows early and delayed seasonal vegetation development. Operating continuously since January 2010, results show ForWarn to be a robust and highly capable tool for detecting changes in forest conditions. ForWarn is the first national-scale system of its kind based on remote sensing developed specifically for forest disturbances. It has operated as a prototype since January 2010 and has provided useful information about the location and extent of disturbances detected during the 2011 growing season, including tornadoes, wildfires, and extreme drought. The ForWarn system had an official unveiling and rollout in March 2012, initiated by a joint NASA and USDA press release. The ForWarn home page has had 2,632 unique visitors since rollout in March 2012, with 39% returning visits. ForWarn was used to map tornado scars from the historic April 27, 2011 tornado outbreak, and detected timber damage within more than a dozen tornado tracks across northern Mississippi, Alabama, and Georgia. ForWarn is the result of an ongoing, substantive cooperation among four different government agencies: USDA, NASA, USGS, and DOE. Disturbance maps are available on the web through the ForWarn Change Assessment Viewer at http://forwarn.forestthreats.org/fcav. No user id or password is required, and there is no cost. The Assessment Viewer operates within any popular web browser using nearly any type of computer. It lets users pan, zoom, and scroll around within ForWarn maps, and also contains an up-to-date library of co-registered, near real-time ancillary maps from diverse sources that allows users to assess the nature of particular forest disturbances and ascribe their most-likely causes. Users can check the current week's U.S. Drought Monitor, USGS VegDRI maps, FHM Historical Aerial Disturbance Surveys, MODIS Cumulative Current Year Fire Detections, and many others. A "Share this map" feature lets users save the current map view and extent into a web URL, so that users can easily share what they are looking at inside the Assessment Viewer with others via an email, a document, or a web page. The ForWarn Rapid National Assessment Team examined more than 60 ForWarn forest disturbance events in 2011-2012, and issued over 30 alerts. We hope to automate forest disturbance alerts and supply them through various subscription services. Forest owners and managers would only be alerted to disturbances occurring near their own forest resources.

Inventory of forest and rangeland and detection of forest stress. [Colorado and California

NASA Technical Reports Server (NTRS)

Heller, R. C.; Aldrich, R. C.; Weber, F. P.; Driscoll, R. S. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Disturbances in a forest environment that cause reductions in forest area, timber volume, and timber growth can be detected on ERTS-1 combined color composites. However, detection depends on comparing a conventional aerial photograph taken at some base year with an ERTS-1 image taken in some subsequent year. In a test made on the Atlanta site, 1:63,360 scale aerial photo index sheets made in 1966 were compared with ERTS-1 image 1264-15445 (April 1973). Five factors were found important to detection reliability: (1) the quality of the imagery; (2) the season of the imagery; (3) the size of the disturbed area; (4) the number of years since the disturbances; and (5) the type of cutting treatment. Of 209 disturbances verified on aerial photography, 165 (or approximately 80%) were detected on the ERTS-1 image by one independent interpreter. Improved training and additional experience in using this low resolution imagery should improve detection. Of the two seasons of data studies (fall and early spring), early spring is the best for detecting land use changes. Generally speaking, winter, early spring, and early summer are the best times of year for detecting forest disturbances.

Forest cover of North America in the 1970s mapped using Landsat MSS data

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

Development of a Unique Web2.0 Interface for Global Collaboration in Land Cover Change Research

NASA Astrophysics Data System (ADS)

Dunham, M.; Boriah, S.; Mithal, V.; Garg, A.; Steinbach, M.; Kumar, V.; Potter, C. S.; Klooster, S.; Castilla-Rubio, J.

2010-12-01

The ability to detect changes in forest cover is of critical importance for both economic and scientific reasons, e.g. using forests for economic carbon sink management and studying natural and anthropogenic impacts on ecosystems. The contribution of greenhouse gases from deforestation is one of the most uncertain elements of the global carbon cycle. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, a key ingredient for effective forest management, whether for carbon trading or other purposes, is quantifiable knowledge about changes in forest cover. Rich amounts of data from remotely-sensed images are now becoming available for detecting changes in forests or more generally, land cover. However, in spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data acquisition, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that can be used for decision making and policy planning purposes. We have developed innovations in a number of technical areas with the goal of providing actionable knowledge to end users: (i) identification of changes in global forest cover, (ii) characterization of those changes, (iii) discovery of relationships between the number, magnitude, and type of these changes with natural and anthropogenic variables, and (iv) a web-based platform that supports interactive visualization of disturbances and relationships. The focus of this abstract is on the interactive web-based platform. This key component of the project is a graphical user interface built on the Flash framework. The viewer is a groundbreaking, multi-purpose application used for everything from algorithm refinement and data analysis for the team to a demonstration platform for research partners. The team continues to develop the utility to allow for worldwide researcher and community contributions with the hopes of enhancing global understanding of environmental change.

Changes in Soil Carbon Storage in Industrial Forests of Western Oregon and Washington Following Modern Timber Harvesting Practices

NASA Astrophysics Data System (ADS)

Holub, S. M.; Hatten, J. A.

2016-12-01

Carbon in forest soils is often overlooked because it is less conspicuous than the live trees, downed wood, and forest floor layer that are easily visible when walking through a forest. However, the amount of carbon in forest soils to one meter depth is generally one to two times the amount of carbon we see above ground in mature forests, making soils an important carbon storage pool in forest ecosystems. Given the large quantity of carbon stored in soil, there is some concern that disturbances to forest ecosystems could push some soils out of steady state and lead to a release of carbon from the soil, potentially contributing to the already large amount of greenhouse gas emissions from the burning of fossil fuels for energy. This has implications for the carbon neutrality of timberlands. Thus, careful investigation of the carbon cycle in forest soils is a key component in deciphering the gains and losses of carbon from forests, and ultimately understanding the effects of forest soils on the global carbon cycle. The study objective was to measure pre-harvest soil carbon stores to 1 m depth with enough precision to detect a small change upon resampling post-harvest. The 9 sites examined ranged from 100 to 400 Mg C / ha before harvest with minimum detectible differences around 5%. Three and a half years post-harvest the average of all 9 sites showed a very modest increase in mineral soil carbon as a result of modern timber harvest. Mineral soil carbon did not change significantly at 6 of the 9 sites, individually (range -2% to +5%), while two sites gained soil carbon (+6% and +11%) and soil carbon decreased at one site (-6%).

Development of Early Warning System Using ALOS-2/PALSAR-2 Data to Detect and Prevent Deforestation

NASA Astrophysics Data System (ADS)

Hayashi, M.; Nagatani, I.; Watanabe, T.; Tadono, T.; Miyoshi, H.; Watanabe, M.; Koyama, C.; Shimada, M.; Ogawa, T.; Ishii, K.; Higashiuwatoko, T.; Miura, M.; Okonogi, H.; Adachi, K.; Morita, T.

2017-12-01

Satellite observation is an efficient method for monitoring deforestation, and a synthetic aperture radar (SAR) is useful especially in cloudy tropical forest regions. In this context, JICA and JAXA cooperate to operate the deforestation monitoring system acquired data by the Phased Array type L-band SAR-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), which is named as "JICA-JAXA Forest Early Warning System in the Tropics" (JJ-FAST), and it have been released on November 2016. JJ-FAST detects deforestation areas, and provides their positional information for 77 countries, which is covering almost all tropical forests. It uses PALSAR-2 ScanSAR observation mode (wide-observation swath width) image, which is 50 m spatial resolution acquired at 1.5 months interval. The dark change areas compared with in two acquisitions by PALSAR-2 HV-polarization images are identified as deforestations in the system. We conducted field surveys to validate detection accuracy of the JJ-FAST in Peru (November and December, 2016), Botswana (April, 2017), and Gabon (July, 2017). As the results, 15 of 18 detected areas were correct deforestation areas, therefore user's accuracy could be confirmed as 83.3 % from limited number of the validation data. Erroneous detection areas were caused by seasonal change in agricultural land and open burning in grass land. For improvement of the accuracy, such areas must be excluded from the analysis by additional algorithms e.g. estimation of accurate masking for non-forested areas. Therefore, we are revising the forest map used for pre-processing step in the system. The JJ-FAST can be expected to contribute to monitor and reduce illegal deforestation activities in tropical forests.

Design and analysis for detection monitoring of forest health

Treesearch

F. A. Roesch

1995-01-01

An analysis procedure is proposed for the sample design of the Forest Health Monitoring Program (FHM) in the United States. The procedure is intended to provide increased sensitivity to localized but potentially important changes in forest health by explicitly accounting for the spatial relationships between plots in the FHM design. After a series of median sweeps...

Forest Inventory and Analysis Database of the United States of America (FIA)

Treesearch

Andrew N. Gray; Thomas J. Brandeis; John D. Shaw; William H. McWilliams; Patrick Miles

2012-01-01

Extensive vegetation inventories established with a probabilistic design are an indispensable tool in describing distributions of species and community types and detecting changes in composition in response to climate or other drivers. The Forest Inventory and Analysis Program measures vegetation in permanent plots on forested lands across the United States of America...

Evaluation of landsat imagery for detecting ice storm damage in upland forests of Eastern Kentucky

Treesearch

Henry W. McNab; Tracy Roof; Jeffrey F. Lewis; David L. Loftis

2007-01-01

Two categories of forest canopy damage (none to light vs. moderate to heavy) resulting from a 2003 ice storm in eastern Kentucky could be identified on readily available Landsat Thematic Mapper imagery using change detection techniques to evaluate the ratio of spectral bands 4 and 5. Regression analysis was used to evaluate several model formulations based on the...

Spatiotemporal Change Detection in Forest Cover Dynamics Along Landslide Susceptible Region of Karakoram Highway, Pakistan

NASA Astrophysics Data System (ADS)

Rashid, Barira; Iqbal, Javed

2018-04-01

Forest Cover dynamics and its understanding is essential for a country's social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it's a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.

Investigation of the effects of construction and stage filling of reservoirs on the environment and ecology: Preproject baseline. [Missouri

NASA Technical Reports Server (NTRS)

Riggins, R. E. (Principal Investigator); Anderson, J. R.

1977-01-01

The author has identified the following significant results: (1) LANDSAT imagery can be used effectively as a baseline for detection of environmental change, resulting from construction of a major inland reservoir. (2) Forest cover can be observed adequately on two-band composite enlargements at a scale of 1:130,000. (3) Forest cover delineated on LANDSAT enlargements compares accurately with ground truth at a scale of 1:250,000. (4) A dual image mapping technique superimposing winter, summer, and spring scenes using the zoom transfer scope facilitates the determination. (5) The same technique can be used to detect changes in the project area, resulting from construction activities. (6) High altitude aircraft imagery can also be used to interpret changes in land use and forest type. (7) Construction operations can be more clearly detailed on the air photos than on LANDSAT imagery.

Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland.

PubMed

Lara, Mark J; Genet, Hélène; McGuire, Anthony D; Euskirchen, Eugénie S; Zhang, Yujin; Brown, Dana R N; Jorgenson, Mark T; Romanovsky, Vladimir; Breen, Amy; Bolton, William R

2016-02-01

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type. © 2015 John Wiley & Sons Ltd.

Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland

USGS Publications Warehouse

Lara, M.; Genet, Helene; McGuire, A. David; Euskirchen, Eugénie S.; Zhang, Yujin; Brown, Dana R. N.; Jorgenson, M.T.; Romanovsky, V.; Breen, Amy L.; Bolton, W.R.

2016-01-01

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.

ALOS PALSAR Applications in the Tropics and Subtropics: Characterisation, Mapping and Detecting Change in Forests and Coastal Wetlands

NASA Astrophysics Data System (ADS)

Lucas, Richard; Carreiras, Joao; Proisy, Christophe; Buniting, Peter

2008-11-01

Research undertaken as part of the Japanese Space Exploration Agency (JAXA) Principal Investigator (PI) and Kyoto and Carbon (K&C) programs has focused on the regional characterization (growth stage as a function of biomass and structure) and mapping of forests across northern Australia and mangroves (including wetlands) in selected tropical regions (northern Australia, Belize, French Guiana and Brazil) using Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) data, either singularly or in conjunction with other remote sensing (e.g., optical) data. Comparison against existing baseline datasets has allowed these data to be used for detecting change in these tropical and subtropical regions. Regional products (e.g., forest growth stage, mangrove/wetland extent and change) generated from the K&C dual polarimetric strip data are anticipated to benefit conservation of these ecosystems and allow better assessments of carbon stocks and changes in these as a function of natural and anthropogenic drivers, thereby supporting key international conventions.

No evidence for consistent long-term growth stimulation of 13 tropical tree species: results from tree-ring analysis.

PubMed

Groenendijk, Peter; van der Sleen, Peter; Vlam, Mart; Bunyavejchewin, Sarayudh; Bongers, Frans; Zuidema, Pieter A

2015-10-01

The important role of tropical forests in the global carbon cycle makes it imperative to assess changes in their carbon dynamics for accurate projections of future climate-vegetation feedbacks. Forest monitoring studies conducted over the past decades have found evidence for both increasing and decreasing growth rates of tropical forest trees. The limited duration of these studies restrained analyses to decadal scales, and it is still unclear whether growth changes occurred over longer time scales, as would be expected if CO2 -fertilization stimulated tree growth. Furthermore, studies have so far dealt with changes in biomass gain at forest-stand level, but insights into species-specific growth changes - that ultimately determine community-level responses - are lacking. Here, we analyse species-specific growth changes on a centennial scale, using growth data from tree-ring analysis for 13 tree species (~1300 trees), from three sites distributed across the tropics. We used an established (regional curve standardization) and a new (size-class isolation) growth-trend detection method and explicitly assessed the influence of biases on the trend detection. In addition, we assessed whether aggregated trends were present within and across study sites. We found evidence for decreasing growth rates over time for 8-10 species, whereas increases were noted for two species and one showed no trend. Additionally, we found evidence for weak aggregated growth decreases at the site in Thailand and when analysing all sites simultaneously. The observed growth reductions suggest deteriorating growth conditions, perhaps due to warming. However, other causes cannot be excluded, such as recovery from large-scale disturbances or changing forest dynamics. Our findings contrast growth patterns that would be expected if elevated CO2 would stimulate tree growth. These results suggest that commonly assumed growth increases of tropical forests may not occur, which could lead to erroneous predictions of carbon dynamics of tropical forest under climate change. © 2015 John Wiley & Sons Ltd.

Using Land Surface Phenology as the Basis for a National Early Warning System for Forest Disturbances

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Norman, S. P.; Hoffman, F. M.

2011-12-01

The National Early Warning System (EWS) provides an 8-day coast-to-coast snapshot of potentially disturbed forests across the U.S.. A prototype system has produced national maps of potential forest disturbances every eight days since January 2010, identifying locations that may require further investigation. Through phenology, the system shows both early and delayed vegetation development and detects all types of unexpected forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, landslides, drought, flood, and climate change. The USDA Forest Service Eastern Forest Environmental Threat Assessment Center is collaborating with NASA Stennis Space Center and the Western Wildland Environmental Threat Assessment Center to develop the tool. The EWS uses differences in phenological responses between an expectation based on historical data and a current view to strategically identify potential forest disturbances and direct attention to locations where forest behavior seems unusual. Disturbance maps are available via the Forest Change Assessment Viewer (FCAV) (http://ews.forestthreats.org/gis), which allows resource managers and other users to see the most current national disturbance maps as soon as they are available. Phenology-based detections show not only vegetation disturbances in the classical sense, but all departures from normal seasonal vegetation behavior. In 2010, the EWS detected a repeated late-frost event at high elevations in North Carolina, USA, that resulted in delayed seasonal development, contrasting with an early spring development at lower elevations, all within close geographic proximity. Throughout 2011, there was a high degree of correspondence between the National Climatic Data Center's North American Drought Monitor maps and EWS maps of phenological drought disturbance in forests. Urban forests showed earlier and more severe phenological drought disturbance than surrounding non-urban forests. An EWS news page (http://www.geobabbble.org/~hnw/EWSNews) highlights disturbances the system has detected during the 2011 season. Unsupervised statistical multivariate clustering of smoothed phenology data every 8 days over an 11-year period produces a detailed map of national vegetation types, including major disturbances. Examining the constancy of these phenological classifications at a particular location from year to year produces a national map showing the persistence of vegetation, regardless of vegetation type. Using spectral unmixing methods, national maps of evergreen decline can be produced which are a composite of insect, disease, and anthropogenic factors causing chronic decline in these forests, including hemlock wooly adelgid, mountain pine beetle, wildfire, tree harvest, and urbanization. Because phenology shows vegetation responses, all disturbance and recovery events detected by the EWS are viewed through the lens of the vegetation.

A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

USGS Publications Warehouse

Chen, X.; Vierling, Lee; Deering, D.

2005-01-01

Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r 2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence with normalized data. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared to some previous relative radiometric normalization methods, this new method does not require high level programming and statistical skills, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare. While this normalization method allowed detection of a range of land use, land cover, and phenological/biophysical changes in the Siberian boreal forest region studied here, it is necessary to further examine images representing a wide variety of ecoregions to thoroughly evaluate the TIC method against other normalization schemes. ?? 2005 Elsevier Inc. All rights reserved.

Monitoring of Biodiversity Indicators in Boreal Forests: A Need for Improved Focus

Treesearch

Ian D. Thompson

2006-01-01

The general principles of scale and coarse and fine filters have been widely accepted, but management agencies and industry are still grappling with the question of what to monitor to detect changes in forest biodiversity after forest management. Part of this problem can be attributed to the lack of focused questions for monitoring associated with an absence of null...

Post-Fire Changes in Forest Biomass Retrieved by Airborne LiDAR in Amazonia

Treesearch

Luciane Sato; Vitor Gomes; Yosio Shimabukuro; Michael Keller; Egidio Arai; Maiza dos-Santos; Irving Brown; Luiz Aragão

2016-01-01

Fire is one of the main factors directly impacting Amazonian forest biomass and dynamics. Because of Amazonia’s large geographical extent, remote sensing techniques are required for comprehensively assessing forest fire impacts at the landscape level. In this context, Light Detection and Ranging (LiDAR) stands out as a technology capable of retrieving direct...

Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

NASA Astrophysics Data System (ADS)

Kumar, Lalit; Ghosh, Manoj Kumer

2012-01-01

Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

BIRD COMMUNITIES AND HABITAT AS ECOLOGICAL INDICATORS OF FOREST CONDITION IN REGIONAL MONITORING

EPA Science Inventory

Ecological indicators for long-term monitoring programs are needed to detect and assess changing environmental conditions, We developed and tested community-level environmental indicators for monitoring forest bird populations and associated habitat. We surveyed 197 sampling plo...

Mapping and spatiotemporal characterization of degraded forests in the Brazilian Amazon through remote sensing

NASA Astrophysics Data System (ADS)

de Souza, Carlos Moreira, Jr.

Large forested areas have recently been impoverished by degradation caused by selective logging, forest fires and fragmentation in the Amazon region, causing partial change of the original forest structure and composition. As opposed to deforestation that has been monitored with Landsat images since the late 70's, degraded forests have not been monitored in the Amazon region. In this dissertation, remote sensing techniques for identifying and mapping unambiguously degraded forests with Landsat images are proposed. The test area was the region of Sinop, located in the state of Mato Grosso, Brazil. This region was selected because a gradient of degraded forest environments exist and a robust time-series of Landsat images and forest transect data were available. First, statistical analyses were applied to identify the best set of spectral information extracted from Landsat images to detect several types of degraded forest environments. Fraction images derived from Spectral Mixture Analysis (SMA) were the best type of information for that purpose. A new spectral index based on fraction images---Normalized Difference Fraction Index (NDFI)---was proposed to enhance the detection of canopy damaged areas in degraded forests. Second, a contextual classification algorithm was implemented to separate unambiguously forest degradation caused by anthropogenic activities from natural forest disturbances. These techniques were validated using forest transects and high resolution aerial videography images and proved to be highly accurate. Next, these techniques were applied to a time-series data set of Landsat images, encompassing 20 years, to evaluate the relationship between forest degradation and deforestation. The most important finding of the forest change detection analysis was that forest degradation and deforestation are independent events in the study area, making worse the current forest impacts in the Amazon region. Finally, the techniques developed and tested in the Sinop region were successfully applied to forty Landsat images covering other regions of the Brazilian Amazon. Standard fractions and NDFI images were computed for these other regions and both physically and spatially consistent results were obtained. An automated decision tree classification using genetic algorithm was implemented successfully to classify land cover types and sub-classes of degraded forests. The remote sensing techniques proposed in this dissertation are fully automated and have the potential to be used in tropical forest monitoring programs.

Forest cover change and fragmentation using Landsat data in Maçka State Forest Enterprise in Turkey.

PubMed

Cakir, Günay; Sivrikaya, Fatih; Keleş, Sedat

2008-02-01

Monitoring forest cover change and understanding the dynamic of forest cover is increasingly important in sustainable development and management of forest ecosystems. This paper uses remote sensing (RS) techniques to monitor forest cover change in Maçka State Forest Enterprise (MSFE) located in NE of Turkey through 1975 to 2000 and then analyses spatial and temporal changes in forest cover by Geographical Information Systems (GIS) and FRAGSTATStrade mark. Forest cover changes were detected from a time series of satellite images of Landsat MSS in 1975, Landsat TM in 1987, and Landsat ETM+ in 2000 using RS and GIS. The results showed that total forest area, productive forest area and degraded forest area increased while broadleaf forest area and non forest area decreased. Mixed forest and degraded forest increased during the first (1975-1987) period, but decreased during the second (1987-2000) period. During the whole study period, the annual forestation rate was 152 ha year(-1), equivalent to 0.27% year(-1) using the compound-interest-rate formula. The total number of patches increased from 36,204 to 48,092 (33%), and mean size of forest patch (MPS) decreased from 2.8 ha to 2.1 ha during a 25 year period. Number of smaller patches (patches in 0-100 ha size class) increased, indicating more fragmented landscape over time that might create a risk for the maintenance of biodiversity of the area. While total population increased from 1975 to 2000 (3.7%), rural population constantly decreased. The increase of forest areas may well be explained by the fact that demographic movement of rural areas concentrated into Maçka City Center. These figures also indicated that decrease in the rural population might likely lead to the release of human pressure to forest areas, probably resulting in a positive development of forest areas.

Recent forest cover changes (2002-2015) in the Southern Carpathians: A case study of the Iezer Mountains, Romania.

PubMed

Mihai, Bogdan; Săvulescu, Ionuț; Rujoiu-Mare, Marina; Nistor, Constantin

2017-12-01

The paper explores the dynamics of the forest cover change in the Iezer Mountains, part of Southern Carpathians, in the context of the forest ownership recovery and deforestation processes, combined with the effects of biotic and abiotic disturbances. The aim of the study is to map and evaluate the typology and the spatial extension of changes in the montane forest cover between 700 and 2462m a.s.l., sampling all the representative Carpathian ecosystems, from the European beech zone up to the spruce-fir zone and the subalpine-alpine pastures. The methodology uses a change detection analysis of satellite imagery with Landsat ETM+/OLI and Sentinel-2 MSI data. The workflow started with a complete calibration of multispectral data from 2002, before the massive forest restitution to private owners, after the Law 247/2005 empowerment, and 2015, the intensification of deforestation process. For the data classification, a Maximum Likelihood supervised classification algorithm was utilized. The forest change map was developed after combining the classifications in a unitary formula using image difference. The principal outcome of the research identifies the type of forest cover change using a quantitative formula. This information can be integrated in the future decision-making strategies for forest stand management and sustainable development. Copyright © 2017 Elsevier B.V. All rights reserved.

Remotely-sensed detection of effects of extreme droughts on gross primary production.

PubMed

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-06-15

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.

Effects of scale and logging on landscape structure in a forest mosaic.

PubMed

Leimgruber, P; McShea, W J; Schnell, G D

2002-03-01

Landscape structure in a forest mosaic changes with spatial scale (i.e. spatial extent) and thresholds may occur where structure changes markedly. Forest management alters landscape structure and may affect the intensity and location of thresholds. Our purpose was to examine landscape structure at different scales to determine thresholds where landscape structure changes markedly in managed forest mosaics of the Appalachian Mountains in the eastern United States. We also investigated how logging influences landscape structure and whether these management activities change threshold values. Using threshold and autocorrelation analyses, we found that thresholds in landscape indices exist at 400, 500, and 800 m intervals from the outer edge of management units in our study region. For landscape indices that consider all landcover categories, such as dominance and contagion, landscape structure and thresholds did not change after logging occurred. Measurements for these overall landscape indices were strongly influenced by midsuccessional deciduous forest, the most common landcover category in the landscape. When restricting analyses for mean patch size and percent cover to individual forest types, thresholds for early-successional forests changed after logging. However, logging changed the landscape structure at small spatial scale, but did not alter the structure of the entire forest mosaic. Previous forest management may already have increased the heterogeneity of the landscape beyond the point where additional small cuts alter the overall structure of the forest. Because measurements for landscape indices yield very different results at different spatial scales, it is important first to identify thresholds in order to determine the appropriate scales for landscape ecological studies. We found that threshold and autocorrelation analyses were simple but powerful tools for the detection of appropriate scales in the managed forest mosaic under study.

Foreword: The dynamics of change in Alaska’s boreal forests: Resilience and vulnerability in response to climate warming

USGS Publications Warehouse

McGuire, A. David; Chapin, F. Stuart; Ruess, Roger W.

2016-01-01

Long-term research by the Bonanza Creek (BNZ) Long Term Ecological Research (LTER) program has documented natural patterns of interannual and successional variability of the boreal forest in interior Alaska against which we can detect changes in system behavior. Between 2004 and 2010 the BNZ LTER program focused on understanding the dynamics of change through studying the resilience and vulnerability of Alaska's boreal forest in response to climate warming. The overarching question in this endeavor has been “How are boreal ecosystems responding, both gradually and abruptly, to climate warming, and what new landscape patterns are emerging?”

Point count length and detection of forest neotropical migrant birds

USGS Publications Warehouse

Dawson, D.K.; Smith, D.R.; Robbins, C.S.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Comparisons of bird abundances among years or among habitats assume that the rates at which birds are detected and counted are constant within species. We use point count data collected in forests of the Mid-Atlantic states to estimate detection probabilities for Neotropical migrant bird species as a function of count length. For some species, significant differences existed among years or observers in both the probability of detecting the species and in the rate at which individuals are counted. We demonstrate the consequence that variability in species' detection probabilities can have on estimates of population change, and discuss ways for reducing this source of bias in point count studies.

Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

PubMed Central

2011-01-01

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i.e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates. PMID:22115360

Global patterns of kelp forest change over the past half-century.

PubMed

Krumhansl, Kira A; Okamoto, Daniel K; Rassweiler, Andrew; Novak, Mark; Bolton, John J; Cavanaugh, Kyle C; Connell, Sean D; Johnson, Craig R; Konar, Brenda; Ling, Scott D; Micheli, Fiorenza; Norderhaug, Kjell M; Pérez-Matus, Alejandro; Sousa-Pinto, Isabel; Reed, Daniel C; Salomon, Anne K; Shears, Nick T; Wernberg, Thomas; Anderson, Robert J; Barrett, Nevell S; Buschmann, Alejandro H; Carr, Mark H; Caselle, Jennifer E; Derrien-Courtel, Sandrine; Edgar, Graham J; Edwards, Matt; Estes, James A; Goodwin, Claire; Kenner, Michael C; Kushner, David J; Moy, Frithjof E; Nunn, Julia; Steneck, Robert S; Vásquez, Julio; Watson, Jane; Witman, Jon D; Byrnes, Jarrett E K

2016-11-29

Kelp forests (Order Laminariales) form key biogenic habitats in coastal regions of temperate and Arctic seas worldwide, providing ecosystem services valued in the range of billions of dollars annually. Although local evidence suggests that kelp forests are increasingly threatened by a variety of stressors, no comprehensive global analysis of change in kelp abundances currently exists. Here, we build and analyze a global database of kelp time series spanning the past half-century to assess regional and global trends in kelp abundances. We detected a high degree of geographic variation in trends, with regional variability in the direction and magnitude of change far exceeding a small global average decline (instantaneous rate of change = -0.018 y -1 ). Our analysis identified declines in 38% of ecoregions for which there are data (-0.015 to -0.18 y -1 ), increases in 27% of ecoregions (0.015 to 0.11 y -1 ), and no detectable change in 35% of ecoregions. These spatially variable trajectories reflected regional differences in the drivers of change, uncertainty in some regions owing to poor spatial and temporal data coverage, and the dynamic nature of kelp populations. We conclude that although global drivers could be affecting kelp forests at multiple scales, local stressors and regional variation in the effects of these drivers dominate kelp dynamics, in contrast to many other marine and terrestrial foundation species.

Global patterns of kelp forest change over the past half-century

PubMed Central

Krumhansl, Kira A.; Okamoto, Daniel K.; Rassweiler, Andrew; Novak, Mark; Bolton, John J.; Cavanaugh, Kyle C.; Connell, Sean D.; Johnson, Craig R.; Konar, Brenda; Ling, Scott D.; Micheli, Fiorenza; Norderhaug, Kjell M.; Pérez-Matus, Alejandro; Sousa-Pinto, Isabel; Reed, Daniel C.; Salomon, Anne K.; Shears, Nick T.; Wernberg, Thomas; Anderson, Robert J.; Barrett, Nevell S.; Buschmann, Alejandro H.; Carr, Mark H.; Caselle, Jennifer E.; Derrien-Courtel, Sandrine; Edgar, Graham J.; Edwards, Matt; Estes, James A.; Goodwin, Claire; Kenner, Michael C.; Kushner, David J.; Nunn, Julia; Steneck, Robert S.; Vásquez, Julio; Watson, Jane; Witman, Jon D.

2016-01-01

Kelp forests (Order Laminariales) form key biogenic habitats in coastal regions of temperate and Arctic seas worldwide, providing ecosystem services valued in the range of billions of dollars annually. Although local evidence suggests that kelp forests are increasingly threatened by a variety of stressors, no comprehensive global analysis of change in kelp abundances currently exists. Here, we build and analyze a global database of kelp time series spanning the past half-century to assess regional and global trends in kelp abundances. We detected a high degree of geographic variation in trends, with regional variability in the direction and magnitude of change far exceeding a small global average decline (instantaneous rate of change = −0.018 y−1). Our analysis identified declines in 38% of ecoregions for which there are data (−0.015 to −0.18 y−1), increases in 27% of ecoregions (0.015 to 0.11 y−1), and no detectable change in 35% of ecoregions. These spatially variable trajectories reflected regional differences in the drivers of change, uncertainty in some regions owing to poor spatial and temporal data coverage, and the dynamic nature of kelp populations. We conclude that although global drivers could be affecting kelp forests at multiple scales, local stressors and regional variation in the effects of these drivers dominate kelp dynamics, in contrast to many other marine and terrestrial foundation species. PMID:27849580

Inventory of forest and rangeland and detection of forest stress. [Manitou, Colorado, Atlanta, Georgia, and Black Hills test sites

NASA Technical Reports Server (NTRS)

Heller, R. C.; Aldrich, R. C.; Weber, F. P.; Driscoll, R. S. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Eucalyptus tree stands killed by low temperatures in December 1972 were outlined by image enhancement of two separate dates of ERTS-1 images (January 22, 1973-I.D. 1183-18175 and April 22, 1973-I.D. 1273-18183). Three stands larger than 500 meters in size were detected very accurately. In Colorado, range and grassland communities were analyzed by visual interpretation of color composite scene I.D. 1028-17135. It was found that mixtures of plant litter, amount and kind of bare soil, and plant foliage cover made classification of grasslands very difficult. Changes in forest land use were detected on areas as small as 5 acres when ERTS-1 color composite scene 1264-15445 (April 13, 1973) was compared with 1966 ASCS index mosaics (scale 1:60,000). Verification of the changes were made from RB-57 underflight CIR transparencies (scale 1:120,000).

Responses of Tree Growths to Tree Size, Competition, and Topographic Conditions in Sierra Nevada Forests Using Bi-temporal Airborne LiDAR Data

NASA Astrophysics Data System (ADS)

Ma, Q.; Su, Y.; Tao, S.; Guo, Q.

2016-12-01

Trees in the Sierra Nevada (SN) forests are experiencing rapid changes due to human disturbances and climatic changes. An improved monitoring of tree growth and understanding of how tree growth responses to different impact factors, such as tree competition, forest density, topographic and hydrologic conditions, are urgently needed in tree growth modeling. Traditional tree growth modeling mainly relied on field survey, which was highly time-consuming and labor-intensive. Airborne Light detection and ranging System (ALS) is increasingly used in forest survey, due to its high efficiency and accuracy in three-dimensional tree structure delineation and terrain characterization. This study successfully detected individual tree growth in height (ΔH), crown area (ΔA), and crown volume (ΔV) over a five-year period (2007-2012) using bi-temporal ALS data in two conifer forest areas in SN. We further analyzed their responses to original tree size, competition indices, forest structure indices, and topographic environmental parameters at individual tree and forest stand scales. Our results indicated ΔH was strongly sensitive to topographic wetness index; whereas ΔA and ΔV were highly responsive to forest density and original tree sizes. These ALS based findings in ΔH were consistent with field measurements. Our study demonstrated the promising potential of using bi-temporal ALS data in forest growth measurements and analysis. A more comprehensive study over a longer temporal period and a wider range of forest stands would give better insights into tree growth in the SN, and provide useful guides for forest growth monitoring, modeling, and management.

Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space

NASA Astrophysics Data System (ADS)

Jaramillo, Fernando; Cory, Neil; Arheimer, Berit; Laudon, Hjalmar; van der Velde, Ype; Hasper, Thomas B.; Teutschbein, Claudia; Uddling, Johan

2018-01-01

During the last 6 decades, forest biomass has increased in Sweden mainly due to forest management, with a possible increasing effect on evapotranspiration. However, increasing global CO2 concentrations may also trigger physiological water-saving responses in broadleaf tree species, and to a lesser degree in some needleleaf conifer species, inducing an opposite effect. Additionally, changes in other forest attributes may also affect evapotranspiration. In this study, we aimed to detect the dominating effect(s) of forest change on evapotranspiration by studying changes in the ratio of actual evapotranspiration to precipitation, known as the evaporative ratio, during the period 1961-2012. We first used the Budyko framework of water and energy availability at the basin scale to study the hydroclimatic movements in Budyko space of 65 temperate and boreal basins during this period. We found that movements in Budyko space could not be explained by climatic changes in precipitation and potential evapotranspiration in 60 % of these basins, suggesting the existence of other dominant drivers of hydroclimatic change. In both the temperate and boreal basin groups studied, a negative climatic effect on the evaporative ratio was counteracted by a positive residual effect. The positive residual effect occurred along with increasing standing forest biomass in the temperate and boreal basin groups, increasing forest cover in the temperate basin group and no apparent changes in forest species composition in any group. From the three forest attributes, standing forest biomass was the one that could explain most of the variance of the residual effect in both basin groups. These results further suggest that the water-saving response to increasing CO2 in these forests is either negligible or overridden by the opposite effect of the increasing forest biomass. Thus, we conclude that increasing standing forest biomass is the dominant driver of long-term and large-scale evapotranspiration changes in Swedish forests.

Evidence of Incipient Forest Transition in Southern Mexico

PubMed Central

Vaca, Raúl Abel; Golicher, Duncan John; Cayuela, Luis; Hewson, Jenny; Steininger, Marc

2012-01-01

Case studies of land use change have suggested that deforestation across Southern Mexico is accelerating. However, forest transition theory predicts that trajectories of change can be modified by economic factors, leading to spatial and temporal heterogeneity in rates of change that may take the form of the Environmental Kuznets Curve (EKC). This study aimed to assess the evidence regarding potential forest transition in Southern Mexico by classifying regional forest cover change using Landsat imagery from 1990 through to 2006. Patterns of forest cover change were found to be complex and non-linear. When rates of forest loss were averaged over 342 municipalities using mixed-effects modelling the results showed a significant (p<0.001) overall reduction of the mean rate of forest loss from 0.85% per year in the 1990–2000 period to 0.67% in the 2000–2006 period. The overall regional annual rate of deforestation has fallen from 0.33% to 0.28% from the 1990s to 2000s. A high proportion of the spatial variability in forest cover change cannot be explained statistically. However analysis using spline based general additive models detected underlying relationships between forest cover and income or population density of a form consistent with the EKC. The incipient forest transition has not, as yet, resulted in widespread reforestation. Forest recovery remains below 0.20% per year. Reforestation is mostly the result of passive processes associated with reductions in the intensity of land use. Deforestation continues to occur at high rates in some focal areas. A transition could be accelerated if there were a broader recognition among policy makers that the regional rate of forest loss has now begun to fall. The changing trajectory provides an opportunity to actively restore forest cover through stimulating afforestation and stimulating more sustainable land use practices. The results have clear implications for policy aimed at carbon sequestration through reducing deforestation and enhancing forest growth. PMID:22905123

Evidence of incipient forest transition in Southern Mexico.

PubMed

Vaca, Raúl Abel; Golicher, Duncan John; Cayuela, Luis; Hewson, Jenny; Steininger, Marc

2012-01-01

Case studies of land use change have suggested that deforestation across Southern Mexico is accelerating. However, forest transition theory predicts that trajectories of change can be modified by economic factors, leading to spatial and temporal heterogeneity in rates of change that may take the form of the Environmental Kuznets Curve (EKC). This study aimed to assess the evidence regarding potential forest transition in Southern Mexico by classifying regional forest cover change using Landsat imagery from 1990 through to 2006. Patterns of forest cover change were found to be complex and non-linear. When rates of forest loss were averaged over 342 municipalities using mixed-effects modelling the results showed a significant (p<0.001) overall reduction of the mean rate of forest loss from 0.85% per year in the 1990-2000 period to 0.67% in the 2000-2006 period. The overall regional annual rate of deforestation has fallen from 0.33% to 0.28% from the 1990s to 2000s. A high proportion of the spatial variability in forest cover change cannot be explained statistically. However analysis using spline based general additive models detected underlying relationships between forest cover and income or population density of a form consistent with the EKC. The incipient forest transition has not, as yet, resulted in widespread reforestation. Forest recovery remains below 0.20% per year. Reforestation is mostly the result of passive processes associated with reductions in the intensity of land use. Deforestation continues to occur at high rates in some focal areas. A transition could be accelerated if there were a broader recognition among policy makers that the regional rate of forest loss has now begun to fall. The changing trajectory provides an opportunity to actively restore forest cover through stimulating afforestation and stimulating more sustainable land use practices. The results have clear implications for policy aimed at carbon sequestration through reducing deforestation and enhancing forest growth.

Threshold Responses of Forest Birds to Landscape Changes around Exurban Development

PubMed Central

Suarez-Rubio, Marcela; Wilson, Scott; Leimgruber, Peter; Lookingbill, Todd

2013-01-01

Low-density residential development (i.e., exurban development) is often embedded within a matrix of protected areas and natural amenities, raising concern about its ecological consequences. Forest-dependent species are particularly susceptible to human settlement even at low housing densities typical of exurban areas. However, few studies have examined the response of forest birds to this increasingly common form of land conversion. The aim of this study was to assess whether, how, and at what scale forest birds respond to changes in habitat due to exurban growth. We evaluated changes in habitat composition (amount) and configuration (arrangement) for forest and forest-edge species around North America Breeding Bird Survey (BBS) stops between 1986 and 2009. We used Threshold Indicator Taxa Analysis to detect change points in species occurrence at two spatial extents (400-m and 1-km radius buffer). Our results show that exurban development reduced forest cover and increased habitat fragmentation around BBS stops. Forest birds responded nonlinearly to most measures of habitat loss and fragmentation at both the local and landscape extents. However, the strength and even direction of the response changed with the extent for several of the metrics. The majority of forest birds’ responses could be predicted by their habitat preferences indicating that management practices in exurban areas might target the maintenance of forested habitats, for example through easements or more focused management for birds within existing or new protected areas. PMID:23826325

RS Application for conducting change detection within the Sundarban Mangrove Forest, Bangladesh to meet REDD+ initiatives

NASA Astrophysics Data System (ADS)

Biswas, T.; Maus, P.; Megown, K.

2011-12-01

The U.S. Forest Service (USFS) provided technical support to the Resource Information Management System (RIMS) unit of the Forest Department (FD) of Bangladesh in developing a method to monitor changes within the Sundarbans Reserve Forest using remote sensing and GIS technology to meet the Reducing Emissions from Deforestation and Degradation (REDD+) initiatives within Bangladesh. It included comparing the simple image differencing method with the Z-score outlier change detection method to examine changes within the mangroves of Bangladesh. Landsat data from three time periods (1989, 1999, 2009) were used to quantify change within four canopy cover classes (High, Medium, Low, and Very Low) within Sundarbans. The Z-score change analysis and image differencing was done for all the 6 reflective bands obtained from Landsat and two spectral indices NDVI and NDMI, derived from these bands for each year. Our results indicated very subtle changes in the mangrove forest within the past twenty years and the Z-score analysis was found to be more useful in capturing these subtle changes than the simple image difference method. Percent change in Z-score of NDVI provided the most meaningful index of vegetation change. It was used to summarize change for the entire study area by pixel, by canopy cover classes and the management compartment during this analysis. Our analysis showed less than 5% overall change in area within the mangroves for the entire study period. Percent change in forest canopy cover reduced from 4% in 1989-99 to 2% by 1999-2009 indicating an increase in forest canopy cover. Percent change in NDVI Z-score of each pixel was used to compute the overall percent change in z-score within the entire study area, mean percent change within each canopy cover class and management compartments from 1989 to 1999 and from 1999 to 2009. The above analysis provided insight to the spatial distribution of percent change in NDVI between the study periods and helped in identifying potential area for management intervention. The mean distribution of change from both study periods was observed within ± 20% SD.Our results were in agreement with the independent field study conducted by the US Forest Service earlier the same year for biomass and carbon stock estimation. The 10m field plots that showed a decline in carbon stock between 1995 and 2010 overall coincided with the compartments or region that showed a decline in forest canopy cover between 1999 and 2009 from the present analysis. These results led us to believe that the Z-score analysis can be a potential quantitatively rigorous tool to quantify change in ecosystems that are mostly stable and do not undergo drastic land use or land cover change. The field and remote sensing study together provided important scientific information and direction for future management of the forest resources, baseline information for long term monitoring of the forest, and identifying potential REDD+ Carbon financing projects in Sundarbans, as well as other potential REDD+ sites within forested area of Bangladesh. Given the rising concern and interest in REDD+ initiative we consider the Z-score analysis to be a potential tool in monitoring and providing a quick spatial assessment of change using remote sensing technology.

Automated Detection and Annotation of Disturbance in Eastern Forests

NASA Astrophysics Data System (ADS)

Hughes, M. J.; Chen, G.; Hayes, D. J.

2013-12-01

Forest disturbances represent an important component of the terrestrial carbon budget. To generate spatially-explicit estimates of disturbance and regrowth, we developed an automated system to detect and characterize forest change in the eastern United States at 30 m resolution from a 28-year Landsat Thematic Mapper time-series (1984-2011). Forest changes are labeled as 'disturbances' or 'regrowth', assigned to a severity class, and attributed to a disturbance type: either fire, insects, harvest, or 'unknown'. The system generates cloud-free summertime composite images for each year from multiple summer scenes and calculates vegetation indices from these composites. Patches of similar terrain on the landscape are identified by segmenting the Normalized Burn Ratio image. The spatial variance within each patch, which has been found to be a good indicator of diffuse disturbances such as forest insect damage, is then calculated for each index, creating an additional set of indexes. To identify vegetation change and quantify its degree, the derivative through time is calculated for each index using total variance regularization to account for noise and create a piecewise-linear trend. These indexes and their derivatives detect areas of disturbance and regrowth and are also used as inputs into a neural network that classifies the disturbance type/agent. Disturbance and disease information from the US Forest Service Aerial Detection Surveys (ADS) geodatabase and disturbed plots from the US Forest Service Forest Inventory and Analysis (FIA) database provided training data for the neural network. Although there have been recent advances in discriminating between disturbance types in boreal forests, due to the larger number of forest species and cosmopolitan nature of overstory communities in eastern forests, separation remains difficult. The ADS database, derived from sketch maps and later digitized, commonly designates a single large area encompassing many smaller effected areas as disturbed, overestimating disturbance and creating ambiguity in the neural network. Even so, total classification error in a neighboring testing region is 22%. Most error comes labeling disturbances that are unknown in the training data as a known disturbance type. Confusion within known disturbance types is low, with 7% misclassification error for southern pine beetle, and 11% misclassification error for fire, which is likely due to over-estimates of disturbance extent in ADS polygons. Additionally, we used the Terrestrial Ecosystem Model (TEM) to quantify the carbon flux associated with a subset of selected disturbances of different severity and type. Early results show that combined disturbances resulted in a net carbon source of 1.27 kg/m2 between 1981 and 2010, which is about 8% of the total carbon storage in forests. This carbon loss offset much of the carbon sink effects resulting from elevated atmospheric CO2 and nitrogen deposition.

African Savanna-Forest Boundary Dynamics: A 20-Year Study

PubMed Central

Cuni-Sanchez, Aida; White, Lee J. T.; Calders, Kim; Jeffery, Kathryn J.; Abernethy, Katharine; Burt, Andrew; Disney, Mathias; Gilpin, Martin; Gomez-Dans, Jose L.; Lewis, Simon L.

2016-01-01

Recent studies show widespread encroachment of forest into savannas with important consequences for the global carbon cycle and land-atmosphere interactions. However, little research has focused on in situ measurements of the successional sequence of savanna to forest in Africa. Using long-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4) in Lopé National Park, central Gabon, plus novel 3D terrestrial laser scanning (TLS) measurements to assess forest structure differences. Over 20 years no plot changed to a new stage in the putative succession, but F1 forests strongly moved towards the structure, AGB and diversity of F2 forests. Overall, savanna plots showed no detectable change in structure, AGB or diversity using this method, with zero trees ≥10 cm diameter in 1993 and 2013. F1 and F2 forests increased in AGB, mainly as a result of adding recruited stems (F1) and increased Basal Area (F2), whereas F3 and F4 forests did not change substantially in structure, AGB or diversity. Critically, the stability of the F3 stage implies that this stage may be maintained for long periods. Soil carbon was low, and did not show a successional gradient as for AGB and diversity. TLS vertical plant profiles showed distinctive differences amongst the vegetation types, indicating that this technique can improve ecological understanding. We highlight two points: (i) as forest colonises, changes in biodiversity are much slower than changes in forest structure or AGB; and (ii) all forest types store substantial quantities of carbon. Multi-decadal monitoring is likely to be required to assess the speed of transition between vegetation types. PMID:27336632

African Savanna-Forest Boundary Dynamics: A 20-Year Study.

PubMed

Cuni-Sanchez, Aida; White, Lee J T; Calders, Kim; Jeffery, Kathryn J; Abernethy, Katharine; Burt, Andrew; Disney, Mathias; Gilpin, Martin; Gomez-Dans, Jose L; Lewis, Simon L

2016-01-01

Recent studies show widespread encroachment of forest into savannas with important consequences for the global carbon cycle and land-atmosphere interactions. However, little research has focused on in situ measurements of the successional sequence of savanna to forest in Africa. Using long-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4) in Lopé National Park, central Gabon, plus novel 3D terrestrial laser scanning (TLS) measurements to assess forest structure differences. Over 20 years no plot changed to a new stage in the putative succession, but F1 forests strongly moved towards the structure, AGB and diversity of F2 forests. Overall, savanna plots showed no detectable change in structure, AGB or diversity using this method, with zero trees ≥10 cm diameter in 1993 and 2013. F1 and F2 forests increased in AGB, mainly as a result of adding recruited stems (F1) and increased Basal Area (F2), whereas F3 and F4 forests did not change substantially in structure, AGB or diversity. Critically, the stability of the F3 stage implies that this stage may be maintained for long periods. Soil carbon was low, and did not show a successional gradient as for AGB and diversity. TLS vertical plant profiles showed distinctive differences amongst the vegetation types, indicating that this technique can improve ecological understanding. We highlight two points: (i) as forest colonises, changes in biodiversity are much slower than changes in forest structure or AGB; and (ii) all forest types store substantial quantities of carbon. Multi-decadal monitoring is likely to be required to assess the speed of transition between vegetation types.

Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

NASA Astrophysics Data System (ADS)

Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

2011-12-01

The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan-sharpened Landsat imagery with 15m resolution and Very High Resolution imagery from different sensors, obtained from the Department of Defense database that was recently opened to NASA and its Earth Observation partners. Particular emphasis is placed on the detection of agricultural fields and their expansion in primary forests or intensification in secondary forests and fallow fields, as this is the primary driver of deforestation in this area. Fields in this area area also of very small size and irregular shapes, often partly obscured by neighboring forest canopy, hence the technical challenge of correctly detecting them and tracking them through time. Finally, the potential for use of this methodology in other regions where information on land cover changes is needed for land use sustainability planning, is also addressed.

Climate change impacts detection in dry forested ecosystem as indicated by vegetation cover change in -Laikipia, of Kenya.

PubMed

M'mboroki, Kiambi Gilbert; Wandiga, Shem; Oriaso, Silas Odongo

2018-03-29

The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.

Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics

USGS Publications Warehouse

Liu, J.; Liu, S.; Loveland, Thomas R.; Tieszen, L.L.

2008-01-01

Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.

Health and vitality assessment of two common pine species in the context of climate change in southern Europe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sicard, Pierre, E-mail: pierre.sicard@acri-st.fr; Dalstein-Richier, Laurence

The Mediterranean Basin is expected to be more strongly affected by ongoing climate change than most other regions of the earth. The South-eastern France can be considered as case study for assessing global change impacts on forests. Based on non-parametric statistical tests, the climatic parameters (temperature, relative humidity, rainfall, global radiation) and forest-response indicators (crown defoliation, discoloration and visible foliar ozone injury) of two pine species (Pinus halepensis and Pinus cembra) were analyzed. In the last 20 years, the trend analyses reveal a clear hotter and drier climate along the coastline and slightly rainier inland. In the current climate changemore » context, a reduction in ground-level ozone (O{sub 3}) was found at remote sites and the visible foliar O{sub 3} injury decreased while deterioration of the crown conditions was observed likely due to a drier and warmer climate. Clearly, if such climatic and ecological changes are now being detected when the climate, in South-eastern France, has warmed in the last 20 years (+0.46–1.08 °C), it can be expected that many more impacts on tree species will occur in response to predicted temperature changes by 2100 (+1.95–4.59 °C). Climate change is projected to reduce the benefits of O{sub 3} precursor emissions controls leading to a higher O{sub 3} uptake. However, the drier and warmer climate should induce a soil drought leading to a lower O{sub 3} uptake. These two effects, acting together in an opposite way, could mitigate the harmful impacts of O{sub 3} on forests. The development of coordinated emission abatement strategies is useful to reduce both climate change and O{sub 3} pollution. Climate change will create additional challenges for forest management with substantial socio-economic and biological diversity impacts. However, the development of future sustainable and adaptive forest management strategies has the potential to reduce the vulnerability of forest species to climate change. - Highlights: • We assess climate change impacts on forests: South-eastern France as case study in the last 20 years. • We detect and estimate trends for O{sub 3} concentrations, climatic parameters and visible injury. • We establish a state-of-the-art of the health of 2 common pine species in a context of climate change. • We use two valuable bio-indicator species for O{sub 3} stress: Pinus halepensis and Pinus cembra. • Deterioration of crown conditions: climate change creates additional challenges for forest.« less

Advanced Satellite Hardware/Software System Study.

DTIC Science & Technology

1980-04-15

forest vs. pine forest vs. mixed hardwood forest or sand vs. soil vs. rock. Such differences can be used as the basis for secondary distinctions such...this category; however, it usually implies a more restrictive defintion .) ChanRe Detection/Monitoring - To discern the occurrence of changes, both rapid...currently available, several manufacturers expect to market units by 1981. Preliminary specifications for one system indicate a capacity of 2.5 GB per

Analysis of U. S. Forest Service bird point-count monitoring database - implications for designing and implementing avian monitoring

Treesearch

Eric T. Linder; David A. Buehler

2005-01-01

In 1996, Region 8 of the U. S. Forest Service implemented a program to monitor landbirds on southeastern U.S. national forests. The goal was to develop a monitoring system that could document population trends and bird-habitat relationships. Using power analysis, we examined the ability of the monitoring program to detect population trends (3 percent annual change) at...

A Spectral Mapping Signature for the Rapid Ohia Death (ROD) Pathogen in Hawaiian Forests

USDA-ARS?s Scientific Manuscript database

Pathogenic invasions are a major disruptive source of change in both agricultural and natural ecosystems. In forests, fungal pathogens can kill habitat-generating plant species such as canopy trees, but methods for remote detection, mapping and monitoring of such outbreaks are poorly developed. Cera...

LEAF AREA INDEX (LAI) CHANGE DETECTION ON LOBLOLLY PINE FOREST STANDS WITH COMPLETE UNDERSTORY REMOVAL

EPA Science Inventory

The confounding effect of understory vegetation contributions to satellite derived
estimates of leaf area index (LAI) was investigated on two loblolly pine (Pinus taeda) forest stands located in the southeastern United States. Previous studies have shown that understory can a...

LEAF AREA INDEX (LAI) CHANGE DETECTION ON LOBLOLLY PINE FOREST STANDS WITH COMPLETE UNDERSTORY REMOVAL

EPA Science Inventory

The confounding effect of understory vegetation contributions to satellite derived estimates of leaf area index (LAI) was investigated on two loblolly pine forest stands located in the southeastern United States. Previous studies have shown that understory can account from 0-40%...

DETECTING FOREST STRESS AND DECLINE IN RESPONSE TO INCREASING RIVER FLOW IN SOUTHWEST FLORIDA, USA

EPA Science Inventory

Forest stress and decline resulting from increased river flows were investigated in Myakka River State Park (MRSP), Florida, USA. Since 1977, land-use changes around the upper Myakka River watershed have resulted in significant increases in water entering the river, which have...

Land cover changes and forest landscape evolution (1985-2009) in a typical Mediterranean agroforestry system (high Agri Valley)

NASA Astrophysics Data System (ADS)

Simoniello, T.; Coluzzi, R.; Imbrenda, V.; Lanfredi, M.

2015-06-01

The present study focuses on the transformations of a typical Mediterranean agroforestry landscape of southern Italy (high Agri Valley - Basilicata region) that occurred over 24 years. In this period, the valuable agricultural and natural areas that compose such a landscape were subjected to intensive industry-related activities linked to the exploitation of the largest European onshore oil reservoir. Landsat imagery acquired in 1985 and 2009 were used to detect changes in forest areas and major land use trajectories. Landscape metrics indicators were adopted to characterize landscape structure and evolution of both the complex ecomosaic (14 land cover classes) and the forest/non-forest arrangement. Our results indicate a net increase of 11% of forest areas between 1985 and 2009. The major changes concern increase of all forest covers at the expense of pastures and grasses, enlargement of riparian vegetation, and expansion of artificial areas. The observed expansion of forests was accompanied by a decrease of the fragmentation levels likely due to the reduction of small glades that break forest homogeneity and to the recolonization of herbaceous areas. Overall, we observe an evolution towards a more stable configuration depicting a satisfactory picture of vegetation health.

Land cover changes and forest landscape evolution (1985-2009) in a typical Mediterranean agroforestry system (High Agri Valley)

NASA Astrophysics Data System (ADS)

Simoniello, T.; Coluzzi, R.; Imbrenda, V.; Lanfredi, M.

2014-08-01

The present study focuses on the transformations of a typical Mediterranean agroforestry landscape of southern Italy (High Agri Valley - Basilicata region) occurred during 24 years. In this period, the valuable agricultural and natural areas that compose such a landscape were subjected to intensive industry-related activities linked to the exploitation of the largest European on-shore oil reservoir. Landsat imagery acquired in 1985 and 2009 were used to detect changes in forest areas and major land use trajectories. Landscape metrics indicators were adopted to characterize landscape structure and evolution of both the complex ecomosaic (14 land cover classes) and the Forest/Non Forest arrangement. Our results indicate a net increase of 11% of forest areas between 1985 and 2009. The major changes concern: increase of all forest covers at the expense of pastures and grasses, enlargement of riparian vegetation, expansion of artificial areas. The observed expansion of forests was accompanied by a decrease of the fragmentation levels likely due to the reduction of small glades that break forest homogeneity and to the recolonization of herbaceous areas. Overall, we observe an evolution towards a more stable configuration depicting a satisfactory picture of vegetation health.

Monitoring Forest and Rangeland Change in the United States Using Landsat Time Series Data

NASA Astrophysics Data System (ADS)

Vogelmann, J.; Tolk, B.; Xian, G. Z.; Homer, C.

2011-12-01

The LANDFIRE project produces spatial data layers for fire management applications. As part of the project, 2000 vintage Landsat Thematic Mapper and Enhanced Thematic Mapper plus data sets were used to generate detailed vegetation type data sets for the entire United States. We are currently using several approaches to update this information, including incorporation of (1) Landsat-derived historic fire burn information, (2) forest harvest information from Landsat time series data using the Vegetation Change Tracker, and (3) data sets that capture subtle and gradual intra-state disturbances, such as those related to insects and disease as well as succession. The primary focus of this presentation will be on of the detection and characterization of gradual change occurring in forest and rangeland ecosystems, and how to incorporate this information in the LANDFIRE updating process. Landsat data acquired over the previous 25+ years are being used to assess status and trends of forest and rangeland condition. Current study areas are located in the southwestern US, western Nebraska, western Wyoming, western South Dakota, northeastern US and the central Appalachian Mountains. Trends of changing vegetation index values derived from Landsat time series data stacks are the foundation for the gradual change information being developed. Thus far we have found evidence of gradual systematic change in all areas that we have examined. Many of the conifer forests in the southwestern US are showing declining conditions related to insects and drought, and very few of the examined areas are showing evidence of increased canopy cover or greenness. While sagebrush communities are showing decreases in greenness related to fire, mining, and drought, few of these communities are showing evidence of increased greenness or "improving" conditions. However, there is evidence that some forest communities are expanding and that canopy cover density is increasing at some locations. In Nebraska, increases in canopy cover appear to be mostly related to expansion of eastern red cedar. In the White Mountains of New Hampshire, observed increases in forest canopy appear to be related to understory balsam fir expansion, most likely related to release of forest suppression resulting from the thinning of the upper forest canopy. Continued analyses of time series data using multi-spatial scenes and covering multiple years are required in order to develop accurate impressions and representations of the changing ecosystem patterns and trends that are occurring. The approach demonstrates that Landsat time series data can be used operationally for assessing gradual ecosystem change across large areas. This information complements the information derived from other time-series change detection used for LANDFIRE.

Implications of land use change on the national terrestrial carbon budget of Georgia.

