Foresters' Metric Conversions program (version 1.0). [Computer program

Treesearch

Jefferson A. Palmer

1999-01-01

The conversion of scientific measurements has become commonplace in the fields of - engineering, research, and forestry. Foresters? Metric Conversions is a Windows-based computer program that quickly converts user-defined measurements from English to metric and from metric to English. Foresters? Metric Conversions was derived from the publication "Metric...

Statistical properties of mean stand biomass estimators in a LIDAR-based double sampling forest survey design.

Treesearch

H.E. Anderson; J. Breidenbach

2007-01-01

Airborne laser scanning (LIDAR) can be a valuable tool in double-sampling forest survey designs. LIDAR-derived forest structure metrics are often highly correlated with important forest inventory variables, such as mean stand biomass, and LIDAR-based synthetic regression estimators have the potential to be highly efficient compared to single-stage estimators, which...

Disentangling environmental and spatial effects on phylogenetic structure of angiosperm tree communities in China.

PubMed

Qian, Hong; Chen, Shengbin; Zhang, Jin-Long

2017-07-17

Niche-based and neutrality-based theories are two major classes of theories explaining the assembly mechanisms of local communities. Both theories have been frequently used to explain species diversity and composition in local communities but their relative importance remains unclear. Here, we analyzed 57 assemblages of angiosperm trees in 0.1-ha forest plots across China to examine the effects of environmental heterogeneity (relevant to niche-based processes) and spatial contingency (relevant to neutrality-based processes) on phylogenetic structure of angiosperm tree assemblages distributed across a wide range of environment and space. Phylogenetic structure was quantified with six phylogenetic metrics (i.e., phylogenetic diversity, mean pairwise distance, mean nearest taxon distance, and the standardized effect sizes of these three metrics), which emphasize on different depths of evolutionary histories and account for different degrees of species richness effects. Our results showed that the variation in phylogenetic metrics explained independently by environmental variables was on average much greater than that explained independently by spatial structure, and the vast majority of the variation in phylogenetic metrics was explained by spatially structured environmental variables. We conclude that niche-based processes have played a more important role than neutrality-based processes in driving phylogenetic structure of angiosperm tree species in forest communities in China.

Multitemporal analysis of landscape metrics for monitoring forested patterns in coastal and mountainous areas

NASA Astrophysics Data System (ADS)

Carone, M. T.; Imbrenda, V.; Lanfredi, M.; Macchiato, M.; Simoniello, T.

2009-04-01

The role of forested areas for the maintaining of an acceptable landscape balance is crucial. As an example, they contribute to higher biodiversity levels directly and to cleaner fluvial waters indirectly, thus, the degradation of such ecosystems has strong repercussions on many ecological processes. In order to preserve their natural stability, monitoring forest temporal dynamics is very important for a correct management, particularly, in fragile Mediterranean environments that are highly vulnerable to both natural and human-induced perturbations. For analysing the evolution of forested patterns, especially in areas with a strong human presence, landscape metrics are a basilar tool since they allow for evaluating the structure of landscape patterns at different spatio-temporal scales and the relationship between natural environment and human environment. Starting from this premise, we selected a set of Landscape Metrics to evaluate the temporal dynamics of forested covers in two different environments (coastal and mountainous) located in Basilicata Region, Southern Italy. The first one (area A) is located along the Ionian coast and is largely characterized by evergreen forests; in such an area, even if many sites are protected by the European Community (SCI), forests are subjected to a strong incidence of human activities mainly linked to agriculture and tourism as well as to frequent fire events and coastal erosion processes that favour salt-water intrusion. The second one (area B) is a high heterogeneous mountainous area, which also comprehends alluvial planes. The particular configuration of the territory allows for the presence of a very rich faunal and vegetation biodiversity; thus, it is partially under the protection of a National Park, but there are also many critical anthropical activities (e.g. oil drilling, agriculture, etc.). The landscape ecology analyses were performed on multi temporal land cover maps, obtained from hybrid classifications of a time series of Landsat-TM subscenes: for area A, we used five images covering the period 1987-2006; and for area B, three images covering the period 1993-1998. The analysis of landscape structure and dynamics were performed by elaborating metrics based on patch number, size, shape and arrangements of different land cover types. At landscape level, area A provided quite low levels of Evenness (SHEI<0,70) and Diversity (SHDI~1.0) for the analyzed period. Metrics at patch and class levels, particularly for patch dimensions (MPS), complexity (FRACT) and Interdispersion (IJI) showed a little expansion of the urban sites and no important changes for the large agricultural areas. On the contrary, for natural areas a process of fragmentation has been revealed for coniferous forests in the period 1987-1998 when they show an alternation with a less structured and herbaceous vegetation. For area B, the landscape level shows, in the studied period, stable high values of Evenness (SHEI>0.80) and medium values of Diversity (SHDI~1.8). Metrics for patch and class levels reveal, instead, an increment in size and complexity for anthropical vegetation and a decrement for natural forested areas (mainly beeches) accompanied by a high variability of the transitional areas located along the edges of forested sites. On the whole, the combined interpretation of metrics at different levels of landscape structure and at different time steps revealed an increasing trend of forest isolation and fragmentation, which can enhance their sensitivity. The obtained results for both areas suggest that the institution of protected areas is not a complete solution for the maintaining of forest ecosystems balance without a correct management of the surrounding areas. In order to increase the connectivity among forested patches and, more in general, to improve the ecosystem functionality, the ecological analysis of satellite time series represents an operative tool for an efficient intervention planning, such as the location of the most suitable sites for ecological restoration activities.

Updating stand-level forest inventories using airborne laser scanning and Landsat time series data

NASA Astrophysics Data System (ADS)

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

2018-04-01

Vertical forest structure can be mapped over large areas by combining samples of airborne laser scanning (ALS) data with wall-to-wall spatial data, such as Landsat imagery. Here, we use samples of ALS data and Landsat time-series metrics to produce estimates of top height, basal area, and net stem volume for two timber supply areas near Kamloops, British Columbia, Canada, using an imputation approach. Both single-year and time series metrics were calculated from annual, gap-free Landsat reflectance composites representing 1984-2014. Metrics included long-term means of vegetation indices, as well as measures of the variance and slope of the indices through time. Terrain metrics, generated from a 30 m digital elevation model, were also included as predictors. We found that imputation models improved with the inclusion of Landsat time series metrics when compared to single-year Landsat metrics (relative RMSE decreased from 22.8% to 16.5% for top height, from 32.1% to 23.3% for basal area, and from 45.6% to 34.1% for net stem volume). Landsat metrics that characterized 30-years of stand history resulted in more accurate models (for all three structural attributes) than Landsat metrics that characterized only the most recent 10 or 20 years of stand history. To test model transferability, we compared imputed attributes against ALS-based estimates in nearby forest blocks (>150,000 ha) that were not included in model training or testing. Landsat-imputed attributes correlated strongly to ALS-based estimates in these blocks (R2 = 0.62 and relative RMSE = 13.1% for top height, R2 = 0.75 and relative RMSE = 17.8% for basal area, and R2 = 0.67 and relative RMSE = 26.5% for net stem volume), indicating model transferability. These findings suggest that in areas containing spatially-limited ALS data acquisitions, imputation models, and Landsat time series and terrain metrics can be effectively used to produce wall-to-wall estimates of key inventory attributes, providing an opportunity to update estimates of forest attributes in areas where inventory information is either out of date or non-existent.

Quantitative classification of a historic northern Wisconsin (U.S.A.) landscape: mapping forests at regional scales

Treesearch

Lisa A. Schulte; David J. Mladenoff; Erik V. Nordheim

2002-01-01

We developed a quantitative and replicable classification system to improve understanding of historical composition and structure within northern Wisconsin's forests. The classification system was based on statistical cluster analysis and two forest metrics, relative dominance (% basal area) and relative importance (mean of relative dominance and relative density...

Implications of alternative field-sampling designs on Landsat-based mapping of stand age and carbon stocks in Oregon forests

Treesearch

Maureen V. Duane; Warren B. Cohen; John L. Campbell; Tara Hudiburg; David P. Turner; Dale Weyermann

2010-01-01

Empirical models relating forest attributes to remotely sensed metrics are widespread in the literature and underpin many of our efforts to map forest structure across complex landscapes. In this study we compared empirical models relating Landsat reflectance to forest age across Oregon using two alternate sets of ground data: one from a large (n ~ 1500) systematic...

Terrain and vegetation structural influences on local avian species richness in two mixed-conifer forests

Treesearch

Jody C. Vogeler; Andrew T. Hudak; Lee A. Vierling; Jeffrey Evans; Patricia Green; Kerri T. Vierling

2014-01-01

Using remotely-sensed metrics to identify regions containing high animal diversity and/or specific animal species or guilds can help prioritize forest management and conservation objectives across actively managed landscapes. We predicted avian species richness in two mixed conifer forests, Moscow Mountain and Slate Creek, containing different management contexts and...

Landscape-scale changes in forest canopy structure across a partially logged tropical peat swamp

NASA Astrophysics Data System (ADS)

Wedeux, B. M. M.; Coomes, D. A.

2015-07-01

Forest canopy structure is strongly influenced by environmental factors and disturbance, and in turn influences key ecosystem processes including productivity, evapotranspiration and habitat availability. In tropical forests increasingly modified by human activities, the interplaying effects of environmental factors and disturbance legacies on forest canopy structure across landscapes are practically unexplored. We used high-fidelity airborne laser scanning (ALS) data to measure the canopy of old-growth and selectively logged peat swamp forest across a peat dome in Central Kalimantan, Indonesia, and quantified how canopy structure metrics varied with peat depth and under logging. Several million canopy gaps in different height cross-sections of the canopy were measured in 100 plots of 1 km2 spanning the peat dome, allowing us to describe canopy structure with seven metrics. Old-growth forest became shorter and had simpler vertical canopy profiles on deeper peat, consistently with previous work linking deep peat to stunted tree growth. Gap Size Frequency Distributions (GSFDs) indicated fewer and smaller canopy gaps on the deeper peat (i.e. the scaling exponent of pareto functions increased from 1.76 to 3.76 with peat depth). Areas subjected to concessionary logging until 2000, and informal logging since then, had the same canopy top height as old-growth forest, indicating the persistence of some large trees, but mean canopy height was significantly reduced; the total area of canopy gaps increased and the GSFD scaling exponent was reduced. Logging effects were most evident on the deepest peat, where nutrient depletion and waterlogged conditions restrain tree growth and recovery. A tight relationship exists between canopy structure and the peat deph gradient within the old-growth tropical peat swamp. This relationship breaks down after selective logging, with canopy structural recovery being modulated by environmental conditions.

Estimating tropical forest structure using LIDAR AND X-BAND INSAR

NASA Astrophysics Data System (ADS)

Palace, M. W.; Treuhaft, R. N.; Keller, M. M.; Sullivan, F.; Roberto dos Santos, J.; Goncalves, F. G.; Shimbo, J.; Neumann, M.; Madsen, S. N.; Hensley, S.

2013-12-01

Tropical forests are considered the most structurally complex of all forests and are experiencing rapid change due to anthropogenic and climatic factors. The high carbon stocks and fluxes make understanding tropical forests highly important to both regional and global studies involving ecosystems and climate. Large and remote areas in the tropics are prime targets for the use of remotely sensed data. Radar and lidar have previously been used to estimate forest structure, with an emphasis on biomass. These two remote sensing methods have the potential to yield much more information about forest structure, specifically through the use of X-band radar and waveform lidar data. We examined forest structure using both field-based and remotely sensed data in the Tapajos National Forest, Para, Brazil. We measured multiple structural parameters for about 70 plots in the field within a 25 x 15 km area that have TanDEM-X single-pass horizontally and vertically polarized radar interferometric data. High resolution airborne lidar were collected over a 22 sq km portion of the same area, within which 33 plots were co-located. Preliminary analyses suggest that X-band interferometric coherence decreases by about a factor of 2 (from 0.95 to 0.45) with increasing field-measured vertical extent (average heights of 7-25 m) and biomass (10-430 Mg/ha) for a vertical wavelength of 39 m, further suggesting, as has been observed at C-band, that interferometric synthetic aperture radar (InSAR) is substantially more sensitive to forest structure/biomass than SAR. Unlike InSAR coherence versus biomass, SAR power at X-band versus biomass shows no trend. Moreover, airborne lidar coherence at the same vertical wavenumbers as InSAR is also shown to decrease as a function of biomass, as well. Although the lidar coherence decrease is about 15% more than the InSAR, implying that lidar penetrates more than InSAR, these preliminary results suggest that X-band InSAR may be useful for structure and biomass estimation over large spatial scales not attainable with airborne lidar. In this study, we employed a set of less commonly used lidar metrics that we consider analogous to field-based measurements, such as the number of canopy maxima, measures of canopy vegetation distribution diversity and evenness (entropy), and estimates of gap fraction. We incorporated these metrics, as well as lidar coherence metrics pulled from discrete Fourier transforms of pseudowaveforms, and hypothetical stand characteristics of best-fit synthetic vegetation profiles into multiple regression analysis of forest biometric properties. Among simple and complex measures of forest structure, ranging from tree density, diameter at breast height, and various canopy geometry parameters, we found strong relationships with lidar canopy vegetation profile parameters. We suggest that the sole use of lidar height is limited in understanding biomass in a forest with little variation across the landscape and that there are many parameters that may be gleaned by lidar data that inform on forest biometric properties.

A terrestrial lidar assessment of climate change impacts on forest structure

NASA Astrophysics Data System (ADS)

van Aardt, J. A.; Kelbe, D.; Sacca, K.; Giardina, C. P.; Selmants, P. C.; Litton, C. M.; Asner, G. P.

2016-12-01

The projected impact of climate change on ecosystems has received much scientific attention, specifically related to geographical species shifts and carbon allocation. This study, however, was undertaken to assess the expected changes in tropical forest structure as a function of changing temperatures. Our study area is a constrained model ecological system and is located on the eastern flank of Mauna Kea Volcano, Hawaii, USA. Nine plots from this closed-canopy, tropical montane wet forest fall along an elevation-based 5.2°C mean annual temperature (MAT) gradient, where multiple other biotic and abiotic factors are held nearly constant. This MAT gradient has been used to assess subtle temperature effects on ecosystem functioning including carbon cycles, but less has been done on the effects of temperature on vegetation structure. We acquired vegetation structural data using a SICK-LMS151 terrestrial laser scanner (905 nm) for full 270x360° coverage. This Compact Biomass Lidar (CBL) was developed by Rochester Institute of Technology and the University of Massachusetts, Boston. Data for each plot along the temperature gradient were collected in a 20 m x 20 m configuration at a 5 m scan spacing. Initial challenges, related to the irregular radial scan pattern and registration of 25 scans per plot, were addressed in order to extract normalized vegetation density metrics and to mitigate occlusion effects, respectively. However, we believe that the CBL scans can be assessed independently, i.e., treating 25 scans/plot as a population sample. We derived height statistics, return density metrics, canopy rugosity, and higher-order metrics in order to describe the differences in vegetation structure, which ultimately will be tied to the elevation-induced temperature range. We hypothesized that, for this MAT gradient (i) vertical vegetation stratification; (ii) diameter distributions; and (iii) aboveground biomass will differ significantly, while more species-dependent canopy rugosity remain stable. Our results support these hypotheses, allowing for future studies of vegetation structural responses to static and dynamic climate drivers. The findings have implications for forest management, mitigation strategies to limit losses in carbon sequestration, and forest inventory in structurally complex forests.

Detecting understory plant invasion in urban forests using LiDAR

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Davis, Amy J.; Meentemeyer, Ross K.

2015-06-01

Light detection and ranging (LiDAR) data are increasingly used to measure structural characteristics of urban forests but are rarely used to detect the growing problem of exotic understory plant invaders. We explored the merits of using LiDAR-derived metrics alone and through integration with spectral data to detect the spatial distribution of the exotic understory plant Ligustrum sinense, a rapidly spreading invader in the urbanizing region of Charlotte, North Carolina, USA. We analyzed regional-scale L. sinense occurrence data collected over the course of three years with LiDAR-derived metrics of forest structure that were categorized into the following groups: overstory, understory, topography, and overall vegetation characteristics, and IKONOS spectral features - optical. Using random forest (RF) and logistic regression (LR) classifiers, we assessed the relative contributions of LiDAR and IKONOS derived variables to the detection of L. sinense. We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L. sinense across our country-wide study extent. RF classification of LiDAR-derived topography metrics produced the highest mapping accuracy estimates, outperforming IKONOS data by 17.5% and the integration of LiDAR and IKONOS data by 5.3%. The top performing model from the RF classifier produced the highest kappa of 64.8%, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2% over the county extent model. Our results demonstrate the superiority of LiDAR-derived metrics over spectral data and fusion of LiDAR and spectral data for accurately mapping the spatial distribution of the forest understory invader L. sinense.

Differential stemflow yield from European beech saplings: the role and respective importance of individual canopy structure metrics

NASA Astrophysics Data System (ADS)

Levia, Delphis; Michalzik, Beate

2013-04-01

Stemflow yield from individual trees varies as a function of both meteorological conditions and canopy structure. The importance and differential effects of various metrics of canopy structure in relation to stemflow yield is inadequately understood and the subject of debate among forest hydrologists. It is possible to evaluate the role and respective importance of individual canopy structure metrics by holding meteorological conditions constant. Twelve isolated experimental European beech (Fagus sylvatica L.) saplings in Jena, Germany were exposed to identical meteorological conditions to examine the effects of canopy structure on stemflow production during the 2012 growing season. The canopy structure metrics being evaluated include: trunk diameter, trunk lean, tree height, projected crown area, branch inclination angle, branch count, and biomass (foliar and woody). Principal components analysis and multiple regression are utilized to determine the relative importance of different canopy structure metrics on stemflow yield. Experimental results will provide insight as to which metrics of canopy structure most strongly govern stemflow production. Ultimately, with a more thorough understanding of the unique contributions of various canopy structural metrics to stemflow yield, a useful conceptual guide of stemflow generation can be formulated on the basis of canopy structure for management purposes. Sponsor note: This research was funded by the Alexander von Humboldt Foundation.

Landscape-scale changes in forest canopy structure across a partially logged tropical peat swamp

NASA Astrophysics Data System (ADS)

Wedeux, B. M. M.; Coomes, D. A.

2015-11-01

Forest canopy structure is strongly influenced by environmental factors and disturbance, and in turn influences key ecosystem processes including productivity, evapotranspiration and habitat availability. In tropical forests increasingly modified by human activities, the interplay between environmental factors and disturbance legacies on forest canopy structure across landscapes is practically unexplored. We used airborne laser scanning (ALS) data to measure the canopy of old-growth and selectively logged peat swamp forest across a peat dome in Central Kalimantan, Indonesia, and quantified how canopy structure metrics varied with peat depth and under logging. Several million canopy gaps in different height cross-sections of the canopy were measured in 100 plots of 1 km2 spanning the peat dome, allowing us to describe canopy structure with seven metrics. Old-growth forest became shorter and had simpler vertical canopy profiles on deeper peat, consistent with previous work linking deep peat to stunted tree growth. Gap size frequency distributions (GSFDs) indicated fewer and smaller canopy gaps on the deeper peat (i.e. the scaling exponent of Pareto functions increased from 1.76 to 3.76 with peat depth). Areas subjected to concessionary logging until 2000, and illegal logging since then, had the same canopy top height as old-growth forest, indicating the persistence of some large trees, but mean canopy height was significantly reduced. With logging, the total area of canopy gaps increased and the GSFD scaling exponent was reduced. Logging effects were most evident on the deepest peat, where nutrient depletion and waterlogged conditions restrain tree growth and recovery. A tight relationship exists between canopy structure and peat depth gradient within the old-growth tropical peat swamp forest. This relationship breaks down after selective logging, with canopy structural recovery, as observed by ALS, modulated by environmental conditions. These findings improve our understanding of tropical peat swamp ecology and provide important insights for managers aiming to restore degraded forests.

Unsupervised classification of lidar-based vegetation structure metrics at Jean Lafitte National Historical Park and Preserve

USGS Publications Warehouse

Kranenburg, Christine J.; Palaseanu-Lovejoy, Monica; Nayegandhi, Amar; Brock, John; Woodman, Robert

2012-01-01

Traditional vegetation maps capture the horizontal distribution of various vegetation properties, for example, type, species and age/senescence, across a landscape. Ecologists have long known, however, that many important forest properties, for example, interior microclimate, carbon capacity, biomass and habitat suitability, are also dependent on the vertical arrangement of branches and leaves within tree canopies. The objective of this study was to use a digital elevation model (DEM) along with tree canopy-structure metrics derived from a lidar survey conducted using the Experimental Advanced Airborne Research Lidar (EAARL) to capture a three-dimensional view of vegetation communities in the Barataria Preserve unit of Jean Lafitte National Historical Park and Preserve, Louisiana. The EAARL instrument is a raster-scanning, full waveform-resolving, small-footprint, green-wavelength (532-nanometer) lidar system designed to map coastal bathymetry, topography and vegetation structure simultaneously. An unsupervised clustering procedure was then applied to the 3-dimensional-based metrics and DEM to produce a vegetation map based on the vertical structure of the park's vegetation, which includes a flotant marsh, scrub-shrub wetland, bottomland hardwood forest, and baldcypress-tupelo swamp forest. This study was completed in collaboration with the National Park Service Inventory and Monitoring Program's Gulf Coast Network. The methods presented herein are intended to be used as part of a cost-effective monitoring tool to capture change in park resources.

Resilient networks of ant-plant mutualists in Amazonian forest fragments.

PubMed

Passmore, Heather A; Bruna, Emilio M; Heredia, Sylvia M; Vasconcelos, Heraldo L

2012-01-01

The organization of networks of interacting species, such as plants and animals engaged in mutualisms, strongly influences the ecology and evolution of partner communities. Habitat fragmentation is a globally pervasive form of spatial heterogeneity that could profoundly impact the structure of mutualist networks. This is particularly true for biodiversity-rich tropical ecosystems, where the majority of plant species depend on mutualisms with animals and it is thought that changes in the structure of mutualist networks could lead to cascades of extinctions. We evaluated effects of fragmentation on mutualistic networks by calculating metrics of network structure for ant-plant networks in continuous Amazonian forests with those in forest fragments. We hypothesized that networks in fragments would have fewer species and higher connectance, but equal nestedness and resilience compared to forest networks. Only one of the nine metrics we compared differed between continuous forest and forest fragments, indicating that networks were resistant to the biotic and abiotic changes that accompany fragmentation. This is partially the result of the loss of only specialist species with one connection that were lost in forest fragments. We found that the networks of ant-plant mutualists in twenty-five year old fragments are similar to those in continuous forest, suggesting these interactions are resistant to the detrimental changes associated with habitat fragmentation, at least in landscapes that are a mosaic of fragments, regenerating forests, and pastures. However, ant-plant mutualistic networks may have several properties that may promote their persistence in fragmented landscapes. Proactive identification of key mutualist partners may be necessary to focus conservation efforts on the interactions that insure the integrity of network structure and the ecosystems services networks provide.

Historic range of variability in landscape structure in subalpine forests of the Greater Yellowstone Area, USA

USGS Publications Warehouse

Tinker, D.B.; Romme, W.H.; Despain, Don G.

2003-01-01

A measure of the historic range of variability (HRV) in landscape structure is essential for evaluating current landscape patterns of Rocky Mountain coniferous forests that have been subjected to intensive timber harvest. We used a geographic information system (GIS) and FRAGSTATS to calculate key landscape metrics on two ???130,000-ha landscapes in the Greater Yellowstone Area, USA: one in Yellowstone National Park (YNP), which has been primarily shaped by natural fires, and a second in the adjacent Targhee National Forest (TNF), which has undergone intensive clearcutting for nearly 30 years. Digital maps of the current and historical landscape in YNP were developed from earlier stand age maps developed by Romme and Despain. Maps of the TNF landscape were adapted from United States Forest Service Resource Information System (RIS) data. Key landscape metrics were calculated at 20-yr intervals for YNP for the period from 1705-1995. These metrics were used to first evaluate the relative effects of small vs. large fire events on landscape structure and were then compared to similar metrics calculated for both pre- and post-harvest landscapes of the TNF. Large fires, such as those that burned in 1988, produced a structurally different landscape than did previous, smaller fires (1705-1985). The total number of patches of all types was higher after 1988 (694 vs. 340-404 before 1988), and mean patch size was reduced by almost half (186 ha vs. 319-379 ha). The amount of unburned forest was less following the 1988 fires (63% vs. 72-90% prior to 1988), yet the number of unburned patches increased by nearly an order of magnitude (230 vs. a maximum of 41 prior to 1988). Total core area and mean core area per patch decreased after 1988 relative to smaller fires (???73,700 ha vs. 87,000-110,000 ha, and 320 ha vs. 2,123 ha, respectively). Notably, only edge density was similar (17 m ha-1 after 1988) to earlier landscapes (9.8-14.2 m ha-1). Three decades of timber harvesting dramatically altered landscape structure in the TNF. Total number of patches increased threefold (1,481 after harvest vs. 437 before harvest), and mean patch size decreased by ???70% (91.3 ha vs. 309 ha). None of the post-harvest landscape metrics calculated for the TNF fell within the HRV as defined in YNP, even when the post-1988 landscape was considered. In contrast, pre-harvest TNF landscape metrics were all within, or very nearly within, the HRV for YNP While reference conditions such as those identified by this study are useful for local and regional landscape evaluation and planning, additional research is necessary to understand the consequences of changes in landscape structure for population, community, ecosystem, and landscape function.

A Benthic Community Index for streams in the Northern Lakes and Forests Ecoregion

USGS Publications Warehouse

Butcher, Jason T.; Stewart, Paul M.; Simon, Thomas P.

2003-01-01

Encompassing the northern glaciated section of the Midwest United States, the Northern Lakes and Forests Ecoregion is characterized by mixed conifer and deciduous forests and wetlands. Sites were randomly selected in the ecoregion using the Environmental Protection Agency's Environmental Monitoring and Assessment Program designed to develop an index of biotic integrity for wadeable streams. Macroinvertebrates were sampled during the fall of 1998 and 1999 using a multi-habitat, composite-sample method. Two hundred forty-six invertebrate taxa in 97 families were collected from 94 sites. Ten of 42 candidate metrics satisfied metric selection criteria, including six structural metrics (number of Ephemeroptera taxa, number of Diptera taxa, richness, Shannon-Wiener diversity, percent Trichoptera abundance, and percent Crustacea and Mollusca abundance), two functional metrics (number of Filterer taxa and number of Scraper taxa), and two conditional metrics (number of Ephemeroptera, Trichoptera, and Plecoptera taxa and Hilsenhoff Biotic Index). These metrics were used to develop a Benthic Community Index to assess the biological integrity of wadeable streams in the ecoregion. Index values ranged from 10 to 50, and scores from impaired sites were significantly different than non-impaired sites (P<0.001). Index values were divided into three narrative interpretations of biological integrity (poor, fair, and good). After further testing, the index may provide a useful biological assessment tool for resource managers in the ecoregion.

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

USGS Publications Warehouse

Hall, S. A.; Burke, I.C.; Box, D. O.; Kaufmann, M. R.; Stoker, Jason M.

2005-01-01

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

Forest Succession and Maternity Day roost selection by Myotis septentrionalis in a mesophytic hardwood forest

USGS Publications Warehouse

Silvis, Alexander; Ford, W. Mark; Eric R. Britzke,; Nathan R. Beane,; Joshua B. Johnson,

2012-01-01

Conservation of summer maternity roosts is considered critical for bat management in North America, yet many aspects of the physical and environmental factors that drive roost selection are poorly understood. We tracked 58 female northern bats (Myotis septentrionalis) to 105 roost trees of 21 species on the Fort Knox military reservation in north-central Kentucky during the summer of 2011. Sassafras (Sassafras albidum) was used as a day roost more than expected based on forest stand-level availability and accounted for 48.6% of all observed day roosts. Using logistic regression and an information theoretic approach, we were unable to reliably differentiate between sassafras and other roost species or between day roosts used during different maternity periods using models representative of individual tree metrics, site metrics, topographic location, or combinations of these factors. For northern bats, we suggest that day-roost selection is not a function of differences between individual tree species per se, but rather of forest successional patterns, stand and tree structure. Present successional trajectories may not provide this particular selected structure again without management intervention, thereby suggesting that resource managers take a relatively long retrospective view to manage current and future forest conditions for bats.

Season-modulated responses of Neotropical bats to forest fragmentation.

PubMed

Ferreira, Diogo F; Rocha, Ricardo; López-Baucells, Adrià; Farneda, Fábio Z; Carreiras, João M B; Palmeirim, Jorge M; Meyer, Christoph F J

2017-06-01

Seasonality causes fluctuations in resource availability, affecting the presence and abundance of animal species. The impacts of these oscillations on wildlife populations can be exacerbated by habitat fragmentation. We assessed differences in bat species abundance between the wet and dry season in a fragmented landscape in the Central Amazon characterized by primary forest fragments embedded in a secondary forest matrix. We also evaluated whether the relative importance of local vegetation structure versus landscape characteristics (composition and configuration) in shaping bat abundance patterns varied between seasons. Our working hypotheses were that abundance responses are species as well as season specific, and that in the wet season, local vegetation structure is a stronger determinant of bat abundance than landscape-scale attributes. Generalized linear mixed-effects models in combination with hierarchical partitioning revealed that relationships between species abundances and local vegetation structure and landscape characteristics were both season specific and scale dependent. Overall, landscape characteristics were more important than local vegetation characteristics, suggesting that landscape structure is likely to play an even more important role in landscapes with higher fragment-matrix contrast. Responses varied between frugivores and animalivores. In the dry season, frugivores responded more to compositional metrics, whereas during the wet season, local and configurational metrics were more important. Animalivores showed similar patterns in both seasons, responding to the same group of metrics in both seasons. Differences in responses likely reflect seasonal differences in the phenology of flowering and fruiting between primary and secondary forests, which affected the foraging behavior and habitat use of bats. Management actions should encompass multiscale approaches to account for the idiosyncratic responses of species to seasonal variation in resource abundance and consequently to local and landscape scale attributes.

Going beyond the green: senesced vegetation material predicts basal area and biomass in remote sensing of tree cover conditions in an African tropical dry forest (miombo woodland) landscape

NASA Astrophysics Data System (ADS)

Mayes, Marc; Mustard, John; Melillo, Jerry; Neill, Christopher; Nyadzi, Gerson

2017-08-01

In sub-Saharan Africa (SSA), tropical dry forests and savannas cover over 2.5 million km2 and support livelihoods for millions in fast-growing nations. Intensifying land use pressures have driven rapid changes in tree cover structure (basal area, biomass) that remain poorly characterized at regional scales. Here, we posed the hypothesis that tree cover structure related strongly to senesced and non-photosynthetic (NPV) vegetation features in a SSA tropical dry forest landscape, offering improved means for satellite remote sensing of tree cover structure compared to vegetation greenness-based methods. Across regrowth miombo woodland sites in Tanzania, we analyzed relationships among field data on tree structure, land cover, and satellite indices of green and NPV features based on spectral mixture analyses and normalized difference vegetation index calculated from Landsat 8 data. From satellite-field data relationships, we mapped regional basal area and biomass using NPV and greenness-based metrics, and compared map performances at landscape scales. Total canopy cover related significantly to stem basal area (r 2 = 0.815, p < 0.01) and biomass (r 2 = 0.635, p < 0.01), and NPV dominated ground cover (> 60%) at all sites. From these two conditions emerged a key inverse relationship: skyward exposure of NPV ground cover was high at sites with low tree basal area and biomass, and decreased with increasing stem basal area and biomass. This pattern scaled to Landsat NPV metrics, which showed strong inverse correlations to basal area (Pearson r = -0.85, p < 0.01) and biomass (r = -0.86, p < 0.01). Biomass estimates from Landsat NPV-based maps matched field data, and significantly differentiated landscape gradients in woody biomass that greenness metrics failed to track. The results suggest senesced vegetation metrics at Landsat scales are a promising means for improved monitoring of tree structure across disturbance and ecological gradients in African and other tropical dry forests.

Associations between forest characteristics and socio-economic development: a case study from Portugal.

PubMed

Ribeiro, Sónia Carvalho; Lovett, Andrew

2009-07-01

The integration of socio-economic and environmental objectives is a major challenge in developing strategies for sustainable landscapes. We investigated associations between socio-economic variables, landscape metrics and measures of forest condition in the context of Portugal. The main goals of the study were to 1) investigate relationships between forest conditions and measures of socio-economic development at national and regional scales, 2) test the hypothesis that a systematic variation in forest landscape metrics occurs according to the stage of socio-economic development and, 3) assess the extent to which landscape metrics can inform strategies to enhance forest sustainability. A ranking approach and statistical techniques such as Principal Component Analysis were used to achieve these objectives. Relationships between socio-economic characteristics, landscape metrics and measures of forest condition were only significant in the regional analysis of municipalities in Northern Portugal. Landscape metrics for different tree species displayed significant variations across socio-economic groups of municipalities and these differences were consistent with changes in characteristics suggested by the forest transition model. The use of metrics also helped inform place-specific strategies to improve forest management, though it was also apparent that further work was required to better incorporate differences in forest functions into sustainability planning.

Influence of Traditional Management and Environmental Variables on Mediterranean Saproxylic Beetle Assemblages.

PubMed

Ramilo, P; Martínez-Falcón, A P; García-López, A; Brustel, H; Galante, E; Micó, E

2017-12-08

Mediterranean oak forests of the Iberian Peninsula host a great diversity of saproxylic beetles. For centuries, humans have carried out traditional management practices in this area, at both habitat and tree level, causing changes in forest structure. The aim of this study was to evaluate the anthropic effect of these traditional practices on saproxylic beetle diversity by measuring a set of environmental variables related to forest structure at both plot and tree level. Fauna was collected using window traps over a period of 12 mo. Multiple regression procedures showed which variables significantly affected the diversity of the studied assemblage. Our results demonstrated that the different metrics used to assess the diversity of assemblages responded variably depending on the management strategies applied and the level at which they were carried out. Certain management practices that disrupted the landscape from its natural state, such as the introduction of livestock or the local removal of particular trees, maximized species richness but, nevertheless, had a negative effect on the rest of diversity metrics analyzed. However, other practices such as pollarding, which involves the suppression of the main branch of the tree, had a positive effect on all diversity metrics evaluated as it promoted the formation of potential microhabitats for saproxylic fauna. We concluded that not all types and degrees of traditional forest management favor saproxylic beetle diversity and that different diversity metrics should be taken into consideration in future strategies for the protection and conservation of this fauna. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

PubMed

Liu, Feng; Tan, Chang; Lei, Pi-Feng

2014-11-01

Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics.

PubMed

Esbah, Hayriye; Deniz, Bulent; Kara, Baris; Kesgin, Birsen

2010-06-01

Bafa Lake Nature Park is one of Turkey's most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural-natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.

Extensive Sampling of Forest Carbon using High Density Power Line Lidar

NASA Astrophysics Data System (ADS)

Hampton, H. M.; Chen, Q.; Dye, D. G.; Hungate, B. A.

2013-12-01

Estimating carbon sequestration and greenhouse gas emissions from forest management, natural processes, and disturbance is of growing interest for mitigating global warming. Ponderosa pine is common at mid-elevations throughout the western United States and is a dominant tree species in southwestern forests. Existing unmanaged "relict" sites and stand reconstructions of southwestern ponderosa pine forests from before European settlement (late 1800s) provide evidence of forests of larger trees of lower density and less vulnerability to severe fires than today's typical conditions of high densities of small trees that have resulted from a century of fire suppression. Forest treatments to improve forest health in the region include tree cutting focused on small-diameter trees (thinning), low-intensity prescribed burning, and monitoring rather than suppressing wildfires. Stimulated by several uncharacteristically-intense fires in the last decade, a collaborative process found strong stakeholder agreement to accelerate forest treatments to reduce fire risk and restore ecological conditions. Land use planning to ramp up management is underway and could benefit from quick and inexpensive techniques to inventory tree-level carbon because existing inventory data are not adequate to capture the range of forest structural conditions. Our approach overcomes these shortcomings by employing recent breakthroughs in estimating aboveground biomass from high resolution light detection and ranging (lidar) remote sensing. Lidar is an active remote sensing technique, analogous to radar, which measures the time required for a transmitted pulse of laser light to return to the sensor after reflection from a target. Lidar data can capture 3-dimensional forest structure with greater detail and broader spatial coverage than is feasible with conventional field measurements. We developed a novel methodology for extensive sampling and field validation of forest carbon, applicable to managed and unmanaged areas, using high point density lidar collected over transmission line corridors. The lidar metric of quadratic mean height guided our selection of field plots spanning the full range from low to high levels of aboveground biomass across the study region. Before model selection, we minimized two of the major sources of errors in lidar calibration: variance in tree allometry across landscapes and plot edge effects (spatial mismatch between field measurements and lidar points). We tested an assortment of model selection techniques and goodness of fit measures for deriving forest structural metrics of interest. For example, we obtained an R-squared value for aboveground biomass (Mg/ha) of 0.9 using stepwise regression. The forest metrics obtained are being used in the next stage of the project to parameterize biogeochemical models linking terrestrial carbon pools and atmospheric greenhouse gas exchanges.

Canopy rainfall partitioning across an urbanization gradient in forest structure as characterized by terrestrial LiDAR

NASA Astrophysics Data System (ADS)

Mesta, D. C.; Van Stan, J. T., II; Yankine, S. A.; Cote, J. F.; Jarvis, M. T.; Hildebrandt, A.; Friesen, J.; Maldonado, G.

2017-12-01

As urbanization expands, greater forest area is shifting from natural stand structures to urban stand structures, like forest fragments and landscaped tree rows. Changes in forest canopy structure have been found to drastically alter the amount of rainwater reaching the surface. However, stormwater management models generally treat all forest structures (beyond needle versus broadleaved) similarly. This study examines the rainfall partitioning of Pinus spp. canopies along a natural-to-urban forest gradient and compares these to canopy structural measurements using terrestrial LiDAR. Throughfall and meteorological observations were also used to estimate parameters of the commonly-used Gash interception model. Preliminary findings indicate that as forest structure changed from natural, closed canopy conditions to semi-closed canopy fragments and, ultimately, to exposed urban landscaping tree rows, the interchange between throughfall and rainfall interception also changed. This shift in partitioning between throughfall and rainfall interception may be linked to intuitive parameters, like canopy closure and density, as well as more complex metrics, like the fine-scale patterning of gaps (ie, lacunarity). Thus, results indicate that not all forests of the same species should be treated the same by stormwater models. Rather, their canopy structural characteristics should be used to vary their hydrometeorological interactions.

Headwater streams and forest management: does ecoregional context influence logging effects on benthic communities?

USGS Publications Warehouse

Medhurst, R. Bruce; Wipfli, Mark S.; Binckley, Chris; Polivka, Karl; Hessburg, Paul F.; Salter, R. Brion

2010-01-01

Effects of forest management on stream communities have been widely documented, but the role that climate plays in the disturbance outcomes is not understood. In order to determine whether the effect of disturbance from forest management on headwater stream communities varies by climate, we evaluated benthic macroinvertebrate communities in 24 headwater streams that differed in forest management (logged-roaded vs. unlogged-unroaded, hereafter logged and unlogged) within two ecological sub-regions (wet versus dry) within the eastern Cascade Range, Washington, USA. In both ecoregions, total macroinvertebrate density was highest at logged sites (P = 0.001) with gathering-collectors and shredders dominating. Total taxonomic richness and diversity did not differ between ecoregions or forest management types. Shredder densities were positively correlated with total deciduous and Sitka alder (Alnus sinuata) riparian cover. Further, differences in shredder density between logged and unlogged sites were greater in the wet ecoregion (logging × ecoregion interaction; P = 0.006) suggesting that differences in post-logging forest succession between ecoregions were responsible for differences in shredder abundance. Headwater stream benthic community structure was influenced by logging and regional differences in climate. Future development of ecoregional classification models at the subbasin scale, and use of functional metrics in addition to structural metrics, may allow for more accurate assessments of anthropogenic disturbances in mountainous regions where mosaics of localized differences in climate are common.

Assessing forest fragmentation metrics from forest inventory cluster samples

Treesearch

Christoph Kleinn

2000-01-01

Fragmentation of forest area plays an important role in the ongoing discussion of forest dynamics and biological and ecosystem diversity. Among its contributing factors are size, shape, number, and spatial arrangement of forest patches. Several metrics and indexes are in use, predominantly in quantitative landscape ecology. An important area of interest is the...

Forest Resources of the United States, 1997, METRIC UNITS.

Treesearch

W. Brad Smith; John S. Vissage; Davie R. Darr; Raymond M. Sheffield

2002-01-01

Forest resource statistics from the 1987 Forest Resources Planning Act (RPA) Asessment were updated to 1997 to provide current information on the Nation's forests. Resource tables present estimates in metric measure of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State.

Forest restoration: a global dataset for biodiversity and vegetation structure.

PubMed

Crouzeilles, Renato; Ferreira, Mariana S; Curran, Michael

2016-08-01

Restoration initiatives are becoming increasingly applied around the world. Billions of dollars have been spent on ecological restoration research and initiatives, but restoration outcomes differ widely among these initiatives in part due to variable socioeconomic and ecological contexts. Here, we present the most comprehensive dataset gathered to date on forest restoration. It encompasses 269 primary studies across 221 study landscapes in 53 countries and contains 4,645 quantitative comparisons between reference ecosystems (e.g., old-growth forest) and degraded or restored ecosystems for five taxonomic groups (mammals, birds, invertebrates, herpetofauna, and plants) and five measures of vegetation structure reflecting different ecological processes (cover, density, height, biomass, and litter). We selected studies that (1) were conducted in forest ecosystems; (2) had multiple replicate sampling sites to measure indicators of biodiversity and/or vegetation structure in reference and restored and/or degraded ecosystems; and (3) used less-disturbed forests as a reference to the ecosystem under study. We recorded (1) latitude and longitude; (2) study year; (3) country; (4) biogeographic realm; (5) past disturbance type; (6) current disturbance type; (7) forest conversion class; (8) restoration activity; (9) time that a system has been disturbed; (10) time elapsed since restoration started; (11) ecological metric used to assess biodiversity; and (12) quantitative value of the ecological metric of biodiversity and/or vegetation structure for reference and restored and/or degraded ecosystems. These were the most common data available in the selected studies. We also estimated forest cover and configuration in each study landscape using a recently developed 1 km consensus land cover dataset. We measured forest configuration as the (1) mean size of all forest patches; (2) size of the largest forest patch; and (3) edge:area ratio of forest patches. Global analyses of the factors influencing ecological restoration success at both the local and landscape scale are urgently needed to guide restoration initiatives and to further develop restoration knowledge in a topic area of much contemporary interest. © 2016 by the Ecological Society of America.

