Simulating spatial and temporal context of forest management using hypothetical landscapes

Treesearch

Eric J. Gustafson; Thomas R. Crow

1998-01-01

Spatially explicit models that combine remote sensing with geographic information systems (GIS) offer great promise to land managers because they consider the arrangement of landscape elements in time and space. Their visual and geographic nature facilitate the comparison of alternative landscape designs. Among various activities associated with forest management,...

Effect of assessment scale on spatial and temporal variations in CH4, C02, and N20 fluxes in a forested wetland

Treesearch

Zhaohua Dai; Carl Trettin; Changsheng Li; Harbin Li; Ge Sun; Devendra Amatya

2011-01-01

Emissions of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) from a forested watershed (160 ha) in South Carolina, USA, were estimated with a spatially explicit watershed-scale modeling framework that utilizes the spatial variations in physical and biogeochemical characteristics across watersheds. The target watershed (WS80) consisting of wetland (23%) and...

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests. Ph.D. Thesis, 10 Sep. 1991 Abstract Only

NASA Technical Reports Server (NTRS)

Bradshaw, G. A.

1995-01-01

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Assessment and Mapping of Forest Parcel Sizes

Treesearch

Brett J. Butler; Susan L. King

2005-01-01

A method for analyzing and mapping forest parcel sizes in the Northeastern United States is presented. A decision tree model was created that predicts forest parcel size from spatially explicit predictor variables: population density, State, percentage forest land cover, and road density. The model correctly predicted parcel size for 60 percent of the observations in a...

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

Regional Assessment of Remote Forests and Black Bear Habitat from Forest Resource Surveys

Treesearch

Victor A. Rudis; John B. Tansey

1995-01-01

We developed a spatially explicit modeling approach, using a county-scaled remote forest (i.e., forested area reserved from or having no direct human interference) assessment derived from 1984-1990 forest resource inventory data and a 1984 black bear (Ursus americantus) range map for 12 states in the southern United States.We defined minimum suitable and optimal black...

Consistency of forest presence and biomass predictions modeled across overlapping spatial and temporal extents

Treesearch

Mark D. Nelson; Sean Healey; W. Keith Moser; J.G. Masek; Warren Cohen

2011-01-01

We assessed the consistency across space and time of spatially explicit models of forest presence and biomass in southern Missouri, USA, for adjacent, partially overlapping satellite image Path/Rows, and for coincident satellite images from the same Path/Row acquired in different years. Such consistency in satellite image-based classification and estimation is critical...

[Application of spatially explicit landscape model in soil loss study in Huzhong area].

PubMed

Xu, Chonggang; Hu, Yuanman; Chang, Yu; Li, Xiuzhen; Bu, Renchang; He, Hongshi; Leng, Wenfang

2004-10-01

Universal Soil Loss Equation (USLE) has been widely used to estimate the average annual soil loss. In most of the previous work on soil loss evaluation on forestland, cover management factor was calculated from the static forest landscape. The advent of spatially explicit forest landscape model in the last decade, which explicitly simulates the forest succession dynamics under natural and anthropogenic disturbances (fire, wind, harvest and so on) on heterogeneous landscape, makes it possible to take into consideration the change of forest cover, and to dynamically simulate the soil loss in different year (e.g. 10 years and 20 years after current year). In this study, we linked a spatially explicit landscape model (LANDIS) with USLE to simulate the soil loss dynamics under two scenarios: fire and no harvest, fire and harvest. We also simulated the soil loss with no fire and no harvest as a control. The results showed that soil loss varied periodically with simulation year, and the amplitude of change was the lowest under the control scenario and the highest under the fire and no harvest scenario. The effect of harvest on soil loss could not be easily identified on the map; however, the cumulative effect of harvest on soil loss was larger than that of fire. Decreasing the harvest area and the percent of bare soil increased by harvest could significantly reduce soil loss, but had no significant effects on the dynamic of soil loss. Although harvest increased the annual soil loss, it tended to decrease the variability of soil loss between different simulation years.

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

Treesearch

J. A. Blackard; M. V. Finco; E. H. Helmer; G. R. Holden; M. L. Hoppus; D.M. Jacobs; A. J. Lister; G. G. Moisen; M. D. Nelson; R. Riemann; B. Ruefenacht; D. Salajanu; D. L. Weyermann; K. C. Winterberger; T. J. Brandeis; R. L. Czaplewski; R. E. McRoberts; P. L. Patterson; R. P. Tymcio

2008-01-01

A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes...

Integrating bird-habitat modeling into national forest planning for bird conservation in the southern Appalachians

Treesearch

David A. Buehler; Eric T. Linder; Kathleen E. Franzreb; Nathan A. Klaus; Randy Dettmers; John G. Bartlett

2005-01-01

We developed spatially-explicit bird-habitat models with a variety of site-specific and landscape parameters to predict avian species distributions on southern Appalachian National Forests to aid National Forests with bird conservation planning. These models can be used to assess the effects of different forest management alternatives on long-term population viability...

Modeling forest site productivity using mapped geospatial attributes within a South Carolina landscape, USA

Treesearch

B.R. Parresol; D.A. Scott; S.J. Zarnoch; L.A. Edwards; J.I. Blake

2017-01-01

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use...

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A.

Treesearch

Janet L. Ohmann; Matthew J. Gregory

2002-01-01

Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to...

Modeling carbon stocks in a secondary tropical dry forest in the Yucatan Peninsula, Mexico

Treesearch

Zhaohua Dai; Richard A. Birdsey; Kristofer D. Johnson; Juan Manuel Dupuy; Jose Luis Hernandez-Stefanoni; Karen Richardson

2014-01-01

The carbon balance of secondary dry tropical forests of Mexico’s Yucatan Peninsula is sensitive to human and natural disturbances and climate change. The spatially explicit process model Forest-DeNitrification-DeComposition (DNDC) was used to estimate forest carbon dynamics in this region, including the effects of disturbance on carbon stocks. Model evaluation using...

Spatial allocation of forest recreation value

Treesearch

Kenneth A. Baerenklau; Armando Gonzalez-Caban; Catrina Paez; Edgard Chavez

2009-01-01

Non-market valuation methods and geographic information systems are useful planning and management tools for public land managers. Recent attention has been given to investigation and demonstration of methods for combining these tools to provide spatially-explicit representations of non-market value. Most of these efforts have focused on spatial allocation of...

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...

Simulating the effects of the southern pine beetle on regional dynamics 60 years into the future

Treesearch

Jennifer K. Costanza; Jiri Hulcr; Frank H. Koch; Todd Earnhardt; Alexa J. McKerrow; Rob R. Dunn; Jaime A. Collazo

2012-01-01

We developed a spatially explicit model that simulated future southern pine beetle (Dendroctonus frontalis, SPB) dynamics and pine forest management for a real landscape over 60 years to inform regional forest management. The SPB has a considerable effect on forest dynamics in the Southeastern United States, especially in loblolly pine (...

Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

Treesearch

Nathan R. De Jager; Patrick J. Drohan; Brian M. Miranda; Brian R. Sturtevant; Susan L. Stout; Alejandro A. Royo; Eric J. Gustafson; Mark C. Romanski

2017-01-01

Browsing ungulates alter forest productivity and vegetation succession through selective foraging onspecies that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit...

Adding uncertainty to forest inventory plot locations: effects on analyses using geospatial data

Treesearch

Alexia A. Sabor; Volker C. Radeloff; Ronald E. McRoberts; Murray Clayton; Susan I. Stewart

2007-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service alters plot locations before releasing data to the public to ensure landowner confidentiality and sample integrity, but using data with altered plot locations in conjunction with other spatially explicit data layers produces analytical results with unknown amounts of error. We calculated the...

Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico

Treesearch

Robert E. Keane; Scott A. Mincemoyer; Kirsten M. Schmidt; Donald G. Long; Janice L. Garner

2000-01-01

(Please note: This PDF is part of a CD-ROM package only and was not printed on paper.) Fuels and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Gila National Forest in New Mexico. Satellite imagery, terrain modeling, and biophysical simulation were used to create the three...

Modeling the impacts of climate variability and hurricane on carbon sequestration in a coastal forested wetland in South Carolina

Treesearch

Zhaohua Dai; Carl C. Trettin; Changsheng Li; Ge Sun; Devendra M. Amatya; Harbin Li

2013-01-01

The impacts of hurricane disturbance and climate variability on carbon dynamics in a coastal forested wetland in South Carolina of USA were simulated using the Forest-DNDC model with a spatially explicit approach. The model was validated using the measured biomass before and after Hurricane Hugo and the biomass inventories in 2006 and 2007, showed that the Forest-DNDC...

Simulated effects of forest management alternatives on landscape structure and habitat suitability in the Midwestern United States

Treesearch

Stephen R. Shifley; Frank R., III Thompson; William D. Dijak; Michael A. Larson; Joshua J. Millspaugh

2006-01-01

Understanding the cumulative effects and resource trade-offs associated with forest management requires the ability to predict, analyze, and communicate information about how forest landscapes (1000s to > 100,000 ha in extent) respond to silviculture and other disturbances. We applied a spatially explicit landscape simulation model, LANDIS, and compared the outcomes...

Can landscape-level ecological restoration influence fire risk? A spatially-explicit assessment of a northern temperate-southern boreal forest landscape

Treesearch

Douglas J. Shinneman; Brian J. Palik; Meredith W. Cornett

2012-01-01

Management strategies to restore forest landscapes are often designed to concurrently reduce fire risk. However, the compatibility of these two objectives is not always clear, and uncoordinated management among landowners may have unintended consequences. We used a forest landscape simulation model to compare the effects of contemporary management and hypothetical...

A spatially explicit decision support model for restoration of forest bird habitat

USGS Publications Warehouse

Twedt, D.J.; Uihlein, W.B.; Elliott, A.B.

2006-01-01

The historical area of bottomland hardwood forest in the Mississippi Alluvial Valley has been reduced by >75%. Agricultural production was the primary motivator for deforestation; hence, clearing deliberately targeted higher and drier sites. Remaining forests are highly fragmented and hydrologically altered, with larger forest fragments subject to greater inundation, which has negatively affected many forest bird populations. We developed a spatially explicit decision support model, based on a Partners in Flight plan for forest bird conservation, that prioritizes forest restoration to reduce forest fragmentation and increase the area of forest core (interior forest >1 km from 'hostile' edge). Our primary objective was to increase the number of forest patches that harbor >2000 ha of forest core, but we also sought to increase the number and area of forest cores >5000 ha. Concurrently, we targeted restoration within local (320 km2) landscapes to achieve >60% forest cover. Finally, we emphasized restoration of higher-elevation bottomland hardwood forests in areas where restoration would not increase forest fragmentation. Reforestation of 10% of restorable land in the Mississippi Alluvial Valley (approximately 880,000 ha) targeted at priorities established by this decision support model resulted in approximately 824,000 ha of new forest core. This is more than 32 times the amount of core forest added through reforestation of randomly located fields (approximately 25,000 ha). The total area of forest core (1.6 million ha) that resulted from targeted restoration exceeded habitat objectives identified in the Partners in Flight Bird Conservation Plan and approached the area of forest core present in the 1950s.

Measurement of forest disturbance and regrowth with Landsat and forest inventory and analysis data: anticipated benefits from forest and inventory analysis' collaboration with the national aeronautics and space administration and university partners

Treesearch

Sean Healey; Gretchen Moisen; Jeff Masek; Warren Cohen; Sam Goward; < i> et al< /i>

2007-01-01

The Forest Inventory and Analysis (FIA) program has partnered with researchers from the National Aeronautics and Space Administration, the University of Maryland, and other U.S. Department of Agriculture Forest Service units to identify disturbance patterns across the United States using FIA plot data and time series of Landsat satellite images. Spatially explicit...

Spatial Bayesian belief networks as a planning decision tool for mapping ecosystem services trade-offs on forested landscapes.

PubMed

Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro

2016-01-01

An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Use of Forest Inventory and Analysis information in wildlife habitat modeling: a process for linking multiple scales

Treesearch

Thomas C. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Joshua L. Lawler

2002-01-01

We describe our collective efforts to develop and apply methods for using FIA data to model forest resources and wildlife habitat. Our work demonstrates how flexible regression techniques, such as generalized additive models, can be linked with spatially explicit environmental information for the mapping of forest type and structure. We illustrate how these maps of...

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Treesearch

Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

2010-01-01

Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

Quantifying early-seral forest composition with remote sensing

Treesearch

Rayma A. Cooley; Peter T. Wolter; Brian R. Sturtevant

2016-01-01

Spatially explicit modeling of recovering forest structure within two years following wildfire disturbance has not been attempted, yet such knowledge is critical for determining successional pathways. We used remote sensing and field data, along with digital climate and terrain data, to model and map early-seral aspen structure and vegetation species richness following...

Integrated modeling of long-term vegetation and hydrologic dynamics in Rocky Mountain watersheds

Treesearch

Robert Steven Ahl

2007-01-01

Changes in forest structure resulting from natural disturbances, or managed treatments, can have negative and long lasting impacts on water resources. To facilitate integrated management of forest and water resources, a System for Long-Term Integrated Management Modeling (SLIMM) was developed. By combining two spatially explicit, continuous time models, vegetation...

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.

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

PubMed

Pos, Edwin; Guevara Andino, Juan Ernesto; Sabatier, Daniel; Molino, Jean-François; Pitman, Nigel; Mogollón, Hugo; Neill, David; Cerón, Carlos; Rivas-Torres, Gonzalo; Di Fiore, Anthony; Thomas, Raquel; Tirado, Milton; Young, Kenneth R; Wang, Ophelia; Sierra, Rodrigo; García-Villacorta, Roosevelt; Zagt, Roderick; Palacios Cuenca, Walter; Aulestia, Milton; Ter Steege, Hans

2017-06-01

With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large-scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi-explicit simulations based on three large-scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi-explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi-explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)-neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

PubMed Central

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. PMID:24489686

Mapping Fuels on the Okanogan and Wenatchee National Forests

Treesearch

Crystal L. Raymond; Lara-Karena B. Kellogg; Donald McKenzie

2006-01-01

Resource managers need spatially explicit fuels data to manage fire hazard and evaluate the ecological effects of wildland fires and fuel treatments. For this study, fuels were mapped on the Okanogan and Wenatchee National Forests (OWNF) using a rule-based method and the Fuels Characteristic Classification System (FCCS). The FCCS classifies fuels based on their...

Utilizing inventory information to calibrate a landscape simulation model

Treesearch

Steven R. Shifley; Frank R., III Thompson; David R. Larsen; David J. Mladenoff; Eric J. Gustafson

2000-01-01

LANDIS is a spatially explicit model that uses mapped landscape conditions as a starting point and projects the patterns in forest vegetation that will result from alternative harvest practices, alternative fire regimes, and wind events. LANDIS was originally developed for Lake States forests, but it is capable of handling the input, output, bookkeeping, and mapping...

Validation of solar radiation surfaces from MODIS and reanalysis data over topographically complex terrain

Treesearch

Todd A. Schroeder; Robbie Hember; Nicholas C. Coops; Shunlin Liang

2009-01-01

The magnitude and distribution of incoming shortwave solar radiation (SW) has significant influence on the productive capacity of forest vegetation. Models that estimate forest productivity require accurate and spatially explicit radiation surfaces that resolve both long- and short-term temporal climatic patterns and that account for topographic variability of the land...

Model forest landscape change in the Missouri Ozarks under alternative management practices

Treesearch

Stephen R. Shifley; Frank R. Thompson; David R. Larsen; William D. Dijak

2000-01-01

We used a spatially explicit landscape model, LANDIS, to simulate the effects of five management alternatives on a 3216 ha forest landscape in southeast Missouri, USA. We compared management alternatives among two intensities of even-aged management with clearcutting, uneven-aged management with group selection harvest, a mixture of even- and uneven-aged management,...

Proximal Association of Land Management Preferences: Evidence from Family Forest Owners

PubMed Central

Aguilar, Francisco X.; Cai, Zhen; Butler, Brett

2017-01-01

Individual behavior is influenced by factors intrinsic to the decision-maker but also associated with other individuals and their ownerships with such relationship intensified by geographic proximity. The land management literature is scarce in the spatially integrated analysis of biophysical and socio-economic data. Localized land management decisions are likely driven by spatially-explicit but often unobserved resource conditions, influenced by an individual’s own characteristics, proximal lands and fellow owners. This study examined stated choices over the management of family-owned forests as an example of a resource that captures strong pecuniary and non-pecuniary values with identifiable decision makers. An autoregressive model controlled for spatially autocorrelated willingness-to-harvest (WTH) responses using a sample of residential and absentee family forest owners from the U.S. State of Missouri. WTH responses were largely explained by affective, cognitive and experience variables including timber production objectives and past harvest experience. Demographic variables, including income and age, were associated with WTH and helped define socially-proximal groups. The group of closest identity was comprised of resident males over 55 years of age with annual income of at least $50,000. Spatially-explicit models showed that indirect impacts, capturing spillover associations, on average accounted for 14% of total marginal impacts among statistically significant explanatory variables. We argue that not all proximal family forest owners are equal and owners-in-absentia have discernible differences in WTH preferences with important implications for public policy and future research. PMID:28060960

Carbon sequestration and water flow regulation services in mature Mediterranean Forest

NASA Astrophysics Data System (ADS)

Beguería, S.; Ovando, P.

2015-12-01

We develop a forestland use and management model that integrates spatially-explicit biophysical and economic data, to estimate the expected pattern of climate regulation services through carbon dioxide (CO2) sequestration in tree and shrubs biomass, and water flow regulation. We apply this model to examine the potential trade-offs and synergies in the supply of CO2 sequestration and water flow services in mature Mediterranean forest, considering two alternative forest management settings. A forest restoration scenario through investments in facilitating forest regeneration, and a forestry activity abandonment scenario as result of unprofitable forest regeneration investment. The analysis is performed for different discount rates and price settings for carbon and water. The model is applied at the farm level in a group of 567 private silvopastoral farms across Andalusia (Spain), considering the main forest species in this region: Quercus ilex, Q. suber, Pinus pinea, P. halepensis, P. pinaster and Eucalyptus sp., as well as for tree-less shrubland and pastures. The results of this research are provided by forest land unit, vegetation, farm and for the group of municipalities where the farms are located. Our results draw attention to the spatial variability of CO2 and water flow regulation services, and point towards a trade-off between those services. The pattern of economic benefits associated to water and carbon services fluctuates according to the assumptions regarding price levels and discounting rates, as well as in connection to the expected forest management and tree growth models, and to spatially-explicit forest attributes such as existing tree and shrubs inventories, the quality of the sites for growing different tree species, soil structure or the climatic characteristics. The assumptions made regarding the inter-temporal preferences and relative prices have a large effect on the estimated economic value of carbon and water services. These results highlight the uncertainties over the provision of forest ecosistem services under changing economic conditions and social preferences.

Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data

Treesearch

Chad Babcock; Andrew O. Finley; Bruce D. Cook; Aaron Weiskittel; Christopher W. Woodall

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB...

Landscape Builder: software for the creation of initial landscapes for LANDIS from FIA data

Treesearch

William Dijak

2013-01-01

I developed Landscape Builder to create spatially explicit landscapes as starting conditions for LANDIS Pro 7.0 and LANDIS II landscape forest simulation models from classified satellite imagery and Forest Inventory and Analysis (FIA) data collected over multiple years. LANDIS Pro and LANDIS II models project future landscapes by simulating tree growth, tree species...

Anticipating forest and range land development in central Oregon (USA) for landscape analysis, with an example application involving mule deer

Treesearch

Jeffrey D. Kline; Alissa Moses; Theresa Burcsu

2010-01-01

Forest policymakers, public lands managers, and scientists in the Pacific Northwest (USA) seek ways to evaluate the landscape-level effects of policies and management through the multidisciplinary development and application of spatially explicit methods and models. The Interagency Mapping and Analysis Project (IMAP) is an ongoing effort to generate landscape-wide...

Influence of soil thickness on stand characteristics in a Sierra Nevada mixed-conifer forest

Treesearch

Marc D. Meyer; Malcolm P. North; Andrew N. Gray; Harold S. J. Zald

2007-01-01

Soil thickness can be an important factor influencing vegetation, yet few spatially explicit studies have examined soil horizon thickness and vegetation composition in summer drought forests. We compared seismic and soil penetration measurements of combined A + C and Cr horizon thickness, soil moisture and temperature, and stand variables in a contiguous 4-ha mixed-...

Global spatially explicit CO2 emission metrics at 0.25° horizontal resolution for forest bioenergy

NASA Astrophysics Data System (ADS)

Cherubini, F.

2015-12-01

Bioenergy is the most important renewable energy option in studies designed to align with future RCP projections, reaching approximately 250 EJ/yr in RCP2.6, 145 EJ/yr in RCP4.5 and 180 EJ/yr in RCP8.5 by the end of the 21st century. However, many questions enveloping the direct carbon cycle and climate response to bioenergy remain partially unexplored. Bioenergy systems are largely assessed under the default climate neutrality assumption and the time lag between CO2 emissions from biomass combustion and CO2 uptake by vegetation is usually ignored. Emission metrics of CO2 from forest bioenergy are only available on a case-specific basis and their quantification requires processing of a wide spectrum of modelled or observed local climate and forest conditions. On the other hand, emission metrics are widely used to aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.), but a spatially explicit analysis of emission metrics with global forest coverage is today lacking. Examples of emission metrics include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Here, we couple a global forest model, a heterotrophic respiration model, and a global climate model to produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy. We show their applications to global emissions in 2015 and until 2100 under the different RCP scenarios. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2-1 (mean ± standard deviation), 0.05 ± 0.05 kgCO2-eq. kgCO2-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1 for GWP, GTP and aSET, respectively. We also present results aggregated at a grid, national and continental level. The metrics are found to correlate with the site-specific turnover times and local climate variables like annual mean temperature and precipitation. Simplified equations are derived to infer metric values from the turnover time of the biomass feedstock and the fraction of forest residues left on site after harvest. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

PubMed

Bustamante, Mercedes M C; Roitman, Iris; Aide, T Mitchell; Alencar, Ane; Anderson, Liana O; Aragão, Luiz; Asner, Gregory P; Barlow, Jos; Berenguer, Erika; Chambers, Jeffrey; Costa, Marcos H; Fanin, Thierry; Ferreira, Laerte G; Ferreira, Joice; Keller, Michael; Magnusson, William E; Morales-Barquero, Lucia; Morton, Douglas; Ometto, Jean P H B; Palace, Michael; Peres, Carlos A; Silvério, Divino; Trumbore, Susan; Vieira, Ima C G

2016-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation. © 2015 John Wiley & Sons Ltd.

An analysis of the relationship between drought events and mangrove changes along the northern coasts of the Pe rsian Gulf and Oman Sea

NASA Astrophysics Data System (ADS)

Mafi-Gholami, Davood; Mahmoudi, Beytollah; Zenner, Eric K.

2017-12-01

Relating the changes of mangrove forests to spatially explicit reductions in rainfall amounts and increases in drought occurrences is a prerequisite for improving the effectiveness and success of mangrove forest conservation programs. To this end, we investigated the relationship between drought events (quantified using the Standardized Precipitation Index [SPI]) and changes in area and canopy cover of mangrove forests on the northern coast of the Persian Gulf and the Oman Sea using satellite imagery and long-term annual rainfall data over a period of 30 years (1986-2016). Statistical analyses revealed 1998 as the year marking the most significant change-point in the mean annual rainfall values in the catchments and mangroves, after which average SPI values consistently remained at lower levels. In the period of 1998-2016, decreases in the mean annual rainfall and increases in the severity of droughts differed spatially and were greater in the catchments and mangroves on the coasts of the Oman Sea than the coasts of the Persian Gulf. These spatially explicit results were closely mirrored by the mangrove response, with differential in reductions in mangrove areas and canopy cover that corresponded closely with the spatial distribution of drought intensities in the different parts of the coasts, with correlation coefficients ≥0.89 for the different coastal regions.

How effective are biodiversity conservation payments in Mexico?

PubMed

Costedoat, Sébastien; Corbera, Esteve; Ezzine-de-Blas, Driss; Honey-Rosés, Jordi; Baylis, Kathy; Castillo-Santiago, Miguel Angel

2015-01-01

We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled.

Ecosystem accounts define explicit and spatial trade-offs for managing natural resources.

PubMed

Keith, Heather; Vardon, Michael; Stein, John A; Stein, Janet L; Lindenmayer, David

2017-11-01

Decisions about natural resource management are frequently complex and vexed, often leading to public policy compromises. Discord between environmental and economic metrics creates problems in assessing trade-offs between different current or potential resource uses. Ecosystem accounts, which quantify ecosystems and their benefits for human well-being consistent with national economic accounts, provide exciting opportunities to contribute significantly to the policy process. We advanced the application of ecosystem accounts in a regional case study by explicitly and spatially linking impacts of human and natural activities on ecosystem assets and services to their associated industries. This demonstrated contributions of ecosystems beyond the traditional national accounts. Our results revealed that native forests would provide greater benefits from their ecosystem services of carbon sequestration, water yield, habitat provisioning and recreational amenity if harvesting for timber production ceased, thus allowing forests to continue growing to older ages.

Assessing Potential Future Carbon Dynamics with Climate Change and Fire Management in a Mountainous Landscape on the Olympic Peninsula, Washington, USA

NASA Astrophysics Data System (ADS)

Kennedy, R. S.

2010-12-01

Forests of the mountainous landscapes of the maritime Pacific Northwestern USA may have high carbon sequestration potential via their high productivity and moderate to infrequent fire regimes. With climate change, there may be shifts in incidence and severity of fire, especially in the drier areas of the region, via changes to forest productivity and hydrology, and consequent effects to C sequestration and forest structure. To explore this issue, I assessed potential effects of fire management (little fire suppression/wildland fire management/highly effective fire suppression) under two climate change scenarios on future C sequestration dynamics (amounts and spatial pattern) in Olympic National Park, WA, over a 500-year simulation period. I used the simulation platform FireBGCv2, which contains a mechanistic, individual tree succession model, a spatially explicit climate-based biophysical model that uses daily weather data, and a spatially explicit fire model incorporating ignition, spread, and effects on ecosystem components. C sequestration patterns varied over time and spatial and temporal patterns differed somewhat depending on the climate change scenario applied and the fire management methods employed. Under the more extreme climate change scenario with little fire suppression, fires were most frequent and severe and C sequestration decreased. General trends were similar under the more moderate climate change scenario, as compared to current climate, but spatial patterns differed. Both climate change scenarios under highly effective fire suppression showed about 50% of starting total C after the initial transition phase, whereas with 10% fire suppression both scenarios exhibited about 10% of starting amounts. Areas of the landscape that served as refugia for older forest under increasing frequency of high severity fire were also hotspots for C sequestration in a landscape experiencing increasing frequency of disturbance with climate change.

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

DOE PAGES

Parresol, B. R.; Scott, D. A.; Zarnoch, S. J.; ...

2017-12-15

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land usemore » in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).« less

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

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

Parresol, B. R.; Scott, D. A.; Zarnoch, S. J.

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land usemore » in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).« less

Estimating the population density of the Asian tapir (Tapirus indicus) in a selectively logged forest in Peninsular Malaysia.

PubMed

Rayan, D Mark; Mohamad, Shariff Wan; Dorward, Leejiah; Aziz, Sheema Abdul; Clements, Gopalasamy Reuben; Christopher, Wong Chai Thiam; Traeholt, Carl; Magintan, David

2012-12-01

The endangered Asian tapir (Tapirus indicus) is threatened by large-scale habitat loss, forest fragmentation and increased hunting pressure. Conservation planning for this species, however, is hampered by a severe paucity of information on its ecology and population status. We present the first Asian tapir population density estimate from a camera trapping study targeting tigers in a selectively logged forest within Peninsular Malaysia using a spatially explicit capture-recapture maximum likelihood based framework. With a trap effort of 2496 nights, 17 individuals were identified corresponding to a density (standard error) estimate of 9.49 (2.55) adult tapirs/100 km(2) . Although our results include several caveats, we believe that our density estimate still serves as an important baseline to facilitate the monitoring of tapir population trends in Peninsular Malaysia. Our study also highlights the potential of extracting vital ecological and population information for other cryptic individually identifiable animals from tiger-centric studies, especially with the use of a spatially explicit capture-recapture maximum likelihood based framework. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

A method for landscape analysis of forestry guidelines using bird habitat models and the Habplan harvest scheduler

USGS Publications Warehouse

Loehle, C.; Van Deusen, P.; Wigley, T.B.; Mitchell, M.S.; Rutzmoser, S.H.; Aggett, J.; Beebe, J.A.; Smith, M.L.

2006-01-01

Wildlife-habitat relationship models have sometimes been linked with forest simulators to aid in evaluating outcomes of forest management alternatives. However, linking wildlife-habitat models with harvest scheduling software would provide a more direct method for assessing economic and ecological implications of alternative harvest schedules in commercial forest operations. We demonstrate an approach for frontier analyses of wildlife benefits using the Habplan harvest scheduler and spatially explicit wildlife response models in the context of operational forest planning. We used the Habplan harvest scheduler to plan commercial forest management over a 40-year horizon at a landscape scale under five scenarios: unmanaged, an unlimited block-size option both with and without riparian buffers, three cases with different block-size restrictions, and a set-asides scenario in which older stands were withheld from cutting. The potential benefit to wildlife was projected based on spatial models of bird guild richness and species probability of detection. Harvested wood volume provided a measure of scenario costs, which provides an indication of management feasibility. Of nine species and guilds, none appeared to benefit from 50 m riparian buffers, response to an unmanaged scenario was mixed and expensive, and block-size restrictions (maximum harvest unit size) provided no apparent benefit and in some cases were possibly detrimental to bird richness. A set-aside regime, however, appeared to provide significant benefits to all species and groups, probably through increased landscape heterogeneity and increased availability of older forest. Our approach shows promise for evaluating costs and benefits of forest management guidelines in commercial forest enterprises and improves upon the state of the art by utilizing an optimizing harvest scheduler as in commercial forest management, multiple measures of biodiversity (models for multiple species and guilds), and spatially explicit wildlife response models. ?? 2006 Elsevier B.V. All rights reserved.

Forest landscapes: Their effect on the interaction of the southern pine beetle and red-cockaded woodpecker

Treesearch

Robert N. Coulson; Maria D. Guzman; Karen Skordinski; Jeffrey W. Fitzgerald; Richard N. Conner; D. Craig Rudolph; Forrest L. Oliveria; Douglas F. Wunneburger; Paul E. Pulley

1999-01-01

The nature of the interaction of the southern pine beetle and red-cockaded woodpecker was investidgated using spatially explicit information on the structure of a forest landscape mosiac and knowledge of the behavior of the two organisms. This interaction is the basis for defind functional heterogeneity - how an organism perceives and responds to the elements forming...

Upscaling of Solar Induced Chlorophyll Fluorescence from Leaf to Canopy Using the Dart Model and a Realistic 3d Forest Scene

NASA Astrophysics Data System (ADS)

Liu, W.; Atherton, J.; Mõttus, M.; MacArthur, A.; Teemu, H.; Maseyk, K.; Robinson, I.; Honkavaara, E.; Porcar-Castell, A.

2017-10-01

Solar induced chlorophyll a fluorescence (SIF) has been shown to be an excellent proxy of photosynthesis at multiple scales. However, the mechanical linkages between fluorescence and photosynthesis at the leaf level cannot be directly applied at canopy or field scales, as the larger scale SIF emission depends on canopy structure. This is especially true for the forest canopies characterized by high horizontal and vertical heterogeneity. While most of the current studies on SIF radiative transfer in plant canopies are based on the assumption of a homogeneous canopy, recently codes have been developed capable of simulation of fluorescence signal in explicit 3-D forest canopies. Here we present a canopy SIF upscaling method consisting of the integration of the 3-D radiative transfer model DART and a 3-D object model BLENDER. Our aim was to better understand the effect of boreal forest canopy structure on SIF for a spatially explicit forest canopy.

Environmental drivers of spatial variation in whole-tree transpiration in an aspen-dominated upland-to-wetland forest gradient

NASA Astrophysics Data System (ADS)

Loranty, Michael M.; Mackay, D. Scott; Ewers, Brent E.; Adelman, Jonathan D.; Kruger, Eric L.

2008-02-01

Assumed representative center-of-stand measurements are typical inputs to models that scale forest transpiration to stand and regional extents. These inputs do not consider gradients in transpiration at stand boundaries or along moisture gradients and therefore potentially bias the large-scale estimates. We measured half-hourly sap flux (JS) for 173 trees in a spatially explicit cyclic sampling design across a topographically controlled gradient between a forested wetland and upland forest in northern Wisconsin. Our analyses focused on three dominant species in the site: quaking aspen (Populus tremuloides Michx), speckled alder (Alnus incana (DuRoi) Spreng), and white cedar (Thuja occidentalis L.). Sapwood area (AS) was used to scale JS to whole tree transpiration (EC). Because spatial patterns imply underlying processes, geostatistical analyses were employed to quantify patterns of spatial autocorrelation across the site. A simple Jarvis type model parameterized using a Monte Carlo sampling approach was used to simulate EC (EC-SIM). EC-SIM was compared with observed EC(EC-OBS) and found to reproduce both the temporal trends and spatial variance of canopy transpiration. EC-SIM was then used to examine spatial autocorrelation as a function of environmental drivers. We found no spatial autocorrelation in JS across the gradient from forested wetland to forested upland. EC was spatially autocorrelated and this was attributed to spatial variation in AS which suggests species spatial patterns are important for understanding spatial estimates of transpiration. However, the range of autocorrelation in EC-SIM decreased linearly with increasing vapor pressure deficit, implying that consideration of spatial variation in the sensitivity of canopy stomatal conductance to D is also key to accurately scaling up transpiration in space.

Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system

Treesearch

Robert A. Riggs; Robert E. Keane; Norm Cimon; Rachel Cook; Lisa Holsinger; John Cook; Timothy DelCurto; L.Scott Baggett; Donald Justice; David Powell; Martin Vavra; Bridgett Naylor

2015-01-01

Landscape fire succession models (LFSMs) predict spatially-explicit interactions between vegetation succession and disturbance, but these models have yet to fully integrate ungulate herbivory as a driver of their processes. We modified a complex LFSM, FireBGCv2, to include a multi-species herbivory module, GrazeBGC. The system is novel in that it explicitly...

Spatially and seasonally asymmetric responses of Amazon forests to El Niño

NASA Astrophysics Data System (ADS)

Mao, J.; Yan, B.; Dickinson, R. E.; Shi, X.; Ricciuto, D. M.; Norby, R. J.; Dai, Y.; Zhang, X.; McDowell, N.; Wu, J.

2017-12-01

El Niño Southern Oscillation (ENSO) events impose strong inter-annual signals on local climate changes and terrestrial ecosystem dynamics in many regions on the Earth especially tropical forests in the Amazon basin. However, much is still unknown regarding the vulnerability of tropical forests to ENSO effects, especially in a spatially-explicit context. Here, using satellite and ground observations with reanalysis data of climate variables, we analyzed the spatial and temporal patterns of plant growth in response to the warm phase of ENSO (i.e., El Niño), which resulted in precipitation anomaly (or drought) over a large area across the Amazon. We found that the influence of El Niño events on vegetation growth varied spatially and seasonally. During each season (dry or wet), the forests were divided into two sub-regions that were either controlled by precipitation or radiation. The boundaries between the two sub-regions were determined, which were distributed from northwest to southeast in the dry season and from northeast to southwest in the wet season. This result improves our understanding of the water and energy availability co-modulating the vegetation growth in Amazonia and the magnitude and direction of Amazon forests responding to drought.

Oak decline in the Boston Mountains, Arkansas, USA: Spatial and temporal patterns under two fire regimes

Treesearch

Martin A. Spetich; Hong S. He

2008-01-01

A spatially explicit forest succession and disturbance model is used to delineate the extent and dispersion of oak decline under two fire regimes over a 150-year period. The objectives of this study are to delineate potential current and future oak decline areas using species composition and age structure data in combination with ecological land types, and to...

An application of Social Values for Ecosystem Services (SolVES) to three national forests in Colorado and Wyoming

USGS Publications Warehouse

Sherrouse, Benson C.; Semmens, Darius J.; Clement, Jessica M.

2014-01-01

Despite widespread recognition that social-value information is needed to inform stakeholders and decision makers regarding trade-offs in environmental management, it too often remains absent from ecosystem service assessments. Although quantitative indicators of social values need to be explicitly accounted for in the decision-making process, they need not be monetary. Ongoing efforts to map such values demonstrate how they can also be made spatially explicit and relatable to underlying ecological information. We originally developed Social Values for Ecosystem Services (SolVES) as a tool to assess, map, and quantify nonmarket values perceived by various groups of ecosystem stakeholders. With SolVES 2.0 we have extended the functionality by integrating SolVES with Maxent maximum entropy modeling software to generate more complete social-value maps from available value and preference survey data and to produce more robust models describing the relationship between social values and ecosystems. The current study has two objectives: (1) evaluate how effectively the value index, a quantitative, nonmonetary social-value indicator calculated by SolVES, reproduces results from more common statistical methods of social-survey data analysis and (2) examine how the spatial results produced by SolVES provide additional information that could be used by managers and stakeholders to better understand more complex relationships among stakeholder values, attitudes, and preferences. To achieve these objectives, we applied SolVES to value and preference survey data collected for three national forests, the Pike and San Isabel in Colorado and the Bridger–Teton and the Shoshone in Wyoming. Value index results were generally consistent with results found through more common statistical analyses of the survey data such as frequency, discriminant function, and correlation analyses. In addition, spatial analysis of the social-value maps produced by SolVES provided information that was useful for explaining relationships between stakeholder values and forest uses. Our results suggest that SolVES can effectively reproduce information derived from traditional statistical analyses while adding spatially explicit, social-value information that can contribute to integrated resource assessment, planning, and management of forests and other ecosystems.

Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

NASA Astrophysics Data System (ADS)

Poyatos, Rafael; Sus, Oliver; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2018-05-01

The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in the IEFC incomplete dataset (5495 plots) and quantify imputation uncertainty. Resulting spatial patterns of the studied traits in Catalan forests were broadly similar when using species means, regression kriging or the best-performing MICE application, but some important discrepancies were observed at the local level. Our results highlight the need to assess imputation quality beyond just imputation accuracy and show that including environmental information in statistical imputation approaches yields more plausible imputations in spatially explicit plant trait datasets.

Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds

USGS Publications Warehouse

Brown, Michelle L.; Donovan, Therese; Schwenk, W. Scott; Theobald, David M.

2014-01-01

Forest loss and fragmentation are among the largest threats to forest-dwelling wildlife species today, and projected increases in human population growth are expected to increase these threats in the next century. We combined spatially-explicit growth models with wildlife distribution models to predict the effects of human development on 5 forest-dependent bird species in Vermont, New Hampshire, and Massachusetts, USA. We used single-species occupancy models to derive the probability of occupancy for each species across the study area in the years 2000 and 2050. Over half a million new housing units were predicted to be added to the landscape. The maximum change in housing density was nearly 30 houses per hectare; however, 30% of the towns in the study area were projected to add less than 1 housing unit per hectare. In the face of predicted human growth, the overall occupancy of each species decreased by as much as 38% (ranging from 19% to 38% declines in the worst-case scenario) in the year 2050. These declines were greater outside of protected areas than within protected lands. Ninety-seven percent of towns experienced some decline in species occupancy within their borders, highlighting the value of spatially-explicit models. The mean decrease in occupancy probability within towns ranged from 3% for hairy woodpecker to 8% for ovenbird and hermit thrush. Reductions in occupancy probability occurred on the perimeters of cities and towns where exurban development is predicted to increase in the study area. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and forest-dependent wildlife species.

Comparing effects of climate warming, fire, and timber harvesting on a boreal forest landscape in northeastern China.

PubMed

Li, Xiaona; He, Hong S; Wu, Zhiwei; Liang, Yu; Schneiderman, Jeffrey E

2013-01-01

Forest management under a changing climate requires assessing the effects of climate warming and disturbance on the composition, age structure, and spatial patterns of tree species. We investigated these effects on a boreal forest in northeastern China using a factorial experimental design and simulation modeling. We used a spatially explicit forest landscape model (LANDIS) to evaluate the effects of three independent variables: climate (current and expected future), fire regime (current and increased fire), and timber harvesting (no harvest and legal harvest). Simulations indicate that this forested landscape would be significantly impacted under a changing climate. Climate warming would significantly increase the abundance of most trees, especially broadleaf species (aspen, poplar, and willow). However, climate warming would have less impact on the abundance of conifers, diversity of forest age structure, and variation in spatial landscape structure than burning and harvesting. Burning was the predominant influence in the abundance of conifers except larch and the abundance of trees in mid-stage. Harvesting impacts were greatest for the abundance of larch and birch, and the abundance of trees during establishment stage (1-40 years), early stage (41-80 years) and old- growth stage (>180 years). Disturbance by timber harvesting and burning may significantly alter forest ecosystem dynamics by increasing forest fragmentation and decreasing forest diversity. Results from the simulations provide insight into the long term management of this boreal forest.

How Effective Are Biodiversity Conservation Payments in Mexico?

PubMed Central

Costedoat, Sébastien; Corbera, Esteve; Ezzine-de-Blas, Driss; Honey-Rosés, Jordi; Baylis, Kathy; Castillo-Santiago, Miguel Angel

2015-01-01

We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled. PMID:25807118

Spatially explicit estimates of forest carbon emissions, mitigation costs and REDD+ opportunities in Indonesia

NASA Astrophysics Data System (ADS)

Graham, Victoria; Laurance, Susan G.; Grech, Alana; Venter, Oscar

2017-04-01

Carbon emissions from the conversion and degradation of tropical forests contribute to anthropogenic climate change. Implementing programs to reduce emissions from tropical forest loss in Southeast Asia are perceived to be expensive due to high opportunity costs of avoided deforestation. However, these costs are not representative of all REDD+ opportunities as they are typically based on average costs across large land areas and are primarily for reducing deforestation from oil palm or pulp concessions. As mitigation costs and carbon benefits can vary according to site characteristics, spatially-explicit information should be used to assess cost-effectiveness and to guide the allocation of scarce REDD+ resources. We analyzed the cost-effectiveness of the following REDD+ strategies in Indonesia, one of the world’s largest sources of carbon emissions from deforestation: halting additional deforestation in protected areas, timber and oil palm concessions, reforesting degraded land and employing reduced-impact logging techniques in logging concessions. We discover that when spatial variation in costs and benefits is considered, low-cost options emerged even for the two most expensive strategies: protecting forests from conversion to oil palm and timber plantations. To achieve a low emissions reduction target of 25%, we suggest funding should target deforestation in protected areas, and oil palm and timber concessions to maximize emissions reductions at the lowest cumulative cost. Low-cost opportunities for reducing emissions from oil palm are where concessions have been granted on deep peat deposits or unproductive land. To achieve a high emissions reduction target of 75%, funding is allocated across all strategies, emphasizing that no single strategy can reduce emissions cost-effectively across all of Indonesia. These findings demonstrate that by using a spatially-targeted approach to identify high priority locations for reducing emissions from deforestation and forest degradation, REDD+ resources can be allocated cost-effectively across Indonesia.

Modeling animal movements using stochastic differential equations

Treesearch

Haiganoush K. Preisler; Alan A. Ager; Bruce K. Johnson; John G. Kie

2004-01-01

We describe the use of bivariate stochastic differential equations (SDE) for modeling movements of 216 radiocollared female Rocky Mountain elk at the Starkey Experimental Forest and Range in northeastern Oregon. Spatially and temporally explicit vector fields were estimated using approximating difference equations and nonparametric regression techniques. Estimated...

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Fire in the Brazilian Amazon: A Spatially Explicit Model for Policy Impact Analysis

NASA Technical Reports Server (NTRS)

Arima, Eugenio Y.; Simmons, Cynthia S.; Walker, Robert T.; Cochrane, Mark A.

2007-01-01

This article implements a spatially explicit model to estimate the probability of forest and agricultural fires in the Brazilian Amazon. We innovate by using variables that reflect farmgate prices of beef and soy, and also provide a conceptual model of managed and unmanaged fires in order to simulate the impact of road paving, cattle exports, and conservation area designation on the occurrence of fire. Our analysis shows that fire is positively correlated with the price of beef and soy, and that the creation of new conservation units may offset the negative environmental impacts caused by the increasing number of fire events associated with early stages of frontier development.

Ecosystem Services and Opportunity Costs Shift Spatial Priorities for Conserving Forest Biodiversity

PubMed Central

Schröter, Matthias; Rusch, Graciela M.; Barton, David N.; Blumentrath, Stefan; Nordén, Björn

2014-01-01

Inclusion of spatially explicit information on ecosystem services in conservation planning is a fairly new practice. This study analyses how the incorporation of ecosystem services as conservation features can affect conservation of forest biodiversity and how different opportunity cost constraints can change spatial priorities for conservation. We created spatially explicit cost-effective conservation scenarios for 59 forest biodiversity features and five ecosystem services in the county of Telemark (Norway) with the help of the heuristic optimisation planning software, Marxan with Zones. We combined a mix of conservation instruments where forestry is either completely (non-use zone) or partially restricted (partial use zone). Opportunity costs were measured in terms of foregone timber harvest, an important provisioning service in Telemark. Including a number of ecosystem services shifted priority conservation sites compared to a case where only biodiversity was considered, and increased the area of both the partial (+36.2%) and the non-use zone (+3.2%). Furthermore, opportunity costs increased (+6.6%), which suggests that ecosystem services may not be a side-benefit of biodiversity conservation in this area. Opportunity cost levels were systematically changed to analyse their effect on spatial conservation priorities. Conservation of biodiversity and ecosystem services trades off against timber harvest. Currently designated nature reserves and landscape protection areas achieve a very low proportion (9.1%) of the conservation targets we set in our scenario, which illustrates the high importance given to timber production at present. A trade-off curve indicated that large marginal increases in conservation target achievement are possible when the budget for conservation is increased. Forty percent of the maximum hypothetical opportunity costs would yield an average conservation target achievement of 79%. PMID:25393951

Ecosystem services and opportunity costs shift spatial priorities for conserving forest biodiversity.

PubMed

Schröter, Matthias; Rusch, Graciela M; Barton, David N; Blumentrath, Stefan; Nordén, Björn

2014-01-01

Inclusion of spatially explicit information on ecosystem services in conservation planning is a fairly new practice. This study analyses how the incorporation of ecosystem services as conservation features can affect conservation of forest biodiversity and how different opportunity cost constraints can change spatial priorities for conservation. We created spatially explicit cost-effective conservation scenarios for 59 forest biodiversity features and five ecosystem services in the county of Telemark (Norway) with the help of the heuristic optimisation planning software, Marxan with Zones. We combined a mix of conservation instruments where forestry is either completely (non-use zone) or partially restricted (partial use zone). Opportunity costs were measured in terms of foregone timber harvest, an important provisioning service in Telemark. Including a number of ecosystem services shifted priority conservation sites compared to a case where only biodiversity was considered, and increased the area of both the partial (+36.2%) and the non-use zone (+3.2%). Furthermore, opportunity costs increased (+6.6%), which suggests that ecosystem services may not be a side-benefit of biodiversity conservation in this area. Opportunity cost levels were systematically changed to analyse their effect on spatial conservation priorities. Conservation of biodiversity and ecosystem services trades off against timber harvest. Currently designated nature reserves and landscape protection areas achieve a very low proportion (9.1%) of the conservation targets we set in our scenario, which illustrates the high importance given to timber production at present. A trade-off curve indicated that large marginal increases in conservation target achievement are possible when the budget for conservation is increased. Forty percent of the maximum hypothetical opportunity costs would yield an average conservation target achievement of 79%.

THE DOWNSLOPE PROPAGATION OF A DISTURBANCE IN A FORESTED CATCHMENT: AN ECO-HYDROLOGIC SIMULATION STUDY

EPA Science Inventory

We developed and applied a spatially-explicit, eco-hydrologic model to examine how a landscape disturbance affects hydrologic processes, ecosystem cycling of C and N, and ecosystem structure. We simulated how the pattern and magnitude of tree removal in a catchment influences fo...

Analysis of Sensitivity and Uncertainty in an Individual-Based Model of a Threatened Wildlife Species

EPA Science Inventory

We present a multi-faceted sensitivity analysis of a spatially explicit, individual-based model (IBM) (HexSim) of a threatened species, the Northern Spotted Owl (Strix occidentalis caurina) on a national forest in Washington, USA. Few sensitivity analyses have been conducted on ...

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire-induced forest phenology changes at unprecedented temporal and spatial resolutions. This work provides the methodological approach monitor fire-induced forest changes in a spatially explicit manner across scales, with important implications for fire-related forest management and for constraining/benchmarking process models.

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil

PubMed Central

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J.

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns. PMID:27171522

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil.

PubMed

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns.

Comparing Effects of Climate Warming, Fire, and Timber Harvesting on a Boreal Forest Landscape in Northeastern China

PubMed Central

Li, Xiaona; He, Hong S.; Wu, Zhiwei; Liang, Yu; Schneiderman, Jeffrey E.

2013-01-01

Forest management under a changing climate requires assessing the effects of climate warming and disturbance on the composition, age structure, and spatial patterns of tree species. We investigated these effects on a boreal forest in northeastern China using a factorial experimental design and simulation modeling. We used a spatially explicit forest landscape model (LANDIS) to evaluate the effects of three independent variables: climate (current and expected future), fire regime (current and increased fire), and timber harvesting (no harvest and legal harvest). Simulations indicate that this forested landscape would be significantly impacted under a changing climate. Climate warming would significantly increase the abundance of most trees, especially broadleaf species (aspen, poplar, and willow). However, climate warming would have less impact on the abundance of conifers, diversity of forest age structure, and variation in spatial landscape structure than burning and harvesting. Burning was the predominant influence in the abundance of conifers except larch and the abundance of trees in mid-stage. Harvesting impacts were greatest for the abundance of larch and birch, and the abundance of trees during establishment stage (1–40 years), early stage (41–80 years) and old- growth stage (>180 years). Disturbance by timber harvesting and burning may significantly alter forest ecosystem dynamics by increasing forest fragmentation and decreasing forest diversity. Results from the simulations provide insight into the long term management of this boreal forest. PMID:23573209

A theory of forest dynamics: Spatially explicit models and issues of scale

NASA Technical Reports Server (NTRS)

Pacala, S.

1990-01-01

Good progress has been made in the first year of DOE grant (number sign) FG02-90ER60933. The purpose of the project is to develop and investigate models of forest dynamics that apply across a range of spatial scales. The grant is one third of a three-part project. The second third was funded by the NSF this year and is intended to provide the empirical data necessary to calibrate and test small-scale (less than or equal to 1000 ha) models. The final third was also funded this year (NASA), and will provide data to calibrate and test the large-scale features of the models.

Observation and simulation of net primary productivity in Qilian Mountain, western China.

PubMed

Zhou, Y; Zhu, Q; Chen, J M; Wang, Y Q; Liu, J; Sun, R; Tang, S

2007-11-01

We modeled net primary productivity (NPP) at high spatial resolution using an advanced spaceborne thermal emission and reflection radiometer (ASTER) image of a Qilian Mountain study area using the boreal ecosystem productivity simulator (BEPS). Two key driving variables of the model, leaf area index (LAI) and land cover type, were derived from ASTER and moderate resolution imaging spectroradiometer (MODIS) data. Other spatially explicit inputs included daily meteorological data (radiation, precipitation, temperature, humidity), available soil water holding capacity (AWC), and forest biomass. NPP was estimated for coniferous forests and other land cover types in the study area. The result showed that NPP of coniferous forests in the study area was about 4.4 tCha(-1)y(-1). The correlation coefficient between the modeled NPP and ground measurements was 0.84, with a mean relative error of about 13.9%.

Hurricane Katrina's carbon footprint on U.S. Gulf Coast forests.

PubMed

Chambers, Jeffrey Q; Fisher, Jeremy I; Zeng, Hongcheng; Chapman, Elise L; Baker, David B; Hurtt, George C

2007-11-16

Hurricane Katrina's impact on U.S. Gulf Coast forests was quantified by linking ecological field studies, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) image analyses, and empirically based models. Within areas affected by relatively constant wind speed, tree mortality and damage exhibited strong species-controlled gradients. Spatially explicit forest disturbance maps coupled with extrapolation models predicted mortality and severe structural damage to approximately 320 million large trees totaling 105 teragrams of carbon, representing 50 to 140% of the net annual U.S. forest tree carbon sink. Changes in disturbance regimes from increased storm activity expected under a warming climate will reduce forest biomass stocks, increase ecosystem respiration, and may represent an important positive feedback mechanism to elevated atmospheric carbon dioxide.

Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

NASA Astrophysics Data System (ADS)

He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

2014-12-01

Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

Spatially explicit modelling of forest structure and function using airborne lidar and hyperspectral remote sensing data combined with micrometeorological measurements

NASA Astrophysics Data System (ADS)

Thomas, Valerie Anne

This research models canopy-scale photosynthesis at the Groundhog River Flux Site through the integration of high-resolution airborne remote sensing data and micrometeorological measurements collected from a flux tower. Light detection and ranging (lidar) data are analysed to derive models of tree structure, including: canopy height, basal area, crown closure, and average aboveground biomass. Lidar and hyperspectral remote sensing data are used to model canopy chlorophyll (Chl) and carotenoid concentrations (known to be good indicators of photosynthesis). The integration of lidar and hyperspectral data is applied to derive spatially explicit models of the fraction of photosynthetically active radiation (fPAR) absorbed by the canopy as well as a species classification for the site. These products are integrated with flux tower meteorological measurements (i.e., air temperature and global solar radiation) collected on a continuous basis over 2004 to apply the C-Fix model of carbon exchange to the site. Results demonstrate that high resolution lidar and lidar-hyperspectral integration techniques perform well in the boreal mixedwood environment. Lidar models are well correlated with forest structure, despite the complexities introduced in the mixedwood case (e.g., r2=0.84, 0.89, 0.60, and 0.91, for mean dominant height, basal area, crown closure, and average aboveground biomass). Strong relationships are also shown for canopy scale chlorophyll/carotenoid concentration analysis using integrated lidar-hyperspectral techniques (e.g., r2=0.84, 0.84, and 0.82 for Chl(a), Chl(a+b), and Chl(b)). Examination of the spatially explicit models of fPAR reveal distinct spatial patterns which become increasingly apparent throughout the season due to the variation in species groupings (and canopy chlorophyll concentration) within the 1 km radius surrounding the flux tower. Comparison of results from the modified local-scale version of the C-Fix model to tower gross ecosystem productivity (GEP) demonstrate a good correlation to flux tower measured GEP (r2=0.70 for 10 day averages), with the largest deviations occurring in June-July. This research has direct benefits for forest inventory mapping and management practices; mapping of canopy physiology and biochemical constituents related to forest health; and scaling and direct comparison to large resolution satellite models to help bridge the gap between the local-scale measurements at flux towers and predictions derived from continental-scale carbon models.

Combining global land cover datasets to quantify agricultural expansion into forests in Latin America: Limitations and challenges

PubMed Central

Persson, U. Martin

2017-01-01

While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001–2011, by combining two “state-of-the-art” global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010’s Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010’s Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for deriving accurate quantifications of land cover following forest loss. PMID:28704510

Combining global land cover datasets to quantify agricultural expansion into forests in Latin America: Limitations and challenges.

PubMed

Pendrill, Florence; Persson, U Martin

2017-01-01

While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001-2011, by combining two "state-of-the-art" global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010's Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010's Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for deriving accurate quantifications of land cover following forest loss.