PubMed

Olofsson, Pontus; Torchinava, Paata; Woodcock, Curtis E; Baccini, Alessandro; Houghton, Richard A; Ozdogan, Mutlu; Zhao, Feng; Yang, Xiaoyuan

2010-09-13

Globally, the loss of forests now contributes almost 20% of carbon dioxide emissions to the atmosphere. There is an immediate need to reduce the current rates of forest loss, and the associated release of carbon dioxide, but for many areas of the world these rates are largely unknown. The Soviet Union contained a substantial part of the world's forests and the fate of those forests and their effect on carbon dynamics remain unknown for many areas of the former Eastern Bloc. For Georgia, the political and economic transitions following independence in 1991 have been dramatic. In this paper we quantify rates of land use changes and their effect on the terrestrial carbon budget for Georgia. A carbon book-keeping model traces changes in carbon stocks using historical and current rates of land use change. Landsat satellite images acquired circa 1990 and 2000 were analyzed to detect changes in forest cover since 1990. The remote sensing analysis showed that a modest forest loss occurred, with approximately 0.8% of the forest cover having disappeared after 1990. Nevertheless, growth of Georgian forests still contribute a current national sink of about 0.3 Tg of carbon per year, which corresponds to 31% of the country anthropogenic carbon emissions. We assume that the observed forest loss is mainly a result of illegal logging, but we have not found any evidence of large-scale clear-cutting. Instead local harvesting of timber for household use is likely to be the underlying driver of the observed logging. The Georgian forests are a currently a carbon sink and will remain as such until about 2040 if the current rate of deforestation persists. Forest protection efforts, combined with economic growth, are essential for reducing the rate of deforestation and protecting the carbon sink provided by Georgian forests.

Toward a National Early Warning System for Forest Disturbances Using Remotely Sensed Land-Surface Phenology

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.

2010-12-01

A prototype National Early Warning System (EWS) for Forest Disturbances was established in 2010 by producing national maps showing potential forest disturbance across the conterminous United States at 231m resolution every 8 days. Each map is based on Land-Surface Phenology (LSP), calculated using temporally smoothed MODIS MOD13 imagery obtained over the preceding 24-day analysis window. Potential disturbance maps are generated by comparing a spatially and temporally specific historical expectation of normal NDVI "greenness" with NDVI "greenness" from a series of current satellite views. Three different disturbance products are produced using differing lengths of historical baseline periods to calculate the expected normal greenness. The short-term baseline products show only disturbances newer than one year ago, while the intermediate baseline products show disturbances since the prior three years, and the long-term baseline products show all disturbances over the MODIS historical period. A Forest Change Assessment Viewer website, http://ews.forestthreats.org/NPDE/NPDE.html, showcases the three most recent national disturbance maps in full spatial context. Although 2010 was a wet el Nino year without major forest problems, disturbances in 2010 in MI, NY, CO and LA will be highlighted. Forest disturbances caused by wildfire, hurricanes, tornadoes, hail, ice storms, and defoliating insects, including fall cankerworms, forest tent caterpillars, gypsy moths, baldcypress leafrollers and winter moths were successfully detected during the 2009 and 2010 field seasons. The EWS was used in 2010 to detect and alert Forest Health Monitoring (FHM) Aerial Disturbance Survey personnel to an otherwise-unknown outbreak of forest tent caterpillar and baldcypress leafroller in the Atchafalaya and Pearl River regions of southern Louisiana. A local FHM Program Coordinator verified these EWS-detected outbreaks. Many defoliator-induced disturbances were ephemeral, and were followed by recovery in LSP, presumably due to refoliation. 2009 Vegetation Disturbances mapped as percent change in max NDVI from June 10 - July 27 2000-2008

Remotely-sensed detection of effects of extreme droughts on gross primary production

PubMed Central

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-01-01

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space. PMID:27301671

Trends over time in tree and seedling phylogenetic diversity indicate regional differences in forest biodiversity change.

PubMed

Potter, Kevin M; Woodall, Christopher W

2012-03-01

Changing climate conditions may impact the short-term ability of forest tree species to regenerate in many locations. In the longer term, tree species may be unable to persist in some locations while they become established in new places. Over both time frames, forest tree biodiversity may change in unexpected ways. Using repeated inventory measurements five years apart from more than 7000 forested plots in the eastern United States, we tested three hypotheses: phylogenetic diversity is substantially different from species richness as a measure of biodiversity; forest communities have undergone recent changes in phylogenetic diversity that differ by size class, region, and seed dispersal strategy; and these patterns are consistent with expected early effects of climate change. Specifically, the magnitude of diversity change across broad regions should be greater among seedlings than in trees, should be associated with latitude and elevation, and should be greater among species with high dispersal capacity. Our analyses demonstrated that phylogenetic diversity and species richness are decoupled at small and medium scales and are imperfectly associated at large scales. This suggests that it is appropriate to apply indicators of biodiversity change based on phylogenetic diversity, which account for evolutionary relationships among species and may better represent community functional diversity. Our results also detected broadscale patterns of forest biodiversity change that are consistent with expected early effects of climate change. First, the statistically significant increase over time in seedling diversity in the South suggests that conditions there have become more favorable for the reproduction and dispersal of a wider variety of species, whereas the significant decrease in northern seedling diversity indicates that northern conditions have become less favorable. Second, we found weak correlations between seedling diversity change and latitude in both zones, with stronger relationships apparent in some ecoregions. Finally, we detected broadscale seedling diversity increases among species with longer-distance dispersal capacity, even in the northern zone, where overall seedling diversity declined. The statistical power and geographic extent of such analyses will increase as data become available over larger areas and as plot measurements are repeated at regular intervals over a longer period of time.

Resilience of Alaska's Boreal Forest to Climatic Change

NASA Technical Reports Server (NTRS)

Chapin, F. S., III; McGuire, A. D.; Ruess, R. W.; Hollingsworth, T. N.; Mack, M. C.; Johnstone, J. F.; Kasischke, E. S.; Euskirchen, E. S.; Jones, J. B.; Jorgenson, M. T.;

Resilience of Alaska’s boreal forest to climatic change

USGS Publications Warehouse

Chapin, F.S.; McGuire, A. David; Ruess, Roger W.; Hollingsworth, Teresa N.; Mack, M.C.; Johnstone, J.F.; Kasischke, E.S.; Euskirchen, E.S.; Jones, J.B.; Jorgenson, M.T.; Kielland, K.; Kofinas, G.; Turetsky, M.R.; Yarie, J.; Lloyd, A.H.; Taylor, D.L.

2010-01-01

This paper assesses the resilience of Alaska’s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska’s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social–ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Detection of forest decline in Monchegorsk area

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagner, O.; Rigina, O.

1998-01-01

Forests on the Kola Peninsula in Northern Russia are growing close to the limits of the northern tree line. They are subjected to both natural (low temperatures and a short period of biochemical activity) and anthropogenic stress factors. The metallurgic industry complex Severo-nickel close to the city of Monchegorsk in the central Russian Kola Peninsula is one of the major sources of sulfur dioxide (SO{sub 2}), nickel, and copper emissions in the region. The environmental impact on the surrounding area is dramatic. In this study multispectral changes observed in Landsat-MSS satellite image data from 1978, 1986, and 1992 are usedmore » to evaluate the relevance of a mathematical model of SO{sub 2} concentration in ambient air as a component for assessment of forest decline. The multispectral changes detected were found to have a statistically significant correspondence to the modeled (SO{sub 2}) concentration levels in ambient air.« less

Forest cover loss and urban area expansion in the Conterminous Unites States in the first decade of the third millennium

NASA Astrophysics Data System (ADS)

Huo, L. Z.; Boschetti, L.

2016-12-01

Remote sensing has been successfully used for global mapping of changes in forest cover, but further analysis is needed to characterize those changes - and in particular to classify the total loss of forest loss (Gross Forest Cover Loss, GFCL) based on the cause (natural/human) and on the outcome of the change (regeneration to forest/transition to non-forest) (Kurtz et al., 2010). While natural forest disturbances (fires, insect outbreaks) and timber harvest generally involve a temporary change of land cover (vegetated to non-vegetated), they generally do not involve a change in land use, and it is expected that the forest cover loss is followed by recovery. Change of land use, such as the conversion of forest to agricultural or urban areas, is instead generally irreversible. The proper classification of forest cover loss is therefore necessary to properly model the long term effects of the disturbances on the carbon budget. The present study presents a spatial and temporal analysis of the forest cover loss due to urban expansion in the Conterminous United States. The Landsat-derived University of Maryland Global Forest Change product (Hansen et al, 2013) is used to identify all the areas of gross forest cover loss, which are subsequently classified into disturbance type (deforestation, stand-replacing natural disturbances, industrial forest clearcuts) using an object-oriented time series analysis (Huo and Boschetti, 2015). A further refinement of the classification is conducted to identify the areas of transition from forest land use to urban land use based on ancillary datasets such as the National Land Cover Database (Homer et al., 2015) and contextual image analysis techniques (analysis of object proximity, and detection of shapes). Results showed that over 4000 km2of forest were lost to urban area expansion in CONUS over the 2001 to 2010 period (1.8% of the gross forest cover loss). Most of the urban growth was concentrated in large urban areas: Atlanta, GA ranked first, followed by Houston, TX; Charlotte, NC; Jacksonville, FL; and Raleigh, NC. At the state level, the top 10 states with urban growth due to forest loss were GA, FL, TX, NC, SC, AL, LA, MS, VA and WA, which cumulatively accounted for 76 % of the total forest cover loss due to urban growth.

Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

NASA Astrophysics Data System (ADS)

Kolecka, N.; Kozak, J.; Kaim, D.; Dobosz, M.; Ginzler, Ch.; Psomas, A.

2016-06-01

Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.

Cropland management dynamics as a driver of forest cover change in European Russia (Invited)

NASA Astrophysics Data System (ADS)

Tyukavina, A.; Krylov, A.; Potapov, P.; Turubanova, S.; Hansen, M.; McCarty, J. L.

2013-12-01

The European part of Russia spans over 40% of the European subcontinent and comprises most of Europe's temperate and boreal forests. The region has undergone a socio-economic transition during the last two decades that has resulted in radical changes in land management. Large-scale agriculture land abandonment caused massive afforestation in the Central and Northern parts of the region (Alcantara et al. 2012). Afforestation of former croplands is currently not included in the official forestry statistical reports (Potapov et al. 2012), but is likely to have major impacts on regional carbon budgets (Kuemmerle et al. 2009). We employed a complete archive of Landsat TM and ETM+ imagery and automatic data processing algorithm to create regional time-sequential image composites and multi-temporal metrics for 1985-2012. Spectral metrics were used as independent variables to map forest cover and change with help of supervised machine learning algorithms and trend analysis. Forest cover loss was attributed to fires, harvesting, and wind/disease dynamics, while forest cover gain was disaggregated into reforestation and afforestation using pre-1990 TM imagery as baseline data. Special attention was paid to agricultural abandonment. Fire events of the last decade have been further characterized by ignition place, time, and burning intensity using MODIS fire detection data. Change detection products have been validated using field data collected during summer 2012 and 2013 and high resolution imagery. Massive arable land abandonment caused forest area increase within Central agricultural regions. While total logging area decreased after the USSR breakdown, logging and other forms of clearing increased within the Central and Western parts of the region. Gross forest gain and loss were nearly balanced within region; however, the most populated regions of European Russia featured the highest rate of net forest cover loss during the last decade. The annual burned forest area as well as area of windstorms damage significantly increased, especially in the Central regions. Fires predominantly affected pine forests and drained peatlands prone to summer droughts. Fire date and ignition analysis showed that forest fires are not related to extensive spring-time agricultural burning. References: Alcantara, C., T. Kuemmerle, A. V. Prishchepov & V. C. Radeloff. 2012. Mapping abandoned agriculture with multi-temporal MODIS satellite data. 334-347. Remote Sensing of Environment. Kuemmerle, T., O. Chaskovskyy, J. Knorn, V. C. Radeloff, I. Kruhlov, W. S. Keeton & P. Hostert. 2009. Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007. Remote Sensing of Environment, 113, 1194-1207. Potapov, P., S. Turubanova, I. Zhuravleva, M. Hansen, A. Yaroshenko & A. Manisha. 2012. Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990-2005) 1-11. International Journal of Forestry Research.

Ten year change in forest succession and composition measured by remote sensing

NASA Technical Reports Server (NTRS)

Hall, Forrest G.; Botkin, Daniel B.; Strebel, Donald E.; Woods, Kerry K.; Goetz, Scott J.

1987-01-01

Vegetation dynamics and changes in ecological patterns were measured by remote sensing over a 10 year period (1973 to 1983) for 148,406 landscape elements, covering more than 500 sq km in a protected forested wilderness. Quantitative measurements were made possible by methods to detect ecologically meaningful landscape units; these allowed measurement of ecological transition frequencies and calculation of expected recurrence times. Measured ecological transition frequencies reveal boreal forest wilderness as spatially heterogeneous and highly dynamic, with one-sixth of the area in clearings and early successional stages, consistent with recent postulates about the spatial and temporal patterns of natural ecosystems. Differences between managed forest areas and a protected wilderness allow assessment of different management regimes.

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync — Tools for calibration and validation

Treesearch

Warren B. Cohen; Zhiqiang Yang; Robert Kennedy

2010-01-01

Availability of free, high quality Landsat data portends a new era in remote sensing change detection. Using dense (~annual) Landsat time series (LTS), we can now characterize vegetation change over large areas at an annual time step and at the spatial grain of anthropogenic disturbance. Additionally, we expect more accurate detection of subtle disturbances and...

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators

USGS Publications Warehouse

Perles, Stephanie J.; Wagner, Tyler; Irwin, Brian J.; Manning, Douglas R.; Callahan, Kristina K.; Marshall, Matthew R.

2014-01-01

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of theVital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year−1 for all indicators and is appropriate for detecting a 1 % trend·year−1 in most indicators.

Remote Detection and Modeling of Abrupt and Gradual Tree Mortality in the Southwestern USA

NASA Astrophysics Data System (ADS)

Muss, J. D.; Xu, C.; McDowell, N. G.

2014-12-01

Current climate models predict a warming and drying trend that has a high probability of increasing the frequency and spatial extent of tree mortality events. Field surveys can be used to identify, date, and attribute a cause of mortality to specific trees, but monetary and time constraints prevent broad-scale surveys, which are necessary to establish regional or global trends in tree mortality. This is significant because widespread forest mortality will likely lead to radical changes in evapotranspiration and surface albedo, which could compound climate change. While understanding the causes and mechanisms of tree mortality events is crucial, it is equally important to be able to detect and monitor mortality and subsequent changes to the ecosystem at broad spatial- and temporal-scales. Over the past five years our ability to remotely detect abrupt forest mortality events has improved greatly, but gradual events—such as those caused by drought or certain types of insects—are still difficult to identify. Moreover, it is virtually impossible to quantify the amount of mortality that has occurred within a mixed pixel. We have developed a system that fuses climate and satellite-derived spectral data to identify both the date and the agent of forest mortality events. This system has been used with Landsat time series data to detect both abrupt and general trends in tree loss that have occurred during the past quarter-century in northern New Mexico. It has also been used with MODIS data to identify pixels with a high likelihood of drought-caused tree mortality in the Southwestern US. These candidate pixels were then fed to ED-FRT, a coupled forest dynamics-radiative transfer model, to generate estimates of drought-induced. We demonstrate a multi-scale approach that can produce results that will be instrumental in advancing our understanding of tree mortality-climate feedbacks, and improve our ability to predict what forests could look like in the future.

Digital photo monitoring for tree crown

Treesearch

Neil Clark; Sang-Mook Lee

2007-01-01

Assessing change in the amount of foliage within a tree’s crown is the goal of crown transparency estimation, a component in many forest health assessment programs. Many sources of variability limit analysis and interpretation of crown condition data. Increased precision is needed to detect more subtle changes that are important for detection of health problems....

Extensive wildfires, climate change, and an abrupt state change in subalpine ribbon forests, Colorado.

PubMed

Calder, W John; Shuman, Bryan

2017-10-01

Ecosystems may shift abruptly when the effects of climate change and disturbance interact, and landscapes with regularly patterned vegetation may be especially vulnerable to abrupt shifts. Here we use a fossil pollen record from a regularly patterned ribbon forest (alternating bands of forests and meadows) in Colorado to examine whether past changes in wildfire and climate produced abrupt vegetation shifts. Comparing the percentages of conifer pollen with sedimentary δ 18 O data (interpreted as an indicator of temperature or snow accumulation) indicates a first-order linear relationship between vegetation composition and climate change with no detectable lags over the past 2,500 yr (r = 0.55, P < 0.001). Additionally, however, we find that the vegetation changed abruptly within a century of extensive wildfires, which were recognized in a previous study to have burned approximately 80% of the surrounding 1,000 km 2 landscape 1,000 yr ago when temperatures rose ~0.5°C. The vegetation change was larger than expected from the effects of climate change alone. Pollen assemblages changed from a composition associated with closed subalpine forests to one similar to modern ribbon forests. Fossil pollen assemblages then remained like those from modern ribbon forests for the following ~1,000 yr, providing a clear example of how extensive disturbances can trigger persistent new vegetation states and alter how vegetation responds to climate. © 2017 by the Ecological Society of America.

Monitoring the Extent of Forests on National to Global Scales

NASA Astrophysics Data System (ADS)

Townshend, J.; Townshend, J.; Hansen, M.; DeFries, R.; DeFries, R.; Sohlberg, R.; Desch, A.; White, B.

2001-05-01

Information on forest extent and change is important for many purposes, including understanding the global carbon cycle and managing natural resources. International statistics on forest extent are generated using many different sources often producing inconsistent results spatially and through time. Results will be presented comparing forest extent derived from the recent global Food and Agricultural Organization's (FAO) FRA 2000 report with products derived using wall-to-wall Landsat, AVHRR and MODIS data sets. The remotely sensed data sets provide consistent results in terms of total area despite considerable differences in spatial resolution. Although the location of change can be satisfactorily detected with all three remotely sensed data sets, reliable measurement of change can only be achieved through use of Landsat-resolution data. Contrary to the FRA 2000 results we find evidence of an increase in deforestation rates in the late 1990s in several countries. Also we have found evidence of considerable changes in some countries for which little or no change is reported by FAO. The results indicate the benefits of globally consistent analyses of forest cover based on multiscale remotely sensed data sets rather than a reliance on statistics generated by individual countries with very different definitions of forest and methods used to derive them.

Long-term strategy for the statistical design of a forest health monitoring system

Treesearch

Hans T. Schreuder; Raymond L. Czaplewski

1993-01-01

A conceptual framework is given for a broad-scale survey of forest health that accomplishes three objectives: generate descriptive statistics; detect changes in such statistics; and simplify analytical inferences that identify, and possibly establish cause-effect relationships. Our paper discusses the development of sampling schemes to satisfy these three objectives,...

Climate change: detecting climate's imprint on California forests

Treesearch

Anne M. Rosenthal; Constance I. Millar

2003-01-01

Hiking the nearly treeless slopes of western Nevada's Wassuk Range, researcher Connie Millar found dead limber pine throughout the watersheds. Where scanty forests were present, the dead wood occurred above treeline. Investigation of these wood remnants, sculpted by the elements over hundreds of years, revealed a cyclical pattern of limber pine colonization and...

Hyperspectral remote sensing of postfire soil properties

Treesearch

Sarah A. Lewis; Peter R. Robichaud; William J. Elliot; Bruce E. Frazier; Joan Q. Wu

2004-01-01

Forest fires may induce changes in soil organic properties that often lead to water repellent conditions within the soil profile that decrease soil infiltration capacity. The remote detection of water repellent soils after forest fires would lead to quicker and more accurate assessment of erosion potential. An airborne hyperspectral image was acquired over the Hayman...

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Norman, S.; Gasser, J.; Smoot, J.; Kuper, P.

2012-12-01

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide near real time forest change products every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn's geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbance patches of multiple pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Norman, Steve; Gasser, Jerry; Smoot, James; Kuper, Philip D,

2012-01-01

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide NRT forest change products refreshed every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn s geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbances affecting multiple MODIS pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Large-Scale Mixed Temperate Forest Mapping at the Single Tree Level using Airborne Laser Scanning

NASA Astrophysics Data System (ADS)

Scholl, V.; Morsdorf, F.; Ginzler, C.; Schaepman, M. E.

2017-12-01

Monitoring vegetation on a single tree level is critical to understand and model a variety of processes, functions, and changes in forest systems. Remote sensing technologies are increasingly utilized to complement and upscale the field-based measurements of forest inventories. Airborne laser scanning (ALS) systems provide valuable information in the vertical dimension for effective vegetation structure mapping. Although many algorithms exist to extract single tree segments from forest scans, they are often tuned to perform well in homogeneous coniferous or deciduous areas and are not successful in mixed forests. Other methods are too computationally expensive to apply operationally. The aim of this study was to develop a single tree detection workflow using leaf-off ALS data for the canton of Aargau in Switzerland. Aargau covers an area of over 1,400km2 and features mixed forests with various development stages and topography. Forest type was classified using random forests to guide local parameter selection. Canopy height model-based treetop maxima were detected and maintained based on the relationship between tree height and window size, used as a proxy to crown diameter. Watershed segmentation was used to generate crown polygons surrounding each maximum. The location, height, and crown dimensions of single trees were derived from the ALS returns within each polygon. Validation was performed through comparison with field measurements and extrapolated estimates from long-term monitoring plots of the Swiss National Forest Inventory within the framework of the Swiss Federal Institute for Forest, Snow, and Landscape Research. This method shows promise for robust, large-scale single tree detection in mixed forests. The single tree data will aid ecological studies as well as forest management practices. Figure description: Height-normalized ALS point cloud data (top) and resulting single tree segments (bottom) on the Laegeren mountain in Switzerland.

Balancing trade-offs between ecosystem services in Germany’s forests under climate change

NASA Astrophysics Data System (ADS)

Gutsch, Martin; Lasch-Born, Petra; Kollas, Chris; Suckow, Felicitas; Reyer, Christopher P. O.

2018-04-01

Germany’s forests provide a variety of ecosystem services. Sustainable forest management aims to optimize the provision of these services at regional level. However, climate change will impact forest ecosystems and subsequently ecosystem services. The objective of this study is to quantify the effects of two alternative management scenarios and climate impacts on forest variables indicative of ecosystem services related to timber, habitat, water, and carbon. The ecosystem services are represented through nine model output variables (timber harvest, above and belowground biomass, net ecosystem production, soil carbon, percolation, nitrogen leaching, deadwood, tree dimension, broadleaf tree proportion) from the process-based forest model 4C. We simulated forest growth, carbon and water cycling until 2045 with 4C set-up for the whole German forest area based on National Forest Inventory data and driven by three management strategies (nature protection, biomass production and a baseline management) and an ensemble of regional climate scenarios (RCP2.6, RCP 4.5, RCP 8.5). We provide results as relative changes compared to the baseline management and observed climate. Forest management measures have the strongest effects on ecosystem services inducing positive or negative changes of up to 40% depending on the ecosystem service in question, whereas climate change only slightly alters ecosystem services averaged over the whole forest area. The ecosystem services ‘carbon’ and ‘timber’ benefit from climate change, while ‘water’ and ‘habitat’ lose. We detect clear trade-offs between ‘timber’ and all other ecosystem services, as well as synergies between ‘habitat’ and ‘carbon’. When evaluating all ecosystem services simultaneously, our results reveal certain interrelations between climate and management scenarios. North-eastern and western forest regions are more suitable to provide timber (while minimizing the negative impacts on remaining ecosystem services) whereas southern and central forest regions are more suitable to fulfil ‘habitat’ and ‘carbon’ services. The results provide the base for future forest management optimizations at the regional scale in order to maximize ecosystem services and forest ecosystem sustainability at the national scale.

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Foster, James L.

2009-01-01

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Assessing the impacts of climate change and nitrogen deposition on Norway spruce (Picea abies L. Karst) growth in Austria with BIOME-BGC.

PubMed

Eastaugh, Chris S; Pötzelsberger, Elisabeth; Hasenauer, Hubert

2011-03-01

The aim of this paper is to determine whether a detectable impact of climate change is apparent in Austrian forests. In regions of complex terrain such as most of Austria, climatic trends over the past 50 years show marked geographic variability. As climate is one of the key drivers of forest growth, a comparison of growth characteristics between regions with different trends in temperature and precipitation can give insights into the impact of climatic change on forests. This study uses data from several hundred climate recording stations, interpolated to measurement sites of the Austrian National Forest Inventory (NFI). Austria as a whole shows a warming trend over the past 50 years and little overall change in precipitation. The warming trends, however, vary considerably across certain regions and regional precipitation trends vary widely in both directions, which cancel out on the national scale These differences allow the delineation of 'climatic change zones' with internally consistent climatic trends that differ from other zones. This study applies the species-specific adaptation of the biogeochemical model BIOME-BGC to Norway spruce (Picea abies (L.) Karst) across a range of Austrian climatic change zones, using input data from a number of national databases. The relative influence of extant climate change on forest growth is quantified, and compared with the far greater impact of non-climatic factors. At the national scale, climate change is found to have negligible effect on Norway spruce productivity, due in part to opposing effects at the regional level. The magnitudes of the modeled non-climatic influences on aboveground woody biomass increment increases are consistent with previously reported values of 20-40 kg of added stem carbon sequestration per kilogram of additional nitrogen deposition, while climate responses are of a magnitude difficult to detect in NFI data.

Determination of Land Use/ Land Cover Changes in Igneada Alluvial (Longos) Forest Ecosystem, Turkey

NASA Astrophysics Data System (ADS)

Bektas Balcik, F.

2012-12-01

Alluvial (Longos) forests are one of the most fragile and threatened ecosystems in the world. Typically, these types of ecosystems have high biological diversity, high productivity, and high habitat dynamism. In this study, Igneada, Kirklareli was selected as study area. The region, lies between latitudes 41° 46' N and 41° 59' N and stretches between longitudes 27° 50' E and 28° 02' E and it covers approximately 24000 (ha). Igneada Longos ecosystems include mixed forests, streams, flooded (alluvial) forests, marshes, wetlands, lakes and coastal sand dunes with different types of flora and fauna. Igneada was classified by Conservation International as one of the world's top 122 Important Plant Areas, and 185 Important Bird Areas. These types of wild forest in other parts of Turkey and in Europe have been damaged due to anthropogenic effects. Remote sensing is very effective tool to monitor these types of sensitive regions for sustainable management. In this study, 1984 and 2011 dated Landsat 5 TM data were used to determine land cover/land use change detection of the selected region by using six vegetation indices such as Tasseled Cap index of greenness (TCG), brightness (TCB), and wetness (TCW), ratios of near-infrared to red image (RVI), normalized difference vegetation index (NDVI), and soil-adjusted vegetation index (SAVI). Geometric and radiometric corrections were applied in image pre-processing step. Selective Principle Component Analysis (PCA) change detection method was applied to the selected vegetation index imagery to generate change imagery for extracting the changed features between the year of 1984 and 2011. Accuracy assessment was applied based on error matrix by calculating overall accuracy and Kappa statistics.

Inferring responses to climate dynamics from historical demography in neotropical forest lizards

PubMed Central

Xue, Alexander T.; Brown, Jason L.; Alvarado-Serrano, Diego F.; Rodrigues, Miguel T.; Hickerson, Michael J.; Carnaval, Ana C.

2016-01-01

We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future. PMID:27432951

Inferring responses to climate dynamics from historical demography in neotropical forest lizards.

PubMed

Prates, Ivan; Xue, Alexander T; Brown, Jason L; Alvarado-Serrano, Diego F; Rodrigues, Miguel T; Hickerson, Michael J; Carnaval, Ana C

2016-07-19

We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future.

Quantifying resilience of multiple ecosystem services and biodiversity in a temperate forest landscape.

PubMed

Cantarello, Elena; Newton, Adrian C; Martin, Philip A; Evans, Paul M; Gosal, Arjan; Lucash, Melissa S

2017-11-01

Resilience is increasingly being considered as a new paradigm of forest management among scientists, practitioners, and policymakers. However, metrics of resilience to environmental change are lacking. Faced with novel disturbances, forests may be able to sustain existing ecosystem services and biodiversity by exhibiting resilience, or alternatively these attributes may undergo either a linear or nonlinear decline. Here we provide a novel quantitative approach for assessing forest resilience that focuses on three components of resilience, namely resistance, recovery, and net change, using a spatially explicit model of forest dynamics. Under the pulse set scenarios, we explored the resilience of nine ecosystem services and four biodiversity measures following a one-off disturbance applied to an increasing percentage of forest area. Under the pulse + press set scenarios, the six disturbance intensities explored during the pulse set were followed by a continuous disturbance. We detected thresholds in net change under pulse + press scenarios for the majority of the ecosystem services and biodiversity measures, which started to decline sharply when disturbance affected >40% of the landscape. Thresholds in net change were not observed under the pulse scenarios, with the exception of timber volume and ground flora species richness. Thresholds were most pronounced for aboveground biomass, timber volume with respect to the ecosystem services, and ectomycorrhizal fungi and ground flora species richness with respect to the biodiversity measures. Synthesis and applications . The approach presented here illustrates how the multidimensionality of stability research in ecology can be addressed and how forest resilience can be estimated in practice. Managers should adopt specific management actions to support each of the three components of resilience separately, as these may respond differently to disturbance. In addition, management interventions aiming to deliver resilience should incorporate an assessment of both pulse and press disturbances to ensure detection of threshold responses to disturbance, so that appropriate management interventions can be identified.

Canopy gaps decrease microbial densities and disease risk for a shade-intolerant tree species

NASA Astrophysics Data System (ADS)

Reinhart, Kurt O.; Royo, Alejandro A.; Kageyama, Stacie A.; Clay, Keith

2010-11-01

Canopy disturbances such as windthrow events have obvious impacts on forest structure and composition aboveground, but changes in soil microbial communities and the consequences of these changes are less understood. We characterized the densities of a soil-borne pathogenic oomycete ( Pythium) and a common saprotrophic zygomycete ( Mortierella) in nine pairs of forest gaps created by windthrows and adjacent forest understories. We determined the levels of Pythium necessary to cause disease by performing pathogenicity experiments using two Pythium species, a range of Pythium densities, and two common tree species ( Acer rubrum and Prunus serotina) from the study sites. Three years post-disturbance, densities of Mortierella remained suppressed in soil from forest gaps compared to levels in intact forest understories while varying across sites and sampling dates. Pythium were infrequently detected likely because of soil handling effects. Expression of disease symptoms increased with increasing inoculum density for seedlings of P. serotina with each Pythium spp. having a similar effect on this species. Conversely, A. rubrum appeared resistant to the two species of Pythium. These results suggest that Pythium densities at sites where they were detected are sufficient to cause disease and possibly affect establishment of susceptible species like P. serotina. Because early seral environments have lower loads of the saprotrophic Mortierella, pathogen loads may follow a similar pattern, causing susceptible species to establish more frequently in those habitats than in late-seral forests. Forest disturbances that alter the disease landscape may provide an additional mechanism for explaining succession of temperate forests in addition to the shade-tolerance paradigm.

Changes in Spring Vegetation Activity over Eurasian Boreal Forest Associated with Reduction of Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Koh, Y.; Jeong, J. H.; Kim, B. M.; Park, T. W.; Jeong, S. J.

2017-12-01

Vegetation activities over the high-latitude in the Northern-Hemisphere are known to be very sensitive to climate change, which can, in turn, affect the entire climate system. This is one of the important feedback effects on global climate change. In this study, we have detected a declining trend of vegetation index in the boreal forest (Taiga) region of Eurasia in early spring from the late 1990s, and confirmed that the cause is closely related to the decrease in winter temperature linked to the Arctic sea ice change. The reduction of Arctic sea ice induces weakening of the Polar vortex around the Arctic, which has a chilling effect throughout Eurasia until the early spring (March) by strengthening the Siberian high in the Eurasian continent. The decrease of vegetation growth is caused by the extreme cold phenomenon directly affecting the growth of the boreal trees. To verify this, we used vegetation-climate coupled models to investigate climate-vegetation sensitivity to sea ice reduction. As a result, when the Arctic sea ice decreased in the model simulation, the vegetation index of the boreal forest, especially needleleaf evergreen trees, decreased as similarly detected by observations.

Estimation of streamflow response to wildfire and salvage logging in a snow-dominated catchment using a model-based change detection approach

NASA Astrophysics Data System (ADS)

Moore, R. D.; Mahrlein, M.; Chuang, Y. C. M.

2016-12-01

Forest cover changes associated with natural disturbance and forest management can have significant influences on the magnitude and timing of streamflow. This study quantified the effect of a wildfire that burned over 60% of the catchment of Fishtrap Creek in the southern interior of British Columbia in August 2003. Fishtrap Creek has been gauged from 1970 to present. The catchment drains 158 km2 at the gauging station and has a snow-dominated hydrologic regime. In 2006, about one-third of the burned area was salvage logged. A semi-distributed hydrologic model was calibrated and tested using the pre-fire streamflow data. Simulated daily streamflow based on the "best" parameter set, and assuming pre-fire forest cover, was used as a "virtual" control in a paired-catchment analysis. Each year was divided into 73 five-day periods (pentads), and separate pre-fire regressions were fit for each of the 73 pentad time series. This approach avoids issues with autocorrelation and can address seasonally varying model bias. Statistically significant increases in streamflow were detected in late winter and through the month of April, with no evidence for increased peak flows, which is inferred to reflect a de-synchronization of snowmelt between disturbed and undisturbed areas of the catchment. The results of the model-based change detection are consistent with statistical analyses using climatic variables as covariates, but have the advantage of providing more temporal detail. However, the power of the change detection can be limited by insufficiently long records of streamflow and driving weather variables for both the pre- and post-fire periods and model structural errors (e.g., an inability to reproduce winter baseflow). An interesting side result of the study was the identification of parameter uncertainty associated with uncertainty regarding forest cover during the calibration period.

Detecting post-fire salvage logging with Landsat change maps and national fire survey data

Treesearch

Todd A. Schroeder; Michael A. Wulder; Sean P. Healey; Gretchen G. Moisen

2012-01-01

In Canadian boreal forests, wildfire is the predominant agent of natural disturbance often with millions of hectares burning annually. In addition to fire, nearly one quarter of Canada's boreal forest is also managed for industrial wood production. Post-fire logging (or salvage harvesting) is increasingly used to minimize economic losses from fire, notwithstanding...

Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon.

Treesearch

Todd A. Schroeder; Warren B. Cohen; Conghe Song; Morton J. Canty; Zhiqiang Yang

2006-01-01

Detecting and characterizing continuous changes in early forest succession using multi-temporal satellite imagery requires atmospheric correction procedures that are both operationally reliable, and that result in comparable units (e-g., surface reflectance). This paper presents a comparison of five atmospheric correction methods (2 relative, 3 absolute) used to...

High-resolution forest carbon stocks and emissions in the Amazon

Treesearch

G. P. Asner; George V. N. Powell; Joseph Mascaro; David E. Knapp; John K. Clark; James Jacobson; Ty Kennedy-Bowdoin; Aravindh Balaji; Guayana Paez-Acosta; Eloy Victoria; Laura Secada; Michael Valqui; R. Flint. Hughes

2010-01-01

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at...

Near Real Time Change-Point detection in Optical and Thermal Infrared Time Series Using Bayesian Inference over the Dry Chaco Forest

NASA Astrophysics Data System (ADS)

Barraza Bernadas, V.; Grings, F.; Roitberg, E.; Perna, P.; Karszenbaum, H.

2017-12-01

The Dry Chaco region (DCF) has the highest absolute deforestation rates of all Argentinian forests. The most recent report indicates a current deforestation rate of 200,000 Ha year-1. In order to better monitor this process, DCF was chosen to implement an early warning program for illegal deforestation. Although the area is intensively studied using medium resolution imagery (Landsat), the products obtained have a yearly pace and therefore unsuited for an early warning program. In this paper, we evaluated the performance of an online Bayesian change-point detection algorithm for MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) datasets. The goal was to to monitor the abrupt changes in vegetation dynamics associated with deforestation events. We tested this model by simulating 16-day EVI and 8-day LST time series with varying amounts of seasonality, noise, length of the time series and by adding abrupt changes with different magnitudes. This model was then tested on real satellite time series available through the Google Earth Engine, over a pilot area in DCF, where deforestation was common in the 2004-2016 period. A comparison with yearly benchmark products based on Landsat images is also presented (REDAF dataset). The results shows the advantages of using an automatic model to detect a changepoint in the time series than using only visual inspection techniques. Simulating time series with varying amounts of seasonality and noise, and by adding abrupt changes at different times and magnitudes, revealed that this model is robust against noise, and is not influenced by changes in amplitude of the seasonal component. Furthermore, the results compared favorably with REDAF dataset (near 65% of agreement). These results show the potential to combine LST and EVI to identify deforestation events. This work is being developed within the frame of the national Forest Law for the protection and sustainable development of Native Forest in Argentina in agreement with international legislation (REDD+).

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Implications of land use change on the national terrestrial carbon budget of Georgia

PubMed Central

2010-01-01

Background Globally, the loss of forests now contributes almost 20% of carbon dioxide emissions to the atmosphere. There is an immediate need to reduce the current rates of forest loss, and the associated release of carbon dioxide, but for many areas of the world these rates are largely unknown. The Soviet Union contained a substantial part of the world's forests and the fate of those forests and their effect on carbon dynamics remain unknown for many areas of the former Eastern Bloc. For Georgia, the political and economic transitions following independence in 1991 have been dramatic. In this paper we quantify rates of land use changes and their effect on the terrestrial carbon budget for Georgia. A carbon book-keeping model traces changes in carbon stocks using historical and current rates of land use change. Landsat satellite images acquired circa 1990 and 2000 were analyzed to detect changes in forest cover since 1990. Results The remote sensing analysis showed that a modest forest loss occurred, with approximately 0.8% of the forest cover having disappeared after 1990. Nevertheless, growth of Georgian forests still contribute a current national sink of about 0.3 Tg of carbon per year, which corresponds to 31% of the country anthropogenic carbon emissions. Conclusions We assume that the observed forest loss is mainly a result of illegal logging, but we have not found any evidence of large-scale clear-cutting. Instead local harvesting of timber for household use is likely to be the underlying driver of the observed logging. The Georgian forests are a currently a carbon sink and will remain as such until about 2040 if the current rate of deforestation persists. Forest protection efforts, combined with economic growth, are essential for reducing the rate of deforestation and protecting the carbon sink provided by Georgian forests. PMID:20836865

Mangrove forest distributions and dynamics in Madagascar (1975-2005)

USGS Publications Warehouse

Giri, C.; Muhlhausen, J.

2008-01-01

Mangrove forests of Madagascar are declining, albeit at a much slower rate than the global average. The forests are declining due to conversion to other land uses and forest degradation. However, accurate and reliable information on their present distribution and their rates, causes, and consequences of change have not been available. Earlier studies used remotely sensed data to map and, in some cases, to monitor mangrove forests at a local scale. Nonetheless, a comprehensive national assessment and synthesis was lacking. We interpreted time-series satellite data of 1975, 1990, 2000, and 2005 using a hybrid supervised and unsupervised classification approach. Landsat data were geometrically corrected to an accuracy of ?? one-half pixel, an accuracy necessary for change analysis. We used a postclassification change detection approach. Our results showed that Madagascar lost 7% of mangrove forests from 1975 to 2005, to a present extent of ???2,797 km2. Deforestation rates and causes varied both spatially and temporally. The forests increased by 5.6% (212 km2) from 1975 to 1990, decreased by 14.3% (455 km 2) from 1990 to 2000, and decreased by 2.6% (73 km2) from 2000 to 2005. Similarly, major changes occurred in Bombekota Bay, Mahajamba Bay, the coast of Ambanja, the Tsiribihina River, and Cap St Vincent. The main factors responsible for mangrove deforestation include conversion to agriculture (35%), logging (16%), conversion to aquaculture (3%), and urban development (1%). ?? 2008 by MDPI.

Soil Bacterial Community Shift Correlated with Change from Forest to Pasture Vegetation in a Tropical Soil

PubMed Central

Nüsslein, Klaus; Tiedje, James M.

1999-01-01

The change in vegetative cover of a Hawaiian soil from forest to pasture led to significant changes in the composition of the soil bacterial community. DNAs were extracted from both soil habitats and compared for the abundance of guanine-plus-cytosine (G+C) content, by analysis of abundance of phylotypes of small-subunit ribosomal DNA (SSU rDNA) amplified from fractions with 63 and 35% G+C contents, and by phylogenetic analysis of the dominant rDNA clones in the 63% G+C content fraction. All three methods showed differences between the forest and pasture habitats, providing evidence that vegetation had a strong influence on microbial community composition at three levels of taxon resolution. The forest soil DNA had a peak in G+C content of 61%, while the DNA of the pasture soil had a peak in G+C content of 67%. None of the dominant phylotypes found in the forest soil were detected in the pasture soil. For the 63% G+C fraction SSU rDNA sequence analysis of the three most dominant members revealed that their phyla changed from Fibrobacter and Syntrophomonas assemblages in the forest soil to Burkholderia and Rhizobium–Agrobacterium assemblages in the pasture soil. PMID:10427058

Mapping of forest disturbance magnitudes across the US National Forest System

NASA Astrophysics Data System (ADS)

Hernandez, A. J.; Healey, S. P.; Ramsey, R. D.; McGinty, C.; Garrard, C.; Lu, N.; Huang, C.

2013-12-01

A precise record in conjunction with ongoing monitoring of carbon pools constitutes essentials inputs for the continuous modernization of an ever- dynamic science such as climate change. This is particularly important in forested ecosystems for which accurate field archives are available and can be used in combination with historic satellite imagery to obtain spatially explicit estimates of several indicators that can be used in the assessment of said carbon pools. Many forest disturbance processes limit storage of carbon in forested ecosystems and thereby reduce those systems' capacity to mitigate changes in the global climate system. A component of the US National Forest System's (NFS) comprehensive plan for carbon monitoring includes accounting for mapped disturbances, such as fires, harvests, and insect activity. A long-term time series of maps that show the timing, extent, type, and magnitude of disturbances going back to 1990 has been prepared for the United States Forest Service (USFS) Northern Region, and is currently under preparation for the rest of the NFS regions covering more than 75 million hectares. Our mapping approach starts with an automated initial detection of annual disturbances using imagery captured within the growing season from the Landsat archive. Through a meticulous process, the initial detections are then visually inspected, manually corrected and labeled using various USFS ancillary datasets and Google Earth high-resolution historic imagery. We prepared multitemporal models of percent canopy cover and live tree carbon (T/ha) that were calibrated with extensive (in excess of 2000 locations) field data from the US Forest Service Forest Inventory and Analysis program (FIA). The models were then applied to all the years of the radiometrically corrected and normalized Landsat time series in order to provide annual spatially explicit estimates of the magnitude of change in terms of these two attributes. Our results provide objective, widely interpretable estimates of per-year disturbance effects across large areas. Different stakeholders (scientists, managers, policymakers) should benefit from this broad survey of disturbance processes affecting US federal forests over the last 20 years.

Stratifying Tropical Fires by Land Cover: Insights into Amazonian Fires, Aerosol Loading, and Regional Deforestation

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

This study analyzes changes in the number of fires detected on forest, grass, and transition lands during the 2002-2009 biomass burning seasons using fire detection data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the total number of detected fires correlates well with MODIS mean aerosol optical depth (AOD) from year to year, in accord with other studies. However, we also show that the ratio of forest to savanna fires varies substantially from year to year. Forest fires have trended downward, on average, since the beginning of 2006 despite a modest increase in 2007. Our study suggests that high particulate matter loading detected in 2007 was likely due to a large number of savanna/agricultural fires that year. Finally, we illustrate that the correlation between annual Brazilian deforestation estimates and MODIS fires is considerably higher when fires are stratified by MODIS-derived land cover classifications.

A forester's look at the application of image manipulation techniques to multitemporal Landsat data

NASA Technical Reports Server (NTRS)

Williams, D. L.; Stauffer, M. L.; Leung, K. C.

1979-01-01

Registered, multitemporal Landsat data of a study area in central Pennsylvania were analyzed to detect and assess changes in the forest canopy resulting from insect defoliation. Images taken July 19, 1976, and June 27, 1977, were chosen specifically to represent forest canopy conditions before and after defoliation, respectively. Several image manipulation and data transformation techniques, developed primarily for estimating agricultural and rangeland standing green biomass, were applied to these data. The applicability of each technique for estimating the severity of forest canopy defoliation was then evaluated. All techniques tested had highly correlated results. In all cases, heavy defoliation was discriminated from healthy forest. Areas of moderate defoliation were confused with healthy forest on northwest (NW) aspects, but were distinct from healthy forest conditions on southeast (SE)-facing slopes.

Geospatiotemporal Data Mining of Remotely Sensed Phenology for Unsupervised Forest Threat Detection

NASA Astrophysics Data System (ADS)

Mills, R. T.; Hoffman, F. M.; Kumar, J.; Vulli, S. S.; Hargrove, W. W.; Spruce, J.

2010-12-01

Hargrove and Hoffman have previously developed and applied a scalable geospatiotemporal data mining approach to define a set of categorical, multivariate classes or states for describing and tracking the behavior of ecosystem properties through time within a multi-dimensional phase or state space. The method employs a standard k-means cluster analysis with enhancements that reduce the number of required comparisons, dramatically accelerating iterative convergence. In support of efforts by the USDA Forest Service to develop a National Early Warning System for Forest Disturbances, we have applied this geospatiotemporal cluster analysis procedure to annual phenology patterns derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) for unsupervised change detection. We will present initial results from the analysis of seven years of 250-m MODIS NDVI data for the conterminous United States. While determining what constitutes a "normal" phenological pattern for any given location is challenging due to interannual climate variability, a spatially varying climate change trend, and the relatively short record of MODIS NDVI observations, these results demonstrate the utility of the method for detecting significant mortality events, like the progressive damage from mountain pine beetle, and suggest that the technique may be successfully implemented as a key component in an early warning system for identifying forest threats from natural and anthropogenic disturbances at a continental scale.

High-resolution forest carbon stocks and emissions in the Amazon.

PubMed

Asner, Gregory P; Powell, George V N; Mascaro, Joseph; Knapp, David E; Clark, John K; Jacobson, James; Kennedy-Bowdoin, Ty; Balaji, Aravindh; Paez-Acosta, Guayana; Victoria, Eloy; Secada, Laura; Valqui, Michael; Hughes, R Flint

2010-09-21

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha resolution over 4.3 million ha of the Peruvian Amazon, an area twice that of all forests in Costa Rica, to reveal the determinants of forest carbon density and to demonstrate the feasibility of mapping carbon emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based on geologic substrate and forest type. From 1999 to 2009, emissions from land use totaled 1.1% of the standing carbon throughout the region. Forest degradation, such as from selective logging, increased regional carbon emissions by 47% over deforestation alone, and secondary regrowth provided an 18% offset against total gross emissions. Very high-resolution monitoring reduces uncertainty in carbon emissions for REDD programs while uncovering fundamental environmental controls on forest carbon storage and their interactions with land-use change.

Towards a sampling strategy for the assessment of forest condition at European level: combining country estimates.

PubMed

Travaglini, Davide; Fattorini, Lorenzo; Barbati, Anna; Bottalico, Francesca; Corona, Piermaria; Ferretti, Marco; Chirici, Gherardo

2013-04-01

A correct characterization of the status and trend of forest condition is essential to support reporting processes at national and international level. An international forest condition monitoring has been implemented in Europe since 1987 under the auspices of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The monitoring is based on harmonized methodologies, with individual countries being responsible for its implementation. Due to inconsistencies and problems in sampling design, however, the ICP Forests network is not able to produce reliable quantitative estimates of forest condition at European and sometimes at country level. This paper proposes (1) a set of requirements for status and change assessment and (2) a harmonized sampling strategy able to provide unbiased and consistent estimators of forest condition parameters and of their changes at both country and European level. Under the assumption that a common definition of forest holds among European countries, monitoring objectives, parameters of concern and accuracy indexes are stated. On the basis of fixed-area plot sampling performed independently in each country, an unbiased and consistent estimator of forest defoliation indexes is obtained at both country and European level, together with conservative estimators of their sampling variance and power in the detection of changes. The strategy adopts a probabilistic sampling scheme based on fixed-area plots selected by means of systematic or stratified schemes. Operative guidelines for its application are provided.

Identifying Shifts in Leaf-Litter Ant Assemblages (Hymenoptera: Formicidae) across Ecosystem Boundaries Using Multiple Sampling Methods

PubMed Central

Wiezik, Michal; Svitok, Marek; Wieziková, Adela; Dovčiak, Martin

2015-01-01

Global or regional environmental changes in climate or land use have been increasingly implied in shifts in boundaries (ecotones) between adjacent ecosystems such as beech or oak-dominated forests and forest-steppe ecotones that frequently co-occur near the southern range limits of deciduous forest biome in Europe. Yet, our ability to detect changes in biological communities across these ecosystems, or to understand their environmental drivers, can be hampered when different sampling methods are required to characterize biological communities of the adjacent but ecologically different ecosystems. Ants (Hymenoptera: Formicidae) have been shown to be particularly sensitive to changes in temperature and vegetation and they require different sampling methods in closed vs. open habitats. We compared ant assemblages of closed-forests (beech- or oak-dominated) and open forest-steppe habitats in southwestern Carpathians using methods for closed-forest (litter sifting) and open habitats (pitfall trapping), and developed an integrated sampling approach to characterize changes in ant assemblages across these adjacent ecosystems. Using both methods, we collected 5,328 individual ant workers from 28 species. Neither method represented ant communities completely, but pitfall trapping accounted for more species (24) than litter sifting (16). Although pitfall trapping characterized differences in species richness and composition among the ecosystems better, with beech forest being most species poor and ecotone most species rich, litter sifting was more successful in identifying characteristic litter-dwelling species in oak-dominated forest. The integrated sampling approach using both methods yielded more accurate characterization of species richness and composition, and particularly so in species-rich forest-steppe habitat where the combined sample identified significantly higher number of species compared to either of the two methods on their own. Thus, an integrated sampling approach should be used to fully characterize changes in ant assemblages across ecosystem boundaries, or with vegetation change over time, and particularly so in species-rich habitats such as forest-steppe ecotones. PMID:26226140

Identifying Shifts in Leaf-Litter Ant Assemblages (Hymenoptera: Formicidae) across Ecosystem Boundaries Using Multiple Sampling Methods.

PubMed

Wiezik, Michal; Svitok, Marek; Wieziková, Adela; Dovčiak, Martin

2015-01-01

Global or regional environmental changes in climate or land use have been increasingly implied in shifts in boundaries (ecotones) between adjacent ecosystems such as beech or oak-dominated forests and forest-steppe ecotones that frequently co-occur near the southern range limits of deciduous forest biome in Europe. Yet, our ability to detect changes in biological communities across these ecosystems, or to understand their environmental drivers, can be hampered when different sampling methods are required to characterize biological communities of the adjacent but ecologically different ecosystems. Ants (Hymenoptera: Formicidae) have been shown to be particularly sensitive to changes in temperature and vegetation and they require different sampling methods in closed vs. open habitats. We compared ant assemblages of closed-forests (beech- or oak-dominated) and open forest-steppe habitats in southwestern Carpathians using methods for closed-forest (litter sifting) and open habitats (pitfall trapping), and developed an integrated sampling approach to characterize changes in ant assemblages across these adjacent ecosystems. Using both methods, we collected 5,328 individual ant workers from 28 species. Neither method represented ant communities completely, but pitfall trapping accounted for more species (24) than litter sifting (16). Although pitfall trapping characterized differences in species richness and composition among the ecosystems better, with beech forest being most species poor and ecotone most species rich, litter sifting was more successful in identifying characteristic litter-dwelling species in oak-dominated forest. The integrated sampling approach using both methods yielded more accurate characterization of species richness and composition, and particularly so in species-rich forest-steppe habitat where the combined sample identified significantly higher number of species compared to either of the two methods on their own. Thus, an integrated sampling approach should be used to fully characterize changes in ant assemblages across ecosystem boundaries, or with vegetation change over time, and particularly so in species-rich habitats such as forest-steppe ecotones.

An application of remote sensing data in mapping landscape-level forest biomass for monitoring the effectiveness of forest policies in northeastern China.

PubMed

Wang, Xinchuang; Shao, Guofan; Chen, Hua; Lewis, Bernard J; Qi, Guang; Yu, Dapao; Zhou, Li; Dai, Limin

2013-09-01

Monitoring the dynamics of forest biomass at various spatial scales is important for better understanding the terrestrial carbon cycle as well as improving the effectiveness of forest policies and forest management activities. In this article, field data and Landsat image data acquired in 1999 and 2007 were utilized to quantify spatiotemporal changes of forest biomass for Dongsheng Forestry Farm in Changbai Mountain region of northeastern China. We found that Landsat TM band 4 and Difference Vegetation Index with a 3 × 3 window size were the best predictors associated with forest biomass estimations in the study area. The inverse regression model with Landsat TM band 4 predictor was found to be the best model. The total forest biomass in the study area decreased slightly from 2.77 × 10(6) Mg in 1999 to 2.73 × 10(6) Mg in 2007, which agreed closely with field-based model estimates. The area of forested land increased from 17.9 × 10(3) ha in 1999 to 18.1 × 10(3) ha in 2007. The stabilization of forest biomass and the slight increase of forested land occurred in the period following implementations of national forest policies in China in 1999. The pattern of changes in both forest biomass and biomass density was altered due to different management regimes adopted in light of those policies. This study reveals the usefulness of the remote sensing-based approach for detecting and monitoring quantitative changes in forest biomass at a landscape scale.

Urban forest topographical mapping using UAV LIDAR

NASA Astrophysics Data System (ADS)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

Improving Post-Hurricane Katrina Forest Management with MODIS Time Series Products

NASA Technical Reports Server (NTRS)

Lewis, Mark David; Spruce, Joseph; Evans, David; Anderson, Daniel

2012-01-01

Hurricane damage to forests can be severe, causing millions of dollars of timber damage and loss. To help mitigate loss, state agencies require information on location, intensity, and extent of damaged forests. NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data products offers a potential means for state agencies to monitor hurricane-induced forest damage and recovery across a broad region. In response, a project was conducted to produce and assess 250 meter forest disturbance and recovery maps for areas in southern Mississippi impacted by Hurricane Katrina. The products and capabilities from the project were compiled to aid work of the Mississippi Institute for Forest Inventory (MIFI). A series of NDVI change detection products were computed to assess hurricane induced damage and recovery. Hurricane-induced forest damage maps were derived by computing percent change between MODIS MOD13 16-day composited NDVI pre-hurricane "baseline" products (2003 and 2004) and post-hurricane NDVI products (2005). Recovery products were then computed in which post storm 2006, 2007, 2008 and 2009 NDVI data was each singularly compared to the historical baseline NDVI. All percent NDVI change considered the 16-day composite period of August 29 to September 13 for each year in the study. This provided percent change in the maximum NDVI for the 2 week period just after the hurricane event and for each subsequent anniversary through 2009, resulting in forest disturbance products for 2005 and recovery products for the following 4 years. These disturbance and recovery products were produced for the Mississippi Institute for Forest Inventory's (MIFI) Southeast Inventory District and also for the entire hurricane impact zone. MIFI forest inventory products were used as ground truth information for the project. Each NDVI percent change product was classified into 6 categories of forest disturbance intensity. Stand age and stand type raster data, also provided by MIFI, were used along with the forest disturbance/recovery products to create forest damage stratification products integrating 3 stand type classes, 6 stand age classes, and 6 forest disturbance intensity classes. This stratification product will be used to aid MIFI timber inventory planning and to prepare for damage assessments due to future hurricane events. Validation of MODIS percent NDVI change products was performed by comparing the MODIS percent NDVI change products to those from Landsat data for the same time and MIFI inventory district area.

Uav-Borne Thermal Imaging for Forest Health Monitoring: Detection of Disease-Induced Canopy Temperature Increase

NASA Astrophysics Data System (ADS)

Smigaj, M.; Gaulton, R.; Barr, S. L.; Suárez, J. C.

2015-08-01

Climate change has a major influence on forest health and growth, by indirectly affecting the distribution and abundance of forest pathogens, as well as the severity of tree diseases. Temperature rise and changes in precipitation may also allow the ranges of some species to expand, resulting in the introduction of non-native invasive species, which pose a significant risk to forests worldwide. The detection and robust monitoring of affected forest stands is therefore crucial for allowing management interventions to reduce the spread of infections. This paper investigates the use of a low-cost fixed-wing UAV-borne thermal system for monitoring disease-induced canopy temperature rise. Initially, camera calibration was performed revealing a significant overestimation (by over 1 K) of the temperature readings and a non-uniformity (exceeding 1 K) across the imagery. These effects have been minimised with a two-point calibration technique ensuring the offsets of mean image temperature readings from blackbody temperature did not exceed ± 0.23 K, whilst 95.4% of all the image pixels fell within ± 0.14 K (average) of mean temperature reading. The derived calibration parameters were applied to a test data set of UAV-borne imagery acquired over a Scots pine stand, representing a range of Red Band Needle Blight infection levels. At canopy level, the comparison of tree crown temperature recorded by a UAV-borne infrared camera suggests a small temperature increase related to disease progression (R = 0.527, p = 0.001); indicating that UAV-borne cameras might be able to detect sub-degree temperature differences induced by disease onset.

Effects of wildfire on catchment runoff response: a modeling approach to detect changes in snow-dominated forested catchments

Treesearch

Jan Seibert; Jeffrey J. McDonnell; Richard D. Woodsmith

2010-01-01

Wildfire is an important disturbance affecting hydrological processes through alteration of vegetation cover and soil characteristics. The effects of fire on hydrological systems at the catchment scale are not well known, largely because site specific data from both before and after wildfire are rare. In this study a modelling approach was employed for change detection...

Using soundscapes to detect variable degrees of human influence on tropical forests in Papua New Guinea.

PubMed

Burivalova, Zuzana; Towsey, Michael; Boucher, Tim; Truskinger, Anthony; Apelis, Cosmas; Roe, Paul; Game, Edward T

2018-02-01

There is global concern about tropical forest degradation, in part, because of the associated loss of biodiversity. Communities and indigenous people play a fundamental role in tropical forest management and are often efficient at preventing forest degradation. However, monitoring changes in biodiversity due to degradation, especially at a scale appropriate to local tropical forest management, is plagued by difficulties, including the need for expert training, inconsistencies across observers, and lack of baseline or reference data. We used a new biodiversity remote-sensing technology, the recording of soundscapes, to test whether the acoustic saturation of a tropical forest in Papua New Guinea decreases as land-use intensity by the communities that manage the forest increases. We sampled soundscapes continuously for 24 hours at 34 sites in different land-use zones of 3 communities. Land-use zones where forest cover was fully retained had significantly higher soundscape saturation during peak acoustic activity times (i.e., dawn and dusk chorus) compared with land-use types with fragmented forest cover. We conclude that, in Papua New Guinea, the relatively simple measure of soundscape saturation may provide a cheap, objective, reproducible, and effective tool for monitoring tropical forest deviation from an intact state, particularly if it is used to detect the presence of intact dawn and dusk choruses. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Estimating Unbiased Land Cover Change Areas In The Colombian Amazon Using Landsat Time Series And Statistical Inference Methods

NASA Astrophysics Data System (ADS)

Arevalo, P. A.; Olofsson, P.; Woodcock, C. E.

2017-12-01

Unbiased estimation of the areas of conversion between land categories ("activity data") and their uncertainty is crucial for providing more robust calculations of carbon emissions to the atmosphere, as well as their removals. This is particularly important for the REDD+ mechanism of UNFCCC where an economic compensation is tied to the magnitude and direction of such fluxes. Dense time series of Landsat data and statistical protocols are becoming an integral part of forest monitoring efforts, but there are relatively few studies in the tropics focused on using these methods to advance operational MRV systems (Monitoring, Reporting and Verification). We present the results of a prototype methodology for continuous monitoring and unbiased estimation of activity data that is compliant with the IPCC Approach 3 for representation of land. We used a break detection algorithm (Continuous Change Detection and Classification, CCDC) to fit pixel-level temporal segments to time series of Landsat data in the Colombian Amazon. The segments were classified using a Random Forest classifier to obtain annual maps of land categories between 2001 and 2016. Using these maps, a biannual stratified sampling approach was implemented and unbiased stratified estimators constructed to calculate area estimates with confidence intervals for each of the stable and change classes. Our results provide evidence of a decrease in primary forest as a result of conversion to pastures, as well as increase in secondary forest as pastures are abandoned and the forest allowed to regenerate. Estimating areas of other land transitions proved challenging because of their very small mapped areas compared to stable classes like forest, which corresponds to almost 90% of the study area. Implications on remote sensing data processing, sample allocation and uncertainty reduction are also discussed.