Water availability determines the richness and density of fig trees within Brazilian semideciduous forest landscapes

NASA Astrophysics Data System (ADS)

Coelho, Luís Francisco Mello; Ribeiro, Milton Cezar; Pereira, Rodrigo Augusto Santinelo

2014-05-01

The success of fig trees in tropical ecosystems is evidenced by the great diversity (+750 species) and wide geographic distribution of the genus. We assessed the contribution of environmental variables on the species richness and density of fig trees in fragments of seasonal semideciduous forest (SSF) in Brazil. We assessed 20 forest fragments in three regions in Sao Paulo State, Brazil. Fig tree richness and density was estimated in rectangular plots, comprising 31.4 ha sampled. Both richness and fig tree density were linearly modeled as function of variables representing (1) fragment metrics, (2) forest structure, and (3) landscape metrics expressing water drainage in the fragments. Model selection was performed by comparing the AIC values (Akaike Information Criterion) and the relative weight of each model (wAIC). Both species richness and fig tree density were better explained by the water availability in the fragment (meter of streams/ha): wAICrichness = 0.45, wAICdensity = 0.96. The remaining variables related to anthropic perturbation and forest structure were of little weight in the models. The rainfall seasonality in SSF seems to select for both establishment strategies and morphological adaptations in the hemiepiphytic fig tree species. In the studied SSF, hemiepiphytes established at lower heights in their host trees than reported for fig trees in evergreen rainforests. Some hemiepiphytic fig species evolved superficial roots extending up to 100 m from their trunks, resulting in hectare-scale root zones that allow them to efficiently forage water and soil nutrients. The community of fig trees was robust to variation in forest structure and conservation level of SSF fragments, making this group of plants an important element for the functioning of seasonal tropical forests.

Comparison of Hyperspectral and Multispectral Satellites for Forest Alliance Classification in the San Francisco Bay Area

NASA Astrophysics Data System (ADS)

Clark, M. L.

2016-12-01

The goal of this study was to assess multi-temporal, Hyperspectral Infrared Imager (HyspIRI) satellite imagery for improved forest class mapping relative to multispectral satellites. The study area was the western San Francisco Bay Area, California and forest alliances (e.g., forest communities defined by dominant or co-dominant trees) were defined using the U.S. National Vegetation Classification System. Simulated 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery were processed from image data acquired by NASA's AVIRIS airborne sensor in year 2015, with summer and multi-temporal (spring, summer, fall) data analyzed separately. HyspIRI reflectance was used to generate a suite of hyperspectral metrics that targeted key spectral features related to chemical and structural properties. The Random Forests classifier was applied to the simulated images and overall accuracies (OA) were compared to those from real Landsat 8 images. For each image group, broad land cover (e.g., Needle-leaf Trees, Broad-leaf Trees, Annual agriculture, Herbaceous, Built-up) was classified first, followed by a finer-detail forest alliance classification for pixels mapped as closed-canopy forest. There were 5 needle-leaf tree alliances and 16 broad-leaf tree alliances, including 7 Quercus (oak) alliance types. No forest alliance classification exceeded 50% OA, indicating that there was broad spectral similarity among alliances, most of which were not spectrally pure but rather a mix of tree species. In general, needle-leaf (Pine, Redwood, Douglas Fir) alliances had better class accuracies than broad-leaf alliances (Oaks, Madrone, Bay Laurel, Buckeye, etc). Multi-temporal data classifications all had 5-6% greater OA than with comparable summer data. For simulated data, HyspIRI metrics had 4-5% greater OA than Landsat 8 and Sentinel-2 multispectral imagery and 3-4% greater OA than HyspIRI reflectance. Finally, HyspIRI metrics had 8% greater OA than real Landsat 8 imagery. In conclusion, forest alliance classification was found to be a difficult remote sensing application with moderate resolution (30 m) satellite imagery; however, of the data tested, HyspIRI spectral metrics had the best performance relative to multispectral satellites.

Tropical forest heterogeneity from TanDEM-X InSAR and lidar observations in Indonesia

NASA Astrophysics Data System (ADS)

De Grandi, Elsa Carla; Mitchard, Edward

2016-10-01

Fires exacerbated during El Niño Southern Oscillation are a serious threat in Indonesia leading to the destruction and degradation of tropical forests and emissions of CO2 in the atmosphere. Forest structural changes which occurred due to the 1997-1998 El Niño Southern Oscillation in the Sungai Wain Protection Forest (East Kalimantan, Indonesia), a previously intact forest reserve have led to the development of a range of landcover from secondary forest to areas dominated by grassland. These structural differences can be appreciated over large areas by remote sensing instruments such as TanDEM-X and LiDAR that provide information that are sensitive to vegetation vertical and horizontal structure. One-point statistics of TanDEM-X coherence (mean and CV) and LiDAR CHM (mean, CV) and derived metrics such as vegetation volume and canopy cover were tested for the discrimination between 4 landcover classes. Jeffries-Matusita (JM) separability was high between forest classes (primary or secondary forest) and non-forest (grassland) while, primary and secondary forest were not separable. The study tests the potential and the importance of potential of TanDEM-X coherence and LiDAR observations to characterize structural heterogeneity based on one-point statistics in tropical forest but requires improved characterization using two-point statistical measures.

Classification of forest land attributes using multi-source remotely sensed data

NASA Astrophysics Data System (ADS)

Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

2016-02-01

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data

NASA Astrophysics Data System (ADS)

Cao, Lin; Coops, Nicholas C.; Innes, John L.; Dai, Jinsong; Ruan, Honghua; She, Guanghui

2016-07-01

The accurate classification of tree species is critical for the management of forest ecosystems, particularly subtropical forests, which are highly diverse and complex ecosystems. While airborne Light Detection and Ranging (LiDAR) technology offers significant potential to estimate forest structural attributes, the capacity of this new tool to classify species is less well known. In this research, full-waveform metrics were extracted by a voxel-based composite waveform approach and examined with a Random Forests classifier to discriminate six subtropical tree species (i.e., Masson pine (Pinus massoniana Lamb.)), Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), Slash pines (Pinus elliottii Engelm.), Sawtooth oak (Quercus acutissima Carruth.) and Chinese holly (Ilex chinensis Sims.) at three levels of discrimination. As part of the analysis, the optimal voxel size for modelling the composite waveforms was investigated, the most important predictor metrics for species classification assessed and the effect of scan angle on species discrimination examined. Results demonstrate that all tree species were classified with relatively high accuracy (68.6% for six classes, 75.8% for four main species and 86.2% for conifers and broadleaved trees). Full-waveform metrics (based on height of median energy, waveform distance and number of waveform peaks) demonstrated high classification importance and were stable among various voxel sizes. The results also suggest that the voxel based approach can alleviate some of the issues associated with large scan angles. In summary, the results indicate that full-waveform LIDAR data have significant potential for tree species classification in the subtropical forests.

Disentangling the drivers of taxonomic and phylogenetic beta diversities in disturbed and undisturbed subtropical forests

NASA Astrophysics Data System (ADS)

Liu, Jinliang; Qian, Hong; Jin, Yi; Wu, Chuping; Chen, Jianhua; Yu, Shuquan; Wei, Xinliang; Jin, Xiaofeng; Liu, Jiajia; Yu, Mingjian

2016-10-01

Understanding the relative importance of dispersal limitation and environmental filtering processes in structuring the beta diversities of subtropical forests in human disturbed landscapes is still limited. Here we used taxonomic (TBD) and phylogenetic (PBD), including terminal PBD (PBDt) and basal PBD (PBDb), beta diversity indices to quantify the taxonomic and phylogenetic turnovers at different depths of evolutionary history in disturbed and undisturbed subtropical forests. Multiple linear regression model and distance-based redundancy analysis were used to disentangle the relative importance of environmental and spatial variables. Environmental variables were significantly correlated with TBD and PBDt metrics. Temperature and precipitation were major environmental drivers of beta diversity patterns, which explained 7-27% of the variance in TBD and PBDt, whereas the spatial variables independently explained less than 1% of the variation for all forests. The relative importance of environmental and spatial variables differed between disturbed and undisturbed forests (e.g., when Bray-Curtis was used as a beta diversity metric, environmental variable had a significant effect on beta diversity for disturbed forests but had no effect on undisturbed forests). We conclude that environmental filtering plays a more important role than geographical limitation and disturbance history in driving taxonomic and terminal phylogenetic beta diversity.

Disentangling the drivers of taxonomic and phylogenetic beta diversities in disturbed and undisturbed subtropical forests

PubMed Central

Liu, Jinliang; Qian, Hong; Jin, Yi; Wu, Chuping; Chen, Jianhua; Yu, Shuquan; Wei, Xinliang; Jin, Xiaofeng; Liu, Jiajia; Yu, Mingjian

2016-01-01

Understanding the relative importance of dispersal limitation and environmental filtering processes in structuring the beta diversities of subtropical forests in human disturbed landscapes is still limited. Here we used taxonomic (TBD) and phylogenetic (PBD), including terminal PBD (PBDt) and basal PBD (PBDb), beta diversity indices to quantify the taxonomic and phylogenetic turnovers at different depths of evolutionary history in disturbed and undisturbed subtropical forests. Multiple linear regression model and distance-based redundancy analysis were used to disentangle the relative importance of environmental and spatial variables. Environmental variables were significantly correlated with TBD and PBDt metrics. Temperature and precipitation were major environmental drivers of beta diversity patterns, which explained 7–27% of the variance in TBD and PBDt, whereas the spatial variables independently explained less than 1% of the variation for all forests. The relative importance of environmental and spatial variables differed between disturbed and undisturbed forests (e.g., when Bray-Curtis was used as a beta diversity metric, environmental variable had a significant effect on beta diversity for disturbed forests but had no effect on undisturbed forests). We conclude that environmental filtering plays a more important role than geographical limitation and disturbance history in driving taxonomic and terminal phylogenetic beta diversity. PMID:27775021

Important LiDAR metrics for discriminating forest tree species in Central Europe

NASA Astrophysics Data System (ADS)

Shi, Yifang; Wang, Tiejun; Skidmore, Andrew K.; Heurich, Marco

2018-03-01

Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe.

A hierarchical approach to forest landscape pattern characterization.

PubMed

Wang, Jialing; Yang, Xiaojun

2012-01-01

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

An evaluation of ozone exposure metrics for a seasonally drought-stressed ponderosa pine ecosystem.

PubMed

Panek, Jeanne A; Kurpius, Meredith R; Goldstein, Allen H

2002-01-01

Ozone stress has become an increasingly significant factor in cases of forest decline reported throughout the world. Current metrics to estimate ozone exposure for forest trees are derived from atmospheric concentrations and assume that the forest is physiologically active at all times of the growing season. This may be inaccurate in regions with a Mediterranean climate, such as California and the Pacific Northwest, where peak physiological activity occurs early in the season to take advantage of high soil moisture and does not correspond to peak ozone concentrations. It may also misrepresent ecosystems experiencing non-average climate conditions such as drought years. We compared direct measurements of ozone flux into a ponderosa pine canopy with a suite of the most common ozone exposure metrics to determine which best correlated with actual ozone uptake by the forest. Of the metrics we assessed, SUM0 (the sum of all daytime ozone concentrations > 0) best corresponded to ozone uptake by ponderosa pine, however the correlation was only strong at times when the stomata were unconstrained by site moisture conditions. In the early growing season (May and June). SUM0 was an adequate metric for forest ozone exposure. Later in the season, when stomatal conductance was limited by drought. SUM0 overestimated ozone uptake. A better metric for seasonally drought-stressed forests would be one that incorporates forest physiological activity, either through mechanistic modeling, by weighting ozone concentrations by stomatal conductance, or by weighting concentrations by site moisture conditions.

Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics

DOE PAGES

Kelbe, David; Oak Ridge National Lab.; van Aardt, Jan; ...

2016-10-18

Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in ordermore » to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.« less

Mapping of past stand-level forest disturbances and estimation of time since disturbance using simulated spaceborne LiDAR data

NASA Astrophysics Data System (ADS)

Sanchez Lopez, N.; Hudak, A. T.; Boschetti, L.

2017-12-01

Explicit information on the location, the size or the time since disturbance (TSD) at the forest stand level complements field inventories, improves the monitoring of forest attributes and the estimation of biomass and carbon stocks. Even-aged stands display homogenous structural parameters that have often been used as a proxy of stand age. Consequently, performing object-oriented analysis on Light Detection and Ranging (LiDAR) data has potential to detect historical stand-replacing disturbances. Recent research has shown good results in the delineation of forest stands as well as in the prediction of disturbance occurrence and TSD using airborne LiDAR data. Nevertheless, the use of airborne LiDAR for systematic monitoring of forest stands is limited by the sporadic availability of data and its high cost compared to satellite instruments. NASA's forthcoming Global Ecosystem Dynamics Investigations (GEDI) mission will provide systematically data on the vertical structure of the vegetation, but its use presents some challenges compared to the common discrete-return airborne LiDAR. GEDI will be a waveform instrument, hence the summary metrics will be different to those obtained with airborne LiDAR, and the sampling configuration could limit the utility of the data, especially on heterogeneous landscapes. The potential use of GEDI data for forest characterization at the stand level would therefore depend on the predictive power of the GEDI footprint metrics, and on the density of point samples relative to forest stand size (i.e. the number of observation/footprints per stand).In this study, we assess the performance of simulated GEDI-derived metrics for stand characterization and estimation of TSD, and the point density needed to adequately identify forest stands, which translates - due to the fixed sampling configuration - into the minimum temporal interval needed to collect a sufficient number of points. The study area was located in the Clear Creek, Selway River, and Elk Creek watersheds ( 54,000 ha) within the Nez Perce-Clearwater National Forest in Idaho, where airborne LiDAR and reference maps on TSD were available. Simulated GEDI footprints and waveforms were obtained from airborne LiDAR point clouds and the results were compared to similar analysis performed with airborne LiDAR.

Canopy structural complexity as a continental predictor of primary production: Using NEON to transform understanding of forest structure-function

NASA Astrophysics Data System (ADS)

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

2016-12-01

Ecosystem structure-function relationships represent a long-standing research area for ecosystem science. Relationships between canopy structural complexity (CSC) and net primary productivity (NPP), have been characterized for a limited number of sites, yet whether these relationships are conserved across eco-climatic boundaries remains unknown. We hypothesize an underlying mechanistic basis for global NPP-CSC linkages to include improved resource-use efficiency as CSC increases, examined here by correlating CSC with measures of light-use efficiency and nitrogen-use efficiency. Here we present a broad, continental scale analysis of CSC-NPP linkages. We are using multiple NEON sites coupled with other sites across a diverse array of temperate forest types spanning six eco-climatic domains of the continental United States to examine CSC-NPP relationships. Portable canopy LiDAR (PCL) data were used to calculate a suite of CSC metrics at the plot-level within each site. Ongoing work compares CSC to co-located measurements of wood net primary production estimated from the incremental change in woody biomass calculated using tree allometries. Results to date show CSC is highly variable across forest sites and may provide additional explanatory power for predicting NPP that is independent of other commonly used forest structural attributes such as leaf area index. CSC metrics such as rugosity vary widely across sites—ranging from high values (30 - 35) in complex canopies such as the Great Smoky Mountains to low values in open, savanna systems like North-Central Florida (< 0.5 - 2). NPP, and light- and nitrogen-use calculations are underway and will be paired with site-level CSC, with the expectation that CSC, resource-use efficiency, and NPP are positively correlated. Advancing understanding of how and why CSC affects forest NPP across a broad spatial dimension could transform mechanistic understanding of ecosystem structure-carbon cycling relationships, and greatly improve carbon cycling models and remote sensing applications, while providing a crucial linkage between the two.

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

PubMed Central

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

2004-01-01

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

AN EVALUATION OF OZONE EXPOSURE METRICS FOR A SEASONALLY DROUGHT STRESSED PONDEROSA PINE ECOSYSTEM. (R826601)

EPA Science Inventory

Ozone stress has become an increasingly significant factor in cases of forest decline reported throughout the world. Current metrics to estimate ozone exposure for forest trees are derived from atmospheric concentrations and assume that the forest is physiologically active at ...

LINKING IN SITU TIME SERIES FOREST CANOPY LAI AND PHENOLOGY METRICS WITH MODIS AND LANDSAT NDVI AND LAI PRODUCTS

EPA Science Inventory

The subject of this presentation is forest vegetation dynamics as observed by the TERRA spacecraft's Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper, and complimentary in situ time series measurements of forest canopy metrics related to Leaf Area...

Vegetation succession among and within structural layers following wildfire in managed forests

Treesearch

Lori J. Kayes; Paul D. Anderson; Klaus J. Puettmann

2010-01-01

In severely burned plantations, dynamics of (1) shrub, herbaceous, and cryptogam richness; (2) cover; (3) topographic, overstory, and site influences were characterized on two contrasting aspects 2 to 4 years following fire. Analysis of variance was used to examine change in structural layer richness and cover over time. Non-metric multidimensional scaling, multi-...

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.

Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

NASA Astrophysics Data System (ADS)

Safari, A.; Sohrabi, H.

2016-06-01

The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics were able to explain about half of the variation in aboveground carbon stocks. These results demonstrated that Landsat 8 derived texture metrics can be applied for mapping aboveground carbon stocks of coppice Oak Forests in large areas.

Agro-forest landscape and the 'fringe' city: a multivariate assessment of land-use changes in a sprawling region and implications for planning.

PubMed

Salvati, Luca

2014-08-15

The present study evaluates the impact of urban expansion on landscape transformations in Rome's metropolitan area (1500 km(2)) during the last sixty years. Landscape composition, structure and dynamics were assessed for 1949 and 2008 by analyzing the distribution of 26 metrics for nine land-use classes. Changes in landscape structure are analysed by way of a multivariate statistical approach providing a summary measure of rapidity-to-change for each metric and class. Land fragmentation increased during the study period due to urban expansion. Poorly protected or medium-low value added classes (vineyards, arable land, olive groves and pastures) experienced fragmentation processes compared with protected or high-value added classes (e.g. forests, olive groves) showing larger 'core' areas and lower fragmentation. The relationship observed between class area and mean patch size indicates increased fragmentation for all uses of land (both expanding and declining) except for urban areas and forests. Reducing the impact of urban expansion for specific land-use classes is an effective planning strategy to contrast the simplification of Mediterranean landscape in peri-urban areas. Copyright © 2014 Elsevier B.V. All rights reserved.

Forest statistics of the United States, 1992 metric units.

Treesearch

W. Brad Smith; Joanne L. Faulkner; Douglas S. Powell

1994-01-01

The 1987 Resources Planning Act (RPA) Assessment was conducted to provide current information on the nation's forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or state. Statistics are provided in a metric format for international use.

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the potential to improve forest AGB accounting certainty and provide maps for post-model fitting analysis of the spatial distribution of AGB.

Mapping of land cover in northern California with simulated hyperspectral satellite imagery

NASA Astrophysics Data System (ADS)

Clark, Matthew L.; Kilham, Nina E.

2016-09-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands, woodlands and mixed forests from the classification. This 12-class map had significantly improved accuracy of 85.1% (Kappa 0.83) and most classes had over 70% producer and user accuracies. Finally, we summarized important metrics from the multi-temporal Random Forests to infer the underlying chemical and structural properties that best discriminated our land-cover classes across seasons.

Assessing biomass accumulation in second growth forests of Puerto Rico using airborne lidar

NASA Astrophysics Data System (ADS)

Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.

2017-12-01

Degraded and second growth tropical forests provide important ecosystem services, such as carbon sequestration and soil stabilization. Lidar data measure the three-dimensional structure of forest canopies and are commonly used to quantify aboveground biomass in temperate forest landscapes. However, the ability of lidar data to quantify second growth forest biomass in complex, tropical landscapes is less understood. Our goal was to evaluate the use of airborne lidar data to quantify aboveground biomass in a complex tropical landscape, the Caribbean island of Puerto Rico. Puerto Rico provides an ideal place for studying biomass accumulation because of the abundance of second growth forests in different stages of recovery, and the high ecological heterogeneity. Puerto Rico was almost entirely deforested for agriculture until the 1930s. Thereafter, agricultural abandonment resulted in a mosaic of second growth forests that have recovered naturally under different types of climate, land use, topography, and soil fertility. We integrated forest plot data from the US Forest Service, Forest Inventory and Analysis (FIA) Program with recent lidar data from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) airborne imager to quantify forest biomass across the island's landscape. The G-LiHT data consisted on targeted acquisitions over the FIA plots and other forested areas representing the environmental heterogeneity of the island. To fully assess the potential of the lidar data, we compared the ability of lidar-derived canopy metrics to quantify biomass alone, and in combination with intensity and topographic metrics. The results presented here are a key step for improving our understanding of the patterns and drivers of biomass accumulation in tropical forests.

Relating forest attributes with area- and tree-based light detection and ranging metrics for western Oregon

Treesearch

Michael E. Goerndt; Vincente J. Monleon; Hailemariam. Temesgen

2010-01-01

Three sets of linear models were developed to predict several forest attributes, using stand-level and single-tree remote sensing (STRS) light detection and ranging (LiDAR) metrics as predictor variables. The first used only area-level metrics (ALM) associated with first-return height distribution, percentage of cover, and canopy transparency. The second alternative...

A cross-comparison of field, spectral, and lidar estimates of forest canopy cover

Treesearch

Alistair M. S. Smith; Michael J. Falkowski; Andrew T. Hudak; Jeffrey S. Evans; Andrew P. Robinson; Caiti M. Steele

2010-01-01

A common challenge when comparing forest canopy cover and similar metrics across different ecosystems is that there are many field- and landscape-level measurement methods. This research conducts a cross-comparison and evaluation of forest canopy cover metrics produced using unmixing of reflective spectral satellite data, light detection and ranging (lidar) data, and...

Using Lidar and Radar measurements to constrain predictions of forest ecosystem structure and function.

PubMed

Antonarakis, Alexander S; Saatchi, Sassan S; Chazdon, Robin L; Moorcroft, Paul R

2011-06-01

Insights into vegetation and aboveground biomass dynamics within terrestrial ecosystems have come almost exclusively from ground-based forest inventories that are limited in their spatial extent. Lidar and synthetic-aperture Radar are promising remote-sensing-based techniques for obtaining comprehensive measurements of forest structure at regional to global scales. In this study we investigate how Lidar-derived forest heights and Radar-derived aboveground biomass can be used to constrain the dynamics of the ED2 terrestrial biosphere model. Four-year simulations initialized with Lidar and Radar structure variables were compared against simulations initialized from forest-inventory data and output from a long-term potential-vegtation simulation. Both height and biomass initializations from Lidar and Radar measurements significantly improved the representation of forest structure within the model, eliminating the bias of too many large trees that arose in the potential-vegtation-initialized simulation. The Lidar and Radar initializations decreased the proportion of larger trees estimated by the potential vegetation by approximately 20-30%, matching the forest inventory. This resulted in improved predictions of ecosystem-scale carbon fluxes and structural dynamics compared to predictions from the potential-vegtation simulation. The Radar initialization produced biomass values that were 75% closer to the forest inventory, with Lidar initializations producing canopy height values closest to the forest inventory. Net primary production values for the Radar and Lidar initializations were around 6-8% closer to the forest inventory. Correcting the Lidar and Radar initializations for forest composition resulted in improved biomass and basal-area dynamics as well as leaf-area index. Correcting the Lidar and Radar initializations for forest composition and fine-scale structure by combining the remote-sensing measurements with ground-based inventory data further improved predictions, suggesting that further improvements of structural and carbon-flux metrics will also depend on obtaining reliable estimates of forest composition and accurate representation of the fine-scale vertical and horizontal structure of plant canopies.

Quantifying forest fragmentation using Geographic Information Systems and Forest Inventory and Analysis plot data

Treesearch

Dacia M. Meneguzzo; Mark H. Hansen

2009-01-01

Fragmentation metrics provide a means of quantifying and describing forest fragmentation. The most common method of calculating these metrics is through the use of Geographic Information System software to analyze raster data, such as a satellite or aerial image of the study area; however, the spatial resolution of the imagery has a significant impact on the results....

Little effects of reduced-impact logging on insect communities in eastern Amazonia.

PubMed

Nogueira, Denis Silva; Calvão, Lenize Batista; de Assis Montag, Luciano Fogaça; Juen, Leandro; De Marco, Paulo

2016-07-01

Selective logging has become a major source of threats to tropical forest, bringing challenges for both ecologists and managers to develop low-impact forestry. Reduced-impact logging (RIL) is a prominent activity accounting for such forestry practices to prevent strong forest disturbances. Our aims were to evaluate the effects of RIL on insect communities of forested streams from Eastern Amazon and to test the hypothesis of negative effects of RIL on species richness, abundance, and functional feeding groups of aquatic insect assemblages. Neither of the evaluated metrics of the studied assemblages were negatively affected by RIL. Environmental metrics, such as substrate heterogeneity, woody canopy cover, and hill slope height, varied more among RIL streams than in reference streams, indicating a gradient according to logging impacts, and are suitable candidates to monitor RIL impacts in Amazonian streams. In addition, the PHI index also varied among REF and RIL, according to age class and year of logging, which could reflect trends to recover the forest structure after logging in a time frame of only 10 years. We conclude that RIL impacts have not had detrimental impacts on insect communities, but have changed little of the environmental conditions, especially of the riparian vegetation around streams.

Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China

NASA Astrophysics Data System (ADS)

Wu, Hao; Ye, Lu-Ping; Shi, Wen-Zhong; Clarke, Keith C.

2014-10-01

Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.

A tool for assessing ecological status of forest ecosystem

NASA Astrophysics Data System (ADS)

Rahman Kassim, Abd; Afizzul Misman, Muhammad; Azahari Faidi, Mohd; Omar, Hamdan

2016-06-01

Managers and policy makers are beginning to appreciate the value of ecological monitoring of artificially regenerated forest especially in urban areas. With the advent of more advance technology in precision forestry, high resolution remotely sensed data e.g. hyperspectral and LiDAR are becoming available for rapid and precise assessment of the forest condition. An assessment of ecological status of forest ecosystem was developed and tested using FRIM campus forest stand. The forest consisted of three major blocks; the old growth artificially regenerated native species forests, naturally regenerated forest and recent planted forest for commercial timber and other forest products. Our aim is to assess the ecological status and its proximity to the mature old growth artificially regenerated stand. We used airborne LiDAR, orthophoto and thirty field sampling quadrats of 20x20m for ground verification. The parameter assessments were grouped into four broad categories: a. forest community level-composition, structures, function; landscape structures-road network and forest edges. A metric of parameters and rating criteria was introduced as indicators of the forest ecological status. We applied multi-criteria assessment to categorize the ecological status of the forest stand. The paper demonstrates the application of the assessment approach using FRIM campus forest as its first case study. Its potential application to both artificially and naturally regenerated forest in the variety of Malaysian landscape is discussed

Single tree biomass modelling using airborne laser scanning

NASA Astrophysics Data System (ADS)

Kankare, Ville; Räty, Minna; Yu, Xiaowei; Holopainen, Markus; Vastaranta, Mikko; Kantola, Tuula; Hyyppä, Juha; Hyyppä, Hannu; Alho, Petteri; Viitala, Risto

2013-11-01

Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately 10 pulses/m2. Linear models were developed for the following tree biomass components: total, stem wood, living branch and total canopy biomass. ALS-derived geometric and statistical point metrics were used as explanatory variables when creating the models. The total and stem biomass root mean square error per cents equalled 26.3% and 28.4% for Scots pine (Pinus sylvestris L.), and 36.8% and 27.6% for Norway spruce (Picea abies (L.) H. Karst.), respectively. The results showed that higher estimation accuracy for all biomass components can be achieved with models created in this study compared to existing allometric biomass models when ALS-derived height and diameter were used as input parameters. Best results were achieved when adding field-measured diameter and height as inputs in the existing biomass models. The only exceptions to this were the canopy and living branch biomass estimations for spruce. The achieved results are encouraging for the use of ALS-derived metrics in biomass mapping and for further development of the models.

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

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

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

DOE PAGES

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; ...

2016-04-04

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

The influence of soil properties and nutrients on conifer forest growth in Sweden, and the first steps in developing a nutrient availability metric

NASA Astrophysics Data System (ADS)

Van Sundert, Kevin; Horemans, Joanna A.; Stendahl, Johan; Vicca, Sara

2018-06-01

The availability of nutrients is one of the factors that regulate terrestrial carbon cycling and modify ecosystem responses to environmental changes. Nonetheless, nutrient availability is often overlooked in climate-carbon cycle studies because it depends on the interplay of various soil factors that would ideally be comprised into metrics applicable at large spatial scales. Such metrics do not currently exist. Here, we use a Swedish forest inventory database that contains soil data and tree growth data for > 2500 forests across Sweden to (i) test which combination of soil factors best explains variation in tree growth, (ii) evaluate an existing metric of constraints on nutrient availability, and (iii) adjust this metric for boreal forest data. With (iii), we thus aimed to provide an adjustable nutrient metric, applicable for Sweden and with potential for elaboration to other regions. While taking into account confounding factors such as climate, N deposition, and soil oxygen availability, our analyses revealed that the soil organic carbon concentration (SOC) and the ratio of soil carbon to nitrogen (C : N) were the most important factors explaining variation in normalized (climate-independent) productivity (mean annual volume increment - m3 ha-1 yr-1) across Sweden. Normalized forest productivity was significantly negatively related to the soil C : N ratio (R2 = 0.02-0.13), while SOC exhibited an empirical optimum (R2 = 0.05-0.15). For the metric, we started from a (yet unvalidated) metric for constraints on nutrient availability that was previously developed by the International Institute for Applied Systems Analysis (IIASA - Laxenburg, Austria) for evaluating potential productivity of arable land. This IIASA metric requires information on soil properties that are indicative of nutrient availability (SOC, soil texture, total exchangeable bases - TEB, and pH) and is based on theoretical considerations that are also generally valid for nonagricultural ecosystems. However, the IIASA metric was unrelated to normalized forest productivity across Sweden (R2 = 0.00-0.01) because the soil factors under consideration were not optimally implemented according to the Swedish data, and because the soil C : N ratio was not included. Using two methods (each one based on a different way of normalizing productivity for climate), we adjusted this metric by incorporating soil C : N and modifying the relationship between SOC and nutrient availability in view of the observed relationships across our database. In contrast to the IIASA metric, the adjusted metrics explained some variation in normalized productivity in the database (R2 = 0.03-0.21; depending on the applied method). A test for five manually selected local fertility gradients in our database revealed a significant and stronger relationship between the adjusted metrics and productivity for each of the gradients (R2 = 0.09-0.38). This study thus shows for the first time how nutrient availability metrics can be evaluated and adjusted for a particular ecosystem type, using a large-scale database.

Large-scale distribution patterns of mangrove nematodes: A global meta-analysis.

PubMed

Brustolin, Marco C; Nagelkerken, Ivan; Fonseca, Gustavo

2018-05-01

Mangroves harbor diverse invertebrate communities, suggesting that macroecological distribution patterns of habitat-forming foundation species drive the associated faunal distribution. Whether these are driven by mangrove biogeography is still ambiguous. For small-bodied taxa, local factors and landscape metrics might be as important as macroecology. We performed a meta-analysis to address the following questions: (1) can richness of mangrove trees explain macroecological patterns of nematode richness? and (2) do local landscape attributes have equal or higher importance than biogeography in structuring nematode richness? Mangrove areas of Caribbean-Southwest Atlantic, Western Indian, Central Indo-Pacific, and Southwest Pacific biogeographic regions. We used random-effects meta-analyses based on natural logarithm of the response ratio (lnRR) to assess the importance of macroecology (i.e., biogeographic regions, latitude, longitude), local factors (i.e., aboveground mangrove biomass and tree richness), and landscape metrics (forest area and shape) in structuring nematode richness from 34 mangroves sites around the world. Latitude, mangrove forest area, and forest shape index explained 19% of the heterogeneity across studies. Richness was higher at low latitudes, closer to the equator. At local scales, richness increased slightly with landscape complexity and decreased with forest shape index. Our results contrast with biogeographic diversity patterns of mangrove-associated taxa. Global-scale nematode diversity may have evolved independently of mangrove tree richness, and diversity of small-bodied metazoans is probably more closely driven by latitude and associated climates, rather than local, landscape, or global biogeographic patterns.

Tree growth and competition in an old-growth Picea abies forest of boreal Sweden: influence of tree spatial patterning

USGS Publications Warehouse

Fraver, Shawn; D'Amato, Anthony W.; Bradford, John B.; Jonsson, Bengt Gunnar; Jönsson, Mari; Esseen, Per-Anders

2013-01-01

Question: What factors best characterize tree competitive environments in this structurally diverse old-growth forest, and do these factors vary spatially within and among stands? Location: Old-growth Picea abies forest of boreal Sweden. Methods: Using long-term, mapped permanent plot data augmented with dendrochronological analyses, we evaluated the effect of neighbourhood competition on focal tree growth by means of standard competition indices, each modified to include various metrics of trees size, neighbour mortality weighting (for neighbours that died during the inventory period), and within-neighbourhood tree clustering. Candidate models were evaluated using mixed-model linear regression analyses, with mean basal area increment as the response variable. We then analysed stand-level spatial patterns of competition indices and growth rates (via kriging) to determine if the relationship between these patterns could further elucidate factors influencing tree growth. Results: Inter-tree competition clearly affected growth rates, with crown volume being the size metric most strongly influencing the neighbourhood competitive environment. Including neighbour tree mortality weightings in models only slightly improved descriptions of competitive interactions. Although the within-neighbourhood clustering index did not improve model predictions, competition intensity was influenced by the underlying stand-level tree spatial arrangement: stand-level clustering locally intensified competition and reduced tree growth, whereas in the absence of such clustering, inter-tree competition played a lesser role in constraining tree growth. Conclusions: Our findings demonstrate that competition continues to influence forest processes and structures in an old-growth system that has not experienced major disturbances for at least two centuries. The finding that the underlying tree spatial pattern influenced the competitive environment suggests caution in interpreting traditional tree competition studies, in which tree spatial patterning is typically not taken into account. Our findings highlight the importance of forest structure – particularly the spatial arrangement of trees – in regulating inter-tree competition and growth in structurally diverse forests, and they provide insight into the causes and consequences of heterogeneity in this old-growth system.

Analysis on Difference of Forest Phenology Extracted from EVI and LAI Based on PhenoCams

NASA Astrophysics Data System (ADS)

Wang, C.; Jing, L.; Qinhuo, L.

2017-12-01

Land surface phenology can make up for the deficiency of field observation with advantages of capturing the continuous expression of phenology on a large scale. However, there are some variability in phenological metrics derived from different satellite time-series data of vegetation parameters. This paper aims at assessing the difference of phenology information extracted from EVI and LAI time series. To achieve this, some web-camera sites were selected to analyze the characteristics between MODIS-EVI and MODIS-LAI time series from 2010 to 2014 for different forest types, including evergreen coniferous forest, evergreen broadleaf forest, deciduous coniferous forest and deciduous broadleaf forest. At the same time, satellite-based phenological metrics were extracted by the Logistics algorithm and compared with camera-based phenological metrics. Results show that the SOS and EOS that are extracted from LAI are close to bud burst and leaf defoliation respectively, while the SOS and EOS that are extracted from EVI is close to leaf unfolding and leaf coloring respectively. Thus the SOS that is extracted from LAI is earlier than that from EVI, while the EOS that is extracted from LAI is later than that from EVI at deciduous forest sites. Although the seasonal variation characteristics of evergreen forests are not apparent, significant discrepancies exist in LAI time series and EVI time series. In addition, Satellite- and camera-based phenological metrics agree well generally, but EVI has higher correlation with the camera-based canopy greenness (green chromatic coordinate, gcc) than LAI.

Changes in ground beetle diversity and community composition in age structured forests (Coleoptera, Carabidae).

PubMed

Riley, Kathryn N; Browne, Robert A

2011-01-01

We examined diversity, community composition, and wing-state of Carabidae as a function of forest age in Piedmont North Carolina. Carabidae were collected monthly from 396 pitfall traps (12×33 sites) from March 2009 through February 2010, representing 5 forest age classes approximately 0, 10, 50, 85, and 150 years old. A total of 2,568 individuals, representing 30 genera and 63 species, were collected. Carabid species diversity, as estimated by six diversity indices, was significantly different between the oldest and youngest forest age classes for four of the six indices. Most carabid species were habitat generalists, occurring in all or most of the forest age classes. Carabid species composition varied across forest age classes. Seventeen carabid species were identified as potential candidates for ecological indicators of forest age. Non-metric multidimensional scaling (NMDS) showed separation among forest age classes in terms of carabid beetle community composition. The proportion of individuals capable of flight decreased significantly with forest age.

Changes in ground beetle diversity and community composition in age structured forests (Coleoptera, Carabidae)

PubMed Central

Riley, Kathryn N.; Browne, Robert A.

2011-01-01

Abstract We examined diversity, community composition, and wing-state of Carabidae as a function of forest age in Piedmont North Carolina. Carabidae were collected monthly from 396 pitfall traps (12×33 sites) from March 2009 through February 2010, representing 5 forest age classes approximately 0, 10, 50, 85, and 150 years old. A total of 2,568 individuals, representing 30 genera and 63 species, were collected. Carabid species diversity, as estimated by six diversity indices, was significantly different between the oldest and youngest forest age classes for four of the six indices. Most carabid species were habitat generalists, occurring in all or most of the forest age classes. Carabid species composition varied across forest age classes. Seventeen carabid species were identified as potential candidates for ecological indicators of forest age. Non-metric multidimensional scaling (NMDS) showed separation among forest age classes in terms of carabid beetle community composition. The proportion of individuals capable of flight decreased significantly with forest age. PMID:22371677

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.

Regional variation in epiphytic macrolichen communities in northern and central California forests

Treesearch

Sarah Jovan; Bruce McCune

2004-01-01

We studied epiphytic macrolichen communities in northern and central California to 1) describe how gradients in community composition relate to climate, topography, and stand structure and 2) define subregions of relatively homogeneous lichen communities and environmental conditions. Non-metric multidimensional scaling was used to characterize landscape-level trends in...

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

NASA Astrophysics Data System (ADS)

Chu, H.; Baldocchi, D. D.

2017-12-01

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

Using avian functional traits to assess the impact of land-cover change on ecosystem processes linked to resilience in tropical forests.

PubMed

Bregman, Tom P; Lees, Alexander C; MacGregor, Hannah E A; Darski, Bianca; de Moura, Nárgila G; Aleixo, Alexandre; Barlow, Jos; Tobias, Joseph A

2016-12-14

Vertebrates perform key roles in ecosystem processes via trophic interactions with plants and insects, but the response of these interactions to environmental change is difficult to quantify in complex systems, such as tropical forests. Here, we use the functional trait structure of Amazonian forest bird assemblages to explore the impacts of land-cover change on two ecosystem processes: seed dispersal and insect predation. We show that trait structure in assemblages of frugivorous and insectivorous birds remained stable after primary forests were subjected to logging and fire events, but that further intensification of human land use substantially reduced the functional diversity and dispersion of traits, and resulted in communities that occupied a different region of trait space. These effects were only partially reversed in regenerating secondary forests. Our findings suggest that local extinctions caused by the loss and degradation of tropical forest are non-random with respect to functional traits, thus disrupting the network of trophic interactions regulating seed dispersal by forest birds and herbivory by insects, with important implications for the structure and resilience of human-modified tropical forests. Furthermore, our results illustrate how quantitative functional traits for specific guilds can provide a range of metrics for estimating the contribution of biodiversity to ecosystem processes, and the response of such processes to land-cover change. © 2016 The Author(s).

Using avian functional traits to assess the impact of land-cover change on ecosystem processes linked to resilience in tropical forests

PubMed Central

Bregman, Tom P.; Lees, Alexander C.; MacGregor, Hannah E. A.; Darski, Bianca; de Moura, Nárgila G.; Aleixo, Alexandre; Barlow, Jos

2016-01-01

Vertebrates perform key roles in ecosystem processes via trophic interactions with plants and insects, but the response of these interactions to environmental change is difficult to quantify in complex systems, such as tropical forests. Here, we use the functional trait structure of Amazonian forest bird assemblages to explore the impacts of land-cover change on two ecosystem processes: seed dispersal and insect predation. We show that trait structure in assemblages of frugivorous and insectivorous birds remained stable after primary forests were subjected to logging and fire events, but that further intensification of human land use substantially reduced the functional diversity and dispersion of traits, and resulted in communities that occupied a different region of trait space. These effects were only partially reversed in regenerating secondary forests. Our findings suggest that local extinctions caused by the loss and degradation of tropical forest are non-random with respect to functional traits, thus disrupting the network of trophic interactions regulating seed dispersal by forest birds and herbivory by insects, with important implications for the structure and resilience of human-modified tropical forests. Furthermore, our results illustrate how quantitative functional traits for specific guilds can provide a range of metrics for estimating the contribution of biodiversity to ecosystem processes, and the response of such processes to land-cover change. PMID:27928045

Spatial conservation planning framework for assessing conservation opportunities in the Atlantic Forest of Brazil

PubMed Central

Giorgi, Ana Paula; Rovzar, Corey; Davis, Kelsey S.; Fuller, Trevon; Buermann, Wolfgang; Saatchi, Sassan; Smith, Thomas B.; Silveira, Luis Fabio; Gillespie, Thomas W.

2017-01-01

Historic rates of habitat change and growing exploitation of natural resources threaten avian biodiversity in the Brazilian Atlantic Forest, a global biodiversity hotspot. We implemented a twostage framework for conservation planning in the Atlantic Forest. First, we used ecological niche modeling to predict the distributions of 23 endemic bird species using 19 climatic metrics and 12 spectral and radar remote sensing metrics. Second, we utilized the principle of complementarity to prioritize new sites to augment the Atlantic Forest's existing reserves. The best predictors of bird distributions were precipitation metrics (the seasonality of rainfall) and radar remote sensing metrics (QSCAT). The existing protected areas do not include 10% of the habitat of each of the 23 endemic species. We propose a more economical set of protected areas by reducing the extent to which new sites duplicate the biodiversity content of existing protected areas. There is a high concordance between the proposed conservation areas that we designed using computerized algorithms and Important Bird Areas prioritized by BirdLife International. Insofar as deforestation in the Atlantic Forest is similar to land conversion in other biodiversity hotspots, our methodology is applicable to conservation efforts elsewhere in the world. PMID:28210009

EVALUATION OF METRIC PRECISION FOR A RIPARIAN FOREST SURVEY

EPA Science Inventory

This paper evaluates the performance of a protocol to monitor riparian forests in western Oregon based on the quality of the data obtained from a recent field survey. Precision and accuracy are the criteria used to determine the quality of 19 field metrics. The field survey con...

Examining the sensitivity of modelled evapotranspiration to vegetation structural characteristics within boreal peatlands, riparian ecosystems and upland mixedwood forest

NASA Astrophysics Data System (ADS)

Petrone, R. M.; Chasmer, L. E.; Brown, S. M.; Mendoza, C. A.; Diiwu, J.; Quinton, W. L.; Hopkinson, C.; Devito, K. J.

2010-12-01

The Western Boreal Plain (WBP) of northern Alberta is comprised of a complex mosaic of small ponds, riparian buffer zones, and upland aspen dominated mixedwood forests surrounded by low-lying peatlands. The hydrology of the WBP is strongly influenced by climatic drivers and geology, whereby water budgets are often controlled by vertical fluxes. During most years, potential evapotranspiration (PET) exceeds precipitation (P), and changes in P as a result of climatic change will likely alter actual evapotranspiration (AET) and regional water balances. In recent years, the WBP has also undergone intense anthropogenic disturbance via oil and gas exploration and extraction, and silvicultural and forest harvesting activities. The extent to which changes in land cover types/characteristics affect estimates of PET and AET is currently unknown. This study examines the sensitivity of PET using a simple estimate of equilibrium ET (Priestley-Taylor) and AET (Penman-Monteith variant) to variability in canopy structural and ground surface characteristics at 12 sites throughout the 2008 growing season (June, July, August). Energy balance meteorological stations are deployed within four peatland ecosystems, four riparian buffer zones, two regenerating upland mixedwood forests and two mature upland mixedwood forests. Airborne Light Detection and Ranging (LiDAR) is used to derive metrics of canopy height, leaf area index (LAI), uplands and lowlands, elevation, zero plane displacement, roughness length governing momentum, roughness length governing heat and vapour, and understory vegetation characteristics. LiDAR land surface metrics and energy balance measurements are used to model evapotranspiration for classified land cover types throughout the larger basin. Sensitivity of potential and actual estimates to changes in land cover characteristics within each of the three land cover types (peatland, riparian and upland) is quantified.