Coupling a distributed hydrological model with detailed forest structural information for large-scale global change impact assessment

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Huang, Shaochun; Majasalmi, Titta; Bright, Ryan; Astrup, Rasmus; Beldring, Stein

2017-04-01

Forests are recognized for their decisive effect on landscape water balance with structural forest characteristics as stand density or species composition determining energy partitioning and dominant flow paths. However, spatial and temporal variability in forest structure is often poorly represented in hydrological modeling frameworks, in particular in regional to large scale hydrological modeling and impact analysis. As a common practice, prescribed land cover classes (including different generic forest types) are linked to parameter values derived from literature, or parameters are determined by calibration. While national forest inventory (NFI) data provide comprehensive, detailed information on hydrologically relevant forest characteristics, their potential to inform hydrological simulation over larger spatial domains is rarely exploited. In this study we present a modeling framework that couples the distributed hydrological model HBV with forest structural information derived from the Norwegian NFI and multi-source remote sensing data. The modeling framework, set up for the entire of continental Norway at 1 km spatial resolution, is explicitly designed to study the combined and isolated impacts of climate change, forest management and land use change on hydrological fluxes. We use a forest classification system based on forest structure rather than biomes which allows to implicitly account for impacts of forest management on forest structural attributes. In the hydrological model, different forest classes are represented by three parameters: leaf area index (LAI), mean tree height and surface albedo. Seasonal cycles of LAI and surface albedo are dynamically simulated to make the framework applicable under climate change conditions. Based on a hindcast for the pilot regions Nord-Trøndelag and Sør-Trøndelag, we show how forest management has affected regional hydrological fluxes during the second half of the 20th century as contrasted to climate variability.

Land use patterns and related carbon losses following deforestation in South America

NASA Astrophysics Data System (ADS)

De Sy, V.; Herold, M.; Achard, F.; Beuchle, R.; Clevers, J. G. P. W.; Lindquist, E.; Verchot, L.

2015-12-01

Land use change in South America, mainly deforestation, is a large source of anthropogenic CO2 emissions. Identifying and addressing the causes or drivers of anthropogenic forest change is considered crucial for global climate change mitigation. Few countries however, monitor deforestation drivers in a systematic manner. National-level quantitative spatially explicit information on drivers is often lacking. This study quantifies proximate drivers of deforestation and related carbon losses in South America based on remote sensing time series in a systematic, spatially explicit manner. Deforestation areas were derived from the 2010 global remote sensing survey of the Food and Agricultural Organisation Forest Resource Assessment. To assess proximate drivers, land use following deforestation was assigned by visual interpretation of high-resolution satellite imagery. To estimate gross carbon losses from deforestation, default Tier 1 biomass levels per country and eco-zone were used. Pasture was the dominant driver of forest area (71.2%) and related carbon loss (71.6%) in South America, followed by commercial cropland (14% and 12.1% respectively). Hotspots of deforestation due to pasture occurred in Northern Argentina, Western Paraguay, and along the arc of deforestation in Brazil where they gradually moved into higher biomass forests causing additional carbon losses. Deforestation driven by commercial cropland increased in time, with hotspots occurring in Brazil (Mato Grosso State), Northern Argentina, Eastern Paraguay and Central Bolivia. Infrastructure, such as urban expansion and roads, contributed little as proximate drivers of forest area loss (1.7%). Our findings contribute to the understanding of drivers of deforestation and related carbon losses in South America, and are comparable at the national, regional and continental level. In addition, they support the development of national REDD+ interventions and forest monitoring systems, and provide valuable input for statistical analysis and modelling of underlying drivers of deforestation.

Maximizing Conservation and Production with Intensive Forest Management: It's All About Location

NASA Astrophysics Data System (ADS)

Tittler, Rebecca; Filotas, Élise; Kroese, Jasmin; Messier, Christian

2015-11-01

Functional zoning has been suggested as a way to balance the needs of a viable forest industry with those of healthy ecosystems. Under this system, part of the forest is set aside for protected areas, counterbalanced by intensive and extensive management of the rest of the forest. Studies indicate this may provide adequate timber while minimizing road construction and favoring the development of large mature and old stands. However, it is unclear how the spatial arrangement of intensive management areas may affect the success of this zoning. Should these areas be agglomerated or dispersed throughout the forest landscape? Should managers prioritize (a) proximity to existing roads, (b) distance from protected areas, or (c) site-specific productivity? We use a spatially explicit landscape simulation model to examine the effects of different spatial scenarios on landscape structure, connectivity for native forest wildlife, stand diversity, harvest volume, and road construction: (1) random placement of intensive management areas, and (2-8) all possible combinations of rules (a)-(c). Results favor the agglomeration of intensive management areas. For most wildlife species, connectivity was the highest when intensive management was far from the protected areas. This scenario also resulted in relatively high harvest volumes. Maximizing distance of intensive management areas from protected areas may therefore be the best way to maximize the benefits of intensive management areas while minimizing their potentially negative effects on forest structure and biodiversity.

Amount and type of forest cover and edge are important predictorsof golden-cheeked warbler density

Treesearch

Rebecca G. Peak; Frank R. III. Thompson

2013-01-01

Considered endangered by the U.S. Fish and Wildlife Service, the Golden-cheeked Warbler (Setophaga chrysoparia) breeds exclusively in the juniper--oak (Juniperus ashei--Quercus spp.) woodlands of central Texas. Large-scale, spatially explicit models that predict population density as a function of habitat and landscape variables...

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage.

PubMed

Chaplin-Kramer, Rebecca; Sharp, Richard P; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà I Canals, Llorenç; Eichelberger, Bradley A; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M

2015-06-16

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation.

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage

PubMed Central

Chaplin-Kramer, Rebecca; Sharp, Richard P.; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà i Canals, Llorenç; Eichelberger, Bradley A.; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M.

2015-01-01

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation. PMID:26082547

Modeling Precipitation Dependent Forest Resilience in India

NASA Astrophysics Data System (ADS)

Das, P.; Behera, M. D.; Roy, P. S.

2018-04-01

The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution) Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i) forest, (ii) scrubland, (iii) grassland and (iv) treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9 %, 5.05 %, 1.89 % and 7.79 % respectively. Rest of the 65.37 % land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5 km × 5 km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr) < 0.3 in only 0.3 % (200 km2) of total forest cover in India, which was 4.3 % < 0.5 Pr. Majority of the scrubs and grass (64.92 % Pr < 0.5) from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.

Combining multiple approaches and optimized data resolution for an improved understanding of stream temperature dynamics of a forested headwater basin in the Southern Appalachians

NASA Astrophysics Data System (ADS)

Belica, L.; Mitasova, H.; Caldwell, P.; McCarter, J. B.; Nelson, S. A. C.

2017-12-01

Thermal regimes of forested headwater streams continue to be an area of active research as climatic, hydrologic, and land cover changes can influence water temperature, a key aspect of aquatic ecosystems. Widespread monitoring of stream temperatures have provided an important data source, yielding insights on the temporal and spatial patterns and the underlying processes that influence stream temperature. However, small forested streams remain challenging to model due to the high spatial and temporal variability of stream temperatures and the climatic and hydrologic conditions that drive them. Technological advances and increased computational power continue to provide new tools and measurement methods and have allowed spatially explicit analyses of dynamic natural systems at greater temporal resolutions than previously possible. With the goal of understanding how current stream temperature patterns and processes may respond to changing landcover and hydroclimatoligical conditions, we combined high-resolution, spatially explicit geospatial modeling with deterministic heat flux modeling approaches using data sources that ranged from traditional hydrological and climatological measurements to emerging remote sensing techniques. Initial analyses of stream temperature monitoring data revealed that high temporal resolution (5 minutes) and measurement resolutions (<0.1°C) were needed to adequately describe diel stream temperature patterns and capture the differences between paired 1st order and 4th order forest streams draining north and south facing slopes. This finding along with geospatial models of subcanopy solar radiation and channel morphology were used to develop hypotheses and guide field data collection for further heat flux modeling. By integrating multiple approaches and optimizing data resolution for the processes being investigated, small, but ecologically significant differences in stream thermal regimes were revealed. In this case, multi-approach research contributed to the identification of the dominant mechanisms driving stream temperature in the study area and advanced our understanding of the current thermal fluxes and how they may change as environmental conditions change in the future.

Modeling and measuring snow for assessing climate change impacts in Glacier National Park, Montana

USGS Publications Warehouse

Fagre, Daniel B.; Selkowitz, David J.; Reardon, Blase; Holzer, Karen; Mckeon, Lisa L.

2002-01-01

A 12-year program of global change research at Glacier National Park by the U.S. Geological Survey and numerous collaborators has made progress in quantifying the role of snow as a driver of mountain ecosystem processes. Spatially extensive snow surveys during the annual accumulation/ablation cycle covered two mountain watersheds and approximately 1,000 km2 . Over 7,000 snow depth and snow water equivalent (SWE) measurements have been made through spring 2002. These augment two SNOTEL sites, 9 NRCS snow courses, and approximately 150 snow pit analyses. Snow data were used to establish spatially-explicit interannual variability in snowpack SWE. East of the Continental Divide, snowpack SWE was lower but also less variable than west of the Divide. Analysis of snowpacks suggest downward trends in SWE, a reduction in snow cover duration, and earlier melt-out dates during the past 52 years. Concurrently, high elevation forests and treelines have responded with increased growth. However, the 80 year record of snow from 3 NRCS snow courses reflects a strong influence from the Pacific Decadal Oscillation, resulting in 20-30 year phases of greater or lesser mean SWE. Coupled with the fine-resolution spatial snow data from the two watersheds, the ecological consequences of changes in snowpack can be empirically assessed at a habitat patch scale. This will be required because snow distribution models have had varied success in simulating snowpack accumulation/ablation dynamics in these mountain watersheds, ranging from R2=0.38 for individual south-facing forested snow survey routes to R2=0.95 when aggregated to the watershed scale. Key ecological responses to snowpack changes occur below the watershed scale, such as snow-mediated expansion of forest into subalpine meadows, making continued spatially-explicit snow surveys a necessity. 

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.

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient.

PubMed

Fyllas, Nikolaos M; Bentley, Lisa Patrick; Shenkin, Alexander; Asner, Gregory P; Atkin, Owen K; Díaz, Sandra; Enquist, Brian J; Farfan-Rios, William; Gloor, Emanuel; Guerrieri, Rossella; Huasco, Walter Huaraca; Ishida, Yoko; Martin, Roberta E; Meir, Patrick; Phillips, Oliver; Salinas, Norma; Silman, Miles; Weerasinghe, Lasantha K; Zaragoza-Castells, Joana; Malhi, Yadvinder

2017-06-01

One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale. © 2017 John Wiley & Sons Ltd/CNRS.

Landscape-scale GPP and carbon density inform patterns and impacts of an invasive tree across wet forests of Hawaii.

PubMed

Barbosa, Jomar M; Asner, Gregory P; Hughes, R Flint; Johnson, M Tracy

2017-03-01

Plant invasion typically occurs within a landscape-scale framework of abiotic and biotic conditions, often resulting in emergent feedbacks among environment, ecosystem functions, and the dominance of invasive species. Understanding the mechanisms underlying successful invasions is an important component of conservation and management efforts, but this has been poorly investigated in a spatially explicit manner. Knowing where and why invasion patterns change throughout the landscape enables managers to use context-specific controls on the spread of invasive species. Using high-resolution airborne imaging spectroscopy, we studied plant performance in growth within and across landscapes to examine the dominance and spatial distribution of an invasive tree, Psidium cattleianum (strawberry guava), in heterogeneous environmental conditions of a submontane Hawaiian tropical forest. We assessed invader performance using the GPP ratio index, which is the relative difference in remotely sensed estimates of gross primary productivity between canopies of guava and canopies of the invaded plant community. In addition, we used airborne LiDAR data to evaluate the impacts of guava invasion on the forest aboveground carbon density in different environments. Structural equation modeling revealed that substrate type and elevation above sea level interact and amplify landscape-scale differences in productivity between the invasive species and the host plant community (GPP ratio); differences that ultimately control levels of dominance of guava. We found shifts in patterns of forest carbon storage based on both gradual increase of invader dominance and changes in environmental conditions. Overall, our results demonstrate that the remotely sensed index defined as the GPP ratio provided an innovative spatially explicit approach to track and predict the success of invasive plants based in their canopy productivity, particularly within a landscape-scale framework of varying environmental factors such as soils and elevation. This approach may help managers accurately predict where invaders of forests, scrublands, or grasslands are likely to exhibit high levels of dominance before the environment is fully invaded. © 2016 by the Ecological Society of America.

Political Shifts and Forest Transitions: A Review and Theoretical Framework for Future Research

NASA Astrophysics Data System (ADS)

Ordway, E.

2015-12-01

Most armed conflicts in recent history have occurred in biodiversity hotspots. Yet, studies examining impacts of warfare on forests yield contradictory results making it difficult to decipher trends and patterns. This study provides a theoretical framework that can be used to clarify hypothetical relationships between conflict and forest transitions, contributing to our ability to push forward a growing field of research on environmental change and conflict. Landsat TM and ETM+ satellite data were analyzed to examine forest transitions in Rwanda during a conflict and post conflict period. Net trends showed little difference between periods, with a rate of 1.6% annual gain in forest cover during conflict years, and 2.5% after the conflict. Further investigation revealed spatially concentrated forest loss during conflict years; 96% of forest loss occurred in protected areas with the most loss in Gishwati Forest Reserve at a rate of 6.1%. Trends were explored using spatially explicit conflict data that distinguished armed conflict activity from conflict induced settlements. Impacts of conflict on forests in Rwanda appear to be influenced by natural resource use near settlements. Massive migrations of people into settlements during the conflict, who had previously been scattered across the landscape, likely resulted in a redistribution of pressures. Reduced pressure elsewhere supports this inference. Results underscore the vulnerability of protected areas and the spatial dynamics of forest resource dependence during conflicts. This work demonstrates the value of distinguishing conflict activities to assess their varied environmental effects, and contributes to our theoretical development of environmental change and conflict.

CASA Forest Cover Change Data Sets

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2012-01-01

Deforestation and forest fires are global land cover changes that can be caused by both natural and human factors. Although monitoring forest fires in near-real time is critical for operational wildfire management, mapping historical wildfires in a spatially explicit fashion is also important for a number of reasons, including climate change studies (e.g., examining the relationship between rising temperatures and frequency of fires), fuel load management (e.g., deciding when and where to conduct controlled burns), and carbon cycle studies (e.g., quantifying how much CO2 is emitted by fires and for emissions reduction efforts under the United Nations programs for Reducing Emissions from Deforestation and Degradation -- REDD).

Spatially nonrandom tree mortality and ingrowth maintain equilibrium pattern in an old-growth Pseudotsuga-Tsuga forest.

PubMed

Lutz, James A; Larson, Andrew J; Furniss, Tucker J; Donato, Daniel C; Freund, James A; Swanson, Mark E; Bible, Kenneth J; Chen, Jiquan; Franklin, Jerry F

2014-08-01

Mortality processes in old-growth forests are generally assumed to be driven by gap-scale disturbance, with only a limited role ascribed to density-dependent mortality, but these assumptions are rarely tested with data sets incorporating repeated measurements. Using a 12-ha spatially explicit plot censused 13 years apart in an approximately 500-year-old Pseudotsuga-Tsuga forest, we demonstrate significant density-dependent mortality and spatially aggregated tree recruitment. However, the combined effect of these strongly nonrandom demographic processes was to maintain tree patterns in a state of dynamic equilibrium. Density-dependent mortality was most pronounced for the dominant late-successional species, Tsuga heterophylla. The long-lived, early-seral Pseudotsuga menziesii experienced an annual stem mortality rate of 0.84% and no new recruitment. Late-seral species Tsuga and Abies amabilis had nearly balanced demographic rates of ingrowth and mortality. The 2.34% mortality rate for Taxus brevifolia was higher than expected, notably less than ingrowth, and strongly affected by proximity to Tsuga. Large-diameter Tsuga structured both the regenerating conspecific and heterospecific cohorts with recruitment of Tsuga and Abies unlikely in neighborhoods crowded with large-diameter competitors (P < 0.001). Density-dependent competitive interactions strongly shape forest communities even five centuries after stand initiation, underscoring the dynamic nature of even equilibrial old-growth forests.

Assessing accuracy of point fire intervals across landscapes with simulation modelling

Treesearch

Russell A. Parsons; Emily K. Heyerdahl; Robert E. Keane; Brigitte Dorner; Joseph Fall

2007-01-01

We assessed accuracy in point fire intervals using a simulation model that sampled four spatially explicit simulated fire histories. These histories varied in fire frequency and size and were simulated on a flat landscape with two forest types (dry versus mesic). We used three sampling designs (random, systematic grids, and stratified). We assessed the sensitivity of...

Do male and female black-backed woodpeckers respond differently to gaps in habitat?

Treesearch

Jennifer Pierson; Fred W. Allendorf; Vicki Saab; Pierre Drapeau; Michael K. Schwartz

2010-01-01

We used population- and individual-based genetic approaches to assess barriers to movement in black-backed woodpeckers (Picoides arcticus), a fire-specialist that mainly occupies the boreal forest in North America. We tested if male and female woodpeckers exhibited the same movement patterns using both spatially implicit and explicit genetic analyses to define...

Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

USGS Publications Warehouse

DeJager, Nathan R.; Drohan, Patrick J.; Miranda, Brian M.; Sturtevant, Brian R.; Stout, Susan L.; Royo, Alejandro; Gustafson, Eric J.; Romanski, Mark C.

2017-01-01

Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.

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.

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results from various remote sensing scenarios will also be presented.

[Natural succession of vegetation in Tiantong National Forest Park, Zhejiang Province of East China: a simulation study].

PubMed

Lü, Na; Ni, Jian

2013-01-01

By using spatially explicit landscape model (LANDIS 6.0 PRO), and parameterized this model with the long-term research and observation data of Tiantong National Station of Forest Eco-system Observation and Research, this paper simulated the natural succession of evergreen broad-leaved forest in Tiantong National Forest park, Zhejiang Province in the future 500 years, analyzed the spatial distribution and age structure of dominant species and major landscapes, and explored the succession pattern of the evergreen broad-leaved forest. In the park, the species alternation mostly occurred before the stage of evergreen broad-leaved forest. Pinus massoniana, Quercus fabric, and Liquidambar formosana occupied a large proportion during the early succession, but gradually disappeared with the succession process. Schima superba and Castanopsis fargesii took the main advantage in late succession, and developed to the climax community. Under the conditions without disturbances, the community was mainly composed of young forests in the early succession, and of mature or over-mature forests in the late succession, implying the insufficient regeneration ability of the community. LANDIS model could be used for simulating the landscape dynamics of evergreen broad-leaved forest in eastern China. In the future research, both the model structure and the model parameters should be improved, according to the complexity and diversity of subtropical evergreen broad-leaved forest.

Forecasting Urban Forest Ecosystem Structure, Function, and Vulnerability

NASA Astrophysics Data System (ADS)

Steenberg, James W. N.; Millward, Andrew A.; Nowak, David J.; Robinson, Pamela J.; Ellis, Alexis

2017-03-01

The benefits derived from urban forest ecosystems are garnering increasing attention in ecological research and municipal planning. However, because of their location in heterogeneous and highly-altered urban landscapes, urban forests are vulnerable and commonly suffer disproportionate and varying levels of stress and disturbance. The objective of this study is to assess and analyze the spatial and temporal changes, and potential vulnerability, of the urban forest resource in Toronto, Canada. This research was conducted using a spatially-explicit, indicator-based assessment of vulnerability and i-Tree Forecast modeling of temporal changes in forest structure and function. Nine scenarios were simulated for 45 years and model output was analyzed at the ecosystem and municipal scale. Substantial mismatches in ecological processes between spatial scales were found, which can translate into unanticipated loss of function and social inequities if not accounted for in planning and management. At the municipal scale, the effects of Asian longhorned beetle and ice storm disturbance were far less influential on structure and function than changes in management actions. The strategic goals of removing invasive species and increasing tree planting resulted in a decline in carbon storage and leaf biomass. Introducing vulnerability parameters in the modeling increased the spatial heterogeneity in structure and function while expanding the disparities of resident access to ecosystem services. There was often a variable and uncertain relationship between vulnerability and ecosystem structure and function. Vulnerability assessment and analysis can provide strategic planning initiatives with valuable insight into the processes of structural and functional change resulting from management intervention.

Forecasting Urban Forest Ecosystem Structure, Function, and Vulnerability.

PubMed

Steenberg, James W N; Millward, Andrew A; Nowak, David J; Robinson, Pamela J; Ellis, Alexis

2017-03-01

The benefits derived from urban forest ecosystems are garnering increasing attention in ecological research and municipal planning. However, because of their location in heterogeneous and highly-altered urban landscapes, urban forests are vulnerable and commonly suffer disproportionate and varying levels of stress and disturbance. The objective of this study is to assess and analyze the spatial and temporal changes, and potential vulnerability, of the urban forest resource in Toronto, Canada. This research was conducted using a spatially-explicit, indicator-based assessment of vulnerability and i-Tree Forecast modeling of temporal changes in forest structure and function. Nine scenarios were simulated for 45 years and model output was analyzed at the ecosystem and municipal scale. Substantial mismatches in ecological processes between spatial scales were found, which can translate into unanticipated loss of function and social inequities if not accounted for in planning and management. At the municipal scale, the effects of Asian longhorned beetle and ice storm disturbance were far less influential on structure and function than changes in management actions. The strategic goals of removing invasive species and increasing tree planting resulted in a decline in carbon storage and leaf biomass. Introducing vulnerability parameters in the modeling increased the spatial heterogeneity in structure and function while expanding the disparities of resident access to ecosystem services. There was often a variable and uncertain relationship between vulnerability and ecosystem structure and function. Vulnerability assessment and analysis can provide strategic planning initiatives with valuable insight into the processes of structural and functional change resulting from management intervention.

Global Climate Forcing from Albedo Change Caused by Large-scale Deforestation and Reforestation: Quantification and Attribution of Geographic Variation

NASA Technical Reports Server (NTRS)

Gao, Feng; Ghimire, Bardan; Jiao, Tong; Williams, Christopher A.; Masek, Jeffrey; Schaaf, Crystal

2017-01-01

Large-scale deforestation and reforestation have contributed substantially to historical and contemporary global climate change in part through albedo-induced radiative forcing, with meaningful implications for forest management aiming to mitigate climate change. Associated warming or cooling varies widely across the globe due to a range of factors including forest type, snow cover, and insolation, but resulting geographic variation remain spoorly described and has been largely based on model assessments. This study provides an observation-based approach to quantify local and global radiative forcings from large-scale deforestation and reforestation and further examines mechanisms that result in the spatial heterogeneity of radiative forcing. We incorporate a new spatially and temporally explicit land cover-specific albedo product derived from Moderate Resolution Imaging Spectroradiometer with a historical land use data set (Land Use Harmonization product). Spatial variation in radiative forcing was attributed to four mechanisms, including the change in snow-covered albedo, change in snow-free albedo, snow cover fraction, and incoming solar radiation. We find an albedo-only radiative forcing (RF) of -0.819 W m(exp -2) if year 2000 forests were completely deforested and converted to croplands. Albedo RF from global reforestation of present-day croplands to recover year 1700 forests is estimated to be 0.161 W m)exp -2). Snow-cover fraction is identified as the primary factor in determining the spatial variation of radiative forcing in winter, while the magnitude of the change in snow-free albedo is the primary factor determining variations in summertime RF. Findings reinforce the notion that, for conifers at the snowier high latitudes, albedo RF diminishes the warming from forest loss and the cooling from forest gain more so than for other forest types, latitudes, and climate settings.

Assessing Landscape Change and Processes of Recurrence, Replacement, and Recovery in the Southeastern Coastal Plains, USA

NASA Astrophysics Data System (ADS)

Drummond, Mark A.; Stier, Michael P.; Auch, Roger F.; Taylor, Janis L.; Griffith, Glenn E.; Riegle, Jodi L.; Hester, David J.; Soulard, Christopher E.; McBeth, Jamie L.

2015-11-01

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Assessing landscape change and processes of recurrence, replacement, and recovery in the Southeastern Coastal Plains, USA

USGS Publications Warehouse

Drummond, Mark A.; Stier, Michael P.; Auch, Roger F.; Taylor, Janis L.; Griffith, Glenn E.; Hester, David J.; Riegle, Jodi L.; Soulard, Christopher E.; McBeth, Jamie L.

2015-01-01

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Assessing Landscape Change and Processes of Recurrence, Replacement, and Recovery in the Southeastern Coastal Plains, USA.

PubMed

Drummond, Mark A; Stier, Michael P; Auch, Roger F; Taylor, Janis L; Griffith, Glenn E; Riegle, Jodi L; Hester, David J; Soulard, Christopher E; McBeth, Jamie L

2015-11-01

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8% of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15% of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83%. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3% of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Ecological forestry in an uneven-aged, late-successional forest: Simulated effects of contrasting treatments on structure and yield

Treesearch

Jacob J. Hanson; Craig G. Lorimer; Corey R. Halpin; Brian J. Palik

2012-01-01

Ecological forestry practices are designed to retain species and structural features important for maintaining ecosystem function but which may be deficient in conventionally managed stands. We used the spatially-explicit, individual tree model CANOPY to assess tradeoffs in enhanced ecological attributes vs. reductions in timber yield for a wide variety of treatments...

Comparing alternative tree canopy cover estimates derived from digital aerial photography and field-based assessments

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2012-01-01

A spatially-explicit representation of live tree canopy cover, such as the National Land Cover Dataset (NLCD) percent tree canopy cover layer, is a valuable tool for many applications, such as defining forest land, delineating wildlife habitat, estimating carbon, and modeling fire risk and behavior. These layers are generated by predictive models wherein their accuracy...

Historical fire and vegetation dynamics in dry forests of the interior Pacific Northwest, USA, and relationships to northern spotted owl (Strix occidentalis caurina) habitat conservation

Treesearch

Rebecca S.H. Kennedy; Michael C. Wimberly

2009-01-01

Regional conservation planning frequently relies on general assumptions about historical disturbance regimes to inform decisions about landscape restoration, reserve allocations, and landscape management. Spatially explicit simulations of landscape dynamics provide quantitative estimates of landscape structure and allow for the testing of alternative scenarios. We used...

The Application of FIA-based Data to Wildlife Habitat Modeling: A Comparative Study

Treesearch

Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Randall J. Schultz

2005-01-01

We evaluated the capability of two types of models, one based on spatially explicit variables derived from FIA data and one using so-called traditional habitat evaluation methods, for predicting the presence of cavity-nesting bird habitat in Fishlake National Forest, Utah. Both models performed equally well, in measures of predictive accuracy, with the FIA-based model...

Models for mapping potential habitat at landscape scales: an example using northern spotted owls.

Treesearch

William C. McComb; Michael T. McGrath; Thomas A. Spies; David Vesely

2002-01-01

We are assessing the potential for current and alternative policies in the Oregon Coast Range to affect habitat capability for a suite of forest resources. We provide an example of a spatially explicit habitat capability model for northern spotted owls (Strix occidentalis caurina)to illustrate the approach we are taking to assess potential changes...

Simulation modeling of forest landscape disturbances: Where do we go from here?

Treesearch

Ajith H. Perera; Brian R. Sturtevant; Lisa J. Buse

2015-01-01

It was nearly a quarter-century ago when Turner and Gardner (1991) drew attention to methods of quantifying landscape patterns and processes, including simulation modeling. The many authors who contributed to that seminal text collectively signaled the emergence of a new field—spatially explicit simulation modeling of broad-scale ecosystem dynamics. Of particular note...

Global agriculture and carbon trade-offs

PubMed Central

Johnson, Justin Andrew; Runge, Carlisle Ford; Senauer, Benjamin; Foley, Jonathan; Polasky, Stephen

2014-01-01

Feeding a growing and increasingly affluent world will require expanded agricultural production, which may require converting grasslands and forests into cropland. Such conversions can reduce carbon storage, habitat provision, and other ecosystem services, presenting difficult societal trade-offs. In this paper, we use spatially explicit data on agricultural productivity and carbon storage in a global analysis to find where agricultural extensification should occur to meet growing demand while minimizing carbon emissions from land use change. Selective extensification saves ∼6 billion metric tons of carbon compared with a business-as-usual approach, with a value of approximately $1 trillion (2012 US dollars) using recent estimates of the social cost of carbon. This type of spatially explicit geospatial analysis can be expanded to include other ecosystem services and other industries to analyze how to minimize conflicts between economic development and environmental sustainability. PMID:25114254

Global agriculture and carbon trade-offs.

PubMed

Johnson, Justin Andrew; Runge, Carlisle Ford; Senauer, Benjamin; Foley, Jonathan; Polasky, Stephen

2014-08-26

Feeding a growing and increasingly affluent world will require expanded agricultural production, which may require converting grasslands and forests into cropland. Such conversions can reduce carbon storage, habitat provision, and other ecosystem services, presenting difficult societal trade-offs. In this paper, we use spatially explicit data on agricultural productivity and carbon storage in a global analysis to find where agricultural extensification should occur to meet growing demand while minimizing carbon emissions from land use change. Selective extensification saves ∼ 6 billion metric tons of carbon compared with a business-as-usual approach, with a value of approximately $1 trillion (2012 US dollars) using recent estimates of the social cost of carbon. This type of spatially explicit geospatial analysis can be expanded to include other ecosystem services and other industries to analyze how to minimize conflicts between economic development and environmental sustainability.

Understanding the Socioeconomic Effects of Wildfires on Western U.S. Public Lands

NASA Astrophysics Data System (ADS)

Sanchez, J. J.; Srivastava, L.; Marcos-Martinez, R.

2017-12-01

Climate change has resulted in the increased severity and frequency of forest disturbances due to wildfires, droughts, pests and diseases that compromise the sustainable provision of forest ecosystem services (e.g., water quantity and quality, carbon sequestration, recreation). A better understanding of the environmental and socioeconomic consequences of forest disturbances (i.e., wildfires) could improve the management and protection of public lands. We used a single-site benefit transfer function and spatially explicit information for demographic, socioeconomic, and site-specific characteristics to estimate the monetized value of market and non-market ecosystem services provided by forests on Western US public lands. These estimates are then used to approximate the costs of forest disturbances caused by wildfires of varying frequency and intensity, and across sites with heterogeneous characteristics and protection and management strategies. Our analysis provides credible estimates of the benefits of the forest for land management by the United States Forest Service, thereby assisting forest managers in planning resourcing and budgeting priorities.

Implementation of a subcanopy solar radiation model on a forested headwater basin in the Southern Appalachians to estimate riparian canopy density and stream insolation for stream temperature models

NASA Astrophysics Data System (ADS)

Belica, L.; Petras, V.; Iiames, J. S., Jr.; Caldwell, P.; Mitasova, H.; Nelson, S. A. C.

2016-12-01

Water temperature is a key aspect of water quality and understanding how the thermal regimes of forested headwater streams may change in response to climatic and land cover changes is increasingly important to scientists and resource managers. In recent years, the forested mountain watersheds of the Southeastern U.S. have experienced changing climatic patterns as well as the loss of a keystone riparian tree species and anticipated hydrologic responses include lower summer stream flows and decreased stream shading. Solar radiation is the main source of thermal energy to streams and a key parameter in heat-budget models of stream temperature; a decrease in flow volume combined with a reduction in stream shading during summer have the potential to increase stream temperatures. The high spatial variability of forest canopies and the high spatio-temporal variability in sky conditions make estimating the solar radiation reaching small forested headwater streams difficult. The Subcanopy Solar Radiation Model (SSR) (Bode et al. 2014) is a GIS model that generates high resolution, spatially explicit estimates of solar radiation by incorporating topographic and vegetative shading with a light penetration index derived from leaf-on airborne LIDAR data. To evaluate the potential of the SSR model to provide estimates of stream insolation to parameterize heat-budget models, it was applied to the Coweeta Basin in the Southern Appalachians using airborne LIDAR (NCALM 2009, 1m resolution). The LIDAR derived canopy characteristics were compared to current hyperspectral images of the canopy for changes and the SSR estimates of solar radiation were compared with pyranometer measurements of solar radiation at several subcanopy sites during the summer of 2016. Preliminary results indicate the SSR model was effective in identifying variations in canopy density and light penetration, especially in areas associated with road and stream corridors and tree mortality. Current LIDAR data and more solar radiation measurements are needed to fully validate the accuracy of the SSR model in Southern Appalachian forests, but initial results suggest the high resolution, spatially explicit estimates of solar radiation can improve solar radiation parameter estimates in deterministic models of stream temperature in forested landscapes.

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.

Spatially-explicit models of global tree density.

PubMed

Glick, Henry B; Bettigole, Charlie; Maynard, Daniel S; Covey, Kristofer R; Smith, Jeffrey R; Crowther, Thomas W

2016-08-16

Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.

Catchment-scale Validation of a Physically-based, Post-fire Runoff and Erosion Model

NASA Astrophysics Data System (ADS)

Quinn, D.; Brooks, E. S.; Robichaud, P. R.; Dobre, M.; Brown, R. E.; Wagenbrenner, J.

2017-12-01

The cascading consequences of fire-induced ecological changes have profound impacts on both natural and managed forest ecosystems. Forest managers tasked with implementing post-fire mitigation strategies need robust tools to evaluate the effectiveness of their decisions, particularly those affecting hydrological recovery. Various hillslope-scale interfaces of the physically-based Water Erosion Prediction Project (WEPP) model have been successfully validated for this purpose using fire-effected plot experiments, however these interfaces are explicitly designed to simulate single hillslopes. Spatially-distributed, catchment-scale WEPP interfaces have been developed over the past decade, however none have been validated for post-fire simulations, posing a barrier to adoption for forest managers. In this validation study, we compare WEPP simulations with pre- and post-fire hydrological records for three forested catchments (W. Willow, N. Thomas, and S. Thomas) that burned in the 2011 Wallow Fire in Northeastern Arizona, USA. Simulations were conducted using two approaches; the first using automatically created inputs from an online, spatial, post-fire WEPP interface, and the second using manually created inputs which incorporate the spatial variability of fire effects observed in the field. Both approaches were compared to five years of observed post-fire sediment and flow data to assess goodness of fit.

Cost-effectiveness of dryland forest restoration evaluated by spatial analysis of ecosystem services

PubMed Central

Birch, Jennifer C.; Newton, Adrian C.; Aquino, Claudia Alvarez; Cantarello, Elena; Echeverría, Cristian; Kitzberger, Thomas; Schiappacasse, Ignacio; Garavito, Natalia Tejedor

2010-01-01

Although ecological restoration is widely used to combat environmental degradation, very few studies have evaluated the cost-effectiveness of this approach. We examine the potential impact of forest restoration on the value of multiple ecosystem services across four dryland areas in Latin America, by estimating the net value of ecosystem service benefits under different reforestation scenarios. The values of selected ecosystem services were mapped under each scenario, supported by the use of a spatially explicit model of forest dynamics. We explored the economic potential of a change in land use from livestock grazing to restored native forest using different discount rates and performed a cost–benefit analysis of three restoration scenarios. Results show that passive restoration is cost-effective for all study areas on the basis of the services analyzed, whereas the benefits from active restoration are generally outweighed by the relatively high costs involved. These findings were found to be relatively insensitive to discount rate but were sensitive to the market value of carbon. Substantial variation in values was recorded between study areas, demonstrating that ecosystem service values are strongly context specific. However, spatial analysis enabled localized areas of net benefits to be identified, indicating the value of this approach for identifying the relative costs and benefits of restoration interventions across a landscape. PMID:21106761

Cost-effectiveness of dryland forest restoration evaluated by spatial analysis of ecosystem services.

PubMed

Birch, Jennifer C; Newton, Adrian C; Aquino, Claudia Alvarez; Cantarello, Elena; Echeverría, Cristian; Kitzberger, Thomas; Schiappacasse, Ignacio; Garavito, Natalia Tejedor

2010-12-14

Although ecological restoration is widely used to combat environmental degradation, very few studies have evaluated the cost-effectiveness of this approach. We examine the potential impact of forest restoration on the value of multiple ecosystem services across four dryland areas in Latin America, by estimating the net value of ecosystem service benefits under different reforestation scenarios. The values of selected ecosystem services were mapped under each scenario, supported by the use of a spatially explicit model of forest dynamics. We explored the economic potential of a change in land use from livestock grazing to restored native forest using different discount rates and performed a cost-benefit analysis of three restoration scenarios. Results show that passive restoration is cost-effective for all study areas on the basis of the services analyzed, whereas the benefits from active restoration are generally outweighed by the relatively high costs involved. These findings were found to be relatively insensitive to discount rate but were sensitive to the market value of carbon. Substantial variation in values was recorded between study areas, demonstrating that ecosystem service values are strongly context specific. However, spatial analysis enabled localized areas of net benefits to be identified, indicating the value of this approach for identifying the relative costs and benefits of restoration interventions across a landscape.

Linkages between unpaved forest roads and streambed sediment: why context matters in directing road restoration

USGS Publications Warehouse

Al-Chokhachy, Robert K.; Black, Tom A.; Thomas, Cameron; Luce, Charlie H.; Rieman, Bruce; Cissel, Richard; Carlson, Anne; Hendrickson, Shane; Archer, Eric K.; Kershner, Jeffrey L.

2016-01-01

Unpaved forest roads remain a pervasive disturbance on public lands and mitigating sediment from road networks remains a priority for management agencies. Restoring roaded landscapes is becoming increasingly important for many native coldwater fishes that disproportionately rely on public lands for persistence. However, effectively targeting restoration opportunities requires a comprehensive understanding of the effects of roads across different ecosystems. Here, we combine a review and a field study to evaluate the status of knowledge supporting the conceptual framework linking unpaved forest roads with streambed sediment. Through our review, we specifically focused on those studies linking measures of the density of forest roads or sediment delivery with empirical streambed sediment measures. Our field study provides an example of a targeted effort of linking spatially explicit estimates of sediment production with measures of streambed sediment. Surprisingly, our review uncovered few studies (n = 8) that empirically tested the conceptual framework linking unpaved forest roads and streambed sediment, and the results varied considerably. Field results generally supported the conceptual model that unpaved forest roads can control streambed sediment quality, but demonstrated high-spatial variability in the effects of forest roads on streambed sediment and the need to address hotspots of sediment sources. The importance of context in the effects of forest roads is apparent in both our review and field data, suggesting the need for in situ studies to avoid misdirected restoration actions.

Fire Impacts on Mixed Pine-oak Forests Assessed with High Spatial Resolution Imagery, Imaging Spectroscopy, and LiDAR

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Kathy, S. L.; Dennison, P. E.; Cook, B.; Hanavan, R. P.; Serbin, S.

2016-12-01

As a primary disturbance agent, fire significantly influences forest ecosystems, including the modification or resetting of vegetation composition and structure, which can then significantly impact landscape-scale plant function and carbon stocks. Most ecological processes associated with fire effects (e.g. tree damage, mortality, and vegetation recovery) display fine-scale, species specific responses but can also vary spatially within the boundary of the perturbation. For example, both oak and pine species are fire-adapted, but fire can still induce changes in composition, structure, and dominance in a mixed pine-oak forest, mainly because of their varying degrees of fire adaption. Evidence of post-fire shifts in dominance between oak and pine species has been documented in mixed pine-oak forests, but these processes have been poorly investigated in a spatially explicit manner. In addition, traditional field-based means of quantifying the response of partially damaged trees across space and time is logistically challenging. Here we show how combining high resolution satellite imagery (i.e. Worldview-2,WV-2) and airborne imaging spectroscopy and LiDAR (i.e. NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager, G-LiHT) can be effectively used to remotely quantify spatial and temporal patterns of vegetation recovery following a top-killing fire that occurred in 2012 within mixed pine-oak forests in the Long Island Central Pine Barrens Region, New York. We explore the following questions: 1) what are the impacts of fire on species composition, dominance, plant health, and vertical structure; 2) what are the recovery trajectories of forest biomass, structure, and spectral properties for three years following the fire; and 3) to what extent can fire impacts be captured and characterized by multi-sensor remote sensing techniques from active and passive optical remote sensing.

The Interplay among Acorn Abundance and Rodent Behavior Drives the Spatial Pattern of Seedling Recruitment in Mature Mediterranean Oak Forests.

PubMed

Sunyer, Pau; Boixadera, Ester; Muñoz, Alberto; Bonal, Raúl; Espelta, Josep Maria

2015-01-01

The patterns of seedling recruitment in animal-dispersed plants result from the interactions among environmental and behavioral variables. However, we know little on the contribution and combined effect of both kinds of variables. We designed a field study to assess the interplay between environment (vegetation structure, seed abundance, rodent abundance) and behavior (seed dispersal and predation by rodents, and rooting by wild boars), and their contribution to the spatial patterns of seedling recruitment in a Mediterranean mixed-oak forest. In a spatially explicit design, we monitored intensively all environmental and behavioral variables in fixed points at a small spatial scale from autumn to spring, as well as seedling emergence and survival. Our results revealed that the spatial patterns of seedling emergence were strongly related to acorn availability on the ground, but not by a facilitation effect of vegetation cover. Rodents changed seed shadows generated by mother trees by dispersing most seeds from shrubby to open areas, but the spatial patterns of acorn dispersal/predation had no direct effect on recruitment. By contrast, rodents had a strong impact on recruitment as pilferers of cached seeds. Rooting by wild boars also reduced recruitment by reducing seed abundance, but also by changing rodent's behavior towards higher consumption of acorns in situ. Hence, seed abundance and the foraging behavior of scatter-hoarding rodents and wild boars are driving the spatial patterns of seedling recruitment in this mature oak forest, rather than vegetation features. The contribution of vegetation to seedling recruitment (e.g. facilitation by shrubs) may be context dependent, having a little role in closed forests, or being overridden by directed seed dispersal from shrubby to open areas. We warn about the need of using broad approaches that consider the combined action of environment and behavior to improve our knowledge on the dynamics of natural regeneration in forests.

The Interplay among Acorn Abundance and Rodent Behavior Drives the Spatial Pattern of Seedling Recruitment in Mature Mediterranean Oak Forests

PubMed Central

Boixadera, Ester; Bonal, Raúl

2015-01-01

The patterns of seedling recruitment in animal-dispersed plants result from the interactions among environmental and behavioral variables. However, we know little on the contribution and combined effect of both kinds of variables. We designed a field study to assess the interplay between environment (vegetation structure, seed abundance, rodent abundance) and behavior (seed dispersal and predation by rodents, and rooting by wild boars), and their contribution to the spatial patterns of seedling recruitment in a Mediterranean mixed-oak forest. In a spatially explicit design, we monitored intensively all environmental and behavioral variables in fixed points at a small spatial scale from autumn to spring, as well as seedling emergence and survival. Our results revealed that the spatial patterns of seedling emergence were strongly related to acorn availability on the ground, but not by a facilitationeffect of vegetation cover. Rodents changed seed shadows generated by mother trees by dispersing most seeds from shrubby to open areas, but the spatial patterns of acorn dispersal/predation had no direct effect on recruitment. By contrast, rodents had a strong impact on recruitment as pilferers of cached seeds. Rooting by wild boars also reduced recruitment by reducing seed abundance, but also by changing rodent’s behavior towards higher consumption of acorns in situ. Hence, seed abundance and the foraging behavior of scatter-hoarding rodents and wild boars are driving the spatial patterns of seedling recruitment in this mature oak forest, rather than vegetation features. The contribution of vegetation to seedling recruitment (e.g. facilitation by shrubs) may be context dependent, having a little role in closed forests, or being overridden by directed seed dispersal from shrubby to open areas. We warn about the need of using broad approaches that consider the combined action of environment and behavior to improve our knowledge on the dynamics of natural regeneration in forests. PMID:26070129

Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California

Treesearch

Nik J. Cunniffe; Richard C. Cobb; Ross K. Meentemeyer; David M. Rizzo; Christopher A. Gilligan

2016-01-01

Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially-explicit model parameterized using data on...

Measuring crown dynamics of longleaf pine in the sandhills of Eglin Air Force Base

Treesearch

Matt Anderson; Greg L. Somers; W. Rick Smith; Mickey Freeland; Donna Ruth

1998-01-01

The USDA Forest Service SRS, in cooperation with Auburn University, is developing an individual tree, spatially explicit, and btoiogicaily based growth model for natural iongieaf pine sands at Eglin Air Force Base in Florida. The goal of the growth model is to provide a tool for the land managers to compare silvicultural practices effects on the light and water...

Spatially-Explicit Holocene Drought Reconstructions in Amazonian Forests

NASA Astrophysics Data System (ADS)

McMichael, C.; Bush, M. B.

2014-12-01

Climate models predict increasing drought in Amazonian forests over the next century, and the synergy of drought and fire may lead to forest dieback. El Niño Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO) are two primary drivers of Amazonian drought, and each process has a spatially distinct manifestation in the Basin. Paleoecological reconstructions can contextualize the forest response to past drought periods. Stalagmite and lake sediment records have documented that the early- to mid-Holocene, i.e. 10,000 - 5000 calibrated years before present (cal yr BP), was among the driest periods of the last 100,000 years in western Amazonia. Climatic conditions became wetter and more similar to the modern climate over the last 4000 cal yr BP, and fires rarely occurred in the absence of human activity. Yet there are currently no drought and fire reconstructions that examine the spatially explicit patterns of drought during the Holocene. Here, we present regional drought histories from southwestern and northeastern sections Amazonia for the last 10,000 years that document the drought-fire dynamics resulting from both climatic processes. Our reconstructions were based on a compilation of dated soil charcoal fragments (N= 291) collected from within Amazonia sensu stricto, which were analyzed by region using summed probability analysis. The compiled soil charcoal dates contained limited evidence of fire over the last 10,000 years in some regions. Fire frequency rose markedly across the Basin, however, during the last 2000 years, indicating an increased human presence. Fire probabilities, and thus droughts, had similar increasing trajectories between southwestern and northeastern Amazonia from 1500-1100 cal yr BP, which decoupled from 1100-740 cal yr BP, and then regained synchronicity from 740-500 cal yr BP. Fire probability declined markedly after 500 yr cal BP, coincident with European arrival to the Americas. Native populations were decimated, and fire probabilities returned to similar levels before the rise 2000 years ago. These results suggested that the synergy of humans plus drought have played a large role in historical fire regimes in Amazonian forests for the last 2000 years.

A Novel DEM Approach to Simulate Block Propagation on Forested Slopes

NASA Astrophysics Data System (ADS)

Toe, David; Bourrier, Franck; Dorren, Luuk; Berger, Frédéric

2018-03-01

In order to model rockfall on forested slopes, we developed a trajectory rockfall model based on the discrete element method (DEM). This model is able to take the complex mechanical processes at work during an impact into account (large deformations, complex contact conditions) and can explicitly simulate block/soil, block/tree contacts as well as contacts between neighbouring trees. In this paper, we describe the DEM model developed and we use it to assess the protective effect of different types of forest. In addition, we compared it with a more classical rockfall simulation model. The results highlight that forests can significantly reduce rockfall hazard and that the spatial structure of coppice forests has to be taken into account in rockfall simulations in order to avoid overestimating the protective role of these forest structures against rockfall hazard. In addition, the protective role of the forests is mainly influenced by the basal area. Finally, the advantages and limitations of the DEM model were compared with classical rockfall modelling approaches.

Coupling of Water and Carbon Cycles in Boreal Ecosystems at Watershed and National Scales

NASA Astrophysics Data System (ADS)

Chen, J. M.; Ju, W.; Govind, A.; Sonnentag, O.

2009-05-01

The boreal landscapes is relatively flat giving the impression of spatial homogeneity. However, glacial activities have left distinct fingerprints on the vegetation distribution on moderately rolling terrains over the boreal landscape. Upland or lowland forests types or wetlands having various degrees of hydrological connectivitiy to the surrounding terrain are typical of the boreal landscape. The nature of the terrain creates unique hydrological conditions affecting the local-scale ecophysiological and biogeochemical processes. As part of the Canadian Carbon Program, we investigated the importance of lateral water redistribution through surface and subsurface flows in the spatial distribution of the vertical fluxes of water and carbon. A spatially explicit hydroecological model (BEPS-TerrainLab) has been developed and tested in forested and wetland watersheds . Remotely sensed vegetation parameters along with other spatial datasets are used to run this model, and tower flux data are used for partial validation. It is demonstrated in both forest and wetland watersheds that ignoring the lateral water redistribution over the landscape, commonly done in 1-dimensional bucket models, can cause considerable biases in the vertical carbon and water flux estimation, in addition to the distortion of the spatial patterns of these fluxes. The biases in the carbon flux are considerably larger than those in the water flux. The significance of these findings in national carbon budget estimation is demonstrated by separate modeling of 2015 watersheds over the Canadian landmass.

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE PAGES

Meng, Ran; Wu, Jin; Zhao, Feng; ...

2018-06-01

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

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

Meng, Ran; Wu, Jin; Zhao, Feng

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Scale-dependent variation in nitrogen cycling and soil fungal communities along gradients of forest composition and age in regenerating tropical dry forests.

PubMed

Waring, Bonnie G; Adams, Rachel; Branco, Sara; Powers, Jennifer S

2016-01-01

Rates of ecosystem nitrogen (N) cycling may be mediated by the presence of ectomycorrhizal fungi, which compete directly with free-living microbes for N. In the regenerating tropical dry forests of Central America, the distribution of ectomycorrhizal trees is affected by succession and soil parent material, both of which may exert independent influence over soil N fluxes. In order to quantify these interacting controls, we used a scale-explicit sampling strategy to examine soil N cycling at scales ranging from the microsite to ecosystem level. We measured fungal community composition, total and inorganic N pools, gross proteolytic rate, net N mineralization and microbial extracellular enzyme activity at multiple locations within 18 permanent plots that span dramatic gradients of soil N concentration, stand age and forest composition. The ratio of inorganic to organic N cycling was correlated with variation in fungal community structure, consistent with a strong influence of ectomycorrhiza on ecosystem-scale N cycling. However, on average, > 61% of the variation in soil biogeochemistry occurred within plots, and the effects of forest composition were mediated by this local-scale heterogeneity in total soil N concentrations. These cross-scale interactions demonstrate the importance of a spatially explicit approach towards an understanding of controls on element cycling. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Salvage logging following fires can minimize boreal caribou habitat loss while maintaining forest quotas: An example of compensatory cumulative effects.

PubMed

Beguin, Julien; McIntire, Eliot J B; Raulier, Frédéric

2015-11-01

Protected area networks are the dominant conservation approach that is used worldwide for protecting biodiversity. Conservation planning in managed forests, however, presents challenges when endangered species use old-growth forests targeted by the forest industry for timber supply. In many ecosystems, this challenge is further complicated by the occurrence of natural disturbance events that disrupt forest attributes at multiple scales. Using spatially explicit landscape simulation experiments, we gather insights into how these large scale, multifaceted processes (fire risk, timber harvesting and the amount of protected area) influenced both the persistence of the threatened boreal caribou and the level of timber supply in the boreal forest of eastern Canada. Our result showed that failure to account explicitly and a priori for fire risk in the calculation of timber supply led to an overestimation of timber harvest volume, which in turn led to rates of cumulative disturbances that threatened both the long-term persistence of boreal caribou and the sustainability of the timber supply itself. Salvage logging, however, allowed some compensatory cumulative effects. It minimised the reductions of timber supply within a range of ∼10% while reducing the negative impact of cumulative disturbances caused by fire and logging on caribou. With the global increase of the human footprint on forest ecosystems, our approach and results provide useful tools and insights for managers to resolve what often appear as lose-lose situation between the persistence of species at risk and timber harvest in other forest ecosystems. These tools contribute to bridge the gap between conservation and forest management, two disciplines that remain too often disconnected in practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Fleming, B.; Hogan, D. M.

2016-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Spatially explicit quantification of heterogeneous fire effects over long time series: Patterns from two forest types in the northern U.S. Rockies

Treesearch

C. E. Naficy; T. T. Veblen; P. F. Hessburg

2015-01-01

Within the last decade, mixed-severity fire regimes (MSFRs) have gained increasing attention in both the scientific and management communities (Arno and others 2000, Baker and others 2007, Hessburg and others 2007, Perry and others 2011, Halofsky and others 2011, Stine and others 2014). The growing influence of the MSFR model derives from several factors including: (1...

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.

PubMed

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

NASA Astrophysics Data System (ADS)

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Choice of satellite imagery and attribution of changes to disturbance type strongly affects forest carbon balance estimates.

PubMed

Mascorro, Vanessa S; Coops, Nicholas C; Kurz, Werner A; Olguín, Marcela

2015-12-01

Remote sensing products can provide regular and consistent observations of the Earth´s surface to monitor and understand the condition and change of forest ecosystems and to inform estimates of terrestrial carbon dynamics. Yet, challenges remain to select the appropriate satellite data source for ecosystem carbon monitoring. In this study we examine the impacts of three attributes of four remote sensing products derived from Landsat, Landsat-SPOT, and MODIS satellite imagery on estimates of greenhouse gas emissions and removals: (1) the spatial resolution (30 vs. 250 m), (2) the temporal resolution (annual vs. multi-year observations), and (3) the attribution of forest cover changes to disturbance types using supplementary data. With a spatially-explicit version of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), we produced annual estimates of carbon fluxes from 2002 to 2010 over a 3.2 million ha forested region in the Yucatan Peninsula, Mexico. The cumulative carbon balance for the 9-year period differed by 30.7 million MgC (112.5 million Mg CO 2e ) among the four remote sensing products used. The cumulative difference between scenarios with and without attribution of disturbance types was over 5 million Mg C for a single Landsat scene. Uncertainty arising from activity data (rates of land-cover changes) can be reduced by, in order of priority, increasing spatial resolution from 250 to 30 m, obtaining annual observations of forest disturbances, and by attributing land-cover changes by disturbance type. Even missing a single year in the land-cover observations can lead to substantial errors in ecosystems with rapid forest regrowth, such as the Yucatan Peninsula.

Uncertainties in mapping forest carbon in urban ecosystems.