Landscape Change Detected Over A 60 Year Period In The Arctic National Wildlife Refuge, Alaska, Using High Resolution Aerial Photographs And Satellite Images

NASA Astrophysics Data System (ADS)

Jorgenson, J. C.; Jorgenson, M. T.; Boldenow, M.; Orndahl, K. M.

2016-12-01

We documented landscape change over a 60 year period in the Arctic National Wildlife Refuge in northeastern Alaska using aerial photographs and satellite images. We used a stratified random sample to allow inference to the whole refuge (78,050 km2), with five random sites in each of seven ecoregions. Each site (2 km2) had a systematic grid of 100 points for a total of 3500 points. We chose study sites in the overlap area covered by acceptable imagery in three time periods: aerial photographs from 1947 - 1955 and 1978 - 1988, Quick Bird and IKONOS satellite images from 2000 - 2007.At each point a 10 meter radius circle was visually evaluated in ARC-MAP for each time period for vegetation type, disturbance, presence of ice wedge polygon microtopography and surface water. A landscape change category was assigned to each point based on differences detected between the three periods. Change types were assigned for time interval 1, interval 2 and overall. Additional explanatory variables included elevation, slope, aspect, geology, physiography and temperature. Overall, 23% of points changed over the study period. Fire was the most common change agent, affecting 28% of the Boreal Forest points. The next most common change was degradation of soil ice wedges (thermokarst), detected at 12% of the points on the North Slope Tundra. The other most common changes included increase in cover of trees or shrubs (7% of Boreal Forest and Brooks Range points) and erosion or deposition on river floodplains and at the Beaufort Sea coast. Changes on the North Slope Tundra tended to be related to landscape wetting, mainly thermokarst. Changes in the Boreal Forest tended to involve landscape drying, including fire, reduced area of lakes and tree increase on wet sites. The second time interval coincided with a shift towards a warmer climate and had greater change in several categories including thermokarst, lake changes and tree and shrub increase.

Archaeal communities in boreal forest tree rhizospheres respond to changing soil temperatures.

PubMed

Bomberg, Malin; Münster, Uwe; Pumpanen, Jukka; Ilvesniemi, Hannu; Heinonsalo, Jussi

2011-07-01

Temperature has generally great effects on both the activity and composition of microbial communities in different soils. We tested the impact of soil temperature and three different boreal forest tree species on the archaeal populations in the bulk soil, rhizosphere, and mycorrhizosphere. Scots pine, silver birch, and Norway spruce seedlings were grown in forest humus microcosms at three different temperatures, 7-11.5°C (night-day temperature), 12-16°C, and 16-22°C, of which 12-16°C represents the typical mid-summer soil temperature in Finnish forests. RNA and DNA were extracted from indigenous ectomycorrhiza, non-mycorrhizal long roots, and boreal forest humus and tested for the presence of archaea by nested PCR of the archaeal 16S rRNA gene followed by denaturing gradient gel electrophoresis (DGGE) profiling and sequencing. Methanogenic Euryarchaeota belonging to Methanolobus sp. and Methanosaeta sp. were detected on the roots and mycorrhiza. The most commonly detected archaeal 16S rRNA gene sequences belonged to group I.1c Crenarchaeota, which are typically found in boreal and alpine forest soils. Interestingly, also one sequence belonging to group I.1b Crenarchaeota was detected from Scots pine mycorrhiza although sequences of this group are usually found in agricultural and forest soils in temperate areas. Tree- and temperature-related shifts in the archaeal population structure were observed. A clear decrease in crenarchaeotal DGGE band number was seen with increasing temperature, and correspondingly, the number of euryarchaeotal DGGE bands, mostly methanogens, increased. The greatest diversity of archaeal DGGE bands was detected in Scots pine roots and mycorrhizas. No archaea were detected from humus samples from microcosms without tree seedling, indicating that the archaea found in the mycorrhizosphere and root systems were dependent on the plant host. The detection of archaeal 16S rRNA gene sequences from both RNA and DNA extractions show that the archaeal populations were living and that they may have significant contribution to the methane cycle in boreal forest soil, especially when soil temperatures rise.

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, Gerald; Smoot, James; Kuper, Philip D.

2012-01-01

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Evaluating differences in forest fragmentation and restoration between western natural forests and southeastern plantation forests in the United States.

PubMed

Ren, Xinyu; Lv, Yingying; Li, Mingshi

2017-03-01

Changes in forest ecosystem structure and functions are considered some of the research issues in landscape ecology. In this study, advancing Forman's theory, we considered five spatially explicit processes associated with fragmentation, including perforation, dissection, subdivision, shrinkage, and attrition, and two processes associated with restoration, i.e., increment and expansion processes. Following this theory, a forest fragmentation and restoration process model that can detect the spatially explicit processes and ecological consequences of forest landscape change was developed and tested in the current analysis. Using the National Land Cover Databases (2001, 2006 and 2011), the forest fragmentation and restoration process model was applied to US western natural forests and southeastern plantation forests to quantify and classify forest patch losses into one of the four fragmentation processes (the dissection process was merged into the subdivision process) and to classify the newly gained forest patches based on the two restoration processes. At the same time, the spatio-temporal differences in fragmentation and restoration patterns and trends between natural forests and plantations were further compared. Then, through overlaying the forest fragmentation/restoration processes maps with targeting year land cover data and land ownership vectors, the results from forest fragmentation and the contributors to forest restoration in federal and nonfederal lands were identified. Results showed that, in natural forests, the forest change patches concentrated around the urban/forest, cultivated/forest, and shrubland/forest interfaces, while the patterns of plantation change patches were scattered sparsely and irregularly. The shrinkage process was the most common type in forest fragmentation, and the average size was the smallest. Expansion, the most common restoration process, was observed in both natural forests and plantations and often occurred around the previous expansion or covered the previous subdivision or shrinkage processes. The overall temporal fragmentation pattern of natural forests had a "perforation-subdivision/shrinkage-attrition" pathway, which corresponded to Forman's landscape fragmentation rule, while the plantation forests did not follow the rule strictly. The main land cover types resulted from forest fragmentation in natural forests and plantation forests were shrubland and herbaceous, mainly through subdivision and shrinkages process. The processes and effects of restoration of plantation forests were more diverse and efficient, compared to the natural forest, which were simpler with a lower regrowth rate. The fragmentation mostly occurred in nonfederal lands. In natural forests, forest fragmentation pattern differed in different land tenures, yet plantations remained the same in federal and nonfederal lands. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Project to Map and Monitor Baldcypress Forests in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Sader, Steven; Smoot, James

2012-01-01

Cypress swamp forests of Louisiana offer many important ecological and economic benefits: wildlife habitat, forest products, storm buffers, water quality, and recreation. Such forests are also threatened by multiple factors: subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, hurricanes, insect and nutria damage, timber harvesting, and land use conversion. Unfortunately, there are many information gaps regarding the type, location, extent, and condition of these forests. Better more up to date swamp forest mapping products are needed to aid coastal forest conservation and restoration work (e.g., through the Coastal Forest Conservation Initiative or CFCI). In response, a collaborative project was initiated to develop, test and demonstrate cypress swamp forest mapping products, using NASA supported Landsat, ASTER, and MODIS satellite data. Research Objectives are: Develop, test, and demonstrate use of Landsat and ASTER data for computing new cypress forest classification products and Landsat, ASTER, and MODIS satellite data for detecting and monitoring swamp forest change

Toward a National Early Warning System for Forest Disturbances Using Remotely Sensed Canopy Phenology

DOE Office of Scientific and Technical Information (OSTI.GOV)

HargroveJr., William Walter; Spruce, Joe; Gasser, Gerry

2009-01-01

Imagine a national system with the ability to quickly identify forested areas under attack from insects or disease. Such an early warning system might minimize surprises such as the explosion of caterpillars referred to in the quotation to the left. Moderate resolution (ca. 500m) remote sensing repeated at frequent (ca. weekly) intervals could power such a monitoring system that would respond in near real-time. An ideal warning system would be national in scope, automated, able to improve its prognostic ability with experience, and would provide regular map updates online in familiar and accessible formats. Such a goal is quite ambitiousmore » - analyzing vegetation change weekly at a national scale with moderate resolution is a daunting task. The foremost challenge is discerning unusual or unexpected disturbances from the normal backdrop of seasonal and annual changes in vegetation conditions. A historical perspective is needed to define a 'baseline' for expected, normal behavior against which detected changes can be correctly interpreted. It would be necessary to combine temperature, precipitation, soils, and topographic information with the remotely sensed data to discriminate and interpret the changing vegetation conditions on the ground. Conterminous national coverage implies huge data volumes, even at a moderate resolution (250-500m), and likely requires a supercomputing capability. Finally, such a national warning system must carefully balance the rate of successful threat detection with false positives. Since 2005, the USDA Forest Service has partnered with the NASA Stennis Space Center and Oak Ridge National Laboratory to develop methods for monitoring environmental threats, including native insects and diseases, wildfire, invasive pests and pathogens, tornados, hurricanes, and hail. These tools will be instrumental in helping the Forest Service's two Environmental Threat Assessment Centers better meet their Congressional mandate to help track the health of the Nation's forests and rangelands. We envision two scales of forest monitoring: (1) a strategic, satellite-based monitoring of broad regions to identify particular locations where threats are suspected (i.e., early warning), and (2) a fine-scale, tactical tier consisting of airborne overflights and on-the-ground monitoring to check the validity of warnings from the upper tier. The tactical tier is already largely in place within the Forest Service and its State collaborators, consisting of aerial detection surveys (sketch mapping from aircraft), ground surveys, and trapping programs. However, these efforts are expensive and labor-intensive, can be dangerous, and may not provide sufficient broad-area coverage. Far from replacing the tactical tier, the national system will rely on the finer-scale efforts to confirm, validate, and attribute causes of detected forest disturbances. One important objective of the national warning system will be to help direct the focus of the tactical tier, making their efforts more cost efficient and effective.« less

How much will afforestation of former cropland influence soil C stocks? A synthesis of paired sampling, chronosequence sampling and repeated sampling studies

NASA Astrophysics Data System (ADS)

Vesterdal, Lars; Hansen, K.; Stupak, I.; Don, Axel; Poeplau, C.; Leifeld, Jens; van Wesemael, Bas

2010-05-01

The need for documentation of land-use change effects on soil C is high on the agenda in most signatory countries to the Kyoto Protocol. Large land areas in Europe have experienced land-use change from cropland to forest since 1990 by direct afforestation as well as abandonment and regrowth of marginally productive cropland. Soil C dynamics following land-use change remain highly uncertain due to a limited number of available studies and due to influence of interacting factors such as land use history, soil type, and climate. Common approaches for estimation of potential soil C changes following land-use change are i) paired sampling of plots with a long legacy of different land uses, ii) chronosequence studies of land-use change, and lastly iii) repeated sampling of plots subject to changed land use. This paper will synthesize the quantitative effects of cropland afforestation on soil C sequestration based on all three approaches and will report on related work within Cost 639. Paired plots of forest and cropland were used to study the general differences between soil C stocks in the two land uses. At 27 sites in Denmark distributed among different regions and soil types forest floor and mineral soil were sampled in and around soil pits. Soil C stocks were higher in forest than cropland (mean difference 22 Mg C ha-1 to 1 m depth). This difference was caused solely by the presence of a forest floor in forests; mineral soil C stocks were similar (108 vs. 109 Mg C ha-1) in the two land uses regardless of soil type and the soil layers considered. The chronosequence approach was employed in the AFFOREST project for evaluation of C sequestration in biomass and soils following afforestation of cropland. Two oak (Quercus robur) and four Norway spruce (Picea abies) afforestation chronosequences (age range 1 to 90 years) were studied in Denmark, Sweden and the Netherlands. Forest floor and mineral soil (0-25 cm) C contents were as a minimum unchanged and in most cases there was net C sequestration (range 0-1.3 Mg C ha-1 yr-1). The allocation of sequestered soil C was quite different among chronosequences; forest floors consistently sequestered C (0.1-0.7 Mg C ha-1 yr-1) but there was no general pattern in mineral soil C sequestration. While the paired sampling and the chronosequence approaches both may be confounded by site factors other than the land use, repeated sampling of plots best addresses the pure land-use change effect. Repeated sampling after 18 years was done in a systematic 7x7 km grid to address soil C changes in 15 cropland plots that were converted to forest (7-22 years since afforestation). Consistent with the other two approaches, detectable soil C changes were confined to the forest floor component; forest floor C sequestration rates were 0.24 Mg C ha-1 yr-1 while no changes were detected for mineral soils. The three approaches to estimation of soil C sequestration indeed point to a common conclusion: The potential for soil C sequestration is mainly confined to the forest floor whereas notable C sequestration is less likely to occur in the mineral soil. However, more generalizable knowledge is badly needed for reporting of land-use change effects on mineral soil C pools. WG II of Cost 639 and the FP7 project GHG Europe is currently establishing a database of LUC studies. This database will be used to establish so-called Carbon Response Functions (CRF), i.e. simple models predicting the annual rate of change in soil C pools. These CRFs may serve as tools for syntheses of land-use change effects for Europe as well as for improved reporting of soil C dynamics following land-use change.

Spatiotemporal variation of mosquito diversity (Diptera: Culicidae) at places with different land-use types within a neotropical montane cloud forest matrix.

PubMed

Abella-Medrano, Carlos Antonio; Ibáñez-Bernal, Sergio; MacGregor-Fors, Ian; Santiago-Alarcon, Diego

2015-09-24

Land-use change has led to a dramatic decrease in total forest cover, contributing to biodiversity loss and changes of ecosystems' functions. Insect communities of medical importance can be favored by anthropogenic alterations, increasing the risk of novel zoonotic diseases. The response of mosquito (Diptera: Culicidae) abundance and richness to five land-use types (shade coffee plantation, cattle field, urban forest, peri-urban forest, well-preserved montane cloud forest) and three seasons ("dry", "rainy" and "cold") embedded in a neotropical montane cloud forest landscape was evaluated. Standardized collections were performed using 8 CDC miniature black-light traps, baited with CO2 throughout the year. Generalized additive mixed models were used to describe the seasonal and spatial trends of both species richness and abundance. Rank abundance curves and ANCOVAs were used to detect changes in the spatial and temporal structure of the mosquito assemblage. Two cluster analyses were conducted, using 1-βsim and the Morisita-Horn index to evaluate species composition shifts based on incidences and abundances. A total of 2536 adult mosquitoes were collected, belonging to 9 genera and 10 species; the dominant species in the study were: Aedes quadrivittatus, Wyeomyia adelpha, Wy. arthrostigma, and Culex restuans. Highest richness was recorded in the dry season, whereas higher abundance was detected during the rainy season. The urban forest had the highest species richness (n = 7) when compared to all other sites. Species composition cluster analyses show that there is a high degree of similarity in species numbers across sites and seasons throughout the year. However, when considering the abundance of such species, the well-preserved montane cloud forest showed significantly higher abundance. Moreover, the urban forest is only 30 % similar to other sites in terms of species abundances, indicating a possible isolating role of the urban environment. Mosquito assemblage was differentially influenced by land-use change and seasonality, but at the same time the assemblage is rather homogeneous across the studied landscape, suggesting a high degree of spatial connectivity. Information generated in this study is potentially useful in the development of urban planning and surveillance programs focused mainly on mosquito species of medical and veterinary importance.

Photoprotection related to xanthophyll cycle pigments in epiphytic orchids acclimated at different light microenvironments in two tropical dry forests of the Yucatan Peninsula, Mexico.

PubMed

de la Rosa-Manzano, Edilia; Andrade, José Luis; García-Mendoza, Ernesto; Zotz, Gerhard; Reyes-García, Casandra

2015-12-01

Epiphytic orchids from dry forests of Yucatán show considerable photoprotective plasticity during the dry season, which depends on leaf morphology and host tree deciduousness. Nocturnal retention of antheraxanthin and zeaxanthin was detected for the first time in epiphytic orchids. In tropical dry forests, epiphytes experience dramatic changes in light intensity: photosynthetic photon flux density may be up to an order of magnitude higher in the dry season compared to the wet season. To address the seasonal changes of xanthophyll cycle (XC) pigments and photosynthesis that occur throughout the year, leaves of five epiphytic orchid species were studied during the early dry, dry and wet seasons in a deciduous and a semi-deciduous tropical forests at two vertical strata on the host trees (3.5 and 1.5 m height). Differences in XC pigment concentrations and photosynthesis (maximum quantum efficiency of photosystem II; F v/F m) were larger among seasons than between vertical strata in both forests. Antheraxanthin and zeaxanthin retention reflected the stressful conditions of the epiphytic microhabitat, and it is described here in epiphytes for the first time. During the dry season, both XC pigment concentrations and photosystem II heat dissipation of absorbed energy increased in orchids in the deciduous forest, while F v/F m and nocturnal acidification (ΔH(+)) decreased, clearly as a response to excessive light and drought. Concentrations of XC pigments were higher than those in orchids with similar leaf shape in semi-deciduous forest. There, only Encyclia nematocaulon and Lophiaris oerstedii showed somewhat reduced F v/F m. No changes in ΔH(+) and F v/F m were detected in Cohniella ascendens throughout the year. This species, which commonly grows in forests with less open canopies, showed leaf tilting that diminished light interception. Light conditions in the uppermost parts of the canopy probably limit the distribution of epiphytic orchids and the retention of zeaxanthin can help to cope with light and drought stress in these forests during the dry season.

Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon

USGS Publications Warehouse

Burns, W.J.; Coe, J.A.; Kaya, B.S.; Ma, Liwang

2010-01-01

We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.

Challenges and approaches to projecting changes in forest distributions in complex mountain landscape

NASA Astrophysics Data System (ADS)

Kueppers, L. M.; Molotch, N. P.; Meromy, L.; Moyes, A. B.; Conlisk, E.; Castanha, C.

2015-12-01

The extent and density of forest trees in mountain landscapes is a first order control on watershed function, affecting patterns of snow accumulation, timing of snowmelt, and amount and quality of run-off, through alterations of surface energy and water fluxes and wind. Climate change is increasingly affecting the density and distribution of mature forests through changes to disturbance regimes, increases in physiological stress and increases in mortality due to warmer temperatures. In addition, climate change is likely altering patterns of regeneration and driving establishment of trees in high elevation meadows and alpine tundra. Though hard to detect in current forestry datasets, changes in tree establishment are critical to the future of forests. Experimental approaches, such as our climate warming experiment in the Colorado Front Range, can provide valuable data regarding seedling sensitivity to climate variability and change across important landscape positions. We've found that warming enhances negative effects of water stress across forest, treeline and alpine sites, reducing recruitment in the absence of additional summer moisture. At the lowest elevation, reductions with warming have reduced Engelmann spruce recruitment to zero. Species differ in their responses to warming in the alpine, but together confirm the importance of seed dispersal to upward forest shifts. The presence of trees or other vegetation can facilitate tree establishment by modifying microclimates, especially at and above treeline. Ultimately, these ecological and demographic processes govern the timescales of tree and forest responses to climate variability and change. For the long-lived species that dominate high elevation watersheds, these processes can take decades or centuries to play out, meaning many tree populations are and will continue to be out of equilibrium with a rapidly changing climate. Projecting changes in tree distributions and abundances across mountain landscapes requires integration of changes in hydroclimatic conditions across diverse topoclimatic settings; the sensitivity of recruitment, growth and mortality to climate; and feedbacks between trees and microclimate into modeling tools that represent time-explicit ecological and demographic processes.

Forest loss in New England: A projection of recent trends

PubMed Central

Thompson, Jonathan R.; Plisinski, Joshua S.; Olofsson, Pontus; Holden, Christopher E.; Duveneck, Matthew J.

2017-01-01

New England has lost more than 350,000 ha of forest cover since 1985, marking a reversal of a two-hundred-year trend of forest expansion. We a cellular land-cover change model to project a continuation of recent trends (1990–2010) in forest loss across six New England states from 2010 to 2060. Recent trends were estimated using a continuous change detection algorithm applied to twenty years of Landsat images. We addressed three questions: (1) What would be the consequences of a continuation of the recent trends in terms of changes to New England's forest cover mosaic? (2) What social and biophysical attributes are most strongly associated with recent trends in forest loss, and how do these vary geographically? (3) How sensitive are projections of forest loss to the reference period—i.e. how do projections based on the period spanning 1990-to-2000 differ from 2000-to-2010, or from the full period, 1990-to-2010? Over the full reference period, 8201 ha yr-1 and 468 ha yr-1 of forest were lost to low- and high-density development, respectively. Forest loss was concentrated in suburban areas, particularly near Boston. Of the variables considered, 'distance to developed land' was the strongest predictor of forest loss. The next most important predictor varied geographically: 'distance to roads' ranked second in the more developed regions in the south and 'population density' ranked second in the less developed north. The importance and geographical variation in predictor variables were relatively stable between reference periods. In contrast, there was 55% more forest loss during the 1990-to-2000 reference period compared to the 2000-to-2010 period, highlighting the importance of understanding the variation in reference periods when projecting land cover change. The projection of recent trends is an important baseline scenario with implications for the management of forest ecosystems and the services they provide. PMID:29240810

Forest loss in New England: A projection of recent trends.

PubMed

Thompson, Jonathan R; Plisinski, Joshua S; Olofsson, Pontus; Holden, Christopher E; Duveneck, Matthew J

2017-01-01

New England has lost more than 350,000 ha of forest cover since 1985, marking a reversal of a two-hundred-year trend of forest expansion. We a cellular land-cover change model to project a continuation of recent trends (1990-2010) in forest loss across six New England states from 2010 to 2060. Recent trends were estimated using a continuous change detection algorithm applied to twenty years of Landsat images. We addressed three questions: (1) What would be the consequences of a continuation of the recent trends in terms of changes to New England's forest cover mosaic? (2) What social and biophysical attributes are most strongly associated with recent trends in forest loss, and how do these vary geographically? (3) How sensitive are projections of forest loss to the reference period-i.e. how do projections based on the period spanning 1990-to-2000 differ from 2000-to-2010, or from the full period, 1990-to-2010? Over the full reference period, 8201 ha yr-1 and 468 ha yr-1 of forest were lost to low- and high-density development, respectively. Forest loss was concentrated in suburban areas, particularly near Boston. Of the variables considered, 'distance to developed land' was the strongest predictor of forest loss. The next most important predictor varied geographically: 'distance to roads' ranked second in the more developed regions in the south and 'population density' ranked second in the less developed north. The importance and geographical variation in predictor variables were relatively stable between reference periods. In contrast, there was 55% more forest loss during the 1990-to-2000 reference period compared to the 2000-to-2010 period, highlighting the importance of understanding the variation in reference periods when projecting land cover change. The projection of recent trends is an important baseline scenario with implications for the management of forest ecosystems and the services they provide.

Detection and Distribution of Natural Gaps in Tropical Rainforest

NASA Astrophysics Data System (ADS)

Goulamoussène, Y.; Linguet, L.; Hérault, B.

2014-12-01

Forest management is important to assess biodiversity and ecological processes. Requirements for disturbance information have also been motivated by the scientific community. Therefore, understanding and monitoring the distribution frequencies of treefall gaps is relevant to better understanding and predicting the carbon budget in response to global change and land use change. In this work we characterize and quantify the frequency distribution of natural canopy gaps. We observe then interaction between environment variables and gap formation across tropical rainforest of the French Guiana region by using high resolution airborne Light Detection and Ranging (LiDAR). We mapped gaps with canopy model distribution on 40000 ha of forest. We used a Bayesian modelling framework to estimate and select useful covariate model parameters. Topographic variables are included in a model to predict gap size distribution. We discuss results from the interaction between environment and gap size distribution, mainly topographic indexes. The use of both airborne and space-based techniques has improved our ability to supply needed disturbance information. This work is an approach at plot scale. The use of satellite data will allow us to work at forest scale. The inclusion of climate variables in our model will let us assess the impact of global change on tropical rainforest.

Detecting changes in tree health and productivity in silver fir-beech forests of Slovenia

Treesearch

N. Torelli; W.C. Shortle; K. Cufar; F. Ferlin; K.T. Smith

1999-01-01

Cambial electrical resistance (CER) was used as an objective measure of vitality of silver fir (Abies alba) in the forests of Slovenia. Trees were rated during the growing season by CER and a subjective crown status index (CSI). Both CER and CSI were inversely correlated to annual ring width increment. Using both CER and CSI, fir were assigned to...

Examining change detection approaches for tropical mangrove monitoring

USGS Publications Warehouse

Myint, Soe W.; Franklin, Janet; Buenemann, Michaela; Kim, Won; Giri, Chandra

2014-01-01

This study evaluated the effectiveness of different band combinations and classifiers (unsupervised, supervised, object-oriented nearest neighbor, and object-oriented decision rule) for quantifying mangrove forest change using multitemporal Landsat data. A discriminant analysis using spectra of different vegetation types determined that bands 2 (0.52 to 0.6 μm), 5 (1.55 to 1.75 μm), and 7 (2.08 to 2.35 μm) were the most effective bands for differentiating mangrove forests from surrounding land cover types. A ranking of thirty-six change maps, produced by comparing the classification accuracy of twelve change detection approaches, was used. The object-based Nearest Neighbor classifier produced the highest mean overall accuracy (84 percent) regardless of band combinations. The automated decision rule-based approach (mean overall accuracy of 88 percent) as well as a composite of bands 2, 5, and 7 used with the unsupervised classifier and the same composite or all band difference with the object-oriented Nearest Neighbor classifier were the most effective approaches.

Spatially quantifying and attributing 17 years of land cover change to examine post-agricultural forest transition in Hawai`i

NASA Astrophysics Data System (ADS)

Lucas, M.; Trauernicht, C.; Carlson, K. M.; Miura, T.; Giambelluca, T. W.; Chen, Q.

2017-12-01

The past decades in Hawaii have seen large scale land use change and land cover shifts. However, much these dynamics are only described anecdotally or studied at a single locale, with little information on the extent, rate, or direction of change. This lack of data hinders any effort to assess, plan, and prioritize land management. To improve assessments of statewide vegetation and land cover change, this project developed high resolution, sub-pixel, percent cover maps of forest, grassland and bare earth at annual time steps from 1999 to 2016. Vegetation cover was quantified using archived LANDSAT imagery and a custom remote-sensing algorithm developed in the Google Earth Engine platform. A statistical trend analysis of annual maps of the these three proportional land covers were then used to detect land cover transitions across the archipelago. The aim of this work focused on quantifying the total area of change, annual rates of change and final vegetation cover outcomes statewide. Additionally these findings were attributed to past and current land uses and management history by compiling spatial datasets of development, agriculture, forest restoration sites and burned areas statewide. Results indicated that nearly 10% of the state's land surfaces are suspected to have transitioned between the three cover classes during the study period. Total statewide net change resulted in a gain in forest cover with largest areas of change occurring in unmanaged areas, current and past pastoral land, commercial forestry and abandoned cultivated land. The fastest annual rates of change were forest increases that occurred in restoration areas and commercial forestry. These findings indicate that Hawaii is going through a forest transition, primarily driven by agricultural abandonment with likely feedbacks from invasive species, but also influenced by the establishment of forestry production on former agricultural lands that show potential for native forest restoration. These results directly link land management history to land cover outcomes using an innovative approach to quantify change. It is also the first study to quantify forest transition dynamics in Hawaii and points to the need for similar assessments in post-agricultural landscapes on other oceanic islands.

Landscape genetic structure of coastal tailed frogs (Ascaphus truei) in protected vs. managed forests.

PubMed

Spear, Stephen F; Storfer, Andrew

2008-11-01

Habitat loss and fragmentation are the leading causes of species' declines and extinctions. A key component of studying population response to habitat alteration is to understand how fragmentation affects population connectivity in disturbed landscapes. We used landscape genetic analyses to determine how habitat fragmentation due to timber harvest affects genetic population connectivity of the coastal tailed frog (Ascaphus truei), a forest-dwelling, stream-breeding amphibian. We compared rates of gene flow across old-growth (Olympic National Park) and logged landscapes (Olympic National Forest) and used spatial autoregression to estimate the effect of landscape variables on genetic structure. We detected higher overall genetic connectivity across the managed forest, although this was likely a historical signature of continuous forest before timber harvest began. Gene flow also occurred terrestrially, as connectivity was high across unconnected river basins. Autoregressive models demonstrated that closed forest and low solar radiation were correlated with increased gene flow. In addition, there was evidence for a temporal lag in the correlation of decreased gene flow with harvest, suggesting that the full genetic impact may not appear for several generations. Furthermore, we detected genetic evidence of population bottlenecks across the Olympic National Forest, including at sites that were within old-growth forest but surrounded by harvested patches. Collectively, this research suggests that absence of forest (whether due to natural or anthropogenic changes) is a key restrictor of genetic connectivity and that intact forested patches in the surrounding environment are necessary for continued gene flow and population connectivity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patrick Gonzalez; Antonio Lara; Jorge Gayoso

Deforestation of temperate rainforests in Chile has decreased the provision of ecosystem services, including watershed protection, biodiversity conservation, and carbon sequestration. Forest conservation can restore those ecosystem services. Greenhouse gas policies that offer financing for the carbon emissions avoided by preventing deforestation require a projection of future baseline carbon emissions for an area if no forest conservation occurs. For a proposed 570 km{sup 2} conservation area in temperate rainforest around the rural community of Curinanco, Chile, we compared three methods to project future baseline carbon emissions: extrapolation from Landsat observations, Geomod, and Forest Restoration Carbon Analysis (FRCA). Analyses of forestmore » inventory and Landsat remote sensing data show 1986-1999 net deforestation of 1900 ha in the analysis area, proceeding at a rate of 0.0003 y{sup -1}. The gross rate of loss of closed natural forest was 0.042 y{sup -1}. In the period 1986-1999, closed natural forest decreased from 20,000 ha to 11,000 ha, with timber companies clearing natural forest to establish plantations of non-native species. Analyses of previous field measurements of species-specific forest biomass, tree allometry, and the carbon content of vegetation show that the dominant native forest type, broadleaf evergreen (bosque siempreverde), contains 370 {+-} 170 t ha{sup -1} carbon, compared to the carbon density of non-native Pinus radiata plantations of 240 {+-} 60 t ha{sup -1}. The 1986-1999 conversion of closed broadleaf evergreen forest to open broadleaf evergreen forest, Pinus radiata plantations, shrublands, grasslands, urban areas, and bare ground decreased the carbon density from 370 {+-} 170 t ha{sup -1} carbon to an average of 100 t ha{sup -1} (maximum 160 t ha{sup -1}, minimum 50 t ha{sup -1}). Consequently, the conversion released 1.1 million t carbon. These analyses of forest inventory and Landsat remote sensing data provided the data to evaluate the three methods to project future baseline carbon emissions. Extrapolation from Landsat change detection uses the observed rate of change to estimate change in the near future. Geomod is a software program that models the geographic distribution of change using a defined rate of change. FRCA is an integrated spatial analysis of forest inventory, biodiversity, and remote sensing that produces estimates of forest biodiversity and forest carbon density, spatial data layers of future probabilities of reforestation and deforestation, and a projection of future baseline forest carbon sequestration and emissions for an ecologically-defined area of analysis. For the period 1999-2012, extrapolation from Landsat change detection estimated a loss of 5000 ha and 520,000 t carbon from closed natural forest; Geomod modeled a loss of 2500 ha and 250 000 t; FRCA projected a loss of 4700 {+-} 100 ha and 480,000 t (maximum 760,000 t, minimum 220,000 t). Concerning labor time, extrapolation for Landsat required 90 actual days or 120 days normalized to Bachelor degree level wages; Geomod required 240 actual days or 310 normalized days; FRCA required 110 actual days or 170 normalized days. Users experienced difficulties with an MS-DOS version of Geomod before turning to the Idrisi version. For organizations with limited time and financing, extrapolation from Landsat change provides a cost-effective method. Organizations with more time and financing could use FRCA, the only method where that calculates the deforestation rate as a dependent variable rather than assuming a deforestation rate as an independent variable. This research indicates that best practices for the projection of baseline carbon emissions include integration of forest inventory and remote sensing tasks from the beginning of the analysis, definition of an analysis area using ecological characteristics, use of standard and widely used geographic information systems (GIS) software applications, and the use of species-specific allometric equations and wood densities developed for local species.« less

Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA

USGS Publications Warehouse

Soulard, Christopher E.; Walker, Jessica; Griffith, Glenn E.

2017-01-01

Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the Cascade Mountains, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras of logging trends that align with prevailing regulations and economic conditions. We used multiple logistic regression to determine the biophysical and anthropogenic factors that influence fine-scale selection of harvest stands in each time period. Results show that private lands forest cover became significantly reduced and more fragmented from 1985 to 2014. Variables linked to parameters of site conditions, location, climate, and vegetation greenness consistently distinguished harvest selection for each distinct era. This study demonstrates the utility of annual LULC data for investigating the underlying factors that influence land cover change.

Land use change monitoring in Maryland using a probabilistic sample and rapid photointerpretation

Treesearch

Tonya Lister; Andrew Lister; Eunice Alexander

2014-01-01

The U.S. state of Maryland needs to monitor land use change in order to address land management objectives. This paper presents a change detection method that, through automation and standard geographic information system (GIS) techniques, facilitates the estimation of landscape change via photointerpretation. Using the protocols developed, we show a net loss of forest...

Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia

NASA Astrophysics Data System (ADS)

Dutrieux, Loïc Paul; Verbesselt, Jan; Kooistra, Lammert; Herold, Martin

2015-09-01

Automatically detecting forest disturbances as they occur can be extremely challenging for certain types of environments, particularly those presenting strong natural variations. Here, we use a generic structural break detection framework (BFAST) to improve the monitoring of forest cover loss by combining multiple data streams. Forest change monitoring is performed using Landsat data in combination with MODIS or rainfall data to further improve the modelling and monitoring. We tested the use of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) with varying spatial aggregation window sizes as well as a rainfall derived index as external regressors. The method was evaluated on a dry tropical forest area in lowland Bolivia where forest cover loss is known to occur, and we validated the results against a set of ground truth samples manually interpreted using the TimeSync environment. We found that the addition of an external regressor allows to take advantage of the difference in spatial extent between human induced and naturally induced variations and only detect the processes of interest. Of all configurations, we found the 13 by 13 km MODIS NDVI window to be the most successful, with an overall accuracy of 87%. Compared with a single pixel approach, the proposed method produced better time-series model fits resulting in increases of overall accuracy (from 82% to 87%), and decrease in omission and commission errors (from 33% to 24% and from 3% to 0% respectively). The presented approach seems particularly relevant for areas with high inter-annual natural variability, such as forests regularly experiencing exceptional drought events.

Effects of local land-use on riparian vegetation, water quality, and the functional organization of macroinvertebrate assemblages.

PubMed

Fierro, Pablo; Bertrán, Carlos; Tapia, Jaime; Hauenstein, Enrique; Peña-Cortés, Fernando; Vergara, Carolina; Cerna, Cindy; Vargas-Chacoff, Luis

2017-12-31

Land-use change is a principal factor affecting riparian vegetation and river biodiversity. In Chile, land-use change has drastically intensified over the last decade, with native forests converted to exotic forest plantations and agricultural land. However, the effects thereof on aquatic ecosystems are not well understood. Closing this knowledge gap first requires understanding how human perturbations affect riparian and stream biota. Identified biological indicators could then be applied to determine the health of fluvial ecosystems. Therefore, this study investigated the effects of land-use change on the health of riparian and aquatic ecosystems by assessing riparian vegetation, water quality, benthic macroinvertebrate assemblages, and functional feeding groups. Twenty-one sites in catchment areas with different land-uses (i.e. pristine forests, native forests, exotic forest plantations, and agricultural land) were selected and sampled during the 2010 to 2012 dry seasons. Riparian vegetation quality was highest in pristine forests. Per the modified Macroinvertebrate Family Biotic Index for Chilean species, the best conditions existed in native forests and the worst in agricultural catchments. Water quality and macroinvertebrate assemblages significantly varied across land-use areas, with forest plantations and agricultural land having high nutrient concentrations, conductivity, suspended solids, and apparent color. Macroinvertebrate assemblage diversity was lowest for agricultural and exotic forest plantation catchments, with notable non-insect representation. Collector-gatherers were the most abundant functional feeding group, suggesting importance independent of land-use. Land-use areas showed no significant differences in functional feeding groups. In conclusion, anthropogenic land-use changes were detectable through riparian quality, water quality, and macroinvertebrate assemblages, but not through functional feeding groups. These data, particularly the riparian vegetation and macroinvertebrate assemblage parameters, could be applied towards the conservation and management of riparian ecosystems through land-use change studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Monitoring the Mesoamerican Biological Corridor: A NASA/CCAD Cooperative Research Project

NASA Technical Reports Server (NTRS)

Sever, Thomas; Irwin, Daniel; Sader, Steven A.; Saatchi, Sassan

2004-01-01

To foster scientific cooperation under a Memorandum of Understanding between NASA and the Central American countries, the research project developed regional databases to monitor forest condition and environmental change throughout the region. Of particular interest is the Mesoamerican Biological Corridor (MBC), a chain of protected areas and proposed conservation areas that will link segments of natural habitats in Central America from the borders of northern Columbia to southern Mexico. The first and second year of the project focused on the development of regional satellite databases (JERS-IC, MODIS, and Landsat-TM), training of Central American cooperators and forest cover and change analysis. The three regional satellite mosaics were developed and distributed on CD-ROM to cooperators and regional outlets. Four regional remote sensing training courses were conducted in 3 countries including participants from all 7 Central American countries and Mexico. In year 3, regional forest change assessment in reference to Mesoamerican Biological Corridor was completed and land cover maps (from Landsat TM) were developed for 7 Landsat scenes and accuracy assessed. These maps are being used to support validation of MODIS forest/non forest maps and to examine forest fragmentation and forest cover change in selected study sites. A no-cost time extension (2003-2004) allowed the completion of an M.S. thesis by a Costa Rican student and preparation of manuscripts for future submission to peer-reviewed outlets. Proposals initiated at the end of the project have generated external funding from the U.S. Forest Service (to U. Maine), NASA-ESSF (Oregon State U.) and from USAID and EPA (to NASA-MSFC-GHCC) to test MODIS capabilities to detect forest change; conduct literature review on biomass estimation and carbon stocks and develop a regional remote sensing monitoring center in Central America. The success of the project has led to continued cooperation between NASA, other federal agencies, and scientists from all seven Central American Countries (see SERVIR web site for this ongoing work - servir.nsstc.nasa.gov).

Animals as Mobile Biological Sensors for Forest Fire Detection

PubMed Central

2007-01-01

This paper proposes a mobile biological sensor system that can assist in early detection of forest fires one of the most dreaded natural disasters on the earth. The main idea presented in this paper is to utilize animals with sensors as Mobile Biological Sensors (MBS). The devices used in this system are animals which are native animals living in forests, sensors (thermo and radiation sensors with GPS features) that measure the temperature and transmit the location of the MBS, access points for wireless communication and a central computer system which classifies of animal actions. The system offers two different methods, firstly: access points continuously receive data about animals' location using GPS at certain time intervals and the gathered data is then classified and checked to see if there is a sudden movement (panic) of the animal groups: this method is called animal behavior classification (ABC). The second method can be defined as thermal detection (TD): the access points get the temperature values from the MBS devices and send the data to a central computer to check for instant changes in the temperatures. This system may be used for many purposes other than fire detection, namely animal tracking, poaching prevention and detecting instantaneous animal death. PMID:28903281

Estimation and modeling of forest attributes across large spatial scales using BiomeBGC, high-resolution imagery, LiDAR data, and inventory data

NASA Astrophysics Data System (ADS)

Golinkoff, Jordan Seth

The accurate estimation of forest attributes at many different spatial scales is a critical problem. Forest landowners may be interested in estimating timber volume, forest biomass, and forest structure to determine their forest's condition and value. Counties and states may be interested to learn about their forests to develop sustainable management plans and policies related to forests, wildlife, and climate change. Countries and consortiums of countries need information about their forests to set global and national targets to deal with issues of climate change and deforestation as well as to set national targets and understand the state of their forest at a given point in time. This dissertation approaches these questions from two perspectives. The first perspective uses the process model Biome-BGC paired with inventory and remote sensing data to make inferences about a current forest state given known climate and site variables. Using a model of this type, future climate data can be used to make predictions about future forest states as well. An example of this work applied to a forest in northern California is presented. The second perspective of estimating forest attributes uses high resolution aerial imagery paired with light detection and ranging (LiDAR) remote sensing data to develop statistical estimates of forest structure. Two approaches within this perspective are presented: a pixel based approach and an object based approach. Both approaches can serve as the platform on which models (either empirical growth and yield models or process models) can be run to generate inferences about future forest state and current forest biogeochemical cycling.

Detection of spatio-temporal changes of Norway spruce forest stands in Ore Mountains using airborne hyperspectral imagery

NASA Astrophysics Data System (ADS)

Misurec, J.; Kopačková, V.; Lhotáková, Z.; Albrechtova, J.; Campbell, P. K. E.

2015-12-01

The Ore Mountains are an example of the region that suffered from severe environmental pollution caused by long-term coal mining and heavy industry leading to massive dieback of the local Norway spruce forests between the 1970's and 1990's. The situation became getting better at the end of 1990's after pollution loads significantly decreased. In 1998 and 2013, airborne hyperspectral data (with sensor ASAS and APEX, respectively) were used to study recovery of the originally damaged forest stands and compared them with those that have been less affected by environmental pollution. The field campaign (needle biochemical analysis, tree defoliation etc.) accompanied hyperspectral imagery acquisition. An analysis was conducted assessing a set of 16 vegetation indices providing complex information on foliage, biochemistry and canopy biophysics and structure. Five of them (NDVI, NDVI705, VOG1, MSR and TCARI/OSAVI) showing the best results were employed to study spatial gradients as well as temporal changes. The detected gradients are in accordance with ground truth data on representative trees. The obtained results indicate that the original significant differences between the damaged and undamaged stands have been generally levelled until 2013, although it is still possible to detect signs of the previous damages in several cases.

Spatio-Temporal Assessment of Margalla Hills Forest by Using Landsat Imagery for Year 2000 and 2018

NASA Astrophysics Data System (ADS)

Batool, R.; Javaid, K.

2018-04-01

Environmental imbalance due to human activities has shown serious threat to ecosystem and produced negative impacts. The main goal of this study is to identify, monitor and classify temporal changes of forest cover, build up and open spaces in Margalla Hills National Park, Islamabad. Geographic Information Sciences (GISc) and Remote Sensing (RS) techniques has been used for the assessment of analysis. LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 Operational Land Imager (OLI) were utilized for obtaining data of year 2000 and 2018. Temporal changes were evaluated after applying supervised classification and discrimination was analyzed by Per-Pixel based change detection. Results depicts forest cover decrease from 87 % to 74 % whereas build up has increased from 5 % to 7 % over the span. Consequences also justify the presence of open land in study area that has been increased from 2 % to 7 % respectively.

Time series change detection: Algorithms for land cover change

NASA Astrophysics Data System (ADS)

Boriah, Shyam

The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on satellites, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and spatio-temporal data. These massive and information-rich datasets offer huge potential for advancing the science of land cover change, climate change and anthropogenic impacts. One important area where remote sensing data can play a key role is in the study of land cover change. Specifically, the conversion of natural land cover into humandominated cover types continues to be a change of global proportions with many unknown environmental consequences. In addition, being able to assess the carbon risk of changes in forest cover is of critical importance for both economic and scientific reasons. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, there is a need in the earth science domain to systematically study land cover change in order to understand its impact on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Land cover conversions include tree harvests in forested regions, urbanization, and agricultural intensification in former woodland and natural grassland areas. These types of conversions also have significant public policy implications due to issues such as water supply management and atmospheric CO2 output. In spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that can be used for decision making and policy planning purposes. In particular, previous change detection studies have primarily relied on examining differences between two or more satellite images acquired on different dates. Thus, a technological solution that detects global land cover change using high temporal resolution time series data will represent a paradigm-shift in the field of land cover change studies. To realize these ambitious goals, a number of computational challenges in spatio-temporal data mining need to be addressed. Specifically, analysis and discovery approaches need to be cognizant of climate and ecosystem data characteristics such as seasonality, non-stationarity/inter-region variability, multi-scale nature, spatio-temporal autocorrelation, high-dimensionality and massive data size. This dissertation, a step in that direction, translates earth science challenges to computer science problems, and provides computational solutions to address these problems. In particular, three key technical capabilities are developed: (1) Algorithms for time series change detection that are effective and can scale up to handle the large size of earth science data; (2) Change detection algorithms that can handle large numbers of missing and noisy values present in satellite data sets; and (3) Spatio-temporal analysis techniques to identify the scale and scope of disturbance events.

Observation des influences du changement du couvert forestier sur le comportement hydrologique de grands bassins versants tropicaux a l'aide de la teledetection numerique: Cas du bassin versant de Dong Nai, Viet Nam

NASA Astrophysics Data System (ADS)

Pham, Trinh Hung

Monitoring hydrological behavior of a large tropical watershed following a forest cover variation has an important role in water resource management planning as well as for forest sustainable management. Traditional methods in forest hydrology studies are Experimental watersheds, Upstream-downstream, Experimental plots, Statistical regional analysis and Watershed simulation. Those methodes have limitations for large watersheds concerning the monitoring time, the lack of input data especially about forest cover and the capacity of extrapolating results accurately in terms of large watersheds. Moreover, there is still currently a scientific debate in forest ecology on relation between water and forest. The reason of this problem comes from geographical differences in publication concerning study zones, experimental watershed size and applied methods. It gives differences in the conclusions on the influence of tropical forest cover change on the changes of outlet water and yet on the yearly runoff in terms of large watershed. In order to exceed the limitations of actual methods, to solve the difficulty of acquiring forest cover data and to have a better understanding of the relation between tropical forest cover change and hydrological behavior evolution of a large watershed, it is necessary to develop a new approach by using numeric remote sensing. We used the watershed of Dong Nai as a case study. Results show that a fusion between TM and ETM+ Landsat image series and hydro-meteorologic data allow us to observe and detect flooding trends and flooding peaks after an intensive forest cover change from 16% to 20%. Flooding frequency and flooding peaks have clearly decreased when there is an increase of the forest cover from 1983 to 1990. The influence of tropical forest cover on the hydrological behavior is varying with geographical locations of watershed. There is a significant relation between forest cover evolution and environmental facteurs as the runoff coefficient (R = 0,87) and the yearly precipitation (R = 0,93).

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

Increasing large scale windstorm damage in Western, Central and Northern European forests, 1951-2010

NASA Astrophysics Data System (ADS)

Gregow, H.; Laaksonen, A.; Alper, M. E.

2017-04-01

Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) from the European forest institute database (comprising 276 PD reports from 1951-2010), total growing stock (TGS) statistics of European forests and the daily North Atlantic Oscillation (NAO) index, we identify a statistically significant change in storm intensity in Western, Central and Northern Europe (17 countries). Using the validated set of storms, we found that the year 1990 represents a change-point at which the average intensity of the most destructive storms indicated by PD/TGS > 0.08% increased by more than a factor of three. A likelihood ratio test provides strong evidence that the change-point represents a real shift in the statistical behaviour of the time series. All but one of the seven catastrophic storms (PD/TGS > 0.2%) occurred since 1990. Additionally, we detected a related decrease in September-November PD/TGS and an increase in December-February PD/TGS. Our analyses point to the possibility that the impact of climate change on the North Atlantic storms hitting Europe has started during the last two and half decades.

Increasing large scale windstorm damage in Western, Central and Northern European forests, 1951–2010

PubMed Central

Gregow, H.; Laaksonen, A.; Alper, M. E.

2017-01-01

Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) from the European forest institute database (comprising 276 PD reports from 1951–2010), total growing stock (TGS) statistics of European forests and the daily North Atlantic Oscillation (NAO) index, we identify a statistically significant change in storm intensity in Western, Central and Northern Europe (17 countries). Using the validated set of storms, we found that the year 1990 represents a change-point at which the average intensity of the most destructive storms indicated by PD/TGS > 0.08% increased by more than a factor of three. A likelihood ratio test provides strong evidence that the change-point represents a real shift in the statistical behaviour of the time series. All but one of the seven catastrophic storms (PD/TGS > 0.2%) occurred since 1990. Additionally, we detected a related decrease in September–November PD/TGS and an increase in December–February PD/TGS. Our analyses point to the possibility that the impact of climate change on the North Atlantic storms hitting Europe has started during the last two and half decades. PMID:28401947

Scaling properties reveal regulation of river flows in the Amazon through a forest reservoir

NASA Astrophysics Data System (ADS)

Salazar, Juan Fernando; Villegas, Juan Camilo; María Rendón, Angela; Rodríguez, Estiven; Hoyos, Isabel; Mercado-Bettín, Daniel; Poveda, Germán

2018-03-01

Many natural and social phenomena depend on river flow regimes that are being altered by global change. Understanding the mechanisms behind such alterations is crucial for predicting river flow regimes in a changing environment. Here we introduce a novel physical interpretation of the scaling properties of river flows and show that it leads to a parsimonious characterization of the flow regime of any river basin. This allows river basins to be classified as regulated or unregulated, and to identify a critical threshold between these states. We applied this framework to the Amazon river basin and found both states among its main tributaries. Then we introduce the forest reservoir hypothesis to describe the natural capacity of river basins to regulate river flows through land-atmosphere interactions (mainly precipitation recycling) that depend strongly on the presence of forests. A critical implication is that forest loss can force the Amazonian river basins from regulated to unregulated states. Our results provide theoretical and applied foundations for predicting hydrological impacts of global change, including the detection of early-warning signals for critical transitions in river basins.

Health and vitality assessment of two common pine species in the context of climate change in southern Europe.

PubMed

Sicard, Pierre; Dalstein-Richier, Laurence

2015-02-01

The Mediterranean Basin is expected to be more strongly affected by ongoing climate change than most other regions of the earth. The South-eastern France can be considered as case study for assessing global change impacts on forests. Based on non-parametric statistical tests, the climatic parameters (temperature, relative humidity, rainfall, global radiation) and forest-response indicators (crown defoliation, discoloration and visible foliar ozone injury) of two pine species (Pinus halepensis and Pinus cembra) were analyzed. In the last 20 years, the trend analyses reveal a clear hotter and drier climate along the coastline and slightly rainier inland. In the current climate change context, a reduction in ground-level ozone (O3) was found at remote sites and the visible foliar O3 injury decreased while deterioration of the crown conditions was observed likely due to a drier and warmer climate. Clearly, if such climatic and ecological changes are now being detected when the climate, in South-eastern France, has warmed in the last 20 years (+0.46-1.08°C), it can be expected that many more impacts on tree species will occur in response to predicted temperature changes by 2100 (+1.95-4.59°C). Climate change is projected to reduce the benefits of O3 precursor emissions controls leading to a higher O3 uptake. However, the drier and warmer climate should induce a soil drought leading to a lower O3 uptake. These two effects, acting together in an opposite way, could mitigate the harmful impacts of O3 on forests. The development of coordinated emission abatement strategies is useful to reduce both climate change and O3 pollution. Climate change will create additional challenges for forest management with substantial socio-economic and biological diversity impacts. However, the development of future sustainable and adaptive forest management strategies has the potential to reduce the vulnerability of forest species to climate change. Copyright © 2014 Elsevier Inc. All rights reserved.

Near Real-Time Monitoring of Forest Disturbance: A Multi-Sensor Remote Sensing Approach and Assessment Framework

NASA Astrophysics Data System (ADS)

Tang, Xiaojing

Fast and accurate monitoring of tropical forest disturbance is essential for understanding current patterns of deforestation as well as helping eliminate illegal logging. This dissertation explores the use of data from different satellites for near real-time monitoring of forest disturbance in tropical forests, including: development of new monitoring methods; development of new assessment methods; and assessment of the performance and operational readiness of existing methods. Current methods for accuracy assessment of remote sensing products do not address the priority of near real-time monitoring of detecting disturbance events as early as possible. I introduce a new assessment framework for near real-time products that focuses on the timing and the minimum detectable size of disturbance events. The new framework reveals the relationship between change detection accuracy and the time needed to identify events. In regions that are frequently cloudy, near real-time monitoring using data from a single sensor is difficult. This study extends the work by Xin et al. (2013) and develops a new time series method (Fusion2) based on fusion of Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) data. Results of three test sites in the Amazon Basin show that Fusion2 can detect 44.4% of the forest disturbance within 13 clear observations (82 days) after the initial disturbance. The smallest event detected by Fusion2 is 6.5 ha. Also, Fusion2 detects disturbance faster and has less commission error than more conventional methods. In a comparison of coarse resolution sensors, MODIS Terra and Aqua combined provides faster and more accurate detection of disturbance events than VIIRS (Visible Infrared Imaging Radiometer Suite) and MODIS single sensor data. The performance of near real-time monitoring using VIIRS is slightly worse than MODIS Terra but significantly better than MODIS Aqua. New monitoring methods developed in this dissertation provide forest protection organizations the capacity to monitor illegal logging events promptly. In the future, combining two Landsat and two Sentinel-2 satellites will provide global coverage at 30 m resolution every 4 days, and routine monitoring may be possible at high resolution. The methods and assessment framework developed in this dissertation are adaptable to newly available datasets.

Pyrosequencing reveals changes in soil bacterial communities after conversion of Yungas forests to agriculture.

PubMed

Montecchia, Marcela S; Tosi, Micaela; Soria, Marcelo A; Vogrig, Jimena A; Sydorenko, Oksana; Correa, Olga S

2015-01-01

The Southern Andean Yungas in Northwest Argentina constitute one of the main biodiversity hotspots in the world. Considerable changes in land use have taken place in this ecoregion, predominantly related to forest conversion to croplands, inducing losses in above-ground biodiversity and with potential impact on soil microbial communities. In this study, we used high-throughput pyrosequencing of the 16S ribosomal RNA gene to assess whether land-use change and time under agriculture affect the composition and diversity of soil bacterial communities. We selected two areas dedicated to sugarcane and soybean production, comprising both short- and long-term agricultural sites, and used the adjacent native forest soils as a reference. Land-use change altered the composition of bacterial communities, with differences between productive areas despite the similarities between both forests. At the phylum level, only Verrucomicrobia and Firmicutes changed in abundance after deforestation for sugarcane and soybean cropping, respectively. In cultivated soils, Verrucomicrobia decreased sharply (~80%), while Firmicutes were more abundant. Despite the fact that local diversity was increased in sugarcane systems and was not altered by soybean cropping, phylogenetic beta diversity declined along both chronosequences, evidencing a homogenization of soil bacterial communities over time. In spite of the detected alteration in composition and diversity, we found a core microbiome resistant to the disturbances caused by the conversion of forests to cultivated lands and few or none exclusive OTUs for each land-use type. The overall changes in the relative abundance of copiotrophic and oligotrophic taxa may have an impact in soil ecosystem functionality. However, communities with many taxa in common may also share many functional attributes, allowing to maintain at least some soil ecosystem services after forest conversion to croplands.

Pyrosequencing Reveals Changes in Soil Bacterial Communities after Conversion of Yungas Forests to Agriculture

PubMed Central

Montecchia, Marcela S.; Tosi, Micaela; Soria, Marcelo A.; Vogrig, Jimena A.; Sydorenko, Oksana; Correa, Olga S.

2015-01-01

The Southern Andean Yungas in Northwest Argentina constitute one of the main biodiversity hotspots in the world. Considerable changes in land use have taken place in this ecoregion, predominantly related to forest conversion to croplands, inducing losses in above-ground biodiversity and with potential impact on soil microbial communities. In this study, we used high-throughput pyrosequencing of the 16S ribosomal RNA gene to assess whether land-use change and time under agriculture affect the composition and diversity of soil bacterial communities. We selected two areas dedicated to sugarcane and soybean production, comprising both short- and long-term agricultural sites, and used the adjacent native forest soils as a reference. Land-use change altered the composition of bacterial communities, with differences between productive areas despite the similarities between both forests. At the phylum level, only Verrucomicrobia and Firmicutes changed in abundance after deforestation for sugarcane and soybean cropping, respectively. In cultivated soils, Verrucomicrobia decreased sharply (~80%), while Firmicutes were more abundant. Despite the fact that local diversity was increased in sugarcane systems and was not altered by soybean cropping, phylogenetic beta diversity declined along both chronosequences, evidencing a homogenization of soil bacterial communities over time. In spite of the detected alteration in composition and diversity, we found a core microbiome resistant to the disturbances caused by the conversion of forests to cultivated lands and few or none exclusive OTUs for each land-use type. The overall changes in the relative abundance of copiotrophic and oligotrophic taxa may have an impact in soil ecosystem functionality. However, communities with many taxa in common may also share many functional attributes, allowing to maintain at least some soil ecosystem services after forest conversion to croplands. PMID:25793893

Monitoring of environmental conditions in the Alaskan forests using ERS-1 SAR data

NASA Technical Reports Server (NTRS)

Rignot, Eric; Way, Jobea; Mcdonald, Kyle; Viereck, Leslie; Adams, Phyllis

1992-01-01

Preliminary results from an analysis of the multitemporal radar backscatter signatures of tree species acquired by European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data are presented. Significant changes in radar backscatter are detected. Correlation of these differences with ground truth observations indicate that these are due to changes in soil and liquid water content as a result of freeze/thaw events. C-band observations acquired by the NASA/Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) instrument demonstrate the potential of a C-band radar instrument to monitor drought/flood events. The potential of ERS-1 for monitoring phenologic changes in the forest and for classifying tree species is less promising.

Determination of mangrove change in Matang Mangrove Forest using multi temporal satellite imageries

NASA Astrophysics Data System (ADS)

Ibrahim, N. A.; Mustapha, M. A.; Lihan, T.; Ghaffar, M. A.

2013-11-01

Mangrove protects shorelines from damaging storm and hurricane winds, waves, and floods. Mangroves also help prevent erosion by stabilizing sediments with their tangled root systems. They maintain water quality and clarity, filtering pollutants and trapping sediments originating from land. However, mangrove has been reported to be threatened by land conversion for other activities. In this study, land use and land cover changes in Matang Mangrove Forest during the past 18 years (1993 to 2011) were determined using multi-temporal satellite imageries by Landsat TM and RapidEye. In this study, classification of land use and land cover approach was performed using the maximum likelihood classifier (MCL) method along with vegetation index differencing (NDVI) technique. Data obtained was evaluated through Kappa coefficient calculation for accuracy and results revealed that the classification accuracy was 81.25% with Kappa Statistics of 0.78. The results indicated changes in mangrove forest area to water body with 2,490.6 ha, aquaculture with 890.7 ha, horticulture with 1,646.1 ha, palm oil areas with 1,959.2 ha, dry land forest with 2,906.7 ha and urban settlement area with 224.1 ha. Combinations of these approaches were useful for change detection and for indication of the nature of these changes.