Relationships between avian richness and landscape structure at multiple scales using multiple landscapes

USGS Publications Warehouse

Mitchell, M.S.; Rutzmoser, S.H.; Wigley, T.B.; Loehle, C.; Gerwin, J.A.; Keyser, P.D.; Lancia, R.A.; Perry, R.W.; Reynolds, C.J.; Thill, R.E.; Weih, R.; White, D.; Wood, P.B.

2006-01-01

Little is known about factors that structure biodiversity on landscape scales, yet current land management protocols, such as forest certification programs, place an increasing emphasis on managing for sustainable biodiversity at landscape scales. We used a replicated landscape study to evaluate relationships between forest structure and avian diversity at both stand and landscape-levels. We used data on bird communities collected under comparable sampling protocols on four managed forests located across the Southeastern US to develop logistic regression models describing relationships between habitat factors and the distribution of overall richness and richness of selected guilds. Landscape models generated for eight of nine guilds showed a strong relationship between richness and both availability and configuration of landscape features. Diversity of topographic features and heterogeneity of forest structure were primary determinants of avian species richness. Forest heterogeneity, in both age and forest type, were strongly and positively associated with overall avian richness and richness for most guilds. Road density was associated positively but weakly with avian richness. Landscape variables dominated all models generated, but no consistent patterns in metrics or scale were evident. Model fit was strong for neotropical migrants and relatively weak for short-distance migrants and resident species. Our models provide a tool that will allow managers to evaluate and demonstrate quantitatively how management practices affect avian diversity on landscapes.

Characterizing Exterior and Interior Tropical Forest Structure Variability with Full-Waveform Airborne LIDAR Data in Lopé, Gabon

NASA Astrophysics Data System (ADS)

Marselis, S.; Tang, H.; Blair, J. B.; Hofton, M. A.; Armston, J.; Dubayah, R.

2017-12-01

Terrestrial ecotones, transition zones between ecological systems, have been identified as important regions to monitor the effects of environmental and human pressures on ecosystems. To observe such changes, the variability in vegetation horizontal and vertical structure must be characterized. The objective of this study is to quantify changes in vegetation structure in a tropical forest-savanna mosaic using airborne waveform lidar data. The study area is located in the northern part of the Lopé National Park in Gabon and is comprised of the vegetation types: savanna, colonizing forest, monodominant Okoumé forest, young Marantaceae forest and mixed Marantaceae forest. The lidar data were collected by the Land Vegetation and Ice Sensor (LVIS) in early March 2016, during the AfriSAR campaign. Metrics derived from the LVIS waveforms were then used to classify the five main vegetation types and characterize observed structural variability within types and across ecotones. Several supervised and unsupervised classification alogrithms, in combination with statistical analysis, were applied. The investigated methods are promising in their use to directly describe the structural variability within and between different vegetation types, map these vegetation types and the extent and location of their transition zones, and to characterize, among other attributes, the sharpness and width of such ecotones. These results provide important information in ecosystem studies as these methods can be used to study changes in vegetation structure, species-specific habitat, or the effects of deforestation and other human and natural pressures on the exterior and interior forest structure. These methods thus provide ample opportunity to assess the vegetation structure in degraded and second growth tropical forests to explore effects of e.g. grazing, logging or fragmentation. From this study we can conclude that lidar waveform remote sensing is highly useful in distinguishing vegetation types and their transition zones which will be increasingly important when assessing the impact of natural and human pressures on the world's tropical forests.

Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests

NASA Technical Reports Server (NTRS)

Peduzzi, Alicia; Wynne, Randolph Hamilton; Thomas, Valerie A.; Nelson, Ross F.; Reis, James J.; Sanford, Mark

2012-01-01

The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR) alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood; stand age ranging from 12-164 years; mean height ranging from 0.4 to 41.2 m) in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric), five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks) as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R2 to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors), when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.

Characterizing the forest fragmentation of Canada's national parks.

PubMed

Soverel, Nicholas O; Coops, Nicholas C; White, Joanne C; Wulder, Michael A

2010-05-01

Characterizing the amount and configuration of forests can provide insights into habitat quality, biodiversity, and land use. The establishment of protected areas can be a mechanism for maintaining large, contiguous areas of forests, and the loss and fragmentation of forest habitat is a potential threat to Canada's national park system. Using the Earth Observation for Sustainable Development of Forests (EOSD) land cover product (EOSD LC 2000), we characterize the circa 2000 forest patterns in 26 of Canada's national parks and compare these to forest patterns in the ecological units surrounding these parks, referred to as the greater park ecosystem (GPE). Five landscape pattern metrics were analyzed: number of forest patches, mean forest patch size (hectare), standard deviation of forest patch size (hectare), mean forest patch perimeter-to-area ratio (meters per hectare), and edge density of forest patches (meters per hectare). An assumption is often made that forests within park boundaries are less fragmented than the surrounding GPE, as indicated by fewer forest patches, a larger mean forest patch size, less variability in forest patch size, a lower perimeter-to-area ratio, and lower forest edge density. Of the 26 national parks we analyzed, 58% had significantly fewer patches, 46% had a significantly larger mean forest patch size (23% were not significantly different), and 46% had a significantly smaller standard deviation of forest patch size (31% were not significantly different), relative to their GPEs. For forest patch perimeter-to-area ratio and forest edge density, equal proportions of parks had values that were significantly larger or smaller than their respective GPEs and no clear trend emerged. In summary, all the national parks we analyzed, with the exception of the Georgian Bay Islands, were found to be significantly different from their corresponding GPE for at least one of the five metrics assessed, and 50% of the 26 parks were significantly different from their respective GPEs for all of the metrics assessed. The EOSD LC 2000 provides a heretofore unavailable dataset for characterizing broad trends in forest fragmentation in Canada's national parks and in their surrounding GPEs. The interpretation of forest fragmentation metrics must be guided by the underlying land cover context, as many forested ecosystems in Canada are naturally fragmented due to wetlands and topography. Furthermore, interpretation must also consider the management context, as some parks are designed to preserve fragmented habitats. An analysis of forest pattern such as that described herein provides a baseline, from which changes in fragmentation patterns over time could be monitored, enabled by earth observation data.

An assessment of uncertainty in forest carbon budget projections

Treesearch

Linda S. Heath; James E. Smith

2000-01-01

Estimates of uncertainty are presented for projections of forest carbon inventory and average annual net carbon flux on private timberland in the US using the model FORCARB. Uncertainty in carbon inventory was approximately ±9% (2000 million metric tons) of the estimated median in the year 2000, rising to 11% (2800 million metric tons) in projection year 2040...

Challenges in characterizing a parcelized forest landscape: why metric, scale and threshold matter

Treesearch

Michael A. Kilgore; Stephanie A. Snyder; Kayla Block-Torgerson; Steven J. Taff

2013-01-01

Several metrics have been cited in the literature as being useful characterizations of forest land parcelization. Yet no agreed-upon standard measure exists which creates difficulties in identifying where parcelization is occurring as well as comparing the magnitude of its occurrence across different studies and geographic regions. We evaluated three existing (average...

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

USGS Publications Warehouse

Peterson, Birgit E.; Nelson, Kurtis J.

2009-01-01

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

Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

NASA Astrophysics Data System (ADS)

Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

2017-12-01

The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape.

PubMed

Bähner, K W; Zweig, K A; Leal, I R; Wirth, R

2017-10-01

Forest fragmentation and climate change are among the most severe and pervasive forms of human impact. Yet, their combined effects on plant-insect herbivore interaction networks, essential components of forest ecosystems with respect to biodiversity and functioning, are still poorly investigated, particularly in temperate forests. We addressed this issue by analysing plant-insect herbivore networks (PIHNs) from understories of three managed beech forest habitats: small forest fragments (2.2-145 ha), forest edges and forest interior areas within three continuous control forests (1050-5600 ha) in an old hyper-fragmented forest landscape in SW Germany. We assessed the impact of forest fragmentation, particularly edge effects, on PIHNs and the resulting differences in robustness against climate change by habitat-wise comparison of network topology and biologically realistic extinction cascades of networks following scores of vulnerability to climate change for the food plant species involved. Both the topological network metrics (complexity, nestedness, trophic niche redundancy) and robustness to climate change strongly increased in forest edges and fragments as opposed to the managed forest interior. The nature of the changes indicates that human impacts modify network structure mainly via host plant availability to insect herbivores. Improved robustness of PIHNs in forest edges/small fragments to climate-driven extinction cascades was attributable to an overall higher thermotolerance across plant communities, along with positive effects of network structure. The impoverishment of PIHNs in managed forest interiors and the suggested loss of insect diversity from climate-induced co-extinction highlight the need for further research efforts focusing on adequate silvicultural and conservation approaches.

Large off-nadir scan angle of airborne LiDAR can severely affect the estimates of forest structure metrics

NASA Astrophysics Data System (ADS)

Liu, Jing; Skidmore, Andrew K.; Jones, Simon; Wang, Tiejun; Heurich, Marco; Zhu, Xi; Shi, Yifang

2018-02-01

Gap fraction (Pgap) and vertical gap fraction profile (vertical Pgap profile) are important forest structural metrics. Accurate estimation of Pgap and vertical Pgap profile is therefore critical for many ecological applications, including leaf area index (LAI) mapping, LAI profile estimation and wildlife habitat modelling. Although many studies estimated Pgap and vertical Pgap profile from airborne LiDAR data, the scan angle was often overlooked and a nadir view assumed. However, the scan angle can be off-nadir and highly variable in the same flight strip or across different flight strips. In this research, the impact of off-nadir scan angle on Pgap and vertical Pgap profile was evaluated, for several forest types. Airborne LiDAR data from nadir (0°∼7°), small off-nadir (7°∼23°), and large off-nadir (23°∼38°) directions were used to calculate both Pgap and vertical Pgap profile. Digital hemispherical photographs (DHP) acquired during fieldwork were used as references for validation. Our results show that angular Pgap from airborne LiDAR correlates well with angular Pgap from DHP (R2 = 0.74, 0.87, and 0.67 for nadir, small off-nadir and large off-nadir direction). But underestimation of Pgap from LiDAR amplifies at large off-nadir scan angle. By comparing Pgap and vertical Pgap profiles retrieved from different directions, it is shown that scan angle impact on Pgap and vertical Pgap profile differs amongst different forest types. The difference is likely to be caused by different leaf angle distribution and canopy architecture in these forest types. Statistical results demonstrate that the scan angle impact is more severe for plots with discontinuous or sparse canopies. These include coniferous plots, and deciduous or mixed plots with between-crown gaps. In these discontinuous plots, Pgap and vertical Pgap profiles are maximum when observed from nadir direction, and then rapidly decrease with increasing scan angle. The results of this research have many important practical implications. First, it is suggested that large off-nadir scan angle of airborne LiDAR should be avoided to ensure a more accurate Pgap and LAI estimation. Second, the angular dependence of vertical Pgap profiles observed from airborne LiDAR should be accounted for, in order to improve the retrieval of LAI profiles, and other quantitative canopy structural metrics. This is especially necessary when using multi-temporal datasets in discontinuous forest types. Third, the anisotropy of Pgap and vertical Pgap profile observed by airborne LiDAR, can potentially help to resolve the anisotropic behavior of canopy reflectance, and refine the inversion of biophysical and biochemical properties from passive multispectral or hyperspectral data.

An improved real time image detection system for elephant intrusion along the forest border areas.

PubMed

Sugumar, S J; Jayaparvathy, R

2014-01-01

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

Oligarchic forests of economic plants in amazonia: utilization and conservation of an important tropical resource.

PubMed

Peters, C M; Balick, M J; Kahn, F; Anderson, A B

1989-12-01

Tropical forests dominated by only one or two tree species occupy tens of millions of hectares in Ammonia In many cases, the dominant species produce fruits, seeds, or oils of economic importance. Oligarchic (Gr. oligo = few, archic = dominated or ruled by) forests of six economic species, i. e., Euterpe oleracea, Grias peruviana, Jessenia bataua, Mauritia flexuosa, Myrciaria dubia, and Orbignya phalerata, were studied in Brazil and Peru Natural populations of these species contain from 100 to 3,000 conspecific adult trees/ha and produce up to 11.1 metric tons of fruit/hd/yr. These plant populations are utilized and occasionally managed, by rural inhabitants in the region. Periodic fruit harvests, if properly controlled have only a minimal impact on forest structure and function, yet can generate substantial economic returns Market-oriented extraction of the fruits produced by oligarchic forests appears to represent a promising alternative for reconciling the development and conservation of Amazonian forests.

36 CFR 1210.15 - Metric system of measurement.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 36 Parks, Forests, and Public Property 3 2012-07-01 2012-07-01 false Metric system of measurement... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade and...

36 CFR § 1210.15 - Metric system of measurement.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 36 Parks, Forests, and Public Property 3 2013-07-01 2012-07-01 true Metric system of measurement... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade and...

36 CFR 1210.15 - Metric system of measurement.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 36 Parks, Forests, and Public Property 3 2011-07-01 2011-07-01 false Metric system of measurement... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade and...

36 CFR 1210.15 - Metric system of measurement.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Metric system of measurement... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade and...

36 CFR 1210.15 - Metric system of measurement.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 36 Parks, Forests, and Public Property 3 2014-07-01 2014-07-01 false Metric system of measurement... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade and...

Similarity in volatile communities leads to increased herbivory and greater tropical forest diversity.

PubMed

Massad, Tara J; Martins de Moraes, Marcílio; Philbin, Casey; Oliveira, Celso; Cebrian Torrejon, Gerardo; Fumiko Yamaguchi, Lydia; Jeffrey, Christopher S; Dyer, Lee A; Richards, Lora A; Kato, Massuo J

2017-07-01

A longstanding paradigm in ecology is that there are positive associations between herbivore diversity, specialization, and plant species diversity, with a focus on taxonomic diversity. However, phytochemical diversity is also an informative metric, as insect herbivores interact with host plants not as taxonomic entities, but as sources of nutrients, primary metabolites, and mixtures of attractant and repellant chemicals. The present research examines herbivore responses to phytochemical diversity measured as volatile similarity in the tropical genus Piper. We quantified associations between naturally occurring volatile variation and herbivory by specialist and generalist insects. Intraspecific similarity of volatile compounds across individuals was associated with greater overall herbivory. A structural equation model supported the hypothesis that plot level volatile similarity caused greater herbivory by generalists, but not specialists, which led to increased understory plant richness. These results demonstrate that using volatiles as a functional diversity metric is informative for understanding tropical forest diversity and indicate that generalist herbivores contribute to the maintenance of diversity. © 2017 by the Ecological Society of America.

Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

NASA Astrophysics Data System (ADS)

Karila, K.; Karjalainen, M.; Yu, X.; Vastaranta, M.; Holopainen, M.; Hyyppa, J.

2015-04-01

Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project "Advanced_SAR" was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m2). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better performance in forest attribute (i.e. mean tree height, basal area, mean stem diameter, stem volume, and biomass) prediction than stereo-radargrammetry. The results were 20.1% and 28.6% in relative root mean square error (RMSE) for biomass prediction, for TDX and TSX respectively.

Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

NASA Astrophysics Data System (ADS)

Halligan, K. Q.; Roberts, D. A.

2006-12-01

Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation vigor or senescence. Additionally, the strength of hyperspectral data for vegetation classification suggests these data have additional utility for modeling carbon flux dynamics by allowing more accurate plant functional type mapping.

Predicting spatial variations of tree species richness in tropical forests from high-resolution remote sensing.

PubMed

Fricker, Geoffrey A; Wolf, Jeffrey A; Saatchi, Sassan S; Gillespie, Thomas W

2015-10-01

There is an increasing interest in identifying theories, empirical data sets, and remote-sensing metrics that can quantify tropical forest alpha diversity at a landscape scale. Quantifying patterns of tree species richness in the field is time consuming, especially in regions with over 100 tree species/ha. We examine species richness in a 50-ha plot in Barro Colorado Island in Panama and test if biophysical measurements of canopy reflectance from high-resolution satellite imagery and detailed vertical forest structure and topography from light detection and ranging (lidar) are associated with species richness across four tree size classes (>1, 1-10, >10, and >20 cm dbh) and three spatial scales (1, 0.25, and 0.04 ha). We use the 2010 tree inventory, including 204,757 individuals belonging to 301 species of freestanding woody plants or 166 ± 1.5 species/ha (mean ± SE), to compare with remote-sensing data. All remote-sensing metrics became less correlated with species richness as spatial resolution decreased from 1.0 ha to 0.04 ha and tree size increased from 1 cm to 20 cm dbh. When all stems with dbh > 1 cm in 1-ha plots were compared to remote-sensing metrics, standard deviation in canopy reflectance explained 13% of the variance in species richness. The standard deviations of canopy height and the topographic wetness index (TWI) derived from lidar were the best metrics to explain the spatial variance in species richness (15% and 24%, respectively). Using multiple regression models, we made predictions of species richness across Barro Colorado Island (BCI) at the 1-ha spatial scale for different tree size classes. We predicted variation in tree species richness among all plants (adjusted r² = 0.35) and trees with dbh > 10 cm (adjusted r² = 0.25). However, the best model results were for understory trees and shrubs (dbh 1-10 cm) (adjusted r² = 0.52) that comprise the majority of species richness in tropical forests. Our results indicate that high-resolution remote sensing can predict a large percentage of variance in species richness and potentially provide a framework to map and predict alpha diversity among trees in diverse tropical forests.

Comparing forests across climates and biomes: qualitative assessments, reference forests and regional intercomparisons.

PubMed

Salk, Carl F; Frey, Ulrich; Rusch, Hannes

2014-01-01

Communities, policy actors and conservationists benefit from understanding what institutions and land management regimes promote ecosystem services like carbon sequestration and biodiversity conservation. However, the definition of success depends on local conditions. Forests' potential carbon stock, biodiversity and rate of recovery following disturbance are known to vary with a broad suite of factors including temperature, precipitation, seasonality, species' traits and land use history. Methods like tracking over-time changes within forests, or comparison with "pristine" reference forests have been proposed as means to compare the structure and biodiversity of forests in the face of underlying differences. However, data from previous visits or reference forests may be unavailable or costly to obtain. Here, we introduce a new metric of locally weighted forest intercomparison to mitigate the above shortcomings. This method is applied to an international database of nearly 300 community forests and compared with previously published techniques. It is particularly suited to large databases where forests may be compared among one another. Further, it avoids problematic comparisons with old-growth forests which may not resemble the goal of forest management. In most cases, the different methods produce broadly congruent results, suggesting that researchers have the flexibility to compare forest conditions using whatever type of data is available. Forest structure and biodiversity are shown to be independently measurable axes of forest condition, although users' and foresters' estimations of seemingly unrelated attributes are highly correlated, perhaps reflecting an underlying sentiment about forest condition. These findings contribute new tools for large-scale analysis of ecosystem condition and natural resource policy assessment. Although applied here to forestry, these techniques have broader applications to classification and evaluation problems using crowdsourced or repurposed data for which baselines or external validations are not available.

Comparing Forests across Climates and Biomes: Qualitative Assessments, Reference Forests and Regional Intercomparisons

PubMed Central

Salk, Carl F.; Frey, Ulrich; Rusch, Hannes

2014-01-01

Communities, policy actors and conservationists benefit from understanding what institutions and land management regimes promote ecosystem services like carbon sequestration and biodiversity conservation. However, the definition of success depends on local conditions. Forests' potential carbon stock, biodiversity and rate of recovery following disturbance are known to vary with a broad suite of factors including temperature, precipitation, seasonality, species' traits and land use history. Methods like tracking over-time changes within forests, or comparison with “pristine” reference forests have been proposed as means to compare the structure and biodiversity of forests in the face of underlying differences. However, data from previous visits or reference forests may be unavailable or costly to obtain. Here, we introduce a new metric of locally weighted forest intercomparison to mitigate the above shortcomings. This method is applied to an international database of nearly 300 community forests and compared with previously published techniques. It is particularly suited to large databases where forests may be compared among one another. Further, it avoids problematic comparisons with old-growth forests which may not resemble the goal of forest management. In most cases, the different methods produce broadly congruent results, suggesting that researchers have the flexibility to compare forest conditions using whatever type of data is available. Forest structure and biodiversity are shown to be independently measurable axes of forest condition, although users' and foresters' estimations of seemingly unrelated attributes are highly correlated, perhaps reflecting an underlying sentiment about forest condition. These findings contribute new tools for large-scale analysis of ecosystem condition and natural resource policy assessment. Although applied here to forestry, these techniques have broader applications to classification and evaluation problems using crowdsourced or repurposed data for which baselines or external validations are not available. PMID:24743325

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts.

PubMed

Longo, Marcos; Knox, Ryan G; Levine, Naomi M; Alves, Luciana F; Bonal, Damien; Camargo, Plinio B; Fitzjarrald, David R; Hayek, Matthew N; Restrepo-Coupe, Natalia; Saleska, Scott R; da Silva, Rodrigo; Stark, Scott C; Tapajós, Raphael P; Wiedemann, Kenia T; Zhang, Ke; Wofsy, Steven C; Moorcroft, Paul R

2018-05-22

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km 2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Characterizing Tropical Forest Structure using Field-based Measurements and a Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Palace, M. W.; Sullivan, F.; Ducey, M. J.; Herrick, C.

2015-12-01

Forest structure comprises numerous quantifiable components of forest biometric characteristics, one of which is tree architecture. This structural component is important in the understanding of the past and future trajectories of these biomes. Tropical forests are often considered the most structurally complex and yet least understood of forested ecosystems. New technologies have provided novel avenues for quantifying properties of forested ecosystems, one of which is LIght Detection And Ranging (lidar). This sensor can be deployed on satellite, aircraft, unmanned aerial vehicles, and terrestrial platforms. In this study we examined the efficacy of a terrestrial lidar scanner (TLS) system in a tropical forest to estimate forest structure. Our study was conducted in January 2012 at La Selva, Costa Rica at twenty locations in predominantly undisturbed forest. At these locations we collected field measured biometric attributes using a variable plot design. We also collected TLS data from the center of each plot. Using this data we developed relative vegetation profiles (RVPs) and calculated a series of parameters including entropy, FFT, number of layers and plant area index to develop statistical relationships with field data. We developed statistical models using multiple linear regressions, all of which converged on statistically significant relationships with the strongest relationship being for mean crown depth (r2 = 0.87, p < 0.01, RMSE = 1.1 m). Tree density was found to have the least strong statistical relationship (r2 = 0.45, p < 0.01, RMSE = 160.7 n ha-1). We found significant relationship between basal area and lidar metrics (r2 = 0.76, p < 0.001, RMSE = 3.68 number ha-1). Models developed for biomass 1 had a higher r-squared value and lower RMSE than that of biomass2 (biomass1: r2 = 0.7, p < 0.01, RMSE = 28.94 Mg ha-1; biomass2: r2 = 0.67, p < 0.01, RMSE = 40.62 Mg ha-1). Parameters selected in our models varied, thus indicating the potential relevance of multiple features in canopy profiles and geometry that are related to field-measured structure. Our work indicates that TLS data can provide useful information on tropical forest structure.

A method for the selection of relevant pattern indices for monitoring of spatial forest cover pattern at a regional scale

NASA Astrophysics Data System (ADS)

De Clercq, Eva M.; Vandemoortele, Femke; De Wulf, Robert R.

2006-06-01

When signing Agenda 21, several countries agreed to monitor the status of forests to ensure their sustainable use. For reporting on the change in spatial forest cover pattern on a regional scale, pattern metrics are widely used. These indices are not often thoroughly evaluated as to their sensitivity to remote sensing data characteristics. Hence, one would not know whether the change in the metric values was due to actual landscape pattern changes or to characteristic variation of multitemporal remote sensing data. The objective of this study is to empirically test an array of pattern metrics for the monitoring of spatial forest cover. Different user requirements are used as point of departure. This proved to be a straightforward method for selecting relevant pattern indices. We strongly encourage the systematic screening of these indices prior to use in order to get a deeper understanding of the results obtained by them.

Use of two population metrics clarifies biodiversity dynamics in large-scale monitoring: the case of trees in Japanese old-growth forests: the need for multiple population metrics in large-scale monitoring.

PubMed

Ogawa, Mifuyu; Yamaura, Yuichi; Abe, Shin; Hoshino, Daisuke; Hoshizaki, Kazuhiko; Iida, Shigeo; Katsuki, Toshio; Masaki, Takashi; Niiyama, Kaoru; Saito, Satoshi; Sakai, Takeshi; Sugita, Hisashi; Tanouchi, Hiroyuki; Amano, Tatsuya; Taki, Hisatomo; Okabe, Kimiko

2011-07-01

Many indicators/indices provide information on whether the 2010 biodiversity target of reducing declines in biodiversity have been achieved. The strengths and limitations of the various measures used to assess the success of such measures are now being discussed. Biodiversity dynamics are often evaluated by a single biological population metric, such as the abundance of each species. Here we examined tree population dynamics of 52 families (192 species) at 11 research sites (three vegetation zones) of Japanese old-growth forests using two population metrics: number of stems and basal area. We calculated indices that track the rate of change in all species of tree by taking the geometric mean of changes in population metrics between the 1990s and the 2000s at the national level and at the levels of the vegetation zone and family. We specifically focused on whether indices based on these two metrics behaved similarly. The indices showed that (1) the number of stems declined, whereas basal area did not change at the national level and (2) the degree of change in the indices varied by vegetation zone and family. These results suggest that Japanese old-growth forests have not degraded and may even be developing in some vegetation zones, and indicate that the use of a single population metric (or indicator/index) may be insufficient to precisely understand the state of biodiversity. It is therefore important to incorporate more metrics into monitoring schemes to overcome the risk of misunderstanding or misrepresenting biodiversity dynamics.

Unraveling Landscape Complexity: Land Use/Land Cover Changes and Landscape Pattern Dynamics (1954-2008) in Contrasting Peri-Urban and Agro-Forest Regions of Northern Italy.

PubMed

Smiraglia, D; Ceccarelli, T; Bajocco, S; Perini, L; Salvati, L

2015-10-01

This study implements an exploratory data analysis of landscape metrics and a change detection analysis of land use and population density to assess landscape dynamics (1954-2008) in two physiographic zones (plain and hilly-mountain area) of Emilia Romagna, northern Italy. The two areas are characterized by different landscape types: a mixed urban-rural landscape dominated by arable land and peri-urban settlements in the plain and a traditional agro-forest landscape in the hilly-mountain area with deciduous and conifer forests, scrublands, meadows, and crop mosaic. Urbanization and, to a lesser extent, agricultural intensification were identified as the processes underlying landscape change in the plain. Land abandonment determining natural forestation and re-forestation driven by man was identified as the process of change most representative of the hilly-mountain area. Trends in landscape metrics indicate a shift toward more fragmented and convoluted patterns in both areas. Number of patches, the interspersion and juxtaposition index, and the large patch index are the metrics discriminating the two areas in terms of landscape patterns in 1954. In 2008, mean patch size, edge density, interspersion and juxtaposition index, and mean Euclidean nearest neighbor distance were the metrics with the most different spatial patterns in the two areas. The exploratory data analysis of landscape metrics contributed to link changes over time in both landscape composition and configuration providing a comprehensive picture of landscape transformations in a wealthy European region. Evidence from this study are hoped to inform sustainable land management designed for homogeneous landscape units in similar socioeconomic contexts.

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia.

PubMed

Mokross, Karl; Ryder, Thomas B; Côrtes, Marina Corrêa; Wolfe, Jared D; Stouffer, Philip C

2014-02-07

Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

Seasonality of a boreal forest: a remote sensing perspective

NASA Astrophysics Data System (ADS)

Rautiainen, Miina; Heiskanen, Janne; Lukes, Petr; Majasalmi, Titta; Mottus, Matti; Pisek, Jan

2016-04-01

Understanding the seasonal dynamics of boreal ecosystems through interpretation of satellite reflectance data is needed for efficient large-scale monitoring of northern vegetation dynamics and productivity trends. Satellite remote sensing enables continuous global monitoring of vegetation status and is not limited to single-date phenological metrics. Using remote sensing also enables gaining a wider perspective to the seasonality of vegetation dynamics. The seasonal reflectance cycles of boreal forests observed in optical satellite images are explained by changes in biochemical properties and geometrical structure of vegetation as well as seasonal variation in solar illumination. This poster provides a synthesis of a research project (2010-2015) dedicated to monitoring the seasonal cycle of boreal forests. It is based on satellite and field data collected from the Hyytiälä Forestry Field Station in Finland. The results highlight the role understory vegetation has in forming the forest reflectance measured by satellite instruments.

Simulation of ICESat-2 canopy height retrievals for different ecosystems

NASA Astrophysics Data System (ADS)

Neuenschwander, A. L.

2016-12-01

Slated for launch in late 2017 (or early 2018), the ICESat-2 satellite will provide a global distribution of geodetic measurements from a space-based laser altimeter of both the terrain surface and relative canopy heights which will provide a significant benefit to society through a variety of applications ranging from improved global digital terrain models to producing distribution of above ground vegetation structure. The ATLAS instrument designed for ICESat-2, will utilize a different technology than what is found on most laser mapping systems. The photon counting technology of the ATLAS instrument onboard ICESat-2 will record the arrival time associated with a single photon detection. That detection can occur anywhere within the vertical distribution of the reflected signal, that is, anywhere within the vertical distribution of the canopy. This uncertainty of where the photon will be returned from within the vegetation layer is referred to as the vertical sampling error. Preliminary simulation studies to estimate vertical sampling error have been conducted for several ecosystems including woodland savanna, montane conifers, temperate hardwoods, tropical forest, and boreal forest. The results from these simulations indicate that the canopy heights reported on the ATL08 data product will underestimate the top canopy height in the range of 1 - 4 m. Although simulation results indicate the ICESat-2 will underestimate top canopy height, there is, however, a strong correlation between ICESat-2 heights and relative canopy height metrics (e.g. RH75, RH90). In tropical forest, simulation results indicate the ICESat-2 height correlates strongly with RH90. Similarly, in temperate broadleaf forest, the simulated ICESat-2 heights were also strongly correlated with RH90. In boreal forest, the simulated ICESat-2 heights are strongly correlated with RH75 heights. It is hypothesized that the correlations between simulated ICESat-2 heights and canopy height metrics are a function of both canopy cover and vegetation physiology (e.g. leaf size/shape) which contributes to the horizontal and vertical structure of the vegetation.

Seeing through the Canopy: Relationship between Coarse Woody Debris and Forest Structure measured by Airborne Lidar in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Scaranello, M. A., Sr.; Keller, M. M.; dos-Santos, M. N.; Longo, M.; Pinagé, E. R.; Leitold, V.

2016-12-01

Coarse woody debris is an important but infrequently quantified carbon pool in tropical forests. Based on studies at 12 sites spread across the Brazilian Amazon, we quantified coarse woody debris stocks in intact forests and forests affected by different intensities of degradation by logging and/or fire. Measurement were made in-situ and for the first time field measurements of coarse woody debris were related to structural metrics derived from airborne lidar. Using the line-intercept method we established 84 transects for sampling fallen coarse woody debris and associated inventory plots for sampling standing dead wood in intact, conventional logging, reduced impact logging, burned and burned after logging forests. Overall mean and standard deviation of total coarse woody debris were 50.0 Mg ha-1 and 26.4 Mg ha-1 respectively. Forest degradation increased coarse woody debris stocks compared to intact forests by a factor of 1.7 in reduced impact logging forests and up to 3-fold in burned forests, in a side-by-side comparison of nearby areas. The ratio between coarse woody debris and biomass increased linearly with number of degradation events (R²: 0.67, p<0.01). Individual lidar-derived structural variables strongly correlated with coarse woody debris in intact and reduced impact logging forests: the 5th percentile of last returns for in intact forests (R²: 0.78, p<0.01) and forest gap area, mapped using lidar-derived canopy height model, for reduced impact logging forests (R²: 0.63, p<0.01). Individual gap area also played a weak but significant role in determining coarse woody debris in burned forests (R2: 0.21, p<0.05), but with contrasting trend. Both degradation-specific and general multiple models using lidar-derived variables were good predictor of coarse woody debris stocks in different degradation levels in the Brazilian Amazon. The strong relation of coarse woody debris with lidar derived structural variables suggests an approach for quantifying infrequently measured coarse woody debris over large areas.

Tropical forests are thermally buffered despite intensive selective logging.

PubMed

Senior, Rebecca A; Hill, Jane K; Benedick, Suzan; Edwards, David P

2018-03-01

Tropical rainforests are subject to extensive degradation by commercial selective logging. Despite pervasive changes to forest structure, selectively logged forests represent vital refugia for global biodiversity. The ability of these forests to buffer temperature-sensitive species from climate warming will be an important determinant of their future conservation value, although this topic remains largely unexplored. Thermal buffering potential is broadly determined by: (i) the difference between the "macroclimate" (climate at a local scale, m to ha) and the "microclimate" (climate at a fine-scale, mm to m, that is distinct from the macroclimate); (ii) thermal stability of microclimates (e.g. variation in daily temperatures); and (iii) the availability of microclimates to organisms. We compared these metrics in undisturbed primary forest and intensively logged forest on Borneo, using thermal images to capture cool microclimates on the surface of the forest floor, and information from dataloggers placed inside deadwood, tree holes and leaf litter. Although major differences in forest structure remained 9-12 years after repeated selective logging, we found that logging activity had very little effect on thermal buffering, in terms of macroclimate and microclimate temperatures, and the overall availability of microclimates. For 1°C warming in the macroclimate, temperature inside deadwood, tree holes and leaf litter warmed slightly more in primary forest than in logged forest, but the effect amounted to <0.1°C difference between forest types. We therefore conclude that selectively logged forests are similar to primary forests in their potential for thermal buffering, and subsequent ability to retain temperature-sensitive species under climate change. Selectively logged forests can play a crucial role in the long-term maintenance of global biodiversity. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

USGS Publications Warehouse

Danielson, Thomas J.; Loftin, Cynthia S.; Tsomides, Leonidas; DiFranco, Jeanne L.; Connors, Beth

2011-01-01

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models. ?? 2011 by The North American Benthological Society.

Relating structural growth environment to white spruce sapling establishment at the Forest-Tundra Ecotone

NASA Astrophysics Data System (ADS)

Maguire, A.; Boelman, N.; Griffin, K. L.; Jensen, J.; Hiers, E.; Johnson, D. M.; Vierling, L. A.; Eitel, J.

2017-12-01

The effect of climate change on treeline position at the latitudinal Forest-Tundra ecotone (FTE) is poorly understood. While the FTE is expansive (stretching 13,000 km acros the panarctic), understanding relationships between climate and tree function may depend on very fine scale processes. High resolution tools are therefore needed to appropriately characterize the leading (northernmost) edge of the FTE. We hypothesized that microstructural metrics obtainable from lidar remote sensing may explain variation in the physical growth environment that governs sapling establishment. To test our hypothesis, we used terrestrial laser scanning (TLS) to collect highly spatially resolved 3-D structural information of white spruce (Picea glauca) saplings and their aboveground growth environment at the leading edge of a FTE in northern Alaska and Northwest Territories, Canada. Coordinates of sapling locations were extracted from the 3-D TLS data. Within each sampling plot, 20 sets of coordinates were randomly selected from regions where no saplings were present. Ground roughness, canopy roughness, average aspect, average slope, average curvature, wind shelter index, and wetness indexwere extracted from point clouds within a variable radius from all coordinates. Generalized linear models (GLM) were fit to determine which microstructural metrics were most strongly associated with sapling establishment. Preliminary analyses of three plots suggest that vegetation roughness, wetness index, ground roughness, and slope were the most important terrain metrics governing sapling presence (Figure 1). Comprehensive analyses will include eight plots and GLMs optimized for scale at which structural parameters affect sapling establishment. Spatial autocorrelation of sample locations will be accounted for in models. Because these analyses address how the physical growth environment affects sapling establishment, model outputs will provide information for improving understanding of the ecological processes that regulate treeline dynamics. Moreover, establishing relationships between the remotely sensed structural growth environment and tree establishment provides new ways of spatially scaling across larger areas to study ecological change at the FTE.

Estimating number and size of forest patches from FIA plot data

Treesearch

Mark D. Nelson; Andrew J. Lister; Mark H. Hansen

2009-01-01

Forest inventory and analysis (FIA) annual plot data provide for estimates of forest area, type, volume, growth, and other attributes. Estimates of forest landscape metrics, such as those describing abundance, size, and shape of forest patches, however, typically are not derived from FIA plot data but from satellite image-based land cover maps. Associating image-based...

Ecological restoration success is higher for natural regeneration than for active restoration in tropical forests

PubMed Central

Crouzeilles, Renato; Ferreira, Mariana S.; Chazdon, Robin L.; Lindenmayer, David B.; Sansevero, Jerônimo B. B.; Monteiro, Lara; Iribarrem, Alvaro; Latawiec, Agnieszka E.; Strassburg, Bernardo B. N.

2017-01-01

Is active restoration the best approach to achieve ecological restoration success (the return to a reference condition, that is, old-growth forest) when compared to natural regeneration in tropical forests? Our meta-analysis of 133 studies demonstrated that natural regeneration surpasses active restoration in achieving tropical forest restoration success for all three biodiversity groups (plants, birds, and invertebrates) and five measures of vegetation structure (cover, density, litter, biomass, and height) tested. Restoration success for biodiversity and vegetation structure was 34 to 56% and 19 to 56% higher in natural regeneration than in active restoration systems, respectively, after controlling for key biotic and abiotic factors (forest cover, precipitation, time elapsed since restoration started, and past disturbance). Biodiversity responses were based primarily on ecological metrics of abundance and species richness (74%), both of which take far less time to achieve restoration success than similarity and composition. This finding challenges the widely held notion that natural forest regeneration has limited conservation value and that active restoration should be the default ecological restoration strategy. The proposition that active restoration achieves greater restoration success than natural regeneration may have arisen because previous comparisons lacked controls for biotic and abiotic factors; we also did not find any difference between active restoration and natural regeneration outcomes for vegetation structure when we did not control for these factors. Future policy priorities should align the identified patterns of biophysical and ecological conditions where each or both restoration approaches are more successful, cost-effective, and compatible with socioeconomic incentives for tropical forest restoration. PMID:29134195

Ecological restoration success is higher for natural regeneration than for active restoration in tropical forests.

PubMed

Crouzeilles, Renato; Ferreira, Mariana S; Chazdon, Robin L; Lindenmayer, David B; Sansevero, Jerônimo B B; Monteiro, Lara; Iribarrem, Alvaro; Latawiec, Agnieszka E; Strassburg, Bernardo B N

2017-11-01

Is active restoration the best approach to achieve ecological restoration success (the return to a reference condition, that is, old-growth forest) when compared to natural regeneration in tropical forests? Our meta-analysis of 133 studies demonstrated that natural regeneration surpasses active restoration in achieving tropical forest restoration success for all three biodiversity groups (plants, birds, and invertebrates) and five measures of vegetation structure (cover, density, litter, biomass, and height) tested. Restoration success for biodiversity and vegetation structure was 34 to 56% and 19 to 56% higher in natural regeneration than in active restoration systems, respectively, after controlling for key biotic and abiotic factors (forest cover, precipitation, time elapsed since restoration started, and past disturbance). Biodiversity responses were based primarily on ecological metrics of abundance and species richness (74%), both of which take far less time to achieve restoration success than similarity and composition. This finding challenges the widely held notion that natural forest regeneration has limited conservation value and that active restoration should be the default ecological restoration strategy. The proposition that active restoration achieves greater restoration success than natural regeneration may have arisen because previous comparisons lacked controls for biotic and abiotic factors; we also did not find any difference between active restoration and natural regeneration outcomes for vegetation structure when we did not control for these factors. Future policy priorities should align the identified patterns of biophysical and ecological conditions where each or both restoration approaches are more successful, cost-effective, and compatible with socioeconomic incentives for tropical forest restoration.

Initial Response of Pine Seedlings and Weeds to Dried Sewage Sludge in Rehabilitation of an Eroded Forest Site

Treesearch

Charles R. Berry

1977-01-01

Dried sewage sludge was applied at rates of 0, 17, 34, and 69 metric tons/ha on a badly eroded forest site in the Piedmont region of northeast Georgia. Production of weed bio mass varied directly with amount of sludge applied. Heigh growth for both shortleafand loblolly pine seedlings appeared to be greater on plots receiving 17 metric tons of sludge/ha, bu differences...

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

Determining the dynamics of evapotranspiration from fragmented forests under drought in southwestern Amazonia using Landsat imagery

NASA Astrophysics Data System (ADS)

Numata, I.; Khand, K.; Kjaersgaard, J.; Cochrane, M. A.; Silva, S.

2016-12-01

Deforestation in the Amazon has resulted in massive amounts of forest biomass loss and also in extensive forest fragmentation across the region. Fragmented tropical forests are exposed to abrupt environmental changes and experience several biological and ecological changes across distances from forest edges. Extreme droughts in 2005 and 2010 have caused extensive tree mortality across this region. These events may exacerbate edge effects, where already water stressed forest fragments dry more rapidly potentially enabling other disturbances such as forest fire. We analyzed the effects of forest fragmentation and drought on forest evapotranspiration (ET) estimated using the energy balance-based model METRIC with Landsat imagery in Rondônia State in the southwestern Amazon. Forest ET estimates were produced for the dry seasons (June-August) of 2009-2011 thus including the 2010 drought event and pre- and post-event periods. METRIC ET data were combined with forest edge data with edge distances of 100m, 300m, 500m, 1000m, 5000m and >5000m (core forest), generated from Landsat land cover maps for spatiotemporal analysis of forest ET. METRIC ET estimates had an agreement with flux tower ET data from the field of R2 = 0.72. Within the study time period, the 2010 drought year showed the lowest average ET from core forest (2.5mm/day), followed by 2011 (3.0mm/day) and 2009 (3.6mm/day) in the month of August, the mid dry season, while no significant differences were noted among three study years earlier in the dry seasons. In terms of edge effects, the major changes in forest ET occur up to 300 m from the forest edges, with ET decreasees of 30 % at 100 m as compared to further distances. The magnitude of edge-related ET changes became even greater during August of the drought year (2010) and the post-drought year (2011). Annual (drought and non-drought) and seasonal (June-August) forest ET variations were highly significant (p<0.001), while the impact of distance from edge on forest ET was significant only in the drought year (p<0.05).

Mapping standing dead trees (snags) in the aftermath of the 2013 Rim Fire using airborne LiDAR data.

NASA Astrophysics Data System (ADS)

Casas Planes, Á.; Garcia-Alonso, M.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.; Siegel, R.

2014-12-01

Abundance and spatial distribution of standing dead trees (snags) are key indicators of forest biodiversity and ecosystem health and represent a critical component of habitat for various wildlife species, including the great grey owl and the black-backed woodpecker. In this work we assess the potential of light detection and ranging (LiDAR) to discriminate snags from the live trees and map their distribution. The study area encompasses the burn perimeter of the Rim Fire, the third largest wildfire in California's recorded history (~104.000 ha) and represents a heterogeneous mosaic of mixed conifer forests, hardwood, and meadows. The snags mapping procedure is based on a 3D single tree detection using a Watershed algorithm and the extraction of height and intensity metrics within each segment. Variables selected using Gaussian processes form a feature space for a classifier to distinguish between dead trees and live trees. Finally, snag density and snag diameter classes that are relevant for avian species are mapped. This work shows the use of LiDAR metrics to quantify ecological variables related to the vertical heterogeneity of the forest canopy that are important in the identification of snags, for example, fractional cover. We observed that intensity-related variables are critical to the successful identification of snags and their distribution. Our study highlights the importance of high-density LiDAR for characterizing the forest structural variables that contribute to the assessment of wildlife habitat suitability.