PubMed

Chen, Gang; Ozelkan, Emre; Singh, Kunwar K; Zhou, Jun; Brown, Marilyn R; Meentemeyer, Ross K

2017-02-01

Spatially explicit urban forest carbon estimation provides a baseline map for understanding the variation in forest vertical structure, informing sustainable forest management and urban planning. While high-resolution remote sensing has proven promising for carbon mapping in highly fragmented urban landscapes, data cost and availability are the major obstacle prohibiting accurate, consistent, and repeated measurement of forest carbon pools in cities. This study aims to evaluate the uncertainties of forest carbon estimation in response to the combined impacts of remote sensing data resolution and neighborhood spatial patterns in Charlotte, North Carolina. The remote sensing data for carbon mapping were resampled to a range of resolutions, i.e., LiDAR point cloud density - 5.8, 4.6, 2.3, and 1.2 pt s/m 2 , aerial optical NAIP (National Agricultural Imagery Program) imagery - 1, 5, 10, and 20 m. Urban spatial patterns were extracted to represent area, shape complexity, dispersion/interspersion, diversity, and connectivity of landscape patches across the residential neighborhoods with built-up densities from low, medium-low, medium-high, to high. Through statistical analyses, we found that changing remote sensing data resolution introduced noticeable uncertainties (variation) in forest carbon estimation at the neighborhood level. Higher uncertainties were caused by the change of LiDAR point density (causing 8.7-11.0% of variation) than changing NAIP image resolution (causing 6.2-8.6% of variation). For both LiDAR and NAIP, urban neighborhoods with a higher degree of anthropogenic disturbance unveiled a higher level of uncertainty in carbon mapping. However, LiDAR-based results were more likely to be affected by landscape patch connectivity, and the NAIP-based estimation was found to be significantly influenced by the complexity of patch shape. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bundling ecosystem services in the Panama Canal watershed

PubMed Central

Simonit, Silvio; Perrings, Charles

2013-01-01

Land cover change in watersheds affects the supply of a number of ecosystem services, including water supply, the production of timber and nontimber forest products, the provision of habitat for forest species, and climate regulation through carbon sequestration. The Panama Canal watershed is currently being reforested to protect the dry-season flows needed for Canal operations. Whether reforestation of the watershed is desirable depends on its impacts on all services. We develop a spatially explicit model to evaluate the implications of reforestation both for water flows and for other services. We find that reforestation does not necessarily increase water supply, but does increase carbon sequestration and timber production. PMID:23690598

Analysis of spatial patterns informs community assembly and sampling requirements for Collembola in forest soils

NASA Astrophysics Data System (ADS)

Dirilgen, Tara; Juceviča, Edite; Melecis, Viesturs; Querner, Pascal; Bolger, Thomas

2018-01-01

The relative importance of niche separation, non-equilibrial and neutral models of community assembly has been a theme in community ecology for many decades with none appearing to be applicable under all circumstances. In this study, Collembola species abundances were recorded over eleven consecutive years in a spatially explicit grid and used to examine (i) whether observed beta diversity differed from that expected under conditions of neutrality, (ii) whether sampling points differed in their relative contributions to overall beta diversity, and (iii) the number of samples required to provide comparable estimates of species richness across three forest sites. Neutrality could not be rejected for 26 of the forest by year combinations. However, there is a trend toward greater structure in the oldest forest, where beta diversity was greater than predicted by neutrality on five of the eleven sampling dates. The lack of difference in individual- and sample-based rarefaction curves also suggests randomness in the system at this particular scale of investigation. It seems that Collembola communities are not spatially aggregated and assembly is driven primarily by neutral processes particularly in the younger two sites. Whether this finding is due to small sample size or unaccounted for environmental variables cannot be determined. Variability between dates and sites illustrates the potential of drawing incorrect conclusions if data are collected at a single site and a single point in time.

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

PubMed

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

Predicting fecal indicator organism contamination in Oregon coastal streams.

PubMed

Pettus, Paul; Foster, Eugene; Pan, Yangdong

2015-12-01

In this study, we used publicly available GIS layers and statistical tree-based modeling (CART and Random Forest) to predict pathogen indicator counts at a regional scale using 88 spatially explicit landscape predictors and 6657 samples from non-estuarine streams in the Oregon Coast Range. A total of 532 frequently sampled sites were parsed down to 93 pathogen sampling sites to control for spatial and temporal biases. This model's 56.5% explanation of variance, was comparable to other regional models, while still including a large number of variables. Analysis showed the most important predictors on bacteria counts to be: forest and natural riparian zones, cattle related activities, and urban land uses. This research confirmed linkages to anthropogenic activities, with the research prediction mapping showing increased bacteria counts in agricultural and urban land use areas and lower counts with more natural riparian conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Baseline map of carbon emissions from deforestation in tropical regions.

PubMed

Harris, Nancy L; Brown, Sandra; Hagen, Stephen C; Saatchi, Sassan S; Petrova, Silvia; Salas, William; Hansen, Matthew C; Potapov, Peter V; Lotsch, Alexander

2012-06-22

Policies to reduce emissions from deforestation would benefit from clearly derived, spatially explicit, statistically bounded estimates of carbon emissions. Existing efforts derive carbon impacts of land-use change using broad assumptions, unreliable data, or both. We improve on this approach using satellite observations of gross forest cover loss and a map of forest carbon stocks to estimate gross carbon emissions across tropical regions between 2000 and 2005 as 0.81 petagram of carbon per year, with a 90% prediction interval of 0.57 to 1.22 petagrams of carbon per year. This estimate is 25 to 50% of recently published estimates. By systematically matching areas of forest loss with their carbon stocks before clearing, these results serve as a more accurate benchmark for monitoring global progress on reducing emissions from deforestation.

Baseline Map of Carbon Emissions from Deforestation in Tropical Regions

NASA Astrophysics Data System (ADS)

Harris, Nancy L.; Brown, Sandra; Hagen, Stephen C.; Saatchi, Sassan S.; Petrova, Silvia; Salas, William; Hansen, Matthew C.; Potapov, Peter V.; Lotsch, Alexander

2012-06-01

Policies to reduce emissions from deforestation would benefit from clearly derived, spatially explicit, statistically bounded estimates of carbon emissions. Existing efforts derive carbon impacts of land-use change using broad assumptions, unreliable data, or both. We improve on this approach using satellite observations of gross forest cover loss and a map of forest carbon stocks to estimate gross carbon emissions across tropical regions between 2000 and 2005 as 0.81 petagram of carbon per year, with a 90% prediction interval of 0.57 to 1.22 petagrams of carbon per year. This estimate is 25 to 50% of recently published estimates. By systematically matching areas of forest loss with their carbon stocks before clearing, these results serve as a more accurate benchmark for monitoring global progress on reducing emissions from deforestation.

Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems

PubMed Central

Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas

2015-01-01

Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. PMID:26173892

Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

NASA Astrophysics Data System (ADS)

CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

2013-12-01

Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily resemble the FIA aboveground biomass in terms of data distribution, overall agreement, and spatial similarity across scales. Uncertainties are quantified (ranged from 0.2 to 0.4) by taking into account the spatial mismatch (FIA plot vs. PRISM grid), heterogeneity (species composition), and an example bias scenario (= 0.2) in the root system extents.

Spatial and temporal patterns of plantation forests in the United States since the 1930s: an annual and gridded data set for regional Earth system modeling

NASA Astrophysics Data System (ADS)

Chen, Guangsheng; Pan, Shufen; Hayes, Daniel J.; Tian, Hanqin

2017-08-01

Plantation forest area in the conterminous United States (CONUS) ranked second among the world's nations in the land area apportioned to forest plantation. As compared to the naturally regenerated forests, plantation forests demonstrate significant differences in biophysical characteristics, and biogeochemical and hydrological cycles as a result of more intensive management practices. Inventory data have been reported for multiple time periods on plot, state, and regional scales across the CONUS, but the requisite annual and spatially explicit plantation data set over a long-term period for analysis of the role of plantation management on regional or national scales is lacking. Through synthesis of multiple inventory data sources, this study developed methods to spatialize the time series plantation forest and tree species distribution data for the CONUS over the 1928-2012 time period. According to this new data set, plantation forest area increased from near zero in the 1930s to 268.27 thousand km2 in 2012, accounting for 8.65 % of the total forestland area in the CONUS. Regionally, the South contained the highest proportion of plantation forests, accounting for about 19.34 % of total forestland area in 2012. This time series and gridded data set developed here can be readily applied in regional Earth system modeling frameworks for assessing the impacts of plantation management practices on forest productivity, carbon and nitrogen stocks, and greenhouse gases (e.g., CO2, CH4, and N2O) and water fluxes on regional or national scales. The gridded plantation distribution and tree species maps, and the interpolated state-level annual tree planting area and plantation area during 1928-2012, are available from https://doi.org/10.1594/PANGAEA.873558.

Assessing Impacts of Disturbances and Climate Change on Carbon Stocks in Mexican Semidry Forests of the Yucatan Peninsula

NASA Astrophysics Data System (ADS)

Dai, Z.; Birdsey, R.; Johnson, K.; Dupuy, J. M.; Hernandez-Stefanoni, J. L.; Richardson, K.

2014-12-01

The spatially explicit biogeochemical model Forest-DNDC was used to estimate carbon dynamics with disturbances and climate change in secondary semidry forests in Yucatan Peninsula. The model was validated using observations from 276 field plots in a 350 km2 region of semi-deciduous forest surrounding the intensive monitoring site at Kaxil Kiuic, and it performed well with high performance efficiency (E=0.79, R2=0.83). The simulation results showed substantial spatial differences in biomass in the forests due to historical disturbance patterns and heterogeneous forest environments. The simulated impacts of the disturbances that occurred from 1998-2010 revealed an estimated loss of total biomass carbon storage of 154.7 Gg due mainly to about 12 km2 of forestland loss. The results from disturbance scenarios indicate that disastrous storms, which are not uncommon in the Yucatan Peninsula, can substantially impact carbon storage in a short time. However, warming can produce a long-term impact on carbon sequestration, due principally to the decrease in biomass carbon at a mean rate of over 100 kg ha-1yr-1 with an increase in temperature by 1 degree Celsius. The forests in this area are highly sensitive to warming due to a semidry climate where the evapotranspiration is higher than precipitation. Even if each degree of warming increase is accompanied by an increase in precipitation of 10%, the significant impact of warming cannot be dismissed.

The long-term effects of planting and harvesting on secondary forest dynamics under climate change in northeastern China

PubMed Central

Yao, Jing; He, Xingyuan; He, Hongshi; Chen, Wei; Dai, Limin; Lewis, Bernard J.; Yu, Lizhong

2016-01-01

Unlike the virgin forest in the Changbaishan Nature Reserve in northeastern China, little research on a landscape scale has been conducted on secondary forests in the region under conditions of a warming climate. This research was undertaken in the upper Hun River region where the vegetation is representative of the typical secondary forest of northeastern China. The spatially explicit forest landscape model LANDIS was utilized to simulate the responses of forest restoration dynamics to anthropogenic disturbance (planting and harvesting) and evaluate the difference of the restoration process under continuation of current climatic conditions and climate warming. The results showed that: (1) The interaction of planting and harvesting has organizational scale effects on the forest. The combination of planting and harvesting policies has significant effects on the overall forest but not on individual species. (2) The area expansion of the historically dominant species Pinus koraiensis is less under climate warming than under continuation of current climatic conditions. These suggests that we should carefully take historically dominant species as the main focus for forest restoration, especially when they are near their natural distribution boundary, because they are probably less capable of successfully adapting to climate change. PMID:26725308

The long-term effects of planting and harvesting on secondary forest dynamics under climate change in northeastern China.

PubMed

Yao, Jing; He, Xingyuan; He, Hongshi; Chen, Wei; Dai, Limin; Lewis, Bernard J; Yu, Lizhong

2016-01-04

Unlike the virgin forest in the Changbaishan Nature Reserve in northeastern China, little research on a landscape scale has been conducted on secondary forests in the region under conditions of a warming climate. This research was undertaken in the upper Hun River region where the vegetation is representative of the typical secondary forest of northeastern China. The spatially explicit forest landscape model LANDIS was utilized to simulate the responses of forest restoration dynamics to anthropogenic disturbance (planting and harvesting) and evaluate the difference of the restoration process under continuation of current climatic conditions and climate warming. The results showed that: (1) The interaction of planting and harvesting has organizational scale effects on the forest. The combination of planting and harvesting policies has significant effects on the overall forest but not on individual species. (2) The area expansion of the historically dominant species Pinus koraiensis is less under climate warming than under continuation of current climatic conditions. These suggests that we should carefully take historically dominant species as the main focus for forest restoration, especially when they are near their natural distribution boundary, because they are probably less capable of successfully adapting to climate change.

From the stand-scale to the landscape-scale: predicting the spatial patterns of forest regeneration after disturbance.

PubMed

Shive, Kristen L; Preisler, Haiganoush K; Welch, Kevin R; Safford, Hugh D; Butz, Ramona J; O'Hara, Kevin L; Stephens, Scott L

2018-05-29

Shifting disturbance regimes can have cascading effects on many ecosystems processes. This is particularly true when the scale of the disturbance no longer matches the regeneration strategy of the dominant vegetation. In the yellow pine and mixed conifer forests of California, over a century of fire exclusion and the warming climate are increasing the incidence and extent of stand-replacing wildfire; such changes in severity patterns are altering regeneration dynamics by dramatically increasing the distance from live tree seed sources. This has raised concerns about limitations to natural reforestation and the potential for conversion to non-forested vegetation types, which in turn has implications for shifts in many ecological processes and ecosystem services. We used a California region-wide dataset with 1,848 plots across 24 wildfires in yellow pine and mixed conifer forests to build a spatially-explicit habitat suitability model for forecasting postfire forest regeneration. To model the effect of seed availability, the critical initial biological filter for regeneration, we used a novel approach to predicting spatial patterns of seed availability by estimating annual seed production from existing basal area and burn severity maps. The probability of observing any conifer seedling in a 60m 2 area (the field plot scale) was highly dependent on 30-year average annual precipitation, burn severity and seed availability. We then used this model to predict regeneration probabilities across the entire extent of a "new' fire (the 2014 King Fire), which highlights the spatial variability inherent in postfire regeneration patterns. Such accurate forecasts of postfire regeneration patterns are of importance to land managers and conservationists interested in maintaining forest cover on the landscape. Our tool can also help anticipate shifts in ecosystem properties, supporting researchers interested in investigating questions surrounding alternative stable states, and the interaction of altered disturbance regimes and the changing climate. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

China's land cover and land use change from 1700 to 2005: Estimations from high-resolution satellite data and historical archives

NASA Astrophysics Data System (ADS)

Liu, Mingliang; Tian, Hanqin

2010-09-01

One of the major limitations in assessing the impacts of human activities on global biogeochemical cycles and climate is a shortage of reliable data on historical land cover and land use change (LCLUC). China had extreme discrepancies in estimating contemporary and historical patterns of LCLUC over the last 3 centuries because of its geographical complexity, long history of land use, and limited national surveys. This study aims to characterize the spatial and temporal patterns of China's LCLUC during 1700-2005 by reconstructing historical gridded data sets from high-resolution satellite data and long-term historical survey data. During this 300 year period, the major characteristics of LCLUC in China have been shrinking forest (decreased by 22%) and expanding cropland (increased by 42%) and urban areas (including urban and rural settlements, factories, quarries, mining, and other built-up land). New cropland areas have come almost equally from both forested and nonforested land. This study also revealed that substantial conversion between forest and woodland can be attributed to forest harvest, forest regeneration, and land degradation. During 1980-2005, LCLUC was characterized by shrinking cropland, expanding urban and forest areas, and large decadal variations on a national level. LCLUC in China showed significant spatial variations during different time periods, which were caused by spatial heterogeneity in vegetation, soils, and climate and regional imbalance in economy development. During 1700-2005, forests shrunk rapidly while croplands expanded in the northeast and southwest of China. During 1980-2005, we found a serious loss of cropland and urban sprawl in the eastern plain, north, and southeast regions of China and a large increase in forested area in the southeast and southwest regions. The reconstructed LCLUC data sets from this study could be used to assess the impacts of land use change on biogeochemical cycles, the water cycle, and the regional climate in China. To further eliminate uncertainties in this data set and make reliable projections of LCLUC for the future, we need to improve our understanding of the drivers of LCLUC and work toward developing an advanced, spatially explicit land use model.

Disturbance and density-dependent processes (competition and facilitation) influence the fine-scale genetic structure of a tree species' population.

PubMed

Fajardo, Alex; Torres-Díaz, Cristian; Till-Bottraud, Irène

2016-01-01

Disturbances, dispersal and biotic interactions are three major drivers of the spatial distribution of genotypes within populations, the last of which has been less studied than the other two. This study aimed to determine the role of competition and facilitation in the degree of conspecific genetic relatedness of nearby individuals of tree populations. It was expected that competition among conspecifics will lead to low relatedness, while facilitation will lead to high relatedness (selection for high relatedness within clusters). The stand structure and spatial genetic structure (SGS) of trees were examined within old-growth and second-growth forests (including multi-stemmed trees at the edge of forests) of Nothofagus pumilio following large-scale fires in Patagonia, Chile. Genetic spatial autocorrelations were computed on a spatially explicit sampling of the forests using five microsatellite loci. As biotic plant interactions occur among immediate neighbours, mean nearest neighbour distance (MNND) among trees was computed as a threshold for distinguishing the effects of disturbances and biotic interactions. All forests exhibited a significant SGS for distances greater than the MNND. The old-growth forest genetic and stand structure indicated gap recolonization from nearby trees (significantly related trees at distances between 4 and 10 m). At distances smaller than the MNND, trees of the second-growth interior forest showed significantly lower relatedness, suggesting a fading of the recolonization structure by competition, whereas the second-growth edge forest showed a positive and highly significant relatedness among trees (higher among stems of a cluster than among stems of different clusters), resulting from facilitation. Biotic interactions are shown to influence the genetic composition of a tree population. However, facilitation can only persist if individuals are related. Thus, the genetic composition in turn influences what type of biotic interactions will take place among immediate neighbours in post-disturbance forests. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Historical reconstructions of California wildfires vary by data source

USGS Publications Warehouse

Syphard, Alexandra D.; Keeley, Jon E.

2016-01-01

Historical data are essential for understanding how fire activity responds to different drivers. It is important that the source of data is commensurate with the spatial and temporal scale of the question addressed, but fire history databases are derived from different sources with different restrictions. In California, a frequently used fire history dataset is the State of California Fire and Resource Assessment Program (FRAP) fire history database, which circumscribes fire perimeters at a relatively fine scale. It includes large fires on both state and federal lands but only covers fires that were mapped or had other spatially explicit data. A different database is the state and federal governments’ annual reports of all fires. They are more complete than the FRAP database but are only spatially explicit to the level of county (California Department of Forestry and Fire Protection – Cal Fire) or forest (United States Forest Service – USFS). We found substantial differences between the FRAP database and the annual summaries, with the largest and most consistent discrepancy being in fire frequency. The FRAP database missed the majority of fires and is thus a poor indicator of fire frequency or indicators of ignition sources. The FRAP database is also deficient in area burned, especially before 1950. Even in contemporary records, the huge number of smaller fires not included in the FRAP database account for substantial cumulative differences in area burned. Wildfires in California account for nearly half of the western United States fire suppression budget. Therefore, the conclusions about data discrepancies and the implications for fire research are of broad importance.

Canopy structural complexity influences forest canopy reflectance: linking terrestrial lidar with Landsat observations

NASA Astrophysics Data System (ADS)

Hardiman, B. S.; Atkins, J.; Dahlin, K.; Fahey, R. T.; Gough, C. M.

2016-12-01

Canopy physical structure - leaf quantity and arrangement - strongly affects light interception and distribution. As such, canopy physical structure is a key driver of forest carbon (C) dynamics. Terrestrial lidar systems (TLS) provide spatially explicit, quantitative characterizations of canopy physical structure at scales commensurate with plot-scale C cycling processes. As an example, previous TLS-based studies established that light use efficiency is positively correlated with canopy physical structure, influencing the trajectory of net primary production throughout forest development. Linking TLS measurements of canopy structure to multispectral satellite observations of forest canopies may enable scaling of ecosystem C cycling processes from leaves to continents. We will report on our study relating a suite of canopy structural metrics to well-established remotely sensed measurements (NDVI, EVI, albedo, tasseled cap indices, etc.) which are indicative of important forest characteristics (leaf area, canopy nitrogen, light interception, etc.). We used Landsat data, which provides observations at 30m resolution, a scale comparable to that of TLS. TLS data were acquired during 2009-2016 from forest sites throughout Eastern North America, comprised primarily of NEON and Ameriflux sites. Canopy physical structure data were compared with contemporaneous growing-season Landsat data. Metrics of canopy physical structure are expected to covary with forest composition and dominant PFT, likely influencing interaction strength between TLS and Landsat canopy metrics. More structurally complex canopies (those with more heterogeneous distributions of leaf area) are expected to have lower albedo, suggesting greater canopy light absorption (higher fAPAR) than simpler canopies. We expect that vegetation indices (NDVI, EVI) will increase with TLS metrics of spatial heterogeneity, and not simply quantity, of leaves, supporting our hypothesis that canopy light absorption is dependent on both leaf quantity and arrangement. Relating satellite observations of canopy properties to TLS metrics of canopy physical structure represents an important advance for modelling canopy energy balance and forest C cycling processes at large spatial scales.

Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance

USGS Publications Warehouse

Huang, Shengli; Liu, Heping; Dahal, Devendra; Jin, Suming; Welp, Lisa R.; Liu, Jinxun; Liu, Shuguang

2013-01-01

In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004, 5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987–2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (Emax) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in Emax and FPAR were taken into account. The changes in Emax were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose Emax was determined from three fire chronosequence flux towers as 1.1556, 1.3336, and 0.5098 gC/MJ PAR. The changes in FPAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2–17 years, the recovery rate ranged from 54% to 95%. In addition to the averaging, our approach further revealed the spatial heterogeneity of fire impact on GPP, allowing one to examine the spatially explicit GPP change caused by fires.

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

NASA Technical Reports Server (NTRS)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Predicted effects of gypsy moth defoliation and climate change on forest carbon dynamics in the New Jersey pine barrens.

PubMed

Kretchun, Alec M; Scheller, Robert M; Lucash, Melissa S; Clark, Kenneth L; Hom, John; Van Tuyl, Steve

2014-01-01

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years.

Predicted Effects of Gypsy Moth Defoliation and Climate Change on Forest Carbon Dynamics in the New Jersey Pine Barrens

PubMed Central

Kretchun, Alec M.; Scheller, Robert M.; Lucash, Melissa S.; Clark, Kenneth L.; Hom, John; Van Tuyl, Steve

2014-01-01

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years. PMID:25119162

Carbon stock and carbon turnover in boreal and temperate forests - Integration of remote sensing data and global vegetation models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Forkel, Matthias; Tito Rademacher, Tim; Santoro, Maurizio; Tum, Markus; Schmullius, Christiane

2016-04-01

Long-term vegetation dynamics are one of the key uncertainties of the carbon cycle. There are large differences in simulated vegetation carbon stocks and fluxes including productivity, respiration and carbon turnover between global vegetation models. Especially the implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current models and their importance at global scale is highly uncertain. These shortcomings have been due to the lack of spatially extensive information on vegetation carbon stocks, which cannot be provided by inventory data alone. Instead, we recently have been able to estimate northern boreal and temperate forest carbon stocks based on radar remote sensing data. Our spatially explicit product (0.01° resolution) shows strong agreement to inventory-based estimates at a regional scale and allows for a spatial evaluation of carbon stocks and dynamics simulated by global vegetation models. By combining this state-of-the-art biomass product and NPP datasets originating from remote sensing, we are able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests along spatial gradients. We observe an increasing turnover rate with colder winter temperatures and longer winters in boreal forests, suggesting frost damage and the trade-off between frost adaptation and growth being important mortality processes in this ecosystem. In contrast, turnover rate increases with climatic conditions favouring drought and insect outbreaks in temperate forests. Investigated global vegetation models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce observation-based spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well in terms of NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in models and estimating their impact on the land carbon balance.

Uncertainty Analysis in Large Area Aboveground Biomass Mapping

NASA Astrophysics Data System (ADS)

Baccini, A.; Carvalho, L.; Dubayah, R.; Goetz, S. J.; Friedl, M. A.

2011-12-01

Satellite and aircraft-based remote sensing observations are being more frequently used to generate spatially explicit estimates of aboveground carbon stock of forest ecosystems. Because deforestation and forest degradation account for circa 10% of anthropogenic carbon emissions to the atmosphere, policy mechanisms are increasingly recognized as a low-cost mitigation option to reduce carbon emission. They are, however, contingent upon the capacity to accurately measures carbon stored in the forests. Here we examine the sources of uncertainty and error propagation in generating maps of aboveground biomass. We focus on characterizing uncertainties associated with maps at the pixel and spatially aggregated national scales. We pursue three strategies to describe the error and uncertainty properties of aboveground biomass maps, including: (1) model-based assessment using confidence intervals derived from linear regression methods; (2) data-mining algorithms such as regression trees and ensembles of these; (3) empirical assessments using independently collected data sets.. The latter effort explores error propagation using field data acquired within satellite-based lidar (GLAS) acquisitions versus alternative in situ methods that rely upon field measurements that have not been systematically collected for this purpose (e.g. from forest inventory data sets). A key goal of our effort is to provide multi-level characterizations that provide both pixel and biome-level estimates of uncertainties at different scales.

Variable Gene Dispersal Conditions and Spatial Deforestation Patterns Can Interact to Affect Tropical Tree Conservation Outcomes

PubMed Central

Kashimshetty, Yamini; Pelikan, Stephan; Rogstad, Steven H.

2015-01-01

Tropical lowland rain forest (TLRF) biodiversity is under threat from anthropogenic factors including deforestation which creates forest fragments of different sizes that can further undergo various internal patterns of logging. Such interventions can modify previous equilibrium abundance and spatial distribution patterns of offspring recruitment and/or pollen dispersal. Little is known about how these aspects of deforestation and fragmentation might synergistically affect TLRF tree recovery demographics and population genetics in newly formed forest fragments. To investigate these TLRF anthropogenic disturbance processes we used the computer program NEWGARDEN (NG), which models spatially-explicit, individual-based plant populations, to simulate 10% deforestation in six different spatial logging patterns for the plant functional type of a long-lived TLRF canopy tree species. Further, each logging pattern was analyzed under nine varying patterns of offspring versus pollen dispersal distances that could have arisen post-fragmentation. Results indicated that gene dispersal condition (especially via offspring) had a greater effect on population growth and genetic diversity retention (explaining 98.5% and 88.8% of the variance respectively) than spatial logging pattern (0.2% and 4.7% respectively), with ‘Near’ distance dispersal maximizing population growth and genetic diversity relative to distant dispersal. Within logged regions of the fragment, deforestation patterns closer to fragment borders more often exhibited lower population recovery rates and founding genetic diversity retention relative to more centrally located logging. These results suggest newly isolated fragments have populations that are more sensitive to the way in which their offspring and pollen dispersers are affected than the spatial pattern in which subsequent logging occurs, and that large variation in the recovery rates of different TLRF tree species attributable to altered gene dispersal regimens will be a likely outcome of fragmentation. Conservation implications include possible manual interventions (manual manipulations of offspring dispersers and/or pollinators) in forest fragments to increase population recovery and genetic diversity retention. PMID:26000951

Variable gene dispersal conditions and spatial deforestation patterns can interact to affect tropical tree conservation outcomes.

PubMed

Kashimshetty, Yamini; Pelikan, Stephan; Rogstad, Steven H

2015-01-01

Tropical lowland rain forest (TLRF) biodiversity is under threat from anthropogenic factors including deforestation which creates forest fragments of different sizes that can further undergo various internal patterns of logging. Such interventions can modify previous equilibrium abundance and spatial distribution patterns of offspring recruitment and/or pollen dispersal. Little is known about how these aspects of deforestation and fragmentation might synergistically affect TLRF tree recovery demographics and population genetics in newly formed forest fragments. To investigate these TLRF anthropogenic disturbance processes we used the computer program NEWGARDEN (NG), which models spatially-explicit, individual-based plant populations, to simulate 10% deforestation in six different spatial logging patterns for the plant functional type of a long-lived TLRF canopy tree species. Further, each logging pattern was analyzed under nine varying patterns of offspring versus pollen dispersal distances that could have arisen post-fragmentation. Results indicated that gene dispersal condition (especially via offspring) had a greater effect on population growth and genetic diversity retention (explaining 98.5% and 88.8% of the variance respectively) than spatial logging pattern (0.2% and 4.7% respectively), with 'Near' distance dispersal maximizing population growth and genetic diversity relative to distant dispersal. Within logged regions of the fragment, deforestation patterns closer to fragment borders more often exhibited lower population recovery rates and founding genetic diversity retention relative to more centrally located logging. These results suggest newly isolated fragments have populations that are more sensitive to the way in which their offspring and pollen dispersers are affected than the spatial pattern in which subsequent logging occurs, and that large variation in the recovery rates of different TLRF tree species attributable to altered gene dispersal regimens will be a likely outcome of fragmentation. Conservation implications include possible manual interventions (manual manipulations of offspring dispersers and/or pollinators) in forest fragments to increase population recovery and genetic diversity retention.

Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010.

PubMed

Song, Xiao-Peng; Huang, Chengquan; Saatchi, Sassan S; Hansen, Matthew C; Townshend, John R

2015-01-01

Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates-critical inputs for setting reference emission levels for REDD+-are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr(-1) and 0.18 ± 0.07 Pg C•yr(-1) respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha(-1), ~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha(-1)). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha(-1)•yr(-1) from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts.

Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010

PubMed Central

Song, Xiao-Peng; Huang, Chengquan; Saatchi, Sassan S.; Hansen, Matthew C.; Townshend, John R.

2015-01-01

Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates―critical inputs for setting reference emission levels for REDD+―are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr−1 and 0.18 ± 0.07 Pg C•yr−1 respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha−1, ~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha−1). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha−1•yr−1 from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts. PMID:25951328

Future Forest Cover Change Scenarios with Implications for Landslide Risk: An Example from Buzau Subcarpathians, Romania

NASA Astrophysics Data System (ADS)

Malek, Žiga; Boerboom, Luc; Glade, Thomas

2015-11-01

This study focuses on future forest cover change in Buzau Subcarpathians, a landslide prone region in Romania. Past and current trends suggest that the area might expect a future increase in deforestation. We developed spatially explicit scenarios until 2040 to analyze the spatial pattern of future forest cover change and potential changes to landslide risk. First, we generated transition probability maps using the weights of evidence method, followed by a cellular automata allocation model. We performed expert interviews, to develop two future forest management scenarios. The Alternative scenario (ALT) was defined by 67 % more deforestation than the Business as Usual scenario (BAU). We integrated the simulated scenarios with a landslide susceptibility map. In both scenarios, most of deforestation was projected in areas where landslides are less likely to occur. Still, 483 (ALT) and 276 (BAU) ha of deforestation were projected on areas with a high-landslide occurrence likelihood. Thus, deforestation could lead to a local-scale increase in landslide risk, in particular near or adjacent to forestry roads. The parallel process of near 10 % forest expansion until 2040 was projected to occur mostly on areas with high-landslide susceptibility. On a regional scale, forest expansion could so result in improved slope stability. We modeled two additional scenarios with an implemented landslide risk policy, excluding high-risk zones. The reduction of deforestation on high-risk areas was achieved without a drastic decrease in the accessibility of the areas. Together with forest expansion, it could therefore be used as a risk reduction strategy.

Future Forest Cover Change Scenarios with Implications for Landslide Risk: An Example from Buzau Subcarpathians, Romania.

PubMed

Malek, Žiga; Boerboom, Luc; Glade, Thomas

2015-11-01

This study focuses on future forest cover change in Buzau Subcarpathians, a landslide prone region in Romania. Past and current trends suggest that the area might expect a future increase in deforestation. We developed spatially explicit scenarios until 2040 to analyze the spatial pattern of future forest cover change and potential changes to landslide risk. First, we generated transition probability maps using the weights of evidence method, followed by a cellular automata allocation model. We performed expert interviews, to develop two future forest management scenarios. The Alternative scenario (ALT) was defined by 67% more deforestation than the Business as Usual scenario (BAU). We integrated the simulated scenarios with a landslide susceptibility map. In both scenarios, most of deforestation was projected in areas where landslides are less likely to occur. Still, 483 (ALT) and 276 (BAU) ha of deforestation were projected on areas with a high-landslide occurrence likelihood. Thus, deforestation could lead to a local-scale increase in landslide risk, in particular near or adjacent to forestry roads. The parallel process of near 10% forest expansion until 2040 was projected to occur mostly on areas with high-landslide susceptibility. On a regional scale, forest expansion could so result in improved slope stability. We modeled two additional scenarios with an implemented landslide risk policy, excluding high-risk zones. The reduction of deforestation on high-risk areas was achieved without a drastic decrease in the accessibility of the areas. Together with forest expansion, it could therefore be used as a risk reduction strategy.

An Integrated, Observation-based System to Monitor Aboveground Forest Carbon Dynamics in Washington, Oregon, and California

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Hughes, J.; Neeti, N.; Yang, Z.; Gregory, M.; Roberts, H.; Kane, V. R.; Powell, S. L.; Ohmann, J.

2016-12-01

Because carbon pools and fluxes on wooded landscapes are constrained by their type, age and health, understanding the causes and consequences of carbon change requires frequent observation of forest condition and of disturbance, mortality, and growth processes. As part of USDA and NASA funded efforts, we built empirical monitoring system that integrates time-series Landsat imagery, Forest Inventory and Analysis (FIA) plot data, small-footprint lidar data, and aerial photos to characterize key carbon dynamics in forested ecosystems of Washington, Oregon and California. Here we report yearly biomass estimates for every forested 30 by 30m pixel in the states of Washington, Oregon, and California from 1990 to 2010, including spatially explicit estimates of uncertainty in our yearly predictions. Total biomass at the ecoregion scale agrees well with estimates from FIA plot data alone, currently the only method for reliable monitoring in the forests of the region. Comparisons with estimates of biomass modeled from four small-footprint lidar acquisitions in overlapping portions of our study area show general patterns of agreement between the two types of estimation, but also reveal some disparities in spatial pattern potentially attributable to age and vegetation condition. Using machine-learning techniques based on both Landsat image time series and high resolution aerial photos, we then modeled the agent causing change in biomass for every change event in the region, and report the relative distribution of carbon loss attributable to natural disturbances (primarily fire and insect-related mortality) versus anthropogenic causes (forest management and development).

Dominant forest tree species are potentially vulnerable to climate change over large portions of their range even at high latitudes

PubMed Central

de Blois, Sylvie

2016-01-01

Projecting suitable conditions for a species as a function of future climate provides a reasonable, although admittedly imperfect, spatially explicit estimate of species vulnerability associated with climate change. Projections emphasizing range shifts at continental scale, however, can mask contrasting patterns at local or regional scale where management and policy decisions are made. Moreover, models usually show potential for areas to become climatically unsuitable, remain suitable, or become suitable for a particular species with climate change, but each of these outcomes raises markedly different ecological and management issues. Managing forest decline at sites where climatic stress is projected to increase is likely to be the most immediate challenge resulting from climate change. Here we assess habitat suitability with climate change for five dominant tree species of eastern North American forests, focusing on areas of greatest vulnerability (loss of suitability in the baseline range) in Quebec (Canada) rather than opportunities (increase in suitability). Results show that these species are at risk of maladaptation over a remarkably large proportion of their baseline range. Depending on species, 5–21% of currently climatically suitable habitats are projected to be at risk of becoming unsuitable. This suggests that species that have traditionally defined whole regional vegetation assemblages could become less adapted to these regions, with significant impact on ecosystems and forest economy. In spite of their well-recognised limitations and the uncertainty that remains, regionally-explicit risk assessment approaches remain one of the best options to convey that message and the need for climate policies and forest management adaptation strategies. PMID:27478706

Dominant forest tree species are potentially vulnerable to climate change over large portions of their range even at high latitudes.

PubMed

Périé, Catherine; de Blois, Sylvie

2016-01-01

Projecting suitable conditions for a species as a function of future climate provides a reasonable, although admittedly imperfect, spatially explicit estimate of species vulnerability associated with climate change. Projections emphasizing range shifts at continental scale, however, can mask contrasting patterns at local or regional scale where management and policy decisions are made. Moreover, models usually show potential for areas to become climatically unsuitable, remain suitable, or become suitable for a particular species with climate change, but each of these outcomes raises markedly different ecological and management issues. Managing forest decline at sites where climatic stress is projected to increase is likely to be the most immediate challenge resulting from climate change. Here we assess habitat suitability with climate change for five dominant tree species of eastern North American forests, focusing on areas of greatest vulnerability (loss of suitability in the baseline range) in Quebec (Canada) rather than opportunities (increase in suitability). Results show that these species are at risk of maladaptation over a remarkably large proportion of their baseline range. Depending on species, 5-21% of currently climatically suitable habitats are projected to be at risk of becoming unsuitable. This suggests that species that have traditionally defined whole regional vegetation assemblages could become less adapted to these regions, with significant impact on ecosystems and forest economy. In spite of their well-recognised limitations and the uncertainty that remains, regionally-explicit risk assessment approaches remain one of the best options to convey that message and the need for climate policies and forest management adaptation strategies.

A Behavioral Model of Landscape Change in the Amazon Basin: The Colonist Case

NASA Technical Reports Server (NTRS)

Walker, R. A.; Drzyzga, S. A.; Li, Y. L.; Wi, J. G.; Caldas, M.; Arima, E.; Vergara, D.

2004-01-01

This paper presents the prototype of a predictive model capable of describing both magnitudes of deforestation and its spatial articulation into patterns of forest fragmentation. In a departure from other landscape models, it establishes an explicit behavioral foundation for algorithm development, predicated on notions of the peasant economy and on household production theory. It takes a 'bottom-up' approach, generating the process of land-cover change occurring at lot level together with the geography of a transportation system to describe regional landscape change. In other words, it translates the decentralized decisions of individual households into a collective, spatial impact. In so doing, the model unites the richness of survey research on farm households with the analytical rigor of spatial analysis enabled by geographic information systems (GIs). The paper describes earlier efforts at spatial modeling, provides a critique of the so-called spatially explicit model, and elaborates a behavioral foundation by considering farm practices of colonists in the Amazon basin. It then uses, insight from the behavioral statement to motivate a GIs-based model architecture. The model is implemented for a long-standing colonization frontier in the eastern sector of the basin, along the Trans-Amazon Highway in the State of Para, Brazil. Results are subjected to both sensitivity analysis and error assessment, and suggestions are made about how the model could be improved.

Fire regimes, forest change, and self-organization in an old-growth mixed-conifer forest, Yosemite National Park, USA.

PubMed

Scholl, Andrew E; Taylor, Alan H

2010-03-01

Fire is recognized as a keystone process in dry mixed-conifer forests that have been altered by decades of fire suppression, Restoration of fire disturbance to these forests is a guiding principle of resource management in the U.S. National Park Service. Policy implementation is often hindered by a poor understanding of forest conditions before fire exclusion, the characteristics of forest changes since excluding fire, and the influence of topographic or self-organizing controls on forest structure. In this study the spatial and temporal characteristics of fire regimes and forest structure are reconstructed in a 2125-ha mixed-conifer forest. Forests were multi-aged, burned frequently at low severity and fire-return interval, and forest structure did not vary with slope aspect, elevation, or slope position. Fire exclusion has caused an increase in forest density and basal area and a compositional shift to shade-tolerant and fire-intolerant species. The median point fire-return interval and extent of a fire was 10 yr and 115 ha, respectively. The pre-Euro-American settlement fire rotation of 13 yr increased to 378 yr after 1905. The position of fire scars within tree rings indicates that 79% of fires burned in the midsummer to fall period. The spatial pattern of burns exhibited self-organizing behavior. Area burned was 10-fold greater when an area had not been burned by the previous fire. Fires were frequent and widespread, but patches of similar aged trees were < 0.2 ha, suggesting small fire-caused canopy openings. Managers need to apply multiple burns at short intervals for a sustained period to reduce surface fuels and create small canopy openings characteristic of the reference forest. By coupling explicit reference conditions with consideration of current conditions and projected climate change, management activities can balance restoration and risk management.

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PubMed Central

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522

Forest management in Earth system modelling: a vertically discretised canopy description for ORCHIDEE and the modifications to the energy, water and carbon fluxes

NASA Astrophysics Data System (ADS)

Naudts, Kim; Ryder, James; McGrath, Matthew J.; Otto, Juliane; Chen, Yiying; Valade, Aude; Bellasen, Valentin; Ghattas, Josefine; Haverd, Vanessa; MacBean, Natasha; Maignan, Fabienne; Peylin, Philippe; Pinty, Bernard; Solyga, Didier; Vuichard, Nicolas; Luyssaert, Sebastiaan

2015-04-01

Since 70% of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land surface models used in Earth system models, and therefore none of today's predictions of future climate, account for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrizing a version of the land surface model ORCHIDEE to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new model called ORCHIDEE-CAN and the standard version of ORCHIDEE are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes towards a better process representation occurred for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrization was revisited after introducing twelve new parameter sets that represent specific tree species or genera rather than a group of unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, GPP, albedo and evapotranspiration over Europe. For all tested variables ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92% chance to reproduce the spatial and temporal variability of the validation data.

An approach for high-resolution mapping of Hawaiian Metrosideros forest mortality using laser-guided imaging spectroscopy

Treesearch

Nicholas Vaughn; Gregory Asner; Philip Brodrick; Roberta Martin; Joseph Heckler; David Knapp; R. Flint Hughes

2018-01-01

Rapid ‘Ōhi‘a Death (ROD) is a disease aggressively killing large numbers of Metrosideros polymorpha (‘ōhi‘a), a native keystone tree species on Hawaii Island. This loss threatens to deeply alter the biological make-up of this unique island ecosystem. Spatially explicit information about the present and past advancement of the disease is essential...

Moving forward socio-economically focused models of deforestation.

PubMed

Dezécache, Camille; Salles, Jean-Michel; Vieilledent, Ghislain; Hérault, Bruno

2017-09-01

Whilst high-resolution spatial variables contribute to a good fit of spatially explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision-making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio-economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub-models of deforestation intensity based on socio-economic variables, we were able to create a map of predicted deforestation over the period 2001-2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approximately 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio-economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterization of socio-economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio-economic processes in the models. Whilst considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio-economic and political contexts influencing deforestation trends, this explicit characterization of the socio-economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects. © 2017 John Wiley & Sons Ltd.

Contribution of ecosystem services to air quality and climate change mitigation policies: the case of urban forests in Barcelona, Spain.

PubMed

Baró, Francesc; Chaparro, Lydia; Gómez-Baggethun, Erik; Langemeyer, Johannes; Nowak, David J; Terradas, Jaume

2014-05-01

Mounting research highlights the contribution of ecosystem services provided by urban forests to quality of life in cities, yet these services are rarely explicitly considered in environmental policy targets. We quantify regulating services provided by urban forests and evaluate their contribution to comply with policy targets of air quality and climate change mitigation in the municipality of Barcelona, Spain. We apply the i-Tree Eco model to quantify in biophysical and monetary terms the ecosystem services "air purification," "global climate regulation," and the ecosystem disservice "air pollution" associated with biogenic emissions. Our results show that the contribution of urban forests regulating services to abate pollution is substantial in absolute terms, yet modest when compared to overall city levels of air pollution and GHG emissions. We conclude that in order to be effective, green infrastructure-based efforts to offset urban pollution at the municipal level have to be coordinated with territorial policies at broader spatial scales.

Tropical forests are non-equilibrium ecosystems governed by interspecific competition based on universal 1/6 niche width.

PubMed

Fort, Hugo; Inchausti, Pablo

2013-01-01

Tropical forests are mega-diverse ecosystems that display complex and non-equilibrium dynamics. However, theoretical approaches have largely focused on explaining steady-state behaviour and fitting snapshots of data. Here we show that local and niche interspecific competition can realistically and parsimoniously explain the observed non-equilibrium regime of permanent plots of nine tropical forests, in eight different countries. Our spatially-explicit model, besides predicting with accuracy the main biodiversity metrics for these plots, can also reproduce their dynamics. A central finding is that tropical tree species have a universal niche width of approximately 1/6 of the niche axis that echoes the observed widespread convergence in their functional traits enabling them to exploit similar resources and to coexist despite of having large niche overlap. This niche width yields an average ratio of 0.25 between interspecific and intraspecific competition that corresponds to an intermediate value between the extreme claims of the neutral model and the classical niche-based model of community assembly (where interspecific competition is dominant). In addition, our model can explain and yield observed spatial patterns that classical niche-based and neutral theories cannot.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Calculation of Individual Tree Water Use in a Bornean Tropical Rain Forest Using Individual-Based Dynamic Vegetation Model SEIB-DGVM

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Saito, T.; Matsumoto, K.; Kume, T.; Nakagawa, M.; Sato, H.

2015-12-01

Bornean tropical rain forests are among the moistest biomes of the world with abundant rainfall throughout the year, and considered to be vulnerable to a change in the rainfall regime; e.g., high tree mortality was reported in such forests induced by a severe drought associated with the ENSO event in 1997-1998. In order to assess the effect (risk) of future climate change on eco-hydrology in such tropical rain forests, it is important to understand the water use of trees individually, because the vulnerability or mortality of trees against climate change can depend on the size of trees. Therefore, we refined the Spatially Explicit Individual-Based Dynamic Global Vegetation Model (SEIB-DGVM) so that the transpiration and its control by stomata are calculated for each individual tree. By using this model, we simulated the transpiration of each tree and its DBH-size dependency, and successfully reproduced the measured data of sap flow of trees and eddy covariance flux data obtained in a Bornean lowland tropical rain forest in Lambir Hills National Park, Sarawak, Malaysia.

Anticipating Forest and Range Land Development in Central Oregon (USA) for Landscape Analysis, with an Example Application Involving Mule Deer

NASA Astrophysics Data System (ADS)

Kline, Jeffrey D.; Moses, Alissa; Burcsu, Theresa

2010-05-01

Forest policymakers, public lands managers, and scientists in the Pacific Northwest (USA) seek ways to evaluate the landscape-level effects of policies and management through the multidisciplinary development and application of spatially explicit methods and models. The Interagency Mapping and Analysis Project (IMAP) is an ongoing effort to generate landscape-wide vegetation data and models to evaluate the integrated effects of disturbances and management activities on natural resource conditions in Oregon and Washington (USA). In this initial analysis, we characterized the spatial distribution of forest and range land development in a four-county pilot study region in central Oregon. The empirical model describes the spatial distribution of buildings and new building construction as a function of population growth, existing development, topography, land-use zoning, and other factors. We used the model to create geographic information system maps of likely future development based on human population projections to inform complementary landscape analyses underway involving vegetation, habitat, and wildfire interactions. In an example application, we use the model and resulting maps to show the potential impacts of future forest and range land development on mule deer ( Odocoileus hemionus) winter range. Results indicate significant development encroachment and habitat loss already in 2000 with development located along key migration routes and increasing through the projection period to 2040. The example application illustrates a simple way for policymakers and public lands managers to combine existing data and preliminary model outputs to begin to consider the potential effects of development on future landscape conditions.

Assessing the Impact of Disturbance on Carbon Stocks in Western Forests using Remote Sensing and Forest Inventory Data

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A. P.; Landguth, E.; Holden, Z. A.

2014-12-01

Forest disturbances have important impacts on regional and global carbon-climate feedbacks. Tree mortality resulting from disturbance can cause large areas to transition from carbon (C) sinks to C sources. Although severe acute disturbance, such as fire, has been quantified extensively in the literature, the impacts of disturbance that cause more spatially heterogeneous, gradual, mortality, such as beetle kill, are more difficult to quantify and have not been studied as extensively. Combining a 13 year time series of 250 meter, 16-day, MODIS Enhanced Vegetation Index (EVI) data with field data on insect mortality collected by the U.S. Forest Service Forest Inventory and Analysis (FIA) program, we have produced large-scale maps of dead woody biomass resulting from insect epidemics. Using a change detection algorithm, we were able to determine the timing and severity of changes in EVI due to insect epidemics across the western United States. A model was created to predict biomass based on EVI and a variety of environmental variables. Using the difference between post- and pre-outbreak EVI values, we were able to estimate the loss of biomass during insect outbreaks. These biomass data were then converted to carbon as a percentage of dry biomass using the Jenkins equations. This spatially explicit map of C currently stored in beetle kill wood will allow us to assess the vulnerability of this C to re-entering the atmosphere as CO2 via combustion or decomposition.

Bayesian methods to estimate urban growth potential

USGS Publications Warehouse

Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.

2017-01-01

Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

NASA Astrophysics Data System (ADS)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We quantify the sensitivity of calibration equations relating GEDI lidar structure measurements and AGBD to these factors at a range of spatial scales (0.0625-1ha) and discuss the implications for the expanding use of existing in situ ground plot data by GEDI.

Social and Environmental Impacts of Forest Management Certification in Indonesia

PubMed Central

Miteva, Daniela A.; Loucks, Colby J.; Pattanayak, Subhrendu K.

2015-01-01

In response to unsustainable timber production in tropical forest concessions, voluntary forest management certification programs such as the Forest Stewardship Council (FSC) have been introduced to improve environmental, social, and economic performance over existing management practices. However, despite the proliferation of forest certification over the past two decades, few studies have evaluated its effectiveness. Using temporally and spatially explicit village-level data on environmental and socio-economic indicators in Kalimantan (Indonesia), we evaluate the performance of the FSC-certified timber concessions compared to non-certified logging concessions. Employing triple difference matching estimators, we find that between 2000 and 2008 FSC reduced aggregate deforestation by 5 percentage points and the incidence of air pollution by 31%. It had no statistically significant impacts on fire incidence or core areas, but increased forest perforation by 4 km2 on average. In addition, we find that FSC reduced firewood dependence (by 33%), respiratory infections (by 32%) and malnutrition (by 1 person) on average. By conducting a rigorous statistical evaluation of FSC certification in a biodiversity hotspot such as Indonesia, we provide a reference point and offer methodological and data lessons that could aid the design of ongoing and future evaluations of a potentially critical conservation policy. PMID:26132491

High-Resolution Forest Carbon Monitoring and Modeling: Continued Prototype Development and Deployment Across The Tri-state Area (MD, PA, DE), USA

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Birdsey, R.; Campbell, E.; Dolan, K. A.; Dubayah, R.; Escobar, V. M.; Finley, A. O.; Flanagan, S.; Huang, W.; Johnson, K.; Lister, A.; ONeil-Dunne, J.; Sepulveda Carlo, E.; Zhao, M.

2017-12-01

Local, national and international programs have increasing need for precise and accurate estimates of forest carbon and structure to support greenhouse gas reduction plans, climate initiatives, and other international climate treaty frameworks. In 2010 Congress directed NASA to initiate research towards the development of Carbon Monitoring Systems (CMS). In response, our team has worked to develop a robust, replicable framework to produce maps of high-resolution carbon stocks and future carbon sequestration potential. High-resolution (30m) maps of carbon stocks and uncertainty were produced by linking national 1m-resolution imagery and existing wall-to-wall airborne lidar to spatially explicit in-situ field observations such as the USFS Forest Inventory and Analysis (FIA) network. These same data, characterizing forest extent and vertical structure, were used to drive a prognostic ecosystem model to predict carbon fluxes and carbon sequestration potential at unprecedented spatial resolution and scale (90m), more than 100,000 times the spatial resolution of standard global models. Through project development, the domain of this research has expanded from two counties in MD (2,181 km2), to the entire state (32,133 km2), to the tri-state region of MD, PA, and DE (157,868 km2), covering forests in four major USDA ecological providences (Eastern Broadleaf, Northeastern Mixed, Outer Coastal Plain, and Central Appalachian). Across the region, we estimate 694 Tg C (14 DE, 113 MD, 567 PA) in above ground biomass, and estimate a carbon sequestration potential more than twice that amount. Empirical biomass products enhance existing approaches though high resolution accounting for trees outside traditional forest maps. Modeling products move beyond traditional MRV, and map future afforestation and reforestation potential for carbon at local actionable spatial scales. These products are relevant to multiple stakeholder needs in the region as discussed through the Tri-sate Working Group, and are actively being used to inform the state of MD's Greenhouse Gas Reduction Act. The approach is scalable, and provides a protoype framework for application in other domains and for future spaceborne lidar missions.

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes

NASA Astrophysics Data System (ADS)

Naudts, K.; Ryder, J.; McGrath, M. J.; Otto, J.; Chen, Y.; Valade, A.; Bellasen, V.; Berhongaray, G.; Bönisch, G.; Campioli, M.; Ghattas, J.; De Groote, T.; Haverd, V.; Kattge, J.; MacBean, N.; Maignan, F.; Merilä, P.; Penuelas, J.; Peylin, P.; Pinty, B.; Pretzsch, H.; Schulze, E. D.; Solyga, D.; Vuichard, N.; Yan, Y.; Luyssaert, S.

2015-07-01

Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.

Spatiotemporal patterns of fire-induced forest mortality in boreal regions and its potential drivers

NASA Astrophysics Data System (ADS)

Yang, J.; Tian, H.; Pan, S.; Hansen, M.; Wang, Y.

2017-12-01

Wildfire is the major natural disturbance in boreal forests, which have substantially affected various biological and biophysical processes. Although a few previous studies examined fire severity in boreal regions and reported a higher fire-induced forest mortality in boreal North America than in boreal Eurasia, it remains unclear how this mortality changes over time and how environmental factors affect the temporal dynamics of mortality at a large scale. By using a combination of multiple sources of satellite observations, we investigate the spatiotemporal patterns of fire-induced forest mortality in boreal regions, and examine the contributions of potential drivers. Our results show that forest composition is the key factor influencing the spatial variations of fire mortality across ecoregions. For the temporal variations, we find that the late-season burning was associated with higher fire intensity, which lead to greater forest mortality than the early-season burning. Forests burned in the warm and dry years had greater mortality than those burned in the cool and wet years. Our findings suggest that climate warming and drying not only stimulated boreal fire frequency, but also enhanced fire severity and forest mortality. Due to the significant effects of forest mortality on vegetation structure and ecosystem carbon dynamics, the spatiotemporal changes of fire-induced forest mortality should be explicitly considered to better understand fire impacts on regional and global climate change.

Disturbances catalyze the adaptation of forest ecosystems to changing climate conditions

PubMed Central

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2016-01-01

The rates of anthropogenic climate change substantially exceed those at which forest ecosystems – dominated by immobile, long-lived organisms – are able to adapt. The resulting maladaptation of forests has potentially detrimental effects on ecosystem functioning. Furthermore, as many forest-dwelling species are highly dependent on the prevailing tree species, a delayed response of the latter to a changing climate can contribute to an extinction debt and mask climate-induced biodiversity loss. However, climate change will likely also intensify forest disturbances. Here, we tested the hypothesis that disturbances foster the reorganization of ecosystems and catalyze the adaptation of forest composition to climate change. Our specific objectives were (i) to quantify the rate of autonomous forest adaptation to climate change, (ii) examine the role of disturbance in the adaptation process, and (iii) investigate spatial differences in climate-induced species turnover in an unmanaged mountain forest landscape (Kalkalpen National Park, Austria). Simulations with a process-based forest landscape model were performed for 36 unique combinations of climate and disturbance scenarios over 1000 years. We found that climate change strongly favored European beech and oak species (currently prevailing in mid- to low-elevation areas), with novel species associations emerging on the landscape. Yet, it took between 357 and 706 years before the landscape attained a dynamic equilibrium with the climate system. Disturbances generally catalyzed adaptation and decreased the time needed to attain equilibrium by up to 211 years. However, while increasing disturbance frequency and severity accelerated adaptation, increasing disturbance size had the opposite effect. Spatial analyses suggest that particularly the lowest and highest elevation areas will be hotspots of future species change. We conclude that the growing maladaptation of forests to climate and the long lead times of autonomous adaptation need to be considered more explicitly in the ongoing efforts to safeguard biodiversity and ecosystem services provisioning. PMID:27633953

Changes in Patch Features May Exacerbate or Compensate for the Effect of Habitat Loss on Forest Bird Populations

PubMed Central

Magrach, Ainhoa; Larrinaga, Asier R.; Santamaría, Luis

2011-01-01

One and a half centuries after Darwin visited Chiloe Island, what he described as “…an island covered by one great forest…” has lost two-thirds of its forested areas. At this biodiversity hotspot, forest surface is becoming increasingly fragmented due to unregulated logging, clearing for pastures and replacement by exotic tree plantations. Decrease in patch size, increased isolation and “edge effects” can influence the persistence of forest species in remnant fragments. We assessed how these variables affect local density for six forest birds, chosen to include the most important seed dispersers (four species) and bird pollinators (two species, one of which acts also as seed disperser), plus the most common insectivore (Aphrastura spinicauda). Based on cue-count point surveys (8 points per fragment), we estimated bird densities for each species in 22 forest fragments of varying size, shape, isolation and internal-habitat structure (e.g. tree size and epiphyte cover). Bird densities varied with fragment connectivity (three species) and shape (three species), but none of the species was significantly affected by patch size. Satellite image analyses revealed that, from 1985 to 2008, forested area decreased by 8.8% and the remaining forest fragments became 16% smaller, 58–73% more isolated and 11–50% more regular. During that period, bird density estimates for the northern part of Chiloé (covering an area of 1214.75 km2) decreased for one species (elaenia), increased for another two (chucao and hummingbird) and did not vary for three (rayadito, thrust and blackbird). For the first three species, changes in patch features respectively exacerbated, balanced and overcame the effects of forest loss on bird population size (landscape-level abundance). Hence, changes in patch features can modulate the effect of habitat fragmentation on forest birds, suggesting that spatial planning (guided by spatially-explicit models) can be an effective tool to facilitate their conservation. PMID:21738723

Changes in patch features may exacerbate or compensate for the effect of habitat loss on forest bird populations.