Comparing LiDAR-Generated to ground- surveyed channel cross-sectional profiles in a forested mountain stream

Treesearch

Brian C. Dietterick; Russell White; Ryan Hilburn

2012-01-01

Airborne Light Detection and Ranging (LiDAR) holds promise to provide an alternative to traditional ground-based survey methods for stream channel characterization and some change detection purposes, even under challenging landscape conditions. This study compared channel characteristics measured at 53 ground-surveyed and LiDAR-derived crosssectional profiles located...

The difference of detecting water mist and smoke by electromagnetic wave in simulation experiments

NASA Astrophysics Data System (ADS)

Zhang, Jingdi; Cui, Bing; Xiao, Si

2015-10-01

Although mist is similar to smoke in morphology, their compositions are very different. Therefore there is a significant difference between mist and smoke when detected by electromagnetic wave. This paper puts forward a kind of feasible solution based on Ansoft HFSS software about how to determine the forest fire by distinguishing mist and smoke above the forest. The experiments simulate the difference between mist and smoke model when detected by electromagnetic wave in different wavelengths. We find the mist and smoke model cannot absorb or reflect electromagnetic wave efficiently in Megahertz band. While in Gigahertz band mist model began to absorb and reflect electromagnetic wave above 650 Gigahertz band, but no change in smoke model. And the biggest difference appears in Terahertz band.

Forest edges: Effects on vegetation, environmental gradients and local avian communities in the Sierra Juarez, Oaxaca, Mexico

NASA Astrophysics Data System (ADS)

Burcsu, Theresa Katherine

Edge effects are among the most serious threats to forest integrity because as global forest cover decreases overall, forest edge influence increases proportionally, driving habitat change and loss. Edge effects occur at the division between adjacent habitat types. Our understanding of edge effects comes mainly from tropical wet, temperate and boreal forests. Because forest structure in moisture-limited forests differs from wetter forest types, edge dynamics are likely to differ as well. Moreover, dry forests in the tropics have been nearly eliminated or exist only as forest fragments, making edge influence an important conservation and management concern for remaining dry forests. This study addresses this gap in the edge influence knowledge by examining created, regenerating edges associated with forest management in a seasonally dry pine-oak forest of Oaxaca, creating a new data point in edge effects research. In this study I used Landsat TM imagery and a modified semivariance analysis to estimate the distance of edge influence for vegetation. I also used field methods to characterize forest structure and estimate edge influence on canopy and subcanopy vegetation. To finalize the project I extended the study to bird assemblages to identify responses and habitat preferences to local-scale changes associated with regenerating edges created by group-selection timber harvest. Remote sensing analysis estimated that the distance of edge influence was 30-90 m from the edge. Vegetation analysis suggested that edge effects were weak relative to wetter forest types and that remote sensing data did not provide an estimate that was directly applicable to field-measured vegetative edge effects. The bird assemblages likewise responded weakly to habitat change associated with edge effect. Open canopy structure, simple vertical stratigraphy, and topographic variation create forest conditions in which small openings do not create a high contrast to undisturbed forest. Thus, in this seasonally dry, open forest, vegetation and bird communities respond less to small openings than they do in wetter, more closed-canopy forests. Management practices and historical land-use interact and interfere with the detectability of edge influence in our study area. These results support hypotheses proposed for open forest types and suggest that patterns in edge influence in wet forest types may not be applicable to dry sites.

Change in the forested and developed landscape of the Lake Tahoe basin, California and Nevada, USA, 1940-2002

USGS Publications Warehouse

Raumann, C.G.; Cablk, Mary E.

2008-01-01

The current ecological state of the Lake Tahoe basin has been shaped by significant landscape-altering human activity and management practices since the mid-1850s; first through widespread timber harvesting from the 1850s to 1920s followed by urban development from the 1950s to the present. Consequences of landscape change, both from development and forest management practices including fire suppression, have prompted rising levels of concern for the ecological integrity of the region. The impacts from these activities include decreased water quality, degraded biotic communities, and increased fire hazard. To establish an understanding of the Lake Tahoe basin's landscape change in the context of forest management and development we mapped, quantified, and described the spatial and temporal distribution and variability of historical changes in land use and land cover in the southern Lake Tahoe basin (279 km2) from 1940 to 2002. Our assessment relied on post-classification change detection of multi-temporal land-use/cover and impervious-surface-area data that were derived through manual interpretation, image processing, and GIS data integration for four dates of imagery: 1940, 1969, 1987, and 2002. The most significant land conversion during the 62-year study period was an increase in developed lands with a corresponding decrease in forests, wetlands, and shrublands. Forest stand densities increased throughout the 62-year study period, and modern thinning efforts resulted in localized stand density decreases in the latter part of the study period. Additionally forests were gained from succession, and towards the end of the study period extensive tree mortality occurred. The highest rates of change occurred between 1940 and 1969, corresponding with dramatic development, then rates declined through 2002 for all observed landscape changes except forest density decrease and tree mortality. Causes of landscape change included regional population growth, tourism demands, timber harvest for local use, fire suppression, bark beetle attack, and fuels reduction activities. Results from this study offer land managers within the Lake Tahoe basin and in similar regions a basis for making better informed land-use and management decisions to potentially minimize detrimental ecological impacts of landscape change. The perspective to be gained is based on quantitative retrospection of the effects of human-driven changes and the impacts of management action or inaction to the forested landscape. ?? 2008 Elsevier B.V. All rights reserved.

Airborne Remote Sensing

NASA Technical Reports Server (NTRS)

1992-01-01

NASA imaging technology has provided the basis for a commercial agricultural reconnaissance service. AG-RECON furnishes information from airborne sensors, aerial photographs and satellite and ground databases to farmers, foresters, geologists, etc. This service produces color "maps" of Earth conditions, which enable clients to detect crop color changes or temperature changes that may indicate fire damage or pest stress problems.

How does conversion of natural tropical rainforest ecosystems affect soil bacterial and fungal communities in the Nile river watershed of Uganda?

PubMed

Alele, Peter O; Sheil, Douglas; Surget-Groba, Yann; Lingling, Shi; Cannon, Charles H

2014-01-01

Uganda's forests are globally important for their conservation values but are under pressure from increasing human population and consumption. In this study, we examine how conversion of natural forest affects soil bacterial and fungal communities. Comparisons in paired natural forest and human-converted sites among four locations indicated that natural forest soils consistently had higher pH, organic carbon, nitrogen, and calcium, although variation among sites was large. Despite these differences, no effect on the diversity of dominant taxa for either bacterial or fungal communities was detected, using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). Composition of fungal communities did generally appear different in converted sites, but surprisingly, we did not observe a consistent pattern among sites. The spatial distribution of some taxa and community composition was associated with soil pH, organic carbon, phosphorus and sodium, suggesting that changes in soil communities were nuanced and require more robust metagenomic methods to understand the various components of the community. Given the close geographic proximity of the paired sampling sites, the similarity between natural and converted sites might be due to continued dispersal between treatments. Fungal communities showed greater environmental differentiation than bacterial communities, particularly according to soil pH. We detected biotic homogenization in converted ecosystems and substantial contribution of β-diversity to total diversity, indicating considerable geographic structure in soil biota in these forest communities. Overall, our results suggest that soil microbial communities are relatively resilient to forest conversion and despite a substantial and consistent change in the soil environment, the effects of conversion differed widely among sites. The substantial difference in soil chemistry, with generally lower nutrient quantity in converted sites, does bring into question, how long this resilience will last.

How Does Conversion of Natural Tropical Rainforest Ecosystems Affect Soil Bacterial and Fungal Communities in the Nile River Watershed of Uganda?

PubMed Central

Alele, Peter O.; Sheil, Douglas; Surget-Groba, Yann; Lingling, Shi; Cannon, Charles H.

2014-01-01

Uganda's forests are globally important for their conservation values but are under pressure from increasing human population and consumption. In this study, we examine how conversion of natural forest affects soil bacterial and fungal communities. Comparisons in paired natural forest and human-converted sites among four locations indicated that natural forest soils consistently had higher pH, organic carbon, nitrogen, and calcium, although variation among sites was large. Despite these differences, no effect on the diversity of dominant taxa for either bacterial or fungal communities was detected, using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). Composition of fungal communities did generally appear different in converted sites, but surprisingly, we did not observe a consistent pattern among sites. The spatial distribution of some taxa and community composition was associated with soil pH, organic carbon, phosphorus and sodium, suggesting that changes in soil communities were nuanced and require more robust metagenomic methods to understand the various components of the community. Given the close geographic proximity of the paired sampling sites, the similarity between natural and converted sites might be due to continued dispersal between treatments. Fungal communities showed greater environmental differentiation than bacterial communities, particularly according to soil pH. We detected biotic homogenization in converted ecosystems and substantial contribution of β-diversity to total diversity, indicating considerable geographic structure in soil biota in these forest communities. Overall, our results suggest that soil microbial communities are relatively resilient to forest conversion and despite a substantial and consistent change in the soil environment, the effects of conversion differed widely among sites. The substantial difference in soil chemistry, with generally lower nutrient quantity in converted sites, does bring into question, how long this resilience will last. PMID:25118069

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy

PubMed Central

Asner, Gregory P.; Nepstad, Daniel; Cardinot, Gina; Ray, David

2004-01-01

Amazônia contains vast stores of carbon in high-diversity ecosystems, yet this region undergoes major changes in precipitation affecting land use, carbon dynamics, and climate. The extent and structural complexity of Amazon forests impedes ground studies of ecosystem functions such as net primary production (NPP), water cycling, and carbon sequestration. Traditional modeling and remote-sensing approaches are not well suited to tropical forest studies, because (i) biophysical mechanisms determining drought effects on canopy water and carbon dynamics are poorly known, and (ii) remote-sensing metrics of canopy greenness may be insensitive to small changes in leaf area accompanying drought. New spaceborne imaging spectroscopy may detect drought stress in tropical forests, helping to monitor forest physiology and constrain carbon models. We combined a forest drought experiment in Amazônia with spaceborne imaging spectrometer measurements of this area. With field data on rainfall, soil water, and leaf and canopy responses, we tested whether spaceborne hyperspectral observations quantify differences in canopy water and NPP resulting from drought stress. We found that hyperspectral metrics of canopy water content and light-use efficiency are highly sensitive to drought. Using these observations, forest NPP was estimated with greater sensitivity to drought conditions than with traditional combinations of modeling, remote-sensing, and field measurements. Spaceborne imaging spectroscopy will increase the accuracy of ecological studies in humid tropical forests. PMID:15071182

Barren-ground caribou (Rangifer tarandus groenlandicus) behaviour after recent fire events; integrating caribou telemetry data with Landsat fire detection techniques.

PubMed

Rickbeil, Gregory J M; Hermosilla, Txomin; Coops, Nicholas C; White, Joanne C; Wulder, Michael A

2017-03-01

Fire regimes are changing throughout the North American boreal forest in complex ways. Fire is also a major factor governing access to high-quality forage such as terricholous lichens for barren-ground caribou (Rangifer tarandus groenlandicus). Additionally, fire alters forest structure which can affect barren-ground caribou's ability to navigate in a landscape. Here, we characterize how the size and severity of fires are changing across five barren-ground caribou herd ranges in the Northwest Territories and Nunavut, Canada. Additionally, we demonstrate how time since fire, fire severity, and season result in complex changes in caribou behavioural metrics estimated using telemetry data. Fire disturbances were identified using novel gap-free Landsat surface reflectance composites from 1985 to 2011 across all herd ranges. Burn severity was estimated using the differenced normalized burn ratio. Annual area burned and burn severity were assessed through time for each herd and related to two behavioural metrics: velocity and relative turning angle. Neither annual area burned nor burn severity displayed any temporal trend within the study period. However, certain herds, such as the Ahiak/Beverly, have more exposure to fire than other herds (i.e. Cape Bathurst had a maximum forested area burned of less than 4 km 2 ). Time since fire and burn severity both significantly affected velocity and relative turning angles. During fall, winter, and spring, fire virtually eliminated foraging-focused behaviour for all 26 years of analysis while more severe fires resulted in a marked increase in movement-focused behaviour compared to unburnt patches. Between seasons, caribou used burned areas as early as 1-year postfire, demonstrating complex, nonlinear reactions to time since fire, fire severity, and season. In all cases, increases in movement-focused behaviour were detected postfire. We conclude that changes in caribou behaviour immediately postfire are primarily driven by changes in forest structure rather than changes in terricholous lichen availability. © 2016 John Wiley & Sons Ltd.

Combining satellite, aerial and ground measurements to assess forest carbon stocks in Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Beaumont, Benjamin; Bouvy, Alban; Stephenne, Nathalie; Mathoux, Pierre; Bastin, Jean-François; Baudot, Yves; Akkermans, Tom

2015-04-01

Monitoring tropical forest carbon stocks changes has been a rising topic in the recent years as a result of REDD+ mechanisms negotiations. Such monitoring will be mandatory for each project/country willing to benefit from these financial incentives in the future. Aerial and satellite remote sensing technologies offer cost advantages in implementing large scale forest inventories. Despite the recent progress made in the use of airborne LiDAR for carbon stocks estimation, no widely operational and cost effective method has yet been delivered for central Africa forest monitoring. Within the Maï Ndombe region of Democratic Republic of Congo, the EO4REDD project develops a method combining satellite, aerial and ground measurements. This combination is done in three steps: [1] mapping and quantifying forest cover changes using an object-based semi-automatic change detection (deforestation and forest degradation) methodology based on very high resolution satellite imagery (RapidEye), [2] developing an allometric linear model for above ground biomass measurements based on dendrometric parameters (tree crown areas and heights) extracted from airborne stereoscopic image pairs and calibrated using ground measurements of individual trees on a data set of 18 one hectare plots and [3] relating these two products to assess carbon stocks changes at a regional scale. Given the high accuracies obtained in [1] (> 80% for deforestation and 77% for forest degradation) and the suitable, but still to be improved with a larger calibrating sample, model (R² of 0.7) obtained in [2], EO4REDD products can be seen as a valid and replicable option for carbon stocks monitoring in tropical forests. Further improvements are planned to strengthen the cost effectiveness value and the REDD+ suitability in the second phase of EO4REDD. This second phase will include [A] specific model developments per forest type; [B] measurements of afforestation, reforestation and natural regeneration processes and [C] study of Sentinel satellite data series potential use.

Histories of Puerto Rican parrot nests in the Caribbean National Forest/Luquillo Experimental Forest, 1973-2000

USGS Publications Warehouse

Wunderle, J.M.; Snyder, N.F.R.; Muiznieks, B.; Wiley, J.W.; Meyers, J.M.

2003-01-01

This publication summarizes the histories of all known Puerto Rican parrot nests in the Caribbean National Forest/Luquillo Experimental Forest from 1973 through 2000. Included for each nest, when known, are the identifies of the pair, clutch size, known fertile and infertile eggs, number of eggs that hatched, number of chicks that survived, sources of mortality, fostering (source, destination. or both), number of young fledged from the pair and from the nest, and percentage of days the nest was guarded. This information is useful for detecting and assessing potential changes in reproductive output and nest threats and is fundamental for understanding some of the demographic and genetic factors influencing the wild parrot population.

Balancing shifting cultivation and forest conservation: lessons from a "sustainable landscape" in southeastern Mexico.

PubMed

Dalle, Sarah Paule; Pulido, María T; de Blois, Sylvie

2011-07-01

Shifting cultivation is often perceived to be a threat to forests, but it is also central to the culture and livelihoods of millions of people worldwide. Balancing agriculture and forest conservation requires knowledge of how agricultural land uses evolve in landscapes with forest conservation initiatives. Based on a case study from Quintana Roo, Mexico, and remote sensing data, we investigated land use and land cover change (LUCC) in relation to accessibility (from main settlement and road) in search of evidence for agricultural expansion and/or intensification after the initiation of a community forestry program in 1986. Intensification was through a shortening of the fallow period. Defining the sampling space as a function of human needs and accessibility to agricultural resources was critical to ensure a user-centered perspective of the landscape. The composition of the accessible landscape changed substantially between 1976 and 1997. Over the 21-year period studied, the local population saw the accessible landscape transformed from a heterogeneous array of different successional stages including mature forests to a landscape dominated by young fallows. We detected a dynamic characterized by intensification of shifting cultivation in the most accessible areas with milpas being felled more and more from young fallows in spite of a preference for felling secondary forests. We argue that the resulting landscape provides a poorer resource base for sustaining agricultural livelihoods and discuss ways in which agricultural change could be better addressed through participatory land use planning. Balancing agricultural production and forest conservation will become even more important in a context of intense negotiations for carbon credits, an emerging market that is likely to drive future land changes worldwide.

Effects of reforestation on ammonia-oxidizing microbial community composition and abundance in subtropical acidic forest soils.

PubMed

Wu, Ruo-Nan; Meng, Han; Wang, Yong-Feng; Gu, Ji-Dong

2018-06-01

Forest ecosystems have great ecological values in mitigation of climate change and protection of biodiversity of flora and fauna; re-forestry is commonly used to enhance the sequestration of atmospheric CO 2 into forest storage biomass. Therefore, seasonal and spatial dynamics of the major microbial players in nitrification, ammonia-oxidizing archaea (AOA) and bacteria (AOB), in acidic soils of young and matured revegetated forests were investigated to elucidate the changes of microbial communities during forest restoration, and compared to delineate the patterns of community shifts under the influences of environmental factors. AOA were more abundant than AOB in both young and matured revegetated forest soils in both summer and winter seasons. In summer, however, the abundance of amoA-AOA decreased remarkably (p < 0.01), ranging from 1.90 (± 0.07) × 10 8 copies per gram dry soil in matured forest to 5.04 (± 0.43) × 10 8 copies per gram dry soil in young forest, and amoA-AOB was below detection limits to obtain any meaningful values. Moreover, exchangeable Al 3+ and organic matter were found to regulate the physiologically functional nitrifiers, especially AOA abundance in acidic forest soils. AOB community in winter showed stronger correlation with the restoration status of revegetated forests and AOA community dominated by Nitrosotalea devanaterra, in contrast, was more sensitive to the seasonal and spatial variations of environmental factors. These results enrich the current knowledge of nitrification during re-forestry and provide valuable information to developmental status of revegetated forests for management through microbial analysis.

Forest carbon emissions from cropland expansion in the Brazilian Cerrado biome

NASA Astrophysics Data System (ADS)

Noojipady, Praveen; Morton, C. Douglas; Macedo, N. Marcia; Victoria, C. Daniel; Huang, Chengquan; Gibbs, K. Holly; Edson Bolfe, L.

2017-02-01

Land use, land use change, and forestry accounted for two-thirds of Brazil’s greenhouse gas emissions profile in 2005. Amazon deforestation has declined by more than 80% over the past decade, yet Brazil’s forests extend beyond the Amazon biome. Rapid expansion of cropland in the neighboring Cerrado biome has the potential to undermine climate mitigation efforts if emissions from dry forest and woodland conversion negate some of the benefits of avoided Amazon deforestation. Here, we used satellite data on cropland expansion, forest cover, and vegetation carbon stocks to estimate annual gross forest carbon emissions from cropland expansion in the Cerrado biome. Nearly half of the Cerrado met Brazil’s definition of forest cover in 2000 (≥0.5 ha with ≥10% canopy cover). In areas of established crop production, conversion of both forest and non-forest Cerrado formations for cropland declined during 2003-2013. However, forest carbon emissions from cropland expansion increased over the past decade in Matopiba, a new frontier of agricultural production that includes portions of Maranhão, Tocantins, Piauí, and Bahia states. Gross carbon emissions from cropland expansion in the Cerrado averaged 16.28 Tg C yr-1 between 2003 and 2013, with forest-to-cropland conversion accounting for 29% of emissions. The fraction of forest carbon emissions from Matopiba was much higher; between 2010-2013, large-scale cropland conversion in Matopiba contributed 45% of total Cerrado forest carbon emissions. Carbon emissions from Cerrado-to-cropland transitions offset 5%-7% of the avoided emissions from reduced Amazon deforestation rates during 2011-2013. Comprehensive national estimates of forest carbon fluxes, including all biomes, are critical to detect cross-biome leakage within countries and achieve climate mitigation targets to reduce emissions from land use, land use change, and forestry.

Long-Term Post-Disturbance Forest Recovery in the Greater Yellowstone Ecosystem Analyzed Using Landsat Time Series Stack

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Feng R.; Meng, Ran; Huang, Chengquan

Forest recovery from past disturbance is an integral process of ecosystem carbon cycles, and remote sensing provides an effective tool for tracking forest disturbance and recovery over large areas. Although the disturbance products (tracking the conversion from forest to non-forest type) derived using the Landsat Time Series Stack-Vegetation Change Tracker (LTSS-VCT) algorithm have been validated extensively for mapping forest disturbances across the United States, the ability of this approach to characterize long-term post-disturbance recovery (the conversion from non-forest to forest) has yet to be assessed. Here in this study, the LTSS-VCT approach was applied to examine long-term (up to 24more » years) post-disturbance forest spectral recovery following stand-clearing disturbances (fire and harvests) in the Greater Yellowstone Ecosystem (GYE). Using high spatial resolution images from Google Earth, we validated the detectable forest recovery status mapped by VCT by year 2011. Validation results show that the VCT was able to map long-term post-disturbance forest recovery with overall accuracy of ~80% for different disturbance types and forest types in the GYE. Harvested areas in the GYE have higher percentages of forest recovery than burned areas by year 2011, and National Forests land generally has higher recovery rates compared with National Parks. The results also indicate that forest recovery is highly related with forest type, elevation and environmental variables such as soil type. Findings from this study can provide valuable insights for ecosystem modeling that aim to predict future carbon dynamics by integrating fine scale forest recovery conditions in GYE, in the face of climate change. Lastly, with the availability of the VCT product nationwide, this approach can also be applied to examine long-term post-disturbance forest recovery in other study regions across the U.S.« less

Long-Term Post-Disturbance Forest Recovery in the Greater Yellowstone Ecosystem Analyzed Using Landsat Time Series Stack

DOE PAGES

Zhao, Feng R.; Meng, Ran; Huang, Chengquan; ...

2016-10-29

Forest recovery from past disturbance is an integral process of ecosystem carbon cycles, and remote sensing provides an effective tool for tracking forest disturbance and recovery over large areas. Although the disturbance products (tracking the conversion from forest to non-forest type) derived using the Landsat Time Series Stack-Vegetation Change Tracker (LTSS-VCT) algorithm have been validated extensively for mapping forest disturbances across the United States, the ability of this approach to characterize long-term post-disturbance recovery (the conversion from non-forest to forest) has yet to be assessed. Here in this study, the LTSS-VCT approach was applied to examine long-term (up to 24more » years) post-disturbance forest spectral recovery following stand-clearing disturbances (fire and harvests) in the Greater Yellowstone Ecosystem (GYE). Using high spatial resolution images from Google Earth, we validated the detectable forest recovery status mapped by VCT by year 2011. Validation results show that the VCT was able to map long-term post-disturbance forest recovery with overall accuracy of ~80% for different disturbance types and forest types in the GYE. Harvested areas in the GYE have higher percentages of forest recovery than burned areas by year 2011, and National Forests land generally has higher recovery rates compared with National Parks. The results also indicate that forest recovery is highly related with forest type, elevation and environmental variables such as soil type. Findings from this study can provide valuable insights for ecosystem modeling that aim to predict future carbon dynamics by integrating fine scale forest recovery conditions in GYE, in the face of climate change. Lastly, with the availability of the VCT product nationwide, this approach can also be applied to examine long-term post-disturbance forest recovery in other study regions across the U.S.« less

Changes of polarimetric scattering characteristics of ALOS PALSAR caused by the 2011 Eruption of Shinmoe-dake Volcano

NASA Astrophysics Data System (ADS)

Ohkura, Hiroshi

Full polarimetric SAR images of ALOS PALSAR of Shinmoe-dake volcano in Japan were analyzed. The volcano erupted in January, 2011 and volcano ash deposited more than 10 cm in 12 km (2) and 1 m in 2 km (2) . Two images before and after the eruption were compared based on a point view of the four-component scattering model to detect changes of polarimetric scattering characteristics. The main detected changes are as follows. Total power of the four-component scattering model decreased on a farslope after the eruption. An incident angle on a farslope is larger than the angle on a foreslope. Decrease of surface roughness due to deposited volcanic ashes makes back-scattering smaller in the area of a larger incidence angle. However the rate of the double-bounce component got higher in a forest at the foot of a mountain slope and on a plain, where the ground surface is almost horizontal and the incident angle is relatively-large. Decrease of roughness of the forest floor increases forward scattering on the floor of the larger incident angle. This increases the double-bounced scattering due to bouncing back between the forest floor and trunks which stand "perpendicularly" on the almost horizontal forest floor. The rate of the surface scattering component got higher around an area where layover occurred. In the study area, most of layovers occurred at a ridge where an incidence angle was small. Decrease of surface roughness due to the ash deposit increases the surface scattering power in the area of the small incidence angle.

An empirical, integrated forest biomass monitoring system

NASA Astrophysics Data System (ADS)

Kennedy, Robert E.; Ohmann, Janet; Gregory, Matt; Roberts, Heather; Yang, Zhiqiang; Bell, David M.; Kane, Van; Hughes, M. Joseph; Cohen, Warren B.; Powell, Scott; Neeti, Neeti; Larrue, Tara; Hooper, Sam; Kane, Jonathan; Miller, David L.; Perkins, James; Braaten, Justin; Seidl, Rupert

2018-02-01

The fate of live forest biomass is largely controlled by growth and disturbance processes, both natural and anthropogenic. Thus, biomass monitoring strategies must characterize both the biomass of the forests at a given point in time and the dynamic processes that change it. Here, we describe and test an empirical monitoring system designed to meet those needs. Our system uses a mix of field data, statistical modeling, remotely-sensed time-series imagery, and small-footprint lidar data to build and evaluate maps of forest biomass. It ascribes biomass change to specific change agents, and attempts to capture the impact of uncertainty in methodology. We find that: • A common image framework for biomass estimation and for change detection allows for consistent comparison of both state and change processes controlling biomass dynamics. • Regional estimates of total biomass agree well with those from plot data alone. • The system tracks biomass densities up to 450-500 Mg ha-1 with little bias, but begins underestimating true biomass as densities increase further. • Scale considerations are important. Estimates at the 30 m grain size are noisy, but agreement at broad scales is good. Further investigation to determine the appropriate scales is underway. • Uncertainty from methodological choices is evident, but much smaller than uncertainty based on choice of allometric equation used to estimate biomass from tree data. • In this forest-dominated study area, growth and loss processes largely balance in most years, with loss processes dominated by human removal through harvest. In years with substantial fire activity, however, overall biomass loss greatly outpaces growth. Taken together, our methods represent a unique combination of elements foundational to an operational landscape-scale forest biomass monitoring program.

Methods for measuring bird-mediated seed rain: Insights from a Hawaiian mesic forest

USGS Publications Warehouse

Rose, Eli; Stewart, Meredith; Brinkman, Andrew; Paxton, Eben H.; Yelenik, Stephanie G.

2017-01-01

Amount and diversity of bird-dispersed seed rain play important roles in determining forest composition, yet neither is easy to quantify. The complex ecological processes that influence seed movement make the best approach highly context specific. Although recent advances in seed rain theory emphasize quantifying source-specific seed shadows, many ecological questions can be addressed u sing a less mechanistic approach that requires fewer assumptions. Using seed rain rates from 0.38 m2 hoop traps sampled twice monthly over the course of a year, we show that number of traps required to identify changes in seed rain varies across seed species and forest type. Detecting a 50% increase in amount of seed rain required from 65 to >300 traps, while detecting a 200% increase generally required ≤⃒50 traps. Trap size and ecological context dictate the number of seeds found in each trap, but the coefficient of variation (CV) across traps in a given ecological context can help inform future studies about number of traps needed to detect change. To better understand factors influencing variation around estimates of seed rain, we simulated both clustered and evenly distributed patterns of fecal deposition using three different levels of seed aggregation (number of seeds in each fecal deposit). When patterns of fecal deposition were clustered, rather than evenly dispersed across the study area, they required >1.5 times the number of traps to identify a 100% increase in seed rain. Similarly, we found that low seed aggregation required >1.5 times the number of traps to detect a 100% change than when aggregation was medium or high. At low aggregations, fewer seed rain traps contained seeds (low, 33 ± 5%; medium, 23 ± 4%; high, 24 ± 5%), resulting in more variation across traps than medium and high aggregations. We also illustrate the importance of training observers to discern between morphologically similar seeds from different species and provide resources to help identify bird-dispersed seeds commonly found within midelevation mesic Hawaiian forests.

Winter habitat associations of eastern spotted skunks in Virginia

USGS Publications Warehouse

Thorne, Emily D.; Waggy, Charles; Jachowski, David S.; Kelly, Marcella J.; Ford, W. Mark

2017-01-01

Eastern spotted skunk (Spilogale putorius) populations have declined throughout much of their range in the eastern United States over recent decades. Declines have been attributed to habitat loss or change, increased competition with sympatric mesocarnivore species, or disease. To better understand the extant distribution of spotted skunks in the Appalachian Mountains of western Virginia, USA, we used a detection-non-detection sampling approach using baited camera traps to evaluate the influence of landscape-level environmental covariates on spotted skunk detection probability and site occupancy. We conducted camera trap surveys at 91 sites from January to May in 2014 and 2015. Spotted skunk occupancy was associated with young-aged forest stands at lower elevations and more mature forest stands at higher elevations. Both land cover types in this region can be characterized as having complex forest structure, providing cover that varies with stand age, species composition, elevation, and management regime. Our results provide insight into factors that influence spotted skunk spatial distribution and habitat selection, information that can be used to generate conservation assessments and inform management decisions.

Estimating site occupancy and detection probabilities for cooper's and sharp-shinned hawks in the Southern Sierra Nevada

Treesearch

Jennifer E. Carlson; Douglas D. Piirto; John J. Keane; Samantha J. Gill

2015-01-01

Long-term monitoring programs that can detect a population change over time can be useful for managers interested in assessing population trends in response to forest management activities for a particular species. Such long-term monitoring programs have been designed for the Northern Goshawk (Accipiter gentilis), but not for the more elusive Sharp...

Detecting Forest Disturbance Events from MODIS and Landsat Time Series for the Conterminous United States

NASA Astrophysics Data System (ADS)

Zhang, G.; Ganguly, S.; Saatchi, S. S.; Hagen, S. C.; Harris, N.; Yu, Y.; Nemani, R. R.

2013-12-01

Spatial and temporal patterns of forest disturbance and regrowth processes are key for understanding aboveground terrestrial vegetation biomass and carbon stocks at regional-to-continental scales. The NASA Carbon Monitoring System (CMS) program seeks key input datasets, especially information related to impacts due to natural/man-made disturbances in forested landscapes of Conterminous U.S. (CONUS), that would reduce uncertainties in current carbon stock estimation and emission models. This study provides a end-to-end forest disturbance detection framework based on pixel time series analysis from MODIS (Moderate Resolution Imaging Spectroradiometer) and Landsat surface spectral reflectance data. We applied the BFAST (Breaks for Additive Seasonal and Trend) algorithm to the Normalized Difference Vegetation Index (NDVI) data for the time period from 2000 to 2011. A harmonic seasonal model was implemented in BFAST to decompose the time series to seasonal and interannual trend components in order to detect abrupt changes in magnitude and direction of these components. To apply the BFAST for whole CONUS, we built a parallel computing setup for processing massive time-series data using the high performance computing facility of the NASA Earth Exchange (NEX). In the implementation process, we extracted the dominant deforestation events from the magnitude of abrupt changes in both seasonal and interannual components, and estimated dates for corresponding deforestation events. We estimated the recovery rate for deforested regions through regression models developed between NDVI values and time since disturbance for all pixels. A similar implementation of the BFAST algorithm was performed over selected Landsat scenes (all Landsat cloud free data was used to generate NDVI from atmospherically corrected spectral reflectances) to demonstrate the spatial coherence in retrieval layers between MODIS and Landsat. In future, the application of this largely parallel disturbance detection setup will facilitate large scale processing and wall-to-wall mapping of forest disturbance and regrowth of Landsat data for the whole of CONUS. This exercise will aid in improving the present capabilities of the NASA CMS effort in reducing uncertainties in national-level estimates of biomass and carbon stocks.

Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm

Treesearch

Kathleen M. Bergen; Daniel G. Brown; James F. Rutherford; Eric J. Gustafson

2005-01-01

A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our...

Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

Treesearch

Jan Seibert; Jeffrey J. McDonnell

2010-01-01

The effect of land-use or land-cover change on stream runoff dynamics is not fully understood. In many parts of the world, forest management is the major land-cover change agent. While the paired catchment approach has been the primary methodology used to quantify such effects, it is only possible for small headwater catchments where there is uniformity in...

Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest.

PubMed

Campbell, Patrick; Comiskey, James; Alonso, Alfonso; Dallmeier, Francisco; Nuñez, Percy; Beltran, Hamilton; Baldeon, Severo; Nauray, William; de la Colina, Rafael; Acurio, Lucero; Udvardy, Shana

2002-05-01

Resource exploitation in lowland tropical forests is increasing and causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We propose the use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests. We established MWPs at 4 sites to: (1) describe and compare composition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs), and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similar species composition and abundance and that both perform equally well at detecting rare species. However, MWPs tend to record more species, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees > or = 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees > or =10 cm dbh. The value of MWPs for assessment and monitoring is discussed, along with recommendations for improving the sampling design to increase power.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

Use of acoustic tools to reveal otherwise cryptic responses of forest elephants to oil exploration.

PubMed

Wrege, Peter H; Rowland, Elizabeth D; Thompson, Bruce G; Batruch, Nikolas

2010-12-01

Most evaluations of the effects of human activities on wild animals have focused on estimating changes in abundance and distribution of threatened species; however, ecosystem disturbances also affect aspects of animal behavior such as short-term movement, activity budgets, and reproduction. It may take a long time for changes in behavior to manifest as changes in abundance or distribution. Therefore, it is important to have methods with which to detect short-term behavioral responses to human activity. We used continuous acoustic and seismic monitoring to evaluate the short-term effects of seismic prospecting for oil on forest elephants (Loxodonta cyclotis) in Gabon, Central Africa. We monitored changes in elephant abundance and activity as a function of the frequency and intensity of acoustic and seismic signals from dynamite detonation and human activity. Elephants did not flee the area being explored; the relative number of elephants increased in a seasonal pattern typical of elsewhere in the ecosystem. In the exploration area, however, they became more nocturnal. Neither the intensity nor the frequency of dynamite blasts affected the frequency of calling or the daily pattern of elephant activity. Nevertheless, the shift of activity to nocturnal hours became more pronounced as human activity neared each monitored area of forest. This change in activity pattern and its likely causes would not have been detected through standard monitoring methods, which are not sensitive to behavioral changes over short time scales (e.g., dung transects, point counts) or cover a limited area (e.g., camera traps). Simultaneous acoustic monitoring of animal communication, human, and environmental sounds allows the documentation of short-term behavioral changes in response to human disturbance. © 2010 Society for Conservation Biology.

Eye pupil detection system using an ensemble of regression forest and fast radial symmetry transform with a near infrared camera

NASA Astrophysics Data System (ADS)

Jeong, Mira; Nam, Jae-Yeal; Ko, Byoung Chul

2017-09-01

In this paper, we focus on pupil center detection in various video sequences that include head poses and changes in illumination. To detect the pupil center, we first find four eye landmarks in each eye by using cascade local regression based on a regression forest. Based on the rough location of the pupil, a fast radial symmetric transform is applied using the previously found pupil location to rearrange the fine pupil center. As the final step, the pupil displacement is estimated between the previous frame and the current frame to maintain the level of accuracy against a false locating result occurring in a particular frame. We generated a new face dataset, called Keimyung University pupil detection (KMUPD), with infrared camera. The proposed method was successfully applied to the KMUPD dataset, and the results indicate that its pupil center detection capability is better than that of other methods and with a shorter processing time.

Little River revisited - thirty-five years after Hack and Goodlett

USGS Publications Warehouse

Osterkamp, W.R.; Hupp, C.R.; Schening, M.R.

1995-01-01

In possibly the first detailed study to relate geomorphology, vegetation, and hydrology at a watershed scale, Hack and Goodlett (1960) documented variation in the eastern forest with topographic positions of cove, side slope, and nose. The study also described effects on landforms and vegetation of a catastrophic flood that occurred in June, 1949. Field investigations, conducted nearly four decades later, review selected parts of the study by Hack and Goodlett (1960). Replicate data provide a basis to evaluate their interpretations, to document geomorphic change since the 1949 flood, and to identify vegetation change in uplands and bottomlands. Results suggest that change to hillslope landforms has been minor since 1949, but that changes have occurred, seemingly during flow events of 1952, 1955 and 1985. Change in areal extent of forest types was not detected. Change in the relative abundances of dominant species may have resulted from 20th century fire suppression. -from Authors

Macroecology of Australian Tall Eucalypt Forests: Baseline Data from a Continental-Scale Permanent Plot Network

PubMed Central

Wood, Sam W.; Prior, Lynda D.; Stephens, Helen C.; Bowman, David M. J. S.

2015-01-01

Tracking the response of forest ecosystems to climate change demands large (≥1 ha) monitoring plots that are repeatedly measured over long time frames and arranged across macro-ecological gradients. Continental scale networks of permanent forest plots have identified links between climate and carbon fluxes by monitoring trends in tree growth, mortality and recruitment. The relationship between tree growth and climate in Australia has been recently articulated through analysis of data from smaller forest plots, but conclusions were limited by (a) absence of data on recruitment and mortality, (b) exclusion of non-eucalypt species, and (c) lack of knowledge of stand age or disturbance histories. To remedy these gaps we established the Ausplots Forest Monitoring Network: a continental scale network of 48 1 ha permanent plots in highly productive tall eucalypt forests in the mature growth stage. These plots are distributed across cool temperate, Mediterranean, subtropical and tropical climates (mean annual precipitation 850 to 1900 mm per year; mean annual temperature 6 to 21°C). Aboveground carbon stocks (AGC) in these forests are dominated by eucalypts (90% of AGC) whilst non-eucalypts in the understorey dominated species diversity and tree abundance (84% of species; 60% of stems). Aboveground carbon stocks were negatively related to mean annual temperature, with forests at the warm end of the temperature range storing approximately half the amount of carbon as forests at the cool end of the temperature range. This may reflect thermal constraints on tree growth detected through other plot networks and physiological studies. Through common protocols and careful sampling design, the Ausplots Forest Monitoring Network will facilitate the integration of tall eucalypt forests into established global forest monitoring initiatives. In the context of projections of rapidly warming and drying climates in Australia, this plot network will enable detection of links between climate and growth, mortality and carbon dynamics of eucalypt forests. PMID:26368919

Canada lynx Lynx canadensis habitat and forest succession in northern Maine, USA

USGS Publications Warehouse

Hoving, C.L.; Harrison, D.J.; Krohn, W.B.; Jakubas, W.J.; McCollough, M.A.

2004-01-01

The contiguous United States population of Canada lynx Lynx canadensis was listed as threatened in 2000. The long-term viability of lynx populations at the southern edge of their geographic range has been hypothesized to be dependent on old growth forests; however, lynx are a specialist predator on snowshoe hare Lepus americanus, a species associated with early-successional forests. To quantify the effects of succession and forest management on landscape-scale (100 km2) patterns of habitat occupancy by lynx, we compared landscape attributes in northern Maine, USA, where lynx had been detected on snow track surveys to landscape attributes where surveys had been conducted, but lynx tracks had not been detected. Models were constructed a priori and compared using logistic regression and Akaike's Information Criterion (AIC), which quantitatively balances data fit and parsimony. In the models with the lowest (i.e. best) AIC, lynx were more likely to occur in landscapes with much regenerating forest, and less likely to occur in landscapes with much recent clearcut, partial harvest and forested wetland. Lynx were not associated positively or negatively with mature coniferous forest. A probabilistic map of the model indicated a patchy distribution of lynx habitat in northern Maine. According to an additional survey of the study area for lynx tracks during the winter of 2003, the model correctly classified 63.5% of the lynx occurrences and absences. Lynx were more closely associated with young forests than mature forests; however, old-growth forests were functionally absent from the landscape. Lynx habitat could be reduced in northern Maine, given recent trends in forest management practices. Harvest strategies have shifted from clearcutting to partial harvesting. If this trend continues, future landscapes will shift away from extensive regenerating forests and toward landscapes dominated by pole-sized and larger stands. Because Maine presently supports the only verified populations of this federally threatened species in the eastern United States, changes in forest management practices could affect recovery efforts throughout that region.

Inclusion of climatic variables in longleaf pine growth models

Treesearch

Jyoti N. Rayamajhi; John S. Kush

2006-01-01

The Regional Longleaf Growth Study was established by the USDA Forest Service to study the dynamics of naturally regenerated, even-aged longleaf pine (Pinus palustris Mill.) stands. The study accounts for growth change over time by adding new sets of plots in the youngest age class every 10 years. To detect possible changes in productivity with time...

Data Analytics for SAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, David Patrick; Calef, Matthew Thomas

We assess the ability of variants of anomalous change detection (ACD) to identify human activity associated with large outdoor music festivals as they are seen from synthetic aperture radar (SAR) imagery collected by the Sentinel-1 satellite constellation. We found that, with appropriate feature vectors, ACD using random-forest machine learning was most effective at identifying changes associated with the human activity.

Phenology satellite experiment

NASA Technical Reports Server (NTRS)

Dethier, B. E. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The detection of a phenological event (the Brown Wave-vegetation sensescence) for specific forest and crop types using ERTS-1 imagery is described. Data handling techniques including computer analysis and photointerpretation procedures are explained. Computer analysis of multspectral scanner digital tapes in all bands was used to give the relative changes of spectral reflectance with time of forests and specified crops. These data were obtained for a number of the twenty-four sites located within four north-south corridors across the United States. Analysis of ground observation photography and ERTS-1 imagery for sites in the Appalachian Corridor and Mississippi Valley Corridor indicates that the recession of vegetation development can be detected very well. Tentative conclusions are that specific phenological events such as crop maturity or leaf fall can be mapped for specific sites and possible for different regions. Preliminary analysis based on a number of samples in mixed deciduous hardwood stands indicates that as senescence proceeds both the rate of change and differences in color among species can be detected. The results to data show the feasibility of the development and refinement of phenoclimatic models.

Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and Challenges

NASA Technical Reports Server (NTRS)

Townshend, John R.; Masek, Jeffrey G.; Huang, ChengQuan; Vermote, Eric F.; Gao, Feng; Channan, Saurabh; Sexton, Joseph O.; Feng, Min; Narasimhan, Ramghuram; Kim, Dohyung;

Relative impact of previous disturbance history on the likelihood of additional disturbance in the Northern United States Forest Service USFS Region

NASA Astrophysics Data System (ADS)

Hernandez, A. J.

2015-12-01

The Landsat archive is increasingly being used to detect trends in the occurrence of forest disturbance. Beyond information about the amount of area affected, forest managers need to know if and how disturbance regimes change. The National Forest System (NFS) has developed a comprehensive plan for carbon monitoring that requires a detailed temporal mapping of forest disturbances across 75 million hectares. A long-term annual time series that shows the timing, extent, and type of disturbance beginning in 1990 and ending in 2011 has been prepared for several USFS Regions, including the Northern Region. Our mapping starts with an automated detection of annual disturbances using a time series of historical Landsat imagery. Automated detections are meticulously inspected, corrected and labeled using various USFS ancillary datasets. The resulting maps of verified disturbance show the timing and types are fires, harvests, insect activity, disease, and abiotic (wind, drought, avalanche) damage. Also, the magnitude of each change event is modeled in terms of the proportion of canopy cover lost. The sequence of disturbances for every pixel since 1990 has been consistently mapped and is available across the entirety of NFS. Our datasets contain sufficient information to describe the frequency of stand replacement, as well as how often disturbance results in only a partial loss of canopy. This information provides empirical insight into how an initial disturbance may predispose a stand to further disturbance, and it also show a climatic signal in the occurrence of processes such as fire and insect epidemics. Thus, we have the information to model the likelihood of occurrence of certain disturbances after a given event (i.e. if we have a fire in the past what does that do to the likelihood of occurrence of insects in the future). Here, we explore if previous disturbance history is a reliable predictor of additional disturbance in the future and we present results of applying logistic regression to obtain predicted probabilities of occurrence of additional disturbance types. We describe responses in additional disturbance and prominent trends for each major forest type.

Environmental changes, forest history and human impact in the southern part of Valdai Hills (European Russia) during the last 7000 years

NASA Astrophysics Data System (ADS)

Novenko, Elena; Tsyganov, Andery; Pisarchuk, Natalia; Kozlov, Daniil

2017-04-01

Understanding the long-term ecological dynamics of swampy boreal forest is essential for assessment of the possible responses and feedbacks of forest ecosystems to climate change and natural disturbance. The multi-proxy record from the Central Forest State Natural Biosphere Reserve (CFSNBR), locate on the South of Valdai Hills, provides important new data on the forest history, human impact, paludification dynamics and environmental changes in the central part of the East European Plain during the Holocene. The results of peat humification, pollen, plant macrofossil, micro charcoal and testate amoeba analyses from forest pealand show that between 7000 and 4000 cal yr BP the southern part of Valdai Hills was occupied by broad-leaved forests. Spruce occurred in forest communities as small admixture and gradually increased its abundance. After 4000 cal yr BP spruce rapidly become the main forest forming species, however broad-leaved trees took place in plant cover. Despite significant climatic fluctuation, mixed broad-leaved-spruce forests persisted in vegetation until 900 cal yr BP and then were replaced by waterlogged herbal spruce forests. The extensive Sphagnum spruce forests are recent plant communities and were formed during the last 100 years that could be explain by changes in water balance of the territory due to both climate and anthropogenic factors. According to reconstruction of Mid- and Late Holocene climate changes, warm and relatively dry period of the Holocene Thermal Maximum (7000-5500 cal yr BP) was followed by climate cooling that included several relatively cold phases at about 5000, 3500, 2000, 1200 cal yr BP and warm intervals at about 2600, 1500 and 900 cal yr BP. The distinct cooling was reconstructed between 800 and 400 cal yr BP, apparently, correlated with the Little Ice Age. Climate dynamics appeared as significant changes of environmental conditions at local ecosystem. Warming phases are indicated by high peat humification and organic matter content and relatively low peat accumulation rates. Peat deposits poses sign of several fire episodes. During cool and humid phases the rate of vertical and lateral peat growth increased, while degree of peat decomposition become lower. Dramatic changes in environmental conditions in the study area and changes in trends of ecosystem dynamics occurred during the last 400-350 year. The obtained results suggest evident climate warming, significant increase in surface wetness and increase fivefold of peat accumulation rates. During the last hundred years, the local wetness in the studied localities became considerably higher that promoted the growth of Sphagnum mosses and overall transformation of forest stands to Sphagnum spruce forests. Evidences of significant human impact on the area about 300-250 cal yr BP were detected by indicator species in pollen analysis and reconstructions of woodland coverage by BMA approach. The modern vegetation of the Reserve may develop from a plant cover with mosaic pattern that included not only the mature spruce forests but also secondary birch woodlands, meadows and agricultural lands. This study was supported by the Russian Science Foundation (Grant 16-17-10045).

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales-review and recommendations.

PubMed

Vanguelova, E I; Bonifacio, E; De Vos, B; Hoosbeek, M R; Berger, T W; Vesterdal, L; Armolaitis, K; Celi, L; Dinca, L; Kjønaas, O J; Pavlenda, P; Pumpanen, J; Püttsepp, Ü; Reidy, B; Simončič, P; Tobin, B; Zhiyanski, M

2016-11-01

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.

Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia

NASA Astrophysics Data System (ADS)

Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.

2018-03-01

Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class

Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data

NASA Astrophysics Data System (ADS)

Joshi, Neha; Mitchard, Edward TA; Woo, Natalia; Torres, Jorge; Moll-Rocek, Julian; Ehammer, Andrea; Collins, Murray; Jepsen, Martin R.; Fensholt, Rasmus

2015-03-01

Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial and temporal proximity. In the study area in Madre de Dios, Peru, 2.3% of land was found to be disturbed over three years, with a false positive rate of 0.3% of area. A low, but significant, detection rate of degradation from sparse and small-scale selective logging was achieved. Disturbances were most common along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter, and backscatter decrease, suggested that large-scale deforestation was likely in areas with initially low biomass, either naturally or since already under anthropogenic use. Further, backscatter increases following disturbance suggested that radar can be used to characterize successional disturbance dynamics, such as biomass accumulation in lands post-abandonment. The presented radar-based detection algorithm is spatially and temporally scalable, and can support monitoring degradation and deforestation in tropical rainforests with the use of products from ALOS-2 and the future SAOCOM and BIOMASS missions.

Alerts of forest disturbance from MODIS imagery

NASA Astrophysics Data System (ADS)

Hammer, Dan; Kraft, Robin; Wheeler, David

2014-12-01

This paper reports the methodology and computational strategy for a forest cover disturbance alerting system. Analytical techniques from time series econometrics are applied to imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to detect temporal instability in vegetation indices. The characteristics from each MODIS pixel's spectral history are extracted and compared against historical data on forest cover loss to develop a geographically localized classification rule that can be applied across the humid tropical biome. The final output is a probability of forest disturbance for each 500 m pixel that is updated every 16 days. The primary objective is to provide high-confidence alerts of forest disturbance, while minimizing false positives. We find that the alerts serve this purpose exceedingly well in Pará, Brazil, with high probability alerts garnering a user accuracy of 98 percent over the training period and 93 percent after the training period (2000-2005) when compared against the PRODES deforestation data set, which is used to assess spatial accuracy. Implemented in Clojure and Java on the Hadoop distributed data processing platform, the algorithm is a fast, automated, and open source system for detecting forest disturbance. It is intended to be used in conjunction with higher-resolution imagery and data products that cannot be updated as quickly as MODIS-based data products. By highlighting hotspots of change, the algorithm and associated output can focus high-resolution data acquisition and aid in efforts to enforce local forest conservation efforts.

Analysis of the spatial dynamics and drivers of forest cover change in the Lempa River Basin of El Salvador

NASA Astrophysics Data System (ADS)

Castaneda, Hector

This work studies the changes of forest cover that have happened in the Lempa River Basin of El Salvador during the period 1979-2003. Although historically the trend has been towards the loss of forest cover since colonial times, over the period of study a large increase in forest cover was detected. The main tool of evaluation was the analysis of LANDSAT satellite imagery. Images for the dates 1979, 1990-91, and 2003 were classified into forest and noon-forest land covers. Then the changes in land cover were analyzed to determine what were the social, geophysical and climatic drivers determining why and where these new forest appeared. The results indicate that there has been an overall increase in forest cover from 20% in 1979 to 43% in 2003. Although there has been extensive deforestation, this has happened mostly around the main urban centers within the basin. In the more rural and remote areas, the tendency has been towards a resurgence in forest cover. The increase in forest was found to be significantly related to remittances, inaccessibility to roads and markets, density of urban populations, poverty and the civil war of the 1980s. Among the geospatial factors that determined where deforestation and reforestation happened were distance to roads and urban centers, slope, elevation, land use capability, and irrigation potential. The results indicate that the tendency in the future will be towards further reforestation but at a slower rate. Although reforestation and deforestation happened simultaneously, there are clear differences in the spatial patterns that each of these phenomena follow. In terms of climate, it was found areas subjected to inter-annual rainfall extremes due to El Nino Southern Oscillation, particularly areas with low agricultural potential, were more likely to be abandoned and left to revert to forest than those with more stable rainfall. The results of this study support the hypothesis that El Salvador is undergoing a Forest Transition process, that is a recuperation of forest cover due to urbanization, migration and economic growth.

New Remote Sensing Methods for Labeling Disturbance Agents in Appalachian Forests

NASA Astrophysics Data System (ADS)

Hughes, M. J.; Hayes, D. J.

2014-12-01

Forests in the eastern United States are species rich and affected by a variety of disturbance agents such as fire, invasive insects, diseases, and storm events. Millions of hectares of forest are disturbed each year, altering the forest carbon sink and changing forest nutrient cycles. The magnitude and direction of these changes, though, can be different for different disturbance agents. For example, trees that burn in severe fire rapidly release stored carbon into the atmosphere whereas standing deadwood from insect attacks decompose slowly while atmospheric carbon is fixed in regenerating vegetation. The diagnosis and attribution of these processes require accurate and reliable estimates of the extent and frequency of different disturbance agents. Here, a new method is presented that classifies disturbance events identified using time-series analysis of Landsat TM imagery. The method exploits information about changes in the canopy heterogeneity as measured by several texture indices within forest patches. Classifiers were trained using data from the US Forest Service Aerial Detection Surveys and currently differentiate between fires, southern pine beetle, gypsy moth, hemlock woolly adelgid, beech bark disease, anthracnose, and storm events. In addition, the classifier returns a value of 'uncertain' when it is unable to make a clear determination, which is currently approximately 10% of identified disturbances. Classification accuracy for the remainder is 81%, though is variable between agents. For example, the classifier performs well in identifying southern pine beetle and gypsy moth affected areas, but poorly in identifying storms. Reliabilities are similar to accuracies for each agent. The results presented are the first yearly, regional-scale estimates of forest disturbance partitioned by disturbance agent. We find good correspondence with previously described patterns of disturbance and distribution, including direct observational evidence of their predicted periodicities over entire ecoregions. Such estimates are vital for forest monitoring and to better understand the role of the dynamic forest carbon sink in order to reduce uncertainty in atmospheric carbon models. Future work must focus on the inclusion of direct anthropogenic changes such as harvest and urbanization.

Oil palm plantation effects on water quality in Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Carlson, K. M.; Curran, L. M.

2011-12-01

Global demand for palm oil has stimulated a 7-fold increase in oil palm (Elaeis guineensis) plantation area in Indonesia since 1990. Expansion will continue as Indonesia plans to double current production by 2020. Oil palm fertilizers, effluent from oil palm mills, and erosion from land clearing and roads threaten river water quality near plantations. These rivers provide essential ecosystem services including water for drinking, cooking, and washing. Robust empirical measurements of plantation expansion impacts on water resources are necessary to discern the effects of agribusiness on local livelihoods and ecosystems. In Ketapang District, West Kalimantan, Indonesian Borneo, we evaluated the effects of land cover change on water quality by assessing water chemistry in streams draining four end-member watersheds ( ~600-1900 ha watershed-1): Logged forest, mixed agro-forest dominated by rubber and upland rice fallows, young oil palm forest (0-5 years), and old oil palm forest (10-15 years). To assess land cover change, we used CLASLite software to derive fractional cover from a time series (1989-2008) of Landsat data. Nearest neighbor classification and post-classification change detection yielded classes including primary forest, logged forest, secondary forest regrowth, smallholder agriculture, and oil palm. Stream water quality (temperature, dissolved oxygen, turbidity, optical chlorphyll, and pH) and quantity (discharge) were quantified with the YSI 6600-V2 sonde. The sonde was deployed in each stream for month-long intervals 2-3 times from 2009-2010. Such extended deployment captures episodic events such as intense storms and allows examination of interdiel dynamics by sampling continuously and at high frequency, every 10 minutes. We find that across the Ketapang District study region (~12,000 km2), oil palm has cleared mostly forests (49%) and agroforests (39%). What are the impacts of such land cover changes on water quality? Compared to forests and agroforests, streams draining oil palm show greater biological activity, as indicated by elevated pH and reduced dissolved oxygen levels. Moreover, turbidity is elevated in young oil palm plantations watersheds compared to forest, agroforest, and old oil palm land covers. We discuss the implications of these findings for communities and ecosystems.

Diverging climate trends in Mongolian taiga forests influence growth and regeneration of Larix sibirica

PubMed Central

Dulamsuren, Choimaa; Khishigjargal, Mookhor; Leuschner, Hanns Hubert; Leuschner, Christoph

2010-01-01

Central and semiarid north-eastern Asia was subject to twentieth century warming far above the global average. Since forests of this region occur at their drought limit, they are particularly vulnerable to climate change. We studied the regional variations of temperature and precipitation trends and their effects on tree growth and forest regeneration in Mongolia. Tree-ring series from more than 2,300 trees of Siberian larch (Larix sibirica) collected in four regions of Mongolia’s forest zone were analyzed and related to available weather data. Climate trends underlie a remarkable regional variation leading to contrasting responses of tree growth in taiga forests even within the same mountain system. Within a distance of a few hundred kilometers (140–490 km), areas with recently reduced growth and regeneration of larch alternated with regions where these parameters remained constant or even increased. Reduced productivity could be correlated with increasing summer temperatures and decreasing precipitation; improved growth conditions were found at increasing precipitation, but constant summer temperatures. An effect of increasing winter temperatures on tree-ring width or forest regeneration was not detectable. Since declines of productivity and regeneration are more widespread in the Mongolian taiga than the opposite trend, a net loss of forests is likely to occur in the future, as strong increases in temperature and regionally differing changes in precipitation are predicted for the twenty-first century. PMID:20571829

Diverging climate trends in Mongolian taiga forests influence growth and regeneration of Larix sibirica.

PubMed

Dulamsuren, Choimaa; Hauck, Markus; Khishigjargal, Mookhor; Leuschner, Hanns Hubert; Leuschner, Christoph

2010-08-01

Central and semiarid north-eastern Asia was subject to twentieth century warming far above the global average. Since forests of this region occur at their drought limit, they are particularly vulnerable to climate change. We studied the regional variations of temperature and precipitation trends and their effects on tree growth and forest regeneration in Mongolia. Tree-ring series from more than 2,300 trees of Siberian larch (Larix sibirica) collected in four regions of Mongolia's forest zone were analyzed and related to available weather data. Climate trends underlie a remarkable regional variation leading to contrasting responses of tree growth in taiga forests even within the same mountain system. Within a distance of a few hundred kilometers (140-490 km), areas with recently reduced growth and regeneration of larch alternated with regions where these parameters remained constant or even increased. Reduced productivity could be correlated with increasing summer temperatures and decreasing precipitation; improved growth conditions were found at increasing precipitation, but constant summer temperatures. An effect of increasing winter temperatures on tree-ring width or forest regeneration was not detectable. Since declines of productivity and regeneration are more widespread in the Mongolian taiga than the opposite trend, a net loss of forests is likely to occur in the future, as strong increases in temperature and regionally differing changes in precipitation are predicted for the twenty-first century.

Structure, diversity, and biophysical properties of old-growth forestsin the Klamath region, USA

USGS Publications Warehouse

van Mantgem, Phillip J.; Starr, Daniel A

2015-01-01

The diverse old-growth forests in Klamath region of northern California and southern Oregon provide valuable ecosystem services (e.g., maintaining watersheds, wildlife habitat, recreation), but may be vulnerable to a wide range of stressors, including invasive species, disrupted disturbance regimes, and climatic change. Yet our understanding of how forest structure in the Klamath region relates to the current physical environment is limited. Here we provide present-day benchmarks for old-growth forest structure across a climatic gradient ranging from coastal to dry interior sites. We established 16 large (1 ha) forest plots where all stems > 5 cm in diameter were identified to species and mapped. Climate across these sites was highly variable, with estimated actual evapotranspiration correlated to several basic measures of forest structure, including plot basal area, stem size-class inequality, tree species diversity and, to a lesser extent, tree species richness. Analyses of the spatial arrangement of stems indicated a high degree of non-uniformity, with 75% of plots showing significant stem clumping at small spatial scales (0 to 10 m). Downscaled predictions of future site water balance suggest changes will be dominated by rapidly increasing climatic water deficit (D, a biologically meaningful index of drought). While these plots give a picture of current conditions, continued monitoring of these stands is needed to describe forest dynamics and to detect forest responses to ongoing and future stressors.