Landscape trends in Mid-Atlantic and Southeastern United States ecoregions

USGS Publications Warehouse

Griffith, J.A.; Stehman, S.V.; Loveland, Thomas R.

2003-01-01

Landscape pattern and composition metrics are potential indicators for broad-scale monitoring of change and for relating change to human and ecological processes. We used a probability sample of 20-km × 20-km sampling blocks to characterize landscape composition and pattern in five US ecoregions: the Middle Atlantic Coastal Plain, Southeastern Plains, Northern Piedmont, Piedmont, and Blue Ridge Mountains. Land use/land cover (LULC) data for five dates between 1972 and 2000 were obtained for each sample block. Analyses focused on quantifying trends in selected landscape pattern metrics by ecoregion and comparing trends in land cover proportions and pattern metrics among ecoregions. Repeated measures analysis of the landscape pattern documented a statistically significant trend in all five ecoregions towards a more fine-grained landscape from the early 1970s through 2000. The ecologically important forest cover class also became more fine-grained with time (i.e., more numerous and smaller forest patches). Trends in LULC, forest edge, and forest percent like adjacencies differed among ecoregions. These results suggest that ecoregions provide a geographically coherent way to regionalize the story of national land use and land cover change in the United States. This study provides new information on LULC change in the southeast United States. Previous studies of the region from the 1930s to the 1980s showed a decrease in landscape fragmentation and an increase in percent forest, while this study showed an increase in forest fragmentation and a loss of forest cover.

Deforestation and benthic indicators: how much vegetation cover is needed to sustain healthy Andean streams?

PubMed

Iñiguez-Armijos, Carlos; Leiva, Adrián; Frede, Hans-Georg; Hampel, Henrietta; Breuer, Lutz

2014-01-01

Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices) and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS), we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%). Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments.

Deforestation and Benthic Indicators: How Much Vegetation Cover Is Needed to Sustain Healthy Andean Streams?

PubMed Central

Iñiguez–Armijos, Carlos; Leiva, Adrián; Frede, Hans–Georg; Hampel, Henrietta; Breuer, Lutz

2014-01-01

Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices) and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS), we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%). Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments. PMID:25147941

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.

How reliable are amphibian population metrics? A response to Kroll et al.

Treesearch

Hartwell H. Welsh; Karen L. Pope; Clara A. Wheeler

2009-01-01

Kroll et al. [Kroll, A.J., Runge, J.P., MacCracken, J.G., 2009. Unreliable amphibian population metrics may obfuscate more than they reveal. Biological Conservation] criticized our recent advocacy for combining readily attainable metrics of population status to gain insight about relationships between terrestrial plethodontid salamanders and forest succession [Welsh,...

[Extraction of temperate vegetation phenology thresholds in North America based on flux tower observation data].

PubMed

Zhao, Jing-Jing; Liu, Liang-Yun

2013-02-01

Flux tower method can effectively monitor the vegetation seasonal and phenological variation processes. At present, the differences in the detection and quantitative evaluation of various phenology extraction methods were not well validated and quantified. Based on the gross primary productivity (GPP) and net ecosystem productivity (NEP) data of temperate forests from 9 forest FLUXNET sites in North America, and by using the start dates (SOS) and end dates (EOS) of the temperate forest growth seasons extracted by different phenology threshold extraction methods, in combining with the forest ecosystem carbon source/sink functions, this paper analyzed the effects of different threshold standards on the extraction results of the vegetations phenology. The results showed that the effects of different threshold standards on the stability of the extracted results of deciduous broadleaved forest (DBF) phenology were smaller than those on the stability of the extracted results of evergreen needleleaved forest (ENF) phenology. Among the extracted absolute and relative thresholds of the forests GPP, the extracted threshold of the DBF daily GPP= 2 g C.m-2.d-1 had the best agreement with the DBF daily GPP = 20% maximum GPP (GPPmax) , the phenological metrics with a threshold of daily GPP = 4 g C.m-2.d-1 was close to that between daily GPP = 20% GPPmax and daily GPP = 50% GPPmax, and the start date of ecosystem carbon sink function was close to the SOS metrics between daily GPP = 4 g C.m-2.d-1 and daily GPP= 20% GPPmax. For ENF, the phenological metrics with a threshold of daily GPP = 2 g C.m-2.d-1 and daily GPP = 4 g C.m-2.d-1 had the best agreement with the daily GPP = 20% GPPmax and daily GPP = 50% GPPmax, respectively, and the start date of the ecosystem carbon sink function was close to the SOS metrics between daily GPP = 2 g C.m-2.d-1 and daily GPP= 10% GPPmax.

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

Kelbe, David; Oak Ridge National Lab.; van Aardt, Jan

Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in ordermore » to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.« less

Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

PubMed

Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

Tree species and size structure of old-growth Douglas-fir forests in central western Oregon, USA

USGS Publications Warehouse

Poage, Nathan; Tappeiner, J. C.

2005-01-01

We characterized the structure of 91 old-growth forests dominated by Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), using inventory data from recent (1985a??1991) old-growth timber sales in western Oregon. The data were complete counts (i.e., censuses) of all live trees >20 cm diameter at breast height (dbh, measured at 1.4 m above the ground) over a mean area of 17.1 ha at each site. Across all sites, Douglas-fir accounted for 79% of the total basal area (m2/ha) of all species. The average density of trees >100 cm dbh was 19 trees/ha and 90% of these trees were Douglas-fir. Species other than Douglas-fir constituted only about 20% of the total basal area at each old-growth site, on average, but largely accounted for the structural variation between sites. We used multivariate techniques such as cluster analysis, indicator species analysis, and ordination with non-metric multidimensional scaling (NMS) to identify and characterize six structural groups in terms of basal area in different speciesa??diameter classes. Almost 97% of the structural information was captured by the first (r2 = 0.841) and second (r2 = 0.128) NMS ordination axis. Geographic information systems (GIS) analysis and NMS indicated that the structural differences among groups of sites were associated with moisture, temperature, and elevation gradients within the study area. This type of analysis can be used to help define differences among old-growth forests and to set local structural goals for growing forests with old-growth characteristics.

Landslides and sediment budgets in four watersheds in eastern Puerto Rico: Chapter F in Water quality and landscape processes of four watersheds in eastern Puerto Rico

USGS Publications Warehouse

Larsen, Matthew C.; Murphy, Sheila F.; Stallard, Robert F.

2012-01-01

The low-latitude regions of the Earth are undergoing profound, rapid landscape change as forests are converted to agriculture to support growing population. Understanding the effects of these land-use changes requires analysis of watershed-scale geomorphic processes to better inform and manage this usually disorganized process. The investigation of hillslope erosion and the development of sediment budgets provides essential information for resource managers. Four small, montane, humid-tropical watersheds in the Luquillo Experimental Forest and nearby Río Grande de Loíza watershed, Puerto Rico (18° 20' N., 65° 45' W.), were selected to compare and contrast the geomorphic effects of land use and bedrock geology. Two of the watersheds are underlain largely by resistant Cretaceous volcaniclastic rocks but differ in land use and mean annual runoff: the Mameyes watershed, with predominantly primary forest cover and runoff of 2,750 millimeters per year, and the Canóvanas watershed, with mixed secondary forest and pasture and runoff of 970 millimeters per year. The additional two watersheds are underlain by relatively erodible granitic bedrock: the forested Icacos watershed, with runoff of 3,760 millimeters per year and the agriculturally developed Cayaguás watershed, with a mean annual runoff of 1,620 millimeters per year. Annual sediment budgets were estimated for each watershed using landslide, slopewash, soil creep, treethrow, suspended sediment, and streamflow data. The budgets also included estimates of sediment storage in channel beds, bars, floodplains, and in colluvial deposits. In the two watersheds underlain by volcaniclastic rocks, the forested Mameyes and the developed Canóvanas watersheds, landslide frequency (0.21 and 0.04 landslides per square kilometer per year, respectively), slopewash (5 and 30 metric tons per square kilometer per year), and suspended sediment yield (325 and 424 metric tons per square kilometer per year), were lower than in the two watersheds underlain by granitic bedrock. In these granitic watersheds, landslide frequency, slopewash, and suspended sediment yield were 0.43 landslides per square kilometer per year, 20 metric tons per square kilometer per year, and 2,140 metric tons per square kilometer per year, respectively, in the forested Icacos watershed and 0.8 landslides per square kilometer per year, 105 metric tons per square kilometer per year, and 2,110 metric tons per square kilometer per year, respectively, in the agriculturally developed Cayaguás watershed. Comparison of sediment budgets from the forested and developed watersheds indicates that human activities increase landslide frequency by as much as factor of 5 and slopewash by as much as a factor of 6. When the difference in annual runoff is considered, the effect of land use on suspended sediment yields is also notable. Sediment concentration, calculated as sediment yield normalized by runoff, was about 2.3 to 3.7 times as great in the two watersheds in secondary forest and pasture compared with sediment concentration in the watersheds in primary forest. Even in the two watersheds with primary forest cover, the Mameyes and Icacos, located in the Luquillo Experimental Forest, the effects of anthropogenic disturbance were marked: 43 to 63 percent of landslide-related erosion was associated with road construction and maintenance.

Stream Community Structure: An Analysis of Riparian Forest Buffer Restoration in the Chesapeake Bay Watershed

NASA Astrophysics Data System (ADS)

Orzetti, L. L.; Jones, R. C.

2005-05-01

Forested riparian buffer zones have been proposed as an important aid in curtailing upland sources of pollution before they reach stream surface waters, and enhancing habitat for stream organisms. Our objective was to test the efficacy of restored forest riparian buffers along streams in the Chesapeake Bay watershed by examining the stream macrobenthic community structure. To test our hypothesis, we collected riffle benthic and water samples, and performed habitat evaluations at 30 stream sites in the mid-Atlantic Piedmont, ranging in buffer age from 0 to greater than 50 years of age. Results showed that habitat, water quality, and benthic macroinvertebrate metrics improved with age of restored buffer. Habitat scores were driven mostly by instream substrate availability and width and age of riparian buffer zones. Water quality parameters varied within buffer age groups depending age of surrounding forest vegetation. Benthic invertebrate taxa richness, % EPT, % Plecoptera, % Ephemeroptera, and the FBI all improved with age of buffer zone. Instream habitat quality was the greatest driver of benthic macroinvertebrate community diversity and health, and appeared to plateau within 10-15 years of restoration with noticeable improvements occurring within 5-10 years post restoration.

Monitoring state forest lands in standardization with a national forest inventory program

Treesearch

James A. Westfall; Charles T. Scott

2009-01-01

Within the past decade, there has been increasing interest in uniformity of forest inventory techniques and methods. Where forest inventories are already in place, harmonization is often needed to recast various metrics and measurements to a common definition so that results can be compared and summarized across various spatial scales without regard to administrative...

Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data

PubMed Central

van Leeuwen, Willem J. D.

2008-01-01

This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests. PMID:27879809

The impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Williams, P.; Abatzoglou, J. T.

2016-12-01

Increased forest fire activity across the western United States (US) in recent decades has contributed to widespread forest mortality, carbon emissions, periods of degraded air quality, and substantial fire suppression expenditures. The increase in forest fire activity has likely been enabled by a number of factors including the legacy of fire suppression and human settlement, changes in suppression policies, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western US. Anthropogenic increases in temperature and vapor pressure deficit have significantly enhanced fuel aridity across western US forests over the past several decades. Comparing observational climate records to records recalculated after removal of modeled anthropogenic trends, we find that anthropogenic climate change accounted for approximately 55% of observed increases in the eight-metric mean fuel aridity during 1979-2015 across western US forests. This implicates anthropogenic climate change as an important driver of observed increases in fuel aridity, and also highlights the importance of natural multi-decadal climate variability in influencing trends in forest fire potential on the timescales of human lives. Based on a very strong (R2 = 0.76) and mechanistically reasonable relationship between interannual variability in the eight-metric mean fuel aridity and forest-fire area in the western US, we estimate that anthropogenic increases in fuel aridity contributed to an additional 4.2 million ha (95% confidence range: 2.7-6.5 million ha) of forest fire area during 1984-2015, nearly doubling the total forest fire area expected in the absence of anthropogenic climate change. The relationship between annual forest fire area and fuel aridity is exponential and the proportion of total forest area burned in a given year has grown rapidly over the past 32 years. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a chronic driver of increased forest fire activity and should continue to do so where fuels are not limiting.

Alternative characterization of forest fire regimes: incorporating spatial patterns

Treesearch

Brandon M. Collins; Jens T. Stevens; Jay D. Miller; Scott L. Stephens; Peter M. Brown; Malcolm P. North

2017-01-01

ContextThe proportion of fire area that experienced stand-replacing fire effects is an important attribute of individual fires and fire regimes in forests, and this metric has been used to group forest types into characteristic fire regimes. However, relying on proportion alone ignores important spatial characteristics...

A Tale of Two Forest Carbon Assessments in the Eastern United States: Forest Use Versus Cover as a Metric of Change

Treesearch

C. W. Woodall; B. F. Walters; M. B. Russell; J. W. Coulston; G. M. Domke; A. W. D' Amato; P. A. Sowers

2016-01-01

The dynamics of land-use practices (for example, forest versus settlements) is often a major driver of changes in terrestrial carbon (C). As the management and conservation of forest land uses are considered a means of reducing future atmospheric CO2 concentrations, the monitoring of forest C stocks and stock change by categories of land-use...

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

PubMed

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

2017-03-01

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

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

NASA Astrophysics Data System (ADS)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

Relating bat species presence to simple habitat measures in a central Appalachian forest

Treesearch

W. Mark Ford; Michael A. Menzel; Jane L. Rodrigue; Jennifer M. Menzel; Joshua B. Johnson; Joshua B. Johnson

2005-01-01

We actively sampled the bat community at 63 sites using detection and non- detection metrics on the Fernow Experimental Forest (FEF) in the central Appalachians of West Virginia using Anabat acoustical equipment May-June 2001-2003 to relate species presence to simple habitat measures such as proximity to riparian areas, forest canopy cover, forest canopy gap width, and...

Stream amphibians as metrics of critical biological thresholds in the Pacific Northwest, U.S.A.: a response to Kroll et al.

Treesearch

H. H. Welsh; G. R. Hodgson

2009-01-01

1. Kroll, Hayes & MacCracken (in press) Concerns regarding the use of amphibians as metrics of critical biological thresholds: a comment on Welsh and Hodgson 2008. Freshwater Biology, criticised our paper [Welsh & Hodgson (2008) Amphibians as metrics of critical biological thresholds in forested headwater streams of the...

Effects of land use, stream habitat, and water quality on biological communities of wadeable streams in the Illinois River Basin of Arkansas, 2011 and 2012

USGS Publications Warehouse

Petersen, James C.; Justus, B.G.; Meredith, Bradley J.

2014-01-01

The Illinois River Basin includes an area of diverse land use in northwestern Arkansas. Land-use data collected in 2006 indicate that most of the land in the basin is agricultural. The agricultural land is used primarily for production of poultry and cattle. Eighteen sites were selected from the list of candidate sites based on drainage area, land use, presence or absence of an upstream wastewater-treatment plant, water quality, and other information gathered during the reconnaissance. An important consideration in the process was to select sites along gradients of forest to urban land use and forest to agricultural land use. Water-quality samples were collected for analysis of nutrients, and a multiparameter field meter was used to measure water temperature, specific conductance, pH, and dissolved oxygen. Streamflow was measured immediately following the water-quality sampling. Macroalgae coverage was estimated and periphyton, macroinvertebrate, and fish communities were sampled at each site. Stream habitat also was assessed. Many types of land-use, water-quality, and habitat factors affected one or more aspects of the biological communities. Several macroinvertebrate and fish metrics changed in response to changes in percent forest; sites that would be considered most disturbed, based on these metrics, are sites with the highest percentages of urban land use in their associated basins. The presence of large mats of macroalgae was one of the most noticeable biological characteristics in several streams within the Illinois River Basin. The highest macroalgae percent cover values were recorded at four sites downstream from wastewater-treatment plants. Macroalgae percent cover was strongly correlated only with bed substrate size, canopy closure, and specific conductance. Periphyton metrics were most often and most strongly correlated with riparian shading, specific conductance, substrate turbidity, percent agriculture, poultry house density, and unpaved road density; some of these factors were strongly correlated with percent forest, percent urban, or percent agriculture. Total biovolume of periphyton was not strongly correlated with any of the land use, habitat, or water-quality factors assessed in the present study. Although algal growth typically increases with higher nutrient concentrations and less shading, the standing crop of periphyton on rocks can be reduced by herbivorous macroinvertebrates and fish, which may explain why total biovolume in Ozark streams was not strongly affected by water-quality (or other habitat) factors. A macroinvertebrate index and several macroinvertebrate metrics were adversely affected by increasing urban and agricultural land use and associated environmental factors. Factors most commonly affecting the index and metrics included factors associated with water quality, stream geometry, sediment, land-use percentages, and road density. In general, the macroinvertebrate index was higher (indicative of least disturbance) at sites with greater percentages of forest in their basins, lower percentages of urban land in their basins, and lower paved road density. Upstream wastewater-treatment plants affected several metrics. For example, three of the five lowest macroinvertebrate index scores, two of the five lowest percent predator values, and two of the five highest percent gatherer-collector values were at sites downstream from wastewater-treatment plants. The Ozark Highlands fish index of biotic integrity and several fish metrics were adversely affected by increasing urban and agricultural land use and associated factors. Factors affecting these metrics included factors associated with nutrients, sediment, and shading. In general, the fish index of biotic integrity was higher at sites with higher percentages of forest in their basins, lower percentages of urban land in their basins, higher unpaved road density, and lower paved and total road density. Upstream wastewater-treatment plants seemed to affect some fish community metrics substantially but had little effect on other metrics. For example, three of the five lowest relative abundances of lithophilic spawner minus stonerollers and four of the five highest stoneroller abundances were at sites downstream from wastewater-treatment plants. Interpretations of the results of the study described in this report are limited by a number of factors. These factors individually and collectively add to uncertainty and variability in the responses to various environmental stresses. Notwithstanding the limiting factors, the biological responses of macroalgae cover and periphyton, macroinvertebrate, and fish metrics to environmental variables provide multiple lines of evidence that biological communities of these streams are affected by recent and ongoing land-use practices. For several biological metrics there appears to be a threshold of about 40 to 50 percent forest where values of these metrics change in magnitude. However, the four sites with more than 50 percent forest in their basins were the four sites sampled in late May–early June of 2012 (rather than July–August of 2011). The relative influence of season and forest percentage on the biological communities at these sites is unknown.

Quantitative analysis of forest fragmentation in the atlantic forest reveals more threatened bird species than the current red list.

PubMed

Schnell, Jessica K; Harris, Grant M; Pimm, Stuart L; Russell, Gareth J

2013-01-01

Habitat loss and attendant fragmentation threaten the existence of many species. Conserving these species requires a straightforward and objective method that quantifies how these factors affect their survival. Therefore, we compared a variety of metrics that assess habitat fragmentation in bird ranges, using the geographical ranges of 127 forest endemic passerine birds inhabiting the Atlantic Forest of Brazil. A common, non-biological metric - cumulative area of size-ranked fragments within a species range - was misleading, as the least threatened species had the most habitat fragmentation. Instead, we recommend a modified version of metapopulation capacity. The metric links detailed spatial information on fragment sizes and spatial configuration to the birds' abilities to occupy and disperse across large areas (100,000+ km(2)). In the Atlantic Forest, metapopulation capacities were largely bimodal, in that most species' ranges had either low capacity (high risk of extinction) or high capacity (very small risk of extinction). This pattern persisted within taxonomically and ecologically homogenous groups, indicating that it is driven by fragmentation patterns and not differences in species ecology. Worryingly, we found IUCN considers some 28 of 58 species in the low metapopulation capacity cluster to not be threatened. We propose that assessing the effect of fragmentation will separate species more clearly into distinct risk categories than does a simple assessment of remaining habitat.

How livestock and flooding mediate the ecological integrity of working forests in Amazon River floodplains.

PubMed

Lucas, Christine M; Sheikh, Pervaze; Gagnon, Paul R; Mcgrath, David G

2016-01-01

The contribution of working forests to tropical conservation and development depends upon the maintenance of ecological integrity under ongoing land use. Assessment of ecological integrity requires an understanding of the structure, composition, and function and major drivers that govern their variability. Working forests in tropical river floodplains provide many goods and services, yet the data on the ecological processes that sustain these services is scant. In flooded forests of riverside Amazonian communities, we established 46 0.1-ha plots varying in flood duration, use by cattle and water buffalo, and time since agricultural abandonment (30-90 yr). We monitored three aspects of ecological integrity (stand structure, species composition, and dynamics of trees and seedlings) to evaluate the impacts of different trajectories of livestock activity (alleviation, stasis, and intensification) over nine years. Negative effects of livestock intensification were solely evident in the forest understory, and plots alleviated from past heavy disturbance increased in seedling density but had higher abundance of thorny species than plots maintaining low activity. Stand structure, dynamics, and tree species composition were strongly influenced by the natural pulse of seasonal floods, such that the defining characteristics of integrity were dependent upon flood duration (3-200 d). Forests with prolonged floods ≥ 140 d had not only lower species richness but also lower rates of recruitment and species turnover relative to forests with short floods <70 d. Overall, the combined effects of livestock intensification and prolonged flooding hindered forest regeneration, but overall forest integrity was largely related to the hydrological regime and age. Given this disjunction between factors mediating canopy and understory integrity, we present a subset of metrics for regeneration and recruitment to distinguish forest condition by livestock trajectory. Although our study design includes confounded factors that preclude a definitive assessment of the major drivers of ecological change, we provide much-needed data on the regrowth of a critical but poorly studied ecosystem. In addition to its emphasis on the dynamics of tropical wetland forests undergoing anthropogenic and environmental change, our case study is an important example for how to assess of ecological integrity in working forests of tropical ecosystems.

Relating injury to the forest ecosystem near Palmerton, PA, to zinc contamination from smelting

USGS Publications Warehouse

Beyer, W. Nelson; Krafft, Cairn; Klassen, Stephen; Green, Carrie E.; Chaney, Rufus L.

2011-01-01

The forest on Blue Mountain, near Lehigh Gap, has been injured by emissions from two historical zinc (Zn) smelters in Palmerton, PA, located at the northern base of the mountain. The uppermost mineral soil and lower litter from sites along a transect, just south of the ridgetop, contained from 64 to 4400 mg/kg Zn. We measured forest metrics at 15 sampling sites to ascertain how forest structure, species composition and regeneration are related to soil concentrations of Zn, the probable principal cause of the injury. Understanding how ecotoxicological injury is related to soil Zn concentrations helps us quantify the extent of injury to the ecosystem on Blue Mountain as well as to generalize to other sites. The sum of canopy closure and shrub cover, suggested as a broadly inclusive measure of forest structure, was decreased to half at approximately 2060 mg/kg Zn (102 mg/kg Sr(N03)2-extractable Zn). Tree-seedling density was decreased by 80% (from 10.5/m2 to 2.1/m2) at a much lower concentration: 1080 mg/kg Zn (59 mg/kg Sr(N03)2-extractable Zn). Changes in species composition and richness were not as useful for quantifying injury to the forest. Phytotoxicity, desiccation from exposure, and a gypsy moth infestation combined to form a barren area on the ridgetop. Liming the strongly acid Hazleton soils at the sites would partially ameliorate the observed phytotoxicity and should be considered in planning restoration.

Forests of Arkansas, 2013

Treesearch

James F. Rosson

2014-01-01

This resource update is a brief look at some of the basic metrics that describe the status of and changes to forest resources in Arkansas. Estimates presented here are for the measurement year 2013 with resource changes compared against the 2012 survey year. This information is based on field data collected using the Forest Inventory and Analysis (FIA) annualized...

Forests of Arkansas, 2014

Treesearch

James F. Rosson

2015-01-01

This resource update is a brief look at some of the basic metrics that describe the status of and changes to forest resources in Arkansas. Estimates presented here are for the measurement year 2014 with resource changes compared against the 2013 survey year. This information is based on field data collected using the Forest Inventory and Analysis (FIA) annualized...

A PRELIMINARY ASSESSMENT OF THE MONTREAL PROCESS INDICATORS OF FOREST FRAGMENTATION FOR THE UNITED STATES

EPA Science Inventory

As part of the 2003 U.S. Report on Sustainable Forests, four metrics of forest fragmentation patch size, edge amount, inter-patch contrast - were measured within 142,602 non overlapping 56.25 km2 analysis units on land-cover maps derived from satellite imagery for the 48 contermi...

Landscape-level regeneration adequacy for native hardwood forests of Pennsylvania

Treesearch

William H. McWilliams; Todd W. Bowersox; David A. Gansner; Larry H. McCormick; Susan L. Stout

1995-01-01

Studies of advance regeneration and post-disturbance regeneration adequacy were conducted during the recent USDA Forest Service inventory of forest resources in Pennsylvania. The first study examined advance tree-seedling regeneration in stands where stocking levels would suggest that advance regeneration should be abundant. A range of metrics was used to describe...

Exploring the relationship between parcelization metrics and natural resource managers' perceptions of forest land parcelization intensity

Treesearch

Michael A. Kilgore; Stephanie A. Snyder

2016-01-01

A major challenge associated with forest land parcelization, defined as the subdivision of forest land holdings into smaller ownership parcels, is that little information exists on how to measure its severity and judge its impacts across forest landscapes. To address this information gap, an on-line survey presented field-based public natural resource managers in the...

Impact of ecological and socioeconomic determinants on the spread of tallow tree in southern forest lands

Treesearch

Yuan Tan; Joseph Z. Fan; Christopher M. Oswalt

2010-01-01

Based on USDA Forest Service Forest Inventory and Analysis (FIA) database, relationships between the presence of tallow tree and related driving variables including forest landscape metrics, stand and site conditions, as well as natural and anthropogenic disturbances were analyzed for the southern states infested by tallow trees. Of the 9,966 re-measured FIA plots in...

QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

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

Lee Spangler; Lee A. Vierling; Eva K. Stand

2012-04-01

Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 acrossmore » {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density between the 2003 and 2009 did not affect the biomass estimates. Overall, LiDAR data coupled with field reference data offer a powerful method for calculating pools and changes in aboveground carbon in forested systems. The results of our study suggest that multitemporal LiDAR-based approaches are likely to be useful for high quality estimates of aboveground carbon change in conifer forest systems.« less

Abiotic and biotic determinants of coarse woody productivity in temperate mixed forests.

PubMed

Yuan, Zuoqiang; Ali, Arshad; Wang, Shaopeng; Gazol, Antonio; Freckleton, Robert; Wang, Xugao; Lin, Fei; Ye, Ji; Zhou, Li; Hao, Zhanqing; Loreau, Michel

2018-07-15

Forests play an important role in regulating the global carbon cycle. Yet, how abiotic (i.e. soil nutrients) and biotic (i.e. tree diversity, stand structure and initial biomass) factors simultaneously contribute to aboveground biomass (coarse woody) productivity, and how the relative importance of these factors changes over succession remain poorly studied. Coarse woody productivity (CWP) was estimated as the annual aboveground biomass gain of stems using 10-year census data in old growth and secondary forests (25-ha and 4.8-ha, respectively) in northeast China. Boosted regression tree (BRT) model was used to evaluate the relative contribution of multiple metrics of tree diversity (taxonomic, functional and phylogenetic diversity and trait composition as well as stand structure attributes), stand initial biomass and soil nutrients on productivity in the studied forests. Our results showed that community-weighted mean of leaf phosphorus content, initial stand biomass and soil nutrients were the three most important individual predictors for CWP in secondary forest. Instead, initial stand biomass, rather than diversity and functional trait composition (vegetation quality) was the most parsimonious predictor of CWP in old growth forest. By comparing the results from secondary and old growth forest, the summed relative contribution of trait composition and soil nutrients on productivity decreased as those of diversity indices and initial biomass increased, suggesting the stronger effect of diversity and vegetation quantity over time. Vegetation quantity, rather than diversity and soil nutrients, is the main driver of forest productivity in temperate mixed forest. Our results imply that diversity effect for productivity in natural forests may not be so important as often suggested, at least not during the later stage of forest succession. This finding suggests that as a change of the importance of different divers of productivity, the environmentally driven filtering decreases and competitively driven niche differentiation increases with forest succession. Copyright © 2018 Elsevier B.V. All rights reserved.

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

Effects of Stream and Elevation Resolution on Riparian Metrics and Restoration Identification

EPA Science Inventory

Even though riparian areas attenuate nutrients and sediments from agricultural runoff at the field scale, best management practices and locations for restoring riparian areas should be determined at watershed scales. Riparian metrics (e.g., percent forest within 100m of stream)...

Effects of historic forest disturbance on water quality and flow in the Interior Western U.S

Treesearch

M. Matyjasik; G. Moisen; C. Combe; T. Hathcock; S. Mitts; M. Hernandez; T. Frescino; T. Schroeder

2014-01-01

Water quality and flow is affected my many complex factors in the Interior Western U.S. While many studies focus on individual water parameters response to a limited number of changing conditions, little work looks at long term effects of diverse forest disturbances on a broader array of water quality and flow metrics. The U.S. Forest Service Forest Inventory and...

Forests of Arkansas, 2016

Treesearch

James F. Rosson

2017-01-01

This resource update is a brief look at some of the basic metrics that describe the status of and changes to forest resources in Arkansas. Estimates presented here are for the survey year 2016 with resource changes compared against the 2015 survey year. This information is based on field data collected using the Forest Inventory and Analysis (FIA) annualized sample...

Arkansas, 2011 forest inventory and analysis factsheet

Treesearch

James F. Rosson

2012-01-01

This annual factsheet is a brief look at some of the basic metrics that describe the status of and changes to forest resources in Arkansas. Estimates presented here are for the measurement year 2011 with resource changes compared against the 2010 survey year. Information for the factsheet is updated every year by means of the Forest Inventory and Analysis (FIA)...

Arkansas, 2012 forest inventory and analysis factsheet

Treesearch

James F. Rosson

2013-01-01

This annual factsheet is a brief look at some of the basic metrics that describe the status and trends of forest resources in Arkansas. Estimates presented here are for the measurement year 2012 with resource changes compared against the 2011 survey year. Information for the factsheet is updated every year by means of the Forest Inventory and Analysis (FIA) annualized...

Arkansas, 2010 forest inventory and analysis factsheet

Treesearch

James F. Rosson

2011-01-01

This annual factsheet is a brief look at some of the basic metrics that describe forest resources in Arkansas. Estimates presented here are for the measurement year 2010 with resource changes compared against the 2009 survey year. Factsheet information is updated every year by means of the Forest Inventory and Analysis (FIA) annualized sample design. Arkansas has about...

Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest

Treesearch

Brian M. Wing; Martin W. Ritchie; Kevin Boston; Warren B. Cohen; Alix Gitelman; Michael J. Olsen

2012-01-01

Forest understory communities are important components in forest ecosystems providing wildlife habitat and influencing nutrient cycling, fuel loadings, fire behavior and tree species composition over time. One of the most widely utilized understory component metrics is understory vegetation cover, often used as a measure of vegetation abundance. To date, understory...

Stabilization of a locally minimal forest

NASA Astrophysics Data System (ADS)

Ivanov, A. O.; Mel'nikova, A. E.; Tuzhilin, A. A.

2014-03-01

The method of partial stabilization of locally minimal networks, which was invented by Ivanov and Tuzhilin to construct examples of shortest trees with given topology, is developed. According to this method, boundary vertices of degree 2 are not added to all edges of the original locally minimal tree, but only to some of them. The problem of partial stabilization of locally minimal trees in a finite-dimensional Euclidean space is solved completely in the paper, that is, without any restrictions imposed on the number of edges remaining free of subdivision. A criterion for the realizability of such stabilization is established. In addition, the general problem of searching for the shortest forest connecting a finite family of boundary compact sets in an arbitrary metric space is formalized; it is shown that such forests exist for any family of compact sets if and only if for any finite subset of the ambient space there exists a shortest tree connecting it. The theory developed here allows us to establish further generalizations of the stabilization theorem both for arbitrary metric spaces and for metric spaces with some special properties. Bibliography: 10 titles.

Large Footprint LiDAR Data Processing for Ground Detection and Biomass Estimation

NASA Astrophysics Data System (ADS)

Zhuang, Wei

Ground detection in large footprint waveform Light Detection And Ranging (LiDAR) data is important in calculating and estimating downstream products, especially in forestry applications. For example, tree heights are calculated as the difference between the ground peak and first returned signal in a waveform. Forest attributes, such as aboveground biomass, are estimated based on the tree heights. This dissertation investigated new metrics and algorithms for estimating aboveground biomass and extracting ground peak location in large footprint waveform LiDAR data. In the first manuscript, an accurate and computationally efficient algorithm, named Filtering and Clustering Algorithm (FICA), was developed based on a set of multiscale second derivative filters for automatically detecting the ground peak in an waveform from Land, Vegetation and Ice Sensor. Compared to existing ground peak identification algorithms, FICA was tested in different land cover type plots and showed improved accuracy in ground detections of the vegetation plots and similar accuracy in developed area plots. Also, FICA adopted a peak identification strategy rather than following a curve-fitting process, and therefore, exhibited improved efficiency. In the second manuscript, an algorithm was developed specifically for shrub waveforms. The algorithm only partially fitted the shrub canopy reflection and detected the ground peak by investigating the residual signal, which was generated by deducting a Gaussian fitting function from the raw waveform. After the deduction, the overlapping ground peak was identified as the local maximum of the residual signal. In addition, an applicability model was built for determining waveforms where the proposed PCF algorithm should be applied. In the third manuscript, a new set of metrics was developed to increase accuracy in biomass estimation models. The metrics were based on the results of Gaussian decomposition. They incorporated both waveform intensity represented by the area covered by a Gaussian function and its associated heights, which was the centroid of the Gaussian function. By considering signal reflection of different vegetation layers, the developed metrics obtained better estimation accuracy in aboveground biomass when compared to existing metrics. In addition, the new developed metrics showed strong correlation with other forest structural attributes, such as mean Diameter at Breast Height (DBH) and stem density. In sum, the dissertation investigated the various techniques for large footprint waveform LiDAR processing for detecting the ground peak and estimating biomass. The novel techniques developed in this dissertation showed better performance than existing methods or metrics.

Influences of scale on bat habitat relationships in a forested landscape in Nicaragua

Treesearch

Carol L. Chambers; Samuel A. Cushman; Arnulfo Medina-Fitoria; Jose Martinez-Fonseca; Marlon Chavez-Velasquez

2016-01-01

Scale dependence of bat habitat selection is poorly known with few studies evaluating relationships among landscape metrics such as class versus landscape, or metrics that measure composition or configuration. This knowledge can inform conservation approaches to mitigate habitat loss and fragmentation.

Modeling the Effects of Drought, Fire, Beetles, and Management on Future Carbon Cycling in the Western US

NASA Astrophysics Data System (ADS)

Buotte, P.; Law, B. E.; Hicke, J. A.; Hudiburg, T. W.; Levis, S.; Kent, J.

2017-12-01

Fire and beetle outbreaks can have substantial impacts on forest structure, composition, and function and these types of disturbances are expected to increase in the future. Therefore understanding the ecological impacts of these disturbances into the future is important. We used ecosystem process modeling to estimate the future occurrence of fire and beetle outbreaks and their impacts on forest resilience and carbon sequestration. We modified the Community Land Model (CLM4.5) to better represent forest growth and mortality in the western US through multiple avenues: 1) we increased the ecological resolution to recognize 14 forest types common to the region; 2) we improved CLM4.5's ability to handle drought stress by adding forest type-specific controls on stomatal conductance and increased rates of leaf shed during periods of low soil moisture; 3) we developed and implemented a mechanistic model of beetle population growth and subsequent tree mortality; 4) we modified the current fire module to account for more refined forest types; and 5) we developed multiple scenarios of harvest based on past harvest rates and proposed changes in land management policies. We ran CLM4.5 in offline mode with climate forcing data. We compare future forest growth rates and carbon sequestration with historical metrics to estimate the combined influence of future disturbances on forest composition and carbon sequestration in the western US.

Canopy structural complexity predicts forest canopy light absorption at continental scales

NASA Astrophysics Data System (ADS)

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

2017-12-01

Understanding how the physical structure of forest canopies influence light acquisition is a long-standing area of inquiry fundamental to advancing understanding of many areas of the physical sciences, including the modeling and interpretation of biogeochemical cycles. Conventional measures of forest canopy structure employed in earth system models are often limited to leaf area index (LAI)—a measure of the quantity of leaves in the canopy. However, more novel multi-dimensional measures of canopy structural complexity (CSC) that describe the arrangement of vegetation are now possible because of technological advances, and may improve modeled estimates of canopy light absorption. During 2016 and 2017, we surveyed forests at sites from across the eastern, southern, and midwestern United States using portable canopy LiDAR (PCL). This survey included 14 National Ecological Observation Network (NEON), Long-Term Ecological Research Network (LTER,) Ameriflux, and University affiliated sites. Our findings show that a composite model including CSC parameters and LAI explains 96.8% of the variance in light acquisition, measured as the fraction of photosynthetically absorbed radiation (fPAR) at the continental scale, and improvement of 12% over an LAI only model. Under high light sky conditions, measures of CSC are more strongly coupled with light acquisition than under low light, possibly because light scattering partially decouples CSC from canopy light absorption under low, predominately diffuse light conditions. We conclude that scalable estimates of CSC metrics may improve continent-wide estimates of canopy light absorption and, therefore, carbon uptake, with implications for remote sensing and earth system modeling.

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.

CW-SSIM kernel based random forest for image classification

NASA Astrophysics Data System (ADS)

Fan, Guangzhe; Wang, Zhou; Wang, Jiheng

2010-07-01

Complex wavelet structural similarity (CW-SSIM) index has been proposed as a powerful image similarity metric that is robust to translation, scaling and rotation of images, but how to employ it in image classification applications has not been deeply investigated. In this paper, we incorporate CW-SSIM as a kernel function into a random forest learning algorithm. This leads to a novel image classification approach that does not require a feature extraction or dimension reduction stage at the front end. We use hand-written digit recognition as an example to demonstrate our algorithm. We compare the performance of the proposed approach with random forest learning based on other kernels, including the widely adopted Gaussian and the inner product kernels. Empirical evidences show that the proposed method is superior in its classification power. We also compared our proposed approach with the direct random forest method without kernel and the popular kernel-learning method support vector machine. Our test results based on both simulated and realworld data suggest that the proposed approach works superior to traditional methods without the feature selection procedure.

Relationships between common forest metrics and realized impacts of Hurricane Katrina on forest resources in Mississippi

Treesearch

Sonja N. Oswalt; Christopher M. Oswalt

2008-01-01

This paper compares and contrasts hurricane-related damage recorded across the Mississippi landscape in the 2 years following Katrina with initial damage assessments based on modeled parameters by the USDA Forest Service. Logistic and multiple regressions are used to evaluate the influence of stand characteristics on tree damage probability. Specifically, this paper...

Conducting tests for statistically significant differences using forest inventory data

Treesearch

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Virginia, 2012 - forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2014-01-01

This science update is a brief look at some of the basic metrics that describe the status of and changes in forest resources in Virginia. Estimates presented here are for the measurement year 2012. Information for the factsheets is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel)...

Virginia, 2011 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2013-01-01

This science update is a brief look at some of the basic metrics that describe the status and trends of forest resources in Virginia. Estimates presented here are for the measurement year 2011. Information for the factsheets is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in...

Virginia, 2010 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2012-01-01

This science update is a brief look at some of the basic metrics that describe the status of forest resources in Virginia. Estimates presented here are for the measurement year 2010. Information for this factsheet is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Virginia has about 4,600 sample plots across the State and each year...

Virginia, 2009 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2011-01-01

This science update is a brief look at some of the basic metrics that describe forest resources in Virginia. Estimates presented here are for the measurement year 2009. Information for the factsheet is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Virginia has about 4,600 sample plots across the State, and each year 20 percent of...

Forests and carbon storage

Treesearch

Michael G. Ryan

2008-01-01

Forests store much carbon and their growth can be a carbon sink if disturbance or harvesting has killed or removed trees or if trees that can now regrow are planted where they did not historically occur. Forests and long-lived wood products currently offset 310 million metric tons of U.S. fossil fuel emissions of carbon--20 percent of the total (Pacala et al. 2007)....

Using landscape metrics to model source habitat for Neotropical migrants in the midwestern U.S.

Treesearch

Peter T. Fauth; Eric J. Gustafson; Kerry N. Rabenold

2000-01-01

Size of a forest patch is a useful predictor of density and reproductive success of Neotropical migratory birds in much of eastern North America. Within these forested landscapes, large forest tracts appear to be sources-fragments in which surpluses of offspring are produced and can potentially colonize new fragments including woodlot sinks where reproduction fails to...

Response of forest soil properties to urbanization gradients in three metropolitan areas

Treesearch

Richard V. Pouyat; Ian D. Yesilonis; Katalin Szlavecz; Csaba Csuzdi; Elizabeth Hornung; Zoltan Kors& #243; s; Jonathan Russell-Anelli; Vincent Giorgio

2008-01-01

We investigated the effects of urban environments on the chemical properties of forest soils in the metropolitan areas of Baltimore, New York, and Budapest. We hypothesized that soils in forest patches in each city will exhibit changes in chemistry corresponding to urbanization gradients, but more strongly with various urban metrics than distance to the urban core....

Forest carbon benefits, costs and leakage effects of carbon reserve scenarios in the United States

Treesearch

Prakash Nepal; Peter J. Ince; Kenneth E. Skog; Sun J. Chang

2013-01-01

This study evaluated the potential effectiveness of future carbon reserve scenarios, where U.S. forest landowners would hypothetically be paid to sequester carbon on their timberland and forego timber harvests for 100 years. Scenarios featured direct payments to landowners of $0 (baseline), $5, $10, or $15 per metric ton of additional forest carbon sequestered on the...

Predicting forest height using the GOST, Landsat 7 ETM+, and airborne LiDAR for sloping terrains in the Greater Khingan Mountains of China

NASA Astrophysics Data System (ADS)

Gu, Chengyan; Clevers, Jan G. P. W.; Liu, Xiao; Tian, Xin; Li, Zhouyuan; Li, Zengyuan

2018-03-01

Sloping terrain of forests is an overlooked factor in many models simulating the canopy bidirectional reflectance distribution function, which limits the estimation accuracy of forest vertical structure parameters (e.g., forest height). The primary objective of this study was to predict forest height on sloping terrain over large areas with the Geometric-Optical Model for Sloping Terrains (GOST) using airborne Light Detection and Ranging (LiDAR) data and Landsat 7 imagery in the western Greater Khingan Mountains of China. The Sequential Maximum Angle Convex Cone (SMACC) algorithm was used to generate image endmembers and corresponding abundances in Landsat imagery. Then, LiDAR-derived forest metrics, topographical factors and SMACC abundances were used to calibrate and validate the GOST, which aimed to accurately decompose the SMACC mixed forest pixels into sunlit crown, sunlit background and shade components. Finally, the forest height of the study area was retrieved based on a back-propagation neural network and a look-up table. Results showed good performance for coniferous forests on all slopes and at all aspects, with significant coefficients of determination above 0.70 and root mean square errors (RMSEs) between 0.50 m and 1.00 m based on ground observed validation data. Higher RMSEs were found in areas with forest heights below 5 m and above 17 m. For 90% of the forested area, the average RMSE was 3.58 m. Our study demonstrates the tremendous potential of the GOST for quantitative mapping of forest height on sloping terrains with multispectral and LiDAR inputs.