PubMed

Magrach, Ainhoa; Larrinaga, Asier R; Santamaría, Luis

2011-01-01

One and a half centuries after Darwin visited Chiloe Island, what he described as "…an island covered by one great forest…" has lost two-thirds of its forested areas. At this biodiversity hotspot, forest surface is becoming increasingly fragmented due to unregulated logging, clearing for pastures and replacement by exotic tree plantations. Decrease in patch size, increased isolation and "edge effects" can influence the persistence of forest species in remnant fragments. We assessed how these variables affect local density for six forest birds, chosen to include the most important seed dispersers (four species) and bird pollinators (two species, one of which acts also as seed disperser), plus the most common insectivore (Aphrastura spinicauda). Based on cue-count point surveys (8 points per fragment), we estimated bird densities for each species in 22 forest fragments of varying size, shape, isolation and internal-habitat structure (e.g. tree size and epiphyte cover). Bird densities varied with fragment connectivity (three species) and shape (three species), but none of the species was significantly affected by patch size. Satellite image analyses revealed that, from 1985 to 2008, forested area decreased by 8.8% and the remaining forest fragments became 16% smaller, 58-73% more isolated and 11-50% more regular. During that period, bird density estimates for the northern part of Chiloé (covering an area of 1214.75 km(2)) decreased for one species (elaenia), increased for another two (chucao and hummingbird) and did not vary for three (rayadito, thrust and blackbird). For the first three species, changes in patch features respectively exacerbated, balanced and overcame the effects of forest loss on bird population size (landscape-level abundance). Hence, changes in patch features can modulate the effect of habitat fragmentation on forest birds, suggesting that spatial planning (guided by spatially-explicit models) can be an effective tool to facilitate their conservation.

Disturbances catalyze the adaptation of forest ecosystems to changing climate conditions.

PubMed

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2017-01-01

The rates of anthropogenic climate change substantially exceed those at which forest ecosystems - dominated by immobile, long-lived organisms - are able to adapt. The resulting maladaptation of forests has potentially detrimental effects on ecosystem functioning. Furthermore, as many forest-dwelling species are highly dependent on the prevailing tree species, a delayed response of the latter to a changing climate can contribute to an extinction debt and mask climate-induced biodiversity loss. However, climate change will likely also intensify forest disturbances. Here, we tested the hypothesis that disturbances foster the reorganization of ecosystems and catalyze the adaptation of forest composition to climate change. Our specific objectives were (i) to quantify the rate of autonomous forest adaptation to climate change, (ii) examine the role of disturbance in the adaptation process, and (iii) investigate spatial differences in climate-induced species turnover in an unmanaged mountain forest landscape (Kalkalpen National Park, Austria). Simulations with a process-based forest landscape model were performed for 36 unique combinations of climate and disturbance scenarios over 1000 years. We found that climate change strongly favored European beech and oak species (currently prevailing in mid- to low-elevation areas), with novel species associations emerging on the landscape. Yet, it took between 357 and 706 years before the landscape attained a dynamic equilibrium with the climate system. Disturbances generally catalyzed adaptation and decreased the time needed to attain equilibrium by up to 211 years. However, while increasing disturbance frequency and severity accelerated adaptation, increasing disturbance size had the opposite effect. Spatial analyses suggest that particularly the lowest and highest elevation areas will be hotspots of future species change. We conclude that the growing maladaptation of forests to climate and the long lead times of autonomous adaptation need to be considered more explicitly in the ongoing efforts to safeguard biodiversity and ecosystem services provisioning. © 2016 John Wiley & Sons Ltd.

Response of Sierra Nevada forests to projected climate-wildfire interactions.

PubMed

Liang, Shuang; Hurteau, Matthew D; Westerling, Anthony LeRoy

2017-05-01

Climate influences forests directly and indirectly through disturbance. The interaction of climate change and increasing area burned has the potential to alter forest composition and community assembly. However, the overall forest response is likely to be influenced by species-specific responses to environmental change and the scale of change in overstory species cover. In this study, we sought to quantify how projected changes in climate and large wildfire size would alter forest communities and carbon (C) dynamics, irrespective of competition from nontree species and potential changes in other fire regimes, across the Sierra Nevada, USA. We used a species-specific, spatially explicit forest landscape model (LANDIS-II) to evaluate forest response to climate-wildfire interactions under historical (baseline) climate and climate projections from three climate models (GFDL, CCSM3, and CNRM) forced by a medium-high emission scenario (A2) in combination with corresponding climate-specific large wildfire projections. By late century, we found modest changes in the spatial distribution of dominant species by biomass relative to baseline, but extensive changes in recruitment distribution. Although forest recruitment declined across much of the Sierra, we found that projected climate and wildfire favored the recruitment of more drought-tolerant species over less drought-tolerant species relative to baseline, and this change was greatest at mid-elevations. We also found that projected climate and wildfire decreased tree species richness across a large proportion of the study area and transitioned more area to a C source, which reduced landscape-level C sequestration potential. Our study, although a conservative estimate, suggests that by late century, forest community distributions may not change as intact units as predicted by biome-based modeling, but are likely to trend toward simplified community composition as communities gradually disaggregate and the least tolerant species are no longer able to establish. The potential exists for substantial community composition change and forest simplification beyond this century. © 2016 John Wiley & Sons Ltd.

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.

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

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

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

DOE PAGES

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...

2016-07-25

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

PubMed

Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

2018-02-01

The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly, bivariate tests provide evidence of scale-dependence among predictors, such that remotely-sensed variables significantly predict plant richness only at spatial scales that sufficiently subsume geolocational imprecision between remotely-sensed and field data, and best align with stand components including plant size and density, as well as canopy gaps and understory growth patterns. Beyond their insights into the scale-dependent patterns and drivers of plant diversity in Piedmont forests, these results highlight the potential of remotely-sensible essential biodiversity variables for mapping and monitoring landscape floristic diversity from air- and space-borne platforms. © 2017 by the Ecological Society of America.

How does vegetation structure influence woodpeckers and secondary cavity nesting birds in African cork oak forest?

NASA Astrophysics Data System (ADS)

Segura, Amalia

2017-08-01

The Great Spotted Woodpecker provides important information about the status of a forest in terms of structure and age. As a primary cavity creator, it provides small-medium size cavities for passerines. However, despite its interest as an ecosystem engineer, studies of this species in Africa are scarce. Here, spatially explicit predictive models were used to investigate how forest structural variables are related to both the Great Spotted Woodpecker and secondary cavity nesting birds in Maamora cork oak forest (northwest Morocco). A positive association between Great Spotted Woodpecker and both dead-tree density and large mature trees (>60 cm dbh) was found. This study area, Maamora, has an old-growth forest structure incorporating a broad range of size and condition of live and dead trees, favouring Great Spotted Woodpecker by providing high availability of foraging and excavating sites. Secondary cavity nesting birds, represented by Great Tit, African Blue Tit, and Hoopoe, were predicted by Great Spotted Woodpecker detections. The findings suggest that the conservation of the Maamora cork oak forest could be key to maintaining these hole-nesting birds. However, this forest is threatened by forestry practises and livestock overgrazing and the challenge is therefore to find sustainable management strategies that ensure conservation while allowing its exploitation.

Facing uncertainty in ecosystem services-based resource management.

PubMed

Grêt-Regamey, Adrienne; Brunner, Sibyl H; Altwegg, Jürg; Bebi, Peter

2013-09-01

The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ecosystem Processes at the Watershed Scale: Stability and Resilience of Catchment Spatial Structure and Function to Disturbance

NASA Astrophysics Data System (ADS)

Baron, J.; Mast, A.; Clow, D. W.; Wetherbee, G. A.

2014-12-01

Ecohydrological systems evolve spontaneously in response to geologic, hydroclimate and biodiversity drivers. The stability and resilience of these systems to multiple disturbances can be addressed over specific temporal extents, potentially embedded within long term transience in response to geologic or climate change. The limits of ecohydrological resilience of system state in terms of vegetation canopy and soil catenae and the space/time distribution of water, carbon and nutrient cycling is determined by a set of critical feedbacks and potential substitutions of plant functional forms in response to disturbance. The ability of forest systems to return to states functionally similar to states prior to major disturbance, or combinations of multiple disturbances, is a critical question given increasing hydroclimate extremes, biological invasions, and human disturbance. Over the past century, forest landscape ecological patterns appear to have the ability to recover from significant disturbance and re-establish similar hydrological and ecological function in humid, biodiverse regions such as the southern Appalachians, and potentially drier forest ecosystems. Understanding and prediction of past and future long term dynamics requires explicit representation of spatial and temporal feedbacks and dependencies between hydrological, ecosystem and geomorphic processes, and the spatial pattern of species or plant functional type (PFT). Comprehensive models of watershed ecohydrological resilience requires careful balance between the level of process and parameter detail between the interacting components, relative to the structure, organization, space and time scales of the landscape.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

PubMed

Sonter, Laura J; Watson, Keri B; Wood, Spencer A; Ricketts, Taylor H

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

Social-value maps for Arapaho, Roosevelt, Medicine Bow, Routt, and White River National Forests, Colorado and Wyoming

USGS Publications Warehouse

Ancona, Zachary H.; Semmens, Darius J.; Sherrouse, Benson C.

2016-03-25

Executive SummaryThe continued pressures of population growth on the life-sustaining, economic, and cultural ecosystem services provided by our national forests, particularly those located near rapidly growing urban areas, present ongoing challenges to forest managers. Achieving an effective assessment of these ecosystem services includes a proper accounting of the ecological, economic, and social values attributable to them. However, assessments of ecosystem goods and services notably lack information describing the spatial distribution and relative intensity of social values—the perceived, nonmarket values derived particularly from cultural ecosystem services. A geographic information system (GIS) tool developed to fill this need, Social Values for Ecosystem Services (SolVES; http://solves.cr.usgs.gov), now provides the capability to generate social-value maps at a range of spatial scales. This report presents some of the methods behind SolVES, procedures needed to apply the tool, the first formal map products resulting from its application at a regional scale, and a discussion of the management implications associated with this type of information.In this study, we use SolVES to identify the location and relative intensity of social values as derived from survey responses gathered from residents living in counties adjacent to Arapaho, Roosevelt, Medicine Bow, Routt, and White River National Forests. The results, presented as a series of social-value maps, represent the first publicly available spatial data on social-value intensity for the southern Rocky Mountain region. Our analysis identified high-value areas for social values including aesthetic, biodiversity, and life sustaining within wilderness areas. Other values, like recreation, show high-value areas both within wilderness and throughout the general forest areas, which can be attributed to people using the forests for a diverse set of recreational activities. The economic social-value type was lower within wilderness areas, which was an expected outcome because of the restrictions inside wilderness areas that preclude resource extraction, development, and motorized or mechanized recreation.Providing spatially explicit social-value information collected from residents in counties adjacent to these national forests can assist in facilitating the U.S. Department of Agriculture Forest Service’s Multiple-Use Sustained-Yield Act of 1960 (16 U.S.C. 528) note and the 2012 Forest Service Planning Rule (36 CFR Part 219), which encourage public participation in planning and management. By making these maps available to the public, we hope to encourage exploration of potential uses of these data for resource management and planning.

Landsat phenological metrics and their relation to aboveground carbon in the Brazilian Savanna.

PubMed

Schwieder, M; Leitão, P J; Pinto, J R R; Teixeira, A M C; Pedroni, F; Sanchez, M; Bustamante, M M; Hostert, P

2018-05-15

The quantification and spatially explicit mapping of carbon stocks in terrestrial ecosystems is important to better understand the global carbon cycle and to monitor and report change processes, especially in the context of international policy mechanisms such as REDD+ or the implementation of Nationally Determined Contributions (NDCs) and the UN Sustainable Development Goals (SDGs). Especially in heterogeneous ecosystems, such as Savannas, accurate carbon quantifications are still lacking, where highly variable vegetation densities occur and a strong seasonality hinders consistent data acquisition. In order to account for these challenges we analyzed the potential of land surface phenological metrics derived from gap-filled 8-day Landsat time series for carbon mapping. We selected three areas located in different subregions in the central Brazil region, which is a prominent example of a Savanna with significant carbon stocks that has been undergoing extensive land cover conversions. Here phenological metrics from the season 2014/2015 were combined with aboveground carbon field samples of cerrado sensu stricto vegetation using Random Forest regression models to map the regional carbon distribution and to analyze the relation between phenological metrics and aboveground carbon. The gap filling approach enabled to accurately approximate the original Landsat ETM+ and OLI EVI values and the subsequent derivation of annual phenological metrics. Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%). Comparable relationships between remote sensing based land surface phenological metrics and aboveground carbon were observed in all study areas. Aboveground carbon distributions could be mapped and revealed comprehensible spatial patterns. Phenological metrics were derived from 8-day Landsat time series with a spatial resolution that is sufficient to capture gradual changes in carbon stocks of heterogeneous Savanna ecosystems. These metrics revealed the relationship between aboveground carbon and the phenology of the observed vegetation. Our results suggest that metrics relating to the seasonal minimum and maximum values were the most influential variables and bear potential to improve spatially explicit mapping approaches in heterogeneous ecosystems, where both spatial and temporal resolutions are critical.

Environmental Costs of Government-Sponsored Agrarian Settlements in Brazilian Amazonia.

PubMed

Schneider, Maurício; Peres, Carlos A

2015-01-01

Brazil has presided over the most comprehensive agrarian reform frontier colonization program on Earth, in which ~1.2 million settlers have been translocated by successive governments since the 1970's, mostly into forested hinterlands of Brazilian Amazonia. These settlements encompass 5.3% of this ~5 million km2 region, but have contributed with 13.5% of all land conversion into agropastoral land uses. The Brazilian Federal Agrarian Agency (INCRA) has repeatedly claimed that deforestation in these areas largely predates the sanctioned arrival of new settlers. Here, we quantify rates of natural vegetation conversion across 1911 agrarian settlements allocated to 568 Amazonian counties and compare fire incidence and deforestation rates before and after the official occupation of settlements by migrant farmers. The timing and spatial distribution of deforestation and fires in our analysis provides irrefutable chronological and spatially explicit evidence of agropastoral conversion both inside and immediately outside agrarian settlements over the last decade. Deforestation rates are strongly related to local human population density and road access to regional markets. Agrarian settlements consistently accelerated rates of deforestation and fires, compared to neighboring areas outside settlements, but within the same counties. Relocated smallholders allocated to forest areas undoubtedly operate as pivotal agents of deforestation, and most of the forest clearance occurs in the aftermath of government-induced migration.

Environmental Costs of Government-Sponsored Agrarian Settlements in Brazilian Amazonia

PubMed Central

2015-01-01

Brazil has presided over the most comprehensive agrarian reform frontier colonization program on Earth, in which ~1.2 million settlers have been translocated by successive governments since the 1970’s, mostly into forested hinterlands of Brazilian Amazonia. These settlements encompass 5.3% of this ~5 million km2 region, but have contributed with 13.5% of all land conversion into agropastoral land uses. The Brazilian Federal Agrarian Agency (INCRA) has repeatedly claimed that deforestation in these areas largely predates the sanctioned arrival of new settlers. Here, we quantify rates of natural vegetation conversion across 1911 agrarian settlements allocated to 568 Amazonian counties and compare fire incidence and deforestation rates before and after the official occupation of settlements by migrant farmers. The timing and spatial distribution of deforestation and fires in our analysis provides irrefutable chronological and spatially explicit evidence of agropastoral conversion both inside and immediately outside agrarian settlements over the last decade. Deforestation rates are strongly related to local human population density and road access to regional markets. Agrarian settlements consistently accelerated rates of deforestation and fires, compared to neighboring areas outside settlements, but within the same counties. Relocated smallholders allocated to forest areas undoubtedly operate as pivotal agents of deforestation, and most of the forest clearance occurs in the aftermath of government-induced migration. PMID:26247467

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

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

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Whole-system carbon balance for a regional temperate forest in Northern Wisconsin, USA

NASA Astrophysics Data System (ADS)

Peckham, S. D.; Gower, S. T.

2010-12-01

The whole-system (biological + industrial) carbon (C) balance was estimated for the Chequamegon-Nicolet National Forest (CNNF), a temperate forest covering 600,000 ha in Northern Wisconsin, USA. The biological system was modeled using a spatially-explicit version of the ecosystem process model Biome-BGC. The industrial system was modeled using life cycle inventory (LCI) models for wood and paper products. Biome-BGC was used to estimate net primary production, net ecosystem production (NEP), and timber harvest (H) over the entire CNNF. The industrial carbon budget (Ci) was estimated by applying LCI models of CO2 emissions resulting from timber harvest and production of specific wood and paper products in the CNNF region. In 2009, simulated NEP of the CNNF averaged 3.0 tC/ha and H averaged 0.1 tC/ha. Despite model uncertainty, the CNNF region is likely a carbon sink (NEP - Ci > 0), even when CO2 emissions from timber harvest and production of wood and paper products are included in the calculation of the entire forest system C budget.

Agricultural Intensification in the Brazilian Agricultural-Forest Frontier: Land Use Responses to Development and Conservation Policy

NASA Astrophysics Data System (ADS)

Garrett, R.; Koh, I.; le Polain de Waroux, Y.; Lambin, E.; Kastens, J.; Brown, J. C.

2017-12-01

Agricultural expansion, extensive cattle ranching, and deforestation remain pressing challenges for sustainable development and climate mitigation throughout South America. In response to these challenges, national and local governments, as well as private and non-governmental actors have developed new forest conservation governance mechanisms. The objective of this study is to better understand how conservation policies interact with supply chain development to influence land use. In particular, we endeavor to understand the timing and spatial patterns of crop and cattle intensification, an understudied phenomenon that is critical to understanding the future of agricultural-forest frontiers and the impacts of conservation policies. We focus on Mato Grosso, the largest soy and cattle producing state in Brazil, which spans the Cerrado and Amazon biomes and has experienced higher levels of deforestation for agricultural expansion than any other state globally over the last decade. Using a newly created spatially explicit data set of land use intensity, supply chain development, and forest policy, we find that agricultural intensification is occurring rapidly in the region, but is only partially driven by changes in conservation policies. The intensification of cattle production is the result of improvements in deforestation monitoring, penalties, and enforcement, and increased land scarcity. Crop intensification, in contrast, preceded increases in conservation restrictions, and is associated with the positive spillovers resulting from agribusiness agglomeration and development. These results suggest that intensification is not a foregone conclusion of increasing forest conservation restrictions, but is highly dependent on wider development processes. A combined effort to direct agribusiness development away from forest regions via tax credits and subsidized credit, when applied in concert with stringent conservation requirements, could help promote intensification and reduce deforestation leakage.

Habitat monitoring and conservation prioritisation of protected areas in Western Ghats, Kerala, India.

PubMed

Athira, K; Reddy, C Sudhakar; Saranya, K R L; Joseph, Shijo; Jaishanker, R

2017-06-01

Spatially explicit approach is essential to prioritise the ecosystems for biodiversity conservation. In the present study, the conservation status of 20 protected areas of the Western Ghats of Kerala, India, was analysed based on long-term changes in forests (1975-1985-1995-2005-2013), landscape level changes in fragmentation and forest fires (2005-2015). This study has shown that a significant forest loss occurred in protected areas before declaration. Idukki is one of the major protected areas which showed a drastic reduction (18.83%) in its forest cover. During 1985-1995, Periyar tiger reserve had lost 24.19 km 2 core 3 forest area followed by Peppara (18.54 km 2 ), Parambikulam (17.93 km 2 ), Chimmony (17.71 km 2 ), Peechi-Vazhani (12.31 km 2 ) and Neyyar (11.67 km 2 ). An area of 71.33 km 2 of the protected area was affected by fires in 2014. Overall protected area-wise decadal analysis indicates Periyar has the highest number of fire incidences followed by Wayanad, Kurinjimala, Silent Valley and Eravikulam. Disturbances in the form of fires and fragmentation still exist and may have significant conservation threat to flora and fauna. Among protected areas, many are having a probability to go under threat or dynamic stage. Chinnar, Thattekkad and Kurinjimala sanctuaries are representing high levels of vulnerability, or they are near to decline stage. Habitat level monitoring of the anthropogenic disturbances can be efficiently useful for the strategic conservation planning. The present study has provided geospatial database on spatial patterns of deforestation, fragmentation and forest fires in protected areas of Kerala. Conservation prioritization approach based on these parameters will be useful for the strategic planning in the state of Kerala.

Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

USGS Publications Warehouse

Ji, Lei; Wylie, Bruce K.; Brown, Dana R. N.; Peterson, Birgit E.; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.

2015-01-01

Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

Spatial and Temporal Patterns of Unburned Areas within Fire Perimeters in the Northwestern United States from 1984 to 2014

NASA Astrophysics Data System (ADS)

Meddens, A. J.; Kolden, C.; Lutz, J. A.; Abatzoglou, J. T.; Hudak, A. T.

2016-12-01

Recently, there has been concern about increasing extent and severity of wildfires across the globe given rapid climate change. Areas that do not burn within fire perimeters can act as fire refugia, providing (1) protection from the detrimental effects of the fire, (2) seed sources, and (3) post-fire habitat on the landscape. However, recent studies have mainly focused on the higher end of the burn severity spectrum whereas the lower end of the burn severity spectrum has been largely ignored. We developed a spatially explicit database for 2,200 fires across the inland northwestern USA, delineating unburned areas within fire perimeters from 1984 to 2014. We used 1,600 Landsat scenes with one or two scenes before and one or two scenes after the fires to capture the unburned proportion of the fire. Subsequently, we characterized the spatial and temporal patterns of unburned areas and related the unburned proportion to interannual climate variability. The overall classification accuracy detecting unburned locations was 89.2% using a 10-fold cross-validation classification tree approach in combination with 719 randomly located field plots. The unburned proportion ranged from 2% to 58% with an average of 19% for a select number of fires. We find that using both an immediate post-fire image and a one-year post fire image improves classification accuracy of unburned islands over using just a single post-fire image. The spatial characteristics of the unburned islands differ between forested and non-forested regions with a larger amount of unburned area within non-forest. In addition, we show trends of unburned proportion related primarily to concurrent climatic drought conditions across the entire region. This database is important for subsequent analyses of fire refugia prioritization, vegetation recovery studies, ecosystem resilience, and forest management to facilitate unburned islands through fuels breaks, prescribed burning, and fire suppression strategies.

Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

PubMed

Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

2000-06-01

An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances.

Nationwide classification of forest types of India using remote sensing and GIS.

PubMed

Reddy, C Sudhakar; Jha, C S; Diwakar, P G; Dadhwal, V K

2015-12-01

India, a mega-diverse country, possesses a wide range of climate and vegetation types along with a varied topography. The present study has classified forest types of India based on multi-season IRS Resourcesat-2 Advanced Wide Field Sensor (AWiFS) data. The study has characterized 29 land use/land cover classes including 14 forest types and seven scrub types. Hybrid classification approach has been used for the classification of forest types. The classification of vegetation has been carried out based on the ecological rule bases followed by Champion and Seth's (1968) scheme of forest types in India. The present classification scheme has been compared with the available global and national level land cover products. The natural vegetation cover was estimated to be 29.36% of total geographical area of India. The predominant forest types of India are tropical dry deciduous and tropical moist deciduous. Of the total forest cover, tropical dry deciduous forests occupy an area of 2,17,713 km(2) (34.80%) followed by 2,07,649 km(2) (33.19%) under tropical moist deciduous forests, 48,295 km(2) (7.72%) under tropical semi-evergreen forests and 47,192 km(2) (7.54%) under tropical wet evergreen forests. The study has brought out a comprehensive vegetation cover and forest type maps based on inputs critical in defining the various categories of vegetation and forest types. This spatially explicit database will be highly useful for the studies related to changes in various forest types, carbon stocks, climate-vegetation modeling and biogeochemical cycles.

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest.

PubMed

Rother, Débora Cristina; Pizo, Marco Aurélio; Siqueira, Tadeu; Rodrigues, Ricardo Ribeiro; Jordano, Pedro

2015-01-01

Several factors decrease plant survival throughout their lifecycles. Among them, seed dispersal limitation may play a major role by resulting in highly aggregated (contagious) seed and seedling distributions entailing increased mortality. The arrival of seeds, furthermore, may not match suitable environments for seed survival and, consequently, for seedling establishment. In this study, we investigated spatio-temporal patterns of seed and seedling distribution in contrasting microhabitats (bamboo and non-bamboo stands) from the Brazilian Atlantic Forest. Spatial distribution patterns, spatial concordance between seed rain and seedling recruitment between subsequent years in two fruiting seasons (2004-2005 and 2007-2009), and the relation between seeds and seedlings with environmental factors were examined within a spatially-explicit framework. Density and species richness of both seeds and seedlings were randomly distributed in non-bamboo stands, but showed significant clustering in bamboo stands. Seed and seedling distributions showed across-year inconsistency, suggesting a marked spatial decoupling of the seed and seedling stages. Generalized linear mixed effects models indicated that only seed density and seed species richness differed between stand types while accounting for variation in soil characteristics. Our analyses provide evidence of marked recruitment limitation as a result of the interplay between biotic and abiotic factors. Because bamboo stands promote heterogeneity in the forest, they are important components of the landscape. However, at high densities, bamboos may limit recruitment for the plant community by imposing marked discordances of seed arrival and early seedling recruitment.

Integrating spatial modeling, climate change scenarios, invasive species risk, and public perceptions to inform sustainable management in mixed hemlock-hardwood forests in Maine

NASA Astrophysics Data System (ADS)

Dunckel, Kathleen Lois

Introduced invasive pests and climate change are perhaps the most important and persistent catalyst for changes in forest composition. Infestation and outbreak of the hemlock woolly adelgid (HWA, Adelges tsugae) along the eastern coast of the USA, has led to widespread loss of hemlock (Tsuga canadensis (L.) Carr.), and a shift in tree species composition towards hardwood stands. Maine's forest dominated landscape and position at the leading edge of the HWA invasion provides an excellent opportunity to inform sustainable forest management (SFM) practices by using spatially explicit models to predict current tree species distribution, future range shifts, and solicit broad based feedback from Maine residents about forest management goals and preferences. This paper describes an interdisciplinary study of the ecological and social implications of changes in mixed northern hardwood forests due to disturbance. A two stage mapping approach was used where presence/absence of eastern hemlock is predicted with an overall accuracy of 85% and the continuous distribution (% basal area) was predicted with an accuracy of 83%. Given the importance of climate variables in predicting eastern hemlock, forecasts of future range shifts are possible using data generated through climate scenarios. The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset was used to model future shifts in the geographic range of eastern hemlock throughout the state of Maine. The results clearly describe a significant shift in eastern hemlock range with gains in total geographic area that is suitable habitat. Sustaining forest systems across the landscape requires not only ecological knowledge, but also the integration of multiple socio-economic criteria as well, including data obtained through broad-based public participation approaches. Here, 3000 Maine residents were surveyed and asked how they: (1) value local forests; (2) view forest management goals and threats to forest ecosystems; and (3) evaluate alternative treatment options for the control of invasive species - in this case, HWA. Results suggest that despite Maine's historic dependence on forest products, resident values regarding forests are complex and display agreement with both psycho-spiritual and anthropocentric motivations.

Geography of Global Forest Carbon Stocks & Dynamics

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Yu, Y.; Xu, L.; Yang, Y.; Fore, A.; Ganguly, S.; Nemani, R. R.; Zhang, G.; Lefsky, M. A.; Sun, G.; Woodall, C. W.; Naesset, E.; Seibt, U. H.

2014-12-01

Spatially explicit distribution of carbon stocks and dynamics in global forests can greatly reduce the uncertainty in the terrestrial portion of the global carbon cycle by improving estimates of emissions and uptakes from land use activities, and help with green house gas inventory at regional and national scales. Here, we produce the first global distribution of carbon stocks in living woody biomass at ~ 100 m (1-ha) resolution for circa 2005 from a combination of satellite observations and ground inventory data. The total carbon stored in live woody biomass is estimated to be 337 PgC with 258 PgC in aboveground and 79 PgC in roots, and partitioned globally in boreal (20%), tropical evergreen (50%), temperate (12%), and woodland savanna and shrublands (15%). We use a combination of satellite observations of tree height, remote sensing data on deforestation and degradation to quantify the dynamics of these forests at the biome level globally and provide geographical distribution of carbon storage dynamics in terms sinks and sources globally.

The Environmental Legacy of Modern Tropical Deforestation.

PubMed

Rosa, Isabel M D; Smith, Matthew J; Wearn, Oliver R; Purves, Drew; Ewers, Robert M

2016-08-22

Tropical deforestation has caused a significant share of carbon emissions and species losses, but historical patterns have rarely been explicitly considered when estimating these impacts [1]. A deforestation event today leads to a time-delayed future release of carbon, from the eventual decay either of forest products or of slash left at the site [2]. Similarly, deforestation often does not result in the immediate loss of species, and communities may exhibit a process of "relaxation" to their new equilibrium over time [3]. We used a spatially explicit land cover change model [4] to reconstruct the annual rates and spatial patterns of tropical deforestation that occurred between 1950 and 2009 in the Amazon, in the Congo Basin, and across Southeast Asia. Using these patterns, we estimated the resulting gross vegetation carbon emissions [2, 5] and species losses over time [6]. Importantly, we accounted for the time lags inherent in both the release of carbon and the extinction of species. We show that even if deforestation had completely halted in 2010, time lags ensured there would still be a carbon emissions debt of at least 8.6 petagrams, equivalent to 5-10 years of global deforestation, and an extinction debt of more than 140 bird, mammal, and amphibian forest-specific species, which if paid, would increase the number of 20(th)-century extinctions in these groups by 120%. Given the magnitude of these debts, commitments to reduce emissions and biodiversity loss are unlikely to be realized without specific actions that directly address this damaging environmental legacy. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Topographic controls on overland flow generation in a forest - An ensemble tree approach

NASA Astrophysics Data System (ADS)

Loos, Martin; Elsenbeer, Helmut

2011-10-01

SummaryOverland flow is an important hydrological pathway in many forests of the humid tropics. Its generation is subject to topographic controls at differing spatial scales. Our objective was to identify such controls on the occurrence of overland flow in a lowland tropical rainforest. To this end, we installed 95 overland flow detectors (OFDs) in four nested subcatchments of the Lutzito catchment on Barro Colorado Island, Panama, and monitored the frequency of overland flow occurrence during 18 rainfall events at each OFD location temporal frequency. For each such location, we derived three non-digital terrain attributes and 17 digital ones, of which 15 were based on Digital Elevation Models (DEMs) of three different resolutions. These attributes then served as input into a Random Forest ensemble tree model to elucidate the importance and partial and joint dependencies of topographic controls for overland flow occurrence. Lutzito features a high median temporal frequency in overland flow occurrence of 0.421 among OFD locations. However, spatial temporal frequencies of overland flow occurrence vary strongly among these locations and the subcatchments of Lutzito catchment. This variability is best explained by (1) microtopography, (2) coarse terrain sloping and (3) various measures of distance-to-channel, with the contribution of all other terrain attributes being small. Microtopographic features such as concentrated flowlines and wash areas produce highest temporal frequencies, whereas the occurrence of overland flow drops sharply for flow distances and terrain sloping beyond certain threshold values. Our study contributes to understanding both the spatial controls on overland flow generation and the limitations of terrain attributes for the spatially explicit prediction of overland flow frequencies.

Mixing Carrots and Sticks to Conserve Forests in the Brazilian Amazon: A Spatial Probabilistic Modeling Approach

PubMed Central

Börner, Jan; Marinho, Eduardo; Wunder, Sven

2015-01-01

Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to compensate farmers for conservation actions through economic incentives, such as payments for environmental services, at various administrative levels. We develop a spatially explicit simulation model for deforestation decisions in response to policy incentives and disincentives. The model builds on elements of optimal enforcement theory and introduces the notion of imperfect payment contract enforcement in the context of avoided deforestation. We implement the simulations using official deforestation statistics and data collected from field-based forest law enforcement operations in the Amazon region. We show that a large-scale integration of payments with the existing regulatory enforcement strategy involves a tradeoff between the cost-effectiveness of forest conservation and landholder incomes. Introducing payments as a complementary policy measure increases policy implementation cost, reduces income losses for those hit hardest by law enforcement, and can provide additional income to some land users. The magnitude of the tradeoff varies in space, depending on deforestation patterns, conservation opportunity and enforcement costs. Enforcement effectiveness becomes a key determinant of efficiency in the overall policy mix. PMID:25650966

Mixing carrots and sticks to conserve forests in the Brazilian Amazon: a spatial probabilistic modeling approach.

PubMed

Börner, Jan; Marinho, Eduardo; Wunder, Sven

2015-01-01

Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to compensate farmers for conservation actions through economic incentives, such as payments for environmental services, at various administrative levels. We develop a spatially explicit simulation model for deforestation decisions in response to policy incentives and disincentives. The model builds on elements of optimal enforcement theory and introduces the notion of imperfect payment contract enforcement in the context of avoided deforestation. We implement the simulations using official deforestation statistics and data collected from field-based forest law enforcement operations in the Amazon region. We show that a large-scale integration of payments with the existing regulatory enforcement strategy involves a tradeoff between the cost-effectiveness of forest conservation and landholder incomes. Introducing payments as a complementary policy measure increases policy implementation cost, reduces income losses for those hit hardest by law enforcement, and can provide additional income to some land users. The magnitude of the tradeoff varies in space, depending on deforestation patterns, conservation opportunity and enforcement costs. Enforcement effectiveness becomes a key determinant of efficiency in the overall policy mix.

An individual-based growth and competition model for coastal redwood forest restoration

USGS Publications Warehouse

van Mantgem, Phillip J.; Das, Adrian J.

2014-01-01

Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

Negative impacts of high temperatures on growth of black spruce forests intensify with the anticipated climate warming.

PubMed

Girardin, Martin P; Hogg, Edward H; Bernier, Pierre Y; Kurz, Werner A; Guo, Xiao Jing; Cyr, Guillaume

2016-02-01

An increasing number of studies conclude that water limitations and heat stress may hinder the capacity of black spruce (Picea mariana (Mill.) B.S.P.) trees, a dominant species of Canada's boreal forests, to grow and assimilate atmospheric carbon. However, there is currently no scientific consensus on the future of these forests over the next century in the context of widespread climate warming. The large spatial extent of black spruce forests across the Canadian boreal forest and associated variability in climate, demography, and site conditions pose challenges for projecting future climate change responses. Here we provide an evaluation of the impacts of climate warming and drying, as well as increasing [CO2 ], on the aboveground productivity of black spruce forests across Canada south of 60°N for the period 1971 to 2100. We use a new extensive network of tree-ring data obtained from Canada's National Forest Inventory, spatially explicit simulations of net primary productivity (NPP) and its drivers, and multivariate statistical modeling. We found that soil water availability is a significant driver of black spruce interannual variability in productivity across broad areas of the western to eastern Canadian boreal forest. Interannual variability in productivity was also found to be driven by autotrophic respiration in the warmest regions. In most regions, the impacts of soil water availability and respiration on interannual variability in productivity occurred during the phase of carbohydrate accumulation the year preceding tree-ring formation. Results from projections suggest an increase in the importance of soil water availability and respiration as limiting factors on NPP over the next century due to warming, but this response may vary to the extent that other factors such as carbon dioxide fertilization, and respiration acclimation to high temperature, contribute to dampening these limitations. © 2015 Her Majesty the Queen in Right of Canada. Reproduced with the permission of the Minister of Natural Resources Canada.

A neighborhood analysis of the consequences of Quercus suber decline for regeneration dynamics in Mediterranean forests.

PubMed

Ibáñez, Beatriz; Gómez-Aparicio, Lorena; Stoll, Peter; Ávila, José M; Pérez-Ramos, Ignacio M; Marañón, Teodoro

2015-01-01

In forests, the vulnerable seedling stage is largely influenced by the canopy, which modifies the surrounding environment. Consequently, any alteration in the characteristics of the canopy, such as those promoted by forest dieback, might impact regeneration dynamics. Our work analyzes the interaction between canopy neighbors and seedlings in Mediterranean forests affected by the decline of their dominant species (Quercus suber). Our objective was to understand how the impacts of neighbor trees and shrubs on recruitment could affect future dynamics of these declining forests. Seeds of the three dominant tree species (Quercus suber, Olea europaea and Quercus canariensis) were sown in six sites during two consecutive years. Using a spatially-explicit, neighborhood approach we developed models that explained the observed spatial variation in seedling emergence, survival, growth and photochemical efficiency as a function of the size, identity, health, abundance and distribution of adult trees and shrubs in the neighborhood. We found strong neighborhood effects for all the performance estimators, particularly seedling emergence and survival. Tree neighbors positively affected emergence, independently of species identity or health. Alternatively, seedling survival was much lower in neighborhoods dominated by defoliated and dead Q. suber trees than in neighborhoods dominated by healthy trees. For the two oak species, these negative effects were consistent over the three years of the experimental seedlings. These results indicate that ongoing changes in species' relative abundance and canopy trees' health might alter the successional trajectories of Mediterranean oak-forests through neighbor-specific impacts on seedlings. The recruitment failure of dominant late-successional oaks in the gaps opened after Q. suber death would indirectly favor the establishment of other coexisting woody species, such as drought-tolerant shrubs. This could lead current forests to shift into open systems with lower tree cover. Adult canopy decline would therefore represent an additional factor threatening the recruitment of Quercus forests worldwide.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Simulating the Effects of Fire on Forests in the Russian Far East: Integrating a Fire Danger Model and the FAREAST Forest Growth Model Across a Complex Landscape

NASA Astrophysics Data System (ADS)

Sherman, N. J.; Loboda, T.; Sun, G.; Shugart, H. H.; Csiszar, I.

2008-12-01

The remaining natural habitat of the critically endangered Amur tiger (Panthera tigris altaica) and Amur leopard (Panthera pardus orientalis) is a vast, biologically and topographically diverse area in the Russian Far East (RFE). Although wildland fire is a natural component of ecosystem functioning in the RFE, severe or repeated fires frequently re-set the process of forest succession, which may take centuries to return the affected forests to the pre-fire state and thus significantly alters habitat quality and long-term availability. The frequency of severe fire events has increased over the last 25 years, leading to irreversible modifications of some parts of the species' habitats. Moreover, fire regimes are expected to continue to change toward more frequent and severe events under the influence of climate change. Here we present an approach to developing capabilities for a comprehensive assessment of potential Amur tiger and leopard habitat availability throughout the 21st century by integrating regionally parameterized fire danger and forest growth models. The FAREAST model is an individual, gap-based model that simulates forest growth in a single location and demonstrates temporally explicit forest succession leading to mature forests. Including spatially explicit information on probabilities of fire occurrence at 1 km resolution developed from the regionally specific remotely -sensed data-driven fire danger model improves our ability to provide realistic long-term projections of potential forest composition in the RFE. This work presents the first attempt to merge the FAREAST model with a fire disturbance model, to validate its outputs across a large region, and to compare it to remotely-sensed data products as well as in situ assessments of forest structure. We ran the FAREAST model at 1,000 randomly selected points within forested areas in the RFE. At each point, the model was calibrated for temperature, precipitation, slope, elevation, and fire probability. The output of the model includes biomass estimates for 44 tree species that occur in the RFE, grouped by genus. We compared the model outputs with land cover classifications derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data and LIDAR-based estimates of biomass across the entire region, and Russian forest inventory records at selected sites. Overall, we find that the FAREAST estimates of forest biomass and general composition are consistent with the observed distribution of forest types.

Simulating the impact of human land use change on forest composition in the Great Plains agroecosystems with the Seedscape model

USGS Publications Warehouse

Easterling, W.E.; Brandle, J.R.; Hays, C.J.; Guo, Q.; Guertin, D.S.

2001-01-01

The expansion and contraction of marginal cropland in the Great Plains often involves small forested strips of land that provide important ecological benefits. The effect of human disturbance on these forests is not well known. Because of their unique structure such forests are not well-represented by forest gap models. In this paper, the development, testing and application of a new model known as Seedscape are described. Seedscape is a modification of the JABOWA-II model, and it uses a spatially-explicit landscape to resolve small-scale features of highly fragmented forests in the eastern Great Plains. It was tested and evaluated with observations from two sites, one in Nebraska and a second in eastern Iowa. Seedscape realistically simulates succession at the Nebraska site, but is less successful at the Iowa site. Seedscape was also applied to the Nebraska site to simulate the effect that varying forest corridor widths, in response to the presumed expansion/contraction of adjacent agricultural land, has on succession properties. Results suggest that small differences in widths have negligible effects on forest composition, but large differences in widths may cause statistically-significant changes in the relative importance of some species. We assert that long-term ecological change in human dominated landscapes is not well understood, in part, because of inadequate modeling techniques. Seedscape provides a much-needed tool for assessing the ecological implications of land use change in forests of predominately agricultural landscapes.

Spatially explicit population estimates for black bears based on cluster sampling

USGS Publications Warehouse

Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

An assessment of forest cover trends in South and North Korea, from 1980 to 2010.

PubMed

Engler, Robin; Teplyakov, Victor; Adams, Jonathan M

2014-01-01

It is generally believed that forest cover in North Korea has undergone a substantial decrease since 1980, while in South Korea, forest cover has remained relatively static during that same period of time. The United Nations Food and Agriculture Organization (FAO) Forest Resources Assessments--based on the reported forest inventories from North and South Korea--suggest a major forest cover decrease in North Korea, but only a slight decrease in South Korea during the last 30 years. In this study, we seek to check and validate those assessments by comparing them to independently derived forest cover maps compiled for three time intervals between 1990 and 2010, as well as to provide a spatially explicit view of forest cover change in the Korean Peninsula since the 1990s. We extracted tree cover data for the Korean Peninsula from existing global datasets derived from satellite imagery. Our estimates, while qualitatively supporting the FAO results, show that North Korea has lost a large number of densely forested areas, and thus in this sense has suffered heavier forest loss than the FAO assessment suggests. Given the limited time interval studied in our assessment, the overall forest loss from North Korea during the whole span of time since 1980 may have been even heavier than in our estimate. For South Korea, our results indicate that the forest cover has remained relatively stable at the national level, but that important variability in forest cover evolution exists at the regional level: While the northern and western provinces show an overall decrease in forested areas, large areas in the southeastern part of the country have increased their forest cover.

Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific.

PubMed

Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

2015-01-01

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires.

Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific

PubMed Central

Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

2015-01-01

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires. PMID:25691965

An Examination of Drought-Induced Hydraulic Stress in Conifer Forests Using a Coupled Ecohydrologic Model.

NASA Astrophysics Data System (ADS)

Simeone, C.; Maneta, M. P.; Holden, Z. A.; Dobrowski, S.; Sala, A.

2017-12-01

Recent studies indicate that increases in drought stress due to climate change will increase forest mortality across the western U.S. Although ecohydrologic models used to study regional hydrologic stress response in forests have made rapid advances in recent years, they often incorporate simplified descriptions of the local hydrology, do not implement an explicit description of plant hydraulics, and do not permit to study the tradeoffs between frequency, intensity, and accumulation of hydrologic stress in vegetation. We use the spatially-distributed, mechanistic ecohydrologic model Ech2o, which effectively captures spatial variations in both hydrology, energy exchanges, and regional climate to simulate high-resolution tree hydraulics, estimating soil and leaf water potential, tree effective water conductance, and percent loss of conductivity in the xylem (PLC) at 250 meter resolution and sub-daily timestep across a topographically complex landscape. Tree hydraulics are simulated assuming a diffusive process in the soil-tree-atmosphere continuum. We use PLC to develop a vegetation dynamic stress index that scales plant-level processes to the landscape scale, and that takes into account the temporal accumulation of instantaneous hydraulic stress, growing season length, frequency and duration of drought periods, and plant drought tolerance. The resulting index is interpreted as the probability of drought induced tree mortality in a given location during the simulated period. We apply this index to regions of Northern Idaho and Western Montana. Results show that drought stress is highly spatially variable, sensitive to local-scale hydrologic and atmospheric conditions, and responsive to the recovery rate from individual hydraulic stress episodes.

Low leopard populations in protected areas of Maputaland: a consequence of poaching, habitat condition, abundance of prey, and a top predator.

PubMed

Ramesh, Tharmalingam; Kalle, Riddhika; Rosenlund, Havard; Downs, Colleen T

2017-03-01

Identifying the primary causes affecting population densities and distribution of flagship species are necessary in developing sustainable management strategies for large carnivore conservation. We modeled drivers of spatial density of the common leopard ( Panthera pardus ) using a spatially explicit capture-recapture-Bayesian approach to understand their population dynamics in the Maputaland Conservation Unit, South Africa. We camera-trapped leopards in four protected areas (PAs) of varying sizes and disturbance levels covering 198 camera stations. Ours is the first study to explore the effects of poaching level, abundance of prey species (small, medium, and large), competitors (lion Panthera leo and spotted hyenas Crocuta crocuta ), and habitat on the spatial distribution of common leopard density. Twenty-six male and 41 female leopards were individually identified and estimated leopard density ranged from 1.6 ± 0.62/100 km 2 (smallest PA-Ndumo) to 8.4 ± 1.03/100 km 2 (largest PA-western shores). Although dry forest thickets and plantation habitats largely represented the western shores, the plantation areas had extremely low leopard density compared to native forest. We found that leopard density increased in areas when low poaching levels/no poaching was recorded in dry forest thickets and with high abundance of medium-sized prey, but decreased with increasing abundance of lion. Because local leopard populations are vulnerable to extinction, particularly in smaller PAs, the long-term sustainability of leopard populations depend on developing appropriate management strategies that consider a combination of multiple factors to maintain their optimal habitats.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media

PubMed Central

Watson, Keri B.; Wood, Spencer A.; Ricketts, Taylor H.

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making. PMID:27611325

Quantifying forest mortality with the remote sensing of snow

NASA Astrophysics Data System (ADS)

Baker, Emily Hewitt

Greenhouse gas emissions have altered global climate significantly, increasing the frequency of drought, fire, and pest-related mortality in forests across the western United States, with increasing area affected each year. Associated changes in forests are of great concern for the public, land managers, and the broader scientific community. These increased stresses have resulted in a widespread, spatially heterogeneous decline of forest canopies, which in turn exerts strong controls on the accumulation and melt of the snowpack, and changes forest-atmosphere exchanges of carbon, water, and energy. Most satellite-based retrievals of summer-season forest data are insufficient to quantify canopy, as opposed to the combination of canopy and undergrowth, since the signals of the two types of vegetation greenness have proven persistently difficult to distinguish. To overcome this issue, this research develops a method to quantify forest canopy cover using winter-season fractional snow covered area (FSCA) data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow covered area and grain size (MODSCAG) algorithm. In areas where the ground surface and undergrowth are completely snow-covered, a pixel comprises only forest canopy and snow. Following a snowfall event, FSCA initially rises, as snow is intercepted in the canopy, and then falls, as snow unloads. A select set of local minima in a winter F SCA timeseries form a threshold where canopy is snow-free, but forest understory is snow-covered. This serves as a spatially-explicit measurement of forest canopy, and viewable gap fraction (VGF) on a yearly basis. Using this method, we determine that MODIS-observed VGF is significantly correlated with an independent product of yearly crown mortality derived from spectral analysis of Landsat imagery at 25 high-mortality sites in northern Colorado. (r =0.96 +/-0.03, p =0.03). Additionally, we determine the lag timing between green-stage tree mortality and needlefall, showing that needlefall occurred an average of 2.6 +/- 1.2 years after green-stage mortality. We relate observed increases in the VGF with crown mortality, showing that a 1% increase in mortality area produces a 0.33 +/- 0.1 % increase in the VGF.

Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Santoro, Maurizio; Carvalhais, Nuno; Wutzler, Thomas; Schepaschenko, Dmitry; Shvidenko, Anatoly; Kompter, Elisabeth; Levick, Shaun; Schmullius, Christiane

2013-04-01

Quantifying the state and the change of the World's forests is crucial because of their ecological, social and economic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon, energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potential to sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annual variability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome this shortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published, up to now there was a lack of similar products covering boreal and temperate forests. Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data for latitudes above 30° N. Utilizing a wood density and a biomass compartment database, a forest carbon density map covering North-America, Europe and Asia with 0.01° resolution could be derived out of this dataset. Allometric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types (broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty estimation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia, Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 - 0.90). Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) for three biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be stored in boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and 14.5 ± 4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer (62.1 ± 20.7 Mg(C)/ha(Forest)) and broadleaf/mixed forests (58.0 ± 22.1 Mg(C)/ha(Forest)), whereas boreal forests have a carbon density of only 40.0 ± 15.4 Mg(C)/ha(Forest). While European forest carbon stocks are relatively small, the carbon density is higher compared to the other continents. The derived biomass map substantially improves the knowledge on the current carbon stocks of the northern-hemispheric boreal and temperate forests, serving as a new benchmark for spatially explicit and consistent biomass mapping with moderate spatial resolution. This product can be of great value for global carbon cycle models as well as national carbon monitoring systems. Further investigations concentrate on improving biomass parameterizations and representations in such kind of models. The presented map will help to improve the simulation of biomass spatial patterns and variability and enables identifying the dominant influential factors like climatic conditions and disturbances.

Effects of Governance on Availability of Land for Agriculture and Conservation in Brazil.

PubMed

Sparovek, Gerd; Barretto, Alberto Giaroli de Oliveira Pereira; Matsumoto, Marcelo; Berndes, Göran

2015-09-01

The 2012 revision of the Brazilian Forest Act changed the relative importance of private and public governance for nature conservation and agricultural production. We present a spatially explicit land-use model for Brazilian agricultural production and nature conservation that considers the spatial distribution of agricultural land suitability, technological and management options, legal command, and control frameworks including the Atlantic Forest Law, the revised Forest Act, and the Amazonian land-titling, "Terra Legal," and also market-driven land use regulations. The model is used to analyze land use allocation under three scenarios with varying priorities among agricultural production and environmental protection objectives. In all scenarios, the legal command and control frameworks were the most important determinants of conservation outcomes, protecting at least 80% of the existing natural vegetation. Situations where such frameworks are not expected to be effective can be identified and targeted for additional conservation (beyond legal requirements) through voluntary actions or self-regulation in response to markets. All scenarios allow for a substantial increase in crop production, using an area 1.5-2.7 times the current cropland area, with much of new cropland occurring on current pastureland. Current public arrangements that promote conservation can, in conjunction with voluntary schemes on private lands where conversion to agriculture is favored, provide important additional nature conservation without conflicting with national agricultural production objectives.

Reconstructing European forest management from 1600 to 2010

NASA Astrophysics Data System (ADS)

McGrath, M. J.; Luyssaert, S.; Meyfroidt, P.; Kaplan, J. O.; Buergi, M.; Chen, Y.; Erb, K.; Gimmi, U.; McInerney, D.; Naudts, K.; Otto, J.; Pasztor, F.; Ryder, J.; Schelhaas, M.-J.; Valade, A.

2015-04-01

European forest use for fuel, timber and food dates back to pre-Roman times. Century-scale ecological processes and their legacy effects require accounting for forest management when studying today's forest carbon sink. Forest management reconstructions that are used to drive land surface models are one way to quantify the impact of both historical and today's large scale application of forest management on today's forest-related carbon sink and surface climate. In this study we reconstruct European forest management from 1600 to 2010 making use of diverse approaches, data sources and assumptions. Between 1600 and 1828, a demand-supply approach was used in which wood supply was reconstructed based on estimates of historical annual wood increment and land cover reconstructions. For the same period demand estimates accounted for the fuelwood needed in households, wood used in food processing, charcoal used in metal smelting and salt production, timber for construction and population estimates. Comparing estimated demand and supply resulted in a spatially explicit reconstruction of the share of forests under coppice, high stand management and forest left unmanaged. For the reconstruction between 1829 and 2010 a supply-driven back-casting method was used. The method used age reconstructions from the years 1950 to 2010 as its starting point. Our reconstruction reproduces the most important changes in forest management between 1600 and 2010: (1) an increase of 593 000 km2 in conifers at the expense of deciduous forest (decreasing by 538 000 km2), (2) a 612 000 km2 decrease in unmanaged forest, (3) a 152 000 km2 decrease in coppice management, (4) a 818 000 km2 increase in high stand management, and (5) the rise and fall of litter raking which at its peak in 1853 removed 50 Tg dry litter per year.

Estimating rainforest biomass stocks and carbon loss from deforestation and degradation in Papua New Guinea 1972-2002: Best estimates, uncertainties and research needs.

PubMed

Bryan, Jane; Shearman, Phil; Ash, Julian; Kirkpatrick, J B

2010-01-01

Reduction of carbon emissions from tropical deforestation and forest degradation is being considered a cost-effective way of mitigating the impacts of global warming. If such reductions are to be implemented, accurate and repeatable measurements of forest cover change and biomass will be required. In Papua New Guinea (PNG), which has one of the world's largest remaining areas of tropical forest, we used the best available data to estimate rainforest carbon stocks, and emissions from deforestation and degradation. We collated all available PNG field measurements which could be used to estimate carbon stocks in logged and unlogged forest. We extrapolated these plot-level estimates across the forested landscape using high-resolution forest mapping. We found the best estimate of forest carbon stocks contained in logged and unlogged forest in 2002 to be 4770 Mt (+/-13%). Our best estimate of gross forest carbon released through deforestation and degradation between 1972 and 2002 was 1178 Mt (+/-18%). By applying a long-term forest change model, we estimated that the carbon loss resulting from deforestation and degradation in 2001 was 53 Mt (+/-18%), rising from 24 Mt (+/-15%) in 1972. Forty-one percent of 2001 emissions resulted from logging, rising from 21% in 1972. Reducing emissions from logging is therefore a priority for PNG. The large uncertainty in our estimates of carbon stocks and fluxes is primarily due to the dearth of field measurements in both logged and unlogged forest, and the lack of PNG logging damage studies. Research priorities for PNG to increase the accuracy of forest carbon stock assessments are the collection of field measurements in unlogged forest and more spatially explicit logging damage studies. Copyright 2009 Elsevier Ltd. All rights reserved.