Merging National Forest and National Forest Health Inventories to Obtain an Integrated Forest Resource Inventory – Experiences from Bavaria, Slovenia and Sweden

PubMed Central

Kovač, Marko; Bauer, Arthur; Ståhl, Göran

2014-01-01

Backgrounds, Material and Methods To meet the demands of sustainable forest management and international commitments, European nations have designed a variety of forest-monitoring systems for specific needs. While the majority of countries are committed to independent, single-purpose inventorying, a minority of countries have merged their single-purpose forest inventory systems into integrated forest resource inventories. The statistical efficiencies of the Bavarian, Slovene and Swedish integrated forest resource inventory designs are investigated with the various statistical parameters of the variables of growing stock volume, shares of damaged trees, and deadwood volume. The parameters are derived by using the estimators for the given inventory designs. The required sample sizes are derived via the general formula for non-stratified independent samples and via statistical power analyses. The cost effectiveness of the designs is compared via two simple cost effectiveness ratios. Results In terms of precision, the most illustrative parameters of the variables are relative standard errors; their values range between 1% and 3% if the variables’ variations are low (s%<80%) and are higher in the case of higher variations. A comparison of the actual and required sample sizes shows that the actual sample sizes were deliberately set high to provide precise estimates for the majority of variables and strata. In turn, the successive inventories are statistically efficient, because they allow detecting the mean changes of variables with powers higher than 90%; the highest precision is attained for the changes of growing stock volume and the lowest for the changes of the shares of damaged trees. Two indicators of cost effectiveness also show that the time input spent for measuring one variable decreases with the complexity of inventories. Conclusion There is an increasing need for credible information on forest resources to be used for decision making and national and international policy making. Such information can be cost-efficiently provided through integrated forest resource inventories. PMID:24941120

Mapping deforestation and urban expansion in Freetown, Sierra Leone, from pre- to post-war economic recovery.

PubMed

Mansaray, Lamin R; Huang, Jingfeng; Kamara, Alimamy A

2016-08-01

Freetown, the capital of Sierra Leone has experienced vast land-cover changes over the past three decades. In Sierra Leone, however, availability of updated land-cover data is still a problem even for environmental managers. This study was therefore, conducted to provide up-to-date land-cover data for Freetown. Multi-temporal Landsat data at 1986, 2001, and 2015 were obtained, and a maximum likelihood supervised classification was employed. Eight land-cover classes or categories were recognized as follows: water, wetland, built-up, dense forest, sparse forest, grassland, barren, and mangrove. Land-cover changes were mapped via post-classification change detection. The persistence, gain, and loss of each land-cover class, and selected land conversions were also quantified. An overall classification accuracy of 87.3 % and a Kappa statistic of 0.85 were obtained for the 2015 map. From 1986 to 2015, water, built-up, grassland, and barren had net gains, whereas forests, wetlands, and mangrove had net loses. Conversion analyses among forests, grassland, and built-up show that built-up had targeted grassland and avoided forests. This study also revealed that, the overall land-cover change at 2001-2015 was higher (28.5 %) than that recorded at 1986-2001 (20.9 %). This is attributable to the population increase in Freetown and the high economic growth and infrastructural development recorded countrywide after the civil war. In view of the rapid land-cover change and its associated environmental impacts, this study recommends the enactment of policies that would strike a balance between urbanization and environmental sustainability in Freetown.

Use of a forest sapwood area index to explain long-term variability in mean annual evapotranspiration and streamflow in moist eucalypt forests

NASA Astrophysics Data System (ADS)

Benyon, Richard G.; Lane, Patrick N. J.; Jaskierniak, Dominik; Kuczera, George; Haydon, Shane R.

2015-07-01

Mean sapwood thickness, measured in fifteen 73 year old Eucalyptus regnans and E. delegatensis stands, correlated strongly with forest overstorey stocking density (R2 0.72). This curvilinear relationship was used with routine forest stocking density and basal area measurements to estimate sapwood area of the forest overstorey at various times in 15 research catchments in undisturbed and disturbed forests located in the Great Dividing Range, Victoria, Australia. Up to 45 years of annual precipitation and streamflow data available from the 15 catchments were used to examine relationships between mean annual loss (evapotranspiration estimated as mean annual precipitation minus mean annual streamflow), and sapwood area. Catchment mean sapwood area correlated strongly (R2 0.88) with catchment mean annual loss. Variation in sapwood area accounted for 68% more variation in mean annual streamflow than precipitation alone (R2 0.90 compared with R2 0.22). Changes in sapwood area accounted for 96% of the changes in mean annual loss observed after forest thinning or clear-cutting and regeneration. We conclude that forest inventory data can be used reliably to predict spatial and temporal variation in catchment annual losses and streamflow in response to natural and imposed disturbances in even-aged forests. Consequently, recent advances in mapping of sapwood area using airborne light detection and ranging will enable high resolution spatial and temporal mapping of mean annual loss and mean annual streamflow over large areas of forested catchment. This will be particularly beneficial in management of water resources from forested catchments subject to disturbance but lacking reliable long-term (years to decades) streamflow records.

Inferences of Present and Past Changes at Isolated Enclaves and Matrix of Savannas by Carbon Isotopes in a Transitional Forest-Savanna Area in Northern Amazonia

NASA Astrophysics Data System (ADS)

Couto-Santos, F. R.; Luizao, F. J.; Camargo, P. B.

2013-12-01

The evolutionary history of savannas influenced by short term climate cycles, during the Quaternary Period, could prompt variations in forest cover often related to movements of the forest-savanna boundary. In this study we investigated current and past changes in the structure of vegetation and the origins of savannas of different natures in a biogeographically and climatic transitional forest-savanna area in northern Amazonia. Variations in the isotopic composition of soil organic matter (δ13C) from surface soils (0-10 cm) along forest-savanna boundaries, detected by a sigmoidal non-linear function, were used to identify current changes in vegetation, while past changes were inferred by discontinuities in the evolution of δ13C with soil depth using piecewise regression associated with radiocarbon dating (14C). By comparing small isolated savanna enclaves inside a strictly protected nature reserve (ESEC Maracá) with its outskirts unprotected continuous savanna matrix, we found that origins and the patterns of dynamics were distinct between these areas and did not respond in the same way to climate change and fire events, either in the last decades or during the Holocene. The stability of the present boundaries of the surrounding savanna matrix reflects the resilience of the transitional forests under a recent intensified fire regime and favorable climate, while the deep forest soil isotopic signal indicated a forest shrinkage of at least 70 m occurring since its origin in early Holocene until 780 years BP associated with a climate drier than the current one. Contrarily, the protected enclaves inside ESEC Maracá, remained stable since the middle Holocene, suggesting a non-anthropogenic origin related to soil edaphic conditions, but with recent dynamics of advancing forest by 8 m century-1 favored by current climate and lacking fire events. A detailed understanding of the origins of savannas of distinct natures and the way they are affected by climate and fire events provided by carbon isotopes and radiocarbon analysis in both short and long term could help predict the future of these ecosystems under the envisaged climate change scenario. Financial Support: Boticário Group Foundation (Fundação Grupo Boticário); National Council for Scientific and Technological Development (CNPq); The Minas Gerais State Research Foundation (FAPEMIG).

Structural effects of liana presence in secondary tropical dry forests using ground LiDAR

NASA Astrophysics Data System (ADS)

Sánchez-Azofeifa, A.; Portillo-Quintero, C.; Durán, S. M.

2015-10-01

Lianas, woody vines, are a key component of tropical forest because they may reduce carbon storage potential. Lianas are increasing in density and biomass in tropical forests, but it is unknown what the potential consequences of these increases are for forest dynamics. Lianas may proliferate in disturbed areas, such as regenerating forests, but little is known about the role of lianas in secondary succession. In this study, we evaluated the potential of the ground LiDAR to detect differences in the vertical structure of stands of different ages with and without lianas in tropical dry forests. Specifically, we used a terrestrial laser scanner called VEGNET to assess whether liana presence influences the vertical signature of stands of different ages, and whether successional trajectories as detected by the VEGNET could be altered by liana presence. We deployed the VEGNET ground LiDAR system in 15 secondary forests of different ages early (21 years old since land abandonment), intermediate (32-35 years old) and late stages (> 80 years old) with and without lianas. We compared laser-derived vegetation components such as Plant Area Index (PAI), plant area volume density (PAVD), and the radius of gyration (RG) across forest stands between liana and no-liana treatments. In general forest stands without lianas show a clearer distinction of vertical strata and the vertical height of accumulated PAVD. A significant increase of PAI was found from intermediate to late stages in stands without lianas, but in stands where lianas were present there was not a significant trend. This suggests that lianas may be influencing successional trajectories in secondary forests, and these effects can be captured by terrestrial laser scanners such as the VEGNET. This research contributes to estimate the potential effects of lianas in secondary dry forests and highlight the role of ground LiDAR to monitor structural changes in tropical forests due to liana presence.

Vertical Structure of Phyllosphere Fungal Communities in a Tropical Forest in Thailand Uncovered by High-Throughput Sequencing.

PubMed

Izuno, Ayako; Kanzaki, Mamoru; Artchawakom, Taksin; Wachrinrat, Chongrak; Isagi, Yuji

2016-01-01

Phyllosphere fungi harbor a tremendous species diversity and play important ecological roles. However, little is known about their distribution patterns within forest ecosystems. We examined how species diversity and community composition of phyllosphere fungi change along a vertical structure in a tropical forest in Thailand. Fungal communities in 144 leaf samples from 19 vertical layers (1.28-34.4 m above ground) of 73 plant individuals (27 species) were investigated by metabarcoding analysis using Ion Torrent sequencing. In total, 1,524 fungal operational taxonomic units (OTUs) were detected among 890,710 reads obtained from the 144 leaf samples. Taxonomically diverse fungi belonging to as many as 24 orders of Ascomycota and 21 orders of Basidiomycota were detected, most of which inhabited limited parts of the lowest layers closest to the forest floor. Species diversity of phyllosphere fungi was the highest in the lowest layers closest to the forest floor, decreased with increasing height, and lowest in the canopy; 742 and 55 fungal OTUs were detected at the lowest and highest layer, respectively. On the layers close to the forest floor, phyllosphere fungal communities were mainly composed of low frequency OTUs and largely differentiated among plant individuals. Conversely, in the canopy, fungal communities consisted of similar OTUs across plant individuals, and as many as 86.1%-92.7% of the OTUs found in the canopy (≥22 m above ground) were also distributed in the lower layers. Overall, our study showed the variability of phyllosphere fungal communities along the vertical gradient of plant vegetation and environmental conditions, suggesting the significance of biotic and abiotic variation for the species diversity of phyllosphere fungi.

Vegetation indicators of transformation in the urban forest ecosystems of "Kuzminki-Lyublino" Park

NASA Astrophysics Data System (ADS)

Buyvolova, Anna; Trifonova, Tatiana; Bykova, Elena

2017-04-01

Forest ecosystems in the city are at the same time a component of its natural environment and part of urban developmental planning. It imposes upon urban forests a large functional load, both environmental (formation of environment, air purification, noise pollution reducing, etc.) and social (recreational, educational) which defines the special attitude to their management and study. It is not a simple task to preserve maximum accessibility to the forest ecosystems of the large metropolises with a minimum of change. The urban forest vegetates in naturally formed soil, it has all the elements of a morphological structure (canopy layers), represented by natural species of the zonal vegetation. Sometimes it is impossible for a specialist to distinguish between an urban forest and a rural one. However, the urban forests are changing, being under the threat of various negative influences of the city, of which pollution is arguably the most significant. This article presents some indicators of structural changes to the plant communities, which is a response of forest ecosystems to an anthropogenic impact. It is shown that the indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The assessment of the impact of the urban environment on the state of vegetation in the "Kuzminki-Lyublino" Natural-Historical Park was conducted in two key areas least affected by anthropogenic impacts under different plant communities represented by complex pine and birch forests and in similar forest types in the Prioksko-Terrasny Biosphere Reserve. The selection of pine forests as a model is due to the fact that, according to some scientists, pine (Pinus Sylvestris L.), a very ductile and widespread species, is a sensitive indicator of anthropogenic burden, responding to the impact of defoliation and needles discoloration, and survives even at fairly high levels of pollution. The vegetation cover is one of the most dynamic components of the ecosystem and under the conditions of urban existence it is subject to transformation. The indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The further study of plant communities with a view to identifying indicators of transformation in urban environmental conditions will help for the early detection of reversible changes in the ecosystems of urban forests and the development of rational urban forest care technologies.

Application of Remotely Piloted Vehicle (RPV) in monitoring and detecting watershed land use change and problem areas

Treesearch

Long-Ming Huang

2000-01-01

Improper cultivation of steep mountainous areas in Taiwan contributes to serious erosion and landslides. Regular patrol, detection, and administration of these problem areas has been an extremely difficult due to the steep and dangerous terrain of many of the forested watersheds in Taiwan. A remotely piloted vehicle (RPV) has been developed for various civil and...

Comparison of proposed survey procedures for detection of forest carnivores

Treesearch

Kerry R. Foresman; Dean E. Pearson

1998-01-01

American marten (Martes americana), fisher (M. pennanti), wolverine (Gulo gulo), and lynx (Lynx lynx) are forest carnivores believed threatened by disturbance of late-successional forests. To manage forested ecosystems for these species, effective methods for their detection must be available. Recently, the U.S. Forest Service proposed standardized survey procedures...

A Simple and Effective Image Normalization Method to Monitor Boreal Forest Change in a Siberian Burn Chronosequence across Sensors and across Time

NASA Astrophysics Data System (ADS)

Chen, X.; Vierling, L. A.; Deering, D. W.

2004-12-01

Satellite data offer unique perspectives for monitoring and quantifying land cover change, however, the radiometric consistency among co-located multi-temporal images is difficult to maintain due to variations in sensors and atmosphere. To detect accurate landscape change using multi-temporal images, we developed a new relative radiometric normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on 9 June 1990 (Landsat 4), 20 June 2000, and 26 August 2001 (Landsat 7) for analyses over boreal forests near the Siberian city of Krasnoyarsk. Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Reduced Simple Ratio (RSR) were investigated in the normalization study. The temporally invariant cluster (TIC) centers were identified through a point density map of the base image and the target image and a normalization regression line was created through all TIC centers. The target image digital data were then converted using the regression function so that the two images could be compared using the resulting common radiometric scale. We found that EVI was very sensitive to vegetation structure and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. NDVI was a very effective vegetation index to reduce the influence of shadow, while EVI was very sensitive to shadowing. After normalization, correlations of NDVI and EVI with field collected total Leaf Area Index (LAI) data in 2000 and 2001 were significantly improved; the r-square values in these regressions increased from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI ¡°cancellation effect¡± where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared with some previous relative normalization methods, this new method can avoid subjective selection of a normalization regression line. It does not require high level programming and statistical analyses, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare.

Aerodynamic roughness: A simple and alternative metric to detect the seasonality of canopy structure using flux-tower data

NASA Astrophysics Data System (ADS)

Chu, H.; Baldocchi, D. D.

2017-12-01

FLUXNET - the global network of eddy covariance tower sites provides valuable datasets of the direct and in situ measurements of fluxes and ancillary variables that are used across different disciplines and applications. Aerodynamic roughness (i.e., roughness length, zero plane displacement height) are one of the potential parameters that can be derived from flux-tower data and are crucial for the applications of land surface models and flux footprint models. As aerodynamic roughness are tightly associated with canopy structures (e.g., canopy height, leaf area), such parameters could potentially serve as an alternative metric for detecting the change of canopy structure (e.g., change of leaf areas in deciduous ecosystems). This study proposes a simple approach for deriving aerodynamic roughness from flux-tower data, and tests their suitability and robustness in detecting the seasonality of canopy structure. We run tests across a broad range of deciduous forests, and compare the seasonality derived from aerodynamic roughness (i.e., starting and ending dates of leaf-on period and peak-foliage period) against those obtained from remote sensing or in situ leaf area measurements. Our findings show aerodynamic roughness generally captures the timing of changes of leaf areas in deciduous forests. Yet, caution needs to be exercised while interpreting the absolute values of the roughness estimates.

Road-networks, a practical indicator of human impacts on biodiversity in Tropical forests

NASA Astrophysics Data System (ADS)

Hosaka, T.; Yamada, T.; Okuda, T.

2014-02-01

Tropical forests sustain the most diverse plants and animals in the world, but are also being lost most rapidly. Rapid assessment and monitoring using remote sensing on biodiversity of tropical forests is needed to predict and evaluate biodiversity loss by human activities. Identification of reliable indicators of forest biodiversity and/or its loss is an urgent issue. In the present paper, we propose the density of road networks in tropical forests can be a good and practical indicator of human impacts on biodiversity in tropical forests through reviewing papers and introducing our preliminary survey in peninsular Malaysia. Many previous studies suggest a strong negative impact of forest roads on biodiversity in tropical rainforests since they changes microclimate, soil properties, drainage patterns, canopy openness and forest accessibility. Moreover, our preliminary survey also showed that even a narrow logging road (6 m wide) significantly lowered abundance of dung beetles (well-known bio-indicator in biodiversity survey in tropical forests) near the road. Since these road networks are readily to be detected with remote sensing approach such as aerial photographs and Lider, regulation and monitoring of the road networks using remote sensing techniques is a key to slow down the rate of biodiversity loss due to forest degradation in tropical forests.

A Multisensor Machine Vision System for Hardwood Defect Detection

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

1990-01-01

Over the next decade there is going to be a substantial change in the way forest products manufacturing industries do business. The economic forces responsible for these changes include the heightened economic competition that will result from the new world economy and the continued increase in the cost of both raw material and labor. These factors are going to force...

Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA

Treesearch

Timothy J. Brady; Vicente J. Monleon; Andrew N. Gray

2010-01-01

We propose using future vascular plant abundances as indicators of future climate in a way analogous to the reconstruction of past environments by many palaeoecologists. To begin monitoring future short-term climate changes in the forests of Oregon and Washington, USA, we developed a set of transfer functions for a present-day calibration set consisting of climate...

Leaf Area Influence on Surface Layer in a Deciduous Forest. Part 2; Detecting Leaf Area and Surface Resistance During Transition Seasons

NASA Technical Reports Server (NTRS)

Sakai, Ricardo K.; Fitzjarrald, David R.; Moore, Kathleen E.; Sicker, John W.; Munger, Willian J.; Goulden, Michael L.; Wofsy, Steven C.

1996-01-01

Temperate deciduous forest exhibit dramatic seasonal changes in surface exchange properties following on the seasonal changes in leaf area index. The canopy resistance to water vapor transport r(sub c) decreased abruptly at leaf emergence in each year but then also continued to decrease slowly during the remaining growing season due to slowly increasing LAI. Canopy resistance and PAR-albedo (albedo from photosynthetically active radiation) began to increase about one month before leaf fall with the diminishment of CO2 gradient above the canopy as well. At this time evaporation begun to be controlled as if the canopy were leafless.

Evaluating an Automated Approach for Monitoring Forest Disturbances in the Pacific Northwest from Logging, Fire and Insect Outbreaks with Landsat Time Series Data

NASA Technical Reports Server (NTRS)

R.Neigh, Christopher S.; Bolton, Douglas K.; Williams, Jennifer J.; Diabate, Mouhamad

2014-01-01

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometers (AVHRRs). To understand the causal factors of this decline, we evaluated an automated classification method developed for Landsat time series stacks (LTSS) to map forest change. This method included: (1) multiple disturbance index thresholds; and (2) a spectral trajectory-based image analysis with multiple confidence thresholds. We produced 48 maps and verified their accuracy with air photos, monitoring trends in burn severity data and insect aerial detection survey data. Area-based accuracy estimates for change in forest cover resulted in producer's and user's accuracies of 0.21 +/- 0.06 to 0.38 +/- 0.05 for insect disturbance, 0.23 +/- 0.07 to 1 +/- 0 for burned area and 0.74 +/- 0.03 to 0.76 +/- 0.03 for logging. We believe that accuracy was low for insect disturbance because air photo reference data were temporally sparse, hence missing some outbreaks, and the annual anniversary time step is not dense enough to track defoliation and progressive stand mortality. Producer's and user's accuracy for burned area was low due to the temporally abrupt nature of fire and harvest with a similar response of spectral indices between the disturbance index and normalized burn ratio. We conclude that the spectral trajectory approach also captures multi-year stress that could be caused by climate, acid deposition, pathogens, partial harvest, thinning, etc. Our study focused on understanding the transferability of previously successful methods to new ecosystems and found that this automated method does not perform with the same accuracy in Pacific Northwest forests. Using a robust accuracy assessment, we demonstrate the difficulty of transferring change attribution methods to other ecosystems, which has implications for the development of automated detection/attribution approaches. Widespread disturbance was found within AVHRR-negative anomalies, but identifying causal factors in LTSS with adequate mapping accuracy for fire and insects proved to be elusive. Our results provide a background framework for future studies to improve methods for the accuracy assessment of automated LTSS classifications.

Epiphytic lichens as sentinels for heavy metal pollution at forest ecosystems (central Italy).

PubMed

Loppi, Stefano; Pirintsos, Stergios Arg

2003-01-01

The results of a study using epiphytic lichens (Parmelia caperata) as sentinels for heavy metal deposition at six selected forest ecosystems of central Italy are reported. The woods investigated are characterized by holm oak (Quercus ilex), turkey oak (Quercus cerris) and beech (Fagus sylvatica) and represent the typical forest ecosystems of central Italy at low, medium and high elevations, respectively. The results showed that levels of heavy metals in lichens were relatively low and consequently no risk of heavy metal air pollution is expected for the six forest ecosystems investigated. However, for two of them there are indications of a potential risk: the beech forest of Vallombrosa showed signs of contamination by Pb as a consequence of vehicle traffic due to the rather high touristic pressure in the area, and the holm oak forest of Cala Violina showed transboundary pollution by Mn, Cr and Ni originating from the steel industry in Piombino. Epiphytic lichens proved to be very effective as an early warning system to detect signs of a changing environment at forest ecosystems.

Applications of ERTS-1 data to landscape change in eastern Tennessee

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The analysis of landscape change in eastern Tennessee from ERTS-1 data is being derived from three avenues of experimentation and analysis: (1) a multi-stage sampling procedure utilizing ground and aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures and comparisons for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions. Significant results include: maps of strip mining changes and forest inventory, watershed identification and delimitation, and agricultural regions derived from spring plowing patterns appearing on the ERTS-1 imagery.

Comparing the response of birds and butterflies to vegetation-based mountain ecotones using boundary detection approaches.

PubMed

Kent, Rafi; Levanoni, Oded; Banker, Eran; Pe'er, Guy; Kark, Salit

2013-01-01

Mountains provide an opportunity to examine changes in biodiversity across environmental gradients and areas of transition (ecotones). Mountain ecotones separate vegetation belts. Here, we aimed to examine whether transition areas for birds and butterflies spatially correspond with ecotones between three previously described altitudinal vegetation belts on Mt. Hermon, northern Israel. These include the Mediterranean Maquis, xero-montane open forest and Tragacanthic mountain steppe vegetation belts. We sampled the abundance of bird and butterfly species in 34 sampling locations along an elevational gradient between 500 and 2200 m. We applied wombling, a boundary-detection technique, which detects rapid changes in a continuous variable, in order to locate the transition areas for bird and butterfly communities and compare the location of these areas with the location of vegetation belts as described in earlier studies of Mt. Hermon. We found some correspondence between the areas of transition of both bird and butterfly communities and the ecotones between vegetation belts. For birds and butterflies, important transitions occurred at the lower vegetation ecotone between Mediterranean maquis and the xero-montane open forest vegetation belts, and between the xero-montane open forest and the mountain steppe Tragacanthic belts. While patterns of species turnover with elevation were similar for birds and butterflies, the change in species richness and diversity with elevation differed substantially between the two taxa. Birds and butterflies responded quite similarly to the elevational gradient and to the shift between vegetation belts in terms of species turnover rates. While the mechanisms generating these patterns may differ, the resulting areas of peak turnover in species show correspondence among three different taxa (plants, birds and butterflies).

Detecting and monitoring deforestation and forest degradation: Issues and obstacles for Southeast Asia

Treesearch

Douglas Muchoney; Sharon Hamann

2013-01-01

Forest degradation can be defined as the loss of forest volume, biomass and/or forest productivity caused by natural or human influences. Achieving Reduced Emissions from Deforestation and Forest Degradation (REDD+) requires that deforestation and degradation can be efficiently, reliably, and cost-effectively detected and quantified, often where ground and aerial...

Deforestation change detection in North Korea between 1999 and 2008 using multi temporal satellite image

NASA Astrophysics Data System (ADS)

KIM, K. M.

2017-12-01

After the mid-1990s, North Korea has gone through a hard time of shortage of food and fuel due to the large scale flood and landslide. This became a vicious circle, which has kept accelerating the deforestation in North Korea. This study aims to analyze the change of deforestation in North Korea using two different seasonal satellite images of Landsat 5-TM and SPOT-5 between 1999 and 2008. The Land cover was classified into 6 categories: forest, cropland, grassland, bare land, built area and water body. And the deforested and degraded forest area was extracted considering forest land boundary and classified into 3 categories: the cultivated, the unstocked forest land and the bare mountain. For the all classification process, unsupervised classification method was used since North Korea is inaccessible area. The results of the study showed that the stocked forest area has decreased 1,379,000 ha compared with those in 1999, whereas the deforested and degraded forest area has increased 1,207,000 ha in 2008. The increase of 880,000 ha in the unstocked forest land was the biggest expansion among 3 categories of the deforested and degraded forest area during 9 yrs. It is resulted from an increase of firewood usage, which is presumably owing to the severe shortage of fuel and food. I look forward for the outcome of this study to being used as baseline data for inter-Korean forest cooperation. Especially, it is expected to serve as important input data for the potential REDD project site selection with results of the 3rd forest monitoring(2018) of North Korea.

Standardized Assessment of Biodiversity Trends in Tropical Forest Protected Areas: The End Is Not in Sight.

PubMed

Beaudrot, Lydia; Ahumada, Jorge A; O'Brien, Timothy; Alvarez-Loayza, Patricia; Boekee, Kelly; Campos-Arceiz, Ahimsa; Eichberg, David; Espinosa, Santiago; Fegraus, Eric; Fletcher, Christine; Gajapersad, Krisna; Hallam, Chris; Hurtado, Johanna; Jansen, Patrick A; Kumar, Amit; Larney, Eileen; Lima, Marcela Guimarães Moreira; Mahony, Colin; Martin, Emanuel H; McWilliam, Alex; Mugerwa, Badru; Ndoundou-Hockemba, Mireille; Razafimahaimodison, Jean Claude; Romero-Saltos, Hugo; Rovero, Francesco; Salvador, Julia; Santos, Fernanda; Sheil, Douglas; Spironello, Wilson R; Willig, Michael R; Winarni, Nurul L; Zvoleff, Alex; Andelman, Sandy J

2016-01-01

Extinction rates in the Anthropocene are three orders of magnitude higher than background and disproportionately occur in the tropics, home of half the world's species. Despite global efforts to combat tropical species extinctions, lack of high-quality, objective information on tropical biodiversity has hampered quantitative evaluation of conservation strategies. In particular, the scarcity of population-level monitoring in tropical forests has stymied assessment of biodiversity outcomes, such as the status and trends of animal populations in protected areas. Here, we evaluate occupancy trends for 511 populations of terrestrial mammals and birds, representing 244 species from 15 tropical forest protected areas on three continents. For the first time to our knowledge, we use annual surveys from tropical forests worldwide that employ a standardized camera trapping protocol, and we compute data analytics that correct for imperfect detection. We found that occupancy declined in 22%, increased in 17%, and exhibited no change in 22% of populations during the last 3-8 years, while 39% of populations were detected too infrequently to assess occupancy changes. Despite extensive variability in occupancy trends, these 15 tropical protected areas have not exhibited systematic declines in biodiversity (i.e., occupancy, richness, or evenness) at the community level. Our results differ from reports of widespread biodiversity declines based on aggregated secondary data and expert opinion and suggest less extreme deterioration in tropical forest protected areas. We simultaneously fill an important conservation data gap and demonstrate the value of large-scale monitoring infrastructure and powerful analytics, which can be scaled to incorporate additional sites, ecosystems, and monitoring methods. In an era of catastrophic biodiversity loss, robust indicators produced from standardized monitoring infrastructure are critical to accurately assess population outcomes and identify conservation strategies that can avert biodiversity collapse.

Standardized Assessment of Biodiversity Trends in Tropical Forest Protected Areas: The End Is Not in Sight

PubMed Central

O'Brien, Timothy; Alvarez-Loayza, Patricia; Boekee, Kelly; Campos-Arceiz, Ahimsa; Eichberg, David; Espinosa, Santiago; Fegraus, Eric; Fletcher, Christine; Gajapersad, Krisna; Hallam, Chris; Hurtado, Johanna; Jansen, Patrick A.; Kumar, Amit; Larney, Eileen; Lima, Marcela Guimarães Moreira; Mahony, Colin; Martin, Emanuel H.; McWilliam, Alex; Mugerwa, Badru; Ndoundou-Hockemba, Mireille; Razafimahaimodison, Jean Claude; Romero-Saltos, Hugo; Rovero, Francesco; Salvador, Julia; Santos, Fernanda; Sheil, Douglas; Spironello, Wilson R.; Willig, Michael R.; Winarni, Nurul L.; Zvoleff, Alex; Andelman, Sandy J.

2016-01-01

Extinction rates in the Anthropocene are three orders of magnitude higher than background and disproportionately occur in the tropics, home of half the world’s species. Despite global efforts to combat tropical species extinctions, lack of high-quality, objective information on tropical biodiversity has hampered quantitative evaluation of conservation strategies. In particular, the scarcity of population-level monitoring in tropical forests has stymied assessment of biodiversity outcomes, such as the status and trends of animal populations in protected areas. Here, we evaluate occupancy trends for 511 populations of terrestrial mammals and birds, representing 244 species from 15 tropical forest protected areas on three continents. For the first time to our knowledge, we use annual surveys from tropical forests worldwide that employ a standardized camera trapping protocol, and we compute data analytics that correct for imperfect detection. We found that occupancy declined in 22%, increased in 17%, and exhibited no change in 22% of populations during the last 3–8 years, while 39% of populations were detected too infrequently to assess occupancy changes. Despite extensive variability in occupancy trends, these 15 tropical protected areas have not exhibited systematic declines in biodiversity (i.e., occupancy, richness, or evenness) at the community level. Our results differ from reports of widespread biodiversity declines based on aggregated secondary data and expert opinion and suggest less extreme deterioration in tropical forest protected areas. We simultaneously fill an important conservation data gap and demonstrate the value of large-scale monitoring infrastructure and powerful analytics, which can be scaled to incorporate additional sites, ecosystems, and monitoring methods. In an era of catastrophic biodiversity loss, robust indicators produced from standardized monitoring infrastructure are critical to accurately assess population outcomes and identify conservation strategies that can avert biodiversity collapse. PMID:26785119

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Norman Steve; Christie, William

2014-01-01

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Landscape dynamics in Mediterranean oak forests under global change: understanding the role of anthropogenic and environmental drivers across forest types.

PubMed

Acácio, Vanda; Dias, Filipe S; Catry, Filipe X; Rocha, Marta; Moreira, Francisco

2017-03-01

The Mediterranean region is projected to be extremely vulnerable to global change, which will affect the distribution of typical forest types such as native oak forests. However, our understanding of Mediterranean oak forest responses to future conditions is still very limited by the lack of knowledge on oak forest dynamics and species-specific responses to multiple drivers. We compared the long-term (1966-2006) forest persistence and land cover change among evergreen (cork oak and holm oak) and deciduous oak forests and evaluated the importance of anthropogenic and environmental drivers on observed changes for Portugal. We used National Forest Inventories to quantify the changes in oak forests and explored the drivers of change using multinomial logistic regression analysis and an information theoretical approach. We found distinct trends among oak forest types, reflecting the differences in oak economic value, protection status and management schemes: cork oak forests were the most persistent (62%), changing mostly to pines and eucalypt; holm oak forests were less persistent (53.2%), changing mostly to agriculture; and deciduous oak forests were the least persistent (45.7%), changing mostly to shrublands. Drivers of change had distinct importance across oak forest types, but drivers from anthropogenic origin (wildfires, population density, and land accessibility) were always among the most important. Climatic extremes were also important predictors of oak forest changes, namely extreme temperatures for evergreen oak forests and deficit of precipitation for deciduous oak forests. Our results indicate that under increasing human pressure and forecasted climate change, evergreen oak forests will continue declining and deciduous oak forests will be replaced by forests dominated by more xeric species. In the long run, multiple disturbances may change competitive dominance from oak forests to pyrophytic shrublands. A better understanding of forest dynamics and the inclusion of anthropogenic drivers on models of vegetation change will improve predicting the future of Mediterranean oak forests. © 2016 John Wiley & Sons Ltd.

Evaluating the effectiveness of conservation and development investments in reducing deforestation and fires in Ankeniheny-Zahemena Corridor, Madagascar.

PubMed

Tabor, Karyn; Jones, Kelly W; Hewson, Jennifer; Rasolohery, Andriambolantsoa; Rambeloson, Andoniaina; Andrianjohaninarivo, Tokihenintsoa; Harvey, Celia A

2017-01-01

Forest conservation and REDD+ projects invest millions of dollars each year to reduce local communities' dependence on forests and prevent forest loss and degradation. However, to date, there is limited evidence on whether these investments are effective at delivering conservation outcomes. We explored the relationships between 600+ small-scale conservation and development investments that occurred from 2007 to 2014 and conservation outcomes (deforestation rates and fire detections) within Ankeniheny-Zahamena Corridor in Madagascar using linear fixed effects panel regressions. We derived annual changes in forest cover and fires from satellite remote sensing. We found a statistically significant correlation between presence of any investment and reduced deforestation rates in 2010 and 2011 -years with accelerated deforestation elsewhere in the study area. This result indicated investments abated deforestation rates during times of political instability and lack of governance following a 2009 coup in Madagascar. We also found a statistically significant relationship between presence of any investment and reduced fire detections in the study area, suggesting investments had an impact on reducing burning of forest for agriculture. For both outcomes (i.e., deforestation rates and fire detections), we found that more dollars invested led to greater conservation outcomes (i.e. fewer fires or less deforestation), particularly when funding was sustained for one to two years. Our findings suggest that conservation and development investments can reduce deforestation and fire incidence, but also highlight the many challenges and complexities in assessing relationships between investments and conservation outcomes in a dynamic landscape and a volatile political context.

Evaluating the effectiveness of conservation and development investments in reducing deforestation and fires in Ankeniheny-Zahemena Corridor, Madagascar

PubMed Central

Jones, Kelly W.; Hewson, Jennifer; Rasolohery, Andriambolantsoa; Rambeloson, Andoniaina; Andrianjohaninarivo, Tokihenintsoa; Harvey, Celia A.

2017-01-01

Forest conservation and REDD+ projects invest millions of dollars each year to reduce local communities’ dependence on forests and prevent forest loss and degradation. However, to date, there is limited evidence on whether these investments are effective at delivering conservation outcomes. We explored the relationships between 600+ small-scale conservation and development investments that occurred from 2007 to 2014 and conservation outcomes (deforestation rates and fire detections) within Ankeniheny-Zahamena Corridor in Madagascar using linear fixed effects panel regressions. We derived annual changes in forest cover and fires from satellite remote sensing. We found a statistically significant correlation between presence of any investment and reduced deforestation rates in 2010 and 2011 –years with accelerated deforestation elsewhere in the study area. This result indicated investments abated deforestation rates during times of political instability and lack of governance following a 2009 coup in Madagascar. We also found a statistically significant relationship between presence of any investment and reduced fire detections in the study area, suggesting investments had an impact on reducing burning of forest for agriculture. For both outcomes (i.e., deforestation rates and fire detections), we found that more dollars invested led to greater conservation outcomes (i.e. fewer fires or less deforestation), particularly when funding was sustained for one to two years. Our findings suggest that conservation and development investments can reduce deforestation and fire incidence, but also highlight the many challenges and complexities in assessing relationships between investments and conservation outcomes in a dynamic landscape and a volatile political context. PMID:29267356

Disentangling the Long-term Effects of Climate Change and Forest Structure and Species Composition on Streamflow Across the Eastern US

NASA Astrophysics Data System (ADS)

Caldwell, P.; Elliott, K.; Hartsell, A.; Miniat, C.

2016-12-01

Climate change and disturbances are threatening the ability of forested watersheds to provide the clean, reliable, and abundant fresh water necessary to support aquatic ecosystems and a growing human population. Forested watersheds in the eastern US have undergone significant change over the 20th century due to natural and introduced disturbances and a legacy of land use. We hypothesize that changes in forest age and species composition (i.e., forest change) associated with these disturbances may have altered forest water use and thus streamflow (Q) due to inherent differences in transpiration among species and forest ages. To test this hypothesis, we quantified changes in Q from 1960 to 2012 in 202 US Geological Survey forested reference watersheds across the eastern US, and separated the effect of changes in climate from forest change using Auto-Regressive Integrated Moving Average (ARIMA) time series modeling. We linked changes in Q to forest disturbance, forest ages and species composition using the Landsat-based North American Forest Dynamics dataset and plot-level USDA Forest Service Forest Inventory and Analysis (FIA) data. We found that 172 of the 202 sites (85%) exhibited changes in Q not accounted for by climate that we attributed to forest change and/or land use change. Among these, 76 (44%) had declining Q due to forest change (mostly in the southeastern US) while 96 (56%) had increasing Q (mostly in the mid-Atlantic and northeastern US). Across the 172 sites with forest-related changes in Q, 34% had at least 10% of the watershed area disturbed at least once from 1986-2010. In a case study of three watersheds, FIA data indicated that changes in forest structure and species composition explained observed changes in Q beyond climate effects. Our results suggest that forest-related changes in Q may have significant implications for water supply in the region and may inform forest management strategies to mitigate climate change impacts on water resources.

US LAND-COVER MONITORING AND DETECTION OF CHANGES IN SCALE AND CONTEXT OF FOREST

EPA Science Inventory

Disparate land-cover mapping programs, previously focused solely on mission-oriented goals, have organized themselves as the Multi-Resolution Land Characteristics (MRLC) Consortium with a unified goal of producing land-cover nationwide at routine intervals. Under MRLC, United Sta...

World-wide association of timberline forest advance with microsite type along a precipitation gradient

NASA Astrophysics Data System (ADS)

Johnson, A. C.; Yeakley, A.

2009-12-01

Timberline forest advance associated with global climate change is occurring worldwide and is often associated with microsites. Microsites, controlled by topography, substrates, and plant cover, are localized regions dictating temperature, moisture, and solar radiation. These abiotic factors are integral to seedling survival. From a compilation of world-wide information on seedling regeneration on microsites at timberline, including our on-going research in the Pacific Northwest, we classified available literature into four microsite categories, related microsite category to annual precipitation, and used analysis of variance to detect statistical differences in microsite type and associated precipitation. We found statistical differences (p = 0.022) indicating the usefulness of understanding microsite/precipitation associations in detecting world-wide trends in timberline expansion. For example, wetter timberlines with downed wood, had regeneration associated with nurse logs, whereas on windy, drier landscapes, regeneration was typically associated with either leeward sides of tree clumps or on microsites protected from frost by overstory canopy. In our study of timberline expansion in the Pacific Northwest, we expect that such knowledge of microsite types associated with forest expansion will reveal a better understanding of mechanisms and rates of timberline forest advance during global warming.

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

Treesearch

Robert E. Kennedy; Zhiqiang Yang; Warren B. Cohen

2010-01-01

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks (LTS). The method brings together two themes in time-series analysis of LTS: capture of short-duration events and smoothing of long-term trends. Our strategy is...

Using Stable Isotopes to Infer the Impacts of Habitat Change on the Diets and Vertical Stratification of Frugivorous Bats in Madagascar.

PubMed

Reuter, Kim E; Wills, Abigail R; Lee, Raymond W; Cordes, Erik E; Sewall, Brent J

2016-01-01

Human-modified habitats are expanding rapidly; many tropical countries have highly fragmented and degraded forests. Preserving biodiversity in these areas involves protecting species-like frugivorous bats-that are important to forest regeneration. Fruit bats provide critical ecosystem services including seed dispersal, but studies of how their diets are affected by habitat change have often been rather localized. This study used stable isotope analyses (δ15N and δ13C measurement) to examine how two fruit bat species in Madagascar, Pteropus rufus (n = 138) and Eidolon dupreanum (n = 52) are impacted by habitat change across a large spatial scale. Limited data for Rousettus madagascariensis are also presented. Our results indicated that the three species had broadly overlapping diets. Differences in diet were nonetheless detectable between P. rufus and E. dupreanum, and these diets shifted when they co-occurred, suggesting resource partitioning across habitats and vertical strata within the canopy to avoid competition. Changes in diet were correlated with a decrease in forest cover, though at a larger spatial scale in P. rufus than in E. dupreanum. These results suggest fruit bat species exhibit differing responses to habitat change, highlight the threats fruit bats face from habitat change, and clarify the spatial scales at which conservation efforts could be implemented.

Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States

USGS Publications Warehouse

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Rayfield, Bronwyn; Sherba, Jason; Hawbaker, Todd J.; Zhu, Zhiliang; Selmants, Paul; Loveland, Thomas R.

2018-01-01

Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km2 of developed lands, an average rate of 3282 km2 yr−1. On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr−1. In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr−1). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.

Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States

NASA Astrophysics Data System (ADS)

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Rayfield, Bronwyn; Sherba, Jason; Hawbaker, Todd J.; Zhu, Zhiliang; Selmants, Paul C.; Loveland, Thomas R.

2018-04-01

Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km2 of developed lands, an average rate of 3282 km2 yr‑1. On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr‑1. In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr‑1). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.

Climate and Management Controls on Forest Growth and Forest Carbon Balance in the Western United States

NASA Astrophysics Data System (ADS)

Kelsey, Katharine Cashman

Climate change is resulting in a number of rapid changes in forests worldwide. Forests comprise a critical component of the global carbon cycle, and therefore climate-induced changes in forest carbon balance have the potential to create a feedback within the global carbon cycle and affect future trajectories of climate change. In order to further understanding of climate-driven changes in forest carbon balance, I (1) develop a method to improve spatial estimates forest carbon stocks, (2) investigate the effect of climate change and forest management actions on forest recovery and carbon balance following disturbance, and (3) explore the relationship between climate and forest growth, and identify climate-driven trends in forest growth through time, within San Juan National Forest in southwest Colorado, USA. I find that forest carbon estimates based on texture analysis from LandsatTM imagery improve regional forest carbon maps, and this method is particularly useful for estimating carbon stocks in forested regions affected by disturbance. Forest recovery from disturbance is also a critical component of future forest carbon stocks, and my results indicate that both climate and forest management actions have important implications for forest recovery and carbon dynamics following disturbance. Specifically, forest treatments that use woody biomass removed from the forest for electricity production can reduce carbon emissions to the atmosphere, but climate driven changes in fire severity and forest recovery can have the opposite effect on forest carbon stocks. In addition to the effects of disturbance and recovery on forest condition, I also find that climate change is decreasing rates of forest growth in some species, likely in response to warming summer temperatures. These growth declines could result in changes of vegetation composition, or in extreme cases, a shift in vegetation type that would alter forest carbon storage. This work provides insight into both current and future changes in forest carbon balance as a consequence of climate change and forest management in the western US.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

PubMed Central

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

PubMed

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

NASA Astrophysics Data System (ADS)

Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

2017-12-01

Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont.

PubMed

Beckage, Brian; Osborne, Ben; Gavin, Daniel G; Pucko, Carolyn; Siccama, Thomas; Perkins, Timothy

2008-03-18

Detecting latitudinal range shifts of forest trees in response to recent climate change is difficult because of slow demographic rates and limited dispersal but may be facilitated by spatially compressed climatic zones along elevation gradients in montane environments. We resurveyed forest plots established in 1964 along elevation transects in the Green Mountains (Vermont) to examine whether a shift had occurred in the location of the northern hardwood-boreal forest ecotone (NBE) from 1964 to 2004. We found a 19% increase in dominance of northern hardwoods from 70% in 1964 to 89% in 2004 in the lower half of the NBE. This shift was driven by a decrease (up to 76%) in boreal and increase (up to 16%) in northern hardwood basal area within the lower portions of the ecotone. We used aerial photographs and satellite imagery to estimate a 91- to 119-m upslope shift in the upper limits of the NBE from 1962 to 2005. The upward shift is consistent with regional climatic change during the same period; interpolating climate data to the NBE showed a 1.1 degrees C increase in annual temperature, which would predict a 208-m upslope movement of the ecotone, along with a 34% increase in precipitation. The rapid upward movement of the NBE indicates little inertia to climatically induced range shifts in montane forests; the upslope shift may have been accelerated by high turnover in canopy trees that provided opportunities for ingrowth of lower elevation species. Our results indicate that high-elevation forests may be jeopardized by climate change sooner than anticipated.

Hydrologic impacts of climate and land use changes over the Three-North region of China: implication for the forestation programs in arid and semiarid regions

NASA Astrophysics Data System (ADS)

Xie, X.; Liang, S.

2013-12-01

The Three-North region of China, including the northeastern, northern, and northwestern areas, covers an area of more than three million square kilometers. This region is featured for its arid and semiarid environments with annual rainfall less than 450 mm. During the past few decades, the Three-North region has experienced noticeable water-cycle variations owing to the climate and land use changes. Typically, several large-scale forestation programs such as the Three Norths Forest Shelterbelt Program began since late 1970s, have been implemented across this region in order to solve desertification and dust storm problems, and to combat the loss of water and soil. These programs raised debates, however, because their effectiveness does not likely achieve what was expected and they even imposed negative influences on the eco-hydrologic system in some areas. Currently most studies were based on in-situ measurements and individual catchments and primarily attributed the water-cycle variations to the forestation. In this study we attempt to evaluate the impact of combined climate and land use changes using remote sensing data and a sophisticated land surface model, i.e., the Three-Layer Variable Infiltration Capacity (VIC-3L). Four land use maps derived from Landsat TM images for 1990, 1995, 2000 and 2005 were used to detect the land use changes in the three-north regions, and leaf area index (LAI) from the Global Land Surface Satellite (GLASS) LAI product was employed to assess the land cover change and the effect of forestation programs. After model calibration and validation based on gauged streamflow and evapotranspiration from China FluxNet, a series of simulation scenarios were designed to examine the impacts of climate and land use changes on soil moisture, runoff and evapotranspiration and to identify each contribution to water fluxes. It was found that within the study area as a whole, LAI shows an increasing trend during 1980-2009 in response to the forestation programs. However, the hydrologic variables (i.e., the soil moisture, runoff and evapotranspiration) in northern and northwestern regions are more significantly affected by the precipitation and temperature than by the land use changes, although the impacts of land use change are uneven across the entire region. So, the forestation probably plays a modest role in the hydrologic system.

Monitoring basin-scale land cover changes in Kagera Basin of Lake Victoria using ancillary data and remote sensing

NASA Astrophysics Data System (ADS)

Wasige, John E.; Groen, Thomas A.; Smaling, Eric; Jetten, Victor

2013-04-01

The Kagera Basin is a high value ecosystem in the Lake Victoria watershed because of the hydrological and food services it provides. The basin has faced large scale human induced land use and land cover changes (LUCC), but quantitative data is to date lacking. A combination of ancillary data and satellite imagery were interpreted to construct LUCC dynamics for the last century. This study is an initial step towards assessing the impact of LUCC on sustainable agriculture and water quality in the watershed. The results show that large trends of LUCC have rapidly occurred over the last 100 years. The most dominant LUCC processes were gains in farmland areas (not detectable in 1901 to 60% in 2010) and a net reduction in dense forest (7% to 2.6%), woodlands (51% to 6.9%) and savannas (35% to 19.6%) between 1901 and 2010. Forest degradation rapidly occurred during 1974 and 1995 but the forest re-grew between 1995 and 2010 due to forest conservation efforts. Afforestation efforts have resulted in plantation forest increases between 1995 and 2010. The rates of LUCC observed are higher than those reported in Sub Saharan Africa (SSA) and other parts of the world. This is one of the few studies in SSA at a basin scale that combines multi-source spatio-temporal data on land cover to enable long-term quantification of land cover changes. In the discussion we address future research needs for the area based on the results of this study. These research needs include quantifying the impacts of land cover change on nutrient and sediment dynamics, soil organic carbon stocks, and changes in biodiversity.

Monitoring gradual ecosystem change using Landsat time series analyses: case studies in selected forest and rangeland ecosystems

USGS Publications Warehouse

Vogelmann, James E.; Xian, George; Homer, Collin G.; Tolk, Brian

2012-01-01

The focus of the study was to assess gradual changes occurring throughout a range of natural ecosystems using decadal Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM +) time series data. Time series data stacks were generated for four study areas: (1) a four scene area dominated by forest and rangeland ecosystems in the southwestern United States, (2) a sagebrush-dominated rangeland in Wyoming, (3) woodland adjacent to prairie in northwestern Nebraska, and (4) a forested area in the White Mountains of New Hampshire. Through analyses of time series data, we found evidence of gradual systematic change in many of the natural vegetation communities in all four areas. Many of the conifer forests in the southwestern US are showing declines related to insects and drought, but very few are showing evidence of improving conditions or increased greenness. Sagebrush communities are showing decreases in greenness related to fire, mining, and probably drought, but very few of these communities are showing evidence of increased greenness or improving conditions. In Nebraska, forest communities are showing local expansion and increased canopy densification in the prairie–woodland interface, and in the White Mountains high elevation understory conifers are showing range increases towards lower elevations. The trends detected are not obvious through casual inspection of the Landsat images. Analyses of time series data using many scenes and covering multiple years are required in order to develop better impressions and representations of the changing ecosystem patterns and trends that are occurring. The approach described in this paper demonstrates that Landsat time series data can be used operationally for assessing gradual ecosystem change across large areas. Local knowledge and available ancillary data are required in order to fully understand the nature of these trends.

Unraveling Landscape Complexity: Land Use/Land Cover Changes and Landscape Pattern Dynamics (1954-2008) in Contrasting Peri-Urban and Agro-Forest Regions of Northern Italy.

PubMed

Smiraglia, D; Ceccarelli, T; Bajocco, S; Perini, L; Salvati, L

2015-10-01

This study implements an exploratory data analysis of landscape metrics and a change detection analysis of land use and population density to assess landscape dynamics (1954-2008) in two physiographic zones (plain and hilly-mountain area) of Emilia Romagna, northern Italy. The two areas are characterized by different landscape types: a mixed urban-rural landscape dominated by arable land and peri-urban settlements in the plain and a traditional agro-forest landscape in the hilly-mountain area with deciduous and conifer forests, scrublands, meadows, and crop mosaic. Urbanization and, to a lesser extent, agricultural intensification were identified as the processes underlying landscape change in the plain. Land abandonment determining natural forestation and re-forestation driven by man was identified as the process of change most representative of the hilly-mountain area. Trends in landscape metrics indicate a shift toward more fragmented and convoluted patterns in both areas. Number of patches, the interspersion and juxtaposition index, and the large patch index are the metrics discriminating the two areas in terms of landscape patterns in 1954. In 2008, mean patch size, edge density, interspersion and juxtaposition index, and mean Euclidean nearest neighbor distance were the metrics with the most different spatial patterns in the two areas. The exploratory data analysis of landscape metrics contributed to link changes over time in both landscape composition and configuration providing a comprehensive picture of landscape transformations in a wealthy European region. Evidence from this study are hoped to inform sustainable land management designed for homogeneous landscape units in similar socioeconomic contexts.

Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

NASA Astrophysics Data System (ADS)

V V L, P. A.

2015-12-01

In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.

Application of a CO2 dial system for infrared detection of forest fire and reduction of false alarm

NASA Astrophysics Data System (ADS)

Bellecci, C.; Francucci, M.; Gaudio, P.; Gelfusa, M.; Martellucci, S.; Richetta, M.; Lo Feudo, T.

2007-04-01

Forest fires can be the cause of serious environmental and economic damages. For this reason considerable effort has been directed toward forest protection and fire fighting. The means traditionally used for early fire detection mainly consist in human observers dispersed over forest regions. A significant improvement in early warning capabilities could be obtained by using automatic detection apparatus. In order to early detect small forest fires and minimize false alarms, the use of a lidar system and dial technique will be considered. A first evaluation of the lowest detectable concentration will be estimated by numerical simulation. The theoretical model will also be used to get the capability of the dial system to control wooded areas. Fixing the burning rate for several fuels, the maximum range of detection will be evaluated. Finally results of simulations will be reported.

Challenges to Sierra Nevada forests and their local communities: An observational and modeling perspective

NASA Astrophysics Data System (ADS)

Schmidt, Cynthia L.

Global forests are experiencing dramatic changes due to changes in climate as well as anthropogenic activities. Increased warming is causing the advancement of some species upslope and northward, while it is also causing widespread mortality due to increased drought conditions. In addition, increasing human population in mountain regions is resulting in elevated risk of human life and property loss due to larger and more severe wildfires. My research focuses on assessing the current vulnerability of forests and their communities in the Sierra Nevada, and how forests are projected to change in the future based on different climate change scenarios. In the first chapter I use Landsat satellite imagery to identify and attribute cause of forest disturbance between 1985 and 2011, primarily focusing on disturbances due to insect, diseases and drought. The change-detection algorithm, Landtrendr, was successfully used to identify forest disturbance, but identifying cause of disturbance was challenging due to the spectral similarities between disturbance types. Landtrendr was most successful in identifying disturbance due to insect, disease and drought in the San Bernardino National Forest, where there is little forest management activity. In the second chapter, I assess whether state or local land use policies in high-fire prone regions exist to reduce the vulnerability of residential developments to wildfire. Three specific land-use tools associated with reducing wildfire vulnerability are identified: (1) buffers around developments; (2) clustered developments; (3) restricting construction on slopes greater than 25%. The study also determines whether demographic and physical characteristics of selected California counties were related to implementing land use policies related to reducing wildfire vulnerability. Results indicate that land use policies related to preventing wildfire-related losses focus on building materials, road access, water availability and vegetation management, not the three identified land-use tools. San Diego County, the county that has experienced the most devastating fires, had the highest percentage of residential developments with both clustering and buffering. The third chapter focuses on future forest conditions. I used a Dynamic Global Vegetation Model (DGVM) to assess future vegetation dynamics and productivity under changing climate and atmospheric CO2 concentrations in the Sierra Nevada. Model results suggest that Temperate Broadleaved Evergreen Plant Functional Types (PFTs) will move upslope and eastward, replacing Temperate Needleleaved PFTs. Boreal Needleleaved Evergreen PFTs, found primarily at higher elevations, will decline dramatically as temperatures continue to increase. Gross Primary Productivity (GPP) will increase as atmospheric CO2 concentration increases, due primarily to the increase in the more productive broadleaved PFTs. Forest ecosystems play an important role in maintaining climate stability at the regional and global scales as a vital carbon sink, so understanding the role of disturbance and climate change will be vital to both scientists and policy makers in the future.

Results of land cover change detection analysis in and around Cordillera Azul National Park, Peru

USGS Publications Warehouse

Sleeter, Benjamin M.; Halsing, David L.

2005-01-01

The first product of the Optimizing Design and Management of Protected Areas for Conservation Project is a land cover change detection analysis based on Landsat thematic mapper (TM) and enhanced thematic mapper plus (ETM+) imagery collected at intervals between 1989 and 2002. The goal of this analysis was to quantify and analyze patterns of forest clearing, land conversion, and other disturbances in and around the Cordillera Azul National Park in Peru. After removing clouds and cloud shadows from the imagery using a series of automatic and manual processes, a Tasseled Cap Transformation was used to detect pixels of high reflectance, which were classified as bare ground and areas of likely forest clearing. Results showed a slow but steady increase in cleared ground prior to 1999 and a rapid and increasing conversion rate after that time. The highest concentrations of clearings have spread upward from the western border of the study area on the Huallaga River. To date, most disturbances have taken place in the buffer zone around the park, not within it, but the data show dense clearings occurring closer to the park border each year.

Edge effects on foliar stable isotope values in a Madagascan tropical dry forest.

PubMed

Crowley, Brooke E; McGoogan, Keriann C; Lehman, Shawn M

2012-01-01

Edge effects represent an inevitable and important consequence of habitat loss and fragmentation. These effects include changes in microclimate, solar radiation, or temperature. Such abiotic effects can, in turn, impact biotic factors. They can have a substantial impact on species, communities, and ecosystems. Here we examine clinal variations in stable carbon and nitrogen isotope values for trees along an edge-interior gradient in the dry deciduous forest at Ankarafantsika National Park. We predicted that soil respiration and differences in solar irradiance would result in stratified δ¹³C values where leaves collected close to the forest floor would have lower δ¹³C values than those growing higher up in the canopy. We also anticipated that plants growing at the savannah-forest boundary would have higher δ¹³C and δ¹⁵N values than plants growing in the forest interior. As expected, we detected a small but significant canopy effect. Leaves growing below 2 m from the forest floor exhibit δ¹³C values that are, on average, 1.1‰ lower than those growing above this threshold. We did not, however, find any relationship between foliar δ¹³C and distance from the edge. Unpredictably, we detected a striking positive relationship between foliar δ¹⁵N values and increasing distance into the forest interior. Variability in physiology among species, anthropogenic influence, organic input, and rooting depth cannot adequately explain this trend. Instead, this unexpected relationship most likely reflects decreasing nutrient or water availability, or a shift in N-sources with increasing distance from the savannah. Unlike most forest communities, the trees at Ampijoroa are growing in nutrient-limited sands. In addition to being nutrient poor, these well-drained soils likely decrease the amount of soil water available to forest vegetation. Continued research on plant responses to edge effects will improve our understanding of the conservation biology of forest ecosystems in Madagascar.

Edge Effects on Foliar Stable Isotope Values in a Madagascan Tropical Dry Forest

PubMed Central

Crowley, Brooke E.; McGoogan, Keriann C.; Lehman, Shawn M.

2012-01-01

Edge effects represent an inevitable and important consequence of habitat loss and fragmentation. These effects include changes in microclimate, solar radiation, or temperature. Such abiotic effects can, in turn, impact biotic factors. They can have a substantial impact on species, communities, and ecosystems. Here we examine clinal variations in stable carbon and nitrogen isotope values for trees along an edge-interior gradient in the dry deciduous forest at Ankarafantsika National Park. We predicted that soil respiration and differences in solar irradiance would result in stratified δ13C values where leaves collected close to the forest floor would have lower δ13C values than those growing higher up in the canopy. We also anticipated that plants growing at the savannah-forest boundary would have higher δ13C and δ15N values than plants growing in the forest interior. As expected, we detected a small but significant canopy effect. Leaves growing below 2 m from the forest floor exhibit δ13C values that are, on average, 1.1‰ lower than those growing above this threshold. We did not, however, find any relationship between foliar δ13C and distance from the edge. Unpredictably, we detected a striking positive relationship between foliar δ15N values and increasing distance into the forest interior. Variability in physiology among species, anthropogenic influence, organic input, and rooting depth cannot adequately explain this trend. Instead, this unexpected relationship most likely reflects decreasing nutrient or water availability, or a shift in N-sources with increasing distance from the savannah. Unlike most forest communities, the trees at Ampijoroa are growing in nutrient-limited sands. In addition to being nutrient poor, these well-drained soils likely decrease the amount of soil water available to forest vegetation. Continued research on plant responses to edge effects will improve our understanding of the conservation biology of forest ecosystems in Madagascar. PMID:22973460

Detecting and monitoring large-scale drought effects on forests: toward an integrated approach

Treesearch

Steve Norman; Frank H. Koch; William W. Hargrove

2016-01-01

Although drought is recognized as an important and overarching driver of ecosystem change, its occurrence and effects have been difficult to describe over large geographic areas (Hogg and others 2008, Panu and Sharma 2002).