Assessing the habitat suitability of agricultural landscapes for characteristic breeding bird guilds using landscape metrics.

PubMed

Borges, Friederike; Glemnitz, Michael; Schultz, Alfred; Stachow, Ulrich

2017-04-01

Many of the processes behind the decline of farmland birds can be related to modifications in landscape structure (composition and configuration), which can partly be expressed quantitatively with measurable or computable indices, i.e. landscape metrics. This paper aims to identify statistical relationships between the occurrence of birds and the landscape structure. We present a method that combines two comprehensive procedures: the "landscape-centred approach" and "guild classification". Our study is based on more than 20,000 individual bird observations based on a 4-year bird monitoring approach in a typical agricultural area in the north-eastern German lowlands. Five characteristic bird guilds, each with three characteristic species, are defined for the typical habitat types of that area: farmland, grassland, hedgerow, forest and settlement. The suitability of each sample plot for each guild is indicated by the level of persistence (LOP) of occurrence of three respective species. Thus, the sample plots can be classified as "preferred" or "less preferred" depending on the lower and upper quartiles of the LOP values. The landscape structure is characterized by 16 different landscape metrics expressing various aspects of landscape composition and configuration. For each guild, the three landscape metrics with the strongest rank correlation with the LOP values and that are not mutually dependent were identified. For four of the bird guilds, the classification success was better than 80%, compared with only 66% for the grassland bird guild. A subset of six landscape metrics proved to be the most meaningful and sufficiently classified the sample areas with respect to bird guild suitability. In addition, derived logistic functions allowed the production of guild-specific habitat suitability maps for the whole landscape. The analytical results show that the proposed approach is appropriate to assess the habitat suitability of agricultural landscapes for characteristic bird guilds.

Relating injury to the forest ecosystem near Palmerton, PA, to zinc contamination from smelting.

PubMed

Beyer, W Nelson; Krafft, Cairn; Klassen, Stephen; Green, Carrie E; Chaney, Rufus L

2011-10-01

The forest on Blue Mountain, near Lehigh Gap, has been injured by emissions from two historical zinc (Zn) smelters in Palmerton, PA, located at the northern base of the mountain. The uppermost mineral soil and lower litter from sites along a transect, just south of the ridgetop, contained from 64 to 4400 mg/kg Zn. We measured forest metrics at 15 sampling sites to ascertain how forest structure, species composition and regeneration are related to soil concentrations of Zn, the probable principal cause of the injury. Understanding how ecotoxicological injury is related to soil Zn concentrations helps us quantify the extent of injury to the ecosystem on Blue Mountain as well as to generalize to other sites. The sum of canopy closure and shrub cover, suggested as a broadly inclusive measure of forest structure, was decreased to half at approximately 2060 mg/kg Zn (102 mg/kg Sr(N0(3))(2)-extractable Zn). Tree-seedling density was decreased by 80% (from 10.5/m(2) to 2.1/m(2)) at a much lower concentration: 1080 mg/kg Zn (59 mg/kg Sr(N0(3))(2)-extractable Zn). Changes in species composition and richness were not as useful for quantifying injury to the forest. Phytotoxicity, desiccation from exposure, and a gypsy moth infestation combined to form a barren area on the ridgetop. Liming the strongly acid Hazleton soils at the sites would partially ameliorate the observed phytotoxicity and should be considered in planning restoration. © Springer Science+Business Media, LLC (outside the USA) 2011

Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes

NASA Astrophysics Data System (ADS)

Meyer, Victoria; Saatchi, Sassan; Clark, David B.; Keller, Michael; Vincent, Grégoire; Ferraz, António; Espírito-Santo, Fernando; d'Oliveira, Marcus V. N.; Kaki, Dahlia; Chave, Jérôme

2018-06-01

Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (˜ 25-30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha-1, bias = -0.63 Mg ha-1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA-AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.

Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar

PubMed Central

Kristensen, Terje; Næsset, Erik; Ohlson, Mikael; Bolstad, Paul V.; Kolka, Randall

2015-01-01

A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C. PMID:26426532

Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar.

PubMed

Kristensen, Terje; Næsset, Erik; Ohlson, Mikael; Bolstad, Paul V; Kolka, Randall

2015-01-01

A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

Semi-automated stand delineation in Mediterranean Pinus sylvestris plantations through segmentation of LiDAR data: The influence of pulse density

NASA Astrophysics Data System (ADS)

Varo-Martínez, Mª Ángeles; Navarro-Cerrillo, Rafael M.; Hernández-Clemente, Rocío; Duque-Lazo, Joaquín

2017-04-01

Traditionally, forest-stand delineation has been assessed based on orthophotography. The application of LiDAR has improved forest management by providing high-spatial-resolution data on the vertical structure of the forest. The aim of this study was to develop and test a semi-automated algorithm for stands delineation in a plantation of Pinus sylvestris L. using LiDAR data. Three specific objectives were evaluated, i) to assess two complementary LiDAR metrics, Assmann dominant height and basal area, for the characterization of the structure of P. sylvestris Mediterranean forests based on object-oriented segmentation, ii) to evaluate the influence of the LiDAR pulse density on forest-stand delineation accuracy, and iii) to investigate the algorithmś effectiveness in the delineation of P. sylvestris stands for map prediction of Assmann dominant height and basal area. Our results show that it is possible to generate accurate P. sylvestris forest-stand segmentations using multiresolution or mean shift segmentation methods, even with low-pulse-density LiDAR - which is an important economic advantage for forest management. However, eCognition multiresolution methods provided better results than the OTB (Orfeo Tool Box) for stand delineation based on dominant height and basal area estimations. Furthermore, the influence of pulse density on the results was not statistically significant in the basal area calculations. However, there was a significant effect of pulse density on Assmann dominant height [F2,9595 = 5.69, p = 0.003].for low pulse density. We propose that the approach shown here should be considered for stand delineation in other large Pinus plantations in Mediterranean regions with similar characteristics.

Aboveground Biomass Estimation Using Reconstructed Feature of Airborne Discrete-Return LIDAR by Auto-Encoder Neural Network

NASA Astrophysics Data System (ADS)

Li, T.; Wang, Z.; Peng, J.

2018-04-01

Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision AGB estimation. Most of the researches estimate AGB by the feature metrics extracted from the canopy height distribution of the point cloud which calculated based on precise digital terrain model (DTM). However, if forest canopy density is high, the probability of the LiDAR signal penetrating the canopy is lower, resulting in ground points is not enough to establish DTM. Then the distribution of forest canopy height is imprecise and some critical feature metrics which have a strong correlation with biomass such as percentiles, maximums, means and standard deviations of canopy point cloud can hardly be extracted correctly. In order to address this issue, we propose a strategy of first reconstructing LiDAR feature metrics through Auto-Encoder neural network and then using the reconstructed feature metrics to estimate AGB. To assess the prediction ability of the reconstructed feature metrics, both original and reconstructed feature metrics were regressed against field-observed AGB using the multiple stepwise regression (MS) and the partial least squares regression (PLS) respectively. The results showed that the estimation model using reconstructed feature metrics improved R2 by 5.44 %, 18.09 %, decreased RMSE value by 10.06 %, 22.13 % and reduced RMSEcv by 10.00 %, 21.70 % for AGB, respectively. Therefore, reconstructing LiDAR point feature metrics has potential for addressing AGB estimation challenge in dense canopy area.

Diatom Responses to Watershed Development and Potential Moderating Effects of Near-Stream Forest and Wetland Cover

EPA Science Inventory

Watershed development alters hydrology and delivers anthropogenic stressors to streams via pathways affected by impervious cover. We characterized relationships of diatom communities and metrics with upstream watershed % impervious cover (IC) and with riparian % forest and wetlan...

Is there a better metric than site index to indicate the productivity of forested lands?

Treesearch

Maria E. Blanco Martin; Michael Hoppus; Andrew Lister; James A. Westfall

2009-01-01

The Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program selects site trees for each plot that are used to measure site productivity. The ability of a site to produce wood volume is indicated indirectly by comparing total tree height with tree age. This comparison assumes that the rate of height growth is strongly related to...

New exposure-based metric approach for evaluating O3 risk to North American aspen forests

Treesearch

K.E. Percy; M. Nosal; W. Heilman; T. Dann; J. Sober; A.H. Legge; D.F. Karnosky

2007-01-01

The United States and Canada currently use exposure-based metrics to protect vegetation from O3. Using 5 years (1999-2003) of co-measured O3, meteorology and growth response, we have developed exposure-based regression models that predict Populus tremuloides growth change within the North American ambient...

Climate warming feedback from mountain birch forest expansion: reduced albedo dominates carbon uptake.

PubMed

de Wit, Heleen A; Bryn, Anders; Hofgaard, Annika; Karstensen, Jonas; Kvalevåg, Maria M; Peters, Glen P

2014-07-01

Expanding high-elevation and high-latitude forest has contrasting climate feedbacks through carbon sequestration (cooling) and reduced surface reflectance (warming), which are yet poorly quantified. Here, we present an empirically based projection of mountain birch forest expansion in south-central Norway under climate change and absence of land use. Climate effects of carbon sequestration and albedo change are compared using four emission metrics. Forest expansion was modeled for a projected 2.6 °C increase in summer temperature in 2100, with associated reduced snow cover. We find that the current (year 2000) forest line of the region is circa 100 m lower than its climatic potential due to land-use history. In the future scenarios, forest cover increased from 12% to 27% between 2000 and 2100, resulting in a 59% increase in biomass carbon storage and an albedo change from 0.46 to 0.30. Forest expansion in 2100 was behind its climatic potential, forest migration rates being the primary limiting factor. In 2100, the warming caused by lower albedo from expanding forest was 10 to 17 times stronger than the cooling effect from carbon sequestration for all emission metrics considered. Reduced snow cover further exacerbated the net warming feedback. The warming effect is considerably stronger than previously reported for boreal forest cover, because of the typically low biomass density in mountain forests and the large changes in albedo of snow-covered tundra areas. The positive climate feedback of high-latitude and high-elevation expanding forests with seasonal snow cover exceeds those of afforestation at lower elevation, and calls for further attention of both modelers and empiricists. The inclusion and upscaling of these climate feedbacks from mountain forests into global models is warranted to assess the potential global impacts. © 2013 John Wiley & Sons Ltd.

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

Forests growing under dry conditions have higher hydrological resilience to drought than do more humid forests.

PubMed

Helman, David; Lensky, Itamar M; Yakir, Dan; Osem, Yagil

2017-07-01

More frequent and intense droughts are projected during the next century, potentially changing the hydrological balances in many forested catchments. Although the impacts of droughts on forest functionality have been vastly studied, little attention has been given to studying the effect of droughts on forest hydrology. Here, we use the Budyko framework and two recently introduced Budyko metrics (deviation and elasticity) to study the changes in the water yields (rainfall minus evapotranspiration) of forested catchments following a climatic drought (2006-2010) in pine forests distributed along a rainfall gradient (P = 280-820 mm yr -1 ) in the Eastern Mediterranean (aridity factor = 0.17-0.56). We use a satellite-based model and meteorological information to calculate the Budyko metrics. The relative water yield ranged from 48% to 8% (from the rainfall) in humid to dry forests and was mainly associated with rainfall amount (increasing with increased rainfall amount) and bedrock type (higher on hard bedrocks). Forest elasticity was larger in forests growing under drier conditions, implying that drier forests have more predictable responses to drought, according to the Budyko framework, compared to forests growing under more humid conditions. In this context, younger forests were shown more elastic than older forests. Dynamic deviation, which is defined as the water yield departure from the Budyko curve, was positive in all forests (i.e., less-than-expected water yields according to Budyko's curve), increasing with drought severity, suggesting lower hydrological resistance to drought in forests suffering from larger rainfall reductions. However, the dynamic deviation significantly decreased in forests that experienced relatively cooler conditions during the drought period. Our results suggest that forests growing under permanent dry conditions might develop a range of hydrological and eco-physiological adjustments to drought leading to higher hydrological resilience. In the context of predicted climate change, such adjustments are key factors in sustaining forested catchments in water-limited regions. © 2016 John Wiley & Sons Ltd.

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.

Mining-caused changes to habitat structure affect amphibian and reptile population ecology more than metal pollution.

PubMed

Sasaki, Kiyoshi; Lesbarrères, David; Watson, Glen; Litzgus, Jacqueline

2015-12-01

Emissions from smelting not only contaminate water and soil with metals, but also induce extensive forest dieback and changes in resource availability and microclimate. The relative effects of such co-occurring stressors are often unknown, but this information is imperative in developing targeted restoration strategies. We assessed the role and relative effects of structural alterations of terrestrial habitat and metal pollution caused by century-long smelting operations on amphibian and reptile communities by collecting environmental and time- and area-standardized multivariate abundance data along three spatially replicated impact gradients. Overall, species richness, diversity, and abundance declined progressively with increasing levels of metals (As, Cu, and Ni) and soil temperature (T(s)) and decreasing canopy cover, amount of coarse woody debris (CWD), and relative humidity (RH). The composite habitat variable (which included canopy cover, CWD, T(s), and RH) was more strongly associated with most response metrics than the composite metal variable (As, Cu, and Ni), and canopy cover alone explained 19-74% of the variance. Moreover, species that use terrestrial habitat for specific behaviors (e.g., hibernation, dispersal), especially forest-dependent species, were more severely affected than largely aquatic species. These results suggest that structural alterations of terrestrial habitat and concomitant changes in the resource availability and microclimate have stronger effects than metal pollution per se. Furthermore, much of the variation in response metrics was explained by the joint action of several environmental variables, implying synergistic effects (e.g., exacerbation of metal toxicity by elevated temperatures in sites with reduced canopy cover). We thus argue that the restoration of terrestrial habitat conditions is a key to successful recovery of herpetofauna communities in smelting-altered landscapes.

A study of stability effects in forested terrain

NASA Astrophysics Data System (ADS)

Desmond, Cian J.; Watson, Simon

2014-12-01

Data from four well instrumented met masts located in heavily forested European sites in different locations and terrain types are examined. Seven stability metrics are applied to the data sets and a novel method is used to identify the metric which most consistently identifies stability events of importance for wind energy generation. It was found that the Obukhov length, as calculated by fast response sonic anemometer, provides the most reliable results in these highly complex sites. It was also found that non-neutral stabilities can be expected a significant portion of the time for wind speeds of less than 10 m/s at the considered sites.

Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales

USGS Publications Warehouse

Li, Aihua; Dhakal, Shital; Glenn, Nancy F.; Spaete, Luke P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

2017-01-01

Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.

Empirical Evaluation of Hunk Metrics as Bug Predictors

NASA Astrophysics Data System (ADS)

Ferzund, Javed; Ahsan, Syed Nadeem; Wotawa, Franz

Reducing the number of bugs is a crucial issue during software development and maintenance. Software process and product metrics are good indicators of software complexity. These metrics have been used to build bug predictor models to help developers maintain the quality of software. In this paper we empirically evaluate the use of hunk metrics as predictor of bugs. We present a technique for bug prediction that works at smallest units of code change called hunks. We build bug prediction models using random forests, which is an efficient machine learning classifier. Hunk metrics are used to train the classifier and each hunk metric is evaluated for its bug prediction capabilities. Our classifier can classify individual hunks as buggy or bug-free with 86 % accuracy, 83 % buggy hunk precision and 77% buggy hunk recall. We find that history based and change level hunk metrics are better predictors of bugs than code level hunk metrics.

Estimating Carbon Flux Phenology with Satellite-Derived Land Surface Phenology and Climate Drivers for Different Biomes: A Synthesis of AmeriFlux Observations

PubMed Central

Zhu, Wenquan; Chen, Guangsheng; Jiang, Nan; Liu, Jianhong; Mou, Minjie

2013-01-01

Carbon Flux Phenology (CFP) can affect the interannual variation in Net Ecosystem Exchange (NEE) of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP) metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands), using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU) by more than 70% and End of Carbon Uptake (ECU) by more than 60%. The Root Mean Square Error (RMSE) of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data. PMID:24386441

Estimating Carbon Flux Phenology with Satellite-Derived Land Surface Phenology and Climate Drivers for Different Biomes: A Synthesis of AmeriFlux Observations

DOE PAGES

Zhu, Wenquan; Chen, Guangsheng; Jiang, Nan; ...

2013-12-27

Carbon Flux Phenology (CFP) can affect the interannual variation in Net Ecosystem Exchange (NEE) of carbon between terrestrial ecosystems and the atmosphere. In this paper, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP) metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands), using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU) by more than 70% and End of Carbon Uptakemore » (ECU) by more than 60%. The Root Mean Square Error (RMSE) of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. In conclusion, this methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.« less

Enzyme polymorphism in forest trees

Treesearch

M. T. Conkle

1974-01-01

In studies of genetic differences among trees, forest biologists have found that variations fall into two categories. In the first, characterized by metric traits, the phenotypic response results from the combined activity of many genes having minor effects. In the other, characterized by mutants and some resin and disease resistance factors, the phenotypic response...

Landscape and regional context differentially affect nest parasitism and nest predation for Wood Thrush in central Virginia, USA (Presentation)

EPA Science Inventory

Many empirical studies have shown that forest-breeding songbirds suffer greater rates of nest predation and nest parasitism in smaller forest patches and in fragmented landscapes. To compare the performance of different metrics of spatial habitat configuration resulting from defo...

76 FR 28950 - Lynn Canal/Icy Straits Resource Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-19

... DEPARTMENT OF AGRICULTURE Forest Service Lynn Canal/Icy Straits Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Lynn Canal/Icy Straits Resource Advisory Committee will hold a teleconference, June 9, 2011. The purpose of this meeting is to discuss metrics and...

Forests of Arkansas, 2015

Treesearch

James F. Rosson

2016-01-01

This resource update is a brief look at some of the basic metrics that describe the status of and changes to forest resources in Arkansas. Estimates presented here are for the survey year 2015 with resource changes compared against the 2014 survey year. This information is based on field data collected using the Forest Inventory and Analysis (FIA) annualized sample...

A preliminary assessment of Montreal process indicators of forest fragmentation for the United States

Treesearch

Kurt H. Riitters; James D. Wickham; John W. Coulston

2004-01-01

Abstract. As part of the U.S. 2003 National Report on Sustainable Forests, four metrics of forest fragmentation – patch size, edge amount, inter-patch distance, and patch contrast – were measured within 137 744 non-overlapping 5625 ha analysis units on land-cover maps derived from satellite imagery for the 48 conterminous States. The perimeter of a...

Assessing urban forest effects and values: Toronto's urban forest

Treesearch

David J. Nowak; Robert E. III Hoehn; Allison R. Bodine; Eric J. Greenfield; Alexis Ellis; Theodore A. Endreny; Yang Yang; Tian Zhou; Ruthanne Henry

2013-01-01

An analysis of trees in Toronto, Ontario, reveals that this city has about 10.2 million trees with a tree and shrub canopy that covers approximately 26.6 percent of the city. The most common tree species are eastern white-cedar, sugar maple, and Norway maple. The urban forest currently stores an estimated 1.1 million metric tons of carbon valued at CAD$25.0 million. In...

Carbon in U.S. forests and wood products, 1987-1997: state-by-state estimates

Treesearch

R.A. Birdsey; G.M. Lewis

2003-01-01

Estimated changes in carbon stocks are reported for the forests and wood products of the 50 U.S. States. Carbon stocks on forest land and in harvested wood products increased between 1987 and 1997 at an annual rate of 190 million metric tons. Most of this increase was in biomass, followed closely by wood products and landfills. Changes in land use since 1987 caused a...

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

PubMed Central

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G.; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Background Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. Methodology and Principal Findings A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Conclusion and Significance Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level. PMID:22235254

Mapping migratory bird prevalence using remote sensing data fusion.

PubMed

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

Flying Under the LiDAR: Relating Forest Structure to Bat Community Diversity

NASA Astrophysics Data System (ADS)

Swanson, A. C.; Weishampel, J. F.

2015-12-01

Bats are important to many ecological processes such as pollination, insect (and by proxy, disease) control, and seed dispersal and can be used to monitor ecosystem health. However, they are facing unprecedented extinction risks from habitat degradation as well as pressures from pathogens (e.g., white-nose syndrome) and wind turbines. LiDAR allows ecologists to measure structural variables of forested landscapes with increased precision and accuracy at broader spatial scales than previously possible. This study used airborne LiDAR to classify forest habitat/canopy structure at the Ordway-Swisher Biological Station (OSBS) in north central Florida. LiDAR data were acquired by the NEON airborne observation platform in summer 2014. OSBS consists of open-canopy pine savannas, closed-canopy hardwood hammocks, and seasonally wet prairies. Multiple forest structural parameters (e.g., mean, maximum, and standard deviation of height returns) were derived from LiDAR point clouds using the USDA software program FUSION. K-means clustering was used to segregate each 5x5 m raster across the ~3765 ha OSBS area into six different clusters based on the derived canopy metrics. Cluster averages for maximum, mean, and standard deviation of return heights ranged from 0 to 19.4 m, 0 to 15.3 m, and 0 to 3.0 m, respectively. To determine the relationships among these landscape-canopy features and bat species diversity and abundances, AnaBat II bat detectors were deployed from May to September in 2015 stratified by these distinct clusters. Bat calls were recorded from sunset to sunrise during each sampling period. Species were identified using AnalookW. A statistical regression model selection approach was performed in order to evaluate how forest attributes such as understory clutter, open regions, open and closed canopy, etc. influence bat communities. This knowledge provides a deeper understanding of habitat-species interactions to better manage survival of these species.

Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests

NASA Astrophysics Data System (ADS)

Liu, Jing; Skidmore, Andrew K.; Heurich, Marco; Wang, Tiejun

2017-10-01

As an important metric for describing vertical forest structure, the plant area index (PAI) profile is used for many applications including biomass estimation and wildlife habitat assessment. PAI profiles can be estimated with the vertically resolved gap fraction from airborne LiDAR data. Most research utilizes a height normalization algorithm to retrieve local or relative height by assuming the terrain to be flat. However, for many forests this assumption is not valid. In this research, the effect of topographic normalization of airborne LiDAR data on the retrieval of PAI profile was studied in a mountainous forest area in Germany. Results show that, although individual tree height may be retained after topographic normalization, the spatial arrangement of trees is changed. Specifically, topographic normalization vertically condenses and distorts the PAI profile, which consequently alters the distribution pattern of plant area density in space. This effect becomes more evident as the slope increases. Furthermore, topographic normalization may also undermine the complexity (i.e., canopy layer number and entropy) of the PAI profile. The decrease in PAI profile complexity is not solely determined by local topography, but is determined by the interaction between local topography and the spatial distribution of each tree. This research demonstrates that when calculating the PAI profile from airborne LiDAR data, local topography needs to be taken into account. We therefore suggest that for ecological applications, such as vertical forest structure analysis and modeling of biodiversity, topographic normalization should not be applied in non-flat areas when using LiDAR data.

Characterizing fragmentation of the collective forests in southern China from multitemporal Landsat imagery: A case study from Kecheng district of Zhejiang province

USGS Publications Warehouse

Li, M.; Zhu, Z.; Vogelmann, James E.; Xu, D.; Wen, W.; Liu, A.

2011-01-01

Tropical and subtropical forests provide important ecosystem goods and services including carbon sequestration and biodiversity conservation. These forests are facing increasing socioeconomic pressures and are rapidly being degraded and fragmented. This analysis focuses on the rate of change and patterns of fragmentation in a collective forest area in Zhejiang province, China, during the time period 1988–2005. The research consisted of two parts. The first was the development of general land cover maps and the identification of land cover changes by interpreting Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) time series imagery. The second part involved the computation and analysis of forest fragmentation metrics. For this portion of the study, fragmentation statistics were analyzed, and images were developed to depict forest fragmentation patterns and trends. Results revealed that there was a net loss of 7.8% in forest coverage, dropping from 66.8% in 1988 to 59.0% in 2005, primarily caused by agricultural expansion and poor forest management practices. An acceleration of forest fragmentation was also witnessed during the time intervals, which was evidenced by a decreasing trend in interior forest (57.2% in 1988, 55.0% in 1996 and 54.8% in 2005 respectively) coupled with the scales of the selected geospatial metrics. Continued forest loss and fragmentation are closely correlated with the existing political, educational, institutional and economic processes of contemporary China. To unlock the developmental potentials of the collective forests and to effectively mitigate the rate of forest loss and fragmentation, reforms of forest tenure and ecological immigration practices are recognized as a prospective alternative. The produced fragmentation maps further illustrates the importance of assessing landscape change history, especially the spatiotemporal patterns of forest fragments, when developing landscape level plans for biodiversity conservation, land use management and ecologically sustainable forestry.

Bridging gaps: On the performance of airborne LiDAR to model wood mouse-habitat structure relationships in pine forests.

PubMed

Jaime-González, Carlos; Acebes, Pablo; Mateos, Ana; Mezquida, Eduardo T

2017-01-01

LiDAR technology has firmly contributed to strengthen the knowledge of habitat structure-wildlife relationships, though there is an evident bias towards flying vertebrates. To bridge this gap, we investigated and compared the performance of LiDAR and field data to model habitat preferences of wood mouse (Apodemus sylvaticus) in a Mediterranean high mountain pine forest (Pinus sylvestris). We recorded nine field and 13 LiDAR variables that were summarized by means of Principal Component Analyses (PCA). We then analyzed wood mouse's habitat preferences using three different models based on: (i) field PCs predictors, (ii) LiDAR PCs predictors; and (iii) both set of predictors in a combined model, including a variance partitioning analysis. Elevation was also included as a predictor in the three models. Our results indicate that LiDAR derived variables were better predictors than field-based variables. The model combining both data sets slightly improved the predictive power of the model. Field derived variables indicated that wood mouse was positively influenced by the gradient of increasing shrub cover and negatively affected by elevation. Regarding LiDAR data, two LiDAR PCs, i.e. gradients in canopy openness and complexity in forest vertical structure positively influenced wood mouse, although elevation interacted negatively with the complexity in vertical structure, indicating wood mouse's preferences for plots with lower elevations but with complex forest vertical structure. The combined model was similar to the LiDAR-based model and included the gradient of shrub cover measured in the field. Variance partitioning showed that LiDAR-based variables, together with elevation, were the most important predictors and that part of the variation explained by shrub cover was shared. LiDAR derived variables were good surrogates of environmental characteristics explaining habitat preferences by the wood mouse. Our LiDAR metrics represented structural features of the forest patch, such as the presence and cover of shrubs, as well as other characteristics likely including time since perturbation, food availability and predation risk. Our results suggest that LiDAR is a promising technology for further exploring habitat preferences by small mammal communities.

Characterising Vegetation Structural and Functional Differences Across Australian Ecosystems From a Network of Terrestrial Laser Scanning Survey Sites and Airborne and Satellite Image Archives

NASA Astrophysics Data System (ADS)

Phinn, S. R.; Armston, J.; Scarth, P.; Johansen, K.; Schaefer, M.; Suarez, L.; Soto-Berelov, M.; Muir, J.; Woodgate, W.; Jones, S.; Held, A. A.

2015-12-01

Vegetation structural information is critical for environmental monitoring, management and compliance assessment. In this context we refer to vegetation structural properties as vertical, horizontal and volumetric dimensions, including: canopy height; amount and distribution of vegetation by height; foliage projective cover (FPC); leaf area index (LAI); and above ground biomass. Our aim was to determine if there were significant differences between vegetation structural properties across 11 ecosystem types in Australia as measured by terrestrial laser scanner (TLS) structure metrics. The ecosystems sampled included: mesophyll vineforest, wet-dry tropical savannah, mallee woodland, subtropical eucalypt forest, mulga woodland/grassland, wet eucalypt forest, dry eucalypt forest, tall and wet eucalypt forest, and desert grassland/shrublands. Canopy height, plant area-height profiles and LAI were calculated from consistently processed TLS data using Australia's Terrestrial Ecosystem Research Network's (TERN) Supersites by the TERN AusCover remote sensing field teams from 2012-2015. The Supersites were sampled using standardised field protocols within a core set of 1 ha plots as part of a 5 km x 5 km uniform area using a RIEGL-VZ400 waveform recording TLS. Four to seven scans were completed per plot, with one centre point and then at 25 m away from the centre point along transect lines at 0o, 60o and 240o. Individual foliage profiles were sensitive to spatial variation in the distribution of plant materials. Significant differences were visible between each of the vegetation communities assessed when aggregated to plot and ecosystem type scales. Several of the communities exhibited simple profiles with either grass and shrubs (e.g. desert grassland) or grass and trees (e.g. mallee woodland). Others had multiple vegetation forms at different heights, contributing to the profile (e.g. wet eucalypt forest). The TLS data provide significantly more detail about the relative vertical and horizontal distribution of plant materials. TLS data are providing a step change in satellite image based vegetation mapping, and refining our knowledge of vegetation structure and its phenological variability. Open access plot scale TLS measurements are available through the TERN Auscover data portal.

Estimating tree species richness from forest inventory plot data

Treesearch

Ronald E. McRoberts; Dacia M. Meneguzzo

2007-01-01

Montreal Process Criterion 1, Conservation of Biological Diversity, expresses species diversity in terms of number of forest dependent species. Species richness, defined as the total number of species present, is a common metric for analyzing species diversity. A crucial difficulty in estimating species richness from sample data obtained from sources such as inventory...

Density-dependent vulnerability of forest ecosystems to drought

Treesearch

Alessandra Bottero; Anthony W. D' Amato; Brian J. Palik; John B. Bradford; Shawn Fraver; Mike A. Battaglia; Lance A. Asherin; Harald Bugmann

2017-01-01

Climate models predict increasing drought intensity and frequency for many regions, which may have negative consequences for tree recruitment, growth and mortality, as well as forest ecosystem services. Furthermore, practical strategies for minimizing vulnerability to drought are limited. Tree population density, a metric of tree abundance in a given area, is a primary...

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.

Using Landscape Analysis to Test Hypotheses about Drivers of Tick Abundance and Infection Prevalence with Borrelia burgdorferi.

PubMed

Ferrell, A Michelle; Brinkerhoff, R Jory

2018-04-12

Patterns of vector-borne disease risk are changing globally in space and time and elevated disease risk of vector-borne infection can be driven by anthropogenic modification of the environment. Incidence of Lyme disease, caused by the bacterium Borrelia burgdorferi sensu stricto, has risen in a number of locations in North America and this increase may be driven by spatially or numerically expanding populations of the primary tick vector, Ixodes scapularis . We used a model selection approach to identify habitat fragmentation and land-use/land cover variables to test the hypothesis that the amount and configuration of forest cover at spatial scales relevant to deer, the primary hosts of adult ticks, would be the predominant determinants of tick abundance. We expected that land cover heterogeneity and amount of forest edge, a habitat thought to facilitate deer foraging and survival, would be the strongest driver of tick density and that larger spatial scales (5-10 km) would be more important than smaller scales (1 km). We generated metrics of deciduous and mixed forest fragmentation using Fragstats 4.4 implemented in ArcMap 10.3 and found, after adjusting for multicollinearity, that total forest edge within a 5 km buffer had a significant negative effect on tick density and that the proportion of forested land cover within a 10 km buffer was positively associated with density of I. scapularis nymphs. None of the 1 km fragmentation metrics were found to significantly improve the fit of the model. Elevation, previously associated with increased density of I. scapularis nymphs in Virginia, while significantly predictive in univariate analysis, was not an important driver of nymph density relative to fragmentation metrics. Our results suggest that amount of forest cover (i.e., lack of fragmentation) is the most important driver of I. scapularis density in our study system.

Distribution of Aboveground Live Biomass in the Amazon Basin

NASA Technical Reports Server (NTRS)

Saatchi, S. S.; Houghton, R. A.; DosSantos Alvala, R. C.; Soares, J. V.; Yu, Y.

2007-01-01

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300Mgha(sup 1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300Mgha(sup 1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200Mgha(sup 1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and below ground biomass, is 86 PgC with +/- 20% uncertainty.

Opposing Responses of Bird Functional Diversity to Vegetation Structural Diversity in Wet and Dry Forest.

PubMed

Sitters, Holly; York, Alan; Swan, Matthew; Christie, Fiona; Di Stefano, Julian

2016-01-01

Disturbance regimes are changing worldwide, and the consequences for ecosystem function and resilience are largely unknown. Functional diversity (FD) provides a surrogate measure of ecosystem function by capturing the range, abundance and distribution of trait values in a community. Enhanced understanding of the responses of FD to measures of vegetation structure at landscape scales is needed to guide conservation management. To address this knowledge gap, we used a whole-of-landscape sampling approach to examine relationships between bird FD, vegetation diversity and time since fire. We surveyed birds and measured vegetation at 36 landscape sampling units in dry and wet forest in southeast Australia during 2010 and 2011. Four uncorrelated indices of bird FD (richness, evenness, divergence and dispersion) were derived from six bird traits, and we investigated responses of these indices and species richness to both vertical and horizontal vegetation diversity using linear mixed models. We also considered the extent to which the mean and diversity of time since fire were related to vegetation diversity. Results showed opposing responses of FD to vegetation diversity in dry and wet forest. In dry forest, where fire is frequent, species richness and two FD indices (richness and dispersion) were positively related to vertical vegetation diversity, consistent with theory relating to environmental variation and coexistence. However, in wet forest subject to infrequent fire, the same three response variables were negatively associated with vertical diversity. We suggest that competitive dominance by species results in lower FD as vegetation diversity increases in wet forest. The responses of functional evenness were opposite to those of species richness, functional richness and dispersion in both forest types, highlighting the value of examining multiple FD metrics at management-relevant scales. The mean and diversity of time since fire were uncorrelated with vegetation diversity in wet forest, but positively correlated with vegetation diversity in dry forest. We therefore suggest that protection of older vegetation is important, but controlled application of low-severity fire in dry forest may sustain ecosystem function by enhancing different elements of FD.

Opposing Responses of Bird Functional Diversity to Vegetation Structural Diversity in Wet and Dry Forest

PubMed Central

York, Alan; Swan, Matthew; Christie, Fiona; Di Stefano, Julian

2016-01-01

Disturbance regimes are changing worldwide, and the consequences for ecosystem function and resilience are largely unknown. Functional diversity (FD) provides a surrogate measure of ecosystem function by capturing the range, abundance and distribution of trait values in a community. Enhanced understanding of the responses of FD to measures of vegetation structure at landscape scales is needed to guide conservation management. To address this knowledge gap, we used a whole-of-landscape sampling approach to examine relationships between bird FD, vegetation diversity and time since fire. We surveyed birds and measured vegetation at 36 landscape sampling units in dry and wet forest in southeast Australia during 2010 and 2011. Four uncorrelated indices of bird FD (richness, evenness, divergence and dispersion) were derived from six bird traits, and we investigated responses of these indices and species richness to both vertical and horizontal vegetation diversity using linear mixed models. We also considered the extent to which the mean and diversity of time since fire were related to vegetation diversity. Results showed opposing responses of FD to vegetation diversity in dry and wet forest. In dry forest, where fire is frequent, species richness and two FD indices (richness and dispersion) were positively related to vertical vegetation diversity, consistent with theory relating to environmental variation and coexistence. However, in wet forest subject to infrequent fire, the same three response variables were negatively associated with vertical diversity. We suggest that competitive dominance by species results in lower FD as vegetation diversity increases in wet forest. The responses of functional evenness were opposite to those of species richness, functional richness and dispersion in both forest types, highlighting the value of examining multiple FD metrics at management-relevant scales. The mean and diversity of time since fire were uncorrelated with vegetation diversity in wet forest, but positively correlated with vegetation diversity in dry forest. We therefore suggest that protection of older vegetation is important, but controlled application of low-severity fire in dry forest may sustain ecosystem function by enhancing different elements of FD. PMID:27741290

Using remote sensing data to assess salmon habitat status in rivers and floodplains of Puget Sound, USA

NASA Astrophysics Data System (ADS)

Beechie, T. J.; Pess, G. R.; Hall, J.; Timpane-Padgham, B.; Stefankiv, O.; Liermann, M. C.; Fresh, K.; Rowse, M.

2015-12-01

Natural processes create dynamic habitat features in large rivers and floodplains, and past land uses that restrict fluvial processes have altered habitat conditions in those environments in Puget Sound, USA. As a result, Chinook salmon and steelhead are listed as threatened species under the US Endangered Species Act (ESA). To help restore these salmon populations, restoration actions often focus on removing constraints on natural processes to restore fluvial dynamics and ultimately restore critical salmon habitats on floodplains. An important aspect of this restoration effort is monitoring whether habitat conditions are improving as anticipated, yet there are currently few protocols available for monitoring trends in large river and floodplain habitats. We identified several remote-sensing metrics that are indicators of salmon habitat condition, and developed repeatable protocols for measuring those metrics. We then tested their sensitivity to land use change by comparing habitat conditions among land cover classes (developed, agriculture, forested, and mixed). As expected, metrics of habitat complexity or condition such as side-channel length, node density, wood jam area, or riparian buffer widths were highest in forested sites and lowest in agriculture and urban sites. By contrast, percent disconnected floodplain and percent armored banks were highest in developed sites and lowest in forested sites. Our results indicate that remote sensing metrics are sensitive enough to detect differences in habitat status among land cover classes, and therefore help us understand the impact of various land uses on habitat conditions. However, detecting trends in habitat condition through time may be difficult because magnitudes of change through time are very small.

Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

USGS Publications Warehouse

Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

2013-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

Study on forest above-ground biomass synergy inversion from GLAS and HJ-1 data

NASA Astrophysics Data System (ADS)

Fang, Zhou; Cao, Chunxiang; Ji, Wei; Xu, Min; Chen, Wei

2012-10-01

The need exists to develop a systematic approach to inventory and monitor global forests, both for carbon stock evaluation and for land use change analysis. The use of freely available satellite-based data for carbon stock estimation mitigates both the cost and the spatial limitations of field-based techniques. Spaceborne lidar data have been demonstrated as useful for forest aboveground biomass (AGB) estimation over a wide range of biomass values and forest types. However, the application of these data is limited because of their spatially discrete nature. Spaceborne multispectral sensors have been used extensively to estimate AGB, but these methods have been demonstrated as inappropriate for forest structure characterization in high-biomass mature forests. This study uses an integration of ICESat Geospatial Laser Altimeter System (GLAS) lidar and HJ-1 satellites data to develop methods to estimate AGB in an area of Qilian Mountains, Northwest China. Considering the study area belongs to mountainous terrain, the difficulties of this article are how to extract canopy height from GLAS waveform metrics. Combining with HJ-1 data and ground survey data of the study area, we establish forest biomass estimation model for the GLAS data based on BP neural network model. In order to estimate AGB, the training sample data includes the canopy height extracted from GLAS, LAI, vegetation coverage and several kinds of vegetation indices from HJ-1 data. The results of forest aboveground biomass are very close to the fields measured results, and are consistent with land cover data in the spatial distribution.

Spatial and temporal dimensions of landscape fragmentation across the Brazilian Amazon.

PubMed

Rosa, Isabel M D; Gabriel, Cristina; Carreiras, Joāo M B

2017-01-01

The Brazilian Amazon in the past decades has been suffering severe landscape alteration, mainly due to anthropogenic activities, such as road building and land clearing for agriculture. Using a high-resolution time series of land cover maps (classified as mature forest, non-forest, secondary forest) spanning from 1984 through 2011, and four uncorrelated fragmentation metrics (edge density, clumpiness index, area-weighted mean patch size and shape index), we examined the temporal and spatial dynamics of forest fragmentation in three study areas across the Brazilian Amazon (Manaus, Santarém and Machadinho d'Oeste), inside and outside conservation units. Moreover, we compared the impacts on the landscape of: (1) different land uses (e.g. cattle ranching, crop production), (2) occupation processes (spontaneous vs. planned settlements) and (3) implementation of conservation units. By 2010/2011, municipalities located along the Arc of Deforestation had more than 55% of the remaining mature forest strictly confined to conservation units. Further, the planned settlement showed a higher rate of forest loss, a more persistent increase in deforested areas and a higher relative incidence of deforestation inside conservation units. Distinct agricultural activities did not lead to significantly different landscape structures; the accessibility of the municipality showed greater influence in the degree of degradation of the landscapes. Even with a high proportion of the landscapes covered by conservation units, which showed a strong inhibitory effect on forest fragmentation, we show that dynamic agriculturally driven economic activities, in municipalities with extensive road development, led to more regularly shaped, heavily fragmented landscapes, with higher densities of forest edge.

Sensitivity of ALOS/PALSAR imagery to forest degradation by fire in northern Amazon

NASA Astrophysics Data System (ADS)

Martins, Flora da Silva Ramos Vieira; dos Santos, João Roberto; Galvão, Lênio Soares; Xaud, Haron Abrahim Magalhães

2016-07-01

We evaluated the sensitivity of the full polarimetric Phased Array type L-band Synthetic Aperture Radar (PALSAR), onboard the Advanced Land Observing Satellite (ALOS), to forest degradation caused by fires in northern Amazon, Brazil. We searched for changes in PALSAR signal and tri-dimensional polarimetric responses for different classes of fire disturbance defined by fire frequency and severity. Since the aboveground biomass (AGB) is affected by fire, multiple regression models to estimate AGB were obtained for the whole set of coherent and incoherent attributes (general model) and for each set separately (specific models). The results showed that the polarimetric L-band PALSAR attributes were sensitive to variations in canopy structure and AGB caused by forest fire. However, except for the unburned and thrice burned classes, no single PALSAR attribute was able to discriminate between the intermediate classes of forest degradation by fire. Both the coherent and incoherent polarimetric attributes were important to explain AGB variations in tropical forests affected by fire. The HV backscattering coefficient, anisotropy, double-bounce component, orientation angle, volume index and HH-VV phase difference were PALSAR attributes selected from multiple regression analysis to estimate AGB. The general regression model, combining phase and power radar metrics, presented better results than specific models using coherent or incoherent attributes. The polarimetric responses indicated the dominance of VV-oriented backscattering in primary forest and lightly burned forests. The HH-oriented backscattering predominated in heavily and frequently burned forests. The results suggested a greater contribution of horizontally arranged constituents such as fallen trunks or branches in areas severely affected by fire.

Assessing the influence of return density on estimation of lidar-based aboveground biomass in tropical peat swamp forests of Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Manuri, Solichin; Andersen, Hans-Erik; McGaughey, Robert J.; Brack, Cris

2017-04-01

The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition can vary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed the effect of lidar return density on the accuracy of lidar metrics and regression models for estimating aboveground biomass (AGB) and basal area (BA) in tropical peat swamp forests (PSF) in Kalimantan, Indonesia. A large dataset of ALS covering an area of 123,000 ha was used in this study. This study found that cumulative return proportion (CRP) variables represent a better accumulation of AGB over tree heights than height-related variables. The CRP variables in power models explained 80.9% and 90.9% of the BA and AGB variations, respectively. Further, it was found that low-density (and low-cost) lidar should be considered as a feasible option for assessing AGB and BA in vast areas of flat, lowland PSF. The performance of the models generated using reduced return densities as low as 1/9 returns per m2 also yielded strong agreement with the original high-density data. The use model-based statistical inferences enabled relatively precise estimates of the mean AGB at the landscape scale to be obtained with a fairly low-density of 1/4 returns per m2, with less than 10% standard error (SE). Further, even when very low-density lidar data was used (i.e., 1/49 returns per m2) the bias of the mean AGB estimates were still less than 10% with a SE of approximately 15%. This study also investigated the influence of different DTM resolutions for normalizing the elevation during the generation of forest-related lidar metrics using various return densities point cloud. We found that the high-resolution digital terrain model (DTM) had little effect on the accuracy of lidar metrics calculation in PSF. The accuracy of low-density lidar metrics in PSF was more influenced by the density of aboveground returns, rather than the last return. This is due to the flat topography of the study area. The results of this study will be valuable for future economical and feasible assessments of forest metrics over large areas of tropical peat swamp ecosystems.

Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series

PubMed Central

DeVries, Ben; Pratihast, Arun Kumar; Verbesselt, Jan; Kooistra, Lammert; Herold, Martin

2016-01-01

Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries. Advances in satellite-based remote sensing and ground-based technologies have allowed for monitoring of forests with high spatial, temporal and thematic detail. Despite these advances, there is a need to engage communities in monitoring activities and include these stakeholders in national forest monitoring systems. In this study, we analyzed activity data (deforestation and forest degradation) collected by local forest experts over a 3-year period in an Afro-montane forest area in southwestern Ethiopia and corresponding Landsat Time Series (LTS). Local expert data included forest change attributes, geo-location and photo evidence recorded using mobile phones with integrated GPS and photo capabilities. We also assembled LTS using all available data from all spectral bands and a suite of additional indices and temporal metrics based on time series trajectory analysis. We predicted deforestation, degradation or stable forests using random forest models trained with data from local experts and LTS spectral-temporal metrics as model covariates. Resulting models predicted deforestation and degradation with an out of bag (OOB) error estimate of 29% overall, and 26% and 31% for the deforestation and degradation classes, respectively. By dividing the local expert data into training and operational phases corresponding to local monitoring activities, we found that forest change models improved as more local expert data were used. Finally, we produced maps of deforestation and degradation using the most important spectral bands. The results in this study represent some of the first to combine local expert based forest change data and dense LTS, demonstrating the complementary value of both continuous data streams. Our results underpin the utility of both datasets and provide a useful foundation for integrated forest monitoring systems relying on data streams from diverse sources. PMID:27018852

Trends in nitrogen and phosphorus cycling are consistent and constrained during tropical secondary forest succession: is secondary forest young primary forest from a nutrient perspective?

NASA Astrophysics Data System (ADS)

Sullivan, B. W.; Nasto, M.; Alvarez-Clare, S.; Cole, R. J.; Reed, S.; Chazdon, R.; Davidson, E. A.; Cleveland, C. C.

2015-12-01

Extensive deforestation of tropical rainforest often leads to agricultural abandonment and secondary forest regeneration. The land area of secondary rainforest is soon likely to exceed that of primary forest, highlighting the importance of secondary tropical rainforest in the global carbon (C) cycle. Secondary forests often grow rapidly, but the role soil nutrients play in regulating secondary forest productivity remains unsettled. Consistent with biogeochemical theory, a landmark study from a set of sites in the Amazon Basin showed that secondary forests had low nitrogen (N) availability and relatively higher phosphorus (P) availability immediately after abandonment, but that as succession proceeded, N availability "recuperated" and there was relatively less P available. To address whether such changes in N and P availability during secondary forest growth are common, we reviewed 38 studies in lowland tropical rainforest that reported changes in 23 different metrics of N and P cycling during secondary succession. We calculated slopes (rates of change) during secondary succession for each metric in each study, and analyzed patterns in these rates of change. Significant trends during secondary succession were more evident in soils than in plants, but in most cases, the variability among studies was surprisingly low. Both soil N and P availability increased through succession, at least in surface soil. Such consistent changes imply substantial biogeochemical resilience of tropical forest soils in spite of differing land use histories and species compositions among studies. In most cases, slopes were similar whether primary forest was included in, or excluded from, our analysis, suggesting that secondary succession eventually leads to similar biogeochemical conditions as those found in primary forest. Our results suggesting consistent changes in N and P availability during succession provide a biogeochemical rationale for the conservation and restoration value of tropical secondary forests, and may be of utility to coupled C-nutrient models projecting primary productivity in a dynamic tropical biome.

[Spatial characteristics analysis of Huizhou-Styled Village based on ideal ecosystem model and 3D landscape indices: A case in Chengkan, China].

PubMed

Yao, Meng Yuan; Yan, Shi Jiang; Wu, Yan Lan

2016-12-01

Huizhou-Styled Village is a typical representative of the traditional Chinese ancient villages. It preserves plentiful information of the regional culture and ecological connotation. The Huizhou-Style is the apotheosis of harmony between the Chinese ancient people and nature. The research and protection of Huizhou-Styled Village plays a very important role in fields of ecology, geography, architecture and esthetics. This paper took Chengkan Village of Anhui Province as an exa-mple, and proposed a new model of ideal ecosystem oriented in theories of Feng-shui and psychological field. The new method of characterizing 3D landscape index was introduced to explore the spatial patterns of Huizhou-Styled Village and the functionality of the composited landscape components in a quantitative way. The results indicated that, Chengkan Village showed a spatially composited pattern of "mountain-forest-village-river-forest". It formed an ideal settlement ring structure with human architecture in the center and natural landscape around in the horizontal and vertical horizons. The traditional method based on the projection distance caused the deviation of the landscape index, such as underestimating the area and distance of landscape patch. The 3D landscape index of average patch area was 6.7% higher than the 2D landscape index. The increasing rate ofarea proportion in 3D index was 1.0% higher than that of 2D index in forest lands. Area proportion of the other landscapes decreased, especially the artificial landscapes like construction and cropland landscapes. The area and perimeter metric were underestimated, whereas the shape metric and the diversity metric were overestimated. This caused the underestimation of the dominance of natural patches was underestimated and the overestimation of the dominance of artificial patches during the analysis of landscape pattern. The 3D landscape index showed that the natural elements and their combination in Chengkan Village ecosystem reflected better ecological function, the key elements and the composited landscape ecosystem preserved higher stability, connectivity and aggregation. The quantitative confirmation showed that the Huizhou-Styled Village represented by Chengkan Village is an ideal ecosystem.

Dispersal assembly of rain forest tree communities across the Amazon basin

PubMed Central

Lavin, Mathew; Torke, Benjamin M.; Twyford, Alex D.; Kursar, Thomas A.; Coley, Phyllis D.; Drake, Camila; Hollands, Ruth; Pennington, R. Toby

2017-01-01

We investigate patterns of historical assembly of tree communities across Amazonia using a newly developed phylogeny for the species-rich neotropical tree genus Inga. We compare our results with those for three other ecologically important, diverse, and abundant Amazonian tree lineages, Swartzia, Protieae, and Guatteria. Our analyses using phylogenetic diversity metrics demonstrate a clear lack of geographic phylogenetic structure, and show that local communities of Inga and regional communities of all four lineages are assembled by dispersal across Amazonia. The importance of dispersal in the biogeography of Inga and other tree genera in Amazonian and Guianan rain forests suggests that speciation is not driven by vicariance, and that allopatric isolation following dispersal may be involved in the speciation process. A clear implication of these results is that over evolutionary timescales, the metacommunity for any local or regional tree community in the Amazon is the entire Amazon basin. PMID:28213498

Dispersal assembly of rain forest tree communities across the Amazon basin.

PubMed

Dexter, Kyle G; Lavin, Mathew; Torke, Benjamin M; Twyford, Alex D; Kursar, Thomas A; Coley, Phyllis D; Drake, Camila; Hollands, Ruth; Pennington, R Toby

2017-03-07

We investigate patterns of historical assembly of tree communities across Amazonia using a newly developed phylogeny for the species-rich neotropical tree genus Inga We compare our results with those for three other ecologically important, diverse, and abundant Amazonian tree lineages, Swartzia , Protieae, and Guatteria Our analyses using phylogenetic diversity metrics demonstrate a clear lack of geographic phylogenetic structure, and show that local communities of Inga and regional communities of all four lineages are assembled by dispersal across Amazonia. The importance of dispersal in the biogeography of Inga and other tree genera in Amazonian and Guianan rain forests suggests that speciation is not driven by vicariance, and that allopatric isolation following dispersal may be involved in the speciation process. A clear implication of these results is that over evolutionary timescales, the metacommunity for any local or regional tree community in the Amazon is the entire Amazon basin.

Spatial pattern corrections and sample sizes for forest density estimates of historical tree surveys

Treesearch

Brice B. Hanberry; Shawn Fraver; Hong S. He; Jian Yang; Dan C. Dey; Brian J. Palik

2011-01-01

The U.S. General Land Office land surveys document trees present during European settlement. However, use of these surveys for calculating historical forest density and other derived metrics is limited by uncertainty about the performance of plotless density estimators under a range of conditions. Therefore, we tested two plotless density estimators, developed by...

Stand-scale habitat associations across a large geographic region of an old-growth specialist, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

We used two metrics, occupancy and relative abundance, to study forest stand characteristics believed to be important to a threatened seabird that nests in old-growth forests, the Marbled Murrelet (Brachyramphus marmoratus). Occupancy refers to murrelet presence or absence based on observed bird behaviors, while relative abundance refers to...

Using epiphytic macrolichen communities for biomonitoring ammonia in forests of the greater Sierra Nevada, California

Treesearch

Sarah Jovan; Bruce Mccune

2006-01-01

Chronic, excessive nitrogen deposition is potentially an important ecological threat to forests of the greater Sierra Nevada in California. We developed a model for ammonia bioindication, a major nitrogen pollutant in the region, using epiphytic macrolichens. We used non-metric multidimensional scaling to extract gradients in lichen community composition from surveys...

An exergy based assessment of the production and conversion of switchgrass, equine waste and forest residue to bio-oil using fast pyrolysis

USDA-ARS?s Scientific Manuscript database

The resource efficiency of biofuel production via biomass pyrolysis is evaluated using exergy as an assessment metric. Three feedstocks, important to various sectors of US agriculture, switchgrass, forest residue and equine waste are considered for conversion to bio-oil (pyrolysis oil) via fast pyro...

Examination of roundwood utilization rates in West Virginia

Treesearch

Shawn T. Grushecky; Jan Wiedenbeck; Curt C. Hassler

2013-01-01

Forest harvesting is an integral part of the West Virginia forest economy. This component of the supply chain supports a diverse array of primary and secondary processors. A key metric used to describe the efficiency of the roundwood extraction process is the logging utilization factor (LUF). The LUF is one way managers can discern the overall use of harvested...

Patterns among the ashes: Exploring the relationship between landscape pattern and the emerald ash borer

Treesearch

Susan J. Crocker; Dacia M. Meneguzzo; Greg C. Liknes

2010-01-01

Landscape metrics, including host abundance and population density, were calculated using forest inventory and land cover data to assess the relationship between landscape pattern and the presence or absence of the emerald ash borer (EAB) (Agrilus planipennis Fairmaire). The Random Forests classification algorithm in the R statistical environment was...

A Machine Learning and Cross-Validation Approach for the Discrimination of Vegetation Physiognomic Types Using Satellite Based Multispectral and Multitemporal Data.

PubMed

Sharma, Ram C; Hara, Keitarou; Hirayama, Hidetake

2017-01-01

This paper presents the performance and evaluation of a number of machine learning classifiers for the discrimination between the vegetation physiognomic classes using the satellite based time-series of the surface reflectance data. Discrimination of six vegetation physiognomic classes, Evergreen Coniferous Forest, Evergreen Broadleaf Forest, Deciduous Coniferous Forest, Deciduous Broadleaf Forest, Shrubs, and Herbs, was dealt with in the research. Rich-feature data were prepared from time-series of the satellite data for the discrimination and cross-validation of the vegetation physiognomic types using machine learning approach. A set of machine learning experiments comprised of a number of supervised classifiers with different model parameters was conducted to assess how the discrimination of vegetation physiognomic classes varies with classifiers, input features, and ground truth data size. The performance of each experiment was evaluated by using the 10-fold cross-validation method. Experiment using the Random Forests classifier provided highest overall accuracy (0.81) and kappa coefficient (0.78). However, accuracy metrics did not vary much with experiments. Accuracy metrics were found to be very sensitive to input features and size of ground truth data. The results obtained in the research are expected to be useful for improving the vegetation physiognomic mapping in Japan.

Influence of Habitat and Land Use on the Assemblages of Ephemeroptera, Plecoptera, and Trichoptera in Neotropical Streams

PubMed Central

do Amaral, Pedro Henrique Monteiro; da Silveira, Lidimara Souza; Rosa, Beatriz Figueiraujo Jabour Vescovi; de Oliveira, Vívian Campos; Alves, Roberto da Gama

2015-01-01

Insects of the orders Ephemeroptera, Plecoptera, and Trichoptera (EPT) are often used to assess the conditions of aquatic environments, but few studies have examined the differences in these communities between riffles and pools. Our objective was to test whether riffles shelter greater richness and abundance of EPT, as well as to assess the sensitivity of these insects for detecting impacts from different land uses in streams in southeastern Brazil. Samples were collected in the dry season of 2012 with a Surber sampler in riffles and pools of nine streams (forest, pasture, and urban areas). Principal component analysis distinguished the streams according to different land uses as a function of percentage of plant cover and water oxygenation level and showed partial distinction between riffles and pools as a function of current speed and percentage of ultrafine sand. Detrended correspondence analysis indicated the distinction in EPT composition between riffles and pools, except in urban streams. The results of this study confirm the expected differences in the EPT fauna structure between riffles and pools, especially in forest and pasture environments. The individual metrics of riffle and pool assemblages showed significantly different responses to land use. Therefore, we suggest individual sampling of riffles and pools, since the metrics of these assemblages’ insects can differ between these habitats and influence the results of assessments in low-order streams. PMID:25989807

Relationships of sedimentation and benthic macroinvertebrate assemblages in headwater streams using systematic longitudinal sampling at the reach scale.

PubMed

Longing, S D; Voshell, J R; Dolloff, C A; Roghair, C N

2010-02-01

Investigating relationships of benthic invertebrates and sedimentation is challenging because fine sediments act as both natural habitat and potential pollutant at excessive levels. Determining benthic invertebrate sensitivity to sedimentation in forested headwater streams comprised of extreme spatial heterogeneity is even more challenging, especially when associated with a background of historical and intense watershed disturbances that contributed unknown amounts of fine sediments to stream channels. This scenario exists in the Chattahoochee National Forest where such historical timber harvests and contemporary land-uses associated with recreation have potentially affected the biological integrity of headwater streams. In this study, we investigated relationships of sedimentation and the macroinvertebrate assemblages among 14 headwater streams in the forest by assigning 30, 100-m reaches to low, medium, or high sedimentation categories. Only one of 17 assemblage metrics (percent clingers) varied significantly across these categories. This finding has important implications for biological assessments by showing streams impaired physically by sedimentation may not be impaired biologically, at least using traditional approaches. A subsequent multivariate cluster analysis and indicator species analysis were used to further investigate biological patterns independent of sedimentation categories. Evaluating the distribution of sedimentation categories among biological reach clusters showed both within-stream variability in reach-scale sedimentation and sedimentation categories generally variable within clusters, reflecting the overall physical heterogeneity of these headwater environments. Furthermore, relationships of individual sedimentation variables and metrics across the biological cluster groups were weak, suggesting these measures of sedimentation are poor predictors of macroinvertebrate assemblage structure when using a systematic longitudinal sampling design. Further investigations of invertebrate sensitivity to sedimentation may benefit from assessments of sedimentation impacts at different spatial scales, determining compromised physical habitat integrity of specific taxa and developing alternative streambed measures for quantifying sedimentation.

Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data

NASA Astrophysics Data System (ADS)

Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.

2017-12-01

Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910

Simulation and assessment of urbanization impacts on runoff metrics: insights from landuse changes

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Xia, Jun; Yu, Jingjie; Randall, Mark; Zhang, Yichi; Zhao, Tongtiegang; Pan, Xingyao; Zhai, Xiaoyan; Shao, Quanxi

2018-05-01

Urbanization-induced landuse changes alter runoff regimes in complex ways. In this study, a detailed investigation of the urbanization impacts on runoff regimes is provided by using multiple runoff metrics and with consideration of landuse dynamics. A catchment hydrological model is modified by coupling a simplified flow routing module of the urban drainage system and landuse dynamics to improve long-term urban runoff simulations. Moreover, multivariate statistical approach is adopted to mine the spatial variations of runoff metrics so as to further identify critical impact factors of landuse changes. The Qing River catchment as a peri-urban catchment in the Beijing metropolitan area is selected as our study region. Results show that: (1) the dryland agriculture is decreased from 13.9% to 1.5% of the total catchment area in the years 2000-2015, while the percentages of impervious surface, forest and grass are increased from 63.5% to 72.4%, 13.5% to 16.6% and 5.1% to 6.5%, respectively. The most dramatic landuse changes occur in the middle and downstream regions; (2) The combined landuse changes do not alter the average flow metrics obviously at the catchment outlet, but slightly increase the high flow metrics, particularly the extreme high flows; (3) The impacts on runoff metrics in the sub-catchments are more obvious than those at the catchment outlet. For the average flow metrics, the most impacted metric is the runoff depth in the dry season (October ∼ May) with a relative change from -10.9% to 11.6%, and the critical impact factors are the impervious surface and grass. For the high flow metrics, the extreme high flow depth is increased most significantly with a relative change from -0.6% to 10.5%, and the critical impact factors are the impervious surface and dryland agriculture; (4) The runoff depth metrics in the sub-catchments are increased because of the landuse changes from dryland agriculture to impervious surface, but are decreased because of the landuse changes from dryland agriculture or impervious surface to grass or forest. The results of this study provide useful information for urban planning such as Sponge City design.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Woodland salamanders as metrics of forest ecosystem recovery: a case study from California’s redwoods

Treesearch

Hart Welsh; Garth Hodgson

2013-01-01

Woodland (Plethodontid) salamanders occur in huge numbers in healthy forests in North America where the abundances of many species vary along successional gradients. Their high numbers and trophic role as predators on shredder and decomposer arthropods influence nutrient and carbon pathways at the leaf litter/soil interface. Their extreme niche conservatism and low...

Carbon sequestration in forests as a national policy issue

Treesearch

Linda S. Heath; Linda A. Joyce

1997-01-01

The United States' 1993 Climate Change Action Plan called upon the forestry sector to sequester an additional 10 million metric tons/yr by the year 2000. Forests are currently sequestering carbon and may provide opportunities to mitigate fossil fuel emissions in the near-term until fossil fuel emissions can be reduced. Using the analysis of carbon budgets based on...

Changes in landscape patterns and associated forest succession on the western slope of the Rocky Mountains, Colorado

Treesearch

Daniel J. Manier; Richard D. Laven

2001-01-01

Using repeat photography, we conducted a qualitative and quantitative analysis of changes in forest cover on the western slope of the Rocky Mountains in Colorado. For the quantitative analysis, both images in a pair were classified using remote sensing and geographic information system (GIS) technologies. Comparisons were made using three landscape metrics: total...

Valuing fire planning alternatives in forest restoration: using derived demand to integrate economics with ecological restoration.

PubMed

Rideout, Douglas B; Ziesler, Pamela S; Kernohan, Nicole J

2014-08-01

Assessing the value of fire planning alternatives is challenging because fire affects a wide array of ecosystem, market, and social values. Wildland fire management is increasingly used to address forest restoration while pragmatic approaches to assessing the value of fire management have yet to be developed. Earlier approaches to assessing the value of forest management relied on connecting site valuation with management variables. While sound, such analysis is too narrow to account for a broad range of ecosystem services. The metric fire regime condition class (FRCC) was developed from ecosystem management philosophy, but it is entirely biophysical. Its lack of economic information cripples its utility to support decision-making. We present a means of defining and assessing the deviation of a landscape from its desired fire management condition by re-framing the fire management problem as one of derived demand. This valued deviation establishes a performance metric for wildland fire management. Using a case study, we display the deviation across a landscape and sum the deviations to produce a summary metric. This summary metric is used to assess the value of alternative fire management strategies on improving the fire management condition toward its desired state. It enables us to identify which sites are most valuable to restore, even when they are in the same fire regime condition class. The case study site exemplifies how a wide range of disparate values, such as watershed, wildlife, property and timber, can be incorporated into a single landscape assessment. The analysis presented here leverages previous research on environmental capital value and non-market valuation by integrating ecosystem management, restoration, and microeconomics. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-12-01

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

Characteristics of the Remote Sensing Data Used in the Proposed Unfccc REDD+ Forest Reference Emission Levels (frels)

NASA Astrophysics Data System (ADS)

Johnson, B. A.; Scheyvens, H.; Samejima, H.; Onoda, M.

2016-06-01

Developing countries must submit forest reference emission levels (FRELs) to the UNFCCC to receive incentives for REDD+ activities (e.g. reducing emissions from deforestation/forest degradation, sustainable management of forests, forest carbon stock conservation/enhancement). These FRELs are generated based on historical CO2 emissions in the land use, land use change, and forestry sector, and are derived using remote sensing (RS) data and in-situ forest carbon measurements. Since the quality of the historical emissions estimates is affected by the quality and quantity of the RS data used, in this study we calculated five metrics (i-v below) to assess the quality and quantity of the data that has been used thus far. Countries could focus on improving on one or more of these metrics for the submission of future FRELs. Some of our main findings were: (i) the median percentage of each country mapped was 100%, (ii) the median historical timeframe for which RS data was used was 11.5 years, (iii) the median interval of forest map updates was 4.5 years, (iv) the median spatial resolution of the RS data was 30m, and (v) the median number of REDD+ activities that RS data was used for operational monitoring of was 1 (typically deforestation). Many new sources of RS data have become available in recent years, so complementary or alternative RS data sets for generating future FRELs can potentially be identified based on our findings; e.g. alternative RS data sets could be considered if they have similar or higher quality/quantity than the currently-used data sets.

The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R. F.; Dubayah, R. O.; Ranson, K. J.; Kharuk, V.

2014-01-01

The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.

Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

NASA Technical Reports Server (NTRS)

Sumnall, Matthew; Peduzzi, Alicia; Fox, Thomas R.; Wynne, Randolph H.; Thomas, Valerie A.; Cook, Bruce

2016-01-01

Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were disparities between the number of different types of returns and intensity values when comparing the results from two LiDAR sensors, indicating that predictive models developed using such metrics are not transferable between datasets with different acquisition parameters. Each of the indices were significantly correlated with one another, with one exception (LAI proxy), in particular those indices calculated from all returns, which indicates similarities in information content for those indices. It can then be argued that LiDAR indices have reached a similar stage in development to those calculated from optical-spectral sensors, but which offer a number of advantages, such as the reduction or removal of saturation issues in areas of high biomass.

Phylogenetic turnover along local environmental gradients in tropical forest communities.

PubMed

Baldeck, C A; Kembel, S W; Harms, K E; Yavitt, J B; John, R; Turner, B L; Madawala, S; Gunatilleke, N; Gunatilleke, S; Bunyavejchewin, S; Kiratiprayoon, S; Yaacob, A; Supardi, M N N; Valencia, R; Navarrete, H; Davies, S J; Chuyong, G B; Kenfack, D; Thomas, D W; Dalling, J W

2016-10-01

While the importance of local-scale habitat niches in shaping tree species turnover along environmental gradients in tropical forests is well appreciated, relatively little is known about the influence of phylogenetic signal in species' habitat niches in shaping local community structure. We used detailed maps of the soil resource and topographic variation within eight 24-50 ha tropical forest plots combined with species phylogenies created from the APG III phylogeny to examine how phylogenetic beta diversity (indicating the degree of phylogenetic similarity of two communities) was related to environmental gradients within tropical tree communities. Using distance-based redundancy analysis we found that phylogenetic beta diversity, expressed as either nearest neighbor distance or mean pairwise distance, was significantly related to both soil and topographic variation in all study sites. In general, more phylogenetic beta diversity within a forest plot was explained by environmental variables this was expressed as nearest neighbor distance versus mean pairwise distance (3.0-10.3 % and 0.4-8.8 % of variation explained among plots, respectively), and more variation was explained by soil resource variables than topographic variables using either phylogenetic beta diversity metric. We also found that patterns of phylogenetic beta diversity expressed as nearest neighbor distance were consistent with previously observed patterns of niche similarity among congeneric species pairs in these plots. These results indicate the importance of phylogenetic signal in local habitat niches in shaping the phylogenetic structure of tropical tree communities, especially at the level of close phylogenetic neighbors, where similarity in habitat niches is most strongly preserved.

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.

Site-scale disturbance and habitat development best predict an index of amphibian biotic integrity in Ohio shrub and forested wetlands

USGS Publications Warehouse

Micacchion, Mick; Stapanian, Martin A.; Adams, Jean V.

2015-01-01

We determined the best predictors of an index of amphibian biotic integrity calculated from 54 shrub and forested wetlands in Ohio, USA using a two-step sequential holdout validation procedure. We considered 13 variables as predictors: four metrics of wetland condition from the Ohio Rapid Assessment Method (ORAM), a wetland vegetation index of biotic integrity, and eight metrics from a landscape disturbance index. For all iterations, the best model included the single ORAM metric that assesses habitat alteration, substrate disturbance, and habitat development within a wetland. Our results align with results of similar studies that have associated high scores for wetland vegetation indices of biotic integrity with low habitat alteration and substrate disturbance within wetlands. Thus, implementing similar management practices (e.g., not removing downed woody debris, retaining natural morphological features, decreasing nutrient input from surrounding agricultural lands) could concurrently increase ecological integrity of both plant and amphibian communities in a wetland. Further, our results have the unexpected effect of making progress toward a more unifying theory of ecological indices.

Humus soil as a critical driver of flora conversion on karst rock outcrops.

PubMed

Zhu, Xiai; Shen, Youxin; He, Beibei; Zhao, Zhimeng

2017-10-03

Rock outcrop is an important habitat supporting plant communities in karst landscape. However, information on the restoration of higher biotic populations on outcrops is limited. Here, we investigated the diversity, biomass changes of higher vascular plants (VP) and humus soil (HS) on karst outcrops during a restoration process. We surveyed VP on rock outcrops and measured HS reserved by various rock microhabitats in a rock desertification ecosystem (RDE), an anthropogenic forest ecosystem (AFE), and a secondary forest ecosystem (SFE) in Shilin County, southwest China. HS metrics (e.g. quantity and nutrients content) and VP metrics (e.g. richness, diversity and biomass) were higher at AFE than at RDE, but lower than at SFE, suggesting that the restoration of soil subsystem vegetation increased HS properties and favored the succession of VP on rock outcrops. There was significantly positive correlation between VP metrics and HS amount, indicating that the succession of VP was strongly affected by availability and heterogeneity of HS in various rock microhabitats. Thus, floral succession of rock subsystem was slow owing to the limited resources on outcrops, although the vegetation was restored in soil subsystem.

Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia

PubMed Central

Singh, Minerva; Evans, Damian; Coomes, David A.; Friess, Daniel A.; Suy Tan, Boun; Samean Nin, Chan

2016-01-01

This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests. PMID:27176218

Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia.

PubMed

Singh, Minerva; Evans, Damian; Coomes, David A; Friess, Daniel A; Suy Tan, Boun; Samean Nin, Chan

2016-01-01

This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests.

Light Limitation within Southern New Zealand Kelp Forest Communities

PubMed Central

Desmond, Matthew J.; Pritchard, Daniel W.; Hepburn, Christopher D.

2015-01-01

Light is the fundamental driver of primary productivity in the marine environment. Reduced light availability has the potential to alter the distribution, community composition, and productivity of key benthic primary producers, potentially reducing habitat and energy provision to coastal food webs. We compared the underwater light environment of macroalgal dominated shallow subtidal rocky reef habitats on a coastline modified by human activities with a coastline of forested catchments. Key metrics describing the availability of photosynthetically active radiation (PAR) were determined over 295 days and were related to macroalgal depth distribution, community composition, and standing biomass patterns, which were recorded seasonally. Light attenuation was more than twice as high in shallow subtidal zones along the modified coast. Macroalgal biomass was 2–5 times greater within forested sites, and even in shallow water (2m) a significant difference in biomass was observed. Long-term light dose provided the best explanation for differences in observed biomass between modified and forested coasts, with light availability over the study period differing by 60 and 90 mol photons m−2 at 2 and 10 metres, respectively. Higher biomass on the forested coast was driven by the presence of larger individuals rather than species diversity or density. This study suggests that commonly used metrics such as species diversity and density are not as sensitive as direct measures of biomass when detecting the effects of light limitation within macroalgal communities. PMID:25902185

Observing Spring and Fall Phenology in a Deciduous Forest with Aerial Drone Imagery.

PubMed

Klosterman, Stephen; Richardson, Andrew D

2017-12-08

Plant phenology is a sensitive indicator of the effects of global change on terrestrial ecosystems and controls the timing of key ecosystem functions including photosynthesis and transpiration. Aerial drone imagery and photogrammetric techniques promise to advance the study of phenology by enabling the creation of distortion-free orthomosaics of plant canopies at the landscape scale, but with branch-level image resolution. The main goal of this study is to determine the leaf life cycle events corresponding to phenological metrics derived from automated analyses based on color indices calculated from drone imagery. For an oak-dominated, temperate deciduous forest in the northeastern USA, we find that plant area index (PAI) correlates with a canopy greenness index during spring green-up, and a canopy redness index during autumn senescence. Additionally, greenness and redness metrics are significantly correlated with the timing of budburst and leaf expansion on individual trees in spring. However, we note that the specific color index for individual trees must be carefully chosen if new foliage in spring appears red, rather than green-which we observed for some oak trees. In autumn, both decreasing greenness and increasing redness correlate with leaf senescence. Maximum redness indicates the beginning of leaf fall, and the progression of leaf fall correlates with decreasing redness. We also find that cooler air temperature microclimates near a forest edge bordering a wetland advance the onset of senescence. These results demonstrate the use of drones for characterizing the organismic-level variability of phenology in a forested landscape and advance our understanding of which phenophase transitions correspond to color-based metrics derived from digital image analysis.

Observing Spring and Fall Phenology in a Deciduous Forest with Aerial Drone Imagery

PubMed Central

Richardson, Andrew D.

2017-01-01

Plant phenology is a sensitive indicator of the effects of global change on terrestrial ecosystems and controls the timing of key ecosystem functions including photosynthesis and transpiration. Aerial drone imagery and photogrammetric techniques promise to advance the study of phenology by enabling the creation of distortion-free orthomosaics of plant canopies at the landscape scale, but with branch-level image resolution. The main goal of this study is to determine the leaf life cycle events corresponding to phenological metrics derived from automated analyses based on color indices calculated from drone imagery. For an oak-dominated, temperate deciduous forest in the northeastern USA, we find that plant area index (PAI) correlates with a canopy greenness index during spring green-up, and a canopy redness index during autumn senescence. Additionally, greenness and redness metrics are significantly correlated with the timing of budburst and leaf expansion on individual trees in spring. However, we note that the specific color index for individual trees must be carefully chosen if new foliage in spring appears red, rather than green—which we observed for some oak trees. In autumn, both decreasing greenness and increasing redness correlate with leaf senescence. Maximum redness indicates the beginning of leaf fall, and the progression of leaf fall correlates with decreasing redness. We also find that cooler air temperature microclimates near a forest edge bordering a wetland advance the onset of senescence. These results demonstrate the use of drones for characterizing the organismic-level variability of phenology in a forested landscape and advance our understanding of which phenophase transitions correspond to color-based metrics derived from digital image analysis. PMID:29292742

Thermocouple Probe Orientation Affects Prescribed Fire Behavior Estimation.

PubMed

Coates, T Adam; Chow, Alex T; Hagan, Donald L; Waldrop, Thomas A; Wang, G Geoff; Bridges, William C; Rogers, Mary-Frances; Dozier, James H

2018-01-01

Understanding the relationship between fire intensity and fuel mass is essential information for scientists and forest managers seeking to manage forests using prescribed fires. Peak burning temperature, duration of heating, and area under the temperature profile are fire behavior metrics obtained from thermocouple-datalogger assemblies used to characterize prescribed burns. Despite their recurrent usage in prescribed burn studies, there is no simple protocol established to guide the orientation of thermocouple installation. Our results from dormant and growing season burns in coastal longleaf pine ( Mill.) forests in South Carolina suggest that thermocouples located horizontally at the litter-soil interface record significantly higher estimates of peak burning temperature, duration of heating, and area under the temperature profile than thermocouples extending 28 cm vertically above the litter-soil interface ( < 0.01). Surprisingly, vertical and horizontal estimates of these measures did not show strong correlation with one another ( ≤ 0.14). The horizontal duration of heating values were greater in growing season burns than in dormant season burns ( < 0.01), but the vertical values did not indicate this difference ( = 0.52). Field measures of fuel mass and depth before and after fire showed promise as significant predictive variables ( ≤ 0.05) for the fire behavior metrics. However, all correlation coefficients were less than or equal to = 0.41. Given these findings, we encourage scientists, researchers, and managers to carefully consider thermocouple orientation when investigating fire behavior metrics, as orientation may affect estimates of fire intensity and the distinction of fire treatment effects, particularly in forests with litter-dominated surface fuels. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling.

PubMed

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha; Thompson, Jill; Zimmerman, Jess K; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate. © 2017 John Wiley & Sons Ltd.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

USGS Publications Warehouse

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Mapping forest characteristics at fine resolution across large landscapes of the southeastern United States using NAIP imagery and FIA field plot data

Treesearch

John Hogland; Nathaniel Anderson; Joseph St. Peter; Jason Drake; Paul Medley

2018-01-01

Accurate information is important for effective management of natural resources. In the field of forestry, field measurements of forest characteristics such as species composition, basal area, and stand density are used to inform and evaluate management activities. Quantifying these metrics accurately across large landscapes in a meaningful way is extremely important...

Remote sensing of spring phenology in northeastern forests: A comparison of methods, field metrics and sources of uncertainty

Treesearch

Katharine White; Jennifer Pontius; Paul Schaberg

2014-01-01

Current remote sensing studies of phenology have been limited to coarse spatial or temporal resolution and often lack a direct link to field measurements. To address this gap, we compared remote sensing methodologies using Landsat Thematic Mapper (TM) imagery to extensive field measurements in a mixed northern hardwood forest. Five vegetation indices, five mathematical...

Aboveground tree biomass on productive forest land in Alaska.

Treesearch

John Yarie; Delbert Mead

1982-01-01

Total aboveground woody biomass of trees on forest land that can produce 1.4 cubic m eters per hectare per year of industrial wood in Alaska is 1.33 billion metric tons green weight. The estimated energy value of the standing woody biomass is 11.9 x 10'5 Btu's. Statewide tables of biomass and energy values for softwoods, hardwoods, and species groups are...

Inventories of woody residues and solid wood waste in the United States, 2002

Treesearch

David B. McKeever

2004-01-01

Large amounts of woody residues and wood waste are generated annually in the United States. In 2002, an estimated 240 million metric tons was generated during the extraction of timber from the Nation’s forests, from forestry cultural operations, in the conversion of forest land to nonforest uses, in the initial processing of roundwood timber into usable products, in...

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.

Effects of seasonal snow and climatic controls on spring and autumn phenology in Alpine forest regions

NASA Astrophysics Data System (ADS)

Xie, J.; Kneubühler, M.; Garonna, I.; Jong, R. D.; Schaepman, M. E.

2017-12-01

Seasonal accumulation and melt of snow in mountainous regions varies with meteorological factors and affects forest phenology in various ways. However, our knowledge about the relationship between seasonal snow and forest phenology - and particularly its topographical variation - is still limited and needs further investigation. We tested the relationship between a number of snow, meteorological and land surface phenology metrics (satellite-derived and gridded) in the forested regions of the Swiss Alps for the period of 2003-2014. Satellite-derived start of season and end of season metrics (SOS and EOS, respectively), in combination with snow accumulation (SA), snow cover melt date (SCMD), monthly maximum, mean and minimum temperature, monthly mean relative sunshine duration and precipitation were considered in our analysis. We calculated Spearman's rank correlation of interannual differences (Δ) of SOS and EOS with snow and meteorological metrics and examined the variation of these correlations with elevation (from 200 up to 2400 meter above sea level (m a.s.l.)). We found SOS to have a significant (p < 0.05) positive correlation with both SCMD (mean R=0.71, over 34.2% of all pixels) and SA (mean R=0.62, over 19.0% of all pixels). On the other hand, SOS showed a significant negative correlation with spring temperature and relative sunshine duration. EOS showed significant positive correlation with autumn temperature (mean R=0.70, over 30.4% of all pixels). Moreover, we found the forest phenology of the northern and eastern Swiss Alps to be more sensitive to seasonal snow but less sensitive to meteorological factors than in the southern and western Swiss Alps. The areas which are sensitive to seasonal snow and meteorological factors are more pronounced at higher elevations. We conclude that the effect of snow melt on spring phenology is of equal magnitude as spring temperature and relative sunshine duration. Autumn forest phenology is mainly influenced by autumn temperature. The effects of seasonal snow and climatic controls on spring and autumn phenology are more pronounced at higher than at lower elevations. We suggest that alpine forest ecosystems above 1500 m a.s.l. will therefore be particularly sensitive to future changes of seasonal snow and climate warming scenarios in the Swiss Alps.

Patch Size, Functional Isolation, Visibility and Matrix Permeability Influences Neotropical Primate Occurrence within Highly Fragmented Landscapes

PubMed Central

da Silva, Lucas Goulart; Ribeiro, Milton Cezar; Hasui, Érica; da Costa, Carla Aparecida; da Cunha, Rogério Grassetto Teixeira

2015-01-01

Forest fragmentation and habitat loss are among the major current extinction causes. Remaining fragments are mostly small, isolated and showing poor quality. Being primarily arboreal, Neotropical primates are generally sensitive to fragmentation effects. Furthermore, primates are involved in complex ecological process. Thus, landscape changes that negatively interfere with primate population dynamic affect the structure, composition, and ultimately the viability of the whole community. We evaluated if fragment size, isolation and visibility and matrix permeability are important for explaining the occurrence of three Neotropical primate species. Employing playback, we verified the presence of Callicebus nigrifrons, Callithrix aurita and Sapajus nigritus at 45 forest fragments around the municipality of Alfenas, Brazil. We classified the landscape and evaluated the metrics through predictive models of occurrence. We selected the best models through Akaike Selection Criterion. Aiming at validating our results, we applied the plausible models to another region (20 fragments at the neighboring municipality of Poço Fundo, Brazil). Twelve models were plausible, and three were validated, two for Sapajus nigritus (Area and Area+Visibility) and one for Callicebus nigrifrons (Area+Matrix). Our results reinforce the contribution of fragment size to maintain biodiversity within highly degraded habitats. At the same time, they stress the importance of including novel, biologically relevant metrics in landscape studies, such as visibility and matrix permeability, which can provide invaluable help for similar studies in the future and on conservation practices in the long run. PMID:25658108

Influence of habitat and land use on the assemblages of ephemeroptera, plecoptera, and trichoptera in neotropical streams.

PubMed

Amaral, Pedro Henrique Monteiro do; Silveira, Lidimara Souza da; Rosa, Beatriz Figueiraujo Jabour Vescovi; Oliveira, Vívian Campos de; Alves, Roberto da Gama

2015-01-01

Insects of the orders Ephemeroptera, Plecoptera, and Trichoptera (EPT) are often used to assess the conditions of aquatic environments, but few studies have examined the differences in these communities between riffles and pools. Our objective was to test whether riffles shelter greater richness and abundance of EPT, as well as to assess the sensitivity of these insects for detecting impacts from different land uses in streams in southeastern Brazil. Samples were collected in the dry season of 2012 with a Surber sampler in riffles and pools of nine streams (forest, pasture, and urban areas). Principal component analysis distinguished the streams according to different land uses as a function of percentage of plant cover and water oxygenation level and showed partial distinction between riffles and pools as a function of current speed and percentage of ultrafine sand. Detrended correspondence analysis indicated the distinction in EPT composition between riffles and pools, except in urban streams. The results of this study confirm the expected differences in the EPT fauna structure between riffles and pools, especially in forest and pasture environments. The individual metrics of riffle and pool assemblages showed significantly different responses to land use. Therefore, we suggest individual sampling of riffles and pools, since the metrics of these assemblages' insects can differ between these habitats and influence the results of assessments in low-order streams. © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America.

A global review of past land use, climate, and active vs. passive restoration effects on forest recovery

PubMed Central

Meli, Paula; Holl, Karen D.; Rey Benayas, José María; Jones, Holly P.; Jones, Peter C.; Montoya, Daniel; Moreno Mateos, David

2017-01-01

Global forest restoration targets have been set, yet policy makers and land managers lack guiding principles on how to invest limited resources to achieve them. We conducted a meta-analysis of 166 studies in naturally regenerating and actively restored forests worldwide to answer: (1) To what extent do floral and faunal abundance and diversity and biogeochemical functions recover? (2) Does recovery vary as a function of past land use, time since restoration, forest region, or precipitation? (3) Does active restoration result in more complete or faster recovery than passive restoration? Overall, forests showed a high level of recovery, but the time to recovery depended on the metric type measured, past land use, and region. Abundance recovered quickly and completely, whereas diversity recovered slower in tropical than in temperate forests. Biogeochemical functions recovered more slowly after agriculture than after logging or mining. Formerly logged sites were mostly passively restored and generally recovered quickly. Mined sites were nearly always actively restored using a combination of planting and either soil amendments or recontouring topography, which resulted in rapid recovery of the metrics evaluated. Actively restoring former agricultural land, primarily by planting trees, did not result in consistently faster or more complete recovery than passively restored sites. Our results suggest that simply ending the land use is sufficient for forests to recover in many cases, but more studies are needed that directly compare the value added of active versus passive restoration strategies in the same system. Investments in active restoration should be evaluated relative to the past land use, the natural resilience of the system, and the specific objectives of each project. PMID:28158256

A global review of past land use, climate, and active vs. passive restoration effects on forest recovery.

PubMed

Meli, Paula; Holl, Karen D; Rey Benayas, José María; Jones, Holly P; Jones, Peter C; Montoya, Daniel; Moreno Mateos, David

2017-01-01

Global forest restoration targets have been set, yet policy makers and land managers lack guiding principles on how to invest limited resources to achieve them. We conducted a meta-analysis of 166 studies in naturally regenerating and actively restored forests worldwide to answer: (1) To what extent do floral and faunal abundance and diversity and biogeochemical functions recover? (2) Does recovery vary as a function of past land use, time since restoration, forest region, or precipitation? (3) Does active restoration result in more complete or faster recovery than passive restoration? Overall, forests showed a high level of recovery, but the time to recovery depended on the metric type measured, past land use, and region. Abundance recovered quickly and completely, whereas diversity recovered slower in tropical than in temperate forests. Biogeochemical functions recovered more slowly after agriculture than after logging or mining. Formerly logged sites were mostly passively restored and generally recovered quickly. Mined sites were nearly always actively restored using a combination of planting and either soil amendments or recontouring topography, which resulted in rapid recovery of the metrics evaluated. Actively restoring former agricultural land, primarily by planting trees, did not result in consistently faster or more complete recovery than passively restored sites. Our results suggest that simply ending the land use is sufficient for forests to recover in many cases, but more studies are needed that directly compare the value added of active versus passive restoration strategies in the same system. Investments in active restoration should be evaluated relative to the past land use, the natural resilience of the system, and the specific objectives of each project.

Landscape structure and climate influences on hydrologic response

NASA Astrophysics Data System (ADS)

Nippgen, Fabian; McGlynn, Brian L.; Marshall, Lucy A.; Emanuel, Ryan E.