CDPOP: A spatially explicit cost distance population genetics program

Treesearch

Erin L. Landguth; S. A. Cushman

2010-01-01

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

Environmental drivers of spatial patterns of topsoil nitrogen and phosphorus under monsoon conditions in a complex terrain of South Korea

PubMed Central

Choi, Kwanghun; Spohn, Marie; Park, Soo Jin; Huwe, Bernd; Ließ, Mareike

2017-01-01

Nitrogen (N) and phosphorus (P) in topsoils are critical for plant nutrition. Relatively little is known about the spatial patterns of N and P in the organic layer of mountainous landscapes. Therefore, the spatial distributions of N and P in both the organic layer and the A horizon were analyzed using a light detection and ranging (LiDAR) digital elevation model and vegetation metrics. The objective of the study was to analyze the effect of vegetation and topography on the spatial patterns of N and P in a small watershed covered by forest in South Korea. Soil samples were collected using the conditioned latin hypercube method. LiDAR vegetation metrics, the normalized difference vegetation index (NDVI), and terrain parameters were derived as predictors. Spatial explicit predictions of N/P ratios were obtained using a random forest with uncertainty analysis. We tested different strategies of model validation (repeated 2-fold to 20-fold and leave-one-out cross validation). Repeated 10-fold cross validation was selected for model validation due to the comparatively high accuracy and low variance of prediction. Surface curvature was the best predictor of P contents in the organic layer and in the A horizon, while LiDAR vegetation metrics and NDVI were important predictors of N in the organic layer. N/P ratios increased with surface curvature and were higher on the convex upper slope than on the concave lower slope. This was due to P enrichment of the soil on the lower slope and a more even spatial distribution of N. Our digital soil maps showed that the topsoils on the upper slopes contained relatively little P. These findings are critical for understanding N and P dynamics in mountainous ecosystems. PMID:28837590

Modeling mountain pine beetle disturbance in Glacier National Park using multiple lines of evidence

USGS Publications Warehouse

Assal, Timothy; Sibold, Jason

2013-01-01

Temperate forest ecosystems are subject to various disturbances which contribute to ecological legacies that can have profound effects on the structure of the ecosystem. Impacts of disturbance can vary widely in extent, duration and severity over space and time. Given that global climate change is expected to increase rates of forest disturbance, an understanding of these events are critical in the interpretation of contemporary forest patterns and those of the near future. We seek to understand the impact of the 1970s mountain pine beetle outbreak on the landscape of Glacier National Park and investigate any connection between this event and subsequent decades of extensive wildfire. The lack of spatially explicit data on the mountain pine beetle disturbance represents a major data gap and inhibits our ability to test for correlations between outbreak severity and fire severity. To overcome this challenge, we utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We used historical aerial and landscape photos, reports, aerial survey data, a six year collection of Landsat imagery and abiotic data in combination with regression analysis. The use of remotely sensed data is critical in large areas where subsequent disturbance (fire) has erased some of the evidence from the landscape. Results indicate that this method is successful in capturing the spatial heterogeneity of the outbreak in a topographically complex landscape. Furthermore, this study provides an example on the use of existing data to reduce levels of uncertainty associated with an historic disturbance.

Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

USGS Publications Warehouse

Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

2012-01-01

1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations.

PubMed

Felton, Adam; Ranius, Thomas; Roberge, Jean-Michel; Öhman, Karin; Lämås, Tomas; Hynynen, Jari; Juutinen, Artti; Mönkkönen, Mikko; Nilsson, Urban; Lundmark, Tomas; Nordin, Annika

2017-07-15

A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics - biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Copyright © 2017 Elsevier Ltd. All rights reserved.

A methodological framework to assess the carbon balance of tropical managed forests.

PubMed

Piponiot, Camille; Cabon, Antoine; Descroix, Laurent; Dourdain, Aurélie; Mazzei, Lucas; Ouliac, Benjamin; Rutishauser, Ervan; Sist, Plinio; Hérault, Bruno

2016-12-01

Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions.

Land-use change, deforestation, and peasant farm systems: A case study of Mexico's Southern Yucatan Peninsular Region

NASA Astrophysics Data System (ADS)

Vance, Colin James

This dissertation develops spatially explicit econometric models by linking Thematic Mapper (TM) satellite imagery with household survey data to test behavioral propositions of semi-subsistence farmers in the Southern Yucatan Peninsular Region (SYPR) of Mexico. Covering 22,000 km2, this agricultural frontier contains one of the largest and oldest expanses of tropical forests in the Americas outside of Amazonia. Over the past 30 years, the SYPR has undergone significant land-use change largely owing to the construction of a highway through the region's center in 1967. These landscape dynamics are modeled by exploiting a spatial database linking a time series of TM imagery with socio-economic and geo-referenced land-use data collected from a random sample of 188 farm households. The dissertation moves beyond the existing literature on deforestation in three principal respects. Theoretically, the study develops a non-separable model of land-use that relaxes the assumption of profit maximization almost exclusively invoked in studies of the deforestation issue. The model is derived from a utility-maximizing framework that explicitly incorporates the interdependency of the household's production and consumption choices as these affect the allocation of resources. Methodologically, the study assembles a spatial database that couples satellite imagery with household-level socio-economic data. The field survey protocol recorded geo-referenced land-use data through the use of a geographic positioning system and the creation of sketch maps detailing the location of different uses observed within individual plots. Empirically, the study estimates spatially explicit econometric models of land-use change using switching regressions and duration analysis. A distinguishing feature of these models is that they link the dependent and independent variables at the level of the decision unit, the land manager, thereby capturing spatial and temporal heterogeneity that is otherwise obscured in studies using data aggregated to higher scales of analysis. The empirical findings suggest the potential of various policy initiatives to impede or otherwise alter the pattern of land-cover conversions. In this regard, the study reveals that consideration of missing or thin markets is critical to understanding how farmers in the SYPR reach subsistence and commercial cropping decisions.

Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem

USGS Publications Warehouse

Assal, Timothy J.; Anderson, Patrick J.; Sibold, Jason

2016-01-01

Drought has long been recognized as a driving mechanism in the forests of western North America and drought-induced mortality has been documented across genera in recent years. Given the frequency of these events are expected to increase in the future, understanding patterns of mortality and plant response to severe drought is important to resource managers. Drought can affect the functional, physiological, structural, and demographic properties of forest ecosystems. Remote sensing studies have documented changes in forest properties due to direct and indirect effects of drought; however, few studies have addressed this at local scales needed to characterize highly heterogeneous ecosystems in the forest-shrubland ecotone. We analyzed a 22-year Landsat time series (1985–2012) to determine changes in forest in an area that experienced a relatively dry decade punctuated by two years of extreme drought. We assessed the relationship between several vegetation indices and field measured characteristics (e.g. plant area index and canopy gap fraction) and applied these indices to trend analysis to uncover the location, direction and timing of change. Finally, we assessed the interaction of climate and topography by forest functional type. The Normalized Difference Moisture Index (NDMI), a measure of canopy water content, had the strongest correlation with short-term field measures of plant area index (R2 = 0.64) and canopy gap fraction (R2 = 0.65). Over the entire time period, 25% of the forested area experienced a significant (p-value < 0.05) negative trend in NDMI, compared to less than 10% in a positive trend. Coniferous forests were more likely to be associated with a negative NDMI trend than deciduous forest. Forests on southern aspects were least likely to exhibit a negative trend while north aspects were most prevalent. Field plots with a negative trend had a lower live density, and higher amounts of standing dead and down trees compared to plots with no trend. Our analysis identifies spatially explicit patterns of long-term trends anchored with ground based evidence to highlight areas of forest that are resistant, persistent or vulnerable to severe drought. The results provide a long-term perspective for the resource management of this area and can be applied to similar ecosystems throughout western North America.

Incorporating explicit geospatial data shows more species at risk of extinction than the current Red List

PubMed Central

Ocampo-Peñuela, Natalia; Jenkins, Clinton N.; Vijay, Varsha; Li, Binbin V.; Pimm, Stuart L.

2016-01-01

The IUCN (International Union for Conservation of Nature) Red List classifies species according to their risk of extinction, informing global to local conservation decisions. Unfortunately, important geospatial data do not explicitly or efficiently enter this process. Rapid growth in the availability of remotely sensed observations provides fine-scale data on elevation and increasingly sophisticated characterizations of land cover and its changes. These data readily show that species are likely not present within many areas within the overall envelopes of their distributions. Additionally, global databases on protected areas inform how extensively ranges are protected. We selected 586 endemic and threatened forest bird species from six of the world’s most biodiverse and threatened places (Atlantic Forest of Brazil, Central America, Western Andes of Colombia, Madagascar, Sumatra, and Southeast Asia). The Red List deems 18% of these species to be threatened (15 critically endangered, 29 endangered, and 64 vulnerable). Inevitably, after refining ranges by elevation and forest cover, ranges shrink. Do they do so consistently? For example, refined ranges of critically endangered species might reduce by (say) 50% but so might the ranges of endangered, vulnerable, and nonthreatened species. Critically, this is not the case. We find that 43% of species fall below the range threshold where comparable species are deemed threatened. Some 210 bird species belong in a higher-threat category than the current Red List placement, including 189 species that are currently deemed nonthreatened. Incorporating readily available spatial data substantially increases the numbers of species that should be considered at risk and alters priority areas for conservation. PMID:28861465

Incorporating explicit geospatial data shows more species at risk of extinction than the current Red List.

PubMed

Ocampo-Peñuela, Natalia; Jenkins, Clinton N; Vijay, Varsha; Li, Binbin V; Pimm, Stuart L

2016-11-01

The IUCN (International Union for Conservation of Nature) Red List classifies species according to their risk of extinction, informing global to local conservation decisions. Unfortunately, important geospatial data do not explicitly or efficiently enter this process. Rapid growth in the availability of remotely sensed observations provides fine-scale data on elevation and increasingly sophisticated characterizations of land cover and its changes. These data readily show that species are likely not present within many areas within the overall envelopes of their distributions. Additionally, global databases on protected areas inform how extensively ranges are protected. We selected 586 endemic and threatened forest bird species from six of the world's most biodiverse and threatened places (Atlantic Forest of Brazil, Central America, Western Andes of Colombia, Madagascar, Sumatra, and Southeast Asia). The Red List deems 18% of these species to be threatened (15 critically endangered, 29 endangered, and 64 vulnerable). Inevitably, after refining ranges by elevation and forest cover, ranges shrink. Do they do so consistently? For example, refined ranges of critically endangered species might reduce by (say) 50% but so might the ranges of endangered, vulnerable, and nonthreatened species. Critically, this is not the case. We find that 43% of species fall below the range threshold where comparable species are deemed threatened. Some 210 bird species belong in a higher-threat category than the current Red List placement, including 189 species that are currently deemed nonthreatened. Incorporating readily available spatial data substantially increases the numbers of species that should be considered at risk and alters priority areas for conservation.

Long-term scenarios of the invasive black cherry in pine-oak forest: Impact of regeneration success

NASA Astrophysics Data System (ADS)

Vanhellemont, Margot; Baeten, Lander; Verbeeck, Hans; Hermy, Martin; Verheyen, Kris

2011-05-01

The spread of invasive tree species in forests can be slow because of their long life span and the lag phases that may occur during the invasion process. Models of forest succession are a useful tool to explore how these invasive species might affect long-term forest development. We used the spatially explicit individual tree model SORTIE-ND to gain insight into the long-term development of a gap-dependent invasive tree species, Prunus serotina, in a pine-oak forest on sandy soil, the forest type in which P. serotina occurs most often in its introduced range. Forest inventory data, tree ring data, and photographs of the tree crowns were collected in a forest reserve in the Netherlands, characterized by high game densities. The collected data were then combined with data from literature to parameterize the model. We ran the model for two different scenarios in order to evaluate the impact of differences in the regeneration success of the native Quercus robur and the invasive P. serotina. The outcome of the simulations shows two differing courses of forest development. The invasive P. serotina became the dominant species when the regeneration of Q. robur was hindered, e.g., because of high herbivore densities. When both Q. robur and P. serotina were able to regenerate, Q. robur became the most abundant species in the long-term. We hypothesize that the relatively short life span of P. serotina may preclude its dominance if other long-lived tree species are present and able to regenerate.

Asymmetric competition causes multimodal size distributions in spatially structured populations

PubMed Central

Velázquez, Jorge; Allen, Robert B.; Coomes, David A.; Eichhorn, Markus P.

2016-01-01

Plant sizes within populations often exhibit multimodal distributions, even when all individuals are the same age and have experienced identical conditions. To establish the causes of this, we created an individual-based model simulating the growth of trees in a spatially explicit framework, which was parametrized using data from a long-term study of forest stands in New Zealand. First, we demonstrate that asymmetric resource competition is a necessary condition for the formation of multimodal size distributions within cohorts. By contrast, the legacy of small-scale clustering during recruitment is transient and quickly overwhelmed by density-dependent mortality. Complex multi-layered size distributions are generated when established individuals are restricted in the spatial domain within which they can capture resources. The number of modes reveals the effective number of direct competitors, while the separation and spread of modes are influenced by distances among established individuals. Asymmetric competition within local neighbourhoods can therefore generate a range of complex size distributions within even-aged cohorts. PMID:26817778

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India

PubMed Central

Sarkar, Mriganka Shekhar; Johnson, Jeyaraj A.; Sen, Subharanjan

2017-01-01

Background Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals’ ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger (Panthera tigris), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. Methods We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly’s selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D2 method and the Boyce index. Results There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Discussion Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve. PMID:29114438

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India.

PubMed

Sarkar, Mriganka Shekhar; Krishnamurthy, Ramesh; Johnson, Jeyaraj A; Sen, Subharanjan; Saha, Goutam Kumar

2017-01-01

Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals' ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger ( Panthera tigris ), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly's selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D 2 method and the Boyce index. There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

Drought drove forest decline and dune building in eastern upper Michigan, USA, as the upper Great Lakes became closed basins

USGS Publications Warehouse

Loope, Walter L.; Loope, Henry M.; Goble, Ronald J.; Fisher, Timothy G.; Lytle, David E.; Legg, Robert J.; Wysocki, Douglas A.; Hanson, Paul R.; Young, Aaron R.

2012-01-01

Current models of landscape response to Holocene climate change in midcontinent North America largely reconcile Earth orbital and atmospheric climate forcing with pollen-based forest histories on the east and eolian chronologies in Great Plains grasslands on the west. However, thousands of sand dunes spread across 12,000 km2 in eastern upper Michigan (EUM), more than 500 km east of the present forest-prairie ecotone, present a challenge to such models. We use 65 optically stimulated luminescence (OSL) ages on quartz sand deposited in silt caps (n = 8) and dunes (n = 57) to document eolian activity in EUM. Dune building was widespread ca. 10–8 ka, indicating a sharp, sustained decline in forest cover during that period. This decline was roughly coincident with hydrologic closure of the upper Great Lakes, but temporally inconsistent with most pollen-based models that imply canopy closure throughout the Holocene. Early Holocene forest openings are rarely recognized in pollen sums from EUM because faint signatures of non-arboreal pollen are largely obscured by abundant and highly mobile pine pollen. Early Holocene spikes in nonarboreal pollen are recorded in cores from small ponds, but suggest only a modest extent of forest openings. OSL dating of dune emplacement provides a direct, spatially explicit archive of greatly diminished forest cover during a very dry climate in eastern midcontinent North America ca. 10–8 ka.

Evaluating mechanisms of diversification in a Guineo-Congolian tropical forest frog using demographic model selection.

PubMed

Portik, Daniel M; Leaché, Adam D; Rivera, Danielle; Barej, Michael F; Burger, Marius; Hirschfeld, Mareike; Rödel, Mark-Oliver; Blackburn, David C; Fujita, Matthew K

2017-10-01

The accumulation of biodiversity in tropical forests can occur through multiple allopatric and parapatric models of diversification, including forest refugia, riverine barriers and ecological gradients. Considerable debate surrounds the major diversification process, particularly in the West African Lower Guinea forests, which contain a complex geographic arrangement of topographic features and historical refugia. We used genomic data to investigate alternative mechanisms of diversification in the Gaboon forest frog, Scotobleps gabonicus, by first identifying population structure and then performing demographic model selection and spatially explicit analyses. We found that a majority of population divergences are best explained by allopatric models consistent with the forest refugia hypothesis and involve divergence in isolation with subsequent expansion and gene flow. These population divergences occurred simultaneously and conform to predictions based on climatically stable regions inferred through ecological niche modelling. Although forest refugia played a prominent role in the intraspecific diversification of S. gabonicus, we also find evidence for potential interactions between landscape features and historical refugia, including major rivers and elevational barriers such as the Cameroonian Volcanic Line. We outline the advantages of using genomewide variation in a model-testing framework to distinguish between alternative allopatric hypotheses, and the pitfalls of limited geographic and molecular sampling. Although phylogeographic patterns are often species-specific and related to life-history traits, additional comparative studies incorporating genomic data are necessary for separating shared historical processes from idiosyncratic responses to environmental, climatic and geological influences on diversification. © 2017 John Wiley & Sons Ltd.

A thirty year, fine-scale, characterization of area burned in Canadian forests shows evidence of regionally increasing trends in the last decade

PubMed Central

2018-01-01

Fire as a dominant disturbance has profound implications on the terrestrial carbon cycle. We present the first ever multi-decadal, spatially-explicit, 30 meter assessment of fire regimes across the forested ecoregions of Canada at an annual time-step. From 1985 to 2015, 51 Mha burned, impacting over 6.5% of forested ecosystems. Mean annual area burned was 1,651,818 ha and varied markedly (σ = 1,116,119), with 25% of the total area burned occurring in three years: 1989, 1995, and 2015. Boreal forest types contained 98% of the total area burned, with the conifer-dominated Boreal Shield containing one-third of all burned area. While results confirm no significant national trend in burned area for the period of 1985 to 2015, a significant national increasing trend (α = 0.05) of 11% per year was evident for the past decade (2006 to 2015). Regionally, a significant increasing trend in total burned area from 1985 to 2015 was observed in the Montane Cordillera (2.4% increase per year), while the Taiga Plains and Taiga Shield West displayed significant increasing trends from 2006 to 2015 (26.1% and 12.7% increases per year, respectively). The Atlantic Maritime, which had the lowest burned area of all ecozones (0.01% burned per year), was the only ecozone to display a significant negative trend (2.4% decrease per year) from 1985 to 2015. Given the century-long fire return intervals in many of these ecozones, and large annual variability in burned area, short-term trends need to be interpreted with caution. Additional interpretive cautions are related to year used for trend initiation and the nature and extents of spatial regionalizations used for summarizing findings. The results of our analysis provide a baseline for monitoring future national and regional trends in burned area and offer spatially and temporally detailed insights to inform science, policy, and management. PMID:29787562

A thirty year, fine-scale, characterization of area burned in Canadian forests shows evidence of regionally increasing trends in the last decade.

PubMed

Coops, Nicholas C; Hermosilla, Txomin; Wulder, Michael A; White, Joanne C; Bolton, Douglas K

2018-01-01

Fire as a dominant disturbance has profound implications on the terrestrial carbon cycle. We present the first ever multi-decadal, spatially-explicit, 30 meter assessment of fire regimes across the forested ecoregions of Canada at an annual time-step. From 1985 to 2015, 51 Mha burned, impacting over 6.5% of forested ecosystems. Mean annual area burned was 1,651,818 ha and varied markedly (σ = 1,116,119), with 25% of the total area burned occurring in three years: 1989, 1995, and 2015. Boreal forest types contained 98% of the total area burned, with the conifer-dominated Boreal Shield containing one-third of all burned area. While results confirm no significant national trend in burned area for the period of 1985 to 2015, a significant national increasing trend (α = 0.05) of 11% per year was evident for the past decade (2006 to 2015). Regionally, a significant increasing trend in total burned area from 1985 to 2015 was observed in the Montane Cordillera (2.4% increase per year), while the Taiga Plains and Taiga Shield West displayed significant increasing trends from 2006 to 2015 (26.1% and 12.7% increases per year, respectively). The Atlantic Maritime, which had the lowest burned area of all ecozones (0.01% burned per year), was the only ecozone to display a significant negative trend (2.4% decrease per year) from 1985 to 2015. Given the century-long fire return intervals in many of these ecozones, and large annual variability in burned area, short-term trends need to be interpreted with caution. Additional interpretive cautions are related to year used for trend initiation and the nature and extents of spatial regionalizations used for summarizing findings. The results of our analysis provide a baseline for monitoring future national and regional trends in burned area and offer spatially and temporally detailed insights to inform science, policy, and management.

Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

NASA Astrophysics Data System (ADS)

He, Hongxing; Meyer, Astrid; Jansson, Per-Erik; Svensson, Magnus; Rütting, Tobias; Klemedtsson, Leif

2018-02-01

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models.

In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period.

The nonlim approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.

Application of the environmentally sensitive forest growth and mortality submodel, ESGM, for estimating the historic and future forest carbon budget for the Sooke Lake Watershed, British Columbia.

NASA Astrophysics Data System (ADS)

Trofymow, J. A.; Hember, R.; Smiley, B. P.; Morken, S.; Kurz, W. A.

2016-12-01

Forest resource managers require knowledge of how natural disturbances, harvest, land-use change, and climate change affect carbon (C) budgets of complex landscapes. In this study, a retrospective (1911-2012) forest C budget for the 8500 ha Sooke Lake watershed was developed based on forest inventories, disturbance, and stream monitoring data using the Canadian Forest Service's spatially-explicit Generic Carbon Budget Model (GCBM). This standard version of GCBM used species-specific volume-over-age curves and site indices to determine tree growth and thus does not explicitly account for environmental factors (climate, CO2, N deposition) that may affect trees and net ecosystem production (NEP). Therefore, a new submodel was developed for GCBM, ESGM, which uses empirical equations to account for influences of 8 environmental factors on tree growth and mortality, based on analysis of multi-decadal data from 19,777 field plots from western North America. Annual environmental variables were prepared (1910-2012) for input to GCBMesgm and temperature effects on decay rates were turned on in the GCBM soil submodel. In response to fires, harvesting, planting, and deforestation for drinking water reservoir expansions, the standard GCBM run showed over 100 years (1911, 1940, 1991, 2012) aboveground biomass C (262, 189, 148, 177 MgC/ha) and NEP (0.6, -1.3, 0.8, 2.3 Mg C/ha/yr) declined and then increased as harvest and deforestation ceased in 2002. From 1.5 -6.5% of terrestrial humified soil C losses (30,640 Mg C/100 yrs) were estimated to have been exported as dissolved organic carbon. Assuming no future disturbances, the standard GCBM run indicates NEP will peak at 2.64 MgC/ha/yr in 2024 and biomass C reach 1910 levels by 2075. Comparisons will be made between standard GCBM and GCBMesgmruns of the C budget for the historic period and for future climate scenarios (baseline, RCP4.5 and RCP8.5) from the CanESM2 GCM, to explore the potential implications of environmental change for future watershed management.

Developing Spatially Explicit Habitat Models for Grassland Bird Conservation Planning in the Prairie Pothole Region of North Dakota

Treesearch

Neal D. Niemuth; Michael E. Estey; Charles R. Loesch

2005-01-01

Conservation planning for birds is increasingly focused on landscapes. However, little spatially explicit information is available to guide landscape-level conservation planning for many species of birds. We used georeferenced 1995 Breeding Bird Survey (BBS) data in conjunction with land-cover information to develop a spatially explicit habitat model predicting the...

Urban forest ecosystem analysis using fused airborne hyperspectral and lidar data

NASA Astrophysics Data System (ADS)

Alonzo, Mike Gerard

Urban trees are strategically important in a city's effort to mitigate their carbon footprint, heat island effects, air pollution, and stormwater runoff. Currently, the most common method for quantifying urban forest structure and ecosystem function is through field plot sampling. However, taking intensive structural measurements on private properties throughout a city is difficult, and the outputs from sample inventories are not spatially explicit. The overarching goal of this dissertation is to develop methods for mapping urban forest structure and function using fused hyperspectral imagery and waveform lidar data at the individual tree crown scale. Urban forest ecosystem services estimated using the USDA Forest Service's i-Tree Eco (formerly UFORE) model are based largely on tree species and leaf area index (LAI). Accordingly, tree species were mapped in my Santa Barbara, California study area for 29 species comprising >80% of canopy. Crown-scale discriminant analysis methods were introduced for fusing Airborne Visible Infrared Imaging Spectrometry (AVIRIS) data with a suite of lidar structural metrics (e.g., tree height, crown porosity) to maximize classification accuracy in a complex environment. AVIRIS imagery was critical to achieving an overall species-level accuracy of 83.4% while lidar data was most useful for improving the discrimination of small and morphologically unique species. LAI was estimated at both the field-plot scale using laser penetration metrics and at the crown scale using allometry. Agreement of the former with photographic estimates of gap fraction and the latter with allometric estimates based on field measurements was examined. Results indicate that lidar may be used reasonably to measure LAI in an urban environment lacking in continuous canopy and characterized by high species diversity. Finally, urban ecosystem services such as carbon storage and building energy-use modification were analyzed through combination of aforementioned methods and the i-Tree Eco modeling framework. The remote sensing methods developed in this dissertation will allow researchers to more precisely constrain urban ecosystem spatial analyses and equip cities to better manage their urban forest resource.

Evaluation of climate-related carbon turnover processes in global vegetation models for boreal and temperate forests.

PubMed

Thurner, Martin; Beer, Christian; Ciais, Philippe; Friend, Andrew D; Ito, Akihiko; Kleidon, Axel; Lomas, Mark R; Quegan, Shaun; Rademacher, Tim T; Schaphoff, Sibyll; Tum, Markus; Wiltshire, Andy; Carvalhais, Nuno

2017-08-01

Turnover concepts in state-of-the-art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation-based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation-based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation-based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large-scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Assessing bioenergy harvest risks: Geospatially explicit tools for maintaining soil productivity in western US forests

Treesearch

Mark Kimsey; Deborah Page-Dumroese; Mark Coleman

2011-01-01

Biomass harvesting for energy production and forest health can impact the soil resource by altering inherent chemical, physical and biological properties. These impacts raise concern about damaging sensitive forest soils, even with the prospect of maintaining vigorous forest growth through biomass harvesting operations. Current forest biomass harvesting research...

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

DTIC Science & Technology

2015-08-01

21  Figure 4. Data-based proportion of DDD , DDE and DDT in total DDx in fish and sediment by... DDD dichlorodiphenyldichloroethane DDE dichlorodiphenyldichloroethylene DDT dichlorodiphenyltrichloroethane DoD Department of Defense ERM... DDD ) at the other site. The spatially-explicit model consistently predicts tissue concentrations that closely match both the average and the

Tropical forest landscape dynamics: Population consequences for neotropical lianas, genus Passiflora

NASA Astrophysics Data System (ADS)

Plowes, Robert Merrick

Treefall gaps in rainforest landscapes play a crucial role in providing opportunities for establishment and growth of rare, light-demanding plants such as Passifora vines in Corcovado rainforests, Costa Rica. This study considers the interplay of landscape dynamics with plant life history traits and strategies in an ephemeral patch network. In Chapter One, I show how patch quality dynamics and propagule dispersal affect colonization of treefall gaps by Passifora vitifolia. Recruitment required high patch quality, exceeding 3 hours of sunlight and patches closed after about 6 years. Colonization by seed dispersal (80%) was constrained by patch quality and isolation, while clonal growth from dormant plants (20%) was limited to rare adjacent patches. Since patch turnover is critical in these systems, Chapter Two is focused on factors affecting canopy structure. I showed that prior landuse altered the dynamics of frequent, small-scale disturbances during succession following a single, large deforestation event. Here, I used Landsat subpixel analysis, aerial photographs and field surveys to demonstrate major changes in dynamics of regenerating canopies following release from agricultural activity in 1975. Little work has considered the role of life history traits in persistence of patchy populations, and so in Chapter Three I asked what life history strategies are used by 9 Passiflora species that occur in these transient forest gaps. Although Passiflora species exhibited differences in dormancy or dispersal strategies, abundance was not associated with any one strategy. Elasticities of vital rates (stasis, growth and fecundity) of P. vitifolia differed empirically in old growth and regenerating forests. To explore population responses to changes in landscape parameters or life history strategies, I created a spatially-explicit individual-based model. Simulations indicate that plant types with a dormancy phase have a greater suite of responses since they persist after patch extinction with potential to contribute later through both sexual and asexual dispersal. Plants that rely only on high dispersal were extinction prone in low connectivity landscapes. This novel approach of jointly analyzing spatially-explicit patch parameters and life history traits offers a comprehensive framework for further understanding the effects of patch dynamics on populations.

Quantifying home range habitat requirements for bobcats (Lynx rufus) in Vermont, USA

USGS Publications Warehouse

Donovan, Therese; Freeman, Mark; Abouelezz, Hanem; Royar, Kim; Howard, Alan D.; Mickey, R.

2011-01-01

We demonstrate how home range and habitat use analysis can inform landscape-scale conservation planning for the bobcat, Lynx rufus, in Vermont USA. From 2005 to 2008, we outfitted fourteen bobcats with GPS collars that collected spatially explicit locations from individuals every 4 h for 3–4 months. Kernel home range techniques were used to estimate home range size and boundaries, and to quantify the utilization distribution (UD), which is a spatially explicit, topographic mapping of how different areas within the home range are used. We then used GIS methods to quantify both biotic (e.g. habitat types, stream density) and abiotic (e.g. slope) resources within each bobcat’s home range. Across bobcats, upper 20th UD percentiles (core areas) had 18% less agriculture, 42% less development, 26% more bobcat habitat (shrub, deciduous, coniferous forest, and wetland cover types), and 33% lower road density than lower UD percentiles (UD valleys). For each bobcat, we used Akaike’s Information Criterion (AIC) to evaluate and compare 24 alternative Resource Utilization Functions (hypotheses) that could explain the topology of the individual’s UD. A model-averaged population-level Resource Utilization Function suggested positive responses to shrub, deciduous, coniferous forest, and wetland cover types within 1 km of a location, and negative responses to roads and mixed forest cover types within 1 km of a location. Applying this model-averaged function to each pixel in the study area revealed habitat suitability for bobcats across the entire study area, with suitability scores ranging between −1.69 and 1.44, where higher values were assumed to represent higher quality habitat. The southern Champlain Valley, which contained ample wetland and shrub habitat, was a concentrated area of highly suitable habitat, while areas at higher elevation areas were less suitable. Female bobcat home ranges, on average, had an average habitat suitability score of near 0, indicating that home ranges consisted of both beneficial and detrimental habitat types. We discuss the application of habitat suitability mapping and home range requirements for bobcat conservation and landscape scale management.

Quantifying home range habitat requirements for bobcats (Lynx rufus) in Vermont, USA

USGS Publications Warehouse

Donovan, T.M.; Freeman, M.; Abouelezz, H.; Royar, Kim; Howard, A.; Mickey, R.

2011-01-01

We demonstrate how home range and habitat use analysis can inform landscape-scale conservation planning for the bobcat, Lynx rufus, in Vermont USA. From 2005 to 2008, we outfitted fourteen bobcats with GPS collars that collected spatially explicit locations from individuals every 4. h for 3-4. months. Kernel home range techniques were used to estimate home range size and boundaries, and to quantify the utilization distribution (UD), which is a spatially explicit, topographic mapping of how different areas within the home range are used. We then used GIS methods to quantify both biotic (e.g. habitat types, stream density) and abiotic (e.g. slope) resources within each bobcat's home range. Across bobcats, upper 20th UD percentiles (core areas) had 18% less agriculture, 42% less development, 26% more bobcat habitat (shrub, deciduous, coniferous forest, and wetland cover types), and 33% lower road density than lower UD percentiles (UD valleys). For each bobcat, we used Akaike's Information Criterion (AIC) to evaluate and compare 24 alternative Resource Utilization Functions (hypotheses) that could explain the topology of the individual's UD. A model-averaged population-level Resource Utilization Function suggested positive responses to shrub, deciduous, coniferous forest, and wetland cover types within 1. km of a location, and negative responses to roads and mixed forest cover types within 1. km of a location. Applying this model-averaged function to each pixel in the study area revealed habitat suitability for bobcats across the entire study area, with suitability scores ranging between -1.69 and 1.44, where higher values were assumed to represent higher quality habitat. The southern Champlain Valley, which contained ample wetland and shrub habitat, was a concentrated area of highly suitable habitat, while areas at higher elevation areas were less suitable. Female bobcat home ranges, on average, had an average habitat suitability score of near 0, indicating that home ranges consisted of both beneficial and detrimental habitat types. We discuss the application of habitat suitability mapping and home range requirements for bobcat conservation and landscape scale management. ?? 2011.

Do birds see the forest for the trees? Scale-dependent effects of tree diversity on avian predation of artificial larvae.

PubMed

Muiruri, Evalyne W; Rainio, Kalle; Koricheva, Julia

2016-03-01

The enemies hypothesis states that reduced insect herbivory in mixed-species stands can be attributed to more effective top-down control by predators with increasing plant diversity. Although evidence for this mechanism exists for invertebrate predators, studies on avian predation are comparatively rare and have not explicitly tested the effects of diversity at different spatial scales, even though heterogeneity at macro- and micro-scales can influence bird foraging selection. We studied bird predation in an established forest diversity experiment in SW Finland, using artificial larvae installed on birch, alder and pine trees. Effects of tree species diversity and densities on bird predation were tested at two different scales: between plots and within the neighbourhood around focal trees. At the neighbourhood scale, birds preferentially foraged on focal trees surrounded by a higher diversity of neighbours. However, predation rates did not increase with tree species richness at the plot level and were instead negatively affected by tree height variation within the plot. The highest probability of predation was observed on pine, and rates of predation increased with the density of pine regardless of scale. Strong tree species preferences observed may be due to a combination of innate bird species preferences and opportunistic foraging on profitable-looking artificial prey. This study therefore finds partial support for the enemies hypothesis and highlights the importance of spatial scale and focal tree species in modifying trophic interactions between avian predators and insect herbivores in forest ecosystems.

Global economic trade-offs between wild nature and tropical agriculture.

PubMed

Carrasco, Luis R; Webb, Edward L; Symes, William S; Koh, Lian P; Sodhi, Navjot S

2017-07-01

Global demands for agricultural and forestry products provide economic incentives for deforestation across the tropics. Much of this deforestation occurs with a lack of information on the spatial distribution of benefits and costs of deforestation. To inform global sustainable land-use policies, we combine geographic information systems (GIS) with a meta-analysis of ecosystem services (ES) studies to perform a spatially explicit analysis of the trade-offs between agricultural benefits, carbon emissions, and losses of multiple ecosystem services because of tropical deforestation from 2000 to 2012. Even though the value of ecosystem services presents large inherent uncertainties, we find a pattern supporting the argument that the externalities of destroying tropical forests are greater than the current direct economic benefits derived from agriculture in all cases bar one: when yield and rent potentials of high-value crops could be realized in the future. Our analysis identifies the Atlantic Forest, areas around the Gulf of Guinea, and Thailand as areas where agricultural conversion appears economically efficient, indicating a major impediment to the long-term financial sustainability of Reducing Emissions from Deforestation and forest Degradation (REDD+) schemes in those countries. By contrast, Latin America, insular Southeast Asia, and Madagascar present areas with low agricultural rents (ARs) and high values in carbon stocks and ES, suggesting that they are economically viable conservation targets. Our study helps identify optimal areas for conservation and agriculture together with their associated uncertainties, which could enhance the efficiency and sustainability of pantropical land-use policies and help direct future research efforts.

A decision support system for forest harvest planning in North Carolina

Treesearch

D.G. Jones

2010-01-01

Forest preharvest planning (FPP) can enhance recognition of environmentally-sensitive areas in advance of forest harvesting, including soil and water resources. While preharvest planning is often a standard component of many forest harvesting operations, either explicitly with paper-based checklists or implicitly with best professional judgment, Geographic Information...

Minimum cost strategies for sequestering carbon in forests.

Treesearch

Darius M. Adams; Ralph J. Alig; Bruce A. McCarl; John M. Callaway; Steven M. Winnett

1999-01-01

This paper examines the costs of meeting explicit targets for increments of carbon sequestered in forests when both forest management decisions and the area of forests can be varied. Costs are estimated as welfare losses in markets for forest and agricultural products. Results show greatest change in management actions when targets require large near-term flux...

Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations

NASA Astrophysics Data System (ADS)

Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik

2018-06-01

The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.

Influence of Forest Management Regimes on Forest Dynamics in the Upstream Region of the Hun River in Northeastern China

PubMed Central

Yao, Jing; He, Xingyuan; Wang, Anzhi; Chen, Wei; Li, Xiaoyu; Lewis, Bernard J.; Lv, Xiaotao

2012-01-01

Balancing forest harvesting and restoration is critical for forest ecosystem management. In this study, we used LANDIS, a spatially explicit forest landscape model, to evaluate the effects of 21 alternative forest management initiatives which were drafted for forests in the upstream region of the Hun River in northeastern China. These management initiatives included a wide range of planting and harvest intensities for Pinus koraiensis, the historically dominant tree species in the region. Multivariate analysis of variance, Shannon's Diversity Index, and planting efficiency (which indicates how many cells of the target species at the final year benefit from per-cell of the planting trees) estimates were used as indicators to analyze the effects of planting and harvesting regimes on forests in the region. The results showed that the following: (1) Increased planting intensity, although augmenting the coverage of P. koraiensis, was accompanied by decreases in planting efficiency and forest diversity. (2) While selective harvesting could increase forest diversity, the abrupt increase of early succession species accompanying this method merits attention. (3) Stimulating rapid forest succession may not be a good management strategy, since the climax species would crowd out other species which are likely more adapted to future climatic conditions in the long run. In light of the above, we suggest a combination of 30% planting intensity with selective harvesting of 50% and 70% of primary and secondary timber species, respectively, as the most effective management regime in this area. In the long run this would accelerate the ultimate dominance of P. koraiensis in the forest via a more effective rate of planting, while maintaining a higher degree of forest diversity. These results are particularly useful for forest managers constrained by limited financial and labor resources who must deal with conflicts between forest harvesting and restoration. PMID:22723930

Forest restoration as a strategy to mitigate climate impacts on wildfire, vegetation, and water in semiarid forests.

PubMed

O'Donnell, Frances C; Flatley, William T; Springer, Abraham E; Fulé, Peter Z

2018-06-25

Climate change and wildfire are interacting to drive vegetation change and potentially reduce water quantity and quality in the southwestern United States, Forest restoration is a management approach that could mitigate some of these negative outcomes. However, little information exists on how restoration combined with climate change might influence hydrology across large forest landscapes that incorporate multiple vegetation types and complex fire regimes. We combined spatially explicit vegetation and fire modeling with statistical water and sediment yield models for a large forested landscape (335,000 ha) on the Kaibab Plateau in northern Arizona, USA. Our objective was to assess the impacts of climate change and forest restoration on the future fire regime, forest vegetation, and watershed outputs. Our model results predict that the combination of climate change and high-severity fire will drive forest turnover, biomass declines, and compositional change in future forests. Restoration treatments may reduce the area burned in high-severity fires and reduce conversions from forested to non-forested conditions. Even though mid-elevation forests are the targets of restoration, the treatments are expected to delay the decline of high-elevation spruce-fir, aspen, and mixed conifer forests by reducing the occurrence of high-severity fires that may spread across ecoregions. We estimate that climate-induced vegetation changes will result in annual runoff declines of up to 10%, while restoration reduced or reversed this decline. The hydrologic model suggests that mid-elevation forests, which are the targets of restoration treatments, provide around 80% of runoff in this system and the conservation of mid- to high-elevation forests types provides the greatest benefit in terms of water conservation. We also predict that restoration treatments will conserve water quality by reducing patches of high-severity fire that are associated with high sediment yield. Restoration treatments are a management strategy that may reduce undesirable outcomes for multiple ecosystem services. © 2018 by the Ecological Society of America.

Digital mapping of soil properties in Canadian managed forests at 250 m of resolution using the k-nearest neighbor method

NASA Astrophysics Data System (ADS)

Mansuy, N. R.; Paré, D.; Thiffault, E.

2015-12-01

Large-scale mapping of soil properties is increasingly important for environmental resource management. Whileforested areas play critical environmental roles at local and global scales, forest soil maps are typically at lowresolution.The objective of this study was to generate continuous national maps of selected soil variables (C, N andsoil texture) for the Canadian managed forest landbase at 250 m resolution. We produced these maps using thekNN method with a training dataset of 538 ground-plots fromthe National Forest Inventory (NFI) across Canada,and 18 environmental predictor variables. The best predictor variables were selected (7 topographic and 5 climaticvariables) using the Least Absolute Shrinkage and Selection Operator method. On average, for all soil variables,topographic predictors explained 37% of the total variance versus 64% for the climatic predictors. Therelative root mean square error (RMSE%) calculated with the leave-one-out cross-validation method gave valuesranging between 22% and 99%, depending on the soil variables tested. RMSE values b 40% can be considered agood imputation in light of the low density of points used in this study. The study demonstrates strong capabilitiesfor mapping forest soil properties at 250m resolution, compared with the current Soil Landscape of CanadaSystem, which is largely oriented towards the agricultural landbase. The methodology used here can potentiallycontribute to the national and international need for spatially explicit soil information in resource managementscience.

Using occupancy models of forest breeding birds to prioritize conservation planning

USGS Publications Warehouse

De Wan, A. A.; Sullivan, P.J.; Lembo, A.J.; Smith, C.R.; Maerz, J.C.; Lassoie, J.P.; Richmond, M.E.

2009-01-01

As urban development continues to encroach on the natural and rural landscape, land-use planners struggle to identify high priority conservation areas for protection. Although knowing where urban-sensitive species may be occurring on the landscape would facilitate conservation planning, research efforts are often not sufficiently designed to make quality predictions at unknown locations. Recent advances in occupancy modeling allow for more precise estimates of occupancy by accounting for differences in detectability. We applied these techniques to produce robust estimates of habitat occupancy for a subset of forest breeding birds, a group that has been shown to be sensitive to urbanization, in a rapidly urbanizing yet biological diverse region of New York State. We found that detection probability ranged widely across species, from 0.05 to 0.8. Our models suggest that detection probability declined with increasing forest fragmentation. We also found that the probability of occupancy of forest breeding birds is negatively influenced by increasing perimeter-area ratio of forest fragments and urbanization in the surrounding habitat matrix. We capitalized on our random sampling design to produce spatially explicit models that predict high priority conservation areas across the entire region, where interior-species were most likely to occur. Finally, we use our predictive maps to demonstrate how a strict sampling design coupled with occupancy modeling can be a valuable tool for prioritizing biodiversity conservation in land-use planning. ?? 2009 Elsevier Ltd.

Enabling large-scale forest restoration in Minas Gerais state, Brazil

NASA Astrophysics Data System (ADS)

Nunes, Felipe S. M.; Soares-Filho, Britaldo S.; Rajão, Raoni; Merry, Frank

2017-04-01

Large-scale forest restoration is a cornerstone of Brazil’s new Forest Code and a key element in its National Determined Contribution (NDC) to emissions reduction. But the path to this target remains unclear due to a lack of information on its economics and implementation challenges. Here, we begin to fill this gap by developing a spatially-explicit model for Minas Gerais state that estimates the costs and benefits of native vegetation regeneration under different restoration approaches. Our results show that 36% (0.7 million ha) of the Forest Code debt in Minas Gerais can be restored using only passive restoration, at a cost of US 175 ± 47 million. Adding low-cost assisted natural regeneration would increase that number to 75% (1.5 million ha) at a cost of US 776 ± 137 million over a 20 yr period. This would result in a potential sequestration of 284 MtCO2e. However, including the intensive planting methods needed to restore the remaining 25% of highly degraded areas—to fully solve the Forest Code debt and result in a potential sequestration of 345 MtCO2e—would more than double the costs to US 1.7 ± 0.3 billion. Our results emphasize the need to implement regional policies that take advantage of the natural regeneration potential as well as prioritize the restoration of areas key to ecosystem services.

Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

NASA Astrophysics Data System (ADS)

Vacchiano, Giorgio; Foderi, Cristiano; Berretti, Roberta; Marchi, Enrico; Motta, Renzo

2018-03-01

Modeling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an Alpine region in Italy using a regional wildfire archive (1995-2009) and MaxEnt modeling. We analyzed separately (i) winter forest fires, (ii) winter fires on grasslands and fallow land, and (iii) summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component. Collinearity among predictors was reduced by a principal component analysis. Regarding ignitions, 30 % occurred in agricultural areas and 24 % in forests. Ignitions peaked in the late winter-early spring. Negligence from agrosilvicultural activities was the main cause of ignition (64 %); lightning accounted for 9 % of causes across the study time frame, but increased from 6 to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of fit (AUC 0.90-0.95). Temperature was proportional to the probability of ignition, and precipitation was inversely proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different effect on summer (positive correlation) and winter (negative) fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such a spatially explicit approach allows us to carry out spatially targeted fire management strategies and may assist in developing better fire management plans.

Effects of fire on regional evapotranspiration in the central Canadian boreal forest

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

Bond-Lamberty, Benjamin; Peckham, Scott D.; Gower, Stith T.

2009-04-08

Changes in fire regimes are driving the carbon balance of much of the North American boreal forest, but few studies have examined fire-driven changes in evapotranspiration (ET) at a regional scale. This study used a version of the Biome-BGC process model with dynamic and competing vegetation types, and explicit spatial representation of a large (106 km2) region, to simulate the effects of wildfire on ET and its components from 1948 to 2005 by comparing the fire dynamics of the 1948-1967 period with those of 1968-2005. Simulated ET averaged, over the entire temporal and spatial modeling domain, 323 mm yr-1; simulationmore » results indicated that changes in fire in recent decades decreased regional ET by 1.4% over the entire simulation, and by 3.9% in the last ten years (1996-2005). Conifers dominated the transpiration (EC) flux (120 mm yr-1) but decreased by 18% relative to deciduous broadleaf trees in the last part of the 20th century, when increased fire resulted in increased soil evaporation, lower canopy evaporation, lower EC and a younger and more deciduous forest. Well- and poorly-drained areas had similar rates of evaporation from the canopy and soil, but EC was twice as high in the well-drained areas. Mosses comprised a significant part of the evaporative flux to the atmosphere (22 mm yr-1). Modeled annual ET was correlated with net primary production, but not with temperature or precipitation; ET and its components were consistent with previous field and modeling studies. Wildfire is thus driving significant changes in hydrological processes, changes that may control the future carbon balance of the boreal forest.« less

Utilization of geoinformation tools for the development of forest fire hazard mapping system: example of Pekan fire, Malaysia

NASA Astrophysics Data System (ADS)

Mahmud, Ahmad Rodzi; Setiawan, Iwan; Mansor, Shattri; Shariff, Abdul Rashid Mohamed; Pradhan, Biswajeet; Nuruddin, Ahmed

2009-12-01

A study in modeling fire hazard assessment will be essential in establishing an effective forest fire management system especially in controlling and preventing peat fire. In this paper, we have used geographic information system (GIS), in combination with other geoinformation technologies such as remote sensing and computer modeling, for all aspects of wild land fire management. Identifying areas that have a high probability of burning is an important component of fire management planning. The development of spatially explicit GIS models has greatly facilitated this process by allowing managers to map and analyze variables contributing to fire occurrence across large, unique geographic units. Using the model and its associated software engine, the fire hazard map was produced. Extensive avenue programming scripts were written to provide additional capabilities in the development of these interfaces to meet the full complement of operational software considering various users requirements. The system developed not only possesses user friendly step by step operations to deliver the fire vulnerability mapping but also allows authorized users to edit, add or modify parameters whenever necessary. Results from the model can support fire hazard mapping in the forest and enhance alert system function by simulating and visualizing forest fire and helps for contingency planning.

Validating a method for transferring social values of ecosystem services between public lands in the Rocky Mountain region

USGS Publications Warehouse

Sherrouse, Benson C.; Semmens, Darius J.

2014-01-01

With growing pressures on ecosystem services, social values attributed to them are increasingly important to land management decisions. Social values, defined here as perceived values the public ascribes to ecosystem services, particularly cultural services, are generally not accounted for through economic markets or considered alongside economic and ecological values in ecosystem service assessments. Social-values data can be elicited through public value and preference surveys; however, limitations prevent them from being regularly collected. These limitations led to our three study objectives: (1) demonstrate an approach for applying benefit transfer, a nonmarket-valuation method, to spatially explicit social values; (2) validate the approach; and (3) identify potential improvements. We applied Social Values for Ecosystem Services (SolVES) to survey data for three national forests in Colorado and Wyoming. Social-value maps and models were generated, describing relationships between the maps and various combinations of environmental variables. Models from each forest were used to estimate social-value maps for the other forests via benefit transfer. Model performance was evaluated relative to the locally derived models. Performance varied with the number and type of environmental variables used, as well as differences in the forests' physical and social contexts. Enhanced metadata and better social-context matching could improve model transferability.

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

PubMed

Johnson, Kristofer D; Birdsey, Richard; Cole, Jason; Swatantran, Anu; O'Neil-Dunne, Jarlath; Dubayah, Ralph; Lister, Andrew

2015-10-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

Multiscale habitat use and selection in cooperatively breeding Micronesian kingfishers

USGS Publications Warehouse

Kesler, D.C.; Haig, S.M.

2007-01-01

Information about the interaction between behavior and landscape resources is key to directing conservation management for endangered species. We studied multi-scale occurrence, habitat use, and selection in a cooperatively breeding population of Micronesian kingfishers (Todiramphus cinnamominus) on the island of Pohnpei, Federated States of Micronesia. At the landscape level, point-transect surveys resulted in kingfisher detection frequencies that were higher than those reported in 1994, although they remained 15-40% lower than 1983 indices. Integration of spatially explicit vegetation information with survey results indicated that kingfisher detections were positively associated with the amount of wet forest and grass-urban vegetative cover, and they were negatively associated with agricultural forest, secondary vegetation, and upland forest cover types. We used radiotelemetry and remote sensing to evaluate habitat use by individual kingfishers at the home-range scale. A comparison of habitats in Micronesian kingfisher home ranges with those in randomly placed polygons illustrated that birds used more forested areas than were randomly available in the immediate surrounding area. Further, members of cooperatively breeding groups included more forest in their home ranges than birds in pair-breeding territories, and forested portions of study areas appeared to be saturated with territories. Together, these results suggested that forest habitats were limited for Micronesian kingfishers. Thus, protecting and managing forests is important for the restoration of Micronesian kingfishers to the island of Guam (United States Territory), where they are currently extirpated, as well as to maintaining kingfisher populations on the islands of Pohnpei and Palau. Results further indicated that limited forest resources may restrict dispersal opportunities and, therefore, play a role in delayed dispersal and cooperative behaviors in Micronesian kingfishers.

Conservation of the Ethiopian church forests: Threats, opportunities and implications for their management.

PubMed

Aerts, Raf; Van Overtveld, Koen; November, Eva; Wassie, Alemayehu; Abiyu, Abrham; Demissew, Sebsebe; Daye, Desalegn D; Giday, Kidane; Haile, Mitiku; TewoldeBerhan, Sarah; Teketay, Demel; Teklehaimanot, Zewge; Binggeli, Pierre; Deckers, Jozef; Friis, Ib; Gratzer, Georg; Hermy, Martin; Heyn, Moïra; Honnay, Olivier; Paris, Maxim; Sterck, Frank J; Muys, Bart; Bongers, Frans; Healey, John R

2016-05-01

In the central and northern highlands of Ethiopia, native forest and forest biodiversity is almost confined to sacred groves associated with churches. Local communities rely on these 'church forests' for essential ecosystem services including shade and fresh water but little is known about their region-wide distribution and conservation value. We (1) performed the first large-scale spatially-explicit assessment of church forests, combining remote-sensing and field data, to assess the number of forests, their size, shape, isolation and woody plant species composition, (2) determined their plant communities and related these to environmental variables and potential natural vegetation, (3) identified the main challenges to biodiversity conservation in view of plant population dynamics and anthropogenic disturbances, and (4) present guidelines for management and policy. The 394 forests identified in satellite images were on average ~2ha in size and generally separated by ~2km from the nearest neighboring forest. Shape complexity, not size, decreased from the northern to the central highlands. Overall, 148 indigenous tree, shrub and liana species were recorded across the 78 surveyed forests. Patch α-diversity increased with mean annual precipitation, but typically only 25 woody species occurred per patch. The combined results showed that >50% of tree species present in tropical northeast Africa were still present in the 78 studied church forests, even though individual forests were small and relatively species-poor. Tree species composition of church forests varied with elevation and precipitation, and resembled the potential natural vegetation. With a wide distribution over the landscape, these church forests have high conservation value. However, long-term conservation of biodiversity of individual patches and evolutionary potential of species may be threatened by isolation, small sizes of tree species populations and disturbance, especially when considering climate change. Forest management interventions are essential and should be supported by environmental education and other forms of public engagement. Copyright © 2016 Elsevier B.V. All rights reserved.

Carbon mapping of Argentine savannas: Using fractional tree cover to scale from field to region

NASA Astrophysics Data System (ADS)

González-Roglich, M.; Swenson, J. J.

2015-12-01

Programs which intend to maintain or enhance carbon (C) stocks in natural ecosystems are promising, but require detailed and spatially explicit C distribution models to monitor the effectiveness of management interventions. Savanna ecosystems are significant components of the global C cycle, covering about one fifth of the global land mass, but they have received less attention in C monitoring protocols. Our goal was to estimate C storage across a broad savanna ecosystem using field surveys and freely available satellite images. We first mapped tree canopies at 2.5 m resolution with a spatial subset of high resolution panchromatic images to then predict regional wall-to-wall tree percent cover using 30-m Landsat imagery and the Random Forests algorithms. We found that a model with summer and winter spectral indices from Landsat, climate and topography performed best. Using a linear relationship between C and % tree cover, we then predicted tree C stocks across the gradient of tree cover, explaining 87 % of the variability. The spatially explicit validation of the tree C model with field-measured C-stocks revealed an RMSE of 8.2 tC/ha which represented ~30% of the mean C stock for areas with tree cover, comparable to studies based on more advanced remote sensing methods, such as LiDAR and RADAR. Sample spatial distribution highly affected the performance of the RF models in predicting tree cover, raising concerns regarding the predictive capabilities of the model in areas for which training data is not present. The 50,000 km2 has ~41 Tg C, which could be released to the atmosphere if agricultural pressure intensifies in this semiarid savanna.

Forest inventories generate scientifically sound information on the forest resource, but do our data and information really matter?

Treesearch

Christoph Keinn; Goran Stahl

2009-01-01

Current research in forest inventory focuses very much on technical-statistical problems geared mainly to the optimization of data collection and information generation. The basic assumption is that better information leads to better decisions and, therefore, to better forest management and forest policy. Not many studies, however, strive to explicitly establish the...

Long-term consistency in spatial patterns of primate seed dispersal.

PubMed

Heymann, Eckhard W; Culot, Laurence; Knogge, Christoph; Noriega Piña, Tony Enrique; Tirado Herrera, Emérita R; Klapproth, Matthias; Zinner, Dietmar

2017-03-01

Seed dispersal is a key ecological process in tropical forests, with effects on various levels ranging from plant reproductive success to the carbon storage potential of tropical rainforests. On a local and landscape scale, spatial patterns of seed dispersal create the template for the recruitment process and thus influence the population dynamics of plant species. The strength of this influence will depend on the long-term consistency of spatial patterns of seed dispersal. We examined the long-term consistency of spatial patterns of seed dispersal with spatially explicit data on seed dispersal by two neotropical primate species, Leontocebus nigrifrons and Saguinus mystax (Callitrichidae), collected during four independent studies between 1994 and 2013. Using distributions of dispersal probability over distances independent of plant species, cumulative dispersal distances, and kernel density estimates, we show that spatial patterns of seed dispersal are highly consistent over time. For a specific plant species, the legume Parkia panurensis , the convergence of cumulative distributions at a distance of 300 m, and the high probability of dispersal within 100 m from source trees coincide with the dimension of the spatial-genetic structure on the embryo/juvenile (300 m) and adult stage (100 m), respectively, of this plant species. Our results are the first demonstration of long-term consistency of spatial patterns of seed dispersal created by tropical frugivores. Such consistency may translate into idiosyncratic patterns of regeneration.