Richness and Abundance of Ichneumonidae in a Fragmented Tropical Rain Forest.

PubMed

Ruiz-Guerra, B; Hanson, P; Guevara, R; Dirzo, R

2013-10-01

Because of the magnitude of land use currently occurring in tropical regions, the local loss of animal species due to habitat fragmentation has been widely studied, particularly in the case of vertebrates. Many invertebrate groups and the ichneumonid wasps in particular, however, have been poorly studied in this context, despite the fact that they are one of the most species-rich groups and play an important role as regulators of other insect populations. Here, we recorded the taxonomic composition of ichneumonid parasitoids and assessed their species richness, abundance, similarity, and dominance in the Los Tuxtlas tropical rain forest, Mexico. We compared two forest types: a continuous forest (640 ha) and a forest fragment (19 ha). We sampled ichneumonids using four malaise traps in both forest types during the dry (September-October) and rainy (March-April) seasons. A total of 104 individuals of Ichneumonidae belonging to 11 subfamilies, 18 genera, and 42 species were collected in the continuous forest and 11 subfamilies, 15 genera, and 24 species were collected in the forest fragment. Species richness, abundance, and diversity of ichneumonids were greater in the continuous forest than in the forest fragment. We did not detect differences between seasons. Species rank/abundance curves showed that the ichneumonid community between the forest types was different. Species similarity between forest types was low. The most dominant species in continuous forest was Neotheronia sp., whereas in the forest fragment, it was Orthocentrus sp. Changes in the ichneumonid wasp community may compromise important tropical ecosystem processes.

Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient.

PubMed

Orihuela, Rodrigo L L; Peres, Carlos A; Mendes, Gabriel; Jarenkow, João A; Tabarelli, Marcelo

2015-01-01

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide.

Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient

PubMed Central

Orihuela, Rodrigo L. L.; Peres, Carlos A.; Mendes, Gabriel; Jarenkow, João A.; Tabarelli, Marcelo

2015-01-01

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide. PMID:26309252

Improvement of Forest Fire Detection Algorithm Using Brightness Temperature Lapse Rate Correction in HIMAWARI-8 IR Channels: Application to the 6 may 2017 Samcheok City, Korea

NASA Astrophysics Data System (ADS)

Park, S. H.; Park, W.; Jung, H. S.

2018-04-01

Forest fires are a major natural disaster that destroys a forest area and a natural environment. In order to minimize the damage caused by the forest fire, it is necessary to know the location and the time of day and continuous monitoring is required until fire is fully put out. We have tried to improve the forest fire detection algorithm by using a method to reduce the variability of surrounding pixels. We focused that forest areas of East Asia, part of the Himawari-8 AHI coverage, are mostly located in mountainous areas. The proposed method was applied to the forest fire detection in Samcheok city, Korea on May 6 to 10, 2017.

Tracking changes and preventing loss in critical tiger habitat

PubMed Central

Joshi, Anup R.; Dinerstein, Eric; Wikramanayake, Eric; Anderson, Michael L.; Olson, David; Jones, Benjamin S.; Seidensticker, John; Lumpkin, Susan; Hansen, Matthew C.; Sizer, Nigel C.; Davis, Crystal L.; Palminteri, Suzanne; Hahn, Nathan R.

2016-01-01

The global population of wild tigers remains dangerously low at fewer than 3500 individuals. Habitat loss, along with poaching, can undermine the international target recovery of doubling the number of wild tigers by 2022. Using a new satellite-based monitoring system, we analyzed 14 years of forest loss data within the 76 landscapes (ranging from 278 to 269,983 km2) that have been prioritized for conservation of wild tigers. Our analysis provides an update of the status of tiger habitat and describes new applications of technology to detect precisely where forest loss is occurring in order to curb future habitat loss. Across the 76 landscapes, forest loss was far less than anticipated (79,597 ± 22,629 km2, 7.7% of remaining habitat) over the 14-year study period (2001–2014). Habitat loss was unevenly distributed within a subset of 29 landscapes deemed most critical for doubling wild tiger populations: 19 showed little change (1.5%), whereas 10 accounted for more than 98% (57,392 ± 16,316 km2) of habitat loss. Habitat loss in source population sites within 76 landscapes ranged from no loss to 435 ± 124 km2 (x¯=24km2, SD = 89, total = 1676 ± 476 km2). Doubling the tiger population by 2022 requires moving beyond tracking annual changes in habitat. We highlight near–real-time forest monitoring technologies that provide alerts of forest loss at relevant spatial and temporal scales to prevent further erosion. PMID:27051881

Tracking changes and preventing loss in critical tiger habitat.

PubMed

Joshi, Anup R; Dinerstein, Eric; Wikramanayake, Eric; Anderson, Michael L; Olson, David; Jones, Benjamin S; Seidensticker, John; Lumpkin, Susan; Hansen, Matthew C; Sizer, Nigel C; Davis, Crystal L; Palminteri, Suzanne; Hahn, Nathan R

2016-04-01

The global population of wild tigers remains dangerously low at fewer than 3500 individuals. Habitat loss, along with poaching, can undermine the international target recovery of doubling the number of wild tigers by 2022. Using a new satellite-based monitoring system, we analyzed 14 years of forest loss data within the 76 landscapes (ranging from 278 to 269,983 km(2)) that have been prioritized for conservation of wild tigers. Our analysis provides an update of the status of tiger habitat and describes new applications of technology to detect precisely where forest loss is occurring in order to curb future habitat loss. Across the 76 landscapes, forest loss was far less than anticipated (79,597 ± 22,629 km(2), 7.7% of remaining habitat) over the 14-year study period (2001-2014). Habitat loss was unevenly distributed within a subset of 29 landscapes deemed most critical for doubling wild tiger populations: 19 showed little change (1.5%), whereas 10 accounted for more than 98% (57,392 ± 16,316 km(2)) of habitat loss. Habitat loss in source population sites within 76 landscapes ranged from no loss to 435 ± 124 km(2) ([Formula: see text], SD = 89, total = 1676 ± 476 km(2)). Doubling the tiger population by 2022 requires moving beyond tracking annual changes in habitat. We highlight near-real-time forest monitoring technologies that provide alerts of forest loss at relevant spatial and temporal scales to prevent further erosion.

Forest resources of nations in relation to human well-being.

PubMed

Kauppi, Pekka E; Sandström, Vilma; Lipponen, Antti

2018-01-01

A universal turnaround has been detected in many countries of the World from shrinking to expanding forests. The forest area of western Europe expanded already in the 19th century. Such early trends of forest resources cannot be associated with the rapid rise of atmospheric carbon dioxide nor with the anthropogenic climate change, which have taken place since the mid 20th century. Modern, most recent spatial patterns of forest expansions and contractions do not correlate with the geography of climate trends nor with dry versus moist areas. Instead, the forest resources trends of nations correlate positively with UNDP Human Development Index. This indicates that forest resources of nations have improved along with progress in human well-being. Highly developed countries apply modern agricultural methods on good farmlands and abandon marginal lands, which become available for forest expansion. Developed countries invest in sustainable programs of forest management and nature protection. Our findings are significant for predicting the future of the terrestrial carbon sink. They suggest that the large sink of carbon recently observed in forests of the World will persist, if the well-being of people continues to improve. However, despite the positive trends in domestic forests, developed nations increasingly outsource their biomass needs abroad through international trade, and all nations rely on unsustainable energy use and wasteful patterns of material consumption.

Data base manipulation for assessment of multiresource suitability and land change

NASA Technical Reports Server (NTRS)

Colwell, J.; Sanders, P.; Davis, G.; Thomson, F. (Principal Investigator)

1981-01-01

Progress is reported in three tasks which support the overall objectives of renewable resources inventory task of the AgRISTARS program. In the first task, the geometric correction algorithms of the Master Data Processor were investigated to determine the utility of data corrected by this processor for U.S. Forest Service uses. The second task involved investigation of logic to form blobs as a precursor step to automatic change detection involving two dates of LANDSAT data. Some routine procedures for selecting BLOB (spatial averaging) parameters were developed. In the third task, a major effort was made to develop land suitability modeling approches for timber, grazing, and wildlife habitat in support of resource planning efforts on the San Juan National Forest.

Rapid Shifts in Soil and Forest Floor Microbial Communities with Changes in Vegetation during Secondary Tropical Forest Succession

NASA Astrophysics Data System (ADS)

Smith, A.; Marin-Spiotta, E.; Balser, T. C.

2012-12-01

Soil microorganisms regulate fundamental biochemical processes in plant litter decomposition and soil organic matter (SOM) transformations. In order to predict how disturbance affects belowground carbon storage, it is important to understand how the forest floor and soil microbial community respond to changes in land cover, and the consequences on SOM formation and stabilization. We are measuring microbial functional diversity and activity across a long-term successional chronosequence of secondary forests regrowing on abandoned pastures in the wet subtropical forest life zone of Puerto Rico. Here we report intra- and interannual data on soil and litter microbial community composition (via phospholipid fatty acid analysis, PLFA) and microbial activity (via extracellular enzyme activity) from active pastures, secondary forests aged 20, 30, 40, 70, and 90-years, and primary forests. Microbial community composition and extracellular enzyme activity differed significantly by season in these wet subtropical ecosystems, even though differences in mean monthly precipitation between the middle of the dry season (January) and the wet season (July) is only 30mm. Despite seasonal differences, there was a persistent strong effect of land cover type and forest successional stage, or age, on overall microbial community PLFA structure. Using principal component analysis, we found differences in microbial community structure among active pastures, early, and late successional forests. The separation of soil microbes into early and late successional communities parallels the clustering of tree composition data. While the successional patterns held across seasons, the importance of different microbial groups driving these patterns differed seasonally. Biomarkers for gram-positive and actinobacteria (i15:0 and 16:0 10Me) were associated with early (20, 30 & 40 year old) secondary forests in the dry season. These younger forest communities were identified by the biomarker for anaerobic gram-negative bacteria (c19:0) in the wet season, which suggests the presence of anaerobic microsites in these very clayey Oxisols. Enzymatic activity did not differ with succession but was highest in the dry season. We expect this may be due to decreased turnover of enzymes with low soil moisture. Interannual sampling has revealed a very rapid microbial response to changes in aboveground cover. Within a year following woody biomass encroachment, we detected a shift in the soil microbial community from a pasture-associated community to an early secondary forest community in one of our replicate pasture sites. This very rapid response in the belowground microbial community structure to changes in vegetation has not been strongly documented in the literature. This data supports a direct link between aboveground and belowground biotic community structures and highlights the importance of long-term repeated sampling of microbial communities in dynamic ecosystems. Our findings have implications for predicting rapid ecological responses to land-cover change.

Forest Area Derivation from SENTINEL-1 Data

NASA Astrophysics Data System (ADS)

Dostálová, Alena; Hollaus, Markus; Milenković, Milutin; Wagner, Wolfgang

2016-06-01

The recently launched Sentinel-1A provides the high resolution Synthetic Aperture Radar (SAR) data with very high temporal coverage over large parts of European continent. Short revisit time and dual polarization availability supports its usability for forestry applications. The following study presents an analysis of the potential of the multi-temporal dual-polarization Sentinel-1A data for the forest area derivation using the standard methods based on Otsu thresholding and K-means clustering. Sentinel-1 data collected in winter season 2014-2015 over a test area in eastern Austria were used to derive forest area mask with spatial resolution of 10m and minimum mapping unit of 500 m2. The validation with reference forest mask derived from airborne full-waveform laser scanning data revealed overall accuracy of 92 % and kappa statistics of 0.81. Even better results can be achieved when using external mask for urban areas, which might be misclassified as forests when using the introduced approach based on SAR data only. The Sentinel-1 data and the described methods are well suited for forest change detection between consecutive years.

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System.

PubMed

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.

Multi-Temporal Classification and Change Detection Using Uav Images

NASA Astrophysics Data System (ADS)

Makuti, S.; Nex, F.; Yang, M. Y.

2018-05-01

In this paper different methodologies for the classification and change detection of UAV image blocks are explored. UAV is not only the cheapest platform for image acquisition but it is also the easiest platform to operate in repeated data collections over a changing area like a building construction site. Two change detection techniques have been evaluated in this study: the pre-classification and the post-classification algorithms. These methods are based on three main steps: feature extraction, classification and change detection. A set of state of the art features have been used in the tests: colour features (HSV), textural features (GLCM) and 3D geometric features. For classification purposes Conditional Random Field (CRF) has been used: the unary potential was determined using the Random Forest algorithm while the pairwise potential was defined by the fully connected CRF. In the performed tests, different feature configurations and settings have been considered to assess the performance of these methods in such challenging task. Experimental results showed that the post-classification approach outperforms the pre-classification change detection method. This was analysed using the overall accuracy, where by post classification have an accuracy of up to 62.6 % and the pre classification change detection have an accuracy of 46.5 %. These results represent a first useful indication for future works and developments.

Landsat Based Woody Vegetation Loss Detection in Queensland, Australia Using the Google Earth Engine

NASA Astrophysics Data System (ADS)

Johansen, K.; Phinn, S. R.; Taylor, M.

2014-12-01

Land clearing detection and woody Foliage Projective Cover (FPC) monitoring at the state and national level in Australia has mainly been undertaken by state governments and the Terrestrial Ecosystem Research Network (TERN) because of the considerable expense, expertise, sustained duration of activities and staffing levels needed. Only recently have services become available, providing low budget, generalized access to change detection tools suited to this task. The objective of this research was to examine if a globally available service, Google Earth Engine Beta, could be used to predict woody vegetation loss with accuracies approaching the methods used by TERN and the government of the state of Queensland, Australia. Two change detection approaches were investigated using Landsat Thematic Mapper time series and the Google Earth Engine Application Programming Interface: (1) CART and Random Forest classifiers; and (2) a normalized time series of Foliage Projective Cover (FPC) and NDVI combined with a spectral index. The CART and Random Forest classifiers produced high user's and producer's mapping accuracies of clearing (77-92% and 54-77%, respectively) when detecting change within epochs for which training data were available, but extrapolation to epochs without training data reduced the mapping accuracies. The use of FPC and NDVI time series provided a more robust approach for calculation of a clearing probability, as it did not rely on training data but instead on the difference of the normalized FPC / NDVI mean and standard deviation of a single year at the change point in relation to the remaining time series. However, the FPC and NDVI time series approach represented a trade-off between user's and producer's accuracies. Both change detection approaches explored in this research were sensitive to ephemeral greening and drying of the landscape. However, the developed normalized FPC and NDVI time series approach can be tuned to provide automated alerts for large woody vegetation clearing events by selecting suitable thresholds to identify very likely clearing. This research provides a comprehensive foundation to build further capacity to use globally accessible, free, online image datasets and processing tools to accurately detect woody vegetation clearing in an automated and rapid manner.

The Ring-Barking Experiment: Analysis of Forest Vitality Using Multi-Temporal Hyperspectral Data

NASA Astrophysics Data System (ADS)

Reichmuth, Anne; Bachmann, Martin; Heiden, Uta; Pinnel, Nicole; Holzwarth, Stefanie; Muller, Andreas; Henning, Lea; Einzmann, Kathrin; Immitzer, Markus; Seitz, Rudolf

2016-08-01

Through new operational optical spaceborne sensors (En- MAP and Sentinel-2) the impact analysis of climate change on forest ecosystems will be fostered. This analysis examines the potential of high spectral, spatial and temporal resolution data for detecting forest vegetation parameters, in particular Chlorophyll and Canopy Water content. The study site is a temperate spruce forest in Germany where in 2013 several trees were Ring-barked for a controlled die-off. During this experiment Ring- barked and Control trees were observed. Twelve airborne hyperspectral HySpex VNIR (Visible/Near Infrared) and SWIR (Shortwave Infrared) data with 1m spatial and 416 bands spectral resolution were acquired during the vegetation periods of 2013 and 2014. Additional laboratory spectral measurements of collected needle samples from Ring-barked and Control trees are available for needle level analysis. Index analysis of the laboratory measurements and image data are presented in this study.

Pervasive phosphorus limitation of tree species but not communities in tropical forests

NASA Astrophysics Data System (ADS)

Turner, Benjamin L.; Brenes-Arguedas, Tania; Condit, Richard

2018-03-01

Phosphorus availability is widely assumed to limit primary productivity in tropical forests, but support for this paradigm is equivocal. Although biogeochemical theory predicts that phosphorus limitation should be prevalent on old, strongly weathered soils, experimental manipulations have failed to detect a consistent response to phosphorus addition in species-rich lowland tropical forests. Here we show, by quantifying the growth of 541 tropical tree species across a steep natural phosphorus gradient in Panama, that phosphorus limitation is widespread at the level of individual species and strengthens markedly below a threshold of two parts per million exchangeable soil phosphate. However, this pervasive species-specific phosphorus limitation does not translate into a community-wide response, because some species grow rapidly on infertile soils despite extremely low phosphorus availability. These results redefine our understanding of nutrient limitation in diverse plant communities and have important implications for attempts to predict the response of tropical forests to environmental change.

LEAF AREA INDEX (LAI) CHANGE DETECTION ANALYSIS ON LOBLOLLY PINE (PINUS TAEDA) FOLLOWING COMPLETE UNDERSTORY REMOVAL

EPA Science Inventory

The confounding effect of understory vegetation contributions to satellite-derived estimates of leaf area index (LAI) was investigated on two loblolly pine (Pinus taeda) forest stands located in Virginia and North Carolina. In order to separate NDVI contributions of the dominantc...

ANALYSIS OF YEAR 2002 SEASONAL FOREST DYNAMICS USING TIME SERIES IN SITU LAI MEASUREMENTS AND MODIS LAI SATELLITE PRODUCTS

EPA Science Inventory

Multitemporal satellite images are the standard basis for regional-scale land-cover (LC) change detection. However, embedded in the data are the confounding effects of vegetation dynamics (phenology). As photosynthetic vegetation progresses through its annual cycle, the spectral ...

Thirty Years of Vegetation Change in the Coastal Santa Cruz Mountains of Northern California Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Results from Landsat satellite image times series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90% of the (predominantly second-growth) evergreen forest locations sampled.

Seeing the future impacts of climate change and forest management: a landscape visualization system for forest managers

Treesearch

Eric J. Gustafson; Melissa Lucash; Johannes Liem; Helen Jenny; Rob Scheller; Kelly Barrett; Brian R. Sturtevant

2016-01-01

Forest managers are increasingly considering how climate change may alter forests' capacity to provide ecosystem goods and services. But identifying potential climate change effects on forests is difficult because interactions among forest growth and mortality, climate change, management, and disturbances are complex and uncertain. Although forest landscape models...

Glare-reducing goggles for lookouts.

Treesearch

Richard E. McArdle; William G. Morris; Thornton T. Munger

1936-01-01

Detection of forest fires while they are still small is so important in forest protection that studies of the visibility of forest fire smokes from lookout points has been one of the principal phases of the fire studies program of the Pacific Northwest Forest Experiment Station. One phase of fire detection is the personal efficiency of the lookout. The Station has...

Impacts of Water Stress on Forest Recovery and Its Interaction with Canopy Height.

PubMed

Xu, Peipei; Zhou, Tao; Yi, Chuixiang; Luo, Hui; Zhao, Xiang; Fang, Wei; Gao, Shan; Liu, Xia

2018-06-13

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI > 0.85), no significant difference in the recovery was found between short and tall trees ( p > 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management.

Utilizing the Landsat spectral-temporal domain for improved mapping and monitoring of ecosystem state and dynamics

NASA Astrophysics Data System (ADS)

Pasquarella, Valerie J.

Just as the carbon dioxide observations that form the Keeling curve revolutionized the study of the global carbon cycle, free and open access to all available Landsat imagery is fundamentally changing how the Landsat record is being used to study ecosystems and ecological dynamics. This dissertation advances the use of Landsat time series for visualization, classification, and detection of changes in terrestrial ecological processes. More specifically, it includes new examples of how complex ecological patterns manifest in time series of Landsat observations, as well as novel approaches for detecting and quantifying these patterns. Exploration of the complexity of spectral-temporal patterns in the Landsat record reveals both seasonal variability and longer-term trajectories difficult to characterize using conventional bi-temporal or even annual observations. These examples provide empirical evidence of hypothetical ecosystem response functions proposed by Kennedy et al. (2014). Quantifying observed seasonal and phenological differences in the spectral reflectance of Massachusetts' forest communities by combining existing harmonic curve fitting and phenology detection algorithms produces stable feature sets that consistently out-performed more traditional approaches for detailed forest type classification. This study addresses the current lack of species-level forest data at Landsat resolutions, demonstrating the advantages of spectral-temporal features as classification inputs. Development of a targeted change detection method using transformations of time series data improves spatial and temporal information on the occurrence of flood events in landscapes actively modified by recovering North American beaver (Castor canadensis) populations. These results indicate the utility of the Landsat record for the study of species-habitat relationships, even in complex wetland environments. Overall, this dissertation confirms the value of the Landsat archive as a continuous record of terrestrial ecosystem state and dynamics. Given the global coverage of remote sensing datasets, the time series visualization and analysis approaches presented here can be extended to other areas. These approaches will also be improved by more frequent collection of moderate resolution imagery, as planned by the Landsat and Sentinel-2 programs. In the modern era of global environmental change, use of the Landsat spectral-temporal domain presents new and exciting opportunities for the long-term large-scale study of ecosystem extent, composition, condition, and change.

Primates decline rapidly in unprotected forests: evidence from a monitoring program with data constraints.

PubMed

Rovero, Francesco; Mtui, Arafat; Kitegile, Amani; Jacob, Philipo; Araldi, Alessandro; Tenan, Simone

2015-01-01

Growing threats to primates in tropical forests make robust and long-term population abundance assessments increasingly important for conservation. Concomitantly, monitoring becomes particularly relevant in countries with primate habitat. Yet monitoring schemes in these countries often suffer from logistic constraints and/or poor rigor in data collection, and a lack of consideration of sources of bias in analysis. To address the need for feasible monitoring schemes and flexible analytical tools for robust trend estimates, we analyzed data collected by local technicians on abundance of three species of arboreal monkey in the Udzungwa Mountains of Tanzania (two Colobus species and one Cercopithecus), an area of international importance for primate endemism and conservation. We counted primate social groups along eight line transects in two forest blocks in the area, one protected and one unprotected, over a span of 11 years. We applied a recently proposed open metapopulation model to estimate abundance trends while controlling for confounding effects of observer, site, and season. Primate populations were stable in the protected forest, while the colobines, including the endemic Udzungwa red colobus, declined severely in the unprotected forest. Targeted hunting pressure at this second site is the most plausible explanation for the trend observed. The unexplained variability in detection probability among transects was greater than the variability due to observers, indicating consistency in data collection among observers. There were no significant differences in both primate abundance and detectability between wet and dry seasons, supporting the choice of sampling during the dry season only based on minimizing practical constraints. Results show that simple monitoring routines implemented by trained local technicians can effectively detect changes in primate populations in tropical countries. The hierarchical Bayesian model formulation adopted provides a flexible tool to determine temporal trends with full account for any imbalance in the data set and for imperfect detection.

Vulnerability of forest vegetation to anthropogenic climate change in China.

PubMed

Wan, Ji-Zhong; Wang, Chun-Jing; Qu, Hong; Liu, Ran; Zhang, Zhi-Xiang

2018-04-15

China has large areas of forest vegetation that are critical to biodiversity and carbon storage. It is important to assess vulnerability of forest vegetation to anthropogenic climate change in China because it may change the distributions and species compositions of forest vegetation. Based on the equilibrium assumption of forest communities across different spatial and temporal scales, we used species distribution modelling coupled with endemics-area relationship to assess the vulnerability of 204 forest communities across 16 vegetation types under different climate change scenarios in China. By mapping the vulnerability of forest vegetation to climate change, we determined that 78.9% and 61.8% of forest vegetation should be relatively stable in the low and high concentration scenarios, respectively. There were large vulnerable areas of forest vegetation under anthropogenic climate change in northeastern and southwestern China. The vegetation of subtropical mixed broadleaf evergreen and deciduous forest, cold-temperate and temperate mountains needleleaf forest, and temperate mixed needleleaf and broadleaf deciduous forest types were the most vulnerable under climate change. Furthermore, the vulnerability of forest vegetation may increase due to high greenhouse gas concentrations. Given our estimates of forest vegetation vulnerability to anthropogenic climate change, it is critical that we ensure long-term monitoring of forest vegetation responses to future climate change to assess our projections against observations. We need to better integrate projected changes of temperature and precipitation into climate-adaptive conservation strategies for forest vegetation in China. Copyright © 2017 Elsevier B.V. All rights reserved.

Detecting Changes of Thermal Environment over the Bohai Coastal Region by Spectral Change Vector Analysis

NASA Astrophysics Data System (ADS)

Hu, Y.; Jia, G.

2009-12-01

Change vector analysis (CVA) is an effective approach for detecting and characterizing land-cover change by comparing pairs of multi-spectral and multi-temporal datasets over certain area derived from various satellite platforms. NDVI is considered as an effective detector for biophysical changes due to its sensitivity to red and near infrared signals, while land surface temperature (LST) is considered as a valuable indicator for changes of ground thermal conditions. Here we try to apply CVA over satellite derived LST datasets to detect changes of land surface thermal properties parallel to climate change and anthropogenic influence in a city cluster since 2001. In this study, monthly land surface temperature datasets from 2001-2008 derived from MODIS collection 5 were used to examine change pattern of thermal environment over the Bohai coastal region by using spectral change vector analysis. The results from principle component analysis (PCA) for LST show that the PC 1-3 contain over 80% information on monthly variations and these PCA components represent the main processes of land thermal environment change over the study area. Time series of CVA magnitude combined with land cover information show that greatest change occurred in urban and heavily populated area, featured with expansion of urban heat island, while moderate change appeared in grassland area in the north. However few changes were observed over large plain area and forest area. Strong signals also are related to economy level and especially the events of surface cover change, such as emergence of railway and port. Two main processes were also noticed about the changes of thermal environment. First, weak signal was detected in mostly natural area influenced by interannual climate change in temperate broadleaf forest area. Second, land surface temperature changes were controlled by human activities as 1) moderate change of LST happened in grassland influenced by grazing and 2) urban heat island was intensifier in major cities, such as Beijing and Tianjin. Further, the continual drier climate combined with human actions over past fifties years have intensified land thermal pattern change and the continuation will be an important aspects to understand land surface processes and local climate change. Land surface temperature trends from 2000-2008 over the Bohai coastal region

Observations from old forests underestimate climate change effects on tree mortality.

PubMed

Luo, Yong; Chen, Han Y H

2013-01-01

Understanding climate change-associated tree mortality is central to linking climate change impacts and forest structure and function. However, whether temporal increases in tree mortality are attributed to climate change or stand developmental processes remains uncertain. Furthermore, interpreting the climate change-associated tree mortality estimated from old forests for regional forests rests on an un-tested assumption that the effects of climate change are the same for young and old forests. Here we disentangle the effects of climate change and stand developmental processes on tree mortality. We show that both climate change and forest development processes influence temporal mortality increases, climate change-associated increases are significantly higher in young than old forests, and higher increases in younger forests are a result of their higher sensitivity to regional warming and drought. We anticipate our analysis to be a starting point for more comprehensive examinations of how forest ecosystems might respond to climate change.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson-Teixeira, Kristina J.; Davies, Stuart J.; Bennett, Amy C.

2014-09-25

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services, including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamic research sites useful for characterizing forest responses to global change. The broad suite of measurements made at the CTFS-ForestGEO sites make it possible to investigate the complex ways in which global change is impacting forest dynamics. ongoing research across the network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forestmore » diversity and dynamics in a era of global change« less

A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont

PubMed Central

Beckage, Brian; Osborne, Ben; Gavin, Daniel G.; Pucko, Carolyn; Siccama, Thomas; Perkins, Timothy

2008-01-01

Detecting latitudinal range shifts of forest trees in response to recent climate change is difficult because of slow demographic rates and limited dispersal but may be facilitated by spatially compressed climatic zones along elevation gradients in montane environments. We resurveyed forest plots established in 1964 along elevation transects in the Green Mountains (Vermont) to examine whether a shift had occurred in the location of the northern hardwood–boreal forest ecotone (NBE) from 1964 to 2004. We found a 19% increase in dominance of northern hardwoods from 70% in 1964 to 89% in 2004 in the lower half of the NBE. This shift was driven by a decrease (up to 76%) in boreal and increase (up to 16%) in northern hardwood basal area within the lower portions of the ecotone. We used aerial photographs and satellite imagery to estimate a 91- to 119-m upslope shift in the upper limits of the NBE from 1962 to 2005. The upward shift is consistent with regional climatic change during the same period; interpolating climate data to the NBE showed a 1.1°C increase in annual temperature, which would predict a 208-m upslope movement of the ecotone, along with a 34% increase in precipitation. The rapid upward movement of the NBE indicates little inertia to climatically induced range shifts in montane forests; the upslope shift may have been accelerated by high turnover in canopy trees that provided opportunities for ingrowth of lower elevation species. Our results indicate that high-elevation forests may be jeopardized by climate change sooner than anticipated. PMID:18334647

Preliminary Assessment of JERS-1 SAR to Discriminating Boreal Landscape Features for the Boreal Forest Mapping Project

NASA Technical Reports Server (NTRS)

McDonald, Kyle; Williams, Cynthia; Podest, Erika; Chapman, Bruce

1999-01-01

This paper presents an overview of the JERS-1 North American Boreal Forest Mapping Project and a preliminary assessment of JERS-1 SAR imagery for application to discriminating features applicable to boreal landscape processes. The present focus of the JERS-1 North American Boreal Forest Mapping Project is the production of continental scale wintertime and summertime SAR mosaics of the North American boreal forest for distribution to the science community. As part of this effort, JERS-1 imagery has been collected over much of Alaska and Canada during the 1997-98 winter and 1998 summer seasons. To complete the mosaics, these data will be augmented with data collected during previous years. These data will be made available to the scientific community via CD ROM containing these and similar data sets compiled from companion studies of Asia and Europe. Regional landscape classification with SAR is important for the baseline information it will provide about distribution of woodlands, positions of treeline, current forest biomass, distribution of wetlands, and extent of major rivercourses. As well as setting the stage for longer term change detection, comparisons across several years provides additional baseline information about short-term landscape change. Rapid changes, including those driven by fire, permafrost heat balance, flooding, and insect outbreaks can dominate boreal systems. We examine JERS-1 imagery covering selected sites in Alaska and Canada to assess quality and applicability to such relevant ecological and hydrological issues. The data are generally of high quality and illustrate many potential applications. A texture-based classification scheme is applied to selected regions to assess the applicability of these data for distinguishing distribution of such landcover types as wetland, tundra, woodland and forested landscapes.

Mapping and detecting bark beetle-caused tree mortality in the western United States

NASA Astrophysics Data System (ADS)

Meddens, Arjan J. H.

Recently, insect outbreaks across North America have dramatically increased and the forest area affected by bark beetles is similar to that affected by fire. Remote sensing offers the potential to detect insect outbreaks with high accuracy. Chapter one involved detection of insect-caused tree mortality on the tree level for a 90km2 area in northcentral Colorado. Classes of interest included green trees, multiple stages of post-insect attack tree mortality including dead trees with red needles ("red-attack") and dead trees without needles ("gray-attack"), and non-forest. The results illustrated that classification of an image with a spatial resolution similar to the area of a tree crown outperformed that from finer and coarser resolution imagery for mapping tree mortality and non-forest classes. I also demonstrated that multispectral imagery could be used to separate multiple postoutbreak attack stages (i.e., red-attack and gray-attack) from other classes in the image. In Chapter 2, I compared and improved methods for detecting bark beetle-caused tree mortality using medium-resolution satellite data. I found that overall classification accuracy was similar between single-date and multi-date classification methods. I developed regression models to predict percent red attack within a 30-m grid cell and these models explained >75% of the variance using three Landsat spectral explanatory variables. Results of the final product showed that approximately 24% of the forest within the Landsat scene was comprised of tree mortality caused by bark beetles. In Chapter 3, I developed a gridded data set with 1-km2 resolution using aerial survey data and improved estimates of tree mortality across the western US and British Columbia. In the US, I also produced an upper estimate by forcing the mortality area to match that from high-resolution imagery in Idaho, Colorado, and New Mexico. Cumulative mortality area from all bark beetles was 5.46 Mha in British Columbia in 2001-2010 and 0.47-5.37 Mha (lower and upper estimate) in the western conterminous US during 1997-2010. Improved methods for detection and mapping of insect outbreak areas will lead to improved assessments of the effects of these forest disturbances on the economy, carbon cycle (and feedback to climate change), fuel loads, hydrology and forest ecology.

Soil organic carbon and total nitrogen gains in an old growth deciduous forest in Germany.

PubMed

Schrumpf, Marion; Kaiser, Klaus; Schulze, Ernst-Detlef

2014-01-01

Temperate forests are assumed to be organic carbon (OC) sinks, either because of biomass increases upon elevated CO2 in the atmosphere and large nitrogen deposition, or due to their age structure. Respective changes in soil OC and total nitrogen (TN) storage have rarely been proven. We analysed OC, TN, and bulk densities of 100 soil cores sampled along a regular grid in an old-growth deciduous forest at the Hainich National Park, Germany, in 2004 and again in 2009. Concentrations of OC and TN increased significantly from 2004 to 2009, mostly in the upper 0-20 cm of the mineral soil. Changes in the fine earth masses per soil volume impeded the detection of OC changes based on fixed soil volumes. When calculated on average fine earth masses, OC stocks increased by 323 ± 146 g m(-2) and TN stocks by 39 ± 10 g m(-2) at 0-20 cm soil depth from 2004 to 2009, giving average annual accumulation rates of 65 ± 29 g OC m(-2) yr(-1) and 7.8 ± 2 g N m(-2) yr(-1). Accumulation rates were largest in the upper part of the B horizon. Regional increases in forest biomass, either due to recovery of forest biomass from previous forest management or to fertilization by elevated CO2 and N deposition, are likely causes for the gains in soil OC and TN. As TN increased stronger (1.3% yr(-1) of existing stocks) than OC (0.9% yr(-1)), the OC-to-TN ratios declined significantly. Results of regression analyses between changes in OC and TN stocks suggest that at no change in OC, still 3.8 g TN m(-2) yr(-1) accumulated. Potential causes for the increase in TN in excess to OC are fixation of inorganic N by the clay-rich soil or changes in microbial communities. The increase in soil OC corresponded on average to 6-13% of the estimated increase in net biome productivity.

Determination of Destructed and Infracted Forest Areas with Multi-temporal High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Seker, D. Z.; Unal, A.; Kaya, S.; Alganci, U.

2015-12-01

Migration from rural areas to city centers and their surroundings is an important problem of not only our country but also the countries that under development stage. This uncontrolled and huge amount of migration brings out urbanization and socio - economic problems. The demand on settling the industrial areas and commercial activities nearby the city centers results with a negative change in natural land cover on cities. Negative impacts of human induced activities on natural resources and land cover has been continuously increasing for decades. The main human activities that resulted with destruction and infraction of forest areas can be defined as mining activities, agricultural activities, industrial / commercial activities and urbanization. Temporal monitoring of the changes in spatial distribution of forest areas is significantly important for effective management and planning progress. Changes can occur as spatially large destructions or small infractions. Therefore there is a need for reliable, fast and accurate data sources. At this point, satellite images proved to be a good data source for determination of the land use /cover changes with their capability of monitoring large areas with reasonable temporal resolutions. Spectral information derived from images provides discrimination of land use/cover types from each other. Developments in remote sensing technology in the last decade improved the spatial resolution of satellites and high resolution images were started to be used to detect even small changes in the land surface. As being the megacity of Turkey, Istanbul has been facing a huge migration for the last 20 years and effects of urbanization and other human based activities over forest areas are significant. Main focus of this study is to determine the destructions and infractions in forest areas of Istanbul, Turkey with 2.5m resolution SPOT 5 multi-temporal satellite imagery. Analysis was mainly constructed on threshold based classification of multi-temporal vegetation index data derived from satellite images. Determined changes were exported to GIS environment and spatial overlay and intersection analyses were performed with use of forest type maps and authorized area maps in order to demonstrate the actual situation of destructions and infractions.

Soil Organic Carbon and Total Nitrogen Gains in an Old Growth Deciduous Forest in Germany

PubMed Central

Schrumpf, Marion; Kaiser, Klaus; Schulze, Ernst-Detlef

2014-01-01

Temperate forests are assumed to be organic carbon (OC) sinks, either because of biomass increases upon elevated CO2 in the atmosphere and large nitrogen deposition, or due to their age structure. Respective changes in soil OC and total nitrogen (TN) storage have rarely been proven. We analysed OC, TN, and bulk densities of 100 soil cores sampled along a regular grid in an old-growth deciduous forest at the Hainich National Park, Germany, in 2004 and again in 2009. Concentrations of OC and TN increased significantly from 2004 to 2009, mostly in the upper 0–20 cm of the mineral soil. Changes in the fine earth masses per soil volume impeded the detection of OC changes based on fixed soil volumes. When calculated on average fine earth masses, OC stocks increased by 323±146 g m−2 and TN stocks by 39±10 g m−2 at 0–20 cm soil depth from 2004 to 2009, giving average annual accumulation rates of 65±29 g OC m−2 yr−1 and 7.8±2 g N m−2 yr−1. Accumulation rates were largest in the upper part of the B horizon. Regional increases in forest biomass, either due to recovery of forest biomass from previous forest management or to fertilization by elevated CO2 and N deposition, are likely causes for the gains in soil OC and TN. As TN increased stronger (1.3% yr−1 of existing stocks) than OC (0.9% yr−1), the OC-to-TN ratios declined significantly. Results of regression analyses between changes in OC and TN stocks suggest that at no change in OC, still 3.8 g TN m−2 yr−1 accumulated. Potential causes for the increase in TN in excess to OC are fixation of inorganic N by the clay-rich soil or changes in microbial communities. The increase in soil OC corresponded on average to 6–13% of the estimated increase in net biome productivity. PMID:24586720

Examining the sensitivity of modelled evapotranspiration to vegetation structural characteristics within boreal peatlands, riparian ecosystems and upland mixedwood forest

NASA Astrophysics Data System (ADS)

Petrone, R. M.; Chasmer, L. E.; Brown, S. M.; Mendoza, C. A.; Diiwu, J.; Quinton, W. L.; Hopkinson, C.; Devito, K. J.

2010-12-01

The Western Boreal Plain (WBP) of northern Alberta is comprised of a complex mosaic of small ponds, riparian buffer zones, and upland aspen dominated mixedwood forests surrounded by low-lying peatlands. The hydrology of the WBP is strongly influenced by climatic drivers and geology, whereby water budgets are often controlled by vertical fluxes. During most years, potential evapotranspiration (PET) exceeds precipitation (P), and changes in P as a result of climatic change will likely alter actual evapotranspiration (AET) and regional water balances. In recent years, the WBP has also undergone intense anthropogenic disturbance via oil and gas exploration and extraction, and silvicultural and forest harvesting activities. The extent to which changes in land cover types/characteristics affect estimates of PET and AET is currently unknown. This study examines the sensitivity of PET using a simple estimate of equilibrium ET (Priestley-Taylor) and AET (Penman-Monteith variant) to variability in canopy structural and ground surface characteristics at 12 sites throughout the 2008 growing season (June, July, August). Energy balance meteorological stations are deployed within four peatland ecosystems, four riparian buffer zones, two regenerating upland mixedwood forests and two mature upland mixedwood forests. Airborne Light Detection and Ranging (LiDAR) is used to derive metrics of canopy height, leaf area index (LAI), uplands and lowlands, elevation, zero plane displacement, roughness length governing momentum, roughness length governing heat and vapour, and understory vegetation characteristics. LiDAR land surface metrics and energy balance measurements are used to model evapotranspiration for classified land cover types throughout the larger basin. Sensitivity of potential and actual estimates to changes in land cover characteristics within each of the three land cover types (peatland, riparian and upland) is quantified.

Decadal land cover change dynamics in Bhutan.

PubMed

Gilani, Hammad; Shrestha, Him Lal; Murthy, M S R; Phuntso, Phuntso; Pradhan, Sudip; Bajracharya, Birendra; Shrestha, Basanta

2015-01-15

Land cover (LC) is one of the most important and easily detectable indicators of change in ecosystem services and livelihood support systems. This paper describes the decadal dynamics in LC changes at national and sub-national level in Bhutan derived by applying object-based image analysis (OBIA) techniques to 1990, 2000, and 2010 Landsat (30 m spatial resolution) data. Ten LC classes were defined in order to give a harmonized legend land cover classification system (LCCS). An accuracy of 83% was achieved for LC-2010 as determined from spot analysis using very high resolution satellite data from Google Earth Pro and limited field verification. At the national level, overall forest increased from 25,558 to 26,732 km(2) between 1990 and 2010, equivalent to an average annual growth rate of 59 km(2)/year (0.22%). There was an overall reduction in grassland, shrubland, and barren area, but the observations were highly dependent on time of acquisition of the satellite data and climatic conditions. The greatest change from non-forest to forest (277 km(2)) was in Bumthang district, followed by Wangdue Phodrang and Trashigang, with the least (1 km(2)) in Tsirang. Forest and scrub forest covers close to 75% of the land area of Bhutan, and just over half of the total area (51%) has some form of conservation status. This study indicates that numerous applications and analyses can be carried out to support improved land cover and land use (LCLU) management. It will be possible to replicate this study in the future as comparable new satellite data is scheduled to become available. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using Landsat to Diagnose Trends in Disturbance Magnitude Across the National Forest System

NASA Astrophysics Data System (ADS)

Hernandez, A. J.; Healey, S. P.; Stehman, S. V.; Ramsey, R. D.

2014-12-01

The Landsat archive is increasingly being used to detect trends in the occurrence of forest disturbance. Beyond information about the amount of area affected, forest managers need to know if and how disturbance severity is changing. For example, the United States National Forest System (NFS) has developed a comprehensive plan for carbon monitoring, which requires a detailed temporal mapping of forest disturbance magnitudes across 75 million hectares. To meet this need, we have prepared multitemporal models of percent canopy cover that were calibrated with extensive field data from the USFS Forest Inventory and Analysis Program (FIA). By applying these models to pre- and post-event Landsat images at the site of known disturbances, we develop maps showing first-order estimates of disturbance magnitude on the basis of cover removal. However, validation activities consistently show that these initial estimates under-estimate disturbance magnitude. We have developed an approach, which quantifies this under-prediction at the landscape level and uses empirical validation data to adjust change magnitude estimates derived from initial disturbance maps. In an assessment of adjusted magnitude trends of NFS' Northern Region from 1990 to the present, we observed significant declines since 1990 (p < .01) in harvest magnitude, likely related to known reduction of clearcutting practices in the region. Fire, conversely, did not show strongly significant trends in magnitude, despite an increase in the overall area affected. As Landsat is used to provide increasingly precise maps of the timing and location of historical forest disturbance, a logical next step is to use the archive to generate widely interpretable and objective estimates of disturbance magnitude.

Estimating Species Richness and Modelling Habitat Preferences of Tropical Forest Mammals from Camera Trap Data

PubMed Central

Rovero, Francesco; Martin, Emanuel; Rosa, Melissa; Ahumada, Jorge A.; Spitale, Daniel

2014-01-01

Medium-to-large mammals within tropical forests represent a rich and functionally diversified component of this biome; however, they continue to be threatened by hunting and habitat loss. Assessing these communities implies studying species’ richness and composition, and determining a state variable of species abundance in order to infer changes in species distribution and habitat associations. The Tropical Ecology, Assessment and Monitoring (TEAM) network fills a chronic gap in standardized data collection by implementing a systematic monitoring framework of biodiversity, including mammal communities, across several sites. In this study, we used TEAM camera trap data collected in the Udzungwa Mountains of Tanzania, an area of exceptional importance for mammal diversity, to propose an example of a baseline assessment of species’ occupancy. We used 60 camera trap locations and cumulated 1,818 camera days in 2009. Sampling yielded 10,647 images of 26 species of mammals. We estimated that a minimum of 32 species are in fact present, matching available knowledge from other sources. Estimated species richness at camera sites did not vary with a suite of habitat covariates derived from remote sensing, however the detection probability varied with functional guilds, with herbivores being more detectable than other guilds. Species-specific occupancy modelling revealed novel ecological knowledge for the 11 most detected species, highlighting patterns such as ‘montane forest dwellers’, e.g. the endemic Sanje mangabey (Cercocebus sanjei), and ‘lowland forest dwellers’, e.g. suni antelope (Neotragus moschatus). Our results show that the analysis of camera trap data with account for imperfect detection can provide a solid ecological assessment of mammal communities that can be systematically replicated across sites. PMID:25054806

Differential Response of Acidobacteria Subgroups to Forest-to-Pasture Conversion and Their Biogeographic Patterns in the Western Brazilian Amazon

PubMed Central

Navarrete, Acacio A.; Venturini, Andressa M.; Meyer, Kyle M.; Klein, Ann M.; Tiedje, James M.; Bohannan, Brendan J. M.; Nüsslein, Klaus; Tsai, Siu M.; Rodrigues, Jorge L. M.

2015-01-01

Members of the phylum Acidobacteria are among the most abundant soil bacteria on Earth, but little is known about their response to environmental changes. We asked how the relative abundance and biogeographic patterning of this phylum and its subgroups responded to forest-to-pasture conversion in soils of the western Brazilian Amazon. Pyrosequencing of 16S rRNA genes was employed to assess the abundance and composition of the Acidobacteria community across 54 soil samples taken using a spatially nested sampling scheme at the landscape level. Numerically, Acidobacteria represented 20% of the total bacterial community in forest soils and 11% in pasture soils. Overall, 15 different Acidobacteria subgroups of the current 26 subgroups were detected, with Acidobacteria subgroups 1, 3, 5, and 6 accounting together for 87% of the total Acidobacteria community in forest soils and 75% in pasture soils. Concomitant with changes in soil chemistry after forest-to-pasture conversion—particularly an increase in properties linked to soil acidity and nutrient availability—we observed an increase in the relative abundances of Acidobacteria subgroups 4, 10, 17, and 18, and a decrease in the relative abundances of other Acidobacteria subgroups in pasture relative to forest soils. The composition of the total Acidobacteria community as well as the most abundant Acidobacteria subgroups (1, 3, 5, and 6) was significantly more similar in composition across space in pasture soils than in forest soils. These results suggest that preponderant responses of Acidobacteria subgroups, especially subgroups 1, 3, 4, 5, and 6, to forest-to-pasture conversion effects in soils could be used to define management-indicators of agricultural practices in the Amazon Basin. These acidobacterial responses are at least in part through alterations on acidity- and nutrient-related properties of the Amazon soils. PMID:26733981

Impacts of climate change on forest phenology and implications for streamflow in the central Appalachian Mountains region, United States

NASA Astrophysics Data System (ADS)

Zegre, N.; Gaertner, B. A.; Fernandez, R.

2016-12-01

The timing of phenological parameters such as spring onset and autumn senescence are important controls on the partitioning of water into evaporation and streamflow. Climate largely drives seasonal characteristics of plants and changes in phenological timing can be used to detect the impacts of climate change on water balance controls. However, limited phenological research is available for regions dominated by forest cover such as the central Appalachian Mountains region of the United States. To quantify the impacts of climate change on phenological timing and streamflow in this region, we used GIMMS AVHRR NDVI 13g data from 1982-2012 and the TIMESAT program to extract seasonality parameters. Results show that spring onset has advanced by 9 days, autumn senescence has been delayed by 11 days, and growing season has lengthened by 20 days. Above 500 m elevation, spring onset occurs 2-3 days later; fall senescence arrives 1-2 days earlier, and growing season shortens by 3-5 days. Streamflow has decreased during the growing season over the 31-year study period throughout the region, with the most pronounced effects for the Tennessee River watershed, the southernmost reach of the study area. The elevation patterns are in general agreement with Hopkins law, which states a one-day delay in spring onset for every 30-meter increase in elevation. Streamflow patterns suggest that the southern central Appalachian region is sensitive to changes in climate and are becoming drier, having important implications for drinking water supply, forest ecosystem management, ecosystem services including drinking water supply, and overall forest health.

Relating bat species presence to simple habitat measures in a central Appalachian forest

Treesearch

W. Mark Ford; Michael A. Menzel; Jane L. Rodrigue; Jennifer M. Menzel; Joshua B. Johnson; Joshua B. Johnson

2005-01-01

We actively sampled the bat community at 63 sites using detection and non- detection metrics on the Fernow Experimental Forest (FEF) in the central Appalachians of West Virginia using Anabat acoustical equipment May-June 2001-2003 to relate species presence to simple habitat measures such as proximity to riparian areas, forest canopy cover, forest canopy gap width, and...

Forest Fire Advanced System Technology (FFAST): A Conceptual Design for Detection and Mapping

Treesearch

J. David Nichols; John R. Warren

1987-01-01

The Forest Fire Advanced System Technology (FFAST) project is developing a data system to provide near-real-time forest fire information to fire management at the fire Incident Command Post (ICP). The completed conceptual design defined an integrated forest fire detection and mapping system that is based upon technology available in the 1990's. System component...

Using Stable Isotopes to Infer the Impacts of Habitat Change on the Diets and Vertical Stratification of Frugivorous Bats in Madagascar

PubMed Central

Reuter, Kim E.; Wills, Abigail R.; Lee, Raymond W.; Cordes, Erik E.; Sewall, Brent J.

2016-01-01

Human-modified habitats are expanding rapidly; many tropical countries have highly fragmented and degraded forests. Preserving biodiversity in these areas involves protecting species–like frugivorous bats–that are important to forest regeneration. Fruit bats provide critical ecosystem services including seed dispersal, but studies of how their diets are affected by habitat change have often been rather localized. This study used stable isotope analyses (δ15N and δ13C measurement) to examine how two fruit bat species in Madagascar, Pteropus rufus (n = 138) and Eidolon dupreanum (n = 52) are impacted by habitat change across a large spatial scale. Limited data for Rousettus madagascariensis are also presented. Our results indicated that the three species had broadly overlapping diets. Differences in diet were nonetheless detectable between P. rufus and E. dupreanum, and these diets shifted when they co-occurred, suggesting resource partitioning across habitats and vertical strata within the canopy to avoid competition. Changes in diet were correlated with a decrease in forest cover, though at a larger spatial scale in P. rufus than in E. dupreanum. These results suggest fruit bat species exhibit differing responses to habitat change, highlight the threats fruit bats face from habitat change, and clarify the spatial scales at which conservation efforts could be implemented. PMID:27097316

Climate change-associated trends in net biomass change are age dependent in western boreal forests of Canada.

PubMed

Chen, Han Y H; Luo, Yong; Reich, Peter B; Searle, Eric B; Biswas, Shekhar R

2016-09-01

The impacts of climate change on forest net biomass change are poorly understood but critical for predicting forest's contribution to the global carbon cycle. Recent studies show climate change-associated net biomass declines in mature forest plots. The representativeness of these plots for regional forests, however, remains uncertain because we lack an assessment of whether climate change impacts differ with forest age. Using data from plots of varying ages from 17 to 210 years, monitored from 1958 to 2011 in western Canada, we found that climate change has little effect on net biomass change in forests ≤ 40 years of age due to increased growth offsetting increased mortality, but has led to large decreases in older forests due to increased mortality accompanying little growth gain. Our analysis highlights the need to incorporate forest age profiles in examining past and projecting future forest responses to climate change. © 2016 John Wiley & Sons Ltd/CNRS.

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

NASA Astrophysics Data System (ADS)

Reyer, Christopher P. O.; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G.; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P.; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Guerra Hernández, Juan; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J.; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João HN; Paulo, Joana A.; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E.; Hanewinkel, Marc

2017-03-01

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

PubMed Central

Reyer, Christopher P O; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Hernández, Juan Guerra; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João HN; Paulo, Joana A; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E; Hanewinkel, Marc

2017-01-01

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures. PMID:28855959

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

PubMed

Reyer, Christopher P O; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Hernández, Juan Guerra; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João Hn; Paulo, Joana A; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E; Hanewinkel, Marc

2017-03-16

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease

Treesearch

Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

2011-01-01

Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate...

Long-term, high-spatial resolution carbon balance monitoring of the Amazonian frontier: Predisturbance and postdisturbance carbon emissions and uptake

NASA Astrophysics Data System (ADS)

Toomey, Michael; Roberts, Dar A.; Caviglia-Harris, Jill; Cochrane, Mark A.; Dewes, Candida F.; Harris, Daniel; Numata, Izaya; Sales, Marcio H.; Sills, Erin; Souza, Carlos M.

2013-06-01

We performed high-spatial and high-temporal resolution modeling of carbon stocks and fluxes in the state of Rondônia, Brazil for the period 1985-2009, using annual Landsat-derived land cover classifications and a modified bookkeeping modeling approach. According to these results, Rondônia contributed 3.5-4% of pantropical humid forest deforestation emissions over this period. Similar to well-known figures reported by the Brazilian Space Agency, we found a decline in deforestation rates since 2006. However, we estimate a lesser decrease, with deforestation rates continuing at levels similar to the early 2000s. Forest carbon stocks declined at an annual rate of 1.51%; emissions from postdisturbance land use nearly equaled those of the initial deforestation events. Carbon uptake by secondary forest was negligible due to limited spatial extent and high turnover rates. Net carbon emissions represented 93% of initial forest carbon stocks, due in part to repeated slash and pasture burnings and secondary forest clearing. We analyzed potential error incurred when spatially aggregating land cover by comparing results based on coarser-resolution (250 m) and full-resolution land cover products. At the coarser resolution, more than 90% of deforestation and secondary forest would be unresolvable, assuming that a 50% change threshold is necessary for detection. Therefore, we strongly suggest the use of Landsat-scale ( 30m) resolution carbon monitoring in tropical regions dominated by nonmechanized, smallholder land use change.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change.

PubMed

Anderson-Teixeira, Kristina J; Davies, Stuart J; Bennett, Amy C; Gonzalez-Akre, Erika B; Muller-Landau, Helene C; Wright, S Joseph; Abu Salim, Kamariah; Almeyda Zambrano, Angélica M; Alonso, Alfonso; Baltzer, Jennifer L; Basset, Yves; Bourg, Norman A; Broadbent, Eben N; Brockelman, Warren Y; Bunyavejchewin, Sarayudh; Burslem, David F R P; Butt, Nathalie; Cao, Min; Cardenas, Dairon; Chuyong, George B; Clay, Keith; Cordell, Susan; Dattaraja, Handanakere S; Deng, Xiaobao; Detto, Matteo; Du, Xiaojun; Duque, Alvaro; Erikson, David L; Ewango, Corneille E N; Fischer, Gunter A; Fletcher, Christine; Foster, Robin B; Giardina, Christian P; Gilbert, Gregory S; Gunatilleke, Nimal; Gunatilleke, Savitri; Hao, Zhanqing; Hargrove, William W; Hart, Terese B; Hau, Billy C H; He, Fangliang; Hoffman, Forrest M; Howe, Robert W; Hubbell, Stephen P; Inman-Narahari, Faith M; Jansen, Patrick A; Jiang, Mingxi; Johnson, Daniel J; Kanzaki, Mamoru; Kassim, Abdul Rahman; Kenfack, David; Kibet, Staline; Kinnaird, Margaret F; Korte, Lisa; Kral, Kamil; Kumar, Jitendra; Larson, Andrew J; Li, Yide; Li, Xiankun; Liu, Shirong; Lum, Shawn K Y; Lutz, James A; Ma, Keping; Maddalena, Damian M; Makana, Jean-Remy; Malhi, Yadvinder; Marthews, Toby; Mat Serudin, Rafizah; McMahon, Sean M; McShea, William J; Memiaghe, Hervé R; Mi, Xiangcheng; Mizuno, Takashi; Morecroft, Michael; Myers, Jonathan A; Novotny, Vojtech; de Oliveira, Alexandre A; Ong, Perry S; Orwig, David A; Ostertag, Rebecca; den Ouden, Jan; Parker, Geoffrey G; Phillips, Richard P; Sack, Lawren; Sainge, Moses N; Sang, Weiguo; Sri-Ngernyuang, Kriangsak; Sukumar, Raman; Sun, I-Fang; Sungpalee, Witchaphart; Suresh, Hebbalalu Sathyanarayana; Tan, Sylvester; Thomas, Sean C; Thomas, Duncan W; Thompson, Jill; Turner, Benjamin L; Uriarte, Maria; Valencia, Renato; Vallejo, Marta I; Vicentini, Alberto; Vrška, Tomáš; Wang, Xihua; Wang, Xugao; Weiblen, George; Wolf, Amy; Xu, Han; Yap, Sandra; Zimmerman, Jess

2015-02-01

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25 ha), all stems ≥ 1 cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 °S-61 °N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 °C), changes in precipitation (up to ± 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8 g N m(-2) yr(-1) and 3.1 g S m(-2) yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5 km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change. © 2014 John Wiley & Sons Ltd.

3D Vegetation Mapping Using UAVSAR, LVIS, and LIDAR Data Acquisition Methods

NASA Technical Reports Server (NTRS)

Calderon, Denice

2011-01-01

The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.

Effects of ice storm on forest ecosystem of southern China in 2008 Shaoqiang Wang1, Lei Zhou1, Weimin Ju2, Kun Huang1 1Key Lab of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Beijing, 10010

NASA Astrophysics Data System (ADS)

Wang, Shaoqiang

2014-05-01

Evidence is mounting that an increase in extreme climate events has begun to occur worldwide during the recent decades, which affect biosphere function and biodiversity. Ecosystems returned to its original structures and functions to maintain its sustainability, which was closely dependent on ecosystem resilience. Understanding the resilience and recovery capacity of ecosystem to extreme climate events is essential to predicting future ecosystem responses to climate change. Given the overwhelming importance of this region in the overall carbon cycle of forest ecosystems in China, south China suffered a destructive ice storm in 2008. In this study, we used the number of freezing day and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS) to characterize the spatial distribution of ice storm region in southeastern China and explore the impacts on carbon cycle of forest ecosystem over the past decade. The ecosystem variables, i.e. Net primary productivity (NPP), Evapotranspiration (ET), and Water use efficiency (WUE, the ratio of NPP to ET) from the outputs of BEPS models were used to detect the resistance and resilience of forest ecosystem in southern China. The pattern of ice storm-induced forest productivity widespread decline was closely related to the number of freezing day during the ice storm period. The NPP of forest area suffered heavy ice storm returned to normal status after five months with high temperature and ample moisture, indicated a high resilience of subtropical forest in China. The long-term changes of forest WUE remain stable, behaving an inherent sensitivity of ecosystem to extreme climate events. In addition, ground visits suggested that the recovery of forest productivity was attributed to rapid growth of understory. Understanding the variability and recovery threshold of ecosystem following extreme climate events help us to better simulate and predict the variability of ecosystem structure and function under current and future climate change.