2011-12-01

Climate variability and catchment structure (topography, geology, vegetation) have a significant influence on the timing and quantity of water discharged from mountainous catchments. How these factors combine to influence runoff dynamics is poorly understood. In this study we linked differences in hydrologic response across catchments and across years to metrics of landscape structure and climate using a simple transfer function rainfall-runoff modeling approach. A transfer function represents the internal catchment properties that convert a measured input (rainfall/snowmelt) into an output (streamflow). We examined modeled mean response time, defined as the average time that it takes for a water input to leave the catchment outlet from the moment it reaches the ground surface. We combined 12 years of precipitation and streamflow data from seven catchments in the Tenderfoot Creek Experimental Forest (Little Belt Mountains, southwestern Montana) with landscape analyses to quantify the first-order controls on mean response times. Differences between responses across the seven catchments were related to the spatial variability in catchment structure (e.g., slope, flowpath lengths, tree height). Annual variability was largely a function of maximum snow water equivalent. Catchment averaged runoff ratios exhibited strong correlations with mean response time while annually averaged runoff ratios were not related to climatic metrics. These results suggest that runoff ratios in snowmelt dominated systems are mainly controlled by topography and not by climatic variability. This approach provides a simple tool for assessing differences in hydrologic response across diverse watersheds and climate conditions.

Not seeing the forest for the trees: size of the minimum spanning trees (MSTs) forest and branch significance in MST-based phylogenetic analysis.

PubMed

Teixeira, Andreia Sofia; Monteiro, Pedro T; Carriço, João A; Ramirez, Mário; Francisco, Alexandre P

2015-01-01

Trees, including minimum spanning trees (MSTs), are commonly used in phylogenetic studies. But, for the research community, it may be unclear that the presented tree is just a hypothesis, chosen from among many possible alternatives. In this scenario, it is important to quantify our confidence in both the trees and the branches/edges included in such trees. In this paper, we address this problem for MSTs by introducing a new edge betweenness metric for undirected and weighted graphs. This spanning edge betweenness metric is defined as the fraction of equivalent MSTs where a given edge is present. The metric provides a per edge statistic that is similar to that of the bootstrap approach frequently used in phylogenetics to support the grouping of taxa. We provide methods for the exact computation of this metric based on the well known Kirchhoff's matrix tree theorem. Moreover, we implement and make available a module for the PHYLOViZ software and evaluate the proposed metric concerning both effectiveness and computational performance. Analysis of trees generated using multilocus sequence typing data (MLST) and the goeBURST algorithm revealed that the space of possible MSTs in real data sets is extremely large. Selection of the edge to be represented using bootstrap could lead to unreliable results since alternative edges are present in the same fraction of equivalent MSTs. The choice of the MST to be presented, results from criteria implemented in the algorithm that must be based in biologically plausible models.

Watershed-Scale Land Use Activities Influence the Physiological Condition of Stream Fish.

PubMed

King, Gregory D; Chapman, Jacqueline M; Midwood, Jonathan D; Cooke, Steven J; Suski, Cory D

2016-01-01

Land use changes within watersheds can have large effects on stream ecosystems, but the mechanistic basis of those effects remains poorly understood. While changes to population size presumably reflect underlying variation in organismal health and condition, such individual-level metrics are rarely evaluated in the context of ecosystem disturbance. To address this deficiency, we combined physiological sampling with geographic information systems to quantify the effects of land use on physiological indicators of health in largemouth bass. More specifically, we first quantified blood metrics relating to nutrition, oxidative stress, and the glucocorticoid stress response from largemouth bass residing in eight watersheds. We then used Akaike's information criterion to define relationships between these blood metrics and land cover, including forests, agricultural areas, urban areas, and wetlands. The proportion of forest cover in a watershed was the best predictor of blood metrics representing recent feeding and resistance to oxidative stress, whereas the proportion of wetlands was the best predictor of glucocorticoid function; however, further investigation is needed, as the explanatory power of the models was relatively low. Patterns in energy reserves were not influenced by any land use practices. Interestingly, anthropogenic land use categories, such as urban and agricultural areas, were not the best predictor for any blood metrics. Together, our results indicate that fish health is most related to natural features of a landscape rather than anthropogenic land uses. Furthermore, these findings suggest that physiological methods could supplement traditional population and community assessments to develop a more comprehensive understanding of ecosystem interactions and improve stream management.

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

PubMed

Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams

PubMed Central

Epting, Steven M.; Hosen, Jacob D.; Alexander, Laurie C.; Lang, Megan W.; Armstrong, Alec W.

2018-01-01

Abstract Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full‐water year (2014–2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj‐R 2 = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid‐Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area. PMID:29576682

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively.

Mediterranean dryland Mosaic: The effect of scale on core area metrics

NASA Astrophysics Data System (ADS)

Alhamad, Mohammad Noor; Alrababah, Mohammad

2014-05-01

Quantifying landscape spatial pattern is essential to understanding the relationship between landscape structure and ecological functions and process. Many landscape metrics have been developed to quantify spatial heterogeneity. Landscape metrics have been employed to measure the impact of humans on landscapes. We examined the response of four core areas metrics to a large range of grain sizes in Mediterranean dryland landscapes. The investigated metrics were (1) mean core area (CORE-MN), (2) area weighted mean core area (CORE-AM) , (3) total core area (TCA) and (4) core area percentage of landscape (CPLAND) within six land use types (urban, agriculture, olive orchids, forestry, shrubland and rangeland). Agriculture areas showed the highest value for minimum TCA (2779.4 ha) within the tested grain sizes, followed by rangeland (1778.3 ha) and Forest (1488.5 ha). On the other hand, shrubland showed the lowest TCA (8.0 ha). The minimum CPLAND values were ranged from 0.002 for shrubland to 0.682 for agriculture land use. The maximum CORE-MN among the tested land use type at all levels of grain sizes was exhibited by agriculture land use type (519.759 ha). The core area metrics showed three types of behavior in response to changing grain size in all landuse types. CORE-MN showed predictable relationship, best explained by non-linear responses to changing grain size (R2=0.99). Both TCA and CPLAND exhibited domain of scale effect in response to changing grain size. The threshold behavior for TCA and CPLAND was at the 4 x 4 grain size (about 1.3 ha). However, CORE-AM exhibited erratic behavior. The unique domain of scale-like behavior may be attributed to the unique characteristics of dryland Mediterranean landscapes; where both natural processes and ancient human activities play a great role in shaping the apparent pattern of the landscape

Evaluating Changes in Distributions of Summer Stream Temperature following Forest Harvest

NASA Astrophysics Data System (ADS)

Johnson, S. L.; Reiter, M.; Jones, J.

2016-12-01

Stream temperature heat budgets are influenced by numerous processes; changes in incoming radiation have been shown to be a major driver of increased stream temperatures. Maximum daily temperature is a commonly used metric for evaluating stream temperature responses to land use. However, single metrics are not able to fully represent the magnitude and duration of temperatures experienced by instream biota. Analyses that make use of all the data: a) more accurately characterize shifts in summer stream temperature regimes, b) quantify potential exposure to critical and non-critical temperatures, and c) help researchers and managers to better understand stream temperature responses to manipulation of streamside and watershed vegetation. Here we examine the distributions of summer stream temperatures before and after forest harvest in the Trask River Watershed Study, in northwestern Oregon. We studied 15 small streams for 10 years; half of the sites had their catchments clearcut harvested in 2012. Four sites had no buffers, with some leave trees, and three sites had 25 ft buffers on both sides. Temperatures were measured during at 30min intervals. Even though these streams are generally cold, we observed high spatial and temporal variation among sites and years, with some sites having normally distributed temperatures, while others showed skewed distributions and long tails. Forest cover, aspect or elevation were not good predictors of temperature distributions pre-harvest. Preliminary analyses using travel time of the stream water suggest that sites with hyporheic flows had narrower distributions of temperatures. After harvest, sites without buffers showed the greatest shift in distributions of temperatures and widest temperature ranges, while sites with narrow buffers showed little change. We are exploring the implications of shifts in temperature distributions before and after harvest against the known thermal tolerances for the dominant resident species (Ascaphus truei; tailed frog tadpoles) in these headwater streams. Rarely in forested mountain landscapes do stream temperatures exceed lethal thresholds for cold water biota; with these analyses, we are quantifying chronic exposure, which could subsequently result in shifts in phenology or community structure.

A multi-scale metrics approach to forest fragmentation for Strategic Environmental Impact Assessment

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

Kim, Eunyoung, E-mail: eykim@kei.re.kr; Song, Wonkyong, E-mail: wksong79@gmail.com; Lee, Dongkun, E-mail: dklee7@snu.ac.kr

Forests are becoming severely fragmented as a result of land development. South Korea has responded to changing community concerns about environmental issues. The nation has developed and is extending a broad range of tools for use in environmental management. Although legally mandated environmental compliance requirements in South Korea have been implemented to predict and evaluate the impacts of land-development projects, these legal instruments are often insufficient to assess the subsequent impact of development on the surrounding forests. It is especially difficult to examine impacts on multiple (e.g., regional and local) scales in detail. Forest configuration and size, including forest fragmentationmore » by land development, are considered on a regional scale. Moreover, forest structure and composition, including biodiversity, are considered on a local scale in the Environmental Impact Assessment process. Recently, the government amended the Environmental Impact Assessment Act, including the SEA, EIA, and small-scale EIA, to require an integrated approach. Therefore, the purpose of this study was to establish an impact assessment system that minimizes the impacts of land development using an approach that is integrated across multiple scales. This study focused on forest fragmentation due to residential development and road construction sites in selected Congestion Restraint Zones (CRZs) in the Greater Seoul Area of South Korea. Based on a review of multiple-scale impacts, this paper integrates models that assess the impacts of land development on forest ecosystems. The applicability of the integrated model for assessing impacts on forest ecosystems through the SEIA process is considered. On a regional scale, it is possible to evaluate the location and size of a land-development project by considering aspects of forest fragmentation, such as the stability of the forest structure and the degree of fragmentation. On a local scale, land-development projects should consider the distances at which impacts occur in the vicinity of the forest ecosystem, and these considerations should include the impacts on forest vegetation and bird species. Impacts can be mitigated by considering the distances at which these influences occur. In particular, this paper presents an integrated environmental impact assessment system to be applied in the SEIA process. The integrated assessment system permits the assessment of the cumulative impacts of land development on multiple scales. -- Highlights: • The model is to assess the impact of forest fragmentation across multiple scales. • The paper suggests the type of forest fragmentation on a regional scale. • The type can be used to evaluate the location and size of a land development. • The paper shows the influence distance of land development on a local scale. • The distance can be used to mitigate the impact at an EIA process.« less

Response of brown-headed cowbirds and three host species to thinning treatments in low-elevation ponderosa pine forests along the northern Colorado Front Range

USGS Publications Warehouse

Keeley, W.H.; Germaine, Stephen S.; Stanley, Thomas R.; Spaulding, Sarah A.; Wanner, C.E.

2013-01-01

Thinning ponderosa pine (Pinus ponderosa) forests to achieve desired ecological conditions remains a priority in the North American west. In addition to reducing the risk of high-severity wildfires in unwanted areas, stand thinning may increase wildlife and plant diversity and provide increased opportunity for seedling recruitment. We initiated conservative (i.e. minimal removal of trees) ponderosa stand thinning treatments with the goals of reducing fire risk and improving habitat conditions for native wildlife and flora. We then compared site occupancy of brown-headed cowbirds (Molothrus ater), chipping sparrows (Spizella passerina), plumbeous vireos (Vireo plumbeus), and western wood-pewees (Contopus sordidulus) in thinned and unthinned (i.e., control) forest stands from 2007 to 2009. Survey stations located in thinned stands had 64% fewer trees/ha, 25% less canopy cover, and 23% less basal area than stations in control stands. Occupancy by all three host species was negatively associated with tree density, suggesting that these species respond favorably to forest thinning treatments in ponderosa pine forests. We also encountered plumbeous vireos more frequently in plots closer to an ecotonal (forest/grassland) edge, an association that may increase their susceptibility to edge-specialist, brood parasites like brown-headed cowbirds. Occupancy of brown-headed cowbirds was not related to forest metrics but was related to occupancy by plumbeous vireos and the other host species in aggregate, supporting previous reports on the affiliation between these species. Forest management practices that promote heterogeneity in forest stand structure may benefit songbird populations in our area, but these treatments may also confer costs associated with increased cowbird occupancy. Further research is required to understand more on the complex relationships between occupancy of cowbirds and host species, and between cowbird occupancy and realized rates of nest parasitism.

VT0005 In Action: National Forest Biomass Inventory Using Airborne Lidar Sampling

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Xu, L.; Meyer, V.; Ferraz, A.; Yang, Y.; Shapiro, A.; Bastin, J. F.

2016-12-01

Tropical countries are required to produce robust and verifiable estimates of forest carbon stocks for successful implementation of climate change mitigation. Lack of systematic national inventory data due to access, cost, and infrastructure, has impacted the capacity of most tropical countries to accurately report the GHG emissions to the international community. Here, we report on the development of the aboveground forest carbon (AGC) map of Democratic Republic of Congo (DRC) by using the VCS (Verified Carbon Standard) methodology developed by Sassan Saatchi (VT0005) using high-resolution airborne LiDAR samples. The methodology provides the distribution of the carbon stocks in aboveground live trees of more than 150 million ha of forests at 1-ha spatial resolution in DRC using more than 430, 000 ha of systematic random airborne Lidar inventory samples of forest structure. We developed a LIDAR aboveground biomass allometry using more than 100 1-ha plots across forest types and power-law model with LIDAR height metrics and average landscape scale wood density. The methodology provided estimates of forest biomass over the entire country using two approaches: 1) mean, variance, and total carbon estimates for each forest type present in DRC using inventory statistical techniques, and 2) a wall-to-wall map of the forest biomass extrapolated using satellite radar (ALOS PALSAR), surface topography from SRTM, and spectral information from Landsat (TM) and machine learning algorithms. We present the methodology, the estimates of carbon stocks and the spatial uncertainty over the entire country. AcknowledgementsThe theoretical research was carried out partially at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration, and the design and implementation in the Democratic Republic of Congo was carried out at the Institute of Environment and Sustainability at University of California Los Angeles through the support of the International Climate Initiative of the German Ministry of Environment, Conservation and Nuclear Security, and the KFW Development Bank.

ROE Carbon Storage - Forest Biomass

EPA Pesticide Factsheets

This polygon dataset depicts the density of forest biomass in counties across the United States, in terms of metric tons of carbon per square mile of land area. These data were provided in spreadsheet form by the U.S. Department of Agriculture (USDA) Forest Service. To produce the Web mapping application, EPA joined the spreadsheet with a shapefile of U.S. county (and county equivalent) boundaries downloaded from the U.S. Census Bureau. EPA calculated biomass density based on the area of each county polygon. These data sets were converted into a single polygon feature class inside a file geodatabase.

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

NASA Technical Reports Server (NTRS)

Morton, D. C.; Keller, M.; Cook, B. D.; Hunter, Maria; Sales, Marcio; Spinelli, L.; Victoria, D.; Andersen, H.-E.; Saleska, S.

2012-01-01

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Validating LiDAR Derived Estimates of Canopy Height, Structure and Fractional Cover in Riparian Areas: A Comparison of Leaf-on and Leaf-off LiDAR Data

NASA Astrophysics Data System (ADS)

Wasser, L. A.; Chasmer, L. E.; Taylor, A.; Day, R.

2010-12-01

Characterization of riparian buffers is integral to understanding the landscape scale impacts of disturbance on wildlife and aquatic ecosystems. Riparian buffers may be characterized using in situ plot sampling or via high resolution remote sensing. Field measurements are time-consuming and may not cover a broad range of ecosystem types. Further, spectral remote sensing methods introduce a compromise between spatial resolution (grain) and area extent. Airborne LiDAR can be used to continuously map and characterize riparian vegetation structure and composition due to the three-dimensional reflectance of laser pulses within and below the canopy, understory and at the ground surface. The distance between reflections (or ‘returns’) allows for detection of narrow buffer corridors at the landscape scale. There is a need to compare leaf-off and leaf-on surveyed LiDAR data with in situ measurements to assess accuracy in landscape scale analysis. These comparisons are particularly important considering increased availability of leaf-off surveyed LiDAR datasets. And given this increased availability, differences between leaf-on and leaf-off derived LiDAR metrics are largely unknown for riparian vegetation of varying composition and structure. This study compares the effectiveness of leaf-on and leaf-off LiDAR in characterizing riparian buffers of varying structure and composition as compared to field measurements. Field measurements were used to validate LiDAR derived metrics. Vegetation height, canopy cover, density and overstory and understory species composition were recorded in 80 random plots of varying vegetation type, density and structure within a Pennsylvania watershed (-77.841, 40.818). Plot data were compared with LiDAR data collected during leaf on and leaf off conditions to determine 1) accuracy of LiDAR derived metrics compared to field measures and 2) differences between leaf-on and leaf-off LiDAR metrics. Results illustrate that differences exist between metrics derived from leaf on and leaf-off surveyed LiDAR. There is greater variability between the two datasets within taller deciduous and mixed (conifer and deciduous) vegetation compared to shorter deciduous and mixed vegetation. Differences decrease as stand density increases for both mixed and deciduous forests. LiDAR derived canopy height is more sensitive to understory vegetation as stand density decreases making measurement of understory vegetation in the field important in the validation process. Finally, while leaf-on LiDAR is often preferred for vegetation analysis, results suggest that leaf-off LiDAR may be sufficient to categorize vegetation into height classes to be used for landscape scale habitat models.

Deriving Animal Behaviour from High-Frequency GPS: Tracking Cows in Open and Forested Habitat

PubMed Central

de Weerd, Nelleke; van Langevelde, Frank; van Oeveren, Herman; Nolet, Bart A.; Kölzsch, Andrea; Prins, Herbert H. T.; de Boer, W. Fred

2015-01-01

The increasing spatiotemporal accuracy of Global Navigation Satellite Systems (GNSS) tracking systems opens the possibility to infer animal behaviour from tracking data. We studied the relationship between high-frequency GNSS data and behaviour, aimed at developing an easily interpretable classification method to infer behaviour from location data. Behavioural observations were carried out during tracking of cows (Bos Taurus) fitted with high-frequency GPS (Global Positioning System) receivers. Data were obtained in an open field and forested area, and movement metrics were calculated for 1 min, 12 s and 2 s intervals. We observed four behaviour types (Foraging, Lying, Standing and Walking). We subsequently used Classification and Regression Trees to classify the simultaneously obtained GPS data as these behaviour types, based on distances and turning angles between fixes. GPS data with a 1 min interval from the open field was classified correctly for more than 70% of the samples. Data from the 12 s and 2 s interval could not be classified successfully, emphasizing that the interval should be long enough for the behaviour to be defined by its characteristic movement metrics. Data obtained in the forested area were classified with a lower accuracy (57%) than the data from the open field, due to a larger positional error of GPS locations and differences in behavioural performance influenced by the habitat type. This demonstrates the importance of understanding the relationship between behaviour and movement metrics, derived from GNSS fixes at different frequencies and in different habitats, in order to successfully infer behaviour. When spatially accurate location data can be obtained, behaviour can be inferred from high-frequency GNSS fixes by calculating simple movement metrics and using easily interpretable decision trees. This allows for the combined study of animal behaviour and habitat use based on location data, and might make it possible to detect deviations in behaviour at the individual level. PMID:26107643

Deriving Animal Behaviour from High-Frequency GPS: Tracking Cows in Open and Forested Habitat.

PubMed

de Weerd, Nelleke; van Langevelde, Frank; van Oeveren, Herman; Nolet, Bart A; Kölzsch, Andrea; Prins, Herbert H T; de Boer, W Fred

2015-01-01

The increasing spatiotemporal accuracy of Global Navigation Satellite Systems (GNSS) tracking systems opens the possibility to infer animal behaviour from tracking data. We studied the relationship between high-frequency GNSS data and behaviour, aimed at developing an easily interpretable classification method to infer behaviour from location data. Behavioural observations were carried out during tracking of cows (Bos Taurus) fitted with high-frequency GPS (Global Positioning System) receivers. Data were obtained in an open field and forested area, and movement metrics were calculated for 1 min, 12 s and 2 s intervals. We observed four behaviour types (Foraging, Lying, Standing and Walking). We subsequently used Classification and Regression Trees to classify the simultaneously obtained GPS data as these behaviour types, based on distances and turning angles between fixes. GPS data with a 1 min interval from the open field was classified correctly for more than 70% of the samples. Data from the 12 s and 2 s interval could not be classified successfully, emphasizing that the interval should be long enough for the behaviour to be defined by its characteristic movement metrics. Data obtained in the forested area were classified with a lower accuracy (57%) than the data from the open field, due to a larger positional error of GPS locations and differences in behavioural performance influenced by the habitat type. This demonstrates the importance of understanding the relationship between behaviour and movement metrics, derived from GNSS fixes at different frequencies and in different habitats, in order to successfully infer behaviour. When spatially accurate location data can be obtained, behaviour can be inferred from high-frequency GNSS fixes by calculating simple movement metrics and using easily interpretable decision trees. This allows for the combined study of animal behaviour and habitat use based on location data, and might make it possible to detect deviations in behaviour at the individual level.

A factor analysis of landscape pattern and structure metrics

Treesearch

Kurt H. Riitters; R.V. O' Neill; C.T. Hunsaker; James D. Wickham; D.H. Yankee; S.P. Timmins; K.B. Jones; B.L. Jackson

1995-01-01

Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These...

Individual tree detection in intact forest and degraded forest areas in the north region of Mato Grosso State, Brazilian Amazon

NASA Astrophysics Data System (ADS)

Santos, E. G.; Jorge, A.; Shimabukuro, Y. E.; Gasparini, K.

2017-12-01

The State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.

A GIS Approach to Prioritizing Habitat for Restoration Using Neotropical Migrant Songbird Criteria

NASA Astrophysics Data System (ADS)

Holzmueller, Eric J.; Gaskins, Michael D.; Mangun, Jean C.

2011-07-01

Restoration efforts to increase wildlife habitat quality in agricultural landscapes have limited funding and are typically done on a first come, first serve basis. In order to increase the efficiency of these restoration efforts, a prioritized ranking system is needed to obtain the greatest increase in habitat quality possible for the fewest amount of hectares restored. This project examines the use of a GIS based multi-criteria approach to prioritize lands for reforestation along the Kaskaskia River in Illinois. Loss of forested area and corresponding increase in forest fragmentation has decreased songbird habitat quality across the Midwestern United States. We prioritized areas for reforestation based on nine landscape metrics: available agricultural land, forest cover gaps, edge density, proximity to river, 200 m corridor area, total forest core area, fringe core area, distance to primary core value, and primary core area. The multi-criteria analysis revealed that high priority areas for reforestation were most likely to be close to the riparian corridor and existing large blocks of forest. Analysis of simulated reforestation (0, 0.5, 1.0, 5.0 10.0, 25.0, and 50.0% of highest priority parcels reforested) revealed different responses for multiple landscape metrics used to quantify forest fragmentation following reforestation, but indicated that the study area would get the greatest rate of return on reforestation efforts by reforesting 10.0% of the highest priority areas. This project demonstrates how GIS and a multi-criteria analysis approach can be used to increase the efficiency of restoration projects. This approach should be considered by land managers when attempting to identify the location and quantity of area for restoration within a landscape.

A GIS approach to prioritizing habitat for restoration using neotropical migrant songbird criteria.

PubMed

Holzmueller, Eric J; Gaskins, Michael D; Mangun, Jean C

2011-07-01

Restoration efforts to increase wildlife habitat quality in agricultural landscapes have limited funding and are typically done on a first come, first serve basis. In order to increase the efficiency of these restoration efforts, a prioritized ranking system is needed to obtain the greatest increase in habitat quality possible for the fewest amount of hectares restored. This project examines the use of a GIS based multi-criteria approach to prioritize lands for reforestation along the Kaskaskia River in Illinois. Loss of forested area and corresponding increase in forest fragmentation has decreased songbird habitat quality across the Midwestern United States. We prioritized areas for reforestation based on nine landscape metrics: available agricultural land, forest cover gaps, edge density, proximity to river, 200 m corridor area, total forest core area, fringe core area, distance to primary core value, and primary core area. The multi-criteria analysis revealed that high priority areas for reforestation were most likely to be close to the riparian corridor and existing large blocks of forest. Analysis of simulated reforestation (0, 0.5, 1.0, 5.0 10.0, 25.0, and 50.0% of highest priority parcels reforested) revealed different responses for multiple landscape metrics used to quantify forest fragmentation following reforestation, but indicated that the study area would get the greatest rate of return on reforestation efforts by reforesting 10.0% of the highest priority areas. This project demonstrates how GIS and a multi-criteria analysis approach can be used to increase the efficiency of restoration projects. This approach should be considered by land managers when attempting to identify the location and quantity of area for restoration within a landscape.

Ordination of breeding birds in relation to environmental gradients in three southeastern United States floodplain forests

USGS Publications Warehouse

Wakeley, J.S.; Guilfoyle, M.P.; Antrobus, T.J.; Fischer, R.A.; Barrow, W.C.; Hamel, P.B.

2007-01-01

We used an ordination approach to identify factors important to the organization of breeding bird communities in three floodplains: Cache River, Arkansas (AR), Iatt Creek, Louisiana (LA), and the Coosawhatchie River, South Carolina (SC), USA. We used 5-min point counts to sample birds in each study area each spring from 1995 to 1998, and measured ground-surface elevations and a suite of other habitat variables to investigate bird distributions and community characteristics in relation to important environmental gradients. In both AR and SC, the average number of Neotropical migrant species detected was lowest in semipermanently flooded Nyssa aquatica Linnaeus habitats and greatest in the highest elevation floodplain zone. Melanerpes carolinus Linnaeus, Protonotaria citrea Boddaert, Quiscalus quiscula Linnaeus, and other species were more abundant in N. aquatica habitats, whereas Wilsonia citrina Boddaert, Oporornis formosus Wilson, Vireo griseus Boddaert, and others were more abundant in drier floodplain zones. In LA, there were no significant differences in community metrics or bird species abundances among forest types. Canonical correspondence analyses revealed that structural development of understory vegetation was the most important factor affecting bird distributions in all three study areas; however, potential causes of these structural gradients differed. In AR and SC, differences in habitat structure were related to the hydrologic gradient, as indexed by ground-surface elevation. In LA, structural variations were related mainly to the frequency of canopy gaps. Thus, bird communities in all three areas appeared to be organized primarily in response to repeated localized disturbance. Our results suggest that regular disturbance due to flooding plays an important role in structuring breeding bird communities in floodplains subject to prolonged inundation, whereas other agents of disturbance (e.g., canopy gaps) may be more important in headwater systems subject to only short-duration flooding. Management for avian community integrity in these systems should strive to maintain forest zonation and natural disturbance regimes. ?? 2007 Springer Science+Business Media B.V.

Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements

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

Meng, Ran; Dennison, Philip E.; Zhao, Feng

Defoliation by herbivorous insects is a widespread forest disturbance driver, affecting global forest health and ecosystem dynamics. Additionally, compared with time- and labor-intensive field surveys, remote sensing provides the only realistic approach to mapping canopy defoliation by herbivorous insects over large spatial and temporal scales. However, the spectral and structural signatures of defoliation by insects at the individual tree level have not been well studied. Additionally, the predictive power of spectral and structural metrics for mapping canopy defoliation has seldom been compared. These critical knowledge gaps prevent us from consistently detecting and mapping canopy defoliation by herbivorous insects across multiplemore » scales. During the peak of a gypsy moth outbreak in Long Island, New York in summer 2016, we leveraged bi-temporal airborne imaging spectroscopy (IS, i.e., hyperspectral imaging) and LiDAR measurements at 1m spatial resolution to explore the spectral and structural signatures of canopy defoliation in a mixed oak-pine forest. We determined that red edge and near-infrared spectral regions within the IS data were most sensitive to crown-scale defoliation severity. LiDAR measurements including B70 (i.e., 70th bincentile height), intensity skewness, and kurtosis were effectively able to detect structural changes caused by herbivorous insects. In addition to canopy leaf loss, increased exposure of understory and non-photosynthetic materials contributed to the detected spectral and structural signatures. Comparing the ability of individual sensors to map canopy defoliation, the LiDAR-only Ordinary Least-Square (OLS) model performed better than the IS-only model (Adj. R-squared = 0.77, RMSE = 15.37% vs. Adj. R- squared = 0.63, RMSE = 19.11%). The IS+LiDAR model improved on performance of the individual sensors (Adj. R-squared = 0.81, RMSE = 14.46%). Our study improves our understanding of spectral and structural signatures of defoliation by herbivorous insects and presents a novel approach for mapping insect defoliation at the individual tree level. Furthermore, with the current and next generation of spaceborne sensors (e.g., WorldView-3, Landsat, Sentinel-2, HyspIRI, and GEDI), higher accuracy and frequent monitoring of insect defoliation may become more feasible across a range of spatial scales, which are critical for ecological research and management of forest resources including the economic consequences of forest insect infestations (e.g., reduced growth and increased mortality), as well as for informing and testing of carbon cycle models.« less

Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements

DOE PAGES

Meng, Ran; Dennison, Philip E.; Zhao, Feng; ...

2018-06-19

Defoliation by herbivorous insects is a widespread forest disturbance driver, affecting global forest health and ecosystem dynamics. Additionally, compared with time- and labor-intensive field surveys, remote sensing provides the only realistic approach to mapping canopy defoliation by herbivorous insects over large spatial and temporal scales. However, the spectral and structural signatures of defoliation by insects at the individual tree level have not been well studied. Additionally, the predictive power of spectral and structural metrics for mapping canopy defoliation has seldom been compared. These critical knowledge gaps prevent us from consistently detecting and mapping canopy defoliation by herbivorous insects across multiplemore » scales. During the peak of a gypsy moth outbreak in Long Island, New York in summer 2016, we leveraged bi-temporal airborne imaging spectroscopy (IS, i.e., hyperspectral imaging) and LiDAR measurements at 1m spatial resolution to explore the spectral and structural signatures of canopy defoliation in a mixed oak-pine forest. We determined that red edge and near-infrared spectral regions within the IS data were most sensitive to crown-scale defoliation severity. LiDAR measurements including B70 (i.e., 70th bincentile height), intensity skewness, and kurtosis were effectively able to detect structural changes caused by herbivorous insects. In addition to canopy leaf loss, increased exposure of understory and non-photosynthetic materials contributed to the detected spectral and structural signatures. Comparing the ability of individual sensors to map canopy defoliation, the LiDAR-only Ordinary Least-Square (OLS) model performed better than the IS-only model (Adj. R-squared = 0.77, RMSE = 15.37% vs. Adj. R- squared = 0.63, RMSE = 19.11%). The IS+LiDAR model improved on performance of the individual sensors (Adj. R-squared = 0.81, RMSE = 14.46%). Our study improves our understanding of spectral and structural signatures of defoliation by herbivorous insects and presents a novel approach for mapping insect defoliation at the individual tree level. Furthermore, with the current and next generation of spaceborne sensors (e.g., WorldView-3, Landsat, Sentinel-2, HyspIRI, and GEDI), higher accuracy and frequent monitoring of insect defoliation may become more feasible across a range of spatial scales, which are critical for ecological research and management of forest resources including the economic consequences of forest insect infestations (e.g., reduced growth and increased mortality), as well as for informing and testing of carbon cycle models.« less

Estimating the relationship between urban 3D morphology and land surface temperature using airborne LiDAR and Landsat-8 Thermal Infrared Sensor data

NASA Astrophysics Data System (ADS)

Lee, J. H.

2015-12-01

Urban forests are known for mitigating the urban heat island effect and heat-related health issues by reducing air and surface temperature. Beyond the amount of the canopy area, however, little is known what kind of spatial patterns and structures of urban forests best contributes to reducing temperatures and mitigating the urban heat effects. Previous studies attempted to find the relationship between the land surface temperature and various indicators of vegetation abundance using remote sensed data but the majority of those studies relied on two dimensional area based metrics, such as tree canopy cover, impervious surface area, and Normalized Differential Vegetation Index, etc. This study investigates the relationship between the three-dimensional spatial structure of urban forests and urban surface temperature focusing on vertical variance. We use a Landsat-8 Thermal Infrared Sensor image (acquired on July 24, 2014) to estimate the land surface temperature of the City of Sacramento, CA. We extract the height and volume of urban features (both vegetation and non-vegetation) using airborne LiDAR (Light Detection and Ranging) and high spatial resolution aerial imagery. Using regression analysis, we apply empirical approach to find the relationship between the land surface temperature and different sets of variables, which describe spatial patterns and structures of various urban features including trees. Our analysis demonstrates that incorporating vertical variance parameters improve the accuracy of the model. The results of the study suggest urban tree planting is an effective and viable solution to mitigate urban heat by increasing the variance of urban surface as well as evaporative cooling effect.

Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

NASA Astrophysics Data System (ADS)

Rodriguez-Galiano, Victor; Aragones, David; Caparros-Santiago, Jose A.; Navarro-Cerrillo, Rafael M.

2017-10-01

Land surface phenology (LSP) can improve the characterisation of forest areas and their change processes. The aim of this work was: i) to characterise the temporal dynamics in Mediterranean Pinus forests, and ii) to evaluate the potential of LSP for species discrimination. The different experiments were based on 679 mono-specific plots for the 5 native species on the Iberian Peninsula: P. sylvestris, P. pinea, P. halepensis, P. nigra and P. pinaster. The entire MODIS NDVI time series (2000-2016) of the MOD13Q1 product was used to characterise phenology. The following phenological parameters were extracted: the start, end and median days of the season, and the length of the season in days, as well as the base value, maximum value, amplitude and integrated value. Multi-temporal metrics were calculated to synthesise the inter-annual variability of the phenological parameters. The species were discriminated by the application of Random Forest (RF) classifiers from different subsets of variables: model 1) NDVI-smoothed time series, model 2) multi-temporal metrics of the phenological parameters, and model 3) multi-temporal metrics and the auxiliary physical variables (altitude, slope, aspect and distance to the coastline). Model 3 was the best, with an overall accuracy of 82%, a kappa coefficient of 0.77 and whose most important variables were: elevation, coast distance, and the end and start days of the growing season. The species that presented the largest errors was P. nigra, (kappa= 0.45), having locations with a similar behaviour to P. sylvestris or P. pinaster.

Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data.

PubMed

González-Ferreiro, Eduardo; Arellano-Pérez, Stéfano; Castedo-Dorado, Fernando; Hevia, Andrea; Vega, José Antonio; Vega-Nieva, Daniel; Álvarez-González, Juan Gabriel; Ruiz-González, Ana Daría

2017-01-01

The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.

Riparian influences on stream fish assemblage structure in urbanizing streams

USGS Publications Warehouse

Roy, A.H.; Freeman, B.J.; Freeman, Mary C.

2007-01-01

We assessed the influence of land cover at multiple spatial extents on fish assemblage integrity, and the degree to which riparian forests can mitigate the negative effects of catchment urbanization on stream fish assemblages. Riparian cover (urban, forest, and agriculture) was determined within 30 m buffers at longitudinal distances of 200 m, 1 km, and the entire network upstream of 59 non-nested fish sampling locations. Catchment and riparian land cover within the upstream network were highly correlated, so we were unable to distinguish between those variables. Most fish assemblage variables were related to % forest and % urban land cover, with the strongest relations at the largest spatial extent of land cover (catchment), followed by riparian land cover in the 1-km and 200-m reach, respectively. For fish variables related to urban land cover in the catchment, we asked whether the influence of riparian land cover on fish assemblages was dependent on the amount of urban development in the catchment. Several fish assemblage metrics (endemic richness, endemic:cosmopolitan abundance, insectivorous cyprinid richness and abundance, and fluvial specialist richness) were all best predicted by single variable models with % urban land cover. However, endemic:cosmopolitan richness, cosmopolitan abundance, and lentic tolerant abundance were related to % forest cover in the 1-km stream reach, but only in streams that had <15% catchment urban land cover. In these cases, catchment urbanization overwhelmed the potential mitigating effects of riparian forests on stream fishes. Together, these results suggest that catchment land cover is an important driver of fish assemblages in urbanizing catchments, and riparian forests are important but not sufficient for protecting stream ecosystems from the impacts of high levels of urbanization.

Faecal corticosterone metabolite concentrations are not a good predictor of habitat suitability for common gartersnakes.

PubMed

Halliday, William D; Gilmour, Kathleen M; Blouin-Demers, Gabriel

2015-01-01

Measuring habitat suitability is important in conservation and in wildlife management. Measuring the abundance or presence-absence of a species in various habitats is not sufficient to measure habitat suitability because these metrics can be poor predictors of population success. Therefore, having some measure of population success is essential in assessing habitat suitability, but estimating population success is difficult. Identifying suitable proxies for population success could thus be beneficial. We examined whether faecal corticosterone metabolite (fCM) concentrations could be used as a proxy for habitat suitability in common gartersnakes (Thamnophis sirtalis). We conducted a validation study and confirmed that fCM concentrations indeed reflect circulating corticosterone concentrations. We estimated abundance, reproductive output and growth rate of gartersnakes in field and in forest habitat and we also measured fCM concentrations of gartersnakes from these same habitats. Common gartersnakes were more abundant and had higher reproductive outputs and higher growth rates in field habitat than in forest habitat, but fCM concentrations did not differ between the same two habitats. Our results suggest either that fCM concentrations are not a useful metric of habitat suitability in common gartersnakes or that the difference in suitability between the two habitats was too small to induce changes in fCM concentrations. Incorporating fitness metrics in estimates of habitat suitability is important, but these metrics of fitness have to be sensitive enough to vary between habitats.

Exploring links between greenspace and sudden unexpected death: A spatial analysis.

PubMed

Wu, Jianyong; Rappazzo, Kristen M; Simpson, Ross J; Joodi, Golsa; Pursell, Irion W; Mounsey, J Paul; Cascio, Wayne E; Jackson, Laura E

2018-04-01

Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning sudden unexpected death (SUD), commonly referred to as sudden cardiac death, which constitutes a large proportion of mortality in the United States. Because greenspace can promote physical activity, reduce stress and buffer air pollutants, it may have beneficial effects for people at risk of SUD, such as those with heart disease, hypertension, and diabetes mellitus. Using several spatial techniques, this study explored the relationship between SUD and greenspace. We adjudicated 396 SUD cases that occurred from March 2013 to February 2015 among reports from emergency medical services (EMS) that attended out-of-hospital deaths in Wake County (central North Carolina, USA). We measured multiple greenspace metrics in each census tract, including the percentages of forest, grassland, average tree canopy, tree canopy diversity, near-road tree canopy and greenway density. The associations between SUD incidence and these greenspace metrics were examined using Poisson regression (non-spatial) and Bayesian spatial models. The results from both models indicated that SUD incidence was inversely associated with both greenway density (adjusted risk ratio [RR] = 0.82, 95% credible/ confidence interval [CI]: 0.69-0.97) and the percentage of forest (adjusted RR = 0.90, 95% CI: 0.81-0.99). These results suggest that increases in greenway density by 1 km/km 2 and in forest by 10% were associated with a decrease in SUD risk of 18% and 10%, respectively. The inverse relationship was not observed between SUD incidence and other metrics, including grassland, average tree canopy, near-road tree canopy and tree canopy diversity. This study implies that greenspace, specifically greenways and forest, may have beneficial effects for people at risk of SUD. Further studies are needed to investigate potential causal relationships between greenspace and SUD, and potential mechanisms such as promoting physical activity and reducing stress. Copyright © 2018 Elsevier Ltd. All rights reserved.

Novel Methods for Measuring LiDAR

NASA Astrophysics Data System (ADS)

Ayrey, E.; Hayes, D. J.; Fraver, S.; Weiskittel, A.; Cook, B.; Kershaw, J.

2017-12-01

The estimation of forest biometrics from airborne LiDAR data has become invaluable for quantifying forest carbon stocks, forest and wildlife ecology research, and sustainable forest management. The area-based approach is arguably the most common method for developing enhanced forest inventories from LiDAR. It involves taking a series of vertical height measurements of the point cloud, then using those measurements with field measured data to develop predictive models. Unfortunately, there is considerable variation in methodology for collecting point cloud data, which can vary in pulse density, seasonality, canopy penetrability, and instrument specifications. Today there exists a wealth of public LiDAR data, however the variation in acquisition parameters makes forest inventory prediction by traditional means unreliable across the different datasets. The goal of this project is to test a series of novel point cloud measurements developed along a conceptual spectrum of human interpretability, and then to use the best measurements to develop regional enhanced forest inventories on Northern New England's and Atlantic Canada's public LiDAR. Similarly to a field-based inventory, individual tree crowns are being segmented, and summary statistics are being used as covariates. Established competition and structural indices are being generated using each tree's relationship to one another, whilst existing allometric equations are being used to estimate diameter and biomass of each tree measured in the LiDAR. Novel metrics measuring light interception, clusteredness, and rugosity are also being measured as predictors. On the other end of the human interpretability spectrum, convolutional neural networks are being employed to directly measure both the canopy height model, and the point clouds by scanning each using two and three dimensional kernals trained to identify features useful for predicting biological attributes such as biomass. Predictive models will be trained and tested against one another using 28 different sites and over 42 different LiDAR acquisitions. The optimal model will then be used to generate regional wall-to-wall forest inventories at a 10 m resolution.

Cloud-based Computing and Applications of New Snow Metrics for Societal Benefit

NASA Astrophysics Data System (ADS)

Nolin, A. W.; Sproles, E. A.; Crumley, R. L.; Wilson, A.; Mar, E.; van de Kerk, M.; Prugh, L.

2017-12-01

Seasonal and interannual variability in snow cover affects socio-environmental systems including water resources, forest ecology, freshwater and terrestrial habitat, and winter recreation. We have developed two new seasonal snow metrics: snow cover frequency (SCF) and snow disappearance date (SDD). These metrics are calculated at 500-m resolution using NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data (MOD10A1). SCF is the number of times snow is observed in a pixel over the user-defined observation period. SDD is the last date of observed snow in a water year. These pixel-level metrics are calculated rapidly and globally in the Google Earth Engine cloud-based environment. SCF and SDD can be interactively visualized in a map-based interface, allowing users to explore spatial and temporal snowcover patterns from 2000-present. These metrics are especially valuable in regions where snow data are sparse or non-existent. We have used these metrics in several ongoing projects. When SCF was linked with a simple hydrologic model in the La Laguna watershed in northern Chile, it successfully predicted summer low flows with a Nash-Sutcliffe value of 0.86. SCF has also been used to help explain changes in Dall sheep populations in Alaska where sheep populations are negatively impacted by late snow cover and low snowline elevation during the spring lambing season. In forest management, SCF and SDD appear to be valuable predictors of post-wildfire vegetation growth. We see a positive relationship between winter SCF and subsequent summer greening for several years post-fire. For western US winter recreation, we are exploring trends in SDD and SCF for regions where snow sports are economically important. In a world with declining snowpacks and increasing uncertainty, these metrics extend across elevations and fill data gaps to provide valuable information for decision-making. SCF and SDD are being produced so that anyone with Internet access and a Google account can access, visualize, and download the data with a minimum of technical expertise and no need for proprietary software.

Climatic controls of vegetation vigor in four contrasting forest types of India--evaluation from National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer datasets (1990-2000).

PubMed

Prasad, V Krishna; Anuradha, E; Badarinath, K V S

2005-09-01

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R2=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.

Changes in Mauna Kea Dry Forest Structure 2000-2014

USGS Publications Warehouse

Banko, Paul C.; Brinck, Kevin W.