Integration of airborne LiDAR data and voxel-based ray tracing to determine high-resolution solar radiation dynamics at the forest floor: implications for improving stand-scale distributed snowmelt models

NASA Astrophysics Data System (ADS)

Musselman, K. N.; Molotch, N. P.; Margulis, S. A.

2012-12-01

Forest architecture dictates sub-canopy solar irradiance and the resulting patterns can vary seasonally and over short spatial distances. These radiation dynamics are thought to have significant implications on snowmelt processes, regional hydrology, and remote sensing signatures. The variability calls into question many assumptions inherent in traditional canopy models (e.g. Beer's Law) when applied at high resolution (i.e. 1 m). We present a method of estimating solar canopy transmissivity using airborne LiDAR data. The canopy structure is represented in 3-D voxel space (i.e. a cubic discretization of a 3-D domain analogous to a pixel representation of a 2-D space). The solar direct beam canopy transmissivity (DBT) is estimated with a ray-tracing algorithm and the diffuse component is estimated from LiDAR-derived effective LAI. Results from one year at five-minute temporal and 1 m spatial resolutions are presented from Sequoia National Park. Compared to estimates from 28 hemispherical photos, the ray-tracing model estimated daily mean DBT with a 10% average error, while the errors from a Beer's-type DBT estimate exceeded 20%. Compared to the ray-tracing estimates, the Beer's-type transmissivity method was unable to resolve complex spatial patterns resulting from canopy gaps, individual tree canopies and boles, and steep variable terrain. The snowmelt model SNOWPACK was applied at locations of ultrasonic snow depth sensors. Two scenarios were tested; 1) a nominal case where canopy model parameters were obtained from hemispherical photographs, and 2) an explicit scenario where the model was modified to accept LiDAR-derived time-variant DBT. The bulk canopy treatment was generally unable to simulate the sub-canopy snowmelt dynamics observed at the depth sensor locations. The explicit treatment reduced error in the snow disappearance date by one week and both positive and negative melt-season SWE biases were reduced. The results highlight the utility of LiDAR canopy measurements and physically based snowmelt models to simulate spatially distributed stand- and slope-scale snowmelt dynamics at resolutions necessary to capture the inherent underlying variability.iDAR-derived solar direct beam canopy transmissivity computed as the daily average for March 1st and May 1st.

The role of gap phase processes in the biomass dynamics of tropical forests

PubMed Central

Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M.N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

2007-01-01

The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four ‘old-growth’ tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr−1) and decreased at HKK (−0.56% yr−1) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget. PMID:17785266

The role of gap phase processes in the biomass dynamics of tropical forests.

PubMed

Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

2007-11-22

The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four 'old-growth' tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr(-1)) and decreased at HKK (-0.56% yr(-1)) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget.

Future Wildfire and Managed Fire Interactions in the Lake Tahoe Basin

NASA Astrophysics Data System (ADS)

Scheller, R.; Kretchun, A.

2017-12-01

Managing large forested landscape in the context of a changing climate and altered disturbance regimes presents new challenges and require integrated assessments of forest disturbance, management, succession, and the carbon cycle. Successful management under these circumstances will require information about trade-offs among multiple objectives and opportunities for spatially optimized landscape-scale management. Improved information about the effects of climate on forest communities, disturbance feedbacks, and the effectiveness of mitigation strategies enables actionable options for landscape managers. We evaluated the effects of fire suppression, wildfires, and forest fuel (thinning) treatments on the long-term carbon storage potential for Lake Tahoe Basin (LTB) forests under various climate futures. We simulated management scenarios that encompass fuel treatments across the larger landscape, beyond the Wildland Urban Interface. We improved upon current fire modeling under climate change via an integrated fire modeling module that, a) explicitly captures the influence of climate, fuels, topography, active fire management (e.g., fire suppression), and fuel treatments, and b) can be parameterized from available data, e.g., remote sensing, field reporting, fire databases, expert opinion. These improvements increase geographic flexibility and decrease reliance on broad historical fire regime statistics - imperfect targets for a no analog future and require minimal parameterization and calibration. We assessed the interactions among fuel treatments, prescribe fire, fire suppression, and stochastically recurring wildfires. Predicted changes in climate and ignition patterns in response to future climatic conditions, vegetation dynamics, and fuel treatments indicate larger potential long-term effects on C emissions, forest structure, and forest composition than prior studies.

Vulnerability of the global terrestrial ecosystems to climate change.

PubMed

Li, Delong; Wu, Shuyao; Liu, Laibao; Zhang, Yatong; Li, Shuangcheng

2018-05-27

Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.

Spatial aspects of tree mortality strongly differ between young and old-growth forests.

PubMed

Larson, Andrew J; Lutz, James A; Donato, Daniel C; Freund, James A; Swanson, Mark E; HilleRisLambers, Janneke; Sprugel, Douglas G; Franklin, Jerry F

2015-11-01

Rates and spatial patterns of tree mortality are predicted to change during forest structural development. In young forests, mortality should be primarily density dependent due to competition for light, leading to an increasingly spatially uniform pattern of surviving trees. In contrast, mortality in old-growth forests should be primarily caused by contagious and spatially autocorrelated agents (e.g., insects, wind), causing spatial aggregation of surviving trees to increase through time. We tested these predictions by contrasting a three-decade record of tree mortality from replicated mapped permanent plots located in young (< 60-year-old) and old-growth (> 300-year-old) Abies amabilis forests. Trees in young forests died at a rate of 4.42% per year, whereas trees in old-growth forests died at 0.60% per year. Tree mortality in young forests was significantly aggregated, strongly density dependent, and caused live tree patterns to become more uniform through time. Mortality in old-growth forests was spatially aggregated, but was density independent and did not change the spatial pattern of surviving trees. These results extend current theory by demonstrating that density-dependent competitive mortality leading to increasingly uniform tree spacing in young forests ultimately transitions late in succession to a more diverse tree mortality regime that maintains spatial heterogeneity through time.

Spatial and Temporal Relationships of Old-Growth and Secondary Forests in Indiana, USA

Treesearch

Martin A. Spetich; George R. Parker; Eric J. Gustafson

1997-01-01

We examined the spatial pattern of forests in Indiana to: (1) determine the extent, connectivity and percent edge of all forests, (2) examine the change in connectivity among these forests if all riparian zones were replanted to forest or other native vegetation, (3) determine the location, spatial dispersion and percent edge of current old-growth forest remnants, (4)...

The spatial extent of change in tropical forest ecosystem services in the Amazon delta

NASA Astrophysics Data System (ADS)

de Araujo Barbosa, C. C.; Atkinson, P.; Dearing, J.

2014-12-01

Deltas hold major economic potential due their strategic location, close to seas and inland waterways, thereby supporting intense economic activity. The increasing pace of human development activities in coastal deltas over the past five decades has also strained environmental resources and produced extensive economic and sociocultural impacts. The Amazon delta is located in the Amazon Basin, North Brazil, the largest river basin on Earth and also one of the least understood. A considerable segment of the population living in the Amazon delta is directly dependent on the local extraction of natural resources for their livelihood. Areas sparsely inhabited may be exploited with few negative consequences for the environment. However, increasing pressure on ecosystem services is amplified by large fluxes of immigrants from other parts of the country, especially from the semi-arid zone in Northeast Brazil to the lowland forests of the Amazon delta. Here we present partial results from a bigger research project. Therefore, the focus will be on presenting an overview of the current state, and the extent of changes on forest related ecosystem services in the Amazon delta over the last three decades. We aggregated a multitude of datasets, from a variety of sources, for example, from satellite imagery such as the Advanced Very High Resolution Radiometer (AVHRR), the Global Inventory Modelling and Mapping Studies (GIMMS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and climate datasets at meteorological station level from the Brazilian National Institute of Meteorology (INMET) and social and economic statistics data from the Brazilian Institute of Geography and Statistics (IBGE) and from the Brazilian Institute of Applied Economic Research (IPEA). Through analysis of socioeconomic and satellite earth observation data we were able to produce and present spatially-explicit information with the current state and transition in forest cover and its impacts to forest ecosystem services providing units in the Amazon delta.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Review of forest landscape models: types, methods, development and applications

Treesearch

Weimin Xi; Robert N. Coulson; Andrew G. Birt; Zong-Bo Shang; John D. Waldron; Charles W. Lafon; David M. Cairns; Maria D. Tchakerian; Kier D. Klepzig

2009-01-01

Forest landscape models simulate forest change through time using spatially referenced data across a broad spatial scale (i.e. landscape scale) generally larger than a single forest stand. Spatial interactions between forest stands are a key component of such models. These models can incorporate other spatio-temporal processes such as...

Modelling the standing timber volume of Baden-Württemberg-A large-scale approach using a fusion of Landsat, airborne LiDAR and National Forest Inventory data

NASA Astrophysics Data System (ADS)

Maack, Joachim; Lingenfelder, Marcus; Weinacker, Holger; Koch, Barbara

2016-07-01

Remote sensing-based timber volume estimation is key for modelling the regional potential, accessibility and price of lignocellulosic raw material for an emerging bioeconomy. We used a unique wall-to-wall airborne LiDAR dataset and Landsat 7 satellite images in combination with terrestrial inventory data derived from the National Forest Inventory (NFI), and applied generalized additive models (GAM) to estimate spatially explicit timber distribution and volume in forested areas. Since the NFI data showed an underlying structure regarding size and ownership, we additionally constructed a socio-economic predictor to enhance the accuracy of the analysis. Furthermore, we balanced the training dataset with a bootstrap method to achieve unbiased regression weights for interpolating timber volume. Finally, we compared and discussed the model performance of the original approach (r2 = 0.56, NRMSE = 9.65%), the approach with balanced training data (r2 = 0.69, NRMSE = 12.43%) and the final approach with balanced training data and the additional socio-economic predictor (r2 = 0.72, NRMSE = 12.17%). The results demonstrate the usefulness of remote sensing techniques for mapping timber volume for a future lignocellulose-based bioeconomy.

Spatial working memory interferes with explicit, but not probabilistic cuing of spatial attention.

PubMed

Won, Bo-Yeong; Jiang, Yuhong V

2015-05-01

Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal that working memory is attention directed toward internal representations. Here, we show that the close relationship between these 2 constructs is limited to some but not all forms of spatial attention. In 5 experiments, participants held color arrays, dot locations, or a sequence of dots in working memory. During the memory retention interval, they performed a T-among-L visual search task. Crucially, the probable target location was cued either implicitly through location probability learning or explicitly with a central arrow or verbal instruction. Our results showed that whereas imposing a visual working memory load diminished the effectiveness of explicit cuing, it did not interfere with probability cuing. We conclude that spatial working memory shares similar mechanisms with explicit, goal-driven attention but is dissociated from implicitly learned attention. (c) 2015 APA, all rights reserved).

Spatial working memory interferes with explicit, but not probabilistic cuing of spatial attention

PubMed Central

Won, Bo-Yeong; Jiang, Yuhong V.

2014-01-01

Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal that working memory is attention directed toward internal representations. Here we show that the close relationship between these two constructs is limited to some but not all forms of spatial attention. In five experiments, participants held color arrays, dot locations, or a sequence of dots in working memory. During the memory retention interval they performed a T-among-L visual search task. Crucially, the probable target location was cued either implicitly through location probability learning, or explicitly with a central arrow or verbal instruction. Our results showed that whereas imposing a visual working memory load diminished the effectiveness of explicit cuing, it did not interfere with probability cuing. We conclude that spatial working memory shares similar mechanisms with explicit, goal-driven attention but is dissociated from implicitly learned attention. PMID:25401460

Assessing Forest Carbon Response to Climate Change and Disturbances Using Long-term Hydro-climatic Observations and Simulations

NASA Astrophysics Data System (ADS)

Trettin, C.; Dai, Z.; Amatya, D. M.

2014-12-01

Long-term climatic and hydrologic observations on the Santee Experimental Forest in the lower coastal plain of South Carolina were used to estimate long-term changes in hydrology and forest carbon dynamics for a pair of first-order watersheds. Over 70 years of climate data indicated that warming in this forest area in the last decades was faster than the global mean; 35+ years of hydrologic records showed that forest ecosystem succession three years following Hurricane Hugo caused a substantial change in the ratio of runoff to precipitation. The change in this relationship between the paired watersheds was attributed to altered evapotranspiration processes caused by greater abundance of pine in the treatment watershed and regeneration of the mixed hardwood-pine forest on the reference watershed. The long-term records and anomalous observations are highly valuable for reliable calibration and validation of hydrological and biogeochemical models capturing the effects of climate variability. We applied the hydrological model MIKESHE that showed that runoff and water table level are sensitive to global warming, and that the sustained warming trends can be expected to decrease stream discharge and lower the mean water table depth. The spatially-explicit biogeochemical model Forest-DNDC, validated using biomass measurements from the watersheds, was used to assess carbon dynamics in response to high resolution hydrologic observation data and simulation results. The simulations showed that the long-term spatiotemporal carbon dynamics, including biomass and fluxes of soil carbon dioxide and methane were highly regulated by disturbance regimes, climatic conditions and water table depth. The utility of linked-modeling framework demonstrated here to assess biogeochemical responses at the watershed scale suggests applications for assessing the consequences of climate change within an urbanizing forested landscape. The approach may also be applicable for validating large-scale models.

Assessing REDD+ performance of countries with low monitoring capacities: the matrix approach

NASA Astrophysics Data System (ADS)

Bucki, M.; Cuypers, D.; Mayaux, P.; Achard, F.; Estreguil, C.; Grassi, G.

2012-03-01

Estimating emissions from deforestation and degradation of forests in many developing countries is so uncertain that the effects of changes in forest management could remain within error ranges (i.e. undetectable) for several years. Meanwhile UNFCCC Parties need consistent time series of meaningful performance indicators to set credible benchmarks and allocate REDD+ incentives to the countries, programs and activities that actually reduce emissions, while providing social and environmental benefits. Introducing widespread measuring of carbon in forest land (which would be required to estimate more accurately changes in emissions from degradation and forest management) will take time and considerable resources. To ensure the overall credibility and effectiveness of REDD+, parties must consider the design of cost-effective systems which can provide reliable and comparable data on anthropogenic forest emissions. Remote sensing can provide consistent time series of land cover maps for most non-Annex-I countries, retrospectively. These maps can be analyzed to identify the forests that are intact (i.e. beyond significant human influence), and whose fragmentation could be a proxy for degradation. This binary stratification of forests biomes (intact/non-intact), a transition matrix and the use of default carbon stock change factors can then be used to provide initial estimates of trends in emission changes. A proof-of-concept is provided for one biome of the Democratic Republic of the Congo over a virtual commitment period (2005-2010). This approach could allow assessment of the performance of the five REDD+ activities (deforestation, degradation, conservation, management and enhancement of forest carbon stocks) in a spatially explicit, verifiable manner. Incentives could then be tailored to prioritize activities depending on the national context and objectives.

Quantifying Forest Ecosystem Services Tradeoff—Coupled Ecological and Economic Models

NASA Astrophysics Data System (ADS)

Haff, P. K.; Ling, P. Y.

2015-12-01

Quantification of the effect of carbon-related forestland management activities on ecosystem services is difficult, because knowledge about the dynamics of coupled social-ecological systems is lacking. Different forestland management activities, such as various amount, timing, and methods of harvesting, and natural disturbances events, such as wind and fires, create shocks and uncertainties to the forest carbon dynamics. A spatially explicit model, Landis-ii, was used to model the forest succession for different harvest management scenarios at the Grandfather District, North Carolina. In addition to harvest, the model takes into account of the impact of natural disturbances, such as fire and insects, and species competition. The result shows the storage of carbon in standing biomass and in wood product for each species for each scenario. In this study, optimization is used to analyze the maximum profit and the number of tree species that each forest landowner can gain at different prices of carbon, roundwood, and interest rates for different harvest management scenarios. Time series of roundwood production of different types were estimated using remote sensing data. Econometric analysis is done to understand the possible interaction and relations between the production of different types of roundwood and roundwood prices, which can indicate the possible planting scheme that a forest owner may make. This study quantifies the tradeoffs between carbon sequestration, roundwood production, and forest species diversity not only from an economic perspective, but also takes into account of the forest succession mechanism in a species-diverse region. The resulting economic impact on the forest landowners is likely to influence their future planting decision, which in turn, will influence the species composition and future revenue of the landowners.

[Spatial pattern of forest biomass and its influencing factors in the Great Xing'an Mountains, Heilongjiang Province, China].

PubMed

Wang, Xiao-Li; Chang, Yu; Chen, Hong-Wei; Hu, Yuan-Man; Jiao, Lin-Lin; Feng, Yu-Ting; Wu, Wen; Wu, Hai-Feng

2014-04-01

Based on field inventory data and vegetation index EVI (enhanced vegetation index), the spatial pattern of the forest biomass in the Great Xing'an Mountains, Heilongjiang Province was quantitatively analyzed. Using the spatial analysis and statistics tools in ArcGIS software, the impacts of climatic zone, elevation, slope, aspect and vegetation type on the spatial pattern of forest biomass were explored. The results showed that the forest biomass in the Great Xing'an Mountains was 350 Tg and spatially aggregated with great increasing potentials. Forest biomass density in the cold temperate humid zone (64.02 t x hm(-2)) was higher than that in the temperate humid zone (60.26 t x hm(-2)). The biomass density of each vegetation type was in the order of mixed coniferous forest (65.13 t x hm(-2)) > spruce-fir forest (63.92 t x hm(-2)) > Pinus pumila-Larix gmelinii forest (63.79 t x hm(-2)) > Pinus sylvestris var. mongolica forest (61.97 t x hm(-2)) > Larix gmelinii forest (61.40 t x hm(-2)) > deciduous broadleaf forest (58.96 t x hm(-2)). With the increasing elevation and slope, the forest biomass density first decreased and then increased. The forest biomass density in the shady slopes was greater than that in the sunny slopes. The spatial pattern of forest biomass in the Great Xing' an Mountains exhibited a heterogeneous pattern due to the variation of climatic zone, vegetation type and topographical factor. This spatial heterogeneity needs to be accounted when evaluating forest biomass at regional scales.

Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

NASA Astrophysics Data System (ADS)

García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

2018-04-01

Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important variable, with Landsat Tasselled Cap Transformation components barely contributing to the models for two of the study sites whereas it had a significant contribution at the third one. Over the temperate conifer forests, Landsat Tasselled Cap variables contributed more than the ALOS-PALSAR HV band to predict the landscape height variability. In all cases, incorporation of multispectral data improved the retrieval of forest canopy height and reduced the estimation uncertainty for tall forests. Finally, we concluded that models trained at one study site had higher uncertainty when applied to other sites, but a model developed from multiple sites performed equally to site-specific models to predict forest canopy height. This result suggest that a biome level model developed from several study sites can be used as a reliable estimator of biome-level forest structure from existing satellite imagery.

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Global economic trade-offs between wild nature and tropical agriculture

PubMed Central

Webb, Edward L.; Symes, William S.; Koh, Lian P.

2017-01-01

Global demands for agricultural and forestry products provide economic incentives for deforestation across the tropics. Much of this deforestation occurs with a lack of information on the spatial distribution of benefits and costs of deforestation. To inform global sustainable land-use policies, we combine geographic information systems (GIS) with a meta-analysis of ecosystem services (ES) studies to perform a spatially explicit analysis of the trade-offs between agricultural benefits, carbon emissions, and losses of multiple ecosystem services because of tropical deforestation from 2000 to 2012. Even though the value of ecosystem services presents large inherent uncertainties, we find a pattern supporting the argument that the externalities of destroying tropical forests are greater than the current direct economic benefits derived from agriculture in all cases bar one: when yield and rent potentials of high-value crops could be realized in the future. Our analysis identifies the Atlantic Forest, areas around the Gulf of Guinea, and Thailand as areas where agricultural conversion appears economically efficient, indicating a major impediment to the long-term financial sustainability of Reducing Emissions from Deforestation and forest Degradation (REDD+) schemes in those countries. By contrast, Latin America, insular Southeast Asia, and Madagascar present areas with low agricultural rents (ARs) and high values in carbon stocks and ES, suggesting that they are economically viable conservation targets. Our study helps identify optimal areas for conservation and agriculture together with their associated uncertainties, which could enhance the efficiency and sustainability of pantropical land-use policies and help direct future research efforts. PMID:28732022

Neighbourhood-scale urban forest ecosystem classification.

PubMed

Steenberg, James W N; Millward, Andrew A; Duinker, Peter N; Nowak, David J; Robinson, Pamela J

2015-11-01

Urban forests are now recognized as essential components of sustainable cities, but there remains uncertainty concerning how to stratify and classify urban landscapes into units of ecological significance at spatial scales appropriate for management. Ecosystem classification is an approach that entails quantifying the social and ecological processes that shape ecosystem conditions into logical and relatively homogeneous management units, making the potential for ecosystem-based decision support available to urban planners. The purpose of this study is to develop and propose a framework for urban forest ecosystem classification (UFEC). The multifactor framework integrates 12 ecosystem components that characterize the biophysical landscape, built environment, and human population. This framework is then applied at the neighbourhood scale in Toronto, Canada, using hierarchical cluster analysis. The analysis used 27 spatially-explicit variables to quantify the ecosystem components in Toronto. Twelve ecosystem classes were identified in this UFEC application. Across the ecosystem classes, tree canopy cover was positively related to economic wealth, especially income. However, education levels and homeownership were occasionally inconsistent with the expected positive relationship with canopy cover. Open green space and stocking had variable relationships with economic wealth and were more closely related to population density, building intensity, and land use. The UFEC can provide ecosystem-based information for greening initiatives, tree planting, and the maintenance of the existing canopy. Moreover, its use has the potential to inform the prioritization of limited municipal resources according to ecological conditions and to concerns of social equity in the access to nature and distribution of ecosystem service supply. Copyright © 2015 Elsevier Ltd. All rights reserved.

Accounting for Forest Harvest and Wildfire in a Spatially-distributed Carbon Cycle Process Model

NASA Astrophysics Data System (ADS)

Turner, D. P.; Ritts, W.; Kennedy, R. E.; Yang, Z.; Law, B. E.

2009-12-01

Forests are subject to natural disturbances in the form of wildfire, as well as management-related disturbances in the form of timber harvest. These disturbance events have strong impacts on local and regional carbon budgets, but quantifying the associated carbon fluxes remains challenging. The ORCA Project aims to quantify regional net ecosystem production (NEP) and net biome production (NBP) in Oregon, California, and Washington, and we have adopted an integrated approach based on Landsat imagery and ecosystem modeling. To account for stand-level carbon fluxes, the Biome-BGC model has been adapted to simulate multiple severities of fire and harvest. New variables include snags, direct fire emissions, and harvest removals. New parameters include fire-intensity-specific combustion factors for each carbon pool (based on field measurements) and proportional removal rates for harvest events. To quantify regional fluxes, the model is applied in a spatially-distributed mode over the domain of interest, with disturbance history derived from a time series of Landsat images. In stand-level simulations, the post disturbance transition from negative (source) to positive (sink) NEP is delayed approximately a decade in the case of high severity fire compared to harvest. Simulated direct pyrogenic emissions range from 11 to 25 % of total non-soil ecosystem carbon. In spatial mode application over Oregon and California, the sum of annual pyrogenic emissions and harvest removals was generally less that half of total NEP, resulting in significant carbon sequestration on the land base. Spatially and temporally explicit simulation of disturbance-related carbon fluxes will contribute to our ability to evaluate effects of management on regional carbon flux, and in our ability to assess potential biospheric feedbacks to climate change mediated by changing disturbance regimes.

Curve Numbers for Nine Mountainous Eastern United States Watersheds: Seasonal Variation and Forest Cutting

EPA Science Inventory

Many engineers and hydrologists use the curve number method to estimate runoff from ungaged watersheds; however, the method does not explicitly account for the influence of season or forest cutting on runoff. This study of observed rainfall and runoff for small, forested watershe...

Explicit Not Implicit Preferences Predict Conservation Intentions for Endangered Species and Biomes.

PubMed

Echeverri, Alejandra; Callahan, Megan M; Chan, Kai M A; Satterfield, Terre; Zhao, Jiaying

2017-01-01

Conservation of biodiversity is determined in part by human preferences. Preferences relevant to conservation have been examined largely via explicit measures (e.g., a self-reported degree of liking), with implicit measures (e.g., preconscious, automatic evaluations) receiving relatively less attention. This is the case despite psychological evidence from other contexts that implicit preferences are more informative of behavior. Thus, the type of measure that predicts conservation intentions for biodiversity is unknown. We conducted three studies to examine conservation intentions in light of people's explicit and implicit preferences toward four endangered species (sea otter, American badger, caribou, yellow-breasted chat) and four biomes (forest, ocean, grassland, tundra). In Study 1 (n = 55), we found that people implicitly preferred caribou most, but explicitly preferred sea otter most, with a significant multiple regression where participants' explicit preferences dictated their stated intended donations for conservation of each species. In Study 2 (n = 57) we found that people implicitly and explicitly preferred forest and ocean over grassland and tundra. Explicit rather than implicit preferences predicted the intended donation for conservation of the ocean biome. Study 3 involved a broader online sample of participants (n = 463) and also found that explicit preferences dictated the intended donations for conservation of biomes and species. Our findings reveal discrepancies between implicit and explicit preferences toward species, but not toward biomes. Importantly, the results demonstrate that explicit rather than implicit preferences predict conservation intentions for biodiversity. The current findings have several implications for conservation and the communication of biodiversity initiatives.

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.

Mapping Forest Inventory and Analysis forest land use: timberland, reserved forest land, and other forest land

Treesearch

Mark D. Nelson; John Vissage

2007-01-01

The Forest Inventory and Analysis (FIA) program produces area estimates of forest land use within three subcategories: timberland, reserved forest land, and other forest land. Mapping these subcategories of forest land requires the ability to spatially distinguish productive from unproductive land, and reserved from nonreserved land. FIA field data were spatially...

Assessing the 100-Year Climate Change Mitigation Potential of Large-Scale Tropical Forest Restoration Under the Bonn Challenge

NASA Astrophysics Data System (ADS)

Wheeler, C. E.; Mitchard, E. T.; Lewis, S. L.

2017-12-01

Restoring degraded and deforested tropical lands to sequester carbon is widely considered to offer substantial climate change mitigation opportunities, if conducted over large spatial scales. Despite this assertion, explicit estimates of how much carbon could be sequestered because of large-scale restoration are rare and have large uncertainties. This is principally due to the many different characteristics of land available for restoration, and different potential restoration activities, which together cause very different rates of carbon sequestration. For different restoration pathways: natural regeneration of degraded and secondary forest, timber plantations and agroforestry, we estimate carbon sequestration rates from the published literature. Then based on tropical restoration commitments made under the Bonn challenge and using carbon density maps, these carbon sequestration rates were used to predict total pan-tropical carbon sequestration to 2100. Restoration of degraded or secondary forest via natural regeneration offers the greatest carbon sequestration potential, considerably exceeding the carbon captured by either timber plantations or agroforestry. This is predominantly due to naturally regenerating forests representing a more permanent store of carbon in comparison to timber plantations and agroforestry land-use options, which, due to their rotational nature, result in the sequential return of carbon to the atmosphere. If the Bonn Challenge is to achieve its ambition of providing substantial climate change mitigation from restoration it must incorporate large areas of natural regeneration back to an intact forest state, otherwise it stands to be a missed opportunity in helping meet the Paris climate change goals.

Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

NASA Astrophysics Data System (ADS)

Fu, W. J.; Jiang, P. K.; Zhou, G. M.; Zhao, K. L.

2014-04-01

Spatial pattern information of carbon density in forest ecosystem including forest litter carbon (FLC) plays an important role in evaluating carbon sequestration potentials. The spatial variation of FLC density in the typical subtropical forests in southeastern China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (south-north) × 6 km (east-west) grid system in Zhejiang province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha-1 to 8841.3 kg ha-1, with an average of 1786.7 kg ha-1. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas, while Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) Basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS, could be used to study spatial patterns of environmental variables related to forest ecosystem.

Using the FORE-SCE model to project land-cover change in the southeastern United States

USGS Publications Warehouse

Sohl, Terry; Sayler, Kristi L.

2008-01-01

A wide variety of ecological applications require spatially explicit current and projected land-use and land-cover data. The southeastern United States has experienced massive land-use change since European settlement and continues to experience extremely high rates of forest cutting, significant urban development, and changes in agricultural land use. Forest-cover patterns and structure are projected to change dramatically in the southeastern United States in the next 50 years due to population growth and demand for wood products [Wear, D.N., Greis, J.G. (Eds.), 2002. Southern Forest Resource Assessment. General Technical Report SRS-53. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, 635 pp]. Along with our climate partners, we are examining the potential effects of southeastern U.S. land-cover change on regional climate. The U.S. Geological Survey (USGS) Land Cover Trends project is analyzing contemporary (1973-2000) land-cover change in the conterminous United States, providing ecoregion-by-ecoregion estimates of the rates of change, descriptive transition matrices, and changes in landscape metrics. The FORecasting SCEnarios of future land-cover (FORE-SCE) model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land-cover change through 2050 for the southeastern United States. Prescriptions for future proportions of land cover for this application were provided by ecoregion-based extrapolations of historical change. Logistic regression was used to develop relationships between suspected drivers of land-cover change and land cover, resulting in the development of probability-of-occurrence surfaces for each unique land-cover type. Forest stand age was initially established with Forest Inventory and Analysis (FIA) data and tracked through model iterations. The spatial allocation procedure placed patches of new land cover on the landscape until the scenario prescriptions were met, using measured Land Cover Trends data to guide patch characteristics and the probability surfaces to guide placement. The approach provides an efficient method for extrapolating historical land-cover trends and is amenable to the incorporation of more detailed and focused studies for the establishment of scenario prescriptions.

Rates, drivers and impacts of reforestation and afforestation in Western Rwanda.

NASA Astrophysics Data System (ADS)

Arakwiye, B.; Rogan, J.; Eastman, R.

2017-12-01

Within East-Africa, Rwanda is the most heavily populated, predominantly rural country where 85% of the population heavily depends on smallholder agriculture and natural resources. The biodiversity-rich, high elevation western region of Rwanda has historically experienced unprecedented forest loss and degradation, resulting in major losses of wildlife habitat, biodiversity and ecosystem services. Forest loss peaked during the 1990s civil wars and genocide when forests sheltered both civilians and combatants or were cleared to resettle refugees. Since the 2000s, national and international initiatives have encouraged reforestation and afforestation activities aiming to reconnect remnant fragments and improve environmental resiliency. However, consistent spatially- and temporally-explicit regional assessments of these afforestation and reforestation activities are still lacking. This study links satellite and in situ socio-ecological data to document the rates and drivers of reforestation and afforestation in Western Rwanda. Random Forest classification was used to map the extent of forests using multitemporal Landsat-5, -7 and -8 images covering the period from 1986 to 2016. Semi-structured interviews with stakeholders were used to identify the potential drivers of afforestation and reforestation. Preliminary results show a net increase of 0.05% in forest cover from 2001 to 2016, predominantly occurring on former croplands and pasture/grasslands. Around 90% of afforested and reforested areas are patchy monocultures of Eucalyptus and Alnus species, valued for timber and wood by-products but with relatively low potential to provide other ecosystem services compared to native tree species. These results highlight the need for an integrated approach to afforestation and reforestation to ensure the sustainable provision of diverse ecosystem services.

Landscape level reforestation priorities for forest breeding landbirds in the Mississippi Alluvial Valley

USGS Publications Warehouse

Twedt, D.J.; Uihlein, W.B.; Fredrickson, L.H.; King, S.L.; Kaminski, R.M.

2005-01-01

Thousands of ha of cleared wetlands are being reforested annually in the Mississippi Alluvial Valley (MAV). Despite the expansive and long-term impacts of reforestation on the biological communities of the MAV, there is generally a lack of landscape level planning in its implementation. To address this deficiency we used raster-based digital data to assess the value of forest restoration to migratory landbirds for each ha within the MAV. Raster themes were developed that reflected distance from 3 existing forest cover parameters: (1) extant forest, (2) contiguous forest patches between 1,012 and 40,000 ha, and (3) forest cores with contiguous area 1 km from an agricultural, urban, or pastoral edge. Two additional raster themes were developed that combined information on the proportion of forest cover and average size of forest patches, respectively, within landscapes of 50,000, 100,000, 150,000, and 200,000 ha. Data from these 5 themes were amalgamated into a single raster using a weighting system that gave increased emphasis to existing forest cores, larger forest patches, and moderately forested landscapes while deemphasizing reforestation near small or isolated forest fragments and within largely agricultural landscapes. This amalgamated raster was then modified by the geographic location of historical forest cover and the current extent of public land ownership to assign a reforestation priority score to each ha in the MAV. However, because reforestation is not required on areas with extant forest cover and because restoration is unlikely on areas of open water and urban communities, these lands were not assigned a reforestation priority score. These spatially explicit reforestation priority scores were used to simulate reforestation of 368,000 ha (5%) of the highest priority lands in the MAV. Targeting restoration to these high priority areas resulted in a 54% increase in forest core - an area of forest core that exceeded the area of simulated reforestation. Bird Conservation Regions, developed within the framework of the Partners in Flight: Mississippi Alluvial Valley Bird Conservation Plan, encompassed a large proportion (circa 70%) of the area with highest priority for reforestation. Similarly, lands with high reforestation priority often were enrolled in the Wetland Reserve Program.

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

Pre-industrial baseline variation of upper midwestern forests in the United States

NASA Astrophysics Data System (ADS)

Dawson, A.; Paciorek, C. J.; Goring, S. J.; Williams, J. W.; Jackson, S. T.; McLachlan, J. S.

2016-12-01

Terrestrial ecosystems play an important role in Earth systems processes, yet we still do not understand how they respond to changes in climate. While it has been argued that terrestrial ecosystems were fairly stable (by Quaternary standards) in the millennia before major anthropogenic disruption, others have emphasized vegetation response to environmental variability during this time. These competing perspectives are not necessarily in conflict, but argue for a quantitative assessment of forest ecosystem variability over the last several millennia. Here we reconstruct maps of forest composition for the last two millenia, with uncertainty. To do this, we use a network of fossil pollen records - the most reliable paleoecological proxy for forest composition. We link the fossil pollen records to public land survey forest composition using a Bayesian hierarchical model which accounts for key processes including pollen production and dispersal. The model is calibrated using data from the pre-settlement time with the hope of minimizing anthropogenic impacts. Process parameters are estimated in the calibration phase, and are subsequently used in the prediction phase to generate spatially explicit maps of relative species composition across the upper Midwestern US over the last 2000 years, with robust uncertainty estimates. Estimates of forest composition and uncertainty show many previously noted vegetation shifts, three of which we discuss here. First, we see expansion of the hemlock range into western Wisconsin. Second, we see changes along the prairie-forest ecotone. Third, we see significant increases in elm at approximately 500 YBP in the region known as the Minnesota Big Woods. These changes are significant in both a statistical and ecological sense, but the scale of these changes is small relative to changes in the early holocene. Our novel spatio-temporal composition estimates will be used to improve the forecasting capabilities of ecosystem models.

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

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...

The Conservation Value of Traditional Rural Landscapes: The Case of Woodpeckers in Transylvania, Romania.

PubMed

Dorresteijn, Ine; Hartel, Tibor; Hanspach, Jan; von Wehrden, Henrik; Fischer, Joern

2013-01-01

Land use change is a major threat to global biodiversity. Forest species face the dual threats of deforestation and intensification of forest management. In regions where forests are under threat, rural landscapes that retain structural components of mature forests potentially provide valuable additional habitat for some forest species. Here, we illustrate the habitat value of traditional wood pastures for a woodpecker assemblage of six species in southern Transylvania, Romania. Wood pastures are created by long-term stable silvo-pastoral management practices, and are composed of open grassland with scattered large, old trees. Because of their demanding habitat requirements, woodpeckers share habitat with many other bird species, and have been considered as possible indicator species for bird species diversity. We first compared woodpecker assemblages between forests and wood pastures. Second, we grouped features of wood pastures into three spatial contexts and addressed how these features related to the occurrence of three woodpecker species that are formally protected. Woodpecker species composition, but not the number of species, differed between forests and wood pastures, with the green woodpecker occurring more commonly in wood pastures, and the lesser spotted woodpecker more commonly in forests. Within wood pastures, the intermediate context (especially surrounding forest cover) best explained the presence of the grey-headed and middle spotted woodpecker. By contrast, variables describing local vegetation structure and characteristics of the surrounding landscape did not affect woodpecker occurrence in wood pastures. In contrast to many other parts of Europe, in which several species of woodpeckers have declined, the traditional rural landscape of Transylvania continues to provide habitat for several woodpecker species, both in forests and wood pastures. Given the apparent habitat value of wood pastures for woodpeckers we recommend wood pastures be explicitly considered in relevant policies of the European Union, namely the Habitats Directive and the EU Common Agricultural Policy.

Technical aspects of the forest carbon inventory of the United States: recent past and near future

Treesearch

Christopher W. Woodall; James E. Smith; Grant M. Domke; Sean P. Healey; John W. Coulston; Andrew N. Gray

2012-01-01

The Forest Inventory and Analysis program of the U.S. Forest Service has explicitly assumed responsibility for providing an inventory of the U.S. forests' carbon stocks and stock change to the U.S. Environmental Protection Agency for numerous years to meet obligations to the United Nations Framework Convention on Climate Change. Recent improvements, plans for the...

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

Predictive modelling of contagious deforestation in the Brazilian Amazon.

PubMed

Rosa, Isabel M D; Purves, Drew; Souza, Carlos; Ewers, Robert M

2013-01-01

Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges "bottom up", as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated-pre- and post-PPCDAM ("Plano de Ação para Proteção e Controle do Desmatamento na Amazônia")-the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protection could allow deforestation to reach the core, which is currently experiencing low deforestation rates due to its isolation.

Predictive Modelling of Contagious Deforestation in the Brazilian Amazon

PubMed Central

Rosa, Isabel M. D.; Purves, Drew; Souza, Carlos; Ewers, Robert M.

2013-01-01

Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges “bottom up”, as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated–pre- and post-PPCDAM (“Plano de Ação para Proteção e Controle do Desmatamento na Amazônia”)–the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protection could allow deforestation to reach the core, which is currently experiencing low deforestation rates due to its isolation. PMID:24204776

Spatial and seasonal variations of leaf area index (LAI) in subtropical secondary forests related to floristic composition and stand characters

NASA Astrophysics Data System (ADS)

Zhu, Wenjuan; Xiang, Wenhua; Pan, Qiong; Zeng, Yelin; Ouyang, Shuai; Lei, Pifeng; Deng, Xiangwen; Fang, Xi; Peng, Changhui

2016-07-01

Leaf area index (LAI) is an important parameter related to carbon, water, and energy exchange between canopy and atmosphere and is widely applied in process models that simulate production and hydrological cycles in forest ecosystems. However, fine-scale spatial heterogeneity of LAI and its controlling factors have yet to be fully understood in Chinese subtropical forests. We used hemispherical photography to measure LAI values in three subtropical forests (Pinus massoniana-Lithocarpus glaber coniferous and evergreen broadleaved mixed forests, Choerospondias axillaris deciduous broadleaved forests, and L. glaber-Cyclobalanopsis glauca evergreen broadleaved forests) from April 2014 to January 2015. Spatial heterogeneity of LAI and its controlling factors were analysed using geostatistical methods and the generalised additive models (GAMs) respectively. Our results showed that LAI values differed greatly in the three forests and their seasonal variations were consistent with plant phenology. LAI values exhibited strong spatial autocorrelation for the three forests measured in January and for the L. glaber-C. glauca forest in April, July, and October. Obvious patch distribution pattern of LAI values occurred in three forests during the non-growing period and this pattern gradually dwindled in the growing season. Stem number, crown coverage, proportion of evergreen conifer species on basal area basis, proportion of deciduous species on basal area basis, and forest types affected the spatial variations in LAI values in January, while stem number and proportion of deciduous species on basal area basis affected the spatial variations in LAI values in July. Floristic composition, spatial heterogeneity, and seasonal variations should be considered for sampling strategy in indirect LAI measurement and application of LAI to simulate functional processes in subtropical forests.

Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.

PubMed

Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane

2018-02-21

Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated with great care. The uncertainties in the LiDAR-estimated AGB propagate further in the wall-to-wall map and can be up to 150%. Thus, when a two-stage up-scaling method is applied, it is crucial to characterize the uncertainties at all stages in order to generate robust results. Considering the findings mentioned above LiDAR can be used as an extension to NFI for example for areas that are difficult or not possible to access.

Connectivity in modelling subsurface stormflow and tracer transport in a forested hillslope

NASA Astrophysics Data System (ADS)

Laine-Kaulio, Hanne; Koivusalo, Harri

2016-04-01

Preferential flow characterizes subsurface water movement in forested hillslopes. Connectivity of preferential flowpaths in soil, as well as connections between the preferential flowpaths and the soil matrix, control the flow patterns in hillslopes. We simulated subsurface stormflow and tracer transport within a forested hillslope section in Eastern Finland with a modifiable and detailed, physically-based 3-D dual-permeability model. The objective was to investigate the role of flowpath connectivity in capturing the observed migration velocity and concentration status of a tracer plume during the different stages of an irrigation experiment. Hypotheses to explain the observed transport behaviour were formulated based on observed spatial variations in the soil properties. The hypotheses were then tested by running corresponding model versions against spatial high-frequency data from the irrigation experiment. The 3-D distribution of preferential flowpaths, and the connections and disconnections between them, had the most crucial role in capturing the observed transport event with the model. Lateral by-pass flow in the preferential flow network and the transmissivity feedback phenomenon dominated the tracer transport. However, disconnections in lateral preferential flow restrained the transport, making the transport route devious instead of being directly lateral. These disconnections were caused by spots of cemented soil material. Stones had an opposite effect on the flow route formation compared to the cemented spots because preferential flowpaths were present on stone surfaces. Preferential flowpaths related to stones were linked with other types of preferential flowpaths in soil, facilitating the connectivity of preferential flowpaths within the entire hillslope. To take into account the discontinuity in lateral preferential flow and the tortuosity of the dominant flow routes in the model, an explicit representation of the 3-D distribution of saturated hydraulic conductivity in the preferential flow network was required. In addition, with-depth changing porosity values of both pore domains of soil, i.e., the preferential flowpaths and the soil matrix, as well as explicit descriptions of local water losses into the underlying bedrock, were found important for successful simulations. Other investigated model features, including complexity in the values of the rest of the model parameters and in the calculation routines used in describing the flow connections between the preferential flowpaths and the soil matrix, were not found beneficial for the model outcome.

Using Moran's I and GIS to study spatial pattern of forest litter carbon density in typical subtropical region, China

NASA Astrophysics Data System (ADS)

Fu, W. J.; Jiang, P. K.; Zhou, G. M.; Zhao, K. L.

2013-12-01

The spatial variation of forest litter carbon (FLC) density in the typical subtropical forests in southeast China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (South-North) × 6 km (East-West) grid system in Zhejiang Province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha-1 to 8841.3 kg ha-1, with an average of 1786.7 kg ha-1. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using Local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas. While Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns in distribution map were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS could be used to study spatial patterns of environmental variables related to forest ecosystem.

Changes of forest cover and disturbance regimes in the mountain forests of the Alps☆

PubMed Central

Bebi, P.; Seidl, R.; Motta, R.; Fuhr, M.; Firm, D.; Krumm, F.; Conedera, M.; Ginzler, C.; Wohlgemuth, T.; Kulakowski, D.

2017-01-01

Natural disturbances, such as avalanches, snow breakage, insect outbreaks, windthrow or fires shape mountain forests globally. However, in many regions over the past centuries human activities have strongly influenced forest dynamics, especially following natural disturbances, thus limiting our understanding of natural ecological processes, particularly in densely-settled regions. In this contribution we briefly review the current understanding of changes in forest cover, forest structure, and disturbance regimes in the mountain forests across the European Alps over the past millennia. We also quantify changes in forest cover across the entire Alps based on inventory data over the past century. Finally, using the Swiss Alps as an example, we analyze in-depth changes in forest cover and forest structure and their effect on patterns of fire and wind disturbances, based on digital historic maps from 1880, modern forest cover maps, inventory data on current forest structure, topographical data, and spatially explicit data on disturbances. This multifaceted approach presents a long-term and detailed picture of the dynamics of mountain forest ecosystems in the Alps. During pre-industrial times, natural disturbances were reduced by fire suppression and land-use, which included extraction of large amounts of biomass that decreased total forest cover. More recently, forest cover has increased again across the entire Alps (on average +4% per decade over the past 25–115 years). Live tree volume (+10% per decade) and dead tree volume (mean +59% per decade) have increased over the last 15–40 years in all regions for which data were available. In the Swiss Alps secondary forests that established after 1880 constitute approximately 43% of the forest cover. Compared to forests established previously, post-1880 forests are situated primarily on steep slopes (>30°), have lower biomass, a more aggregated forest structure (primarily stem-exclusion stage), and have been more strongly affected by fires, but less affected by wind disturbance in the 20th century. More broadly, an increase in growing stock and expanding forest areas since the mid-19th century have - along with climatic changes - contributed to an increasing frequency and size of disturbances in the Alps. Although many areas remain intensively managed, the extent, structure, and dynamics of the forests of the Alps reflect natural drivers more strongly today than at any time in the past millennium. PMID:28860675

Changes of forest cover and disturbance regimes in the mountain forests of the Alps.

PubMed

Bebi, P; Seidl, R; Motta, R; Fuhr, M; Firm, D; Krumm, F; Conedera, M; Ginzler, C; Wohlgemuth, T; Kulakowski, D

2017-03-15

Natural disturbances, such as avalanches, snow breakage, insect outbreaks, windthrow or fires shape mountain forests globally. However, in many regions over the past centuries human activities have strongly influenced forest dynamics, especially following natural disturbances, thus limiting our understanding of natural ecological processes, particularly in densely-settled regions. In this contribution we briefly review the current understanding of changes in forest cover, forest structure, and disturbance regimes in the mountain forests across the European Alps over the past millennia. We also quantify changes in forest cover across the entire Alps based on inventory data over the past century. Finally, using the Swiss Alps as an example, we analyze in-depth changes in forest cover and forest structure and their effect on patterns of fire and wind disturbances, based on digital historic maps from 1880, modern forest cover maps, inventory data on current forest structure, topographical data, and spatially explicit data on disturbances. This multifaceted approach presents a long-term and detailed picture of the dynamics of mountain forest ecosystems in the Alps. During pre-industrial times, natural disturbances were reduced by fire suppression and land-use, which included extraction of large amounts of biomass that decreased total forest cover. More recently, forest cover has increased again across the entire Alps (on average +4% per decade over the past 25-115 years). Live tree volume (+10% per decade) and dead tree volume (mean +59% per decade) have increased over the last 15-40 years in all regions for which data were available. In the Swiss Alps secondary forests that established after 1880 constitute approximately 43% of the forest cover. Compared to forests established previously, post-1880 forests are situated primarily on steep slopes (>30°), have lower biomass, a more aggregated forest structure (primarily stem-exclusion stage), and have been more strongly affected by fires, but less affected by wind disturbance in the 20th century. More broadly, an increase in growing stock and expanding forest areas since the mid-19th century have - along with climatic changes - contributed to an increasing frequency and size of disturbances in the Alps. Although many areas remain intensively managed, the extent, structure, and dynamics of the forests of the Alps reflect natural drivers more strongly today than at any time in the past millennium.

Novel and Lost Forests in the Upper Midwestern United States, from New Estimates of Settlement-Era Composition, Stem Density, and Biomass

PubMed Central

Mladenoff, David J.; Cogbill, Charles V.; Record, Sydne; Paciorek, Christopher J.; Jackson, Stephen T.; Dietze, Michael C.; Dawson, Andria; Matthes, Jaclyn Hatala; McLachlan, Jason S.; Williams, John W.

2016-01-01

Background EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection. Changes in Forest Structure We compare pre-settlement to modern forests using US Forest Service Forest Inventory and Analysis (FIA) data to show the prevalence of lost forests (pre-settlement forests with no current analog), and novel forests (modern forests with no past analogs). Differences between pre-settlement and modern forests are spatially structured owing to differences in land-use impacts and accompanying ecological responses. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 28% of all FIA cells, and 28% of pre-settlement forests no longer exist in a modern context. Lost forests include tamarack forests in northeastern Minnesota, hemlock and cedar dominated forests in north-central Wisconsin and along the Upper Peninsula of Michigan, and elm, oak, basswood and ironwood forests along the forest-prairie boundary in south central Minnesota and eastern Wisconsin. Novel FIA forest assemblages are distributed evenly across the region, but novelty shows a strong relationship to spatial distance from remnant forests in the upper Midwest, with novelty predicted at between 20 to 60km from remnants, depending on historical forest type. The spatial relationships between remnant and novel forests, shifts in ecotone structure and the loss of historic forest types point to significant challenges for land managers if landscape restoration is a priority. The spatial signals of novelty and ecological change also point to potential challenges in using modern spatial distributions of species and communities and their relationship to underlying geophysical and climatic attributes in understanding potential responses to changing climate. The signal of human settlement on modern forests is broad, spatially varying and acts to homogenize modern forests relative to their historic counterparts, with significant implications for future management. PMID:27935944

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.

Novel and Lost Forests in the Upper Midwestern United States, from New Estimates of Settlement-Era Composition, Stem Density, and Biomass.

PubMed

Goring, Simon J; Mladenoff, David J; Cogbill, Charles V; Record, Sydne; Paciorek, Christopher J; Jackson, Stephen T; Dietze, Michael C; Dawson, Andria; Matthes, Jaclyn Hatala; McLachlan, Jason S; Williams, John W

2016-01-01

EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection. We compare pre-settlement to modern forests using US Forest Service Forest Inventory and Analysis (FIA) data to show the prevalence of lost forests (pre-settlement forests with no current analog), and novel forests (modern forests with no past analogs). Differences between pre-settlement and modern forests are spatially structured owing to differences in land-use impacts and accompanying ecological responses. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 28% of all FIA cells, and 28% of pre-settlement forests no longer exist in a modern context. Lost forests include tamarack forests in northeastern Minnesota, hemlock and cedar dominated forests in north-central Wisconsin and along the Upper Peninsula of Michigan, and elm, oak, basswood and ironwood forests along the forest-prairie boundary in south central Minnesota and eastern Wisconsin. Novel FIA forest assemblages are distributed evenly across the region, but novelty shows a strong relationship to spatial distance from remnant forests in the upper Midwest, with novelty predicted at between 20 to 60km from remnants, depending on historical forest type. The spatial relationships between remnant and novel forests, shifts in ecotone structure and the loss of historic forest types point to significant challenges for land managers if landscape restoration is a priority. The spatial signals of novelty and ecological change also point to potential challenges in using modern spatial distributions of species and communities and their relationship to underlying geophysical and climatic attributes in understanding potential responses to changing climate. The signal of human settlement on modern forests is broad, spatially varying and acts to homogenize modern forests relative to their historic counterparts, with significant implications for future management.

The effect of spatially variable overstory on the understory light environment of an open-canopied longleaf pine forest

Treesearch

Michael A. Battaglia; Pu Mou; Brian Palik; Robert J. Mitchell

2002-01-01

Spatial aggregation of forest structure strongly regulates understory light and its spatial variation in longleaf pine (Pinus palustris Mill.) forest ecosystems. Previous studies have demonstrated that light availability strongly influences longleaf pine seedling growth. In this study, the relationship between spatial structure of a longleaf pine...

Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

Treesearch

Benjamin A. Crabb; James A. Powell; Barbara J. Bentz

2012-01-01

Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...

Adaptive management of forest ecosystems: did some rubber hit the road?

Treesearch

B.T. Bormann; R.W. Haynes; J.R. Martin

2007-01-01

Although many scientists recommend adaptive management for large forest tracts, there is little evidence that its use has been effective at this scale. One exception is the 10-million-hectare Northwest Forest Plan, which explicitly included adaptive management in its design. Evidence from 10 years of implementing the plan suggests that formalizing adaptive steps and...

Non-random species loss in a forest herbaceous layer following nitrogen addition

Treesearch

Christopher A. ​Walter; Mary Beth Adams; Frank S. Gilliam; William T. Peterjohn

2017-01-01

Nitrogen (N) additions have decreased species richness (S) in hardwood forest herbaceous layers, yet the functional mechanisms for these decreases have not been explicitly evaluated.We tested two hypothesized mechanisms, random species loss (RSL) and non-random species loss (NRSL), in the hardwood forest herbaceous layer of a long-term, plot-scale...

Living Trees are a Major Source of Methane in the Temperate Forest

NASA Astrophysics Data System (ADS)

Covey, Kristofer

2017-04-01

Globally, forests sequester about 1.1 ± 0.8 Pg C yr-1, an ecosystem service worth hundreds of billions of dollars annually. Following the COP21 meeting in Paris, an international consensus emerged: The protection and expansion of forests worldwide is a necessary component of climate mitigation strategies to limit warming to less than 2°C. The physiological processes governing sequestration of CO2 in living trees are well studied and the resulting pattern in global forest carbon sequestration is clear. The role living trees play in the production and emission of methane (CH4) remains unclear, despite the fact it has the potential to offset climate benefits of forest CO2 sequestration. A known but largely unexplored pathway of forest CH4 production involves microbial-based methanogenesis in the wood of living trees. In the first regional-scale study of tree trunk gas composition, we examine the ubiquity and potential source strength of this pathway. Trunk methane concentrations were as high as 67.4% by volume (375,000-times atmospheric), with the highest concentrations found in older angiosperms (18,293 μLṡL-1 ± 3,096). Bark flux chambers from 23 living trees show emissions under field conditions, and large static chambers demonstrate high rates of production in felled Acer rubrum trunk sections. Diffusion flux modeling of trunk concentrations suggests wood-based microflora could produce a global CH4 efflux of 26 Tg CH4 yr-1. Applying these fluxes to provide a spatially explicit map of trunk-based CH4 flux, we estimate the potential relationship between carbon sequestration rates and CH4 emission by forest trees in Eastern North America. Methane emissions from the trunk-based methanogenic pathway could reduce the average climate mitigation value of these temperate forests by 10-30%. We highlight the need to improve earth systems models to account for the full complexity of forest climate interactions and provide a data layer useful in reducing large uncertainty in global methane budgets.

Coupled nutrient cycling determines tropical forest trajectory under elevated CO2.

NASA Astrophysics Data System (ADS)

Bouskill, N.; Zhu, Q.; Riley, W. J.

2017-12-01

Tropical forests have a disproportionate capacity to affect Earth's climate relative to their areal extent. Despite covering just 12 % of land surface, tropical forests account for 35 % of global net primary productivity and are among the most significant of terrestrial carbon stores. As atmospheric CO2 concentrations increase over the next century, the capacity of tropical forests to assimilate and sequester anthropogenic CO2 depends on limitation by multiple factors, including the availability of soil nutrients. Phosphorus availability has been considered to be the primary factor limiting metabolic processes within tropical forests. However, recent evidence points towards strong spatial and temporal co-limitation of tropical forests by both nitrogen and phosphorus. Here, we use the Accelerated Climate Modeling for Energy (ACME) Land Model (ALMv1-ECA-CNP) to examine how nutrient cycles interact and affect the trajectory of the tropical forest carbon sink under, (i) external nutrient input, (ii) climate (iii) elevated CO2, and (iv) a combination of 1-3. ALMv1 includes recent theoretical advances in representing belowground competition between roots, microbes and minerals for N and P uptake, explicit interactions between the nitrogen and phosphorus cycles (e.g., phosphatase production and nitrogen fixation), the dynamic internal allocation of plant N and P resources, and the integration of global datasets of plant physiological traits. We report nutrient fertilization (N, P, N+P) predictions for four sites in the tropics (El Verde, Puerto Rico, Barro Colorado Island, Panama, Manaus, Brazil and the Osa Peninsula, Coast Rica) to short-term nutrient fertilization (N, P, N+P), and benchmarking of the model against a meta-analysis of forest fertilization experiments. Subsequent simulations focus on the interaction of the carbon, nitrogen, and phosphorus cycles across the tropics with a focus on the implications of coupled nutrient cycling and the fate of the tropical forest carbon sink. Our results highlight the importance of transient CNP allocation, leaf-level stoichiometric controls on photosynthesis, and trade-offs between above and belowground plant investments.