Large-scale pattern of genetic differentiation within African rainforest trees: insights on the roles of ecological gradients and past climate changes on the evolution of Erythrophleum spp (Fabaceae).

PubMed

Duminil, Jerome; Brown, Richard P; Ewédjè, Eben-Ezer B K; Mardulyn, Patrick; Doucet, Jean-Louis; Hardy, Olivier J

2013-09-12

The evolutionary events that have shaped biodiversity patterns in the African rainforests are still poorly documented. Past forest fragmentation and ecological gradients have been advocated as important drivers of genetic differentiation but their respective roles remain unclear. Using nuclear microsatellites (nSSRs) and chloroplast non-coding sequences (pDNA), we characterised the spatial genetic structure of Erythrophleum (Fabaceae) forest trees in West and Central Africa (Guinea Region, GR). This widespread genus displays a wide ecological amplitude and taxonomists recognize two forest tree species, E. ivorense and E. suaveolens, which are difficult to distinguish in the field and often confused. Bayesian-clustering applied on nSSRs of a blind sample of 648 specimens identified three major gene pools showing no or very limited introgression. They present parapatric distributions correlated to rainfall gradients and forest types. One gene pool is restricted to coastal evergreen forests and corresponds to E. ivorense; a second one is found in gallery forests from the dry forest zone of West Africa and North-West Cameroon and corresponds to West-African E. suaveolens; the third gene pool occurs in semi-evergreen forests and corresponds to Central African E. suaveolens. These gene pools have mostly unique pDNA haplotypes but they do not form reciprocally monophyletic clades. Nevertheless, pDNA molecular dating indicates that the divergence between E. ivorense and Central African E. suaveolens predates the Pleistocene. Further Bayesian-clustering applied within each major gene pool identified diffuse genetic discontinuities (minor gene pools displaying substantial introgression) at a latitude between 0 and 2°N in Central Africa for both species, and at a longitude between 5° and 8°E for E. ivorense. Moreover, we detected evidence of past population declines which are consistent with historical habitat fragmentation induced by Pleistocene climate changes. Overall, deep genetic differentiation (major gene pools) follows ecological gradients that may be at the origin of speciation, while diffuse differentiation (minor gene pools) are tentatively interpreted as the signature of past forest fragmentation induced by past climate changes.

Large-scale pattern of genetic differentiation within African rainforest trees: insights on the roles of ecological gradients and past climate changes on the evolution of Erythrophleum spp (Fabaceae)

PubMed Central

2013-01-01

Background The evolutionary events that have shaped biodiversity patterns in the African rainforests are still poorly documented. Past forest fragmentation and ecological gradients have been advocated as important drivers of genetic differentiation but their respective roles remain unclear. Using nuclear microsatellites (nSSRs) and chloroplast non-coding sequences (pDNA), we characterised the spatial genetic structure of Erythrophleum (Fabaceae) forest trees in West and Central Africa (Guinea Region, GR). This widespread genus displays a wide ecological amplitude and taxonomists recognize two forest tree species, E. ivorense and E. suaveolens, which are difficult to distinguish in the field and often confused. Results Bayesian-clustering applied on nSSRs of a blind sample of 648 specimens identified three major gene pools showing no or very limited introgression. They present parapatric distributions correlated to rainfall gradients and forest types. One gene pool is restricted to coastal evergreen forests and corresponds to E. ivorense; a second one is found in gallery forests from the dry forest zone of West Africa and North-West Cameroon and corresponds to West-African E. suaveolens; the third gene pool occurs in semi-evergreen forests and corresponds to Central African E. suaveolens. These gene pools have mostly unique pDNA haplotypes but they do not form reciprocally monophyletic clades. Nevertheless, pDNA molecular dating indicates that the divergence between E. ivorense and Central African E. suaveolens predates the Pleistocene. Further Bayesian-clustering applied within each major gene pool identified diffuse genetic discontinuities (minor gene pools displaying substantial introgression) at a latitude between 0 and 2°N in Central Africa for both species, and at a longitude between 5° and 8°E for E. ivorense. Moreover, we detected evidence of past population declines which are consistent with historical habitat fragmentation induced by Pleistocene climate changes. Conclusions Overall, deep genetic differentiation (major gene pools) follows ecological gradients that may be at the origin of speciation, while diffuse differentiation (minor gene pools) are tentatively interpreted as the signature of past forest fragmentation induced by past climate changes. PMID:24028582

Comparison of the carbon stock in forest soil of sessile oak and beech forests

NASA Astrophysics Data System (ADS)

Horváth, Adrienn; Bene, Zsolt; Bidló, András

2016-04-01

Forest ecosystems are the most important carbon sinks. The forest soils play an important role in the global carbon cycle, because the global climate change or the increase of atmospheric CO2 level. We do not have enough data about the carbon stock of soils and its change due to human activities, which have similar value to carbon content of biomass. In our investigation we measured the carbon stock of soil in 10 stands of Quercus petraea and Fagus sylvatica. We took a 1.1 m soil column with soil borer and divided to 11 samples each column. The course organic and root residues were moved. After evaluation, we compared our results with other studies and the carbon stock of forests to each other. Naturally, the amount of SOC was the highest in the topsoil layers. However, we found significant difference between forest stands which stayed on the same homogenous bedrock, but very close to each other (e.g. distance was 1 or 2 km). We detected that different forest utilizations and tree species have an effect on the forest carbon as the litter as well (amount, composition). In summary, we found larger amount (99.1 C t/ha on average) of SOC in soil of stands, where sessile oak were the main stand-forming tree species. The amount of carbon was the least in turkey oak-sessile oak stands (85.4 C t/ha on average). We found the highest SOC (118.3 C t/ha) in the most mixed stand (silver lime-beech-red oak). In the future, it will be very important: How does climate change affect the spread of tree species or on carbon storage? Beech is more sensitive, but even sessile oak. These species are expected to replace with turkey oak, which is less sensitive to drought. Thus, it is possible in the future that we can expect to decrease of forest soil carbon stock capacity, which was confirmed by our experiment. Keywords: carbon sequestration, mitigation, Fagus sylvatica, Quercus petraea, litter Acknowledgements: Research is supported by the "Agroclimate.2" (VKSZ_12-1-2013-0034) EU-national joint funded research project.

Assessing rates of forest change and fragmentation in Alabama, USA, using the vegetation change tracker model

USGS Publications Warehouse

Li, Mingshi; Huang, Chengquan; Zhu, Zhiliang; Shi, Hua; Lu, Heng; Peng, Shikui

2009-01-01

Forest change is of great concern for land use decision makers and conservation communities. Quantitative and spatial forest change information is critical for addressing many pressing issues, including global climate change, carbon budgets, and sustainability. In this study, our analysis focuses on the differences in geospatial patterns and their changes between federal forests and nonfederal forests in Alabama over the time period 1987–2005, by interpreting 163 Landsat Thematic Mapper (TM) scenes using a vegetation change tracker (VCT) model. Our analysis revealed that for the most part of 1990 s and between 2000 and 2005, Alabama lost about 2% of its forest on an annual basis due to disturbances, but much of the losses were balanced by forest regeneration from previous disturbances. The disturbance maps revealed that federal forests were reasonably well protected, with the fragmentation remaining relatively stable over time. In contrast, nonfederal forests, which are predominant in area share (about 95%), were heavily disturbed, clearly demonstrating decreasing levels of fragmentation during the time period 1987–1993 giving way to a subsequent accelerating fragmentation during the time period 1994–2005. Additionally, the identification of the statistical relationships between forest fragmentation status and forest loss rate and forest net change rate in relation to land ownership implied the distinct differences in forest cutting rate and cutting patterns between federal forests and nonfederal forests. The forest spatial change information derived from the model has provided valuable insights regarding regional forest management practices and disturbance regimes, which are closely associated with regional economics and environmental concerns.

Forest defoliator outbreaks under climate change: effects on the frequency and severity of outbreaks of five pine insect pests.

PubMed

Haynes, Kyle J; Allstadt, Andrew J; Klimetzek, Dietrich

2014-06-01

To identify general patterns in the effects of climate change on the outbreak dynamics of forest-defoliating insect species, we examined a 212-year record (1800-2011) of outbreaks of five pine-defoliating species (Bupalus piniarius, Panolis flammea, Lymantria monacha, Dendrolimus pini, and Diprion pini) in Bavaria, Germany for the evidence of climate-driven changes in the severity, cyclicity, and frequency of outbreaks. We also accounted for historical changes in forestry practices and examined effects of past insecticide use to suppress outbreaks. Analysis of relationships between severity or occurrence of outbreaks and detrended measures of temperature and precipitation revealed a mixture of positive and negative relationships between temperature and outbreak activity. Two moth species (P. flammea and Dendrolimus pini) exhibited lower outbreak activity following years or decades of unusually warm temperatures, whereas a sawfly (Diprion pini), for which voltinism is influenced by temperature, displayed increased outbreak occurrence in years of high summer temperatures. We detected only one apparent effect of precipitation, which showed Dendrolimus pini outbreaks tending to follow drought. Wavelet analysis of outbreak time series suggested climate change may be associated with collapse of L. monacha and Dendrolimus pini outbreak cycles (loss of cyclicity and discontinuation of outbreaks, respectively), but high-frequency cycles for B. piniarius and P. flammea in the late 1900s. Regional outbreak severity was generally not related to past suppression efforts (area treated with insecticides). Recent shifts in forestry practices affecting tree species composition roughly coincided with high-frequency outbreak cycles in B. piniarius and P. flammea but are unlikely to explain the detected relationships between climate and outbreak severity or collapses of outbreak cycles. Our results highlight both individualistic responses of different pine-defoliating species to climate changes and some patterns that are consistent across defoliator species in this and other forest systems, including collapsing of population cycles. © 2014 John Wiley & Sons Ltd.

Forest environmental investments and implications for climate change mitigation.

Treesearch

Ralph J. Alig; Lucas S. Bair

2006-01-01

Forest environmental conditions are affected by climate change, but investments in forest environmental quality can be used as part of the climate change mitigation strategy. A key question involving the potential use of forests to store more carbon as part of climate change mitigation is the impact of forest investments on the timing and quantity of forest volumes...

Climate change and forest diseases

Treesearch

R.N. Sturrock; Susan Frankel; A. V. Brown; Paul Hennon; J. T. Kliejunas; K. J. Lewis; J. J. Worrall; A. J. Woods

2011-01-01

As climate changes, the effects of forest diseases on forest ecosystems will change. We review knowledge of relationships between climate variables and several forest diseases, as well as current evidence of how climate, host and pathogen interactions are responding or might respond to climate change. Many forests can be managed to both adapt to climate change and...

Appendix: Assessment of watershed vulnerability to climate change - Pilot National Forest reports

Treesearch

Michael J. Furniss; Ken B. Roby; Dan Cenderelli; John Chatel; Caty F. Clifton; Alan Clingenpeel; Polly E. Hays; Dale Higgins; Ken Hodges; Carol Howe; Laura Jungst; Joan Louie; Christine Mai; Ralph Martinez; Kerry Overton; Brian P. Staab; Rory Steinke; Mark Weinhold

2013-01-01

Assessment of watershed vulnerability to climate change. Pilot National Forest reports: Gallatin National Forest, Helena National Forest, Grand Mesa, Uncompahgre, and Gunnison National Forests, White River National Forest, Coconino National Forest, Sawtooth National Forest, Shasta-Trinity National Forest, Umatilla National Forest, Umatilla National Forest, Ouachita...

Quantifying widespread canopy cover decline through the course of a beetle kill epidemic in Colorado with remote sensing of snow

NASA Astrophysics Data System (ADS)

Baker, E. H.; Raleigh, M. S.; Molotch, N. P.

2014-12-01

Since the mid-1990s, outbreaks of aggressive bark beetle species have caused extensive forest morality across 600,000 km2 of North-American forests, killing over 17,800 km2 of forest in Colorado alone. This mortality has resulted in a widespread, spatially heterogeneous decline of forest canopies, which in turn exerts strong controls on the accumulation and melt of the snowpack. In the Western United States, where approximately 70-80% of total annual runoff originates as mountain snowmelt, it is important to monitor and quantify changes in forest canopy in snow-dominated catchments. To quantify annual values of forest canopy cover, this research develops a metric from time series of daily fractional snow covered area (FSCA) from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow covered area and grain size (MODSCAG) algorithm. In areas where soil and rock are completely snow-covered, a land pixel is composed only of forest canopy and snow. Following a snowfall event, FSCA initially rises rapidly, as snow is intercepted in the canopy, and then declines, as snow unloads from the canopy. The lower of these local minima form a threshold representative of snow-free canopy conditions, which serves as a spatially explicit metric of forest canopy. Investigation of a site in southern Colorado with over 40% spruce beetle mortality shows a statistically significant decrease of canopy cover, from 76 (±4)% pre-infestation to 55 (±8)% post-infestation (t=-5.1, p<0.01). Additionally, this yearly parameterization of forest canopy is well correlated (ρ=0.76, p<0.01) with an independent product of yearly crown mortality derived from U.S. Forest Service Aerial Detection Surveys. Future work will examine this relationship across varied ecologic settings and geographic locations, and incorporate field measurements of species-specific canopy change after beetle kill.

A Statistical Methodology for Detecting and Monitoring Change in Forest Ecosystems Using Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Mills, R. T.; Kumar, J.; Hoffman, F. M.; Hargrove, W. W.; Spruce, J.

2011-12-01

Variations in vegetation phenology, the annual temporal pattern of leaf growth and senescence, can be a strong indicator of ecological change or disturbance. However, phenology is also strongly influenced by seasonal, interannual, and long-term trends in climate, making identification of changes in forest ecosystems a challenge. Forest ecosystems are vulnerable to extreme weather events, insect and disease attacks, wildfire, harvesting, and other land use change. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a proxy for phenology. NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) at 250 m resolution was used in this study to develop phenological signatures of ecological regimes called phenoregions. By applying a quantitative data mining technique to the NDVI measurements for every eight days over the entire MODIS record, annual maps of phenoregions were developed. This geospatiotemporal cluster analysis technique employs high performance computing resources, enabling analysis of such very large data sets. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. Analysis of the shifts among phenological states yields information about responses to interannual climate variability and, more importantly, changes in ecosystem health due to disturbances. Moreover, a large change in the phenological states occupied by a single location over time indicates a significant disturbance or ecological shift. This methodology has been applied for identification of various forest disturbance events, including wildfire, tree mortality due to Mountain Pine Beetle, and other insect infestation and diseases, as well as extreme events like storms and hurricanes in the U.S. Presented will be results from analysis of phenological state dynamics, along with disturbance and validation data.

A worldwide analysis of the impact of forest cover change on annual runoff across multiple spatial scales

NASA Astrophysics Data System (ADS)

Zhang, M.; Liu, S.

2017-12-01

Despite extensive studies on hydrological responses to forest cover change in small watersheds, the hydrological responses to forest change and associated mechanisms across multiple spatial scales have not been fully understood. This review thus examined about 312 watersheds worldwide to provide a generalized framework to evaluate hydrological responses to forest cover change and to identify the contribution of spatial scale, climate, forest type and hydrological regime in determining the intensity of forest change related hydrological responses in small (<1000 km2) and large watersheds (≥1000 km2). Key findings include: 1) the increase in annual runoff associated with forest cover loss is statistically significant at multiple spatial scales whereas the effect of forest cover gain is statistically inconsistent; 2) the sensitivity of annual runoff to forest cover change tends to attenuate as watershed size increases only in large watersheds; 3) annual runoff is more sensitive to forest cover change in water-limited watersheds than in energy-limited watersheds across all spatial scales; and 4) small mixed forest-dominated watersheds or large snow-dominated watersheds are more hydrologically resilient to forest cover change. These findings improve the understanding of hydrological response to forest cover change at different spatial scales and provide a scientific underpinning to future watershed management in the context of climate change and increasing anthropogenic disturbances.

Lidar Technique for Early Forest Fire Detection : Design and Development Aspects

NASA Astrophysics Data System (ADS)

Traïche, M.; Bourai, K.; Moussaoui, N.; Beggar, R.; Almabouada, F.; Louhibi, D.

2008-09-01

Many countries suffer from forest fires every summer, a phenomenon which wreaks havoc on both local and global environment. As well, it causes enormous damage to public health especially for people living in surrounding areas. For fighting against forest fires, ocular surveillance, in spite of its wide use, is not efficient owing to the costly mobilization of a great number of forest agents and to the fact that most of forest regions are not accessible. Other passive techniques such as infrared camera remote sensing are neither efficient under unfavorable weather conditions. An efficient way to early detect forest fires even under worse environmental conditions and in inaccessible mountainous regions uses the backscattering Lidar technique. This consists of the emission of monowavelength laser pulses spanning azimuthally the entire region subject to surveillance and the detection of the backscattered signal. The detection parameter is the signal to noise ration SNR. In this contribution, we will deal with approach and design aspects inherent to the development task of such a Lidar.

Are Brazil’s Deforesters Avoiding Detection?

PubMed Central

Richards, Peter; Arima, Eugenio; VanWey, Leah; Cohn, Avery; Bhattarai, Nishan

2017-01-01

Rates of deforestation reported by Brazil’s official deforestation monitoring system have declined dramatically in the Brazilian Amazon. Much of Brazil’s success in its fight against deforestation has been credited to a series of policy changes put into place between 2004 and 2008. In this research, we posit that one of these policies, the decision to use the country’s official system for monitoring forest loss in the Amazon as a policing tool, has incentivized landowners to deforest in ways and places that evade Brazil’s official monitoring and enforcement system. As a consequence, we a) show or b) provide several pieces of suggestive evidence that recent successes in protecting monitored forests in the Brazilian Amazon may be doing less to protect the region’s forests than previously assumed. PMID:29270225

Dominance of ammonia-oxidizing archaea community induced by land use change from Masson pine to eucalypt plantation in subtropical China.

PubMed

Zhang, Fang-Qiu; Pan, Wen; Gu, Ji-Dong; Xu, Bin; Zhang, Wei-Hua; Zhu, Bao-Zhu; Wang, Yu-Xia; Wang, Yong-Feng

2016-08-01

A considerable proportion of Masson pine forests have been converted into eucalypt plantations in the last 30 years in Guangdong Province, subtropical China, for economic reasons, which may affect the ammonia-oxidizing archaea (AOA) community and the process of ammonia transformation. In order to determine the effects of forest conversion on AOA community, AOA communities in a Masson pine (Pinus massoniana) plantation and a eucalypt (Eucalyptus urophylla) plantation, which was converted from the Masson pine, were compared. Results showed that the land use change from the Masson pine to the eucalypt plantation decreased soil nutrient levels. A significant decrease of the potential nitrification rates (PNR) was also observed after the forest conversion (p < 5 %, n = 6). AOA were the only ammonia oxidizers in both plantations (no ammonia-oxidizing bacteria were detected). The detected AOA are affiliated with the genera Nitrosotalea and Nitrososphaera. A decrease of AOA abundance and an increase of the diversity were evident with the plantation conversion in the surface layer. AOA amoA gene diversity was negatively correlated with organic C and total N, respectively (p < 0.05, n = 12). AOA amoA gene abundance was negatively correlated with NH4 (+) and available P, respectively (p < 0.05, n = 12). However, AOA abundance was positively correlated with PNR, but not significantly (p < 0.05, n = 6), indicating AOA community change was only a partial reason for the decrease of PNR.

The interplay between climate change, forests, and disturbances.

PubMed

Dale, V H; Joyce, L A; McNulty, S; Neilson, R P

2000-11-15

Climate change affects forests both directly and indirectly through disturbances. Disturbances are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. When disturbances exceed their natural range of variation, the change in forest structure and function may be extreme. Each disturbance affects forests differently. Some disturbances have tight interactions with the species and forest communities which can be disrupted by climate change. Impacts of disturbances and thus of climate change are seen over a board spectrum of spatial and temporal scales. Future observations, research, and tool development are needed to further understand the interactions between climate change and forest disturbances.

Where do forests influence rainfall?

NASA Astrophysics Data System (ADS)

Wang-Erlandsson, Lan; van der Ent, Ruud; Fetzer, Ingo; Keys, Patrick; Savenije, Hubert; Gordon, Line

2017-04-01

Forests play a major role in hydrology. Not only by immediate control of soil moisture and streamflow, but also by regulating climate through evaporation (i.e., transpiration, interception, and soil evaporation). The process of evaporation travelling through the atmosphere and returning as precipitation on land is known as moisture recycling. Whether evaporation is recycled depends on wind direction and geography. Moisture recycling and forest change studies have primarily focused on either one region (e.g. the Amazon), or one biome type (e.g. tropical humid forests). We will advance this via a systematic global inter-comparison of forest change impacts on precipitation depending on both biome type and geographic location. The rainfall effects are studied for three contemporary forest changes: afforestation, deforestation, and replacement of mature forest by forest plantations. Furthermore, as there are indications in the literature that moisture recycling in some places intensifies during dry years, we will also compare the rainfall impacts of forest change between wet and dry years. We model forest change effects on evaporation using the global hydrological model STEAM and trace precipitation changes using the atmospheric moisture tracking scheme WAM-2layers. This research elucidates the role of geographical location of forest change driven modifications on rainfall as a function of the type of forest change and climatic conditions. These knowledge gains are important at a time of both rapid forest and climate change. Our conclusions nuance our understanding of how forests regulate climate and pinpoint hotspot regions for forest-rainfall coupling.

Three Decades of Remote Sensing Based Tropical Forests Phenological Patterns and Trends

NASA Astrophysics Data System (ADS)

Didan, K.

2010-12-01

The faint climatic seasonality of tropical rain forests is believed to be the reason these biomes lack strong and detectable seasonality. Forest seasonality is a critical element of ecosystem functions. It moderates the echo-hydrology, carbon, and nutrient exchange of the area. While deciduous forests exhibit distinct and strong seasonality, tropical forests do not, yet they play a large role in the cycling of energy and mass. Tropical forests represent a large percentage of vegetated land and their importance to the Earth system stems from their biological diversity, their habitat role, their role in regulating global weather, and the role they play in carbon storage. While Tropical forests are well buffered by their sheer size, their vulnerability to climate change is exacerbated by the human pressure. All of this begs the questions of what are the patterns and characteristic of tropical forests phenology and are there any detectable trends over the last three decades of synoptic remote sensing. These three decades comprise different episodes of droughts and an ever increasing level of human encroachment. In so far understanding the function and dynamic of these biomes, field studies continue to play a major role, but synoptic remote sensing is emerging as a viable tool to addressing the spatial and temporal scale associated with this problem. Recent studies of Brazilian rainforest with synoptic remote sensing point to a sizable seasonal signal coincident with the dry season. However, these studies were not extensive in time or space and did not look at other rainforests. Using data from AVHRR and MODIS, we generated a 30 year record of the 2 bands Enhance Vegetation Index (EVI2), and analyzed the patterns and trends of land surface phenology across all tropical forests using the homogeneous phenology cluster approach. We chose EVI because of its superior performance over these dense forests, and we selected the homogeneous phenology cluster approach to abate the noise associated with single pixel approaches. This approach reasonably assumes that land surface seasonality is homogeneous over areas with similar climate, soil, elevation gradient, aspect, and land cover. Our goal was to establish the patterns and characteristic of the land surface phenology of these biomes and to analyze their spatio-temporal trends. Strong variability was observed across the forests of South America, Central Africa and South East Asia. The South American forest exhibited the faintest seasonal signal with the strongest response to droughts. These forests show a more distinct and ever more evident dry season response. The Tropical forest of central Africa shows a more evident seasonal signal and a trend where the season is breaking into a bimodal growth mode, with two distinct and separate growth periods. The Tropical forest of South East Asia shows a more fragmented seasonality that most likely is the result of human pressure and its impact on land cover. Although we have not looked at the underlying climatic factors, we hypothesize that the seasonality of these forests are mostly shaped by the climatic patterns which would suggest that these trends will become more evident as climate continues to change.

Landsat time series and lidar as predictors of live and dead basal area across five bark beetle-affected forests

Treesearch

Benjamin C. Bright; Andrew T. Hudak; Robert E. Kennedy; Arjan J. H. Meddens

2014-01-01

Bark beetle-caused tree mortality affects important forest ecosystem processes. Remote sensing methodologies that quantify live and dead basal area (BA) in bark beetle-affected forests can provide valuable information to forest managers and researchers. We compared the utility of light detection and ranging (lidar) and the Landsat-based detection of trends in...

3D plasmonic transducer based on gold nanoparticles produced by laser ablation on silica nanowires

NASA Astrophysics Data System (ADS)

Gontad, F.; Caricato, A. P.; Manera, M. G.; Colombelli, A.; Resta, V.; Taurino, A.; Cesaria, M.; Leo, C.; Convertino, A.; Klini, A.; Perrone, A.; Rella, R.; Martino, M.

2016-05-01

Silica two-dimensional substrates and nanowires (NWs) forests have been successfully decorated with Au nanoparticles (NPs) through laser ablation by using a pulsed ArF excimer laser, for sensor applications. A uniform coverage of both substrate surfaces with NPs has been achieved controlling the number of laser pulses. The annealing of the as-deposited particles resulted in a uniform well-defined distribution of spherical NPs with an increased average diameter up to 25 nm. The deposited samples on silica NWs forest present a very good plasmonic resonance which resulted to be very sensitive to the changes of the environment (ethanol/water solutions with increasing concentration of ethanol) allowing the detection of changes on the second decimal digit of the refractive index, demonstrating its potentiality for further biosensing functionalities.

Mortality trends and traits of hardwood advance regeneration following seasonal prescribed fires

Treesearch

Patrick Brose; David Van Lear

2003-01-01

Fire ecology studies in eastern hardwood forests generally use traditional, plot-based inventory methods and focus on sprouting stems to detect changes in vegetative composition and structure. Fire intensity often is not quantified or even subjectively classified and, if quantified, is not used in subsequent analysis. Consequently, reported responses of hardwood...

Monitoring crop and vegetation condition using the fused dense time-series landsat-like imagery

USDA-ARS?s Scientific Manuscript database

Since the launch of the first Landsat satellite in the early 1970s, Landsat has been widely used in many applications such as land cover and land use change monitoring, crop yield estimation, forest fire detection, and global ecosystem carbon cycle studies. Medium resolution sensors like Landsat hav...

Dendrochemical response to soil fertilization

Treesearch

David R. DeWalle; Jeffrey S. Tepp; Bryan R. Swistock; Pamela J. Edwards; William E. Sharpe; Mary Beth Adams; James N. Kochenderfer

2003-01-01

Use of chemical element content of tree rings to detect soil acid or base changes was tested at 13 sites of former forest fertilization trials in the eastern United States and Canada. Ammonium sulfate or nitrogen fertilization was the typical acidification treatment, while lime added with or without other fertilizer was the typical base treatment. Molar ratios of...

Forests of opportunities and mischief: disentangling the interactions between forests, parasites and immune responses.

PubMed

Renner, Swen C; Lüdtke, Bruntje; Kaiser, Sonja; Kienle, Julia; Schaefer, H Martin; Segelbacher, Gernot; Tschapka, Marco; Santiago-Alarcon, Diego

2016-08-01

Habitat characteristics determine the presence of individuals through resource availability, but at the same time, such features also influence the occurrence of parasites. We analyzed how birds respond to changes in interior forest structures, to forest management regimes, and to the risk of haemosporidian infections. We captured and took blood samples from blackcaps (Sylvia atricapilla) and chaffinches (Fringilla coelebs) in three different forest types (beech, mixed deciduous, spruce). We measured birds' body asymmetries, detected avian haemosporidians, and counted white blood cells as an immune measure of each individual per forest type. We used, to our knowledge for the first time, continuous forest structural parameters to quantify habitat structure, and found significant effects of habitat structure on parasite prevalence that previously have been undetected. We found three times higher prevalence for blackcaps compared with chaffinches. Parasite intensity varied significantly within host species depending on forest type, being lowest in beech forests for both host species. Structurally complex habitats with a high degree of entropy had a positive effect on the likelihood of acquiring an infection, but the effect on prevalence was negative for forest sections with a south facing aspect. For blackcaps, forest gaps also had a positive effect on prevalence, but canopy height had a negative one. Our results suggest that forest types and variations in forest structure influence the likelihood of acquiring an infection, which subsequently has an influence on host health status and body condition; however, responses to some environmental factors are host-specific. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

NASA Astrophysics Data System (ADS)

Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

2016-09-01

Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

Assessing socioeconomic impacts of climate change on U.S. forests, wood-product markets, and forest recreation

Treesearch

Lloyd C. Irland; Darius Adams; Ralph Alig; Carter J. Betz; Chi-Chung Chen; Mark Hutchins; Bruce A. McCarl; Ken Skog; Brent L. Sohngen

2001-01-01

In this paper we discuss the problems of projecting social and economic changes affecting forests and review recent efforts to assess the wood-market impacts of possible climate changes. To illustrate the range of conditions encountered in projecting socioeconomic change linked to forests, we consider two markedly different uses: forest products markets and forest...

Measuring forest structure along productivity gradients in the Canadian boreal with small-footprint Lidar.

PubMed

Bolton, Douglas K; Coops, Nicholas C; Wulder, Michael A

2013-08-01

The structure and productivity of boreal forests are key components of the global carbon cycle and impact the resources and habitats available for species. With this research, we characterized the relationship between measurements of forest structure and satellite-derived estimates of gross primary production (GPP) over the Canadian boreal. We acquired stand level indicators of canopy cover, canopy height, and structural complexity from nearly 25,000 km of small-footprint discrete return Light Detection and Ranging (Lidar) data and compared these attributes to GPP estimates derived from the MODerate resolution Imaging Spectroradiometer (MODIS). While limited in our capacity to control for stand age, we removed recently disturbed and managed forests using information on fire history, roads, and anthropogenic change. We found that MODIS GPP was strongly linked to Lidar-derived canopy cover (r = 0.74, p < 0.01), however was only weakly related to Lidar-derived canopy height and structural complexity as these attributes are largely a function of stand age. A relationship was apparent between MODIS GPP and the maximum sampled heights derived from Lidar as growth rates and resource availability likely limit tree height in the prolonged absence of disturbance. The most structurally complex stands, as measured by the coefficient of variation of Lidar return heights, occurred where MODIS GPP was highest as productive boreal stands are expected to contain a wider range of tree heights and transition to uneven-aged structures faster than less productive stands. While MODIS GPP related near-linearly to Lidar-derived canopy cover, the weaker relationships to Lidar-derived canopy height and structural complexity highlight the importance of stand age in determining the structure of boreal forests. We conclude that an improved quantification of how both productivity and disturbance shape stand structure is needed to better understand the current state of boreal forests in Canada and how these forests are changing in response to changing climate and disturbance regimes.

Analyzing the carbon dynamics in north western Portugal: calibration and application of Forest-BGC

NASA Astrophysics Data System (ADS)

Rodrigues, M. A.; Lopes, D. M.; Leite, S. M.; Tabuada, V. M.

2010-04-01

Net primary production (NPP) is an important variable that allows monitoring forestry ecosystems fixation of atmospheric Carbon. The importance of monitoring the sequestred carbon is related to the binding commitments established by the Kyoto Protocol. There are ecophysiologic models, as Forest-BGC that allow for estimating NPP. In a first stage, this study aims to analyze the climate evolution at the Vila Real administrative district during the last decades. The historical information will be observed in order to detect the past tendencies of evolution. Past will help us to predict future. In a next stage these tendencies will be used to infer the impact of these change scenarios on the net primary production of the forest ecosystems from this study area. For a parameterization and validation of the FOREST-BGC, this study was carried on based on 500 m2 sampling plots from the National Forest Inventory 2006 and are located in several County Halls of the district of Vila Real (Montalegre, Chaves, Valpaços, Boticas, Vila Pouca de Aguiar, Murça, Mondim de Basto, Alijó, Sabrosa and Vila Real). In order to quantify Biomass dinamics, we have selected 45 sampling plots: 19 from Pinus pinaster stands, 17 from Quercus pyrenaica and 10 from mixed of Quercus pyrenaica with Pinus pinaster. Adaptation strategies for climate change impacts can be proposed based on these research results.

Effects of Land Use Change and Seasonality of Precipitation on Soil Nitrogen in a Dry Tropical Forest Area in the Western Llanos of Venezuela

PubMed Central

González-Pedraza, Ana Francisca; Dezzeo, Nelda

2014-01-01

We evaluated changes of different soil nitrogen forms (total N, available ammonium and nitrate, total N in microbial biomass, and soil N mineralization) after conversion of semideciduous dry tropical forest in 5- and 18-year-old pastures (YP and OP, resp.) in the western Llanos of Venezuela. This evaluation was made at early rainy season, at end rainy season, and during dry season. With few exceptions, no significant differences were detected in the total N in the three study sites. Compared to forest soils, YP showed ammonium losses from 4.2 to 62.9% and nitrate losses from 20.0 to 77.8%, depending on the season of the year. In OP, the ammonium content increased from 50.0 to 69.0% at the end of the rainy season and decreased during the dry season between 25.0 and 55.5%, whereas the nitrate content increased significantly at early rainy season. The net mineralization and the potentially mineralizable N were significantly higher (P < 0.05) in OP than in forest and YP, which would indicate a better quality of the substrate in OP for mineralization. The mineralization rate constant was higher in YP than in forest and OP. This could be associated with a reduced capacity of these soils to preserve the available nitrogen. PMID:25610907

Effects of land use change and seasonality of precipitation on soil nitrogen in a dry tropical forest area in the Western Llanos of Venezuela.

PubMed

González-Pedraza, Ana Francisca; Dezzeo, Nelda

2014-01-01

We evaluated changes of different soil nitrogen forms (total N, available ammonium and nitrate, total N in microbial biomass, and soil N mineralization) after conversion of semideciduous dry tropical forest in 5- and 18-year-old pastures (YP and OP, resp.) in the western Llanos of Venezuela. This evaluation was made at early rainy season, at end rainy season, and during dry season. With few exceptions, no significant differences were detected in the total N in the three study sites. Compared to forest soils, YP showed ammonium losses from 4.2 to 62.9% and nitrate losses from 20.0 to 77.8%, depending on the season of the year. In OP, the ammonium content increased from 50.0 to 69.0% at the end of the rainy season and decreased during the dry season between 25.0 and 55.5%, whereas the nitrate content increased significantly at early rainy season. The net mineralization and the potentially mineralizable N were significantly higher (P < 0.05) in OP than in forest and YP, which would indicate a better quality of the substrate in OP for mineralization. The mineralization rate constant was higher in YP than in forest and OP. This could be associated with a reduced capacity of these soils to preserve the available nitrogen.

Application of stable isotope measurements and microbiological analysis for detecting methanogenic activity in a temperate forest wetland

NASA Astrophysics Data System (ADS)

Itoh, M.; Katsuyama, C.; Kondo, N.; Ohte, N.; Kato, K.

2009-12-01

Generally, forest soils act as a sink for methane (CH4). However, wetlands in riparian zones are recently reported to be “hot spots” of CH4 emissions, especially in forests under a humid climate. To understand how environmental conditions (i.e. hydrological and/or geomorphic condition) control on CH4 production, we investigated both methanogenic pathways (CO2/H2 reduction and acetate fermentation) and metahanogenic microbial communities in a wetland in a temperate forest catchment, central Japan. We used stable carbon isotopic analysis for detecting change in methanogenic pathways, and applied microbiological analysis for understanding the structure of methanogenic community. CH4 emission rates in wetland were strongly dependent on soil temperatures, and were highest in summer and lowest in winter. δ13CO2 increased with CH4 production in every summer, suggesting preferential use of 12CO2 as substrate for CO2/H2 reduction methanogenesis during high CH4 production period. δ13CH4 also increased in summer with δ13CO2. δ13CH4 changed more wildly than δ13CO2 did in summer with normal precipitation when CH4 production was strongly activated under high temperature and high groundwater table condition. This indicates increase in acetoclastic methanogenesis under hot and wet condition, considering that acetclastic methnogens produce heavier CH4 than that from CO2/H2 reducing pathway. Methanogen community composition estimated by cloning and sequence analyses implied that both acetoclastic and CO2/H2 reducing methanogens prevailed in wetland soil sampled in summer. This was consistent with the results of isotope measuremaents. Our results contribute to understand fully how the CH4 production changes with environmental conditions, with considering the activities of both main methanogenic pathway (from CO2 and acetate).

Spatio-temporal change in forest cover and carbon storage considering actual and potential forest cover in South Korea.

PubMed

Nam, Kijun; Lee, Woo-Kyun; Kim, Moonil; Kwak, Doo-Ahn; Byun, Woo-Hyuk; Yu, Hangnan; Kwak, Hanbin; Kwon, Taesung; Sung, Joohan; Chung, Dong-Jun; Lee, Seung-Ho

2015-07-01

This study analyzes change in carbon storage by applying forest growth models and final cutting age to actual and potential forest cover for six major tree species in South Korea. Using National Forest Inventory data, the growth models were developed to estimate mean diameter at breast height, tree height, and number of trees for Pinus densiflora, Pinus koraiensis, Pinus rigida, Larix kaempferi, Castanea crenata and Quercus spp. stands. We assumed that actual forest cover in a forest type map will change into potential forest covers according to the Hydrological and Thermal Analogy Groups model. When actual forest cover reaches the final cutting age, forest volume and carbon storage are estimated by changed forest cover and its growth model. Forest volume between 2010 and 2110 would increase from 126.73 to 157.33 m(3) hm(-2). Our results also show that forest cover, volume, and carbon storage could abruptly change by 2060. This is attributed to the fact that most forests are presumed to reach final cutting age. To avoid such dramatic change, a regeneration and yield control scheme should be prepared and implemented in a way that ensures balance in forest practice and yield.

Detection of degenerative change in lateral projection cervical spine x-ray images

NASA Astrophysics Data System (ADS)

Jebri, Beyrem; Phillips, Michael; Knapp, Karen; Appelboam, Andy; Reuben, Adam; Slabaugh, Greg

2015-03-01

Degenerative changes to the cervical spine can be accompanied by neck pain, which can result from narrowing of the intervertebral disc space and growth of osteophytes. In a lateral x-ray image of the cervical spine, degenerative changes are characterized by vertebral bodies that have indistinct boundaries and limited spacing between vertebrae. In this paper, we present a machine learning approach to detect and localize degenerative changes in lateral x-ray images of the cervical spine. Starting from a user-supplied set of points in the center of each vertebral body, we fit a central spline, from which a region of interest is extracted and image features are computed. A Random Forest classifier labels regions as degenerative change or normal. Leave-one-out cross-validation studies performed on a dataset of 103 patients demonstrates performance of above 95% accuracy.

Successional changes in functional composition contrast for dry and wet tropical forest.

PubMed

Lohbeck, Madelon; Poorter, Lourens; Lebrija-Trejos, Edwin; Martínez-Ramos, Miguel; Meave, Jorge A; Paz, Horacio; Pérez-García, Eduardo A; Romero-Pérez, I Eunice; Tauro, Alejandra; Bongers, Frans

2013-06-01

We tested whether and how functional composition changes with succession in dry deciduous and wet evergreen forests of Mexico. We hypothesized that compositional changes during succession in dry forest were mainly determined by increasing water availability leading to community functional changes from conservative to acquisitive strategies, and in wet forest by decreasing light availability leading to changes from acquisitive to conservative strategies. Research was carried out in 15 dry secondary forest plots (5-63 years after abandonment) and 17 wet secondary forest plots (< 1-25 years after abandonment). Community-level functional traits were represented by community-weighted means based on 11 functional traits measured on 132 species. Successional changes in functional composition are more marked in dry forest than in wet forest and largely characterized by different traits. During dry forest succession, conservative traits related to drought tolerance and drought avoidance decreased, as predicted. Unexpectedly acquisitive leaf traits also decreased, whereas seed size and dependence on biotic dispersal increased. In wet forest succession, functional composition changed from acquisitive to conservative leaf traits, suggesting light availability as the main driver of changes. Distinct suites of traits shape functional composition changes in dry and wet forest succession, responding to different environmental filters.

Microbial Mechanisms Mediating Increased Soil C Storage under Elevated Atmospheric N Deposition

PubMed Central

Freedman, Zachary; Zak, Donald R.; Xue, Kai; He, Zhili; Zhou, Jizhong

2013-01-01

Future rates of anthropogenic N deposition can slow the cycling and enhance the storage of C in forest ecosystems. In a northern hardwood forest ecosystem, experimental N deposition has decreased the extent of forest floor decay, leading to increased soil C storage. To better understand the microbial mechanisms mediating this response, we examined the functional genes derived from communities of actinobacteria and fungi present in the forest floor using GeoChip 4.0, a high-throughput functional-gene microarray. The compositions of functional genes derived from actinobacterial and fungal communities was significantly altered by experimental nitrogen deposition, with more heterogeneity detected in both groups. Experimental N deposition significantly decreased the richness and diversity of genes involved in the depolymerization of starch (∼12%), hemicellulose (∼16%), cellulose (∼16%), chitin (∼15%), and lignin (∼16%). The decrease in richness occurred across all taxonomic groupings detected by the microarray. The compositions of genes encoding oxidoreductases, which plausibly mediate lignin decay, were responsible for much of the observed dissimilarity between actinobacterial communities under ambient and experimental N deposition. This shift in composition and decrease in richness and diversity of genes encoding enzymes that mediate the decay process has occurred in parallel with a reduction in the extent of decay and accumulation of soil organic matter. Our observations indicate that compositional changes in actinobacterial and fungal communities elicited by experimental N deposition have functional implications for the cycling and storage of carbon in forest ecosystems. PMID:23220961

QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee Spangler; Lee A. Vierling; Eva K. Stand

2012-04-01

Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 acrossmore » {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density between the 2003 and 2009 did not affect the biomass estimates. Overall, LiDAR data coupled with field reference data offer a powerful method for calculating pools and changes in aboveground carbon in forested systems. The results of our study suggest that multitemporal LiDAR-based approaches are likely to be useful for high quality estimates of aboveground carbon change in conifer forest systems.« less

The interplay between climate change, forests, and disturbances

Treesearch

Virginia H. Dale; Linda A. Joyce; Steve McNulty; Ronald P. Neilson

2000-01-01

Climate change affects forests both directly and indirectly through disturbances. Disturbances are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. When disturbances exceed their natural range of variation, the change in forest structure and function may be extreme. Each disturbance affects forests differently....

Individual tree detection in intact forest and degraded forest areas in the north region of Mato Grosso State, Brazilian Amazon

NASA Astrophysics Data System (ADS)

Santos, E. G.; Jorge, A.; Shimabukuro, Y. E.; Gasparini, K.

2017-12-01

The State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.

Interoperability of Landsat and DMC imagery for continuous detection and quantification of nonindustrial forest harvests in the Western Upper Peninsula of Michigan, USA

NASA Astrophysics Data System (ADS)

Mayer, A. L.; Tortini, R.; Maianti, P.

2013-12-01

The relationship between human land use and land cover change is critical to sustainable forest management. Land use decisions by small land managers aggregate into substantial land cover changes at landscape and regional scales. Land ownership across large portions of the Upper Great Lakes region is in considerable flux, as large timber industry tracts are split into many smaller non-industrial ownerships, and new owners prioritize amenity and non-timber forest values. Nonindustrial Private Forest (NIPF) owners also transfer their properties to younger generations or other NIPF owners with different management approaches and goals. Survey data on intended harvests and sales are available through the National Woodland Owner Survey (NWOS), run by the USDA Forest Service. However, the disparity between NIPF owner-stated plans to harvest, and what actually occurs, can be substantially different, especially if annual fluctuations in timber prices or general economic fluctuations cause NIPF owners to deviate from their stated management and ownership intentions. This reduces the NWOS' utility. Remote sensing data have considerable value for identifying small scale harvests and, paired with ownership data at the parcel scale, can measure NIPF harvest rates as related to ownership change at a regional scale. Here we focus on the Western Upper Peninsula of Michigan (WUP) and the most recent decade to develop our methodology, using primarily Landsat images from 2003-2013. However, Landsat data series are characterized by gaps in coverage over long temporal and large spatial scales, and so a methodology to combine multiple remote sensing data sources is necessary for regional-scale land use/land cover change research. We filled these gaps by integrating the available Landsat time series with DMC imagery. We then combined these data with GIS overlays of the parcels and stand-level data on removed basal area (BA) during known harvesting events to develop a classification of harvest intensity for the WUP. Images taken during peak growing season were preferred to calculate NDVI and ΔNDVI, and in general for enhancing possible spectral changes. We classified the harvests as clear cut, selective harvesting or thinning using an object-based image analysis. In particular, we defined a clear cut a harvesting event in which ~90-100% BA is removed, commercial harvesting if ~50-80% BA is removed and thinning if ~20-40% BA removal. This work demonstrates that DMC images can effectively fill the Landsat data gap for the detection and quantification of harvesting events. Preliminary results show that the method is capable of identifying harvests down to ~20% BA removal. These results can then be used to monitor the accuracy of the NWOS, and to develop a probability estimate of harvest given either ownership change or changes in market conditions.

Recent drought-induced mortality of aspen forests along a water-balance tipping point for ecosystems in western Canada

NASA Astrophysics Data System (ADS)

Hogg, E.

2009-05-01

In western Canada, the boundary between boreal forest and prairie grasslands marks a dramatic change in nearly all aspects of ecosystem functioning. These include a steep spatial gradient in hydrological characteristics of the landscape (lake level variability, water runoff and stream flow patterns) that coincides with the southern range limit of peatlands and several species of boreal conifers. Previous studies indicate that the forest-grassland boundary in this region represents a critical "tipping point" (Lenton et al. 2008) where long-term water input by precipitation is barely sufficient to satisfy the water use demands of productive, closed-canopy forests. This concept is consistent with the observed, regional gradient in the character of forests dominated by aspen (Populus tremuloides), the most abundant and widespread deciduous tree in North America. Aspen-dominated forests are productive and continuous in the boreal zone, but are stunted and patchy in the boreal-grassland transition zone, often referred to as the aspen parkland. Based on the "tipping point" concept, there are concerns that aspen forests in this region are especially sensitive to the projected trend toward warmer and drier conditions under human-induced climate change. In response to these concerns, a large-scale study was established across west-central Canada in 2000, entitled "Climate Impacts on Productivity and Health of Aspen" (CIPHA). The study has hierarchical sampling design that is aimed at "scaling up" forest-climate responses from individual trees to the region. During 2001-2002, the region was affected by an exceptionally severe drought that subsequently led to massive dieback and mortality of aspen forests within the boreal-grassland transition zone. Drought severity and extent was quantified using a simple climate moisture index (CMI), and drought impacts were quantified using tree-ring analysis, in combination with plot-based and remotely-sensed measures. Results showed that stand-level productivity, dieback and mortality were governed primarily by moisture variation. Furthermore, during and following this drought there was increasing damage by wood-boring insects and elevated, regional-scale mortality of aspen over at least 6 years (2002-2008). Although it is premature to attribute these impacts to anthropogenic climate change, they provide an excellent analog for what may be expected in future, even under a modest trend toward drying over the next few decades. Furthermore, the recent aspen mortality in western Canada shares many features common to other recent episodes of drought-induced forest mortality that have been documented on all of the earth's forested continents. This suggests the need for an integrated, global research and monitoring system that would enable early detection and attribution of large-scale ecosystem changes, especially in climatically-sensitive regions along forest-grassland boundaries around the world.

Atmospheric deposition to forests in the eastern USA

USGS Publications Warehouse

Risch, Martin R.; DeWild, John F.; Gay, David A.; Zhang, Leiming; Boyer, Elizabeth W.; Krabbenhoft, David P.

2017-01-01

Atmospheric mercury (Hg) deposition to forests is important because half of the land cover in the eastern USA is forest. Mercury was measured in autumn litterfall and weekly precipitation samples at a total of 27 National Atmospheric Deposition Program (NADP) monitoring sites in deciduous and mixed deciduous-coniferous forests in 16 states in the eastern USA during 2007–2014. These simultaneous, uniform, repeated, annual measurements of forest Hg include the broadest area and longest time frame to date. The autumn litterfall-Hg concentrations and litterfall mass at the study sites each year were combined with annual precipitation-Hg data. Rates of litterfall-Hg deposition were higher than or equal to precipitation-Hg deposition rates in 70% of the annual data, which indicates a substantial contribution from litterfall to total atmospheric-Hg deposition. Annual litterfall-Hg deposition in this study had a median of 11.7 μg per square meter per year (μg/m2/yr) and ranged from 2.2 to 23.4 μg/m2/yr. It closely matched modeled dry-Hg deposition, based on land cover at selected NADP Hg-monitoring sites. Mean annual atmospheric-Hg deposition at forest study sites exhibited a spatial pattern partly explained by statistical differences among five forest-cover types and related to the mapped density of Hg emissions. Forest canopies apparently recorded changes in atmospheric-Hg concentrations over time because litterfall-Hg concentrations decreased year to year and litterfall-Hg concentrations were significantly higher in 2007–2009 than in 2012–2014. These findings reinforce reported decreases in Hg emissions and atmospheric elemental-Hg concentrations during this same time period. Methylmercury (MeHg) was detected in all litterfall samples at all sites, compared with MeHg detections in less than half the precipitation samples at selected sites during the study. These results indicate MeHg in litterfall is a pathway into the terrestrial food web where it can accumulate in the prey of songbirds, bats, and raptors.

Atmospheric mercury deposition to forests in the eastern USA.

PubMed

Risch, Martin R; DeWild, John F; Gay, David A; Zhang, Leiming; Boyer, Elizabeth W; Krabbenhoft, David P

2017-09-01

Atmospheric mercury (Hg) deposition to forests is important because half of the land cover in the eastern USA is forest. Mercury was measured in autumn litterfall and weekly precipitation samples at a total of 27 National Atmospheric Deposition Program (NADP) monitoring sites in deciduous and mixed deciduous-coniferous forests in 16 states in the eastern USA during 2007-2014. These simultaneous, uniform, repeated, annual measurements of forest Hg include the broadest area and longest time frame to date. The autumn litterfall-Hg concentrations and litterfall mass at the study sites each year were combined with annual precipitation-Hg data. Rates of litterfall-Hg deposition were higher than or equal to precipitation-Hg deposition rates in 70% of the annual data, which indicates a substantial contribution from litterfall to total atmospheric-Hg deposition. Annual litterfall-Hg deposition in this study had a median of 11.7 μg per square meter per year (μg/m 2 /yr) and ranged from 2.2 to 23.4 μg/m 2 /yr. It closely matched modeled dry-Hg deposition, based on land cover at selected NADP Hg-monitoring sites. Mean annual atmospheric-Hg deposition at forest study sites exhibited a spatial pattern partly explained by statistical differences among five forest-cover types and related to the mapped density of Hg emissions. Forest canopies apparently recorded changes in atmospheric-Hg concentrations over time because litterfall-Hg concentrations decreased year to year and litterfall-Hg concentrations were significantly higher in 2007-2009 than in 2012-2014. These findings reinforce reported decreases in Hg emissions and atmospheric elemental-Hg concentrations during this same time period. Methylmercury (MeHg) was detected in all litterfall samples at all sites, compared with MeHg detections in less than half the precipitation samples at selected sites during the study. These results indicate MeHg in litterfall is a pathway into the terrestrial food web where it can accumulate in the prey of songbirds, bats, and raptors. Published by Elsevier Ltd.

Forest Health Monitoring and Forest Inventory Analysis programs monitor climate change effects in forest ecosystems

Treesearch

Kenneth W. Stolte

2001-01-01

The Forest Health Monitoring (FHM) and Forest Inventory and Analyses (FIA) programs are integrated bilogical monitoring systems that use nationally standardized methods to evaluate and report on the health and sustainability of forest ecosystems in the United States. Many of the anticipated changes in forest ecosystems from climate change were also issues addressed in...

Carbon changes in conterminous US forests associated with growth and major disturbances: 1992-2001

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2011-01-01

We estimated forest area and carbon changes in the conterminous United States using a remote sensing based land cover change map, forest fire data from the Monitoring Trends in Burn Severity program, and forest growth and harvest data from the USDA Forest Service, Forest Inventory and Analysis Program. Natural and human-associated disturbances reduced the forest...

K-12 Phenology Lessons for the Phenocam Project

NASA Astrophysics Data System (ADS)

Bennett, K. F.

2013-12-01

Phenology is defined as periodic [or annual] life cycles of plants and animals driven by seasonal environmental changes. Climate change impinges a strong effect on phenology, potentially altering the structure and functioning of ecosystems. In the fall of 2011, the Ashburnham-Westminster Regional School District became the first of five schools to join Harvard University's Phenocam Network with the installation of a webcam to monitor phenology (or 'phenocam') at Overlook Middle School in Ashburnham, Massachusetts. Our school district is now part of a network of near-surface remote sensing phenocams that capture and send images of forest, shrub, and grassland vegetation cover at more than 130 diverse sites in North America. Our phenocam provides a digital image every half hour of the mixed forest canopy north from the school, enabling the detection of changes in canopy development, quantified as canopy 'greenness'. As a part of the Phenocam project, students at the K-12 level have expanded the scope of phenological monitoring protocol that is part of the Harvard Forest Schoolyard Ecology Program, Buds, Leaves, and Global Warming. In this protocol, students work with ecologists at Harvard Forest to monitor buds and leaves on schoolyard trees to determine the length of the growing season, giving them the opportunity to be a part of real and important research concerning the critical environmental issue of climate change. Students involved in the Buds, Leaves, and Global Warming study have the opportunity to compare their ground data on budburst, color change, and leaf drop to the phenocam images, as well as to similar forested sites in locations throughout the United States. Lessons have been developed for comparing student data to phenocam images, canopy greenness time series graphs extracted from the images, and satellite data. Lessons addressing map scale and the Urban Heat Island effect will also be available for teachers. This project will greatly enhance the district's Science, Technology, Engineering and Math, (STEM) initiative and further our goal of educating ecologically literate citizens.

When and where to move: Dynamic occupancy models explain the range dynamics of a food nomadic bird under climate and land cover change.

PubMed

Kalle, Riddhika; Ramesh, Tharmalingam; Downs, Colleen T

2018-01-01

Globally, long-term research is critical to monitor the responses of tropical species to climate and land cover change at the range scale. Citizen science surveys can reveal the long-term persistence of poorly known nomadic tropical birds occupying fragmented forest patches. We applied dynamic occupancy models to 13 years (2002-2014) of citizen science-driven presence/absence data on Cape parrot (Poicephalus robustus), a food nomadic bird endemic to South Africa. We modeled its underlying range dynamics as a function of resource distribution, and change in climate and land cover through the estimation of colonization and extinction patterns. The range occupancy of Cape parrot changed little over time (ψ = 0.75-0.83) because extinction was balanced by recolonization. Yet, there was considerable regional variability in occupancy and detection probability increased over the years. Colonizations increased with warmer temperature and area of orchards, thus explaining their range shifts southeastwards in recent years. Although colonizations were higher in the presence of nests and yellowwood trees (Afrocarpus and Podocarpus spp.), the extinctions in small forest patches (≤227 ha) and during low precipitation (≤41 mm) are attributed to resource constraints and unsuitable climatic conditions. Loss of indigenous forest cover and artificial lake/water bodies increased extinction probabilities of Cape parrot. The land use matrix (fruit farms, gardens, and cultivations) surrounding forest patches provides alternative food sources, thereby facilitating spatiotemporal colonization and extinction in the human-modified matrix. Our models show that Cape parrots are vulnerable to extreme climatic conditions such as drought which is predicted to increase under climate change. Therefore, management of optimum sized high-quality forest patches is essential for long-term survival of Cape parrot populations. Our novel application of dynamic occupancy models to long-term citizen science monitoring data unfolds the complex relationships between the environmental dynamics and range fluctuations of this food nomadic species. © 2017 John Wiley & Sons Ltd.

Implications of land-use change on forest carbon stocks in the eastern United States

NASA Astrophysics Data System (ADS)

Puhlick, Joshua; Woodall, Christopher; Weiskittel, Aaron

2017-02-01

Given the substantial role that forests play in removing CO2 from the atmosphere, there has been a growing need to evaluate the carbon (C) implications of various forest management and land-use decisions. Although assessment of land-use change is central to national-level greenhouse gas monitoring guidelines, it is rarely incorporated into forest stand-level evaluations of C dynamics and trajectories. To better inform the assessment of forest stand C dynamics in the context of potential land-use change, we used a region-wide repeated forest inventory (n = 71 444 plots) across the eastern United States to assess forest land-use conversion and associated changes in forest C stocks. Specifically, the probability of forest area reduction between 2002-2006 and 2007-2012 on these plots was related to key driving factors such as proportion of the landscape in forest land use, distance to roads, and initial forest C. Additional factors influencing the actual reduction in forest area were then used to assess the risk of forest land-use conversion to agriculture, settlement, and water. Plots in forests along the Great Plains had the highest periodic (approximately 5 years) probability of land-use change (0.160 ± 0.075; mean ± SD) with forest conversion to agricultural uses accounting for 70.5% of the observed land-use change. Aboveground forest C stock change for plots with a reduction in forest area was -4.2 ± 17.7 Mg ha-1 (mean ± SD). The finding that poorly stocked stands and/or those with small diameter trees had the highest probability of conversion to non-forest land uses suggests that forest management strategies can maintain the US terrestrial C sink not only in terms of increased net forest growth but also retention of forest area to avoid conversion. This study highlights the importance of considering land-use change in planning and policy decisions that seek to maintain or enhance regional C sinks.

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System

PubMed Central

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications. PMID:27031694

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

Integrated evaluation of the vulnerability to thermokarst disturbance and its implications for the regional carbon balance in boreal Alaska

NASA Astrophysics Data System (ADS)

Helene, G.; Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Bolton, W. R.; Romanovsky, V. E.

2017-12-01

Our capacity to project future ecosystem trajectories in northern permafrost regions depends on our ability to characterize complex interactions between climatic and ecological processes at play in the soil, the vegetation, and the atmosphere. We present a study that uses remote sensing analyses, field observations, and data synthesis to inform models for the prediction of ecosystem responses to climate change in the boreal zone of Alaska. Recent warming, altered precipitation and fire regimes are driving permafrost degradation, threatening to mobilize vast reservoirs of ancient carbon previously protected from decomposition. Although large scale, progressive, top-down permafrost thaw have been well studied and represented in high-latitude ecosystem models, the consequences of abrupt and local thermokarst disturbances (TK) are less well understood. To fill this gap, we conducted a detection analysis characterizing 60 years of land cover change in the Tanana Flats, a wetland complex subjected to TK disturbance in Interior Alaska, using aerial and satellite images. We observed a nonlinear loss of permafrost plateau forest associated with TK and driven by precipitation and forest fragmentation. The results of this analysis were integrated into the Alaska Thermokarst Model (ATM), a state-and-transition model that simulates land cover change associated with TK disturbance. Thermokarst-related land cover change was simulated from 2000 to 2100 across the Tanana Flats. By 2100, the model predicts a mean decrease of 7.4% (sd 1.8%) in permafrost plateau forests associated with an increase in TK fens and bogs. Transitions from permafrost plateau forests to TK wetlands are accompanied with changes in physical and biogeochemical processes affecting ecosystem carbon balance. We evaluated the consequences of TK disturbances on the regional carbon balance by coupling outputs from the ATM and from a process-based biogeochemical model. We used long-term field observations of vegetation and soil physical and biogeochemical attributes to develop new parameterizations for TK wetlands and permafrost plateau forest land cover types. Preliminary simulations from 2000 to 2100 estimate that the conversion of permafrost plateau forest to young TK wetlands would result in a 7.5% (sd 3.5%) decrease in Net Ecosystem Exchange.