2014-01-01

Changes in the structure of the subalpine vegetation of Palila Critical Habitat on the southwestern slope of Mauna Kea Volcano, Hawai‘i, were analyzed using 12 metrics of change in māmane (Sophora chrysophylla) and naio (Myoporum sandwicense) trees surveyed on plots in 2000 and 2014. These two dominant species were analyzed separately, and changes in their structure indicated changes in the forest’s health. There was a significant increase in māmane minimum crown height (indicating a higher ungulate “browse line”), canopy area, canopy volume, percentage of trees with ungulate damage, and percentage of dead trees. No significant changes were observed in māmane maximum crown height, proportion of plots with trees, sapling density, proportion of plots with saplings, or the height distribution of trees. The only significant positive change was for māmane tree density. Significantly negative changes were observed for naio minimum crown height, tree height, canopy area, canopy volume, and percentage of dead trees. No significant changes were observed in naio tree density, proportion of plots with trees, proportion of plots with saplings, or percentage of trees with ungulate damage. Significantly positive changes were observed in naio sapling density and the height distribution of trees. There was also a significant increase in the proportion of māmane vs. naio trees in the survey area. The survey methods did not allow us to distinguish among potential factors driving these changes for metrics other than the percentage of trees with ungulate damage. Continued ungulate browsing and prolonged drought are likely the factors contributing most to the observed changes in vegetation, but tree disease or insect infestation of māmane, or naio, and competition from alien grasses and other weeds could also be causing or exacerbating the impacts to the forest. Although māmane tree density has increased since 2000, this study also demonstrates that efforts by managers to remove sheep (Ovis spp.) from Palila Critical Habitat have not overcome the ability of sheep to continue to damage māmane trees and impede restoration of the vegetation.

Primary forests are irreplaceable for sustaining tropical biodiversity.

PubMed

Gibson, Luke; Lee, Tien Ming; Koh, Lian Pin; Brook, Barry W; Gardner, Toby A; Barlow, Jos; Peres, Carlos A; Bradshaw, Corey J A; Laurance, William F; Lovejoy, Thomas E; Sodhi, Navjot S

2011-09-14

Human-driven land-use changes increasingly threaten biodiversity, particularly in tropical forests where both species diversity and human pressures on natural environments are high. The rapid conversion of tropical forests for agriculture, timber production and other uses has generated vast, human-dominated landscapes with potentially dire consequences for tropical biodiversity. Today, few truly undisturbed tropical forests exist, whereas those degraded by repeated logging and fires, as well as secondary and plantation forests, are rapidly expanding. Here we provide a global assessment of the impact of disturbance and land conversion on biodiversity in tropical forests using a meta-analysis of 138 studies. We analysed 2,220 pairwise comparisons of biodiversity values in primary forests (with little or no human disturbance) and disturbed forests. We found that biodiversity values were substantially lower in degraded forests, but that this varied considerably by geographic region, taxonomic group, ecological metric and disturbance type. Even after partly accounting for confounding colonization and succession effects due to the composition of surrounding habitats, isolation and time since disturbance, we find that most forms of forest degradation have an overwhelmingly detrimental effect on tropical biodiversity. Our results clearly indicate that when it comes to maintaining tropical biodiversity, there is no substitute for primary forests.

Cumulative Industrial Activity Alters Lotic Fish Assemblages in Two Boreal Forest Watersheds of Alberta, Canada

NASA Astrophysics Data System (ADS)

Scrimgeour, Garry J.; Hvenegaard, Paul J.; Tchir, John

2008-12-01

We evaluated the cumulative effects of land use disturbance resulting from forest harvesting, and exploration and extraction of oil and gas resources on the occurrence and structure of stream fish assemblages in the Kakwa and Simonette watersheds in Alberta, Canada. Logistic regression models showed that the occurrence of numerically dominant species in both watersheds was related to two metrics defining industrial activity (i.e., percent disturbance and road density), in addition to stream wetted width, elevation, reach slope, and percent fines. Occurrences of bull trout, slimy sculpin, and white sucker were negatively related to percent disturbance and that of Arctic grayling, and mountain whitefish were positively related to percent disturbance and road density. Assessments of individual sites showed that 76% of the 74 and 46 test sites in the Kakwa and Simonette watersheds were possibly impaired or impaired. Impaired sites in the Kakwa Watershed supported lower densities of bull trout, mountain whitefish, and rainbow trout, but higher densities of Arctic grayling compared to appropriate reference sites. Impaired sites in the Simonette Watershed supported lower densities of bull trout, but higher densities of lake chub compared to reference sites. Our data suggest that current levels of land use disturbance alters the occurrence and structure of stream fish assemblages.

Global Forest Canopy Height Maps Validation and Calibration for The Potential of Forest Biomass Estimation in The Southern United States

NASA Astrophysics Data System (ADS)

Ku, N. W.; Popescu, S. C.

2015-12-01

In the past few years, three global forest canopy height maps have been released. Lefsky (2010) first utilized the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate a global forest canopy height map in 2010. Simard et al. (2011) integrated GLAS data and other ancillary variables, such as MODIS, Shuttle Radar Topography Mission (STRM), and climatic data, to generate another global forest canopy height map in 2011. Los et al. (2012) also used GLAS data to create a vegetation height map in 2012.Several studies attempted to compare these global height maps to other sources of data., Bolton et al. (2013) concluded that Simard's forest canopy height map has strong agreement with airborne lidar derived heights. Los map is a coarse spatial resolution vegetation height map with a 0.5 decimal degrees horizontal resolution, around 50 km in the US, which is not feasible for the purpose of our research. Thus, Simard's global forest canopy height map is the primary map for this research study. The main objectives of this research were to validate and calibrate Simard's map with airborne lidar data and other ancillary variables in the southern United States. The airborne lidar data was collected between 2010 and 2012 from: (1) NASA LiDAR, Hyperspectral & Thermal Image (G-LiHT) program; (2) National Ecological Observatory Network's (NEON) prototype data sharing program; (3) NSF Open Topography Facility; and (4) the Department of Ecosystem Science and Management at Texas A&M University. The airborne lidar study areas also cover a wide variety of vegetation types across the southern US. The airborne lidar data is post-processed to generate lidar-derived metrics and assigned to four different classes of point cloud data. The four classes of point cloud data are the data with ground points, above 1 m, above 3 m, and above 5 m. The root mean square error (RMSE) and coefficient of determination (R2) are used for examining the discrepancies of the canopy heights between the airborne lidar-derived metrics and global forest canopy height map, and the regression and random forest approaches are used to calibrate the global forest canopy height map. In summary, the research shows a calibrated forest canopy height map of the southern US.

Dynamics of Vegetatin Indices in Tropical and Subtropical Savannas Defined by Ecoregions and Moderate Resolution Imaging Spectoradiometer (MODIS) Land Cover

NASA Technical Reports Server (NTRS)

Hill, Michael J.; Roman, Miguel O.; Schaaf, Crytal B.

2011-01-01

In this study, we explored the capacity of vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products to characterize global savannas in Australia, Africa and South America. The savannas were spatially defined and subdivided using the World Wildlife Fund (WWF) global ecoregions and MODIS land cover classes. Average annual profiles of Normalized Difference Vegetation Index, shortwave infrared ratio (SWIR32), White Sky Albedo (WSA) and the Structural Scattering Index (SSI) were created. Metrics derived from average annual profiles of vegetation indices were used to classify savanna ecoregions. The response spaces between vegetation indices were used to examine the potential to derive structural and fractional cover measures. The ecoregions showed distinct temporal profiles and formed groups with similar structural properties, including higher levels of woody vegetation, similar forest savanna mixtures and similar grassland predominance. The potential benefits from the use of combinations of indices to characterize savannas are discussed.

Quality Measurements in Radiology: A Systematic Review of the Literature and Survey of Radiology Benefit Management Groups.

PubMed

Narayan, Anand; Cinelli, Christina; Carrino, John A; Nagy, Paul; Coresh, Josef; Riese, Victoria G; Durand, Daniel J

2015-11-01

As the US health care system transitions toward value-based reimbursement, there is an increasing need for metrics to quantify health care quality. Within radiology, many quality metrics are in use, and still more have been proposed, but there have been limited attempts to systematically inventory these measures and classify them using a standard framework. The purpose of this study was to develop an exhaustive inventory of public and private sector imaging quality metrics classified according to the classic Donabedian framework (structure, process, and outcome). A systematic review was performed in which eligibility criteria included published articles (from 2000 onward) from multiple databases. Studies were double-read, with discrepancies resolved by consensus. For the radiology benefit management group (RBM) survey, the six known companies nationally were surveyed. Outcome measures were organized on the basis of standard categories (structure, process, and outcome) and reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search strategy yielded 1,816 citations; review yielded 110 reports (29 included for final analysis). Three of six RBMs (50%) responded to the survey; the websites of the other RBMs were searched for additional metrics. Seventy-five unique metrics were reported: 35 structure (46%), 20 outcome (27%), and 20 process (27%) metrics. For RBMs, 35 metrics were reported: 27 structure (77%), 4 process (11%), and 4 outcome (11%) metrics. The most commonly cited structure, process, and outcome metrics included ACR accreditation (37%), ACR Appropriateness Criteria (85%), and peer review (95%), respectively. Imaging quality metrics are more likely to be structural (46%) than process (27%) or outcome (27%) based (P < .05). As national value-based reimbursement programs increasingly emphasize outcome-based metrics, radiologists must keep pace by developing the data infrastructure required to collect outcome-based quality metrics. Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Deforestation trends of tropical dry forests in central Brazil

USGS Publications Warehouse

Bianchi, Carlos A.; Haig, Susan M.

2013-01-01

Tropical dry forests are the most threatened forest type in the world yet a paucity of research about them stymies development of appropriate conservation actions. The Paranã River Basin has the most significant dry forest formations in the Cerrado biome of central Brazil and is threatened by intense land conversion to pastures and agriculture. We examined changes in Paranã River Basin deforestation rates and fragmentation across three time intervals that covered 31 yr using Landsat imagery. Our results indicated a 66.3 percent decrease in forest extent between 1977 and 2008, with an annual rate of forest cover change of 3.5 percent. Landscape metrics further indicated severe forest loss and fragmentation, resulting in an increase in the number of fragments and reduction in patch sizes. Forest fragments in flatlands have virtually disappeared and the only significant forest remnants are mostly found over limestone outcrops in the eastern part of the basin. If current patterns persist, we project that these forests will likely disappear within 25 yr. These patterns may be reversed with creation of protected areas and involvement of local people to preserve small fragments that can be managed for restoration.

Avian nest success in midwestern forests fragmented by agriculture

USGS Publications Warehouse

Knutson, M.G.; Friberg, M.A.; Niemi, G.J.; Newton, W.E.

2004-01-01

Knutson et al. (2004) report the results of an avian nest success study conducted to investigate how forest-bird nest success varied by nest location and type as well as by landscape context from 1996 to 1998 in an agricultural region of southwestern Minnesota, and southwestern Wisconsin, and northeastern Iowa. The authors found an overall Mayfield adjusted nest success of 48%, 82% for cavity-nesting species, and 42% for cup-nesting species. Common species varied from 23% for American Redstart (Setophaga ruticilla) to 43% for the Eastern Wood-Pewee (Contopus virens). Nest success was lowest for open-cup nesters, species that reject Brown-headed Cowbird (Molothrus ater) eggs, species that next near forest edges, and Neotropical migrants. These tendencies were consistent across the years of the study. Assessments of nest success considering surrounding landscape metrics indicated that forest area may not be a strong indicator of nest success in landscapes where all the available forests are fragmented.

Parameterized centrality metric for network analysis

NASA Astrophysics Data System (ADS)

Ghosh, Rumi; Lerman, Kristina

2011-06-01

A variety of metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-centrality [P. Bonacich, Am. J. Sociol.0002-960210.1086/228631 92, 1170 (1987)], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this metric and use it to study network structure, for example, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method for community detection to use this metric as the measure of node connectivity. Normalized alpha-centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. Studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed metric to several benchmark networks and show that it leads to better insights into network structure than alternative metrics.

Phonological and Phonetic Evidence for Trochaic Metrical Structure in Standard Chinese

ERIC Educational Resources Information Center

Sui, Yanyan

2013-01-01

Native speakers of Standard Chinese have significant difficulty judging the prominence of words with tones in a consistent way. How then can metrical structure in the language be diagnosed? This study approaches the question by investigating how metrical structure interacts with other aspects of phonology, especially tone; what foot type is used…

Using spatial metrics and surveys for the assessment of trans-boundary deforestation in protected areas of the Maya Mountain Massif: Belize-Guatemala border.

PubMed

Chicas, S D; Omine, K; Ford, J B; Sugimura, K; Yoshida, K

2017-02-01

Understanding the trans-boundary deforestation history and patterns in protected areas along the Belize-Guatemala border is of regional and global importance. To assess deforestation history and patterns in our study area along a section of the Belize-Guatemala border, we incorporated multi-temporal deforestation rate analysis and spatial metrics with survey results. This multi-faceted approach provides spatial analysis with relevant insights from local stakeholders to better understand historic deforestation dynamics, spatial characteristics and human perspectives regarding the underlying causes thereof. During the study period 1991-2014, forest cover declined in Belize's protected areas: Vaca Forest Reserve 97.88%-87.62%, Chiquibul National Park 99.36%-92.12%, Caracol Archeological Reserve 99.47%-78.10% and Colombia River Forest Reserve 89.22%-78.38% respectively. A comparison of deforestation rates and spatial metrics indices indicated that between time periods 1991-1995 and 2012-2014 deforestation and fragmentation increased in protected areas. The major underlying causes, drivers, impacts, and barriers to bi-national collaboration and solutions of deforestation along the Belize-Guatemala border were identified by community leaders and stakeholders. The Mann-Whitney U test identified significant differences between leaders and stakeholders regarding the ranking of challenges faced by management organizations in the Maya Mountain Massif, except for the lack of assessment and quantification of deforestation (LD, SH: 18.67, 23.25, U = 148, p > 0.05). The survey results indicated that failure to integrate buffer communities, coordinate among managing organizations and establish strong bi-national collaboration has resulted in continued ecological and environmental degradation. The information provided by this research should aid managing organizations in their continued aim to implement effective deforestation mitigation strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data

PubMed Central

Castedo-Dorado, Fernando; Hevia, Andrea; Vega, José Antonio; Vega-Nieva, Daniel; Ruiz-González, Ana Daría

2017-01-01

The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard. PMID:28448524

Modeled streamflow metrics on small, ungaged stream reaches in the Upper Colorado River Basin

USGS Publications Warehouse

Reynolds, Lindsay V.; Shafroth, Patrick B.

2016-01-20

Modeling streamflow is an important approach for understanding landscape-scale drivers of flow and estimating flows where there are no streamgage records. In this study conducted by the U.S. Geological Survey in cooperation with Colorado State University, the objectives were to model streamflow metrics on small, ungaged streams in the Upper Colorado River Basin and identify streams that are potentially threatened with becoming intermittent under drier climate conditions. The Upper Colorado River Basin is a region that is critical for water resources and also projected to experience large future climate shifts toward a drying climate. A random forest modeling approach was used to model the relationship between streamflow metrics and environmental variables. Flow metrics were then projected to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream, represented as raster cells, in the basin. Last, the projected random forest models of minimum flow coefficient of variation and specific mean daily flow were used to highlight streams that had greater than 61.84 percent minimum flow coefficient of variation and less than 0.096 specific mean daily flow and suggested that these streams will be most threatened to shift to intermittent flow regimes under drier climate conditions. Map projection products can help scientists, land managers, and policymakers understand current hydrology in the Upper Colorado River Basin and make informed decisions regarding water resources. With knowledge of which streams are likely to undergo significant drying in the future, managers and scientists can plan for stream-dependent ecosystems and human water users.

Temporal variation in bat-fruit interactions: Foraging strategies influence network structure over time

NASA Astrophysics Data System (ADS)

Zapata-Mesa, Natalya; Montoya-Bustamante, Sebastián; Murillo-García, Oscar E.

2017-11-01

Mutualistic interactions, such as seed dispersal, are important for the maintenance of structure and stability of tropical communities. However, there is a lack of information about spatial and temporal variation in plant-animal interaction networks. Thus, our goal was to assess the effect of bat's foraging strategies on temporal variation in the structure and robustness of bat-fruit networks in both a dry and a rain tropical forest. We evaluated monthly variation in bat-fruit networks by using seven structure metrics: network size, average path length, nestedness, modularity, complementary specialization, normalized degree and betweenness centrality. Seed dispersal networks showed variations in size, species composition and modularity; did not present nested structures and their complementary specialization was high compared to other studies. Both networks presented short path lengths, and a constantly high robustness, despite their monthly variations. Sedentary bat species were recorded during all the study periods and occupied more central positions than nomadic species. We conclude that foraging strategies are important structuring factors that affect the dynamic of networks by determining the functional roles of frugivorous bats over time; thus sedentary bats are more important than nomadic species for the maintenance of the network structure, and their conservation is a must.

Structural texture similarity metrics for image analysis and retrieval.

PubMed

Zujovic, Jana; Pappas, Thrasyvoulos N; Neuhoff, David L

2013-07-01

We develop new metrics for texture similarity that accounts for human visual perception and the stochastic nature of textures. The metrics rely entirely on local image statistics and allow substantial point-by-point deviations between textures that according to human judgment are essentially identical. The proposed metrics extend the ideas of structural similarity and are guided by research in texture analysis-synthesis. They are implemented using a steerable filter decomposition and incorporate a concise set of subband statistics, computed globally or in sliding windows. We conduct systematic tests to investigate metric performance in the context of "known-item search," the retrieval of textures that are "identical" to the query texture. This eliminates the need for cumbersome subjective tests, thus enabling comparisons with human performance on a large database. Our experimental results indicate that the proposed metrics outperform peak signal-to-noise ratio (PSNR), structural similarity metric (SSIM) and its variations, as well as state-of-the-art texture classification metrics, using standard statistical measures.

Carbon Offset Forestry: Forecasting Ecosystem Effects (COFFEE) Project Implementation Plan

EPA Science Inventory

COFFEE will evaluate the environmental impacts of implementing various COF practices by using the amount of total ecosystem C (TEC) sequestered in forests as the integrative response metric. These evaluations will be done for current-climate and future-climate scenarios and will...

Determination of forest fuels characteristics in mortality-affected Pinus forests using integrated hyperspectral and ALS data

NASA Astrophysics Data System (ADS)

Romero Ramirez, Francisco J.; Navarro-Cerrillo, Rafael Mª.; Varo-Martínez, Mª. Ángeles; Quero, Jose Luis; Doerr, Stefan; Hernández-Clemente, Rocío

2018-06-01

Widespread tree mortality caused by forest decline in recent decades has raised concern among forest managers about how to assess forest fuels in these conditions. To investigate this question, we developed and tested an objective, consistent approach to the characterization of canopy fuel metrics - such as fuel load (FL), live fuel moisture content (LFMC), and live-dead ratio (LDR) - by integrating airborne laser scanning (ALS) and hyperspectral data to produce more-accurate estimates at the stand level. Regression models were developed for Pinus sylvestris and P. nigra stands representative of pine plantations in southern Spain, using field data acquired for different spatial fuel types and distributions as well as high resolution airborne hyperspectral data (AHS) and ALS datasets. Strong relationships were found between ALS and FL using a density of 2 points m-2 (R2 = 0.64) and between LFMC and Temperature/NDVI index at a spatial resolution of 5 m (R2 = 0.91). The red edge normalized index provided the highest separability (Jeffries-Matusita distance = 1.83) between types of LDR. The plot-aggregate ALS and AHS metrics performed better at spatial resolutions of 5 m and 2 points m-2 than at other scales. Cartography of the estimations of FL, LFMC, and LDR made using the empirical models from the ALS and AHS data showed a mean FL value of 65.87 Mg ha-1, an average LFMC content of 57.51%, and 30.75% of the surface classified as dead fuel (≥60% defoliation). The results suggest that our remote sensing approach could improve the estimation of canopy fuels characteristics at higher spatial resolutions as well as estimations of fuel cartography, to assist the planning and management of fuel reduction treatments.

Associations among arbuscular mycorrhizal fungi and seedlings are predicted to change with tree successional status.

PubMed

Bachelot, Benedicte; Uriarte, María; Muscarella, Robert; Forero-Montaña, Jimena; Thompson, Jill; McGuire, Krista; Zimmerman, Jess; Swenson, Nathan G; Clark, James S

2018-03-01

Arbuscular mycorrhizal (AM) fungi in the soil may influence tropical tree dynamics and forest succession. The mechanisms are poorly understood, because the functional characteristics and abundances of tree species and AM fungi are likely to be codependent. We used generalized joint attribute modeling to evaluate if AM fungi are associated with three forest community metrics for a sub-tropical montane forest in Puerto Rico. The metrics chosen to reflect changes during forest succession are the abundance of seedlings of different successional status, the amount of foliar damage on seedlings of different successional status, and community-weighted mean functional trait values (adult specific leaf area [SLA], adult wood density, and seed mass). We used high-throughput DNA sequencing to identify fungal operational taxonomic units (OTUs) in the soil. Model predictions showed that seedlings of mid- and late-successional species had less leaf damage when the 12 most common AM fungi were abundant compared to when these fungi were absent. We also found that seedlings of mid-successional species were predicted to be more abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. In contrast, early-successional tree seedlings were predicted to be less abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. Finally, we showed that, among the 12 most common AM fungi, different AM fungi were correlated with functional trait characteristics of early- or late-successional species. Together, these results suggest that early-successional species might not rely as much as mid- and late-successional species on AM fungi, and AM fungi might accelerate forest succession. © 2017 by the Ecological Society of America.

Hurricane Maria Puerto Rico Landsat Analysis

DOE Data Explorer

Feng, Yanlei; Chambers, Jeff [LBNL; Negron-Juarez, Robinson [LBNL; Patricola, Chris; Clinton, Nick; Uriarte, Maria; Hall, Jaz; Collins, William

2018-01-01

Hurricane Maria made landfall as a strong Category 4 storm in southeast Puerto Rico on September 20th, 2018. The powerful storm traversed the island in a northwesterly direction causing widespread destruction. This study focused on a rapid assessment of Hurricane Marias impact to Puerto Ricos forests. Calibrated and corrected Landsat 8 image composites for the entire island were generated using Google Earth Engine for a comparable pre-Maria and post-Maria time period that accounted for phenology. Spectral mixture analysis (SMA) using image-derived end members was carried out on both composites to calculate the change in the non-photosynthetic vegetation (Delta-NPV) spectral response, a metric that quantifies the increased fraction of exposed wood and surface litter associated with tree mortality and crown damage from the storm. Hurricane simulations were also conducted using the Weather Research and Forecasting (WRF) regional climate model to estimate wind speeds associated with forest disturbance. Dramatic changes in forest structure across the entire island were evident from pre- and post-Maria composited Landsat 8 images. A Delta-NPV map for only the forested pixels illustrated significant spatial variability in disturbance, with patterns that associated with factors such as slope, aspect and elevation. An initial order-of-magnitude impact estimate based on previous work indicated that Hurricane Maria may have caused mortality and severe damage to 23-31 million trees. Additional field work and image analyses are required to further detail the impact of Hurricane Maria to Puerto Rico forests. A minor update to this dataset was posted on April 20, 2018. The previous version is being retired. If you need access to the prior version of the data, email ngee-tropics-archive@lbl.gov.

Seasonality of photosynthesis of a Rocky Mountain subalpine forest: implications for SIF as a metric for GPP

NASA Astrophysics Data System (ADS)

Bowling, D. R.; Blanken, P.; Burns, S. P.; Frankenberg, C.; Grossman, K.; Lin, J. C.; Logan, B. A.; Magney, T. S.; Richardson, A. D.; Stutz, J.; Aubrecht, D.

2017-12-01

Temperate and boreal conifer forests are dormant for many months during the cold season, during which they continue to absorb solar radiation. Thus they exhibit a marked seasonal change in light-use efficiency, challenging our ability to monitor gross primary productivity (GPP) from remote sensing platforms. We are studying the factors limiting the seasonality of photosynthesis of a high-elevation subalpine forest in Colorado. Using in-situ thermal imagery, we find that foliage in winter is sometimes near the optimum temperature for photosynthesis, but photosynthesis is shut down for most of the cold season. Water transport is limited by blockage of sap transport by frozen boles, but not by frozen soils. Foliar carotenoid content exhibits strong upregulation during winter, driven largely by increase in the pool size of the photoprotective xanthophyll cycle, but with no seasonal change in chlorophyll content. The seasonality of GPP is strongly linked to xanthophyll cycle conversion state and thawing of boles. Ongoing research includes examination of leaf-level chlorophyll fluorescence emission and gas exchange, combined with measurement of canopy-level spectral reflectance and solar-induced fluorescence (SIF) at high spatio-temporal resolution using a custom tower-based PhotoSpec scanning spectrometer system. These results will be synthesized in the context of using SIF as a metric for GPP.

Impact of landscape disturbance on the quality of terrestrial sediment carbon in temperate streams

NASA Astrophysics Data System (ADS)

Fox, James F.; Ford, William I.

2016-09-01

Recent studies have shown the super saturation of fluvial networks with respect to carbon dioxide, and the concept that the high carbon dioxide is at least partially the result of turnover of sediment organic carbon that ranges in age from years to millennia. Currently, there is a need for more highly resolved studies at stream and river scales that enable estimates of terrestrial carbon turnover within fluvial networks. Our objective was to develop a new isotope-based metric to estimate the quality of sediment organic carbon delivered to temperate streams and to use the new metric to estimate carbon quality across landscape disturbance gradients. Carbon quality is defined to be consistent with in-stream turnover and our metric is used to measure the labile or recalcitrant nature of the terrestrial-derived carbon within streams. Our hypothesis was that intensively-disturbed landscapes would tend to produce low quality carbon because deep, recalcitrant soil carbon would be eroded and transported to the fluvial system while moderately disturbed or undisturbed landscapes would tend to produce higher quality carbon from well-developed surface soils and litter. The hypothesis was tested by applying the new carbon quality metric to 15 temperate streams with a wide range of landscape disturbance levels. We find that our hypothesis premised on an indirect relationship between the extent of landscape disturbance and the quality of sediment carbon in streams holds true for moderate and high disturbances but not for un-disturbed forests. We explain the results based on the connectivity, or dis-connectivity, between terrestrial carbon sources and pathways for sediment transport. While pathways are typically un-limited for disturbed landscapes, the un-disturbed forests have dis-connectivity between labile carbon of the forest floor and the stream corridor. Only in the case when trees fell into the stream corridor due to severe ice storms did the quality of sediment carbon increase in the streams. We argue that as scientists continue to estimate the in-stream turnover of terrestrially-derived carbon in fluvial carbon budgets, the assumption of pathway connectivity between carbon sources to the stream should be justified.

Assessing Transboundary Wildfire Exposure in the Southwestern United States.

PubMed

Ager, Alan A; Palaiologou, Palaiologos; R Evers, Cody; Day, Michelle A; G Barros, Ana M

2018-04-25

We assessed transboundary wildfire exposure among federal, state, and private lands and 447 communities in the state of Arizona, southwestern United States. The study quantified the relative magnitude of transboundary (incoming, outgoing) versus nontransboundary (i.e., self-burning) wildfire exposure based on land tenure or community of the simulated ignition and the resulting fire perimeter. We developed and described several new metrics to quantify and map transboundary exposure. We found that incoming transboundary fire accounted for 37% of the total area burned on large parcels of federal and state lands, whereas 63% of the area burned was burned by ignitions within the parcel. However, substantial parcel to parcel variation was observed for all land tenures for all metrics. We found that incoming transboundary fire accounted for 66% of the total area burned within communities versus 34% of the area burned by self-burning ignitions. Of the total area burned within communities, private lands contributed the largest proportion (36.7%), followed by national forests (19.5%), and state lands (15.4%). On average seven land tenures contributed wildfire to individual communities. Annual wildfire exposure to structures was highest for wildfires ignited on state and national forest land, followed by tribal, private, and BLM. We mapped community firesheds, that is, the area where ignitions can spawn fires that can burn into communities, and estimated that they covered 7.7 million ha, or 26% of the state of Arizona. Our methods address gaps in existing wildfire risk assessments, and their implementation can help reduce fragmentation in governance systems and inefficiencies in risk planning. Published 2018. This article is a U.S. government work and is in the public domain in the USA.

Variance and Rate-of-Change as Early Warning Signals for a Critical Transition in an Aquatic Ecosystem State: A Test Case From Tasmania, Australia

NASA Astrophysics Data System (ADS)

Beck, Kristen K.; Fletcher, Michael-Shawn; Gadd, Patricia S.; Heijnis, Henk; Saunders, Krystyna M.; Simpson, Gavin L.; Zawadzki, Atun

2018-02-01

Critical transitions in ecosystem states are often sudden and unpredictable. Consequently, there is a concerted effort to identify measurable early warning signals (EWS) for these important events. Aquatic ecosystems provide an opportunity to observe critical transitions due to their high sensitivity and rapid response times. Using palaeoecological techniques, we can measure properties of time series data to determine if critical transitions are preceded by any measurable ecosystem metrics, that is, identify EWS. Using a suite of palaeoenvironmental data spanning the last 2,400 years (diatoms, pollen, geochemistry, and charcoal influx), we assess whether a critical transition in diatom community structure was preceded by measurable EWS. Lake Vera, in the temperate rain forest of western Tasmania, Australia, has a diatom community dominated by Discostella stelligera and undergoes an abrupt compositional shift at ca. 820 cal yr BP that is concomitant with increased fire disturbance of the local vegetation. This shift is manifest as a transition from less oligotrophic acidic diatom flora (Achnanthidium minutissimum, Brachysira styriaca, and Fragilaria capucina) to more oligotrophic acidic taxa (Frustulia elongatissima, Eunotia diodon, and Gomphonema multiforme). We observe a marked increase in compositional variance and rate-of-change prior to this critical transition, revealing these metrics are useful EWS in this system. Interestingly, vegetation remains complacent to fire disturbance until after the shift in the diatom community. Disturbance taxa invade and the vegetation system experiences an increase in both compositional variance and rate-of-change. These trends imply an approaching critical transition in the vegetation and the probable collapse of the local rain forest system.

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.

PubMed

Lenselink, Eelke B; Ten Dijke, Niels; Bongers, Brandon; Papadatos, George; van Vlijmen, Herman W T; Kowalczyk, Wojtek; IJzerman, Adriaan P; van Westen, Gerard J P

2017-08-14

The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method ('DNN_PCM') performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized 'DNN_PCM'). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols. Graphical Abstract .

Sleep state classification using pressure sensor mats.

PubMed

Baran Pouyan, M; Nourani, M; Pompeo, M

2015-08-01

Sleep state detection is valuable in assessing patient's sleep quality and in-bed general behavior. In this paper, a novel classification approach of sleep states (sleep, pre-wake, wake) is proposed that uses only surface pressure sensors. In our method, a mobility metric is defined based on successive pressure body maps. Then, suitable statistical features are computed based on the mobility metric. Finally, a customized random forest classifier is employed to identify various classes including a new class for pre-wake state. Our algorithm achieves 96.1% and 88% accuracies for two (sleep, wake) and three (sleep, pre-wake, wake) class identification, respectively.

Assessment of various supervised learning algorithms using different performance metrics

NASA Astrophysics Data System (ADS)

Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

USGS Publications Warehouse

Hagar, Joan C.; Eskelson, Bianca N.I.; Haggerty, Patricia K.; Nelson, S. Kim; Vesely, David G.

2014-01-01

LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (Brachyramphus marmoratus) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

Improving Glaucoma Detection Using Spatially Correspondent Clusters of Damage and by Combining Standard Automated Perimetry and Optical Coherence Tomography

PubMed Central

Raza, Ali S.; Zhang, Xian; De Moraes, Carlos G. V.; Reisman, Charles A.; Liebmann, Jeffrey M.; Ritch, Robert; Hood, Donald C.

2014-01-01

Purpose. To improve the detection of glaucoma, techniques for assessing local patterns of damage and for combining structure and function were developed. Methods. Standard automated perimetry (SAP) and frequency-domain optical coherence tomography (fdOCT) data, consisting of macular retinal ganglion cell plus inner plexiform layer (mRGCPL) as well as macular and optic disc retinal nerve fiber layer (mRNFL and dRNFL) thicknesses, were collected from 52 eyes of 52 healthy controls and 156 eyes of 96 glaucoma suspects and patients. In addition to generating simple global metrics, SAP and fdOCT data were searched for contiguous clusters of abnormal points and converted to a continuous metric (pcc). The pcc metric, along with simpler methods, was used to combine the information from the SAP and fdOCT. The performance of different methods was assessed using the area under receiver operator characteristic curves (AROC scores). Results. The pcc metric performed better than simple global measures for both the fdOCT and SAP. The best combined structure-function metric (mRGCPL&SAP pcc, AROC = 0.868 ± 0.032) was better (statistically significant) than the best metrics for independent measures of structure and function. When SAP was used as part of the inclusion and exclusion criteria, AROC scores increased for all metrics, including the best combined structure-function metric (AROC = 0.975 ± 0.014). Conclusions. A combined structure-function metric improved the detection of glaucomatous eyes. Overall, the primary sources of value-added for glaucoma detection stem from the continuous cluster search (the pcc), the mRGCPL data, and the combination of structure and function. PMID:24408977

Instream wood recruitment, channel complexity, and their relationship to stream ecology in forested headwater streams under alternative stable states

NASA Astrophysics Data System (ADS)

Livers, B.; Wohl, E.

2015-12-01

Human alteration to forests has had lasting effects on stream channels worldwide. Such land use changes affect how wood enters and is stored in streams as individual pieces and as logjams. Changes in wood recruitment affect the complexity and benefits wood can provide to the stream environment, such as zones of flow separation that store fine sediment and organic matter, increased nutrient processing, and greater habitat potential, which can enhance biota and cascade through stream-riparian ecosystems. Previous research in our study area shows that modern headwater streams flowing through old-growth, unmanaged forests have more wood than streams in young, managed forests, but does not explicitly evaluate how wood affects channel complexity or local ecology. 'Managed' refers to forests previously or currently exposed to human alteration. Alteration has long since ceased in some areas, but reduced wood loads in managed streams persist. Our primary objective was to quantify stream complexity metrics, with instream wood as a mediator, on streams across a gradient of management and disturbance histories in order to examine legacy effects of human alteration to forests. Data collected in the Southern Rocky Mountains include 24 2nd to 3rd order subalpine streams categorized into: old-growth unmanaged; younger, naturally disturbed unmanaged; and younger managed. We assessed instream wood loads and logjams and evaluated how they relate to channel complexity using a number of metrics, such as standard deviation of bed and banks, volume of pools, ratios of stream to valley lengths and stream to valley area, and diversity of substrate, gradient, and morphology. Preliminary results show that channel complexity is directly related to instream wood loads and is greatest in streams in old-growth. Related research in the field area indicates that streams with greater wood loads also have increased nutrient processing and greater abundance and diversity of aquatic insect predators.

Measured and modeled evidence for a two-fold increase in water use efficiency at an old-growth forest site in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Jiang, Y.; Rastogi, B.; Kim, J. B.; Voelker, S.; Meinzer, F. C.; Still, C. J.

2017-12-01

Water use efficiency (WUE), the ratio of carbon uptake to transpiration, has been widely recognized as an important measure of carbon and water cycling in plants, and is used to track forest ecosystem responses to climate change and rising atmospheric CO2concentrations. In this study we used eddy covariance measurement data and Ecosystem Demography model (ED2) simulations to explore the patterns and physiological and biophysical controls of WUE at Wind River Experimental Forest, an old-growth coniferous forest in the Pacific Northwest. We characterized how observed and simulated WUE vary between wet and dry years, and explored the drivers of the differences in WUE between the wet and dry years. Through this explorative process, we evaluated the utility of various ways that WUE have been computed in literature. Measurement-based and simulated WUE at the old-growth forest increased over twofold from 1998 to 2015. The primary driver of this trend is a decreasing trend in evapotranspiration (ET). There were significant inter-annual variations. For example, during drought years, higher air temperature drove increases in early season ET, thereby depleting soil water and decreasing GPP. Lower GPP in turn resulted in lower WUE. This mechanism might drive changes in future carbon and water budgets under warming climate. Our evaluation of multiple WUE metrics demonstrates that each metric has a distinct sensitivity to climate anomalies, but also indicates a robust increasing trend of WUE. Statistical (multiple linear regression) and machine learning (Random Forest) analyses of flux measurements indicated that atmospheric CO2 concentration, air temperature and radiation were the most important predictors of WUE at monthly, daily and half-hourly time scale, respectively. In contrast, WUE mechanism was stable across all time scales in ED2 simulations: vapor pressure deficit was consistently the most important predictor of WUE at the monthly, daily and half-hourly time scales.

Environmental drivers of Ixodes ricinus abundance in forest fragments of rural European landscapes.

PubMed

Ehrmann, Steffen; Liira, Jaan; Gärtner, Stefanie; Hansen, Karin; Brunet, Jörg; Cousins, Sara A O; Deconchat, Marc; Decocq, Guillaume; De Frenne, Pieter; De Smedt, Pallieter; Diekmann, Martin; Gallet-Moron, Emilie; Kolb, Annette; Lenoir, Jonathan; Lindgren, Jessica; Naaf, Tobias; Paal, Taavi; Valdés, Alicia; Verheyen, Kris; Wulf, Monika; Scherer-Lorenzen, Michael

2017-09-06

The castor bean tick (Ixodes ricinus) transmits infectious diseases such as Lyme borreliosis, which constitutes an important ecosystem disservice. Despite many local studies, a comprehensive understanding of the key drivers of tick abundance at the continental scale is still lacking. We analyze a large set of environmental factors as potential drivers of I. ricinus abundance. Our multi-scale study was carried out in deciduous forest fragments dispersed within two contrasting rural landscapes of eight regions, along a macroclimatic gradient stretching from southern France to central Sweden and Estonia. We surveyed the abundance of I. ricinus, plant community composition, forest structure and soil properties and compiled data on landscape structure, macroclimate and habitat properties. We used linear mixed models to analyze patterns and derived the relative importance of the significant drivers. Many drivers had, on their own, either a moderate or small explanatory value for the abundance of I. ricinus, but combined they explained a substantial part of variation. This emphasizes the complex ecology of I. ricinus and the relevance of environmental factors for tick abundance. Macroclimate only explained a small fraction of variation, while properties of macro- and microhabitat, which buffer macroclimate, had a considerable impact on tick abundance. The amount of forest and the composition of the surrounding rural landscape were additionally important drivers of tick abundance. Functional (dispersules) and structural (density of tree and shrub layers) properties of the habitat patch played an important role. Various diversity metrics had only a small relative importance. Ontogenetic tick stages showed pronounced differences in their response. The abundance of nymphs and adults is explained by the preceding stage with a positive relationship, indicating a cumulative effect of drivers. Our findings suggest that the ecosystem disservices of tick-borne diseases, via the abundance of ticks, strongly depends on habitat properties and thus on how humans manage ecosystems from the scale of the microhabitat to the landscape. This study stresses the need to further evaluate the interaction between climate change and ecosystem management on I. ricinus abundance.

Unraveling the drivers of community dissimilarity and species extinction in fragmented landscapes.

PubMed

Banks-Leite, Cristina; Ewers, Robert M; Metzger, Jean Paul

2012-12-01

Communities in fragmented landscapes are often assumed to be structured by species extinction due to habitat loss, which has led to extensive use of the species-area relationship (SAR) in fragmentation studies. However, the use of the SAR presupposes that habitat loss leads species to extinction but does not allow for extinction to be offset by colonization of disturbed-habitat specialists. Moreover, the use of SAR assumes that species richness is a good proxy of community changes in fragmented landscapes. Here, we assessed how communities dwelling in fragmented landscapes are influenced by habitat loss at multiple scales; then we estimated the ability of models ruled by SAR and by species turnover in successfully predicting changes in community composition, and asked whether species richness is indeed an informative community metric. To address these issues, we used a data set consisting of 140 bird species sampled in 65 patches, from six landscapes with different proportions of forest cover in the Atlantic Forest of Brazil. We compared empirical patterns against simulations of over 8 million communities structured by different magnitudes of the power-law SAR and with species-specific rules to assign species to sites. Empirical results showed that, while bird community composition was strongly influenced by habitat loss at the patch and landscape scale, species richness remained largely unaffected. Modeling results revealed that the compositional changes observed in the Atlantic Forest bird metacommunity were only matched by models with either unrealistic magnitudes of the SAR or by models ruled by species turnover, akin to what would be observed along natural gradients. We show that, in the presence of such compositional turnover, species richness is poorly correlated with species extinction, and z values of the SAR strongly underestimate the effects of habitat loss. We suggest that the observed compositional changes are driven by each species reaching its individual extinction threshold: either a threshold of forest cover for species that disappear with habitat loss, or of matrix cover for species that benefit from habitat loss.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

PubMed

Johnson, Michelle O; Galbraith, David; Gloor, Manuel; De Deurwaerder, Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; von Randow, Celso; Monteagudo, Abel; Phillips, Oliver L; Brienen, Roel J W; Feldpausch, Ted R; Lopez Gonzalez, Gabriela; Fauset, Sophie; Quesada, Carlos A; Christoffersen, Bradley; Ciais, Philippe; Sampaio, Gilvan; Kruijt, Bart; Meir, Patrick; Moorcroft, Paul; Zhang, Ke; Alvarez-Davila, Esteban; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; Bonal, Damien; Boot, Rene; Camargo, Jose; Chave, Jerome; Cogollo, Alvaro; Cornejo Valverde, Fernando; Lola da Costa, Antonio C; Di Fiore, Anthony; Ferreira, Leandro; Higuchi, Niro; Honorio, Euridice N; Killeen, Tim J; Laurance, Susan G; Laurance, William F; Licona, Juan; Lovejoy, Thomas; Malhi, Yadvinder; Marimon, Bia; Marimon, Ben Hur; Matos, Darley C L; Mendoza, Casimiro; Neill, David A; Pardo, Guido; Peña-Claros, Marielos; Pitman, Nigel C A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Roopsind, Anand; Rudas, Agustin; Salomao, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van der Heijden, Geertje M F; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A; Baker, Timothy R

2016-12-01

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Characterizing fire-related spatial patterns in fire-prone ecosystems using optical and microwave remote sensing

NASA Astrophysics Data System (ADS)

Henry, Mary Catherine

The use of active and passive remote sensing systems for relating forest spatial patterns to fire history was tested over one of the Arizona Sky Islands. Using Landsat Thematic Mapper (TM), Shuttle Imaging Radar (SIR-C), and data fusion I examined the relationship between landscape metrics and a range of fire history characteristics. Each data type (TM, SIR-C, and fused) was processed in the following manner: each band, channel, or derived feature was simplified to a thematic layer and landscape statistics were calculated for plots with known fire history. These landscape metrics were then correlated with fire history characteristics, including number of fire-free years in a given time period, mean fire-free interval, and time since fire. Results from all three case studies showed significant relationships between fire history and forest spatial patterns. Data fusion performed as well or better than Landsat TM alone, and better than SIR-C alone. These comparisons were based on number and strength of significant correlations each method achieved. The landscape metric that was most consistent and obtained the greatest number of significant correlations was Shannon's Diversity Index. Results also agreed with field-based research that has linked higher fire frequency to increased landscape diversity and patchiness. An additional finding was that the fused data seem to detect fire-related spatial patterns over a range of scales.

A SPATIAL ANALYSIS OF FINE-ROOT BIOMASS FROM STAND DATA IN OREGON AND WASHINGTON

EPA Science Inventory

Because of the high spatial variability of fine roots in natural forest stands, accurate estimates of stand-level fine root biomass are difficult and expensive to obtain by standard coring methods. This study compares two different approaches that employ aboveground tree metrics...

A SPATIAL