Total belowground carbon flux in subalpine forests is related to leaf area index, soil nitrogen, and tree height

USGS Publications Warehouse

Berryman, Erin Michele; Ryan, Michael G.; Bradford, John B.; Hawbaker, Todd J.; Birdsey, R.

2016-01-01

In forests, total belowground carbon (C) flux (TBCF) is a large component of the C budget and represents a critical pathway for delivery of plant C to soil. Reducing uncertainty around regional estimates of forest C cycling may be aided by incorporating knowledge of controls over soil respiration and TBCF. Photosynthesis, and presumably TBCF, declines with advancing tree size and age, and photosynthesis increases yet C partitioning to TBCF decreases in response to high soil fertility. We hypothesized that these causal relationships would result in predictable patterns of TBCF, and partitioning of C to TBCF, with natural variability in leaf area index (LAI), soil nitrogen (N), and tree height in subalpine forests in the Rocky Mountains, USA. Using three consecutive years of soil respiration data collected from 22 0.38-ha locations across three 1-km2 subalpine forested landscapes, we tested three hypotheses: (1) annual soil respiration and TBCF will show a hump-shaped relationship with LAI; (2) variability in TBCF unexplained by LAI will be related to soil nitrogen (N); and (3) partitioning of C to TBCF (relative to woody growth) will decline with increasing soil N and tree height. We found partial support for Hypothesis 1 and full support for Hypotheses 2 and 3. TBCF, but not soil respiration, was explained by LAI and soil N patterns (r2 = 0.49), and the ratio of annual TBCF to TBCF plus aboveground net primary productivity (ANPP) was related to soil N and tree height (r2 = 0.72). Thus, forest C partitioning to TBCF can vary even within the same forest type and region, and approaches that assume a constant fraction of TBCF relative to ANPP may be missing some of this variability. These relationships can aid with estimates of forest soil respiration and TBCF across landscapes, using spatially explicit forest data such as national inventories or remotely sensed data products.

The organisation of spatial and temporal relations in memory.

PubMed

Rondina, Renante; Curtiss, Kaitlin; Meltzer, Jed A; Barense, Morgan D; Ryan, Jennifer D

2017-04-01

Episodic memories are comprised of details of "where" and "when"; spatial and temporal relations, respectively. However, evidence from behavioural, neuropsychological, and neuroimaging studies has provided mixed interpretations about how memories for spatial and temporal relations are organised-they may be hierarchical, fully interactive, or independent. In the current study, we examined the interaction of memory for spatial and temporal relations. Using explicit reports and eye-tracking, we assessed younger and older adults' memory for spatial and temporal relations of objects that were presented singly across time in unique spatial locations. Explicit change detection of spatial relations was affected by a change in temporal relations, but explicit change detection of temporal relations was not affected by a change in spatial relations. Younger and older adults showed eye movement evidence of incidental memory for temporal relations, but only younger adults showed eye movement evidence of incidental memory for spatial relations. Together, these findings point towards a hierarchical organisation of relational memory. The implications of these findings are discussed in the context of the neural mechanisms that may support such a hierarchical organisation of memory.

From Cycle Rooted Spanning Forests to the Critical Ising Model: an Explicit Construction

NASA Astrophysics Data System (ADS)

de Tilière, Béatrice

2013-04-01

Fisher established an explicit correspondence between the 2-dimensional Ising model defined on a graph G and the dimer model defined on a decorated version {{G}} of this graph (Fisher in J Math Phys 7:1776-1781, 1966). In this paper we explicitly relate the dimer model associated to the critical Ising model and critical cycle rooted spanning forests (CRSFs). This relation is established through characteristic polynomials, whose definition only depends on the respective fundamental domains, and which encode the combinatorics of the model. We first show a matrix-tree type theorem establishing that the dimer characteristic polynomial counts CRSFs of the decorated fundamental domain {{G}_1}. Our main result consists in explicitly constructing CRSFs of {{G}_1} counted by the dimer characteristic polynomial, from CRSFs of G 1, where edges are assigned Kenyon's critical weight function (Kenyon in Invent Math 150(2):409-439, 2002); thus proving a relation on the level of configurations between two well known 2-dimensional critical models.

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Development of LiDAR aware allometrics for Abies grandis: A Case Study

NASA Astrophysics Data System (ADS)

Stone, G. A.; Tinkham, W. T.; Smith, A. M.; Hudak, A. T.; Falkowski, M. J.; Keefe, R.

2012-12-01

Forest managers rely increasingly on accurate allometric relationships to inform decisions regarding stand rotations, silvilcultural treatments, timber harvesting, and biometric modeling. At the same time, advances in remote sensing techniques like LiDAR (light detection and ranging) have brought about opportunities to advance how we assess forest growth, and thus are contributing to the need for more accurate allometries. Past studies have attempted to relate LiDAR data to both plot and individual tree measures of forest biomass. However, many of these studies have been limited by the accuracy of their coincident observations. In this study, 24 Abies grandis were measured, felled, and dissected for the explicit objective of developing LiDAR aware allometrics. The analysis predicts spatial variables of competition, growth potential (e.g, trees per acre, aspect, elevation, etc.) and common statistical distributional metrics (e.g., mean, mode, percentiles, variance, skewness, kurtosis, etc.) derived from LiDAR point cloud returns to coincident in situ measures of Abies grandis stem biomass. The resulting allometries exemplify a new approach for predicting structural attributes of interest (biomass, basal area, volume, etc.) directly from LiDAR point cloud data, precluding the measurement errors that are propogated by indirectly predicting these structure attributes of interest from LiDAR data using traditional plot-based measurements.

A modelling approach to estimate carbon emissions from D.R.C. deforestation

NASA Astrophysics Data System (ADS)

Najdovski, Nicolas; Poulter, Benjamin; Defourny, Pierre; Moreau, Inès; Maignan, Fabienne; Ciais, Philippe; Verhegghen, Astrid; Kibambe Lubamba, Jean-Paul; Jungers, Quentin; De Weirdt, Marjolein; Verbeeck, Hans; MacBean, Natasha; Peylin, Philippe

2014-05-01

With its 1.8 million squared kilometres, the Congo basin dense forest represents the second largest contiguous forest of the world. These extensive forest ecosystems play a significant role in the regulation of global climate by their potential carbon dioxide emissions and carbon storage. Under a stable climate, the vegetation, assumed to be at the equilibrium, is known to present neutral emissions over a year with seasonal variations. However, modifications in temperatures, precipitations, CO2 atmospheric concentrations have the potential to modify this balance leading to higher or lower biomass storage. In addition, deforestation and forest degradation have played a significant role over the past several decades and are expected to become increasingly important in the future. Here, we quantify the relative effects of deforestation and 21st century climate change on carbon emissions in Congo Basin over the next three decades (2005-2035). Carbon dioxide emissions are estimated using a series of moderate resolution (10 km) vegetation maps merged with spatially explicit deforestation projections and developed to work with a prognostic carbon cycle model. The inversion of the deforestation model allowed hindcast land-use patterns back to 1800 by using land cover change rates based on the HYDE database. Simulations were made over the Democratic Republic of Congo (DRC) using the ORCHIDEE dynamic global vegetation model with climate forcing from the CMIP5 Representative Concentration Pathway 8.5 scenario for the HadGEM2. Two simulations were made, a reference simulation with land cover fixed at 2005 and a land cover change simulation with changing climate and CO2, to quantify the net land cover change emissions and climate emissions directly. Because of the relatively high resolution of the model simulations, the spatial patterns of human-driven carbon losses can be tracked in the context of climate change, providing information for mitigation and vulnerability activities.

On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

2010-12-01

A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

What's Upstream? GIS's critical role in developing nutrient ...

EPA Pesticide Factsheets

Eutrophication due to excess levels of nitrogen and phosphorus can seriously impair ecological function in estuaries. Protective criteria for nutrients are difficult to establish because the source can vary spatially and seasonally, originate either from the watershed or the ocean, and be natural or anthropogenic. GIS tools and processes can help in developing nutrient criteria by establishing reference conditions representative of natural background nutrient levels. Along the Oregon Coast in the Pacific Northwest, the primary source of nutrients in the wet season (November-April) is generally riverine. We delineated and extracted explicit spatial data from watersheds upstream of riverine water quality monitoring stations for parametric comparison to recorded nutrient levels. The SPARROW model (Wise and Johnson, 2011) was used to estimate relative contributions of nutrient sources at each station. Both raster and vector spatial data were used and include land use / land cover, demography, geology, terrain, precipitation and forest type. The relationships of nutrients to spatial data were then explored as an approach to establishing the reference expectation. The abstract introduces Geographic Information Systems (GIS) tools and processes employed for research conducted under the Safe and Sustainable Water Resources (SSWR) Task 2.3A, entitled “Nutrient Management for Sustainability of Aquatic Ecosystems.” One of the goals of the EPA Office of Water is to

Spatial patterns and controls on historical fire regimes and forest structure in the Klamath Mountains

Treesearch

Alan H. Taylor; Carl N. Skinner

2003-01-01

Fire exclusion in mixed conifer forests has increased the risk of fire due to decades of fuel accumulation. Restoration of fire into altered forests is a challenge because of a poor understanding of the spatial and temporal dynamics of fire regimes. In this study the spatial and temporal characteristics of fire regimes and forest age structure are reconstructed in a...

Genetic censusing identifies an unexpectedly sizeable population of an endangered large mammal in a fragmented forest landscape.

PubMed

McCarthy, Maureen S; Lester, Jack D; Howe, Eric J; Arandjelovic, Mimi; Stanford, Craig B; Vigilant, Linda

2015-08-25

As habitat degradation and fragmentation continue to impact wildlife populations around the world, it is critical to understand the behavioral flexibility of species in these environments. In Uganda, the mostly unprotected forest fragment landscape between the Budongo and Bugoma Forests is a potential corridor for chimpanzees, yet little is known about the status of chimpanzee populations in these fragments. From 2011 through 2013, we noninvasively collected 865 chimpanzee fecal samples across 633 km(2) and successfully genotyped 662 (77%) at up to 14 microsatellite loci. These genotypes corresponded to 182 chimpanzees, with a mean of 3.5 captures per individual. We obtained population size estimates of 256 (95% confidence interval 246-321) and 319 (288-357) chimpanzees using capture-with-replacement and spatially explicit capture-recapture models, respectively. The spatial clustering of associated genotypes suggests the presence of at least nine communities containing a minimum of 8-33 individuals each. Putative community distributions defined by the locations of associated genotypes correspond well with the distribution of 14 Y-chromosome haplotypes. These census figures are more than three times greater than a previous estimate based on an extrapolation from small-scale nest count surveys that tend to underestimate population size. The distribution of genotype clusters and Y-chromosome haplotypes together indicate the presence of numerous male philopatric chimpanzee communities throughout the corridor habitat. Our findings demonstrate that, despite extensive habitat loss and fragmentation, chimpanzees remain widely distributed and exhibit distinct community home ranges. Our results further imply that elusive and rare species may adapt to degraded habitats more successfully than previously believed. Their long-term persistence is unlikely, however, if protection is not afforded to them and habitat loss continues unabated.

Spatial and temporal patterns of carbon storage in forest ecosystems on Hainan island, southern China.

PubMed

Ren, Hai; Li, Linjun; Liu, Qiang; Wang, Xu; Li, Yide; Hui, Dafeng; Jian, Shuguang; Wang, Jun; Yang, Huai; Lu, Hongfang; Zhou, Guoyi; Tang, Xuli; Zhang, Qianmei; Wang, Dong; Yuan, Lianlian; Chen, Xubing

2014-01-01

Spatial and temporal patterns of carbon (C) storage in forest ecosystems significantly affect the terrestrial C budget, but such patterns are unclear in the forests in Hainan Province, the largest tropical island in China. Here, we estimated the spatial and temporal patterns of C storage from 1993-2008 in Hainan's forest ecosystems by combining our measured data with four consecutive national forest inventories data. Forest coverage increased from 20.7% in the 1950s to 56.4% in the 2010s. The average C density of 163.7 Mg C/ha in Hainan's forest ecosystems in this study was slightly higher than that of China's mainland forests, but was remarkably lower than that in the tropical forests worldwide. Total forest ecosystem C storage in Hainan increased from 109.51 Tg in 1993 to 279.17 Tg in 2008. Soil C accounted for more than 70% of total forest ecosystem C. The spatial distribution of forest C storage in Hainan was uneven, reflecting differences in land use change and forest management. The potential carbon sequestration of forest ecosystems was 77.3 Tg C if all forested lands were restored to natural tropical forests. To increase the C sequestration potential on Hainan Island, future forest management should focus on the conservation of natural forests, selection of tree species, planting of understory species, and implementation of sustainable practices.

Spatial and Temporal Patterns of Carbon Storage in Forest Ecosystems on Hainan Island, Southern China

PubMed Central

Tang, Xuli; Zhang, Qianmei; Wang, Dong; Yuan, Lianlian; Chen, Xubing

2014-01-01

Spatial and temporal patterns of carbon (C) storage in forest ecosystems significantly affect the terrestrial C budget, but such patterns are unclear in the forests in Hainan Province, the largest tropical island in China. Here, we estimated the spatial and temporal patterns of C storage from 1993–2008 in Hainan's forest ecosystems by combining our measured data with four consecutive national forest inventories data. Forest coverage increased from 20.7% in the 1950s to 56.4% in the 2010s. The average C density of 163.7 Mg C/ha in Hainan's forest ecosystems in this study was slightly higher than that of China's mainland forests, but was remarkably lower than that in the tropical forests worldwide. Total forest ecosystem C storage in Hainan increased from 109.51 Tg in 1993 to 279.17 Tg in 2008. Soil C accounted for more than 70% of total forest ecosystem C. The spatial distribution of forest C storage in Hainan was uneven, reflecting differences in land use change and forest management. The potential carbon sequestration of forest ecosystems was 77.3 Tg C if all forested lands were restored to natural tropical forests. To increase the C sequestration potential on Hainan Island, future forest management should focus on the conservation of natural forests, selection of tree species, planting of understory species, and implementation of sustainable practices. PMID:25229628

Integrating remotely sensed fires for predicting deforestation for REDD.

PubMed

Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

2017-06-01

Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

Analyzing the management and disturbance in European forest based on self-thinning theory

NASA Astrophysics Data System (ADS)

Yan, Y.; Gielen, B.; Schelhaas, M.; Mohren, F.; Luyssaert, S.; Janssens, I. A.

2012-04-01

There is increasing awareness that natural and anthropogenic disturbance in forests affects exchange of CO2, H2O and energy between the ecosystem and the atmosphere. Consequently quantification of land use and disturbance intensity is one of the next steps needed to improve our understanding of the carbon cycle, its interactions with the atmosphere and its main drivers at local as well as at global level. The conventional NPP-based approaches to quantify the intensity of land management are limited because they lack a sound ecological basis. Here we apply a new way of characterising the degree of management and disturbance in forests using the self- thinning theory and observations of diameter at breast height and stand density. We used plot level information on dominant tree species, diameter at breast height, stand density and soil type from the French national forest inventory from 2005 to 2010. Stand density and diameter at breast height were used to parameterize the intercept of the self-thinning relationship and combined with theoretical slope to obtain an upper boundary for stand productivity given its density. Subsequently, we tested the sensitivity of the self-thinning relationship for tree species, soil type, climate and other environmental characteristics. We could find statistical differences in the self-thinning relationship between species and soil types, mainly due to the large uncertainty of the parameter estimates. Deviation from the theoretical self-thinning line defined as DBH=αN-3/4, was used as a proxy for disturbances, allowing to make spatially explicit maps of forest disturbance over France. The same framework was used to quantify the density-DBH trajectory of even-aged stand management of beech and oak over France. These trajectories will be used as a driver of forest management in the land surface model ORCHIDEE.

DEFINING RECOVERY GOALS AND STRATEGIES FOR ENDANGERED SPECIES USING SPATIALLY-EXPLICIT POPULATION MODELS

EPA Science Inventory

We used a spatially explicit population model of wolves (Canis lupus) to propose a framework for defining rangewide recovery priorities and finer-scale strategies for regional reintroductions. The model predicts that Yellowstone and central Idaho, where wolves have recently been ...

Understanding and Integrating Local Perceptions of Trees and Forests into Incentives for Sustainable Landscape Management

NASA Astrophysics Data System (ADS)

Pfund, Jean-Laurent; Watts, John Daniel; Boissière, Manuel; Boucard, Amandine; Bullock, Renee Marie; Ekadinata, Andree; Dewi, Sonya; Feintrenie, Laurène; Levang, Patrice; Rantala, Salla; Sheil, Douglas; Sunderland, Terence Clarence Heethom; Urech, Zora Lea

2011-08-01

We examine five forested landscapes in Africa (Cameroon, Madagascar, and Tanzania) and Asia (Indonesia and Laos) at different stages of landscape change. In all five areas, forest cover (outside of protected areas) continues to decrease despite local people's recognition of the importance of forest products and services. After forest conversion, agroforestry systems and fallows provide multiple functions and valued products, and retain significant biodiversity. But there are indications that such land use is transitory, with gradual simplification and loss of complex agroforests and fallows as land use becomes increasingly individualistic and profit driven. In Indonesia and Tanzania, farmers favor monocultures (rubber and oil palm, and sugarcane, respectively) for their high financial returns, with these systems replacing existing complex agroforests. In the study sites in Madagascar and Laos, investments in agroforests and new crops remain rare, despite government attempts to eradicate swidden systems and their multifunctional fallows. We discuss approaches to assessing local values related to landscape cover and associated goods and services. We highlight discrepancies between individual and collective responses in characterizing land use tendencies, and discuss the effects of accessibility on land management. We conclude that a combination of social, economic, and spatially explicit assessment methods is necessary to inform land use planning. Furthermore, any efforts to modify current trends will require clear incentives, such as through carbon finance. We speculate on the nature of such incentive schemes and the possibility of rewarding the provision of ecosystem services at a landscape scale and in a socially equitable manner.

Environmental correlates of plant diversity in Korean temperate forests

NASA Astrophysics Data System (ADS)

Černý, Tomáš; Doležal, Jiří; Janeček, Štěpán; Šrůtek, Miroslav; Valachovič, Milan; Petřík, Petr; Altman, Jan; Bartoš, Michael; Song, Jong-Suk

2013-02-01

Mountainous areas of the Korean Peninsula are among the biodiversity hotspots of the world's temperate forests. Understanding patterns in spatial distribution of their species richness requires explicit consideration of different environmental drivers and their effects on functionally differing components. In this study, we assess the impact of both geographical and soil variables on the fine-scale (400 m2) pattern of plant diversity using field data from six national parks, spanning a 1300 m altitudinal gradient. Species richness and the slopes of species-area curves were calculated separately for the tree, shrub and herb layer and used as response variables in regression tree analyses. A cluster analysis distinguished three dominant forest communities with specific patterns in the diversity-environment relationship. The most widespread middle-altitude oak forests had the highest tree richness but the lowest richness of herbaceous plants due to a dense bamboo understory. Total richness was positively associated with soil reaction and negatively associated with soluble phosphorus and solar radiation (site dryness). Tree richness was associated mainly with soil factors, although trees are frequently assumed to be controlled mainly by factors with large-scale impact. A U-shaped relationship was found between herbaceous plant richness and altitude, caused by a distribution pattern of dwarf bamboo in understory. No correlation between the degree of canopy openness and herb layer richness was detected. Slopes of the species-area curves indicated the various origins of forest communities. Variable diversity-environment responses in different layers and communities reinforce the necessity of context-dependent differentiation for the assessment of impacts of climate and land-use changes in these diverse but intensively exploited regions.

A distribution-oriented approach to support landscape connectivity for ecologically distinct bird species.

PubMed

Herrera, José M; Alagador, Diogo; Salgueiro, Pedro; Mira, António

2018-01-01

Managing landscape connectivity is a widely recognized overarching strategy for conserving biodiversity in human-impacted landscapes. However, planning the conservation and management of landscape connectivity of multiple and ecologically distinct species is still challenging. Here we provide a spatially-explicit framework which identifies and prioritizes connectivity conservation and restoration actions for species with distinct habitat affinities. Specifically, our study system comprised three groups of common bird species, forest-specialists, farmland-specialists, and generalists, populating a highly heterogeneous agricultural countryside in the southwestern Iberian Peninsula. We first performed a comprehensive analysis of the environmental variables underlying the distributional patterns of each bird species to reveal generalities in their guild-specific responses to landscape structure. Then, we identified sites which could be considered pivotal in maintaining current levels of landscape connectivity for the three bird guilds simultaneously, as well as the number and location of sites that need to be restored to maximize connectivity levels. Interestingly, we found that a small number of sites defined the shortest connectivity paths for the three bird guilds simultaneously, and were therefore considered key for conservation. Moreover, an even smaller number of sites were identified as critical to expand the landscape connectivity at maximum for the regional bird assemblage as a whole. Our spatially-explicit framework can provide valuable decision-making support to conservation practitioners aiming to identify key connectivity and restoration sites, a particularly urgent task in rapidly changing landscapes such as agroecosystems.

A distribution-oriented approach to support landscape connectivity for ecologically distinct bird species

PubMed Central

Salgueiro, Pedro; Mira, António

2018-01-01

Managing landscape connectivity is a widely recognized overarching strategy for conserving biodiversity in human-impacted landscapes. However, planning the conservation and management of landscape connectivity of multiple and ecologically distinct species is still challenging. Here we provide a spatially-explicit framework which identifies and prioritizes connectivity conservation and restoration actions for species with distinct habitat affinities. Specifically, our study system comprised three groups of common bird species, forest-specialists, farmland-specialists, and generalists, populating a highly heterogeneous agricultural countryside in the southwestern Iberian Peninsula. We first performed a comprehensive analysis of the environmental variables underlying the distributional patterns of each bird species to reveal generalities in their guild-specific responses to landscape structure. Then, we identified sites which could be considered pivotal in maintaining current levels of landscape connectivity for the three bird guilds simultaneously, as well as the number and location of sites that need to be restored to maximize connectivity levels. Interestingly, we found that a small number of sites defined the shortest connectivity paths for the three bird guilds simultaneously, and were therefore considered key for conservation. Moreover, an even smaller number of sites were identified as critical to expand the landscape connectivity at maximum for the regional bird assemblage as a whole. Our spatially-explicit framework can provide valuable decision-making support to conservation practitioners aiming to identify key connectivity and restoration sites, a particularly urgent task in rapidly changing landscapes such as agroecosystems. PMID:29641610

Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling.

PubMed

Walz, Yvonne; Wegmann, Martin; Leutner, Benjamin; Dech, Stefan; Vounatsou, Penelope; N'Goran, Eliézer K; Raso, Giovanna; Utzinger, Jürg

2015-11-30

Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d'Ivoire using high- and moderate-resolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixel-based modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

Getting the biggest birch for the bang: restoring and expanding upland birchwoods in the Scottish Highlands by managing red deer

PubMed Central

Tanentzap, Andrew J; Zou, James; Coomes, David A

2013-01-01

High deer populations threaten the conservation value of woodlands and grasslands, but predicting the success of deer culling, in terms of allowing vegetation to recover, is difficult. Numerical simulation modeling is one approach to gain insight into the outcomes of management scenarios. We develop a spatially explicit model to predict the responses of Betula spp. to red deer (Cervus elaphus) and land management in the Scottish Highlands. Our model integrates a Bayesian stochastic stage-based matrix model within the framework of a widely used individual-based forest simulation model, using data collected along spatial and temporal gradients in deer browsing. By initializing our model with the historical spatial locations of trees, we find that densities of juvenile trees (<3 m tall) predicted after 9–13 years closely match counts observed in the field. This is among the first tests of the accuracy of a dynamical simulation model for predicting the responses of tree regeneration to herbivores. We then test the relative importance of deer browsing, ground cover vegetation, and seed availability in facilitating landscape-level birch regeneration using simulations in which we varied these three variables. We find that deer primarily control transitions of birch to taller (>3 m) height tiers over 30 years, but regeneration also requires suitable ground cover for seedling establishment. Densities of adult seed sources did not influence regeneration, nor did an active management scenario where we altered the spatial configuration of adults by creating “woodland islets”. Our results show that managers interested in maximizing tree regeneration cannot simply reduce deer densities but must also improve ground cover for seedling establishment, and the model we develop now enables managers to quantify explicitly how much both these factors need to be altered. More broadly, our findings emphasize the need for land managers to consider the impacts of large herbivores rather than their densities. PMID:23919137

Curve numbers for nine mountainous eastern United States watersheds: seasonal variation and forest cutting

Treesearch

Negussie H. Tedela; Steven C. McCutcheon; John L. Campbell; Wayne T. Swank; Mary Beth Adams; Todd C. Rasmussen

2012-01-01

Many engineers and hydrologists use the curve number method to estimate runoff from ungaged watersheds; however, the method does not explicitly account for the influence of season or forest cutting on runoff. This study of observed rainfall and runoff for small, forested watersheds that span the Appalachian Mountains of the eastern United States showed that curve...

A comparison of airborne evapotranspiration maps and sapflow measurements in oak and beech forest stands

NASA Astrophysics Data System (ADS)

Schlerf, M.; Mallick, K.; Hassler, S. K.; Blume, T.; Ronellenfitsch, F.; Gerhards, M.; Udelhoven, T.; Weiler, M.

2017-12-01

Accurate estimations of spatially explicit daily Evapotranspiration (ET) may help water managers quantifying the water requirements of agricultural crops or trees. Airborne remote sensing may provide suitable ET maps, but uncertainties need to be better understood. In this study we compared high spatial resolution remotely sensed ET maps for 7 July 2016 with sap flow measurements over 32 forest stands located in the Attert catchment, Luxembourg. Forest stands differed in terms of species (Quercus robur, Fagus sylvatica), geology (schist, marl, sandstone), and geomorphology (slope position, plain, valley). Within each plot, at 1-3 trees the sap flow velocity (cm per hour) was measured between 8 am and 8 pm in 10 min intervals and averaged into a single value per plot and converted into values of volume flux (litres per day). Remotely sensed ET maps were derived by integrating airborne thermal infrared (TIR) images with an analytical surface energy balance model, Surface Temperature Initiated Closure (STIC1.2, Mallick et al. 2016). Airborne TIR images were acquired under clear sky conditions at 9:12, 10:08, 13:56, 14:50, 15:54, and 18:41 local time using a hyperspectral-thermal instrument. Images were geometrically corrected, calibrated, mosaicked, and converted to surface radiometric temperature. Surface temperature maps in conjunction with meteorological measurements recorded in the forest plots (air temperature, global radiation, relative humidity) were used as input to STIC1.2, for simultaneously estimating ET, sensible heat flux as well as surface and aerodynamic conductances. Instantaneous maps of ET were converted into daily ET maps and compared with the sap flow measurements. Results reveal a significant correspondence between remote sensing and field measured ET. The differences in the magnitude of predicted versus observed ET was found to be associated the biophysical conductances, radiometric surface temperature, and ecohydrological characteristics of the underlying landscape. Forest plots reveal differences in ET depending on the underlying geology and the slope position. Airborne remote sensing offers new ways of estimating the diurnal course of plant transpiration over entire landscapes and is an important bridging technology before high resolution TIR sensors will come into space.

Decline of forest interior conditions in the conterminous United States

Treesearch

Kurt H. Riitters; James D. Wickham

2012-01-01

Forest fragmentation threatens the sustainability of forest interior environments, thereby endangering subordinate ecological attributes and functions. We analyzed the spatial patterns of forest loss and gain for the conterminous United States from 2001 to 2006 to determine whether forest interior environments were maintained at five spatial scales. A 1.1% net loss of...

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad Z.; Cruise, James F.; Rickman, Douglas L.; Quattrochi, Dale A.

2007-01-01

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Spatially explicit watershed modeling: tracking water, mercury and nitrogen in multiple systems under diverse conditions

EPA Science Inventory

Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

Spatial Patterns of Forest Cover Loss in the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Molinario, G.; Hansen, M.; Potapov, P.; Justice, C. O.

2013-12-01

Three groups of metrics of spatial patterns of forest cover loss were calculated for the Democratic Republic of Congo (DRC). While other studies had previously assessed landscape patterns in the Congo Basin, they had done so for small areas due to data limitations. The input data for this study, the Forets d;Afrique Central Evaluee par Teledetection(FACET), allowed the analysis to be performed at the national level. FACET is a landsat-scale dataset giving an unprecedented synoptic view of forest cover and forest cover loss for the DRC for three time periods: 2000, 2005 and 2010. The three groups of metrics evaluated the following spatial characteristics of forest cover loss for the same standard 1.5km unit of area: proportions of typologies of forest lost, forest fragmentation and proximity of forest loss patches from other land cover types. Results indicate that there are several different typologies of forest cover loss in the DRC, and offer quantitative explanations of these differences, providing a valuable locally-relevant tool for land use planning, available at the national level. Spatial patterns of forest cover loss highlight differences between areas of high primary forest loss due to agriculture conversion in frontier deforestation, such as in the east of the country, areas of equivalent primary and secondary forest loss emanating from the rural complex and areas of variable proportions of primary and secondary forest loss but important ecological repercussions of forest fragmentation due to isolated, but systematic forest perforations. Typologies of spatial patterns of forest cover loss are presented as well as their correlated drivers, and ecological, conservation and land use planning considerations are discussed.

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)

NASA Astrophysics Data System (ADS)

Wang, B.; Shugart, H. H., Jr.; Lerdau, M.

2017-12-01

A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.

Deforestation projections for carbon-rich peat swamp forests of Central Kalimantan, Indonesia.

PubMed

Fuller, Douglas O; Hardiono, Martin; Meijaard, Erik

2011-09-01

We evaluated three spatially explicit land use and cover change (LUCC) models to project deforestation from 2005-2020 in the carbon-rich peat swamp forests (PSF) of Central Kalimantan, Indonesia. Such models are increasingly used to evaluate the impact of deforestation on carbon fluxes between the biosphere and the atmosphere. We considered both business-as-usual (BAU) and a forest protection scenario to evaluate each model's accuracy, sensitivity, and total projected deforestation and landscape-level fragmentation patterns. The three models, Dinamica EGO (DE), GEOMOD and the Land Change Modeler (LCM), projected similar total deforestation amounts by 2020 with a mean of 1.01 million ha (Mha) and standard deviation of 0.17 Mha. The inclusion of a 0.54 Mha strict protected area in the LCM simulations reduced projected loss to 0.77 Mha over 15 years. Calibrated parameterizations of the models using nearly identical input drivers produced very different landscape properties, as measured by the number of forest patches, mean patch area, contagion, and Euclidean nearest neighbor determined using Fragstats software. The average BAU outputs of the models suggests that Central Kalimantan may lose slightly less than half (45.1%) of its 2005 PSF by 2020 if measures are not taken to reduce deforestation there. The relatively small reduction of 0.24 Mha in deforestation found in the 0.54 Mha protection scenario suggests that these models can identify potential leakage effects in which deforestation is forced to occur elsewhere in response to a policy intervention.

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

USGS Publications Warehouse

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; Veblen, Thomas T; Smith, Jeremy M.; Kueppers, Lara M.

2017-01-01

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively.Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers.Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forest and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine.Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.

From water use to water scarcity footprinting in environmentally extended input-output analysis.

PubMed

Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A

2018-05-18

Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.

Historical effects of dissolved organic carbon export and land management decisions on the watershed-scale forest carbon budget of a coastal British Columbia Douglas-fir-dominated landscape.

PubMed

Smiley, B P; Trofymow, J A

2017-12-01

To address how natural disturbance, forest harvest, and deforestation from reservoir creation affect landscape-level carbon (C) budgets, a retrospective C budget for the 8500 ha Sooke Lake Watershed (SLW) from 1911 to 2012 was developed using historical spatial inventory and disturbance data. To simulate forest C dynamics, data was input into a spatially-explicit version of the Carbon Budget Model-Canadian Forest Sector (CBM-CFS3). Transfers of terrestrial C to inland aquatic environments need to be considered to better capture the watershed scale C balance. Using dissolved organic C (DOC) and stream flow measurements from three SLW catchments, DOC load into the reservoir was derived for a 17-year period. C stocks and stock changes between a baseline and two alternative management scenarios were compared to understand the relative impact of successive reservoir expansions and sustained harvest activity over the 100-year period. Dissolved organic C flux for the three catchments ranged from 0.017 to 0.057 Mg C ha -1  year -1 . Constraining CBM-CFS3 to observed DOC loads required parameterization of humified soil C losses of 2.5, 5.5, and 6.5%. Scaled to the watershed and assuming none of the exported terrestrial DOC was respired to CO 2 , we hypothesize that over 100 years up to 30,657 Mg C may have been available for sequestration in sediment. By 2012, deforestation due to reservoir creation/expansion resulted in the watershed forest lands sequestering 14 Mg C ha -1 less than without reservoir expansion. Sustained harvest activity had a substantially greater impact, reducing forest C stores by 93 Mg C ha -1 by 2012. However approximately half of the C exported as merchantable wood during logging (~176,000 Mg C) may remain in harvested wood products, reducing the cumulative impact of forestry activity from 93 to 71 Mg C ha -1 . Dissolved organic C flux from temperate forest ecosystems is a small but persistent C flux which may have long term implications for C storage in inland aquatic systems. This is a first step integrating fluvial transport of C into a forest carbon model by parameterizing DOC flux from soil C pools. While deforestation related to successive reservoir expansions did impact the watershed-scale C budget, over multi-decadal time periods, sustained harvest activity was more influential.

Exploring the effect of the spatial scale of fishery management.

PubMed

Takashina, Nao; Baskett, Marissa L

2016-02-07

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

Predicting spatio-temporal failure in large scale observational and micro scale experimental systems

NASA Astrophysics Data System (ADS)

de las Heras, Alejandro; Hu, Yong

2006-10-01

Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

Potential for spatial management of hunted mammal populations in tropical forests

Treesearch

Miranda H. Mockrin; Kent H. Redford

2011-01-01

Unsustainable hunting in tropical forests threatens biodiversity and rural livelihoods, yet managing these harvests in remote forests with low scientific capacity and funding is challenging. In response, some conservationists propose managing harvests through spatial management, a system of establishing notake zones where hunting is not allowed. Spatial management was...

On the patterns and processes of wood in northern California streams

NASA Astrophysics Data System (ADS)

Benda, Lee; Bigelow, Paul

2014-03-01

Forest management and stream habitat can be improved by clarifying the primary riparian and geomorphic controls on streams. To this end, we evaluated the recruitment, storage, transport, and the function of wood in 95 km of streams (most drainage areas < 30 km2) in northern California, crossing four coastal to inland regions with different histories of forest management (managed, less-managed, unmanaged). The dominant source of variability in stream wood storage and recruitment is driven by local variation in rates of bank erosion, forest mortality, and mass wasting. These processes are controlled by changes in watershed structure, including the location of canyons, floodplains and tributary confluences; types of geology and topography; and forest types and management history. Average wood storage volumes in coastal streams are 5 to 20 times greater than inland sites primarily from higher riparian forest biomass and growth rates (productivity), with some influence by longer residence time of wood in streams and more wood from landsliding and logging sources. Wood recruitment by mortality (windthrow, disease, senescence) was substantial across all sites (mean 50%) followed by bank erosion (43%) and more locally by mass wasting (7%). The distances to sources of stream wood are controlled by recruitment process and tree height. Ninety percent of wood recruitment occurs within 10 to 35 m of channels in managed and less-managed forests and upward of 50 m in unmanaged Sequoia and coast redwood forests. Local landsliding extends the source distance. The recruitment of large wood pieces that create jams (mean diameter 0.7 m) is primarily by bank erosion in managed forests and by mortality in unmanaged forests. Formation of pools by wood is more frequent in streams with low stream power, indicating the further relevance of environmental context and watershed structure. Forest management influences stream wood dynamics, where smaller trees in managed forests often generate shorter distances to sources of stream wood, lower stream wood storage, and smaller diameter stream wood. These findings can be used to improve riparian protection and inform spatially explicit riparian management.

The role of forest disturbance in global forest mortality and terrestrial carbon fluxes

NASA Astrophysics Data System (ADS)

Pugh, Thomas; Arneth, Almut; Smith, Benjamin; Poulter, Benjamin

2017-04-01

Large-scale forest disturbance dynamics such as insect outbreaks, wind-throw and fires, along with anthropogenic disturbances such as logging, have been shown to turn forests from carbon sinks into intermittent sources, often quite dramatically so. There is also increasing evidence that disturbance regimes in many regions are changing as a result of climatic change and human land-management practices. But how these landscape-scale events fit into the wider picture of global tree mortality is not well understood. Do such events dominate global carbon turnover, or are their effects highly regional? How sensitive is global terrestrial carbon exchange to realistic changes in the occurrence rate of such disturbances? Here, we combine recent advances in global satellite observations of stand-replacing forest disturbances and in compilations of forest inventory data, with a global terrestrial ecosystem model which incorporates an explicit representation of the role of disturbance in forest dynamics. We find that stand-replacing disturbances account for a fraction of wood carbon turnover that varies spatially from less than 5% in the tropical rainforest to ca. 50% in the mid latitudes, and as much as 90% in some heavily-managed regions. We contrast the size of the land-atmosphere carbon flux due to this disturbance with other components of the terrestrial carbon budget. In terms of sensitivity, we find a quasi log-linear relationship of disturbance rate to total carbon storage. Relatively small changes in disturbance rates at all latitudes have marked effects on vegetation carbon storage, with potentially very substantial implications for the global terrestrial carbon sink. Our results suggest a surprisingly small effect of disturbance type on large-scale forest vegetation dynamics and carbon storage, with limited evidence of widespread increases in nitrogen limitation as a result of increasing future disturbance. However, the influence of disturbance type on soil carbon stocks is very large, illustrating the importance of further efforts to distinguish disturbance drivers at the global scale. Setting our knowledge of forest disturbance into the wider uncertainty in forest mortality processes generally, we offer a perspective for improving understanding of the role of disturbance in global forest carbon cycling.

Temporal trends of forest interior conditions in the United States

Treesearch

Kurt Riitters; James. Wickham

2012-01-01

Nature's benefits derived from forest interior environments cannot be sustained if the natural capital of forest interior area is not sustained. We analyzed the spatial patterns of forest loss and gain for the conterminous United States from 2001 to 2006 to determine whether forest interior environments were maintained at five spatial scales. A 1.1 percent net...

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Treesearch

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Spatial impact assessment of conifer stands in the Hoosier National Forest

Treesearch

Richard Thurau; Craig Wayson; Dale Weigel; Jeff Ehman

2011-01-01

Forest management decisions on Federal lands must be administered at many spatial and temporal scales. Forest condition, size class, and cover type at the stand level determine how silvicultural practices today will impact management area and overall forest goals in the future. The Hoosier National Forest (HNF) Land Resource Management Plan lists eight goals for...

Raccoon spatial requirements and multi-scale habitat selection within an intensively managed central Appalachian forest

USGS Publications Warehouse

Owen, Sheldon F.; Berl, Jacob L.; Edwards, John W.; Ford, W. Mark; Wood, Petra Bohall

2015-01-01

We studied a raccoon (Procyon lotor) population within a managed central Appalachian hardwood forest in West Virginia to investigate the effects of intensive forest management on raccoon spatial requirements and habitat selection. Raccoon home-range (95% utilization distribution) and core-area (50% utilization distribution) size differed between sexes with males maintaining larger (2×) home ranges and core areas than females. Home-range and core-area size did not differ between seasons for either sex. We used compositional analysis to quantify raccoon selection of six different habitat types at multiple spatial scales. Raccoons selected riparian corridors (riparian management zones [RMZ]) and intact forests (> 70 y old) at the core-area spatial scale. RMZs likely were used by raccoons because they provided abundant denning resources (i.e., large-diameter trees) as well as access to water. Habitat composition associated with raccoon foraging locations indicated selection for intact forests, riparian areas, and regenerating harvest (stands <10 y old). Although raccoons were able to utilize multiple habitat types for foraging resources, a selection of intact forest and RMZs at multiple spatial scales indicates the need of mature forest (with large-diameter trees) for this species in managed forests in the central Appalachians.

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution. [Sam Houston National Forest, Texas

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Sadowski, F. E.; Sarno, J. E.

1976-01-01

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Forest dynamics in the U.S. indicate disproportionate attrition in western forests, rural areas and public lands

PubMed Central

2017-01-01

Forests are experiencing significant changes; studying geographic patterns in forests is critical in understanding the impact of forest dynamics to biodiversity, soil erosion, water chemistry and climate. Few studies have examined forest geographic pattern changes other than fragmentation; however, other spatial processes of forest dynamics are of equal importance. Here, we study forest attrition, the complete removal of forest patches, that can result in complete habitat loss, severe decline of population sizes and species richness, and shifts of local and regional environmental conditions. We aim to develop a simple yet insightful proximity-based spatial indicator capturing forest attrition that is independent of spatial scale and boundaries with worldwide application potential. Using this proximity indicator, we evaluate forest attrition across ecoregions, land ownership and urbanization stratifications across continental United States of America. Nationally, the total forest cover loss was approximately 90,400 km2, roughly the size of the state of Maine, constituting a decline of 2.96%. Examining the spatial arrangement of this change the average FAD was 3674m in 1992 and increased by 514m or 14.0% in 2001. Simulations of forest cover loss indicate only a 10m FAD increase suggesting that the observed FAD increase was more than an order of magnitude higher than expected. Furthermore, forest attrition is considerably higher in the western United States, in rural areas and in public lands. Our mathematical model (R2 = 0.93) supports estimation of attrition for a given forest cover. The FAD metric quantifies forest attrition across spatial scales and geographic boundaries and assesses unambiguously changes over time. The metric is applicable to any landscape and offers a new complementary insight on forest landscape patterns from local to global scales, improving future exploration of drivers and repercussions of forest cover changes and supporting more informative management of forest carbon, changing climate and species biodiversity. PMID:28225787

Forest dynamics in the U.S. indicate disproportionate attrition in western forests, rural areas and public lands.

PubMed

Yang, Sheng; Mountrakis, Giorgos

2017-01-01

Forests are experiencing significant changes; studying geographic patterns in forests is critical in understanding the impact of forest dynamics to biodiversity, soil erosion, water chemistry and climate. Few studies have examined forest geographic pattern changes other than fragmentation; however, other spatial processes of forest dynamics are of equal importance. Here, we study forest attrition, the complete removal of forest patches, that can result in complete habitat loss, severe decline of population sizes and species richness, and shifts of local and regional environmental conditions. We aim to develop a simple yet insightful proximity-based spatial indicator capturing forest attrition that is independent of spatial scale and boundaries with worldwide application potential. Using this proximity indicator, we evaluate forest attrition across ecoregions, land ownership and urbanization stratifications across continental United States of America. Nationally, the total forest cover loss was approximately 90,400 km2, roughly the size of the state of Maine, constituting a decline of 2.96%. Examining the spatial arrangement of this change the average FAD was 3674m in 1992 and increased by 514m or 14.0% in 2001. Simulations of forest cover loss indicate only a 10m FAD increase suggesting that the observed FAD increase was more than an order of magnitude higher than expected. Furthermore, forest attrition is considerably higher in the western United States, in rural areas and in public lands. Our mathematical model (R2 = 0.93) supports estimation of attrition for a given forest cover. The FAD metric quantifies forest attrition across spatial scales and geographic boundaries and assesses unambiguously changes over time. The metric is applicable to any landscape and offers a new complementary insight on forest landscape patterns from local to global scales, improving future exploration of drivers and repercussions of forest cover changes and supporting more informative management of forest carbon, changing climate and species biodiversity.

Influence of spatially dependent, modeled soil carbon emission factors on life-cycle greenhouse gas emissions of corn and cellulosic ethanol

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

Qin, Zhangcai; Dunn, Jennifer B.; Kwon, Hoyoung

Converting land to biofuel feedstock production incurs changes in soil organic carbon (SOC) that can influence biofuel life-cycle greenhouse gas (GHG) emissions. Estimates of these land use change (LUC) and life-cycle GHG emissions affect biofuels’ attractiveness and eligibility under a number of renewable fuel policies in the U.S. and abroad. Modeling was used to refine the spatial resolution and depth-extent of domestic estimates of SOC change for land (cropland, cropland pasture, grasslands, and forests) conversion scenarios to biofuel crops (corn, corn stover, switchgrass, Miscanthus, poplar, and willow). In most regions, conversions from cropland and cropland pasture to biofuel crops ledmore » to neutral or small levels of SOC sequestration, while conversion of grassland and forest generally caused net SOC loss. Results of SOC change were incorporated into the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model to assess their influence on life-cycle GHG emissions for the biofuels considered. Total LUC GHG emissions (g CO2eq MJ-1) were 2.1–9.3 for corn, -0.7 for corn stover, -3.4–12.9 for switchgrass, and -20.1–-6.2 for Miscanthus; these varied with SOC modeling assumptions applied. Extending soil depth from 30 to 100cm affected spatially-explicit SOC change and overall LUC GHG emissions; however the influence on LUC GHG emissions estimates were less significant in corn and corn stover than cellulosic feedstocks. Total life-cycle GHG emissions (g CO2eq MJ-1, 100cm) were estimated to be 59–66 for corn ethanol, 14 for stover ethanol, 18-26 for switchgrass ethanol, and -0.6–-7 for Miscanthus ethanol.« less

Contribution of ecosystem services to air quality and climate change mitigation policies: The case of urban forests in Barcelona, Spain

Treesearch

Francesc Baró; Lydia Chaparro; Erik Gómez-Baggethun; Johannes Langemeyer; David J. Nowak; Jaume Terradas

2014-01-01

Mounting research highlights the contribution of ecosystem services provided by urban forests to quality of life in cities, yet these services are rarely explicitly considered in environmental policy targets. We quantify regulating services provided by urban forests and evaluate their contribution to comply with policy targets of air quality and climate change...

Disturbance, tree mortality, and implications for contemporary regional forest change in the Pacific Northwest

Treesearch

Matthew J. Reilly; Thomas A. Spies

2016-01-01

Tree mortality is an important demographic process and primary driver of forest dynamics, yet there are relatively few plot-based studies that explicitly quantify mortality and compare the relative contribution of endogenous and exogenous disturbances at regional scales. We used repeated observations on 289,390 trees in 3673 1 ha plots on U.S. Forest Service lands in...

Contrasting spatial patterns in active-fire and fire-suppressed Mediterranean climate old-growth mixed conifer forests

Treesearch

Danny L. Fry; Scott L. Stephens; Brandon M. Collins; Malcolm North; Ernesto Franco-Vizcaino; Samantha J. Gill

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference...

Spatial patterning of fuels and fire hazard across a central U.S. deciduous forest region

Treesearch

Michael C. Stambaugh; Daniel C. Dey; Richard P. Guyette; Hong S. He; Joseph M. Marschall

2011-01-01

Information describing spatial and temporal variability of forest fuel conditions is essential to assessing overall fire hazard and risk. Limited information exists describing spatial characteristics of fuels in the eastern deciduous forest region, particularly in dry oak-dominated regions that historically burned relatively frequently. From an extensive fuels survey...

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Seed-deposition and recruitment patterns of Clusia species in a disturbed tropical montane forest in Bolivia

NASA Astrophysics Data System (ADS)

Saavedra, Francisco; Hensen, Isabell; Apaza Quevedo, Amira; Neuschulz, Eike Lena; Schleuning, Matthias

2017-11-01

Spatial patterns of seed dispersal and recruitment of fleshy-fruited plants in tropical forests are supposed to be driven by the activity of animal seed dispersers, but the spatial patterns of seed dispersal, seedlings and saplings have rarely been analyzed simultaneously. We studied seed deposition and recruitment patterns of three Clusia species in a tropical montane forest of the Bolivian Andes and tested whether these patterns changed between habitat types (forest edge vs. forest interior), distance to the fruiting tree and consecutive recruitment stages of the seedlings. We recorded the number of seeds deposited in seed traps to assess the local seed-deposition pattern and the abundance and distribution of seedlings and saplings to evaluate the spatial pattern of recruitment. More seeds were removed and deposited at the forest edge than in the interior. The number of deposited seeds decreased with distance from the fruiting tree and was spatially clustered in both habitat types. The density of 1-yr-old seedlings and saplings was higher at forest edges, whereas the density of 2-yr-old seedlings was similar in both habitat types. While seedlings were almost randomly distributed, seeds and saplings were spatially clustered in both habitat types. Our findings demonstrate systematic changes in spatial patterns of recruits across the plant regeneration cycle and suggest that the differential effects of biotic and abiotic factors determine plant recruitment at the edges and in the interior of tropical montane forests. These differences in the spatial distribution of individuals across recruitment stages may have strong effects on plant community dynamics and influence plant species coexistence in disturbed tropical forests.

A Watershed-based spatially-explicit demonstration of an Integrated Environmental Modeling Framework for Ecosystem Services in the Coal River Basin (WV, USA)

EPA Science Inventory

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quant...

Spatially explicit shallow landslide susceptibility mapping over large areas

Treesearch

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

Evaluating spatially explicit burn probabilities for strategic fire management planning

Treesearch

C. Miller; M.-A. Parisien; A. A. Ager; M. A. Finney

2008-01-01

Spatially explicit information on the probability of burning is necessary for virtually all strategic fire and fuels management planning activities, including conducting wildland fire risk assessments, optimizing fuel treatments, and prevention planning. Predictive models providing a reliable estimate of the annual likelihood of fire at each point on the landscape have...

Empirical methods for modeling landscape change, ecosystem services, and biodiversity

Treesearch

David Lewis; Ralph Alig

2009-01-01

The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...

SPATIALLY EXPLICIT MICRO-LEVEL MODELLING OF LAND USE CHANGE AT THE RURAL-URBAN INTERFACE. (R828012)

EPA Science Inventory

This paper describes micro-economic models of land use change applicable to the rural–urban interface in the US. Use of a spatially explicit micro-level modelling approach permits the analysis of regional patterns of land use as the aggregate outcomes of many, disparate...

An Integer Programming Model for the Management of a Forest in the North of Portugal

NASA Astrophysics Data System (ADS)

Cerveira, Adelaide; Fonseca, Teresa; Mota, Artur; Martins, Isabel

2011-09-01

This study aims to develop an approach for the management of a forest of maritime pine located in the north region of Portugal. The forest is classified into five public lands, the so-called baldios, extending over 4432 ha. These baldios are co-managed by the Official Forest Services and the local communities mainly for timber production purposes. The forest planning involves non-spatial and spatial constraints. Spatial constraints dictate a maximum clearcut area and an exclusion time. An integer programming model is presented and the computational results are discussed.

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

PubMed

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

A 50-m Forest Cover Map in Southeast Asia from ALOS/PALSAR and Its Application on Forest Fragmentation Assessment

PubMed Central

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Dinh Duong, Nguyen; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×106 km2 (GlobCover) to 2.69×106 km2 (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity. PMID:24465714

Disturbance and productivity interactions mediate stability of forest composition and structure.

PubMed

O'Connor, Christopher D; Falk, Donald A; Lynch, Ann M; Swetnam, Thomas W; Wilcox, Craig P

2017-04-01

Fire is returning to many conifer-dominated forests where species composition and structure have been altered by fire exclusion. Ecological effects of these fires are influenced strongly by the degree of forest change during the fire-free period. Response of fire-adapted species assemblages to extended fire-free intervals is highly variable, even in communities with similar historical fire regimes. This variability in plant community response to fire exclusion is not well understood; however, ecological mechanisms such as individual species' adaptations to disturbance or competition and underlying site characteristics that facilitate or impede establishment and growth have been proposed as potential drivers of assemblage response. We used spatially explicit dendrochronological reconstruction of tree population dynamics and fire regimes to examine the influence of historical disturbance frequency (a proxy for adaptation to disturbance or competition), and potential site productivity (a proxy for underlying site characteristics) on the stability of forest composition and structure along a continuous ecological gradient of pine, dry mixed-conifer, mesic mixed-conifer, and spruce-fir forests following fire exclusion. While average structural density increased in all forests, species composition was relatively stable in the lowest productivity pine-dominated and highest productivity spruce-fir-dominated sites immediately following fire exclusion and for the next 100 years, suggesting site productivity as a primary control on species composition and structure in forests with very different historical fire regimes. Species composition was least stable on intermediate productivity sites dominated by mixed-conifer forests, shifting from primarily fire-adapted species to competition-adapted, fire-sensitive species within 20 years of fire exclusion. Rapid changes to species composition and stand densities have been interpreted by some as evidence of high-severity fire. We demonstrate that the very different ecological process of fire exclusion can produce similar changes by shifting selective pressures from disturbance-mediated to productivity-mediated controls. Restoring disturbance-adapted species composition and structure to intermediate productivity forests may help to buffer them against projected increasing temperatures, lengthening fire seasons, and more frequent and prolonged moisture stress. Fewer management options are available to promote adaptation in forest assemblages historically constrained by underlying site productivity. © 2016 by the Ecological Society of America.

The underlying processes of a soil mite metacommunity on a small scale.

PubMed

Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.

The underlying processes of a soil mite metacommunity on a small scale

PubMed Central

Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906

An ecosystem management strategy for Sierran mixed-conifer forests

Treesearch

Malcolm North; Peter Stine; Kevin O' Hara; William Zielinski; Scott Stephens

2009-01-01

Current Sierra Nevada forest management is often focused on strategically reducing fuels without an explicit strategy for ecological restoration across the landscape matrix. Summarizing recent scientific literature, we suggest managers produce different stand structures and densities across the landscape using topographic variables (i.e., slope shape, aspect, and slope...

Transformation of the oak forest spatial structure in the Minneapolis/St. Paul metropolitan area, Minnesota, USA over 7 years

Treesearch

Kathleen Ward; Kathryn Kromroy; Jennifer Juzwik

2007-01-01

The Twin Cities Metropolitan Area (TCMA) oak (Quercus spp.) forest area decreased by 5.6% between 1991 and 1998. Accompanying spatial transformation of the forest can have great impacts on forest health, water flow and quality, wildlife habitat, potential for the spread of invasive transformation that occurred along with the loss of oak forest in the...

Is forest fragmentation driven by the spatial configuration of land quality? The case of western Oregon.

Treesearch

Ralph J. Alig; David J. Lewis; Jennifer J. Swenson

2005-01-01

We investigated spatial configuration of economic returns, to enhance models of forest fragmentation for western Oregon and western Washington. Drawing from spatial land rent theory, economic drivers of forest fragmentation at the landscape level include land quality comprised of attributes such as soil fertility or the distance of urban plots to amenities. We included...

Change in spatial characteristics of forest openings in the Klamath Mountains of northwestern California, USA

Treesearch

Carl N. Skinner

1995-01-01

Change in the spatial characteristics of forest openings was investigated in three forested watersheds in northwestern Siskiyou County, California totalling approximately 24,600 hectares. Watersheds with minimal human disturbance were chosen for study. However, fi;e suppression has been pervasive throughout. Characteristics of forest openings (area, perimeter, distance...