Temporal change in fragmentation of continental US forests

Treesearch

James D. Wickham; Kurt H. Riitters; Timothy G. Wade; Collin Homer

2008-01-01

Changes in forest ecosystem function and condition arise from changes in forest fragmentation. Previous studies estimated forest fragmentation for the continental United States (US). In this study, new temporal land-cover data from the National Land Cover Database (NLCD) were used to estimate changes in forest fragmentation at multiple scales for the continental US....

Monitoring forests from space: quantifying forest change by using satellite data.

Treesearch

Jonathan Thompson

2006-01-01

Change is the only constant in forest ecosystems. Quantifying regional-scale forest change is increasingly done with remote sensing, which relies on data sent from digital camera-like sensors mounted to Earth-orbiting satellites. Through remote sensing, changes in forests can be studied comprehensively and uniformly across time and space.

Effects of wastewater on forested wetlands

USGS Publications Warehouse

Doyle, Thomas W.

2002-01-01

Cycling nutrient-enriched wastewater from holding ponds through natural, forested wetlands is a practice that municipal waste treatment managers are considering as a viable option for disposing of wastewater. In this wastewater cycling process, sewer effluent that has been circulated through aerated ponds is discharged into neighboring wetland systems. To understand how wastewater cycling affects forest and species productivity, researchers at the USGS National Wetlands Research Center conducted dendroecological investigations in a swamp system and in a bog system that have been exposed to wastewater effluent for many decades. Dendroecology involves the study of forest changes over time as interpreted from tree rings. Tree-ring chronologies describe the pattern and history of growth suppression and release that can be associated with aging and disturbances such as hurricanes, floods, and fires. But because of limited monitoring, little is known about the potential for long-term effects on forested wetlands as a result of wastewater flooding. USGS researchers used tree rings to detect the effect of wastewater cycling on tree growth. Scientists expected to find that tree-ring width would be increased as a result of added nutrients.

Urban Change Detection of Pingtan City based on Bi-temporal Remote Sensing Images

NASA Astrophysics Data System (ADS)

Degang, JIANG; Jinyan, XU; Yikang, GAO

2017-02-01

In this paper, a pair of SPOT 5-6 images with the resolution of 0.5m is selected. An object-oriented classification method is used to the two images and five classes of ground features were identified as man-made objects, farmland, forest, waterbody and unutilized land. An auxiliary ASTER GDEM was used to improve the classification accuracy. And the change detection based on the classification results was performed. Accuracy assessment was carried out finally. Consequently, satisfactory results were obtained. The results show that great changes of the Pingtan city have been detected as the expansion of the city area and the intensity increase of man-made buildings, roads and other infrastructures with the establishment of Pingtan comprehensive experimental zone. Wide range of open sea area along the island coast zones has been reclaimed for port and CBDs construction.

Habitat Effects on the Breeding Performance of Three Forest-Dwelling Hawks.

PubMed

Björklund, Heidi; Valkama, Jari; Tomppo, Erkki; Laaksonen, Toni

2015-01-01

Habitat loss causes population declines, but the mechanisms are rarely known. In the European Boreal Zone, loss of old forest due to intensive forestry is suspected to cause declines in forest-dwelling raptors by reducing their breeding performance. We studied the boreal breeding habitat and habitat-associated breeding performance of the northern goshawk (Accipiter gentilis), common buzzard (Buteo buteo) and European honey buzzard (Pernis apivorus). We combined long-term Finnish bird-of-prey data with multi-source national forest inventory data at various distances (100-4000 m) around the hawk nests. We found that breeding success of the goshawk was best explained by the habitat within a 2000-m radius around the nests; breeding was more successful with increasing proportions of old spruce forest and water, and decreasing proportions of young thinning forest. None of the habitat variables affected significantly the breeding success of the common buzzard or the honey buzzard, or the brood size of any of the species. The amount of old spruce forest decreased both around goshawk and common buzzard nests and throughout southern Finland in 1992-2010. In contrast, the area of young forest increased in southern Finland but not around hawk nests. We emphasize the importance of studying habitats at several spatial and temporal scales to determine the relevant species-specific scale and to detect environmental changes. Further effort is needed to reconcile the socioeconomic and ecological functions of forests and habitat requirements of old forest specialists.

A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?

PubMed

Pannatier, Elisabeth Graf; Thimonier, Anne; Schmitt, Maria; Walthert, Lorenz; Waldner, Peter

2011-03-01

Trends in atmospheric acid deposition and in soil solution acidity from 1995 or later until 2007 were investigated at several forest sites throughout Switzerland to assess the effects of air pollution abatements on deposition and the response of the soil solution chemistry. Deposition of the major elements was estimated from throughfall and bulk deposition measurements at nine sites of the Swiss Long-Term Forest Ecosystem Research network (LWF) since 1995 or later. Soil solution was measured at seven plots at four soil depths since 1998 or later. Trends in the molar ratio of base cations to aluminum (BC/Al) in soil solutions and in concentrations and fluxes of inorganic N (NO(3)-N + NH(4)-N), sulfate (SO(4)-S), and base cations (BC) were used to detect changes in soil solution chemistry. Acid deposition significantly decreased at three out of the nine study sites due to a decrease in total N deposition. Total SO(4)-S deposition decreased at the nine sites, but due to the relatively low amount of SO(4)-S load compared to N deposition, it did not contribute to decrease acid deposition significantly. No trend in total BC deposition was detected. In the soil solution, no trend in concentrations and fluxes of BC, SO(4)-S, and inorganic N were found at most soil depths at five out of the seven sites. This suggests that the soil solution reacted very little to the changes in atmospheric deposition. A stronger reduction in base cations compared to aluminum was detected at two sites, which might indicate that acidification of the soil solution was proceeding faster at these sites.

Prototype of microbolometer thermal infrared camera for forest fire detection from space

NASA Astrophysics Data System (ADS)

Guerin, Francois; Dantes, Didier; Bouzou, Nathalie; Chorier, Philippe; Bouchardy, Anne-Marie; Rollin, Joël.

2017-11-01

The contribution of the thermal infrared (TIR) camera to the Earth observation FUEGO mission is to participate; to discriminate the clouds and smoke; to detect the false alarms of forest fires; to monitor the forest fires. Consequently, the camera needs a large dynamic range of detectable radiances. A small volume, low mass and power are required by the small FUEGO payload. These specifications can be attractive for other similar missions.

Community structure and diversity of tropical forest mammals: data from a global camera trap network.

PubMed

Ahumada, Jorge A; Silva, Carlos E F; Gajapersad, Krisna; Hallam, Chris; Hurtado, Johanna; Martin, Emanuel; McWilliam, Alex; Mugerwa, Badru; O'Brien, Tim; Rovero, Francesco; Sheil, Douglas; Spironello, Wilson R; Winarni, Nurul; Andelman, Sandy J

2011-09-27

Terrestrial mammals are a key component of tropical forest communities as indicators of ecosystem health and providers of important ecosystem services. However, there is little quantitative information about how they change with local, regional and global threats. In this paper, the first standardized pantropical forest terrestrial mammal community study, we examine several aspects of terrestrial mammal species and community diversity (species richness, species diversity, evenness, dominance, functional diversity and community structure) at seven sites around the globe using a single standardized camera trapping methodology approach. The sites-located in Uganda, Tanzania, Indonesia, Lao PDR, Suriname, Brazil and Costa Rica-are surrounded by different landscape configurations, from continuous forests to highly fragmented forests. We obtained more than 51 000 images and detected 105 species of mammals with a total sampling effort of 12 687 camera trap days. We find that mammal communities from highly fragmented sites have lower species richness, species diversity, functional diversity and higher dominance when compared with sites in partially fragmented and continuous forest. We emphasize the importance of standardized camera trapping approaches for obtaining baselines for monitoring forest mammal communities so as to adequately understand the effect of global, regional and local threats and appropriately inform conservation actions.

Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon.

PubMed

Souza-Filho, Pedro Walfir M; de Souza, Everaldo B; Silva Júnior, Renato O; Nascimento, Wilson R; Versiani de Mendonça, Breno R; Guimarães, José Tasso F; Dall'Agnol, Roberto; Siqueira, José Oswaldo

2016-02-01

Long-term human-induced impacts have significantly changed the Amazonian landscape. The most dramatic land cover and land use (LCLU) changes began in the early 1970s with the establishment of the Trans-Amazon Highway and large government projects associated with the expansion of agricultural settlement and cattle ranching, which cleared significant tropical forest cover in the areas of new and accelerated human development. Taking the changes in the LCLU over the past four decades as a basis, this study aims to determine the consequences of land cover (forest and savanna) and land use (pasturelands, mining and urban) changes on the hydroclimatology of the Itacaiúnas River watershed area of the located in the southeastern Amazon region. We analyzed a multi-decadal Landsat dataset from 1973, 1984, 1994, 2004 and 2013 and a 40-yr time series of water discharge from the Itacaiúnas River, as well as air temperature and relative humidity data over this drainage area for the same period. We employed standard Landsat image processing techniques in conjunction with a geographic object-based image analysis and multi-resolution classification approach. With the goal of detecting possible long-term trends, non-parametric Mann-Kendall test was applied, based on a Sen slope estimator on a 40-yr annual PREC, TMED and RH time series, considering the spatial average of the entire watershed. In the 1970s, the region was entirely covered by forest (99%) and savanna (∼0.3%). Four decades later, only ∼48% of the tropical forest remains, while pasturelands occupy approximately 50% of the watershed area. Moreover, in protected areas, nearly 97% of the tropical forest remains conserved, while the forest cover of non-protected areas is quite fragmented and, consequently, unevenly distributed, covering an area of only 30%. Based on observational data analysis, there is evidence that the conversion of forest cover to extensive and homogeneous pasturelands was accompanied by systematic modifications to the hydroclimatology cycle of the Itacaiúnas watershed, thus highlighting drier environmental conditions due to a rise in the region's air temperature, a decrease in the relative humidity, and an increase in river discharge. Copyright © 2015 Elsevier Ltd. All rights reserved.

Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality

USGS Publications Warehouse

Foster, Jane R.; D'Amato, Anthony W.; Bradford, John B.

2014-01-01

Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20–30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25–30 % higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.

Effects of wildlife forestry on abundance of breeding birds in bottomland hardwood forests of Louisiana

USGS Publications Warehouse

Norris, Jennifer L.; Chamberlain, Michael J.; Twedt, Daniel J.

2009-01-01

Effects of silvicultural activities on birds are of increasing interest because of documented national declines in breeding bird populations for some species and the potential that these declines are in part due to changes in forest habitat. Silviculturally induced disturbances have been advocated as a means to achieve suitable forest conditions for priority wildlife species in bottomland hardwood forests. We evaluated how silvicultural activities on conservation lands in bottomland hardwood forests of Louisiana, USA, influenced species-specific densities of breeding birds. Our data were from independent studies, which used standardized point-count surveys for breeding birds in 124 bottomland hardwood forest stands on 12 management areas. We used Program DISTANCE 5.0, Release 2.0 (Thomas et al. 2006) to estimate density for 43 species with > 50 detections. For 36 of those species we compared density estimates among harvest regimes (individual selection, group selection, extensive harvest, and no harvest). We observed 10 species with similar densities in those harvest regimes compared with densities in stands not harvested. However, we observed 10 species that were negatively impacted by harvest with greater densities in stands not harvested, 9 species with greater densities in individual selection stands, 4 species with greater densities in group selection stands, and 4 species with greater densities in stands receiving an extensive harvest (e.g., > 40% canopy removal). Differences in intensity of harvest influenced densities of breeding birds. Moreover, community-wide avian conservation values of stands subjected to individual and group selection, and stands not harvested, were similar to each other and greater than that of stands subjected to extensive harvest that removed > 40% canopy cover. These results have implications for managers estimating breeding bird populations, in addition to predicting changes in bird communities as a result of prescribed and future forest management practices.

Forest Management Intensity Affects Aquatic Communities in Artificial Tree Holes.

PubMed

Petermann, Jana S; Rohland, Anja; Sichardt, Nora; Lade, Peggy; Guidetti, Brenda; Weisser, Wolfgang W; Gossner, Martin M

2016-01-01

Forest management could potentially affect organisms in all forest habitats. However, aquatic communities in water-filled tree-holes may be especially sensitive because of small population sizes, the risk of drought and potential dispersal limitation. We set up artificial tree holes in forest stands subject to different management intensities in two regions in Germany and assessed the influence of local environmental properties (tree-hole opening type, tree diameter, water volume and water temperature) as well as regional drivers (forest management intensity, tree-hole density) on tree-hole insect communities (not considering other organisms such as nematodes or rotifers), detritus content, oxygen and nutrient concentrations. In addition, we compared data from artificial tree holes with data from natural tree holes in the same area to evaluate the methodological approach of using tree-hole analogues. We found that forest management had strong effects on communities in artificial tree holes in both regions and across the season. Abundance and species richness declined, community composition shifted and detritus content declined with increasing forest management intensity. Environmental variables, such as tree-hole density and tree diameter partly explained these changes. However, dispersal limitation, indicated by effects of tree-hole density, generally showed rather weak impacts on communities. Artificial tree holes had higher water temperatures (on average 2°C higher) and oxygen concentrations (on average 25% higher) than natural tree holes. The abundance of organisms was higher but species richness was lower in artificial tree holes. Community composition differed between artificial and natural tree holes. Negative management effects were detectable in both tree-hole systems, despite their abiotic and biotic differences. Our results indicate that forest management has substantial and pervasive effects on tree-hole communities and may alter their structure and functioning. We furthermore conclude that artificial tree-hole analogues represent a useful experimental alternative to test effects of changes in forest management on natural communities.

Forest Management Intensity Affects Aquatic Communities in Artificial Tree Holes

PubMed Central

Petermann, Jana S.; Rohland, Anja; Sichardt, Nora; Lade, Peggy; Guidetti, Brenda; Weisser, Wolfgang W.; Gossner, Martin M.

2016-01-01

Forest management could potentially affect organisms in all forest habitats. However, aquatic communities in water-filled tree-holes may be especially sensitive because of small population sizes, the risk of drought and potential dispersal limitation. We set up artificial tree holes in forest stands subject to different management intensities in two regions in Germany and assessed the influence of local environmental properties (tree-hole opening type, tree diameter, water volume and water temperature) as well as regional drivers (forest management intensity, tree-hole density) on tree-hole insect communities (not considering other organisms such as nematodes or rotifers), detritus content, oxygen and nutrient concentrations. In addition, we compared data from artificial tree holes with data from natural tree holes in the same area to evaluate the methodological approach of using tree-hole analogues. We found that forest management had strong effects on communities in artificial tree holes in both regions and across the season. Abundance and species richness declined, community composition shifted and detritus content declined with increasing forest management intensity. Environmental variables, such as tree-hole density and tree diameter partly explained these changes. However, dispersal limitation, indicated by effects of tree-hole density, generally showed rather weak impacts on communities. Artificial tree holes had higher water temperatures (on average 2°C higher) and oxygen concentrations (on average 25% higher) than natural tree holes. The abundance of organisms was higher but species richness was lower in artificial tree holes. Community composition differed between artificial and natural tree holes. Negative management effects were detectable in both tree-hole systems, despite their abiotic and biotic differences. Our results indicate that forest management has substantial and pervasive effects on tree-hole communities and may alter their structure and functioning. We furthermore conclude that artificial tree-hole analogues represent a useful experimental alternative to test effects of changes in forest management on natural communities. PMID:27187741

Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data

NASA Technical Reports Server (NTRS)

Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.

1989-01-01

Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.

Space Radar Image of Prince Albert, Canada, seasonal

NASA Image and Video Library

1999-05-01

This is a comparison of images over Prince Albert, produced by NASA Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on its 20th orbit on April 10, 1994. The area is centered at 53.91 degrees north latitude and 104.69 degrees west longitude and is located 40 kilometers (25 miles) north and 30 kilometers (18.5 miles) east of the town of Prince Albert in the Saskatchewan province of Canada. The image covers the area east of Candle Lake, between the gravel highway of 120 and west of highway 106. The area imaged is near the southern limit of the boreal forest. The boreal forest of North America is a continuous vegetation belt at high latitudes stretching across the continent from the Atlantic shoreline of central Labrador and then westward across Canada to the interior mountains and central coastal plains of Alaska. The forest is also part of a larger northern hemisphere circumpolar boreal forest belt. Coniferous trees dominate the entire forest but deciduous trees are also present. During the month of April, the forest experiences seasonal changes from a frozen condition to a thawed condition. The trees are completely frozen over the winter season and the forest floor is covered by snow. As the average temperature rises in the spring, the trees are thawed and the snow melts. This transition has an impact on the rate of moisture evaporation and release of carbon dioxide into the atmosphere. In late September and early October, the boreal forest experiences a relatively different seasonal change. At this time, the leaves on deciduous trees start changing color and dropping off. The soil and trees are quite often moist due to frequent rainfall and cloud cover. The evaporation of moisture and carbon dioxide into the atmosphere also diminishes at this time. SIR-C/X-SAR is sensitive to the moisture of soil and vegetation and can sense this freeze-thaw cycle and the summer-fall seasonal transition over forested areas in particular. Optical sensors, by contrast, are blind to these regions, which are perpetually obscured by thick cloud cover. These changes were detected by comparing the April and October color composite images of L-band data in red, C-band data in green and X-band (vertically received and transmitted) in blue. The changes in intensity of each color over lakes, various forest stands and clear cuts in the two images is striking. Lakes such as Lake Heiberg, Crabtree Lake and Williams Lake, in the right middle part of the image, are frozen in April (appearing in bright blue) and melted (appearing in black) in October. The higher intensity of blue over lakes in April is due to low penetration of the X-band (vertically received and transmitted) and the radar's high sensitivity to surface features. Forest stands also exhibit major changes between the two images. The red areas in the October image are old jack pine canopies that cause higher return at L-band because of their moist condition in late summer compared to their partially frozen condition in April (in purple). Similarly, in the areas near the middle of the image, where black spruce and mixed aspen and jack pine trees dominate, the contrast between blue in October and red and green in April is an indication that the top of the canopy (needles and branches) were frozen in April and moist in October. The changes due to deforestation by logging companies or natural fires can also be detected by comparing the images. For example, the small blue area near the intersection of Harding Road and Highway 120 is the result of logging which occurred after the April data was acquired. The surface area of clear cut is approximately 4 hectares, which is calculated from the high-resolution capability of the radar images and verified by scientists participating in field work during the mission. http://photojournal.jpl.nasa.gov/catalog/PIA01732

Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

PubMed

Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou

2008-09-01

During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.

Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure

USGS Publications Warehouse

McCarley, T. Ryan; Kolden, Crystal A.; Vaillant, Nicole M.; Hudak, Andrew T.; Smith, Alistair M.S.; Wing, Brian M.; Kellogg, Bryce; Kreitler, Jason R.

2017-01-01

Measuring post-fire effects at landscape scales is critical to an ecological understanding of wildfire effects. Predominantly this is accomplished with either multi-spectral remote sensing data or through ground-based field sampling plots. While these methods are important, field data is usually limited to opportunistic post-fire observations, and spectral data often lacks validation with specific variables of change. Additional uncertainty remains regarding how best to account for environmental variables influencing fire effects (e.g., weather) for which observational data cannot easily be acquired, and whether pre-fire agents of change such as bark beetle and timber harvest impact model accuracy. This study quantifies wildfire effects by correlating changes in forest structure derived from multi-temporal Light Detection and Ranging (LiDAR) acquisitions to multi-temporal spectral changes captured by the Landsat Thematic Mapper and Operational Land Imager for the 2012 Pole Creek Fire in central Oregon. Spatial regression modeling was assessed as a methodology to account for spatial autocorrelation, and model consistency was quantified across areas impacted by pre-fire mountain pine beetle and timber harvest. The strongest relationship (pseudo-r2 = 0.86, p < 0.0001) was observed between the ratio of shortwave infrared and near infrared reflectance (d74) and LiDAR-derived estimate of canopy cover change. Relationships between percentage of LiDAR returns in forest strata and spectral indices generally increased in strength with strata height. Structural measurements made closer to the ground were not well correlated. The spatial regression approach improved all relationships, demonstrating its utility, but model performance declined across pre-fire agents of change, suggesting that such studies should stratify by pre-fire forest condition. This study establishes that spectral indices such as d74 and dNBR are most sensitive to wildfire-caused structural changes such as reduction in canopy cover and perform best when that structure has not been reduced pre-fire.

Deforestation and Industrial Forest Patterns in Colombia: a Case Study

NASA Astrophysics Data System (ADS)

Huo, L. Z.; Boschetti, L.; Sparks, A. M.; Clerici, N.

2017-12-01

The recent peace agreement between the government and the Revolutionary Armed Forces of Colombia (FARC) offers new opportunities for peaceful and sustainable development, but at the same time requires a timely effort to protect biological resources, and ecosystem services (Clerici et al., 2016). In this context, we use the 2001-2017 Landsat data record to prototype a methodology to establish a baseline of deforestation, afforestation and industrial forest practices (i.e. establishment and harvest of forest plantations), and to monitor future changes. Two study areas, which have seen considerable deforestation in recent years, were selected: one in the South of the country, at the edge of the Amazon Forest (WRS path 008 row 059) and one in the center, in mixed forest (WRS path 008 row 055). The time series of all the available cloud free Landsat 5, Landsat 7 and Landsat 8 data was classified into a sequence of binary forest/non forest maps using a deep learning model, successfully used in the natural language processing field, trained to detect forest transitions. Recurrent Neural Networks (RNN) is a class of artificial neural network that extends the conventional neural network with loops in the connections (Graves et al., 2013). Unlike a feed-forward neural network, an RNN is able to process the sequential inputs by having a recurrent hidden state whose activation at each step depends on that of the previous steps. In this manner, the RNN provides a good framework to dynamically model time series data, and has been successfully applied to natural language processing in Google (Sutskever et al., 2014). The sequence of forest cover state maps was subsequently post-processed to differentiate between deforestation (e.g. transition from forest to non forest land use) and industrial forest harvest (i.e. timber harvest followed by regrowth), by integrating the detection of temporal patterns, and spatial patterns. References Clerici, N., et al., (2016). Colombia: Dealing in conservation. Science, 354(6309), 190-190. Sutskever I.,et al. (2014). Sequence to sequence learning with neural networks. Advances in neural information processing systems, 3104-3112. Graves A., et al. (2013). Speech recognition with deep recurrent neural networks. In Proc. IEEE Int. Conf. Acoust. Speech Signal Process., 6645-6649.

National Detection Surveys for Sudden Oak Death

Treesearch

B. M. Tkacz; S. W. Oak; W. D. Smith

2006-01-01

The Forest Health Monitoring program, a partnership of Federal and State forest management agencies, has developed and tested protocols for identifying and surveying forest ecosystems that may be vulnerable to invasion by Phytophthora ramorum, the cause of Sudden Oak Death in California and Oregon. This detection survey is targeting areas outside the currently known...

Humid tropical rain forest has expanded into eucalypt forest and savanna over the last 50 years

PubMed Central

Tng, David Y P; Murphy, Brett P; Weber, Ellen; Sanders, Gregor; Williamson, Grant J; Kemp, Jeanette; Bowman, David M J S

2012-01-01

Tropical rain forest expansion and savanna woody vegetation thickening appear to be a global trend, but there remains uncertainty about whether there is a common set of global drivers. Using geographic information techniques, we analyzed aerial photography of five areas in the humid tropics of northeastern Queensland, Australia, taken in the 1950s and 2008, to determine if changes in rain forest extent match those reported for the Australian monsoon tropics using similar techniques. Mapping of the 1950s aerial photography showed that of the combined study area (64,430 ha), 63% was classified as eucalypt forests/woodland and 37% as rain forest. Our mapping revealed that although most boundaries remained stable, there was a net increase of 732 ha of the original rain forest area over the study period, and negligible conversion of rain forest to eucalypt forest/woodland. Statistical modeling, controlling for spatial autocorrelation, indicated distance from preexisting rain forest as the strongest determinant of rain forest expansion. Margin extension had a mean rate across the five sites of 0.6 m per decade. Expansion was greater in tall open forest types but also occurred in shorter, more flammable woodland vegetation types. No correlations were detected with other local variables (aspect, elevation, geology, topography, drainage). Using a geographically weighted mean rate of rain forest margin extension across the whole region, we predict that over 25% of tall open forest (a forest type of high conservation significance) would still remain after 2000 years of rain forest expansion. This slow replacement is due to the convoluted nature of the rain forest boundary and the irregular shape of the tall open forest patches. Our analyses point to the increased concentration of atmospheric CO2 as the most likely global driver of indiscriminate rain forest expansion occurring in northeastern Australia, by increasing tree growth and thereby overriding the effects of fire disturbance. PMID:22408724

A dataset of forest biomass structure for Eurasia.

PubMed

Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael

2017-05-16

The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

A dataset of forest biomass structure for Eurasia

NASA Astrophysics Data System (ADS)

Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael

2017-05-01

The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

How does forest disturbance and succession affect summer streamflow recession?

NASA Astrophysics Data System (ADS)

Brena, A.; Stahl, K.; Weiler, M.

2011-12-01

Streamflow recession is a main signature of catchment behavior during dry conditions. The storage-discharge relationship of every catchment reflects the aquifer properties and land surface processes including evapotranspiration rates. Commonly, the storage-discharge relationship in watersheds is analyzed through the recession limb of the hydrograph, which generally follows a nonlinear pattern. It is, however, unknown how forest disturbance and succession may modify the degree of nonlinearity of baseflow recession and the magnitude of baseflow. The presented study analyzes and characterizes streamflow recession during summer before and after forest disturbance using data from six experimental paired-watersheds with controlled forest disturbances across different climatic regions and ecozones of the USA. Characteristic non-linear recession parameters were fitted by a Monte Carlo resampling method. No systematic relationship was found between annual precipitation, drainage area, mean elevation, and recession characteristics. However, higher storage rates and low flows across the sites were detected following forest disturbance. Exceptions are the snow-dominated watersheds and changes appear to be stronger in watersheds with deciduous forests. The results are however dependent on the method of recession limb selection, including start level and time. Further research is needed over a wide range of forest sites and according to the type of disturbance (e.g. fire, disease), which may ultimately define the dynamics of forest succession and therefore the streamflow recession behavior.

Regional-scale drivers of forest structure and function in northwestern Amazonia.

PubMed

Higgins, Mark A; Asner, Gregory P; Anderson, Christopher B; Martin, Roberta E; Knapp, David E; Tupayachi, Raul; Perez, Eneas; Elespuru, Nydia; Alonso, Alfonso

2015-01-01

Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging) data and VSWIR (Visible to Shortwave Infrared) imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest.

Crown Health of Reserve Hardwood Trees Following Reproduction Cutting in the Ouachita Mountains

Treesearch

Dale A. Starkey; James M. Guldin

2004-01-01

Abstract - Monitoring the health of reserve hardwood trees is being performed as part of the Ecosystem Management Research Project on the Ouachita and Ozark National Forests in Arkansas. A suite of crown variables (diameter, live crown ratio, density, dieback, and foliage transparency) was used to detect significant changes in reserve tree health...

Fire Science Strategy: Resource Conservation and Climate Change

DTIC Science & Technology

2014-09-01

SMOKE MANAGEMENT ISSUES: CONCLUSIONS—KEY RESEARCH/DEMONSTRATION GAPS COVER PHOTO: CHONG, JOEY 2011. USDA FOREST SERVICE. FORT JACKSON...Fire Science Program LiDAR Light Detection and Ranging LANL Los Alamos National Lab NASA National Aeronautics and Space Administration NCAR...entities include the National Aeronautics and Space Administration ( NASA ), EPA, National Center for Atmospheric Research (NCAR), National Institute of

Functional traits variation explains the distribution of Aextoxicon punctatum (Aextoxicaceae) in pronounced moisture gradients within fog-dependent forest fragments.

PubMed

Salgado-Negret, Beatriz; Canessa, Rafaella; Valladares, Fernando; Armesto, Juan J; Pérez, Fernanda

2015-01-01

Climate change and fragmentation are major threats to world forests. Understanding how functional traits related to drought tolerance change across small-scale, pronounced moisture gradients in fragmented forests is important to predict species' responses to these threats. In the case of Aextoxicon punctatum, a dominant canopy tree in fog-dependent rain forest patches in semiarid Chile, we explored how the magnitude, variability and correlation patterns of leaf and xylem vessel traits and hydraulic conductivity varied across soil moisture (SM) gradients established within and among forest patches of different size, which are associated with differences in tree establishment and mortality patterns. Leaf traits varied across soil-moisture gradients produced by fog interception. Trees growing at drier leeward edges showed higher leaf mass per area, trichome and stomatal density than trees from the wetter core and windward zones. In contrast, xylem vessel traits (vessels diameter and density) did not vary producing loss of hydraulic conductivity at drier leeward edges. We also detected higher levels of phenotypic integration and variability at leeward edges. The ability of A. punctatum to modify leaf traits in response to differences in SM availability established over short distances (<500 m) facilitates its persistence in contrasting microhabitats within forest patches. However, xylem anatomy showed limited plasticity, which increases cavitation risk at leeward edges. Greater patch fragmentation, together with fluctuations in irradiance and SM in small patches, could result in higher risk of drought-related tree mortality, with profound impacts on hydrological balances at the ecosystem scale.

Functional traits variation explains the distribution of Aextoxicon punctatum (Aextoxicaceae) in pronounced moisture gradients within fog-dependent forest fragments

PubMed Central

Salgado-Negret, Beatriz; Canessa, Rafaella; Valladares, Fernando; Armesto, Juan J.; Pérez, Fernanda

2015-01-01

Climate change and fragmentation are major threats to world forests. Understanding how functional traits related to drought tolerance change across small-scale, pronounced moisture gradients in fragmented forests is important to predict species’ responses to these threats. In the case of Aextoxicon punctatum, a dominant canopy tree in fog-dependent rain forest patches in semiarid Chile, we explored how the magnitude, variability and correlation patterns of leaf and xylem vessel traits and hydraulic conductivity varied across soil moisture (SM) gradients established within and among forest patches of different size, which are associated with differences in tree establishment and mortality patterns. Leaf traits varied across soil-moisture gradients produced by fog interception. Trees growing at drier leeward edges showed higher leaf mass per area, trichome and stomatal density than trees from the wetter core and windward zones. In contrast, xylem vessel traits (vessels diameter and density) did not vary producing loss of hydraulic conductivity at drier leeward edges. We also detected higher levels of phenotypic integration and variability at leeward edges. The ability of A. punctatum to modify leaf traits in response to differences in SM availability established over short distances (<500 m) facilitates its persistence in contrasting microhabitats within forest patches. However, xylem anatomy showed limited plasticity, which increases cavitation risk at leeward edges. Greater patch fragmentation, together with fluctuations in irradiance and SM in small patches, could result in higher risk of drought-related tree mortality, with profound impacts on hydrological balances at the ecosystem scale. PMID:26257746

Climate- and successional-related changes in functional composition of European forests are strongly driven by tree mortality.

PubMed

Ruiz-Benito, Paloma; Ratcliffe, Sophia; Zavala, Miguel A; Martínez-Vilalta, Jordi; Vilà-Cabrera, Albert; Lloret, Francisco; Madrigal-González, Jaime; Wirth, Christian; Greenwood, Sarah; Kändler, Gerald; Lehtonen, Aleksi; Kattge, Jens; Dahlgren, Jonas; Jump, Alistair S

2017-10-01

Intense droughts combined with increased temperatures are one of the major threats to forest persistence in the 21st century. Despite the direct impact of climate change on forest growth and shifts in species abundance, the effect of altered demography on changes in the composition of functional traits is not well known. We sought to (1) quantify the recent changes in functional composition of European forests; (2) identify the relative importance of climate change, mean climate and forest development for changes in functional composition; and (3) analyse the roles of tree mortality and growth underlying any functional changes in different forest types. We quantified changes in functional composition from the 1980s to the 2000s across Europe by two dimensions of functional trait variation: the first dimension was mainly related to changes in leaf mass per area and wood density (partially related to the trait differences between angiosperms and gymnosperms), and the second dimension was related to changes in maximum tree height. Our results indicate that climate change and mean climatic effects strongly interacted with forest development and it was not possible to completely disentangle their effects. Where recent climate change was not too extreme, the patterns of functional change generally followed the expected patterns under secondary succession (e.g. towards late-successional short-statured hardwoods in Mediterranean forests and taller gymnosperms in boreal forests) and latitudinal gradients (e.g. larger proportion of gymnosperm-like strategies at low water availability in forests formerly dominated by broad-leaved deciduous species). Recent climate change generally favoured the dominance of angiosperm-like related traits under increased temperature and intense droughts. Our results show functional composition changes over relatively short time scales in European forests. These changes are largely determined by tree mortality, which should be further investigated and modelled to adequately predict the impacts of climate change on forest function. © 2017 John Wiley & Sons Ltd.

Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets

USGS Publications Warehouse

Hansen, Matt; Stehman, Steve; Loveland, Tom; Vogelmann, Jim; Cochrane, Mark

2009-01-01

Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.

Forests and climate change: forcings, feedbacks, and the climate benefits of forests.

PubMed

Bonan, Gordon B

2008-06-13

The world's forests influence climate through physical, chemical, and biological processes that affect planetary energetics, the hydrologic cycle, and atmospheric composition. These complex and nonlinear forest-atmosphere interactions can dampen or amplify anthropogenic climate change. Tropical, temperate, and boreal reforestation and afforestation attenuate global warming through carbon sequestration. Biogeophysical feedbacks can enhance or diminish this negative climate forcing. Tropical forests mitigate warming through evaporative cooling, but the low albedo of boreal forests is a positive climate forcing. The evaporative effect of temperate forests is unclear. The net climate forcing from these and other processes is not known. Forests are under tremendous pressure from global change. Interdisciplinary science that integrates knowledge of the many interacting climate services of forests with the impacts of global change is necessary to identify and understand as yet unexplored feedbacks in the Earth system and the potential of forests to mitigate climate change.

Trends in atmospheric deposition fluxes of sulphur and nitrogen in Czech forests.

PubMed

Hůnová, Iva; Maznová, Jana; Kurfürst, Pavel

2014-01-01

We present the temporal trends and spatial changes of deposition of sulphur and nitrogen in Czech forests based on records from long-term monitoring. A statistically significant trend for sulphur was detected at most of the sites measuring for wet, dry, and total deposition fluxes and at many of these the trend was also present for the period after 2000. The spatial pattern of the changes in sulphur deposition flux between 1995 and 2011 shows the decrease over the entire forested area in a wide range of 18.1-0.2 g m(-2) year(-1) with the most pronounced improvement in formerly most impacted regions. Nitrogen still represents a considerable stress in many areas. The value of nitrogen deposition flux of 1 g m(-2) year(-1) is exceeded over a significant portion of the country. On an equivalent basis, the ion ratios of NO3(-)/SO4(2-) and NH4(+)/SO4(2-) in precipitation show significantly increasing trends in time similarly to those of pH. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial models reveal the microclimatic buffering capacity of old-growth forests

PubMed Central

Frey, Sarah J. K.; Hadley, Adam S.; Johnson, Sherri L.; Schulze, Mark; Jones, Julia A.; Betts, Matthew G.

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming. PMID:27152339

Evaluation and parameterization of ATCOR3 topographic correction method for forest cover mapping in mountain areas

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Lambin, Eric F.

2012-08-01

A topographic correction of optical remote sensing data is necessary to improve the quality of quantitative forest cover change analyses in mountainous terrain. The implementation of semi-empirical correction methods requires the calibration of model parameters that are empirically defined. This study develops a method to improve the performance of topographic corrections for forest cover change detection in mountainous terrain through an iterative tuning method of model parameters based on a systematic evaluation of the performance of the correction. The latter was based on: (i) the general matching of reflectances between sunlit and shaded slopes and (ii) the occurrence of abnormal reflectance values, qualified as statistical outliers, in very low illuminated areas. The method was tested on Landsat ETM+ data for rough (Ecuadorian Andes) and very rough mountainous terrain (Bhutan Himalayas). Compared to a reference level (no topographic correction), the ATCOR3 semi-empirical correction method resulted in a considerable reduction of dissimilarities between reflectance values of forested sites in different topographic orientations. Our results indicate that optimal parameter combinations are depending on the site, sun elevation and azimuth and spectral conditions. We demonstrate that the results of relatively simple topographic correction methods can be greatly improved through a feedback loop between parameter tuning and evaluation of the performance of the correction model.

Spatial models reveal the microclimatic buffering capacity of old-growth forests.

PubMed

Frey, Sarah J K; Hadley, Adam S; Johnson, Sherri L; Schulze, Mark; Jones, Julia A; Betts, Matthew G

2016-04-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.

Conservation of forest birds: evidence of a shifting baseline in community structure.

PubMed

Rittenhouse, Chadwick D; Pidgeon, Anna M; Albright, Thomas P; Culbert, Patrick D; Clayton, Murray K; Flather, Curtis H; Huang, Chengquan; Masek, Jeffrey G; Stewart, Susan I; Radeloff, Volker C

2010-08-02

Quantifying changes in forest bird diversity is an essential task for developing effective conservation actions. When subtle changes in diversity accumulate over time, annual comparisons may offer an incomplete perspective of changes in diversity. In this case, progressive change, the comparison of changes in diversity from a baseline condition, may offer greater insight because changes in diversity are assessed over longer periods of times. Our objectives were to determine how forest bird diversity has changed over time and whether those changes were associated with forest disturbance. We used North American Breeding Bird Survey data, a time series of Landsat images classified with respect to land cover change, and mixed-effects models to associate changes in forest bird community structure with forest disturbance, latitude, and longitude in the conterminous United States for the years 1985 to 2006. We document a significant divergence from the baseline structure for all birds of similar migratory habit and nest location, and all forest birds as a group from 1985 to 2006. Unexpectedly, decreases in progressive similarity resulted from small changes in richness (<1 species per route for the 22-year study period) and modest losses in abundance (-28.7 - -10.2 individuals per route) that varied by migratory habit and nest location. Forest disturbance increased progressive similarity for Neotropical migrants, permanent residents, ground nesting, and cavity nesting species. We also documented highest progressive similarity in the eastern United States. Contemporary forest bird community structure is changing rapidly over a relatively short period of time (e.g., approximately 22 years). Forest disturbance and forest regeneration are primary factors associated with contemporary forest bird community structure, longitude and latitude are secondary factors, and forest loss is a tertiary factor. Importantly, these findings suggest some regions of the United States may already fall below the habitat amount threshold where fragmentation effects become important predictors of forest bird community structure.

Extracting Forest Canopy Characteristics from Remote Sensing Imagery: Implications for Sentinel-2 Mission

NASA Astrophysics Data System (ADS)

Gholizadeh, Asa; Kopaekova, Veronika; Rogass, Christian; Mielke, Christian; Misurec, Jan

2016-08-01

Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change. Remote sensing has been introduced as a time and cost- efficient way to carry out large scale monitoring of vegetation parameters. Red-Edge Position (REP) is a hyperspectrally detectable parameter which is sensitive to vegetation Chl. In the current study, REP was modelled for the Norway spruce forest canopy resampled to HyMap and Sentinel-2 spectral resolution as well as calculated from the real HyMap and Sentinel-2 simulated data. Different REP extraction methods (4PLI, PF, LE, 4PLIH and 4PLIS) were assessed. The study showed the way for effective utilization of the forthcoming hyper and superspectral remote sensing sensors from orbit to monitor vegetation attributes.

Detecting targets hidden in random forests

NASA Astrophysics Data System (ADS)

Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

2009-05-01

Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

Detecting deforestation with a spectral change detection approach using multitemporal Landsat data: a case study of Kinabalu Park, Sabah, Malaysia.

PubMed

Phua, Mui-How; Tsuyuki, Satoshi; Furuya, Naoyuki; Lee, Jung Soo

2008-09-01

Tropical deforestation is occurring at an alarming rate, threatening the ecological integrity of protected areas. This makes it vital to regularly assess protected areas to confirm the efficacy of measures that protect that area from clearing. Satellite remote sensing offers a systematic and objective means for detecting and monitoring deforestation. This paper examines a spectral change approach to detect deforestation using pattern decomposition (PD) coefficients from multitemporal Landsat data. Our results show that the PD coefficients for soil and vegetation can be used to detect deforestation using change vector analysis (CVA). CVA analysis demonstrates that deforestation in the Kinabalu area, Sabah, Malaysia has significantly slowed from 1.2% in period 1 (1973 and 1991) to 0.1% in period 2 (1991 and 1996). A comparison of deforestation both inside and outside Kinabalu Park has highlighted the effectiveness of the park in protecting the tropical forest against clearing. However, the park is still facing pressure from the area immediately surrounding the park (the 1 km buffer zone) where the deforestation rate has remained unchanged.

Landscape variability of vegetation change across the forest to tundra transition of central Canada

NASA Astrophysics Data System (ADS)

Bonney, Mitchell Thurston

Widespread vegetation productivity increases in tundra ecosystems and stagnation, or even productivity decreases, in boreal forest ecosystems have been detected from coarse-scale remote sensing observations over the last few decades. However, finer-scale Landsat studies have shown that these changes are heterogeneous and may be related to landscape and regional variability in climate, land cover, topography and moisture. In this study, a Landsat Normalized Difference Vegetation Index (NDVI) time-series (1984-2016) was examined for a study area spanning the entirety of the sub-Arctic boreal forest to Low Arctic tundra transition of central Canada (i.e., Yellowknife to the Arctic Ocean). NDVI trend analysis indicated that 27% of un-masked pixels in the study area exhibited a significant (p < 0.05) trend and virtually all (99.3%) of those pixels were greening. Greening pixels were most common in the northern tundra zone and the southern forest-tundra ecotone zone. NDVI trends were positive throughout the study area, but were smallest in the forest zone and largest in the northern tundra zone. These results were supported by ground validation, which found a strong relationship (R2 = 0.81) between bulk vegetation volume (BVV) and NDVI for non-tree functional groups in the North Slave region of Northwest Territories. Field observations indicate that alder (Alnus spp.) shrublands and open woodland sites with shrubby understories were most likely to exhibit greening in that area. Random Forest (RF) modelling of the relationship between NDVI trends and environmental variables found that the magnitude and direction of trends differed across the forest to tundra transition. Increased summer temperatures, shrubland and forest land cover, closer proximity to major drainage systems, longer distances from major lakes and lower elevations were generally more important and associated with larger positive NDVI trends. These findings indicate that the largest positive NDVI trends were primarily associated with the increased productivity of shrubby environments, especially at, and north of the forest-tundra ecotone in areas with more favorable growing conditions. Smaller and less significant NDVI trends in boreal forest environments south of the forest-tundra ecotone were likely associated with long-term recovery from fire disturbance rather than the variables analyzed here.

Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

Treesearch

William D. Dijak; Brice B. Hanberry; Jacob S. Fraser; Hong S. He; Wen J. Wang; Frank R. Thompson

2017-01-01

Context. Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest...

Preface. Forest ecohydrological processes in a changing environment.

Treesearch

Xiaohua Wei; Ge Sun; James Vose; Kyoichi Otsuki; Zhiqiang Zhang; Keith Smetterm

2011-01-01

The papers in this issue are a selection of the presentations made at the second International Conference on Forests and Water in a Changing Environment. This special issue ‘Forest Ecohydrological Processes in a Changing Environment’ covers the topics regarding the effects of forest, land use and climate changes on ecohydrological processes across forest stand,...

Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000

USGS Publications Warehouse

Raumann, Christian G.; Soulard, Christopher E.

2007-01-01

The U.S. Geological Survey has developed and is implementing the Land Cover Trends project to estimate and describe the temporal and spatial distribution and variability of contemporary land-use and land-cover change in the United States. As part of the Land Cover Trends project, the purpose of this study was to assess land-use/land-cover change in the Sierra Nevada ecoregion for the period 1973 to 2000 using a probability sampling technique and satellite imagery. We randomly selected 36 100-km2 sample blocks to derive thematic images of land-use/land-cover for five dates of Landsat imagery (1973, 1980, 1986, 1992, 2000). We visually interpreted as many as 11 land-use/land-cover classes using a 60-meter minimum mapping unit from the five dates of imagery yielding four periods for analysis. Change-detection results from post-classification comparison of our mapped data showed that landscape disturbance from fire was the dominant change from 1973-2000. The second most-common change was forest disturbance resulting from harvest of timber resources by way of clear-cutting. The rates of forest regeneration from temporary fire and harvest disturbances coincided with the rates of disturbance from the previous period. Relatively minor landscape changes were caused by new development and reservoir drawdown. Multiple linear regression analysis suggests that land ownership and the proportion of forest and developed cover types were significant determinants of the likelihood of direct human-induced change occurring in sampling units. Driving forces of change include land ownership, land management such as fire suppression policy, and demand for natural resources.

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PubMed

Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

Land-cover change detection

USGS Publications Warehouse

Chen, Xuexia; Giri, Chandra; Vogelmann, James

2012-01-01

Land cover is the biophysical material on the surface of the earth. Land-cover types include grass, shrubs, trees, barren, water, and man-made features. Land cover changes continuously.  The rate of change can be either dramatic and abrupt, such as the changes caused by logging, hurricanes and fire, or subtle and gradual, such as regeneration of forests and damage caused by insects (Verbesselt et al., 2001).  Previous studies have shown that land cover has changed dramatically during the past sevearal centuries and that these changes have severely affected our ecosystems (Foody, 2010; Lambin et al., 2001). Lambin and Strahlers (1994b) summarized five types of cause for land-cover changes: (1) long-term natural changes in climate conditions, (2) geomorphological and ecological processes, (3) human-induced alterations of vegetation cover and landscapes, (4) interannual climate variability, and (5) human-induced greenhouse effect.  Tools and techniques are needed to detect, describe, and predict these changes to facilitate sustainable management of natural resources.

Detection of early warning signals of forest mortality in California

NASA Astrophysics Data System (ADS)

Liu, Y.; Kumar, M.; Katul, G. G.; Porporato, A. M.

2017-12-01

Massive forest mortality was observed in California during the most recent drought. Owing to complex interactions of physiological mechanisms under stress, prediction of climate-induced forest mortality using dynamic global vegetation models remains fraught with uncertainty. Given that forest ecosystems approaching mortality tend to exhibit reduction in resilience, we evaluate the time-varying resilience from time series of satellite images to detect early warning signals (EWSs) of mortality. Four metrics of EWSs are used: (1) low greenness, (2) high empirical autocorrelation of greenness, (3) high autocorrelation inferred using a Bayesian dynamic linear model considering the influence of seasonality and climate conditions, and (4) low recovery rate inferred from the drift term in the Langevin equation describing stochastic dynamics. Spatial accuracy and lead-time of these EWSs are evaluated by comparing the EWSs against observed mortality from aerial surveys conducted by the US Forest Service. Our results show that most forested areas in California that underwent mortality exhibit a EWS with a lead time of three months to two years ahead of observed mortality. Notably, EWS is also detected in some areas without mortality, suggesting reduced resilience during drought. Furthermore, the influence of the previous drought (2007-2009) may have propagated into the recent drought (2012-2016) through reduced resilience, hence contributing to the massive forest mortality observed recently. Methodologies developed in this study for detection of EWS will improve the near-term predictability of forest mortality, thus providing crucial information for forest and water resource management.

Sensitivity of managed boreal forests in Finland to climate change, with implications for adaptive management.

PubMed

Kellomäki, Seppo; Peltola, Heli; Nuutinen, Tuula; Korhonen, Kari T; Strandman, Harri

2008-07-12

This study investigated the sensitivity of managed boreal forests to climate change, with consequent needs to adapt the management to climate change. Model simulations representing the Finnish territory between 60 and 70 degrees N showed that climate change may substantially change the dynamics of managed boreal forests in northern Europe. This is especially probable at the northern and southern edges of this forest zone. In the north, forest growth may increase, but the special features of northern forests may be diminished. In the south, climate change may create a suboptimal environment for Norway spruce. Dominance of Scots pine may increase on less fertile sites currently occupied by Norway spruce. Birches may compete with Scots pine even in these sites and the dominance of birches may increase. These changes may reduce the total forest growth locally but, over the whole of Finland, total forest growth may increase by 44%, with an increase of 82% in the potential cutting drain. The choice of appropriate species and reduced rotation length may sustain the productivity of forest land under climate change.

Air-Pollution-Mediated Changes in Alpine Ecosystems and Ecotones.

PubMed

Rusek, Josef

1993-08-01

Soil biological parameters (e.g., Collembola), soil types, soil chemical parameters (pH, humus substances), and plant communities were studied in different ecosystems and ecotones in alpine, subalpine, and spruce forest zones in the Tatra National Park, Slovak Republic. The preliminary, selected data, based on a long-term research program, showed a high sensitivity of some alpine ecotones and ecosystems to long-distance transported acid deposits. The changes in different ecosystem parameters since 1977 were more extensive in alpine grasslands on limestone than on granite. The greatest soil pH decrease was in the plant communities Festucetum versicoloris (-1.5 pH), Geranio-Alchemilletum crinitae (-1.32 pH), and Saxifragetum perdurantis (-1.25 pH), which are restricted to places with snow accumulation and water runoff gullies. In these ecosystems the greatest changes occurred in the leaching of humus substances. Some formerly less abundant and rare soil animals restricted to acid bedrock became dominant in some ecosystems on limestone as well as on granite; other formerly dominant species disappeared from the entire study area (e.g., Folsomia alpina). The aerial extent of some ecosystems changed substantially since 1977, and their surrounding ecotones moved into the space formerly occupied by one of the adjacent ecosystems. These changes are detectable by remote-sensing methods. In Central European mountains, strongly affected by global and regional industrial air pollution (e.g., Krusne Hory, Krkonose, Beskydy), spruce forests started to die back from higher to lower mountain elevations. The effects of air pollution on alpine and subalpine vegetation were not studied there. Strong alterations in alpine ecosystems and ecotones were detected by the author during long-term studies in the High Tatra Mountains, and I suggest that subalpine and mountain forest belts will be affected here in the near future as they were in the more polluted Central European mountains. The ecosystems and ecotones in higher alpine zones are likely to be affected earlier than the ecosystems at lower altitudes. Detection of ecosystem alteration in the alpine zone may be used for prediction of acidification processes and global change in ecosystems at lower altitudes. The consequences of global climate change are predictable by monitoring changes in the extent of some ecosystems located in discrete mountain geomorphological units (e.g., karstic sinkholes, water runoff gullies, wind shadows, ridges exposed to wind, etc.) and ecotones among them because of their dependence on duration of snow cover, water supply, wind and frost exposure, and other abiotic and biotic factors. © 1993 by the Ecological Society of America.

Shifting and Expanding Forest Values: The Case of the U.S. National Forests

Treesearch

David N. Bengston; Zhi Xu

1996-01-01

The idea that public forest values have changed significantly in recent decades has become widespread. According to this view, forest values-conceptions of what is good or desirable about forests-have changed in two important ways. First, it is often claimed that forest values have shifted, i.e., the relative importance of different values has changed. Social...

Monitoring network confirms land use change is a substantial component of the forest carbon sink in the eastern United States

Treesearch

Christopher W. Woodall; Brian F. Walters; John Coulston; A.W. D’Amato; Grant M. Domke; M.B. Russell; Paul Sowers

2015-01-01

Quantifying forest carbon (C) stocks and stock change within a matrix of land use (LU) and LU change is a central component of large-scale forest C monitoring and reporting practices prescribed by the Intergovernmental Panel on Climate Change (IPCC). Using a region–wide, repeated forest inventory, forest C stocks and stock change by pool were examined by LU categories...

[Responses of boreal forest landscape in northern Great Xing'an Mountains of Northeast China to climate change].

PubMed

Li, Xiao-Na; He, Hong-Shi; Wu, Zhi-Wei; Liang, Yu

2012-12-01

With the combination of forest landscape model (LANDIS) and forest gap model (LINKAGES), this paper simulated the effects of climate change on the boreal forest landscape in the Great Xing'an Mountains, and compared the direct effects of climate change and the effects of climate warming-induced fires on the forest landscape. The results showed that under the current climate conditions and fire disturbances, the forest landscape in the study area could maintain its dynamic balance, and Larix gmelinii was still the dominant tree species. Under the future climate and fire disturbances scenario, the distribution area of L. gmelinii and Pinus pumila would be decreased, while that of Betula platyphylla, Populus davidiana, Populus suaveolens, Chosenia arbutifolia, and Pinus sylvestris var. mongolica would be increased, and the forest fragmentation and forest diversity would have an increase. The changes of the forest landscape lagged behind climate change. Climate warming would increase the growth of most tree species except L. gmelinii, while the increased fires would increase the distribution area of P. davidiana, P. suaveolens, and C. arbutifolia and decrease the distribution area of L. gmelinii, P. sylvestris var. mongolica, and P. pumila. The effects of climate warming-induced fires on the forest landscape were almost equal to the direct effects of climate change, and aggravated the direct effects of climate change on forest composition, forest landscape fragmentation, and forest landscape diversity.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Treesearch

Kristina J. Anderson-Teixeira; Stuart J. Davies; Amy C. Bennett; Erika B. Gonzalez-Akre; Helene C. Muller-Landau; S. Joseph Wright; Kamariah Abu Salim; Angélica M. Almeyda Zambrano; Alfonso Alonso; Jennifer L. Baltzer; Yves Basset; Norman A. Bourg; Eben N. Broadbent; Warren Y. Brockelman; Sarayudh Bunyavejchewin; David F. R. P. Burslem; Nathalie Butt; Min Cao; Dairon Cardenas; George B. Chuyong; Keith Clay; Susan Cordell; Handanakere S. Dattaraja; Xiaobao Deng; Matteo Detto; Xiaojun Du; Alvaro Duque; David L. Erikson; Corneille E.N. Ewango; Gunter A. Fischer; Christine Fletcher; Robin B. Foster; Christian P. Giardina; Gregory S. Gilbert; Nimal Gunatilleke; Savitri Gunatilleke; Zhanqing Hao; William W. Hargrove; Terese B. Hart; Billy C.H. Hau; Fangliang He; Forrest M. Hoffman; Robert W. Howe; Stephen P. Hubbell; Faith M. Inman-Narahari; Patrick A. Jansen; Mingxi Jiang; Daniel J. Johnson; Mamoru Kanzaki; Abdul Rahman Kassim; David Kenfack; Staline Kibet; Margaret F. Kinnaird; Lisa Korte; Kamil Kral; Jitendra Kumar; Andrew J. Larson; Yide Li; Xiankun Li; Shirong Liu; Shawn K.Y. Lum; James A. Lutz; Keping Ma; Damian M. Maddalena; Jean-Remy Makana; Yadvinder Malhi; Toby Marthews; Rafizah Mat Serudin; Sean M. McMahon; William J. McShea; Hervé R. Memiaghe; Xiangcheng Mi; Takashi Mizuno; Michael Morecroft; Jonathan A. Myers; Vojtech Novotny; Alexandre A. de Oliveira; Perry S. Ong; David A. Orwig; Rebecca Ostertag; Jan den Ouden; Geoffrey G. Parker; Richard P. Phillips; Lawren Sack; Moses N. Sainge; Weiguo Sang; Kriangsak Sri-ngernyuang; Raman Sukumar; I-Fang Sun; Witchaphart Sungpalee; Hebbalalu Sathyanarayana Suresh; Sylvester Tan; Sean C. Thomas; Duncan W. Thomas; Jill Thompson; Benjamin L. Turner; Maria Uriarte; Renato Valencia; Marta I. Vallejo; Alberto Vicentini; Tomáš Vrška; Xihua Wang; Xugao Wang; George Weiblen; Amy Wolf; Han Xu; Sandra Yap; Jess Zimmerman

2014-01-01

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses...

Consequences of climate change for biogeochemical cycling in forests of northeastern North America

Treesearch

John L. Campbell; Lindsey E. Rustad; Elizabeth W. Boyer; Sheila F. Christopher; Charles T. Driscoll; Ivan .J. Fernandez; Peter M. Groffman; Daniel Houle; Jana Kiekbusch; Alison H. Magill; Myron J. Mitchell; Scott V. Ollinger

2009-01-01

A critical component of assessing the impacts of climate change on forest ecosystems involves understanding associated changes in biogeochemical cycling of elements. Evidence from research on northeastern North American forests shows that direct effects of climate change will evoke changes in biogeochemical cycling by altering plant physiology forest productivity, and...

High-resolution records detect human-caused changes to the boreal forest wildfire regime in interior Alaska

USGS Publications Warehouse

Gaglioti, Benjamin V.; Mann, Daniel H.; Jones, Benjamin M.; Wooller, Matthew J.; Finney, Bruce P.

2016-01-01

Stand-replacing wildfires are a keystone disturbance in the boreal forest, and they are becoming more common as the climate warms. Paleo-fire archives from the wildland–urban interface can quantify the prehistoric fire regime and assess how both human land-use and climate change impact ecosystem dynamics. Here, we use a combination of a sedimentary charcoal record preserved in varved lake sediments (annually layered) and fire scars in living trees to document changes in local fire return intervals (FRIs) and regional fire activity over the last 500 years. Ace Lake is within the boreal forest, located near the town of Fairbanks in interior Alaska, which was settled by gold miners in AD 1902. In the 400 years before settlement, fires occurred near the lake on average every 58 years. After settlement, fires became much more frequent (average every 18  years), and background charcoal flux rates rose to four times their preindustrial levels, indicating a region-wide increase in burning. Despite this surge in burning, the preindustrial boreal forest ecosystem and permafrost in the watershed have remained intact. Although fire suppression has reduced charcoal influx since the 1950s, an aging fuel load experiencing increasingly warm summers may pose management problems for this and other boreal sites that have similar land-use and fire histories. The large human-caused fire events that we identify can be used to test how increasingly common megafires may alter ecosystem dynamics in the future.

The Role of Atmospheric Organic Nitrogen in Forest Nitrogen Cycling

NASA Astrophysics Data System (ADS)

Lockwood, A.; Shepson, P.; Rhodes, D.

2003-12-01

Changes in the global climate and atmosphere cause significant effects to the biosphere. Forests respond to these global changes in various ways which all can affect their ability to store carbon, which in turn impacts climate change. Many temperate latitude forests are nitrogen-limited. A current working hypothesis is that atmospheric nitrogen compounds that are deposited to the canopy may be directly utilized by the plant as a nitrogen source. A significant fraction of atmospheric reactive nitrogen that can be deposited is organic. Organic nitrogen deposition is not well characterized nor have the ecological consequences been assessed. Our hypothesis is that organic nitrogen deposition to the canopy is significant, and that that nitrogen is utilized by trees. Fumigation experiments were conducted with 14N and 15N-labeled organic nitrates (focusing on 1-nitrooxy-3-methyl butane as a surrogate for isoprene nitrates) to determine if and how that nitrogen gets incorporated into the leaves by detecting the 15N-labeled leaf amino acids. This research builds on work completed during past summer intensives as part of the Program for Research on Oxidants: PHotochemistry, Emissions, and Transport (PROPHET), and begins the next stage of research as part of the Biosphere Atmosphere Research & Training program (BART) at the University of Michigan Biological Station (UMBS). The overall goal of the new effort, the Biosphere Exchange of Atmospheric Carbon and Odd Nitrogen (BEACON) program, is to evaluate the interactive roles of the atmosphere and forest in the coupling of the carbon and nitrogen cycles.