The effect of Appalachian mountaintop mining on interior forest

Treesearch

J.D. Wickham; Kurt H. Riitters; T.G. Wade; M. Coan; C. Homer

2007-01-01

Southern Appalachian forests are predominantly interior because they are spatially extensive with little disturbance imposed by other uses of the land. Appalachian mountaintop mining increased substantially during the 1990s, posing a threat to the interior character of the forest. We used spatial convolution to identify interior forest at multiple scales on circa 1992...

Understanding and managing the water use of planted forests in a changing environment

Treesearch

Jami Nettles

2016-01-01

Forest productivity will only become more important in the future, not just for carbon sequestration and renewable energy but for wood products and economic security for an increasing population. However, the threat of increasing drought and resource scarcity means a need for more explicit characterization of the water use of planted forests and the understanding of...

Range expansion of invasive shrubs: implication for crown fire risk in forestlands of the southern USA.

PubMed

Wang, Hsiao-Hsuan; Wonkka, Carissa L; Grant, William E; Rogers, William E

2016-01-01

Non-native plant invasions and changing management activities have dramatically altered the structure and composition of forests worldwide. Invasive shrubs and fire suppression have led to increased densification and biomass accumulation in forest ecosystems of the southeastern USA. Notably, Chinese and European privets are rapid growing, shade-tolerant shrubs which number among the most aggressive invasive species in these forests. Privet encroachment has caused losses of native diversity, alteration of ecosystem processes and changes in community structure. The latter has become manifest through decreases in fine herbaceous fuels concurrent with increases in coarse woody fuels in forest understoreys. These alterations in fuel structure will potentially lead to less frequent, but more severe forest fires, which threaten important forest resources during extreme weather conditions. Drawing on extensive data sets compiled by the US Forest Service, we integrated statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework to predict potential range expansion of Chinese and European privet (Ligustrum sinenseandL. vulgare) and the associated increase in crown fire risk over the next two decades in forestlands of Mississippi and Alabama. Our results indicate that probability of invasion is positively associated with elevation, adjacency (within 300 m) to water bodies, mean daily maximum temperature, site productivity and private land ownership, and is negatively associated with slope, stand age, artificial regeneration, distance to the nearest road and fire disturbance. Our projections suggest the total area invaded will increase from 1.36 to ≈31.39% of all forestlands in Mississippi and Alabama (≈7 million hectares) and the annual frequency of crown fires in these forestlands will approximately double within the next two decades. Such time series projections of annual range expansions and crown fire frequency should provide land managers and restoration practitioners with an invasion chronology upon which to base proactive management plans. Published by Oxford University Press on behalf of the Annals of Botany Company.

Projected gains and losses of wildlife habitat from bioenergy-induced landscape change

USGS Publications Warehouse

Tarr, Nathan M.; Rubino, Matthew J.; Costanza, Jennifer K.; McKerrow, Alexa; Collazo, Jaime A.; Abt, Robert C.

2016-01-01

Domestic and foreign renewable energy targets and financial incentives have increased demand for woody biomass and bioenergy in the southeastern United States. This demand is expected to be met through purpose-grown agricultural bioenergy crops, short-rotation tree plantations, thinning and harvest of planted and natural forests, and forest harvest residues. With results from a forest economics model, spatially explicit state-and-transition simulation models, and species–habitat models, we projected change in habitat amount for 16 wildlife species caused by meeting a renewable fuel target and expected demand for wood pellets in North Carolina, USA. We projected changes over 40 years under a baseline ‘business-as-usual’ scenario without bioenergy production and five scenarios with unique feedstock portfolios. Bioenergy demand had potential to influence trends in habitat availability for some species in our study area. We found variation in impacts among species, and no scenario was the ‘best’ or ‘worst’ across all species. Our models projected that shrub-associated species would gain habitat under some scenarios because of increases in the amount of regenerating forests on the landscape, while species restricted to mature forests would lose habitat. Some forest species could also lose habitat from the conversion of forests on marginal soils to purpose-grown feedstocks. The conversion of agricultural lands on marginal soils to purpose-grown feedstocks increased habitat losses for one species with strong associations with pasture, which is being lost to urbanization in our study region. Our results indicate that landscape-scale impacts on wildlife habitat will vary among species and depend upon the bioenergy feedstock portfolio. Therefore, decisions about bioenergy and wildlife will likely involve trade-offs among wildlife species, and the choice of focal species is likely to affect the results of landscape-scale assessments. We offer general principals to consider when crafting lists of focal species for bioenergy impact assessments at the landscape scale.

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.

Average Stand Age from Forest Inventory Plots Does Not Describe Historical Fire Regimes in Ponderosa Pine and Mixed-Conifer Forests of Western North America.

PubMed

Stevens, Jens T; Safford, Hugh D; North, Malcolm P; Fried, Jeremy S; Gray, Andrew N; Brown, Peter M; Dolanc, Christopher R; Dobrowski, Solomon Z; Falk, Donald A; Farris, Calvin A; Franklin, Jerry F; Fulé, Peter Z; Hagmann, R Keala; Knapp, Eric E; Miller, Jay D; Smith, Douglas F; Swetnam, Thomas W; Taylor, Alan H

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the "stand age" variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical "mixed-severity" fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data.

Average Stand Age from Forest Inventory Plots Does Not Describe Historical Fire Regimes in Ponderosa Pine and Mixed-Conifer Forests of Western North America

PubMed Central

Stevens, Jens T.; Safford, Hugh D.; North, Malcolm P.; Fried, Jeremy S.; Gray, Andrew N.; Brown, Peter M.; Dolanc, Christopher R.; Dobrowski, Solomon Z.; Falk, Donald A.; Farris, Calvin A.; Franklin, Jerry F.; Fulé, Peter Z.; Hagmann, R. Keala; Knapp, Eric E.; Miller, Jay D.; Smith, Douglas F.; Swetnam, Thomas W.; Taylor, Alan H.

2016-01-01

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the “stand age” variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical “mixed-severity” fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data. PMID:27196621

Range expansion of invasive shrubs: implication for crown fire risk in forestlands of the southern USA

PubMed Central

Wang, Hsiao-Hsuan; Wonkka, Carissa L.; Grant, William E.; Rogers, William E.

2016-01-01

Non-native plant invasions and changing management activities have dramatically altered the structure and composition of forests worldwide. Invasive shrubs and fire suppression have led to increased densification and biomass accumulation in forest ecosystems of the southeastern USA. Notably, Chinese and European privets are rapid growing, shade-tolerant shrubs which number among the most aggressive invasive species in these forests. Privet encroachment has caused losses of native diversity, alteration of ecosystem processes and changes in community structure. The latter has become manifest through decreases in fine herbaceous fuels concurrent with increases in coarse woody fuels in forest understoreys. These alterations in fuel structure will potentially lead to less frequent, but more severe forest fires, which threaten important forest resources during extreme weather conditions. Drawing on extensive data sets compiled by the US Forest Service, we integrated statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework to predict potential range expansion of Chinese and European privet (Ligustrum sinense and L. vulgare) and the associated increase in crown fire risk over the next two decades in forestlands of Mississippi and Alabama. Our results indicate that probability of invasion is positively associated with elevation, adjacency (within 300 m) to water bodies, mean daily maximum temperature, site productivity and private land ownership, and is negatively associated with slope, stand age, artificial regeneration, distance to the nearest road and fire disturbance. Our projections suggest the total area invaded will increase from 1.36 to ≈31.39% of all forestlands in Mississippi and Alabama (≈7 million hectares) and the annual frequency of crown fires in these forestlands will approximately double within the next two decades. Such time series projections of annual range expansions and crown fire frequency should provide land managers and restoration practitioners with an invasion chronology upon which to base proactive management plans. PMID:26903488

A hydroeconomic modeling framework for optimal integrated management of forest and water

NASA Astrophysics Data System (ADS)

Garcia-Prats, Alberto; del Campo, Antonio D.; Pulido-Velazquez, Manuel

2016-10-01

Forests play a determinant role in the hydrologic cycle, with water being the most important ecosystem service they provide in semiarid regions. However, this contribution is usually neither quantified nor explicitly valued. The aim of this study is to develop a novel hydroeconomic modeling framework for assessing and designing the optimal integrated forest and water management for forested catchments. The optimization model explicitly integrates changes in water yield in the stands (increase in groundwater recharge) induced by forest management and the value of the additional water provided to the system. The model determines the optimal schedule of silvicultural interventions in the stands of the catchment in order to maximize the total net benefit in the system. Canopy cover and biomass evolution over time were simulated using growth and yield allometric equations specific for the species in Mediterranean conditions. Silvicultural operation costs according to stand density and canopy cover were modeled using local cost databases. Groundwater recharge was simulated using HYDRUS, calibrated and validated with data from the experimental plots. In order to illustrate the presented modeling framework, a case study was carried out in a planted pine forest (Pinus halepensis Mill.) located in south-western Valencia province (Spain). The optimized scenario increased groundwater recharge. This novel modeling framework can be used in the design of a "payment for environmental services" scheme in which water beneficiaries could contribute to fund and promote efficient forest management operations.

Attaining the canopy in dry and moist tropical forests: strong differences in tree growth trajectories reflect variation in growing conditions.

PubMed

Brienen, Roel J W; Zuidema, Pieter A; Martínez-Ramos, Miguel

2010-06-01

Availability of light and water differs between tropical moist and dry forests, with typically higher understorey light levels and lower water availability in the latter. Therefore, growth trajectories of juvenile trees--those that have not attained the canopy--are likely governed by temporal fluctuations in light availability in moist forests (suppressions and releases), and by spatial heterogeneity in water availability in dry forests. In this study, we compared juvenile growth trajectories of Cedrela odorata in a dry (Mexico) and a moist forest (Bolivia) using tree rings. We tested the following specific hypotheses: (1) moist forest juveniles show more and longer suppressions, and more and stronger releases; (2) moist forest juveniles exhibit wider variation in canopy accession pattern, i.e. the typical growth trajectory to the canopy; (3) growth variation among dry forest juveniles persists over longer time due to spatial heterogeneity in water availability. As expected, the proportion of suppressed juveniles was higher in moist than in dry forest (72 vs. 17%). Moist forest suppressions also lasted longer (9 vs. 5 years). The proportion of juveniles that experienced releases in moist forest (76%) was higher than in dry forest (41%), and releases in moist forests were much stronger. Trees in the moist forest also had a wider variation in canopy accession patterns compared to the dry forest. Our results also showed that growth variation among juvenile trees persisted over substantially longer periods of time in dry forest (>64 years) compared to moist forest (12 years), most probably because of larger persistent spatial variation in water availability. Our results suggest that periodic increases in light availability are more important for attaining the canopy in moist forests, and that spatial heterogeneity in water availability governs long-term tree growth in dry forests.

Carbon Budget and its Dynamics over Northern Eurasia Forest Ecosystems

NASA Astrophysics Data System (ADS)

Shvidenko, Anatoly; Schepaschenko, Dmitry; Kraxner, Florian; Maksyutov, Shamil

2016-04-01

The presentation contains an overview of recent findings and results of assessment of carbon cycling of forest ecosystems of Northern Eurasia. From a methodological point of view, there is a clear tendency in understanding a need of a Full and Verified Carbon Account (FCA), i.e. in reliable assessment of uncertainties for all modules and all stages of FCA. FCA is considered as a fuzzy (underspecified) system that supposes a system integration of major methods of carbon cycling study (land-ecosystem approach, LEA; process-based models; eddy covariance; and inverse modelling). Landscape-ecosystem approach 1) serves for accumulation of all relevant knowledge of landscape and ecosystems; 2) for strict systems designing the account, 3) contains all relevant spatially distributed empirical and semi-empirical data and models, and 4) is presented in form of an Integrated Land Information System (ILIS). The ILIS includes a hybrid land cover in a spatially and temporarily explicit way and corresponding attributive databases. The forest mask is provided by utilizing multi-sensor remote sensing data, geographically weighed regression and validation within GEO-wiki platform. By-pixel parametrization of forest cover is based on a special optimization algorithms using all available knowledge and information sources (data of forest inventory and different surveys, observations in situ, official statistics of forest management etc.). Major carbon fluxes within the LEA (NPP, HR, disturbances etc.) are estimated based on fusion of empirical data and aggregations with process-based elements by sets of regionally distributed models. Uncertainties within LEA are assessed for each module and at each step of the account. Within method results of LEA and corresponding uncertainties are harmonized and mutually constrained with independent outputs received by other methods based on the Bayesian approach. The above methodology have been applied to carbon account of Russian forests for 2000-2012. It has been shown that the Net Ecosystem Carbon Budget (NECB) of Russian forests for this period was in range of 0.5-0.7 Pg C yr-1 with a slight negative trend during the period due to acceleration of disturbance regimes and negative impacts of weather extremes (heat waves etc.). Uncertainties of the FCA for individual years were estimated at about 25% (CI 0.9). It has been shown that some models (e.g. majority of DGVMs) do not describe some processes on permafrost satisfactory while results of applications of ensembles of inverse models on average are closed to empirical assessments. A most important conclusion from this experience is that future improvements of knowledge of carbon cycling of Northern Eurasia forests requires development of an integrated observing system as a unified information background, as well as systems methodological improvements of all methods of cognition of carbon cycling.

Reconstructing the spatial pattern of historical forest land in China in the past 300 years

NASA Astrophysics Data System (ADS)

Yang, Xuhong; Jin, Xiaobin; Xiang, Xiaomin; Fan, Yeting; Shan, Wei; Zhou, Yinkang

2018-06-01

The reconstruction of the historical forest spatial distribution is of a great significance to understanding land surface cover in historical periods as well as its climate and ecological effects. Based on the maximum scope of historical forest land before human intervention, the characteristics of human behaviors in farmland reclamation and deforestation for heating and timber, we create a spatial evolution model to reconstruct the spatial pattern of historical forest land. The model integrates the land suitability for reclamation, the difficulty of deforestation, the attractiveness of timber trading markets and the abundance of forest resources to calibrate the potential scope of historical forest land with the rationale that the higher the probability of deforestation for reclamation and wood, the greater the likelihood that the forest land will be deforested. Compared to the satellite-based forest land distribution in 2000, about 78.5% of our reconstructed historical forest grids are of the absolute error between 25% and -25% while as many as 95.85% of those grids are of the absolute error between 50% and -50%, which indirectly validates the feasibility of our reconstructed model. Then, we simulate the spatial distribution of forest land in China in 1661, 1724, 1820, 1887, 1933 and 1952 with the grid resolution of 1 km × 1 km. Our result shows that (1) the reconstructed historical forest land in China in the past 300 years concentrates in DaXingAnLing, XiaoXingAnLing, ChangBaiShan, HengDuanShan, DaBaShan, WuYiShan, DaBieShan, XueFengShang and etc.; (2) in terms of the spatial evolution, historical forest land shrank gradually in LiaoHe plains, SongHuaJiang-NenJiang plains and SanJiang plains of eastnorth of China, Sichuan basins and YunNan-GuiZhou Plateaus; and (3) these observations are consistent to the proceeding of agriculture reclamation in China in past 300 years towards Northeast China and Southwest China.

High overlap between traditional ecological knowledge and forest conservation found in the Bolivian Amazon.

PubMed

Paneque-Gálvez, Jaime; Pérez-Llorente, Irene; Luz, Ana Catarina; Guèze, Maximilien; Mas, Jean-François; Macía, Manuel J; Orta-Martínez, Martí; Reyes-García, Victoria

2018-03-12

It has been suggested that traditional ecological knowledge (TEK) may play a key role in forest conservation. However, empirical studies assessing to what extent TEK is associated with forest conservation compared with other variables are rare. Furthermore, to our knowledge, the spatial overlap of TEK and forest conservation has not been evaluated at fine scales. In this paper, we address both issues through a case study with Tsimane' Amerindians in the Bolivian Amazon. We sampled 624 households across 59 villages to estimate TEK and used remote sensing data to assess forest conservation. We ran statistical and spatial analyses to evaluate whether TEK was associated and spatially overlapped with forest conservation at the village level. We find that Tsimane' TEK is significantly and positively associated with forest conservation although acculturation variables bear stronger and negative associations with forest conservation. We also find a very significant spatial overlap between levels of Tsimane' TEK and forest conservation. We discuss the potential reasons underpinning our results, which provide insights that may be useful for informing policies in the realms of development, conservation, and climate. We posit that the protection of indigenous cultural systems is vital and urgent to create more effective policies in such realms.

Evaluation of spatial models to predict vulnerability of forest birds to brood parasitism by cowbirds

USGS Publications Warehouse

Gustafson, E.J.; Knutson, M.G.; Niemi, G.J.; Friberg, M.

2002-01-01

We constructed alternative spatial models at two scales to predict Brown-headed Cowbird (Molothrus ater) parasitism rates from land cover maps. The local-scale models tested competing hypotheses about the relationship between cowbird parasitism and distance of host nests from a forest edge (forest-nonforest boundary). The landscape models tested competing hypotheses about how landscape features (e.g., forests, agricultural fields) interact to determine rates of cowbird parasitism. The models incorporate spatial neighborhoods with a radius of 2.5 km in their formulation, reflecting the scale of the majority of cowbird commuting activity. Field data on parasitism by cowbirds (parasitism rate and number of cowbird eggs per nest) were collected at 28 sites in the Driftless Area Ecoregion of Wisconsin, Minnesota, and Iowa and were compared to the predictions of the alternative models. At the local scale, there was a significant positive relationship between cowbird parasitism and mean distance of nest sites from the forest edge. At the landscape scale, the best fitting models were the forest-dependent and forest-fragmentation-dependent models, in which more heavily forested and less fragmented landscapes had higher parasitism rates. However, much of the explanatory power of these models results from the inclusion of the local-scale relationship in these models. We found lower rates of cowbird parasitism than did most Midwestern studies, and we identified landscape patterns of cowbird parasitism that are opposite to those reported in several other studies of Midwestern songbirds. We caution that cowbird parasitism patterns can be unpredictable, depending upon ecoregional location and the spatial extent, and that our models should be tested in other ecoregions before they are applied there. Our study confirms that cowbird biology has a strong spatial component, and that improved spatial models applied at multiple spatial scales will be required to predict the effects of landscape and forest management on cowbird parasitism of forest birds.

Continuing Climate Warming Will Result in Failure of Post-Harvest Natural Regeneration across the Landscape in Interior Alaska

NASA Astrophysics Data System (ADS)

Morimoto, M.; Juday, G. P.; Huettmann, F.

2016-12-01

Following forest disturbance, the stand initiation stage decisively influences future forest structure. Understanding post-harvest regeneration, especially under climate change, is essential to predicting future carbon stores in this extensive forest biome. We apply IPCC B1, A1B, and A2 climate scenarios to generate plausible future forest conditions under different management. We recorded presence of white spruce, birch, and aspen in 726 plots on 30 state forest white spruce harvest units. We built spatially explicit models and scenarios of species presence/absence using TreeNet (Stochastic Gradient Boosting). Post-harvest tree regeneration predictions in calibration data closely matched the validation set, indicating tree regeneration scenarios are reliable. Early stage post-harvest regeneration is similar to post-fire regeneration and matches the pattern of long-term natural vegetation distribution, confirming that site environmental factors are more important than management practices. Post-harvest natural regeneration of tree species increases under moderate warming scenarios, but fails under strong warming scenarios in landscape positions with high temperatures and low precipitation. Under all warming scenarios, the most successful regenerating species following white spruce harvest is white spruce. Birch experiences about 30% regeneration failure under A2 scenario by 2050. White spruce and aspen are projected to regenerate more successfully when site preparation is applied. Although white spruce has been the major managed species, birch may require more intensive management. Sites likely to experience regeneration failure of current tree species apparently will experience biome shift, although adaptive migration of existing or new species might be an option. Our scenario modeling tool allows resource managers to forecast tree regeneration on productive managed sites that have made a disproportionate contribution to carbon flux in a critical region.

Influence of Pleistocene glacial/interglacial cycles on the genetic structure of the mistletoe cactus Rhipsalis baccifera (Cactaceae) in Mesoamerica.

PubMed

Ornelas, Juan Francisco; Rodríguez-Gómez, Flor

2015-01-01

Phylogeographical work on cloud forest-adapted species provides inconsistent evidence on cloud forest dynamics during glacial cycles. A study of Rhipsalis baccifera (Cactaceae), a bird-dispersed epiphytic mistletoe cactus, was conducted to investigate genetic variation at sequence data from nuclear [internal transcribed spacer (ITS), 677 bp] and chloroplast (rpl32-trnL, 1092bp) DNA for 154 individuals across the species range in Mesoamerica to determine if such patterns are consistent with the expansion/contraction model of cloud forest during glacial cycles. We conducted population and spatial genetic analyses as well as gene flow and divergence time estimates between 24 populations comprising the distribution of R. baccifera in Mexico and Guatemala to gain insight of the evolutionary history of these populations, and a complementary species distribution modeling approach to frame information derived from the genetic analyses into an explicit paleoecological context. The results revealed a phylogeographical break at the Isthmus of Tehuantepec, and high levels of genetic diversity among populations and cloud forest areas. Despite the genetic differentiation of some R. baccifera populations, the widespread ITS ribotypes suggest effective nuclear gene flow via pollen and population differentiation shown by the rpl32-trnL suggests more restricted seed flow. Predictions of species distribution models under past last glacial maximum (LGM) climatic conditions and a significant signal of demographic expansion suggest that R. baccifera populations experienced a range expansion tracking the conditions of the cloud forest distribution and shifted to the lowlands with population connectivity during the LGM. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The First Estimates of Marbled Cat Pardofelis marmorata Population Density from Bornean Primary and Selectively Logged Forest.

PubMed

Hearn, Andrew J; Ross, Joanna; Bernard, Henry; Bakar, Soffian Abu; Hunter, Luke T B; Macdonald, David W

2016-01-01

The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36) and 7.10 (SD: 1.90) individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38) individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches.

Committed carbon emissions, deforestation, and community land conversion from oil palm plantation expansion in West Kalimantan, Indonesia.

PubMed

Carlson, Kimberly M; Curran, Lisa M; Ratnasari, Dessy; Pittman, Alice M; Soares-Filho, Britaldo S; Asner, Gregory P; Trigg, Simon N; Gaveau, David A; Lawrence, Deborah; Rodrigues, Hermann O

2012-05-08

Industrial agricultural plantations are a rapidly increasing yet largely unmeasured source of tropical land cover change. Here, we evaluate impacts of oil palm plantation development on land cover, carbon flux, and agrarian community lands in West Kalimantan, Indonesian Borneo. With a spatially explicit land change/carbon bookkeeping model, parameterized using high-resolution satellite time series and informed by socioeconomic surveys, we assess previous and project future plantation expansion under five scenarios. Although fire was the primary proximate cause of 1989-2008 deforestation (93%) and net carbon emissions (69%), by 2007-2008, oil palm directly caused 27% of total and 40% of peatland deforestation. Plantation land sources exhibited distinctive temporal dynamics, comprising 81% forests on mineral soils (1994-2001), shifting to 69% peatlands (2008-2011). Plantation leases reveal vast development potential. In 2008, leases spanned ∼65% of the region, including 62% on peatlands and 59% of community-managed lands, yet <10% of lease area was planted. Projecting business as usual (BAU), by 2020 ∼40% of regional and 35% of community lands are cleared for oil palm, generating 26% of net carbon emissions. Intact forest cover declines to 4%, and the proportion of emissions sourced from peatlands increases 38%. Prohibiting intact and logged forest and peatland conversion to oil palm reduces emissions only 4% below BAU, because of continued uncontrolled fire. Protecting logged forests achieves greater carbon emissions reductions (21%) than protecting intact forests alone (9%) and is critical for mitigating carbon emissions. Extensive allocated leases constrain land management options, requiring trade-offs among oil palm production, carbon emissions mitigation, and maintaining community landholdings.

Committed carbon emissions, deforestation, and community land conversion from oil palm plantation expansion in West Kalimantan, Indonesia

PubMed Central

Carlson, Kimberly M.; Curran, Lisa M.; Ratnasari, Dessy; Pittman, Alice M.; Soares-Filho, Britaldo S.; Asner, Gregory P.; Trigg, Simon N.; Gaveau, David A.; Lawrence, Deborah; Rodrigues, Hermann O.

2012-01-01

Industrial agricultural plantations are a rapidly increasing yet largely unmeasured source of tropical land cover change. Here, we evaluate impacts of oil palm plantation development on land cover, carbon flux, and agrarian community lands in West Kalimantan, Indonesian Borneo. With a spatially explicit land change/carbon bookkeeping model, parameterized using high-resolution satellite time series and informed by socioeconomic surveys, we assess previous and project future plantation expansion under five scenarios. Although fire was the primary proximate cause of 1989–2008 deforestation (93%) and net carbon emissions (69%), by 2007–2008, oil palm directly caused 27% of total and 40% of peatland deforestation. Plantation land sources exhibited distinctive temporal dynamics, comprising 81% forests on mineral soils (1994–2001), shifting to 69% peatlands (2008–2011). Plantation leases reveal vast development potential. In 2008, leases spanned ∼65% of the region, including 62% on peatlands and 59% of community-managed lands, yet <10% of lease area was planted. Projecting business as usual (BAU), by 2020 ∼40% of regional and 35% of community lands are cleared for oil palm, generating 26% of net carbon emissions. Intact forest cover declines to 4%, and the proportion of emissions sourced from peatlands increases 38%. Prohibiting intact and logged forest and peatland conversion to oil palm reduces emissions only 4% below BAU, because of continued uncontrolled fire. Protecting logged forests achieves greater carbon emissions reductions (21%) than protecting intact forests alone (9%) and is critical for mitigating carbon emissions. Extensive allocated leases constrain land management options, requiring trade-offs among oil palm production, carbon emissions mitigation, and maintaining community landholdings. PMID:22523241

The First Estimates of Marbled Cat Pardofelis marmorata Population Density from Bornean Primary and Selectively Logged Forest

PubMed Central

Hearn, Andrew J.; Ross, Joanna; Bernard, Henry; Bakar, Soffian Abu; Hunter, Luke T. B.; Macdonald, David W.

2016-01-01

The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36) and 7.10 (SD: 1.90) individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38) individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches. PMID:27007219

Contrasting spatial patterns in active-fire and fire-suppressed Mediterranean climate old-growth mixed conifer forests.

PubMed

Fry, Danny L; Stephens, Scott L; Collins, Brandon M; North, Malcolm P; Franco-Vizcaíno, Ernesto; Gill, Samantha J

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha(-1), and occupied 27-46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11-20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥ 56%) in large patches (≥ 10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types.

Large-scale climatic and geophysical controls on the leaf economics spectrum.

PubMed

Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Vaughn, Nicholas

2016-07-12

Leaf economics spectrum (LES) theory suggests a universal trade-off between resource acquisition and storage strategies in plants, expressed in relationships between foliar nitrogen (N) and phosphorus (P), leaf mass per area (LMA), and photosynthesis. However, how environmental conditions mediate LES trait interrelationships, particularly at large biospheric scales, remains unknown because of a lack of spatially explicit data, which ultimately limits our understanding of ecosystem processes, such as primary productivity and biogeochemical cycles. We used airborne imaging spectroscopy and geospatial modeling to generate, to our knowledge, the first biospheric maps of LES traits, here centered on 76 million ha of Andean and Amazonian forest, to assess climatic and geophysical determinants of LES traits and their interrelationships. Elevation and substrate were codominant drivers of leaf trait distributions. Multiple additional climatic and geophysical factors were secondary determinants of plant traits. Anticorrelations between N and LMA followed general LES theory, but topo-edaphic conditions strongly mediated and, at times, eliminated this classic relationship. We found no evidence for simple P-LMA or N-P trade-offs in forest canopies; rather, we mapped a continuum of N-P-LMA interactions that are sensitive to elevation and temperature. Our results reveal nested climatic and geophysical filtering of LES traits and their interrelationships, with important implications for predictions of forest productivity and acclimation to rapid climate change.

Maximizing Amazonia's Ecosystem Services: Juggling the potential for carbon storage, agricultural yield and biodiversity in the Amazon

NASA Astrophysics Data System (ADS)

O'Connell, C. S.; Foley, J. A.; Gerber, J. S.; Polasky, S.

2011-12-01

The Amazon is not only an exceptionally biodiverse and carbon-rich tract of tropical forest, it is also a case study in land use change. Over the next forty years it will continue to experience pressure from an urbanizing and increasingly affluent populace: under a business-as-usual scenario, global cropland, pasture and biofuels systems will carry on expanding, while the Amazon's carbon storage potential will likely become another viable revenue source under REDD+. Balancing those competing land use pressures ought also take into account Amazonia's high - but heterogeneous - biodiversity. Knowing where Amazonia has opportunities to make efficient or optimal trade offs between carbon storage, agricultural production and biodiversity can allow policymakers to direct or influence LUC drivers. This analysis uses a spatially-explicit model that takes climate and management into account to quantify the potential agricultural yield of both the Amazon's most important agricultural commodities - sugar, soy and maize - as well as several that are going to come into increasing prominence, including palm oil. In addition, it maps the potential for carbon to be stored in forest biomass and relative species richness across Amazonia. We then compare carbon storage, agricultural yield and species richness and identify areas where efficient trade offs occur between food, carbon, and biodiversity - three critical ecosystem goods and services provided by the world's largest tropical forest.

Implicit and Explicit Gender Beliefs in Spatial Ability: Stronger Stereotyping in Boys than Girls.

PubMed

Vander Heyden, Karin M; van Atteveldt, Nienke M; Huizinga, Mariette; Jolles, Jelle

2016-01-01

Sex differences in spatial ability are a seriously debated topic, given the importance of spatial ability for success in the fields of science, technology, engineering, and mathematics (STEM) and girls' underrepresentation in these domains. In the current study we investigated the presence of stereotypic gender beliefs on spatial ability (i.e., "spatial ability is for boys") in 10- and 12-year-old children. We used both an explicit measure (i.e., a self-report questionnaire) and an implicit measure (i.e., a child IAT). Results of the explicit measure showed that both sexes associated spatial ability with boys, with boys holding more male stereotyped attitudes than girls. On the implicit measure, boys associated spatial ability with boys, while girls were gender-neutral. In addition, we examined the effects of gender beliefs on spatial performance, by experimentally activating gender beliefs within a pretest-instruction-posttest design. We compared three types of instruction: boys are better, girls are better, and no sex differences. No effects of these gender belief instructions were found on children's spatial test performance (i.e., mental rotation and paper folding). The finding that children of this age already have stereotypic beliefs about the spatial capacities of their own sex is important, as these beliefs may influence children's choices for spatial leisure activities and educational tracks in the STEM domain.

Implicit and Explicit Gender Beliefs in Spatial Ability: Stronger Stereotyping in Boys than Girls

PubMed Central

Vander Heyden, Karin M.; van Atteveldt, Nienke M.; Huizinga, Mariette; Jolles, Jelle

2016-01-01

Sex differences in spatial ability are a seriously debated topic, given the importance of spatial ability for success in the fields of science, technology, engineering, and mathematics (STEM) and girls' underrepresentation in these domains. In the current study we investigated the presence of stereotypic gender beliefs on spatial ability (i.e., “spatial ability is for boys”) in 10- and 12-year-old children. We used both an explicit measure (i.e., a self-report questionnaire) and an implicit measure (i.e., a child IAT). Results of the explicit measure showed that both sexes associated spatial ability with boys, with boys holding more male stereotyped attitudes than girls. On the implicit measure, boys associated spatial ability with boys, while girls were gender-neutral. In addition, we examined the effects of gender beliefs on spatial performance, by experimentally activating gender beliefs within a pretest—instruction—posttest design. We compared three types of instruction: boys are better, girls are better, and no sex differences. No effects of these gender belief instructions were found on children's spatial test performance (i.e., mental rotation and paper folding). The finding that children of this age already have stereotypic beliefs about the spatial capacities of their own sex is important, as these beliefs may influence children's choices for spatial leisure activities and educational tracks in the STEM domain. PMID:27507956

Spatial configuration and distribution of forest patches in Champaign County, Illinois: 1940 to 1993

Treesearch

J. Danilo Chinea

1997-01-01

Spatial configuration and distribution of landscape elements have implications for the dynamics of forest ecosystems, and, therefore, for the management of these resources. The forest cover of Champaign County, in east-central Illinois, was mapped from 1940 and 1993 aerial photography and entered in a geographical information system database. In 1940, 208 forest...

International research to monitor sustainable forest spatial patterns: proceedings of the 2005 IUFRO World Congress symposium

Treesearch

Kurt Riitters; Christine Estreguil

2007-01-01

Presentations from the symposium "International Research to Monitor Sustainable Forest Spatial Patterns," which was organized as part of the International Union of Forest Research Organizations (IUFRO) World Congress in August 2005, are summarized in this report. The overall theme of the World Congress was "Forests in the Balance: Linking Tradition and...

Regression and Geostatistical Techniques: Considerations and Observations from Experiences in NE-FIA

Treesearch

Rachel Riemann; Andrew Lister

2005-01-01

Maps of forest variables improve our understanding of the forest resource by allowing us to view and analyze it spatially. The USDA Forest Service's Northeastern Forest Inventory and Analysis unit (NE-FIA) has used geostatistical techniques, particularly stochastic simulation, to produce maps and spatial data sets of FIA variables. That work underscores the...

Preliminary results of spatial modeling of selected forest health variables in Georgia

Treesearch

Brock Stewart; Chris J. Cieszewski

2009-01-01

Variables relating to forest health monitoring, such as mortality, are difficult to predict and model. We present here the results of fitting various spatial regression models to these variables. We interpolate plot-level values compiled from the Forest Inventory and Analysis National Information Management System (FIA-NIMS) data that are related to forest health....

Spatial heterogeneity and air pollution removal by an urban forest

Treesearch

Francisco J. Escobedo; David J. Nowak

2009-01-01

Estimates of air pollution removal by the urban forest have mostly been based on mean values of forest structure variables for an entire city. However, the urban forest is not uniformly distributed across a city because of biophysical and social factors. Consequently, air pollution removal function by urban vegetation should vary because of this spatial heterogeneity....

Forest fire spatial pattern analysis in Galicia (NW Spain).

PubMed

Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

2013-10-15

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.

Theorizing Land Cover and Land Use Changes: The Case of Tropical Deforestation

NASA Technical Reports Server (NTRS)

Walker, Robert

2004-01-01

This article addresses land-cover and land-use dynamics from the perspective of regional science and economic geography. It first provides an account of the so-called spatially explicit model, which has emerged in recent years as a key empirical approach to the issue. The article uses this discussion as a springboard to evaluate the potential utility of von Thuenen to the discourse on land-cover and land-use change. After identifying shortcomings of current theoretical approaches to land use in mainly urban models, the article filters a discussion of deforestation through the lens of bid-rent and assesses its effectiveness in helping us comprehend the destruction of tropical forest in the Amazon basin. The article considers the adjustments that would have to be made to existing theory to make it more useful to the empirical issues.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Global Mapping of Provisioning Ecosystem Services

NASA Astrophysics Data System (ADS)

Bingham, Lisa; Straatsma, Menno; Karssenberg, Derek

2016-04-01

Attributing monetary value to ecosystem services for decision-making has become more relevant as a basis for decision-making. There are a number of problematic aspects of the calculations, including consistency of economy represented (e.g., purchasing price, production price) and determining which ecosystem subservices to include in a valuation. While several authors have proposed methods for calculating ecosystem services and calculations are presented for global and regional studies, the calculations are mostly broken down into biomes and regions without showing spatially explicit results. The key to decision-making for governments is to be able to make spatial-based decisions because a large spatial variation may exist within a biome or region. Our objective was to compute the spatial distribution of global ecosystem services based on 89 subservices. Initially, only the provisioning ecosystem service category is presented. The provisioning ecosystem service category was calculated using 6 ecosystem services (food, water, raw materials, genetic resources, medical resources, and ornaments) divided into 41 subservices. Global data sets were obtained from a variety of governmental and research agencies for the year 2005 because this is the most data complete and recent year available. All data originated either in tabular or grid formats and were disaggregated to 10 km cell length grids. A lookup table with production values by subservice by country were disaggregated over the economic zone (either marine, land, or combination) based on the spatial existence of the subservice (e.g. forest cover, crop land, non-arable land). Values express the production price in international dollars per hectare. The ecosystem services and the ecosystem service category(ies) maps may be used to show spatial variation of a service within and between countries as well as to specifically show the values within specific regions (e.g. countries, continents), biomes (e.g. coastal, forest), or hazardous regions (e.g. landslides, flood plains, war zones). A preliminary example of the provisioning ecosystem service category illustrates the valuation of deltaic regions and a second example illustrates the valuation of the subservice category of food production prices in flood zones. Future work of this research will spatially represent the calculations of the remaining three ecosystem service categories (regulating, habitat, cultural) and investigate the propagation of uncertainty of the input data to ecosystem service maps.

Forest Management Under Uncertainty for Multiple Bird Population Objectives

Treesearch

Clinton T. Moore; W. Todd Plummer; Michael J. Conroy

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in...

Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest

USGS Publications Warehouse

van Mantgem, P.J.; Schwilk, D.W.

2009-01-01

Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.

Simulation Studies of the Effect of Forest Spatial Structure on InSAR Signature

NASA Technical Reports Server (NTRS)

Sun, Guoqing; Liu, Dawei; Ranson, K. Jon; Koetz, Benjamin

2007-01-01

The height of scattering phase retrieved from InSAR data is considered being correlated with the tree height and the spatial structure of the forest stand. Though some researchers have used simple backscattering models to estimate tree height from the height of scattering center, the effect of forest spatial structure on InSAR data is not well understood yet. A three-dimensional coherent radar backscattering model for forest canopies based on realistic three-dimensional scene was used to investigate the effect in this paper. The realistic spatial structure of forest canopies was established either by field measurements (stem map) or through use of forest growth model. Field measurements or a forest growth model parameterized using local environmental parameters provides information of forest species composition and tree sizes in certain growth phases. A fractal tree model (L-system) was used to simulate individual 3- D tree structure of different ages or heights. Trees were positioned in a stand in certain patterns resulting in a 3-D medium of discrete scatterers. The radar coherent backscatter model took the 3-D forest scene as input and simulates the coherent radar backscattering signature. Interferometric SAR images of 3D scenes were simulated and heights of scattering phase centers were estimated from the simulated InSAR data. The effects of tree height, crown cover, crown depth, and the spatial distribution patterns of trees on the scattering phase center were analyzed. The results will be presented in the paper.

Quantifying spatial patterns of tree groups and gaps in mixed-conifer forests: reference conditions and long-term changes following fire suppression and logging

Treesearch

Jamie M. Lydersen; Malcolm P. North; Eric E. Knapp; Brandon M. Collins

2013-01-01

Fire suppression and past logging have dramatically altered forest conditions in many areas, but changes to within-stand tree spatial patterns over time are not as well understood. The few studies available suggest that variability in tree spatial patterns is an important structural feature of forests with intact frequent fire regimes that should be incorporated in...

Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Treesearch

Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow

PubMed Central

Tague, Christina L.; Moritz, Max A.

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. PMID:27575592

Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird.

PubMed

Khimoun, Aurélie; Peterman, William; Eraud, Cyril; Faivre, Bruno; Navarro, Nicolas; Garnier, Stéphane

2017-10-01

Within the framework of landscape genetics, resistance surface modelling is particularly relevant to explicitly test competing hypotheses about landscape effects on gene flow. To investigate how fragmentation of tropical forest affects population connectivity in a forest specialist bird species, we optimized resistance surfaces without a priori specification, using least-cost (LCP) or resistance (IBR) distances. We implemented a two-step procedure in order (i) to objectively define the landscape thematic resolution (level of detail in classification scheme to describe landscape variables) and spatial extent (area within the landscape boundaries) and then (ii) to test the relative role of several landscape features (elevation, roads, land cover) in genetic differentiation in the Plumbeous Warbler (Setophaga plumbea). We detected a small-scale reduction of gene flow mainly driven by land cover, with a negative impact of the nonforest matrix on landscape functional connectivity. However, matrix components did not equally constrain gene flow, as their conductivity increased with increasing structural similarity with forest habitat: urban areas and meadows had the highest resistance values whereas agricultural areas had intermediate resistance values. Our results revealed a higher performance of IBR compared to LCP in explaining gene flow, reflecting suboptimal movements across this human-modified landscape, challenging the common use of LCP to design habitat corridors and advocating for a broader use of circuit theory modelling. Finally, our results emphasize the need for an objective definition of landscape scales (landscape extent and thematic resolution) and highlight potential pitfalls associated with parameterization of resistance surfaces. © 2017 John Wiley & Sons Ltd.

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow.

PubMed

Bart, Ryan R; Tague, Christina L; Moritz, Max A

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.

Simulating effects of fire on northern Rocky Mountain landscapes with the ecological process model FIRE-BGC.

PubMed

Keane, R E; Ryan, K C; Running, S W

1996-03-01

A mechanistic, biogeochemical succession model, FIRE-BGC, was used to investigate the role of fire on long-term landscape dynamics in northern Rocky Mountain coniferous forests of Glacier National Park, Montana, USA. FIRE-BGC is an individual-tree model-created by merging the gap-phase process-based model FIRESUM with the mechanistic ecosystem biogeochemical model FOREST-BGC-that has mixed spatial and temporal resolution in its simulation architecture. Ecological processes that act at a landscape level, such as fire and seed dispersal, are simulated annually from stand and topographic information. Stand-level processes, such as tree establishment, growth and mortality, organic matter accumulation and decomposition, and undergrowth plant dynamics are simulated both daily and annually. Tree growth is mechanistically modeled based on the ecosystem process approach of FOREST-BGC where carbon is fixed daily by forest canopy photosynthesis at the stand level. Carbon allocated to the tree stem at the end of the year generates the corresponding diameter and height growth. The model also explicitly simulates fire behavior and effects on landscape characteristics. We simulated the effects of fire on ecosystem characteristics of net primary productivity, evapotranspiration, standing crop biomass, nitrogen cycling and leaf area index over 200 years for the 50,000-ha McDonald Drainage in Glacier National Park. Results show increases in net primary productivity and available nitrogen when fires are included in the simulation. Standing crop biomass and evapotranspiration decrease under a fire regime. Shade-intolerant species dominate the landscape when fires are excluded. Model tree increment predictions compared well with field data.

Contemporary carbon dynamics in terrestrial ecosystems in the Southeastern Plains of the United States

USGS Publications Warehouse

Liu, S.; Loveland, Thomas R.; Kurtz, R.M.

2004-01-01

Quantifying carbon dynamics over large areas is frequently hindered by the lack of consistent, high-quality, spatially explicit land use and land cover change databases and appropriate modeling techniques. In this paper, we present a generic approach to address some of these challenges. Land cover change information in the Southeastern Plains ecoregion was derived from Landsat data acquired in 1973, 1980, 1986, 1992, and 2000 within 11 randomly located 20-km × 20-km sample blocks. Carbon dynamics within each of the sample blocks was simulated using the General Ensemble Biogeochemical Modeling System (GEMS), capable of assimilating the variances and covariance of major input variables into simulations using an ensemble approach. Results indicate that urban and forest areas have been increasing, whereas agricultural land has been decreasing since 1973. Forest clear-cutting activity has intensified, more than doubling from 1973 to 2000. The Southeastern Plains has been acting as a carbon sink since 1973, with an average rate of 0.89 Mg C/ha/yr. Biomass, soil organic carbon (SOC), and harvested materials account for 56%, 34%, and 10% of the sink, respectively. However, the sink has declined continuously during the same period owing to forest aging in the northern part of the ecoregion and increased forest clear-cutting activities in the south. The relative contributions to the sink from SOC and harvested materials have increased, implying that these components deserve more study in the future. The methods developed here can be used to quantify the impacts of human management activities on the carbon cycle at landscape to global scales.

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

Huang, Maoyi; Asner, Gregory P.

Amazon deforestation contributes significantly to global carbon (C) emissions. In comparison, the contribution from selective logging to atmospheric CO2 emissions, and its impact on regional C dynamics, is highly uncertain. Using a new geographically-based modeling approach in combination with high resolution remote sensing data from 1999-2002, we estimate that C emissions were 0.04 – 0.05 Pg C yr-1 due to selective logging from a ~2,664,960 km2 region of the Brazilian Amazon. Selective logging was responsible for 15-19% higher carbon emissions than reported from deforestation (clear-cutting) alone. Our simulations indicated that forest carbon lost via selective logging lasts two to threemore » decades following harvest, and that the original live biomass takes up to a century to recover, if the forests are not subsequently cleared. The two- to three-decade loss of carbon results from the biomass damaged by logging activities, including leaves, wood, and roots, estimated to be 89.1 Tg C yr-1 from 1999-2002 over the study region, leaving 70.0 Tg C yr-1 and 7.9 Tg C yr-1 to accumulate as coarse woody debris and soil C, respectively. While avoided deforestation is central to crediting rainforest nations for reduced carbon emissions, the extent and intensity of selective logging are also critical to determining carbon emissions in the context of Reduced Emissions from Deforestation and Forest Degradation (REDD). We show that a combination of automated high-resolution satellite monitoring and detailed forest C modeling can yield spatially explicit estimates of harvest related C losses and subsequent recovery in support of REDD and other international carbon market mechanisms.« less

Historical forest structure, composition, and spatial pattern in dry conifer forests of the western Blue Mountains, Oregon

Treesearch

Derek J. Churchill; Gunnar C. Carnwath; Andrew J. Larson; Sean A. Jeronimo

2017-01-01

In frequent-fire forests of the interior Western United States, historical (prefire suppression) conditions are often used as a reference to set management objectives, guide prescriptions, and monitor treatment effectiveness. We quantified the historical size, density, composition, and spatial patterns of dry mixed-conifer forests in the Blue Mountains of Oregon to...

Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

Treesearch

Jill M. Nakawatase; David L. Peterson

2006-01-01

For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....

The effects of seed dispersal on the simulation of long-term forest landscape change

Treesearch

Hong S. He; David J. Mladenoff

1999-01-01

The study of forest landscape change requires an understanding of the complex interactions of both spatial and temporal factors. Traditionally, forest gap models have been used to simulate change on small and independent plots. While gap models are useful in examining forest ecological dynamics across temporal scales, large, spatial processes, such as seed dispersal,...

Spatial Information Needs on the Fishlake National Forest: Can FIA Help?

Treesearch

Robert B., Jr. Campbell; Renee A. O' Brien

2005-01-01

National forest staff members are frequently challenged to make assessments with existing information. They rarely have the time or resources to go to the field to gather new data specific to the question at hand. Forest Inventory and Analysis (FIA) data have proved useful in the past, but there is an increasing need for spatial depictions of forest resources to...

Prioritizing bird conservation actions in the Prairie Hardwood transition of the Midwestern United States

USGS Publications Warehouse

Thogmartin, Wayne E.; Crimmins, Shawn M.; Pearce, Jennie

2014-01-01

Large-scale planning for the conservation of species is often hindered by a poor understanding of factors limiting populations. In regions with declining wildlife populations, it is critical that objective metrics of conservation success are developed to ensure that conservation actions achieve desired results. Using spatially explicit estimates of bird abundance, we evaluated several management alternatives for conserving bird populations in the Prairie Hardwood Transition of the United States. We designed landscapes conserving species at 50% of their current predicted abundance as well as landscapes attempting to achieve species population targets (which often required the doubling of current abundance). Conserving species at reduced (half of current) abundance led to few conservation conflicts. However, because of extensive modification of the landscape to suit human use, strategies for achieving regional population targets for forest bird species would be difficult under even ideal circumstances, and even more so if maintenance of grassland bird populations is also desired. Our results indicated that large-scale restoration of agricultural lands to native grassland and forest habitats may be the most productive conservation action for increasing bird population sizes but the level of landscape transition required to approach target bird population sizes may be societally unacceptable.

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Contrasting Spatial Patterns in Active-Fire and Fire-Suppressed Mediterranean Climate Old-Growth Mixed Conifer Forests

PubMed Central

Fry, Danny L.; Stephens, Scott L.; Collins, Brandon M.; North, Malcolm P.; Franco-Vizcaíno, Ernesto; Gill, Samantha J.

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha−1, and occupied 27–46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11–20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥56%) in large patches (≥10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types. PMID:24586472

The impacts of disturbance on the spatial and temporal variations of carbon balance in forest ecosystems on Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Hirata, R.; Ito, A.; Saigusa, N.

2013-12-01

Carbon balance in a forest ecosystem can be quite variable if the forest ecosystem structure and function change abruptly as a result of disturbance and subsequent recovery processes. A map of forest age is useful for upscaling carbon balance from the site level to a regional scale because it provides information about when disturbance occurred and how it spread over a wide area. In this study, we used maps of forest age to help evaluate spatial and temporal variations in the carbon balance of forest ecosystems with a process-based ecosystem model. Forests less than 60 years old account for more than 70% of Japanese forests because forest stands have been quickly replaced after disturbance caused by thinning, harvesting, plantations, fires, typhoons, and insect damage. However, few studies have attempted to quantify how much disturbance affects the spatial and temporal variations of carbon balance. In this study, we focused on how disturbance and subsequent re-growth affected the spatial and temporal variations of the carbon balance of forests. We adapted the Vegetation Integrative SImulator for Trace Gases (VISIT) model in order to simulate carbon balance on Hokkaido, which is the northernmost island of Japan. The model was validated with tower flux data obtained from forests with ages between 0 and 43 years. Simulations of the carbon balance were conducted for the period 1948-2010 after a 1000-year spin-up at a spatial resolution of 1 km × 1 km. We investigated two case studies of simulated carbon balance: one that took into account the spatial distribution of forest ages derived from forest inventory data, and another that ignored the impact of disturbance (i.e., no disturbance and a homogeneous distribution of ages). We first focused on the difference from 2000-2010 in the spatial distribution of net ecosystem production (NEP) between the disturbance and non-disturbance cases. In the non-disturbance case, the temporal and spatial changes in NEP were gradual and ranged from 0 to 1 t C ha-1 y-1, depending on meteorological conditions such as temperature or solar radiation. In the disturbance case, however, large NEP changes ranging from 3 to 5 t C ha-1 y-1 were distributed in patches like hotspots, because the forests in those spots ranged in age from 20 to 100 years and were younger than the forests in the non-disturbance case. In the 1970s, wood harvesting and tree planting were conducted intensively on Hokkaido. In the disturbance case during this period, there were many hotspots where NEP was negative. We next focused on the difference between the disturbance and non-disturbance cases of temporal variations of spatially averaged NEP on Hokkaido. Until 1970, the difference between the two cases of average NEP was less than 0.01 t C ha-1 y-1. After 1970, the difference became large and reached about 0.5 t C ha-1 y-1, the implication being that the regional NEP in the disturbance case increased to as much as 2-5 times the regional NEP of the non-disturbance case. Our results show the importance of considering forest age when simulating the carbon balance of forests. Carbon balance maps that take forest age into account are useful for carbon management and prediction of ecosystem feedbacks on climate change.

Development of national database on long-term deforestation (1930-2014) in Bangladesh

NASA Astrophysics Data System (ADS)

Reddy, C. Sudhakar; Pasha, S. Vazeed; Jha, C. S.; Diwakar, P. G.; Dadhwal, V. K.

2016-04-01

The aim of the present study is to prepare a nation-wide spatial database on forest cover to assess and monitor the land use changes associated with deforestation in Bangladesh. The multi-source data were interpreted to get the forest cover map of 1930, 1975, 1985, 1995, 2006 and 2014. The spatial information generated on total area under forest cover, rate of deforestation and afforestation, changes across forest types, forest canopy density, replacement land use in deforested area and deforestation hotspots. This spatial analysis has indicated that forest cover is undergoing significant negative change in area and quality. We report that forests in Bangladesh covered an area of 23,140 km2 in 1930 which has decreased to 14,086 km2 in 2014, a net loss of 9054 km2 (39.1%) in eight decades. Analysis of annual rate of gross deforestation for the recent period indicates 0.77% during 2006-2014. During the past eight decades, semi-evergreen forests show loss of 56.4% of forest cover followed by moist deciduous forests (51.5%), dry deciduous forests (43.1%) and mangroves (6.5%). The loss of 23.5% of dense forest cover was found from 1975 to 2014. Dense semi-evergreen forests shows more negative change (36.9%) followed by dense moist deciduous forest (32.7%) from 1975 to 2014. Annual rate of deforestation is higher in dense forests compared to open forests from 2006 to 2014 and indicates increased threat due to anthropogenic pressures. The spatial analysis of forest cover change in mangroves has shown a lower rate of deforestation. Most of the forest conversions have led to the degradation of forests to scrub and transition to agriculture and plantation. The study has identified the 'deforestation hotspots' can help in strategic planning for conservation and management of forest resources.

Development of Spatial Scaling Technique of Forest Health Sample Point Information

NASA Astrophysics Data System (ADS)

Lee, J. H.; Ryu, J. E.; Chung, H. I.; Choi, Y. Y.; Jeon, S. W.; Kim, S. H.

2018-04-01

Forests provide many goods, Ecosystem services, and resources to humans such as recreation air purification and water protection functions. In rececnt years, there has been an increase in the factors that threaten the health of forests such as global warming due to climate change, environmental pollution, and the increase in interest in forests, and efforts are being made in various countries for forest management. Thus, existing forest ecosystem survey method is a monitoring method of sampling points, and it is difficult to utilize forests for forest management because Korea is surveying only a small part of the forest area occupying 63.7 % of the country (Ministry of Land Infrastructure and Transport Korea, 2016). Therefore, in order to manage large forests, a method of interpolating and spatializing data is needed. In this study, The 1st Korea Forest Health Management biodiversity Shannon;s index data (National Institute of Forests Science, 2015) were used for spatial interpolation. Two widely used methods of interpolation, Kriging method and IDW(Inverse Distance Weighted) method were used to interpolate the biodiversity index. Vegetation indices SAVI, NDVI, LAI and SR were used. As a result, Kriging method was the most accurate method.

Transition from traditional to modern forest management shaped the spatial extent of cattle pasturing in Białowieża Primeval Forest in the nineteenth and twentieth centuries.

PubMed

Samojlik, Tomasz; Fedotova, Anastasia; Kuijper, Dries P J

2016-12-01

Pasturing of livestock in forests has had profound consequences for Europe's landscapes. In Białowieża Primeval Forest (BPF), cattle pasturing was a part of traditional forest use that ceased only in the second half of the twentieth century. We collected information on the institutional changes governing forest cattle pasturing and the changes in spatial extent of cattle presence in BPF in last two centuries and information on cattle numbers and their impact on forest regeneration. The spatial extent of cattle pasturing was highly variable, with the distribution of grazing areas frequently changing. Forest near villages (constituting less than 10 % of the area) was most often used for cattle grazing during continued longer time periods. Historical data showed that cattle have had a clear impact on forest regeneration. However, the frequent changes that occurred in the extent of cattle grazing indicate that their impact occurred locally, was smaller in other less intensively used areas, and in the forest as a whole.

A heuristic for landscape management

Treesearch

Martín Alfonso B. Mendoza; Jesús S. Zepeta; Juan José A. Fajardo

2006-01-01

The development of landscape ecology has stressed out the importance of spatial and sequential relationships as explanations to forest stand dynamics, and for other natural ambiences. This presentation offers a specific design that introduces spatial considerations into forest planning with the idea of regulating fragmentation and connectivity in commercial forest...

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

Luiz, Amom Mendes; Sawaya, Ricardo J.

2018-01-01

Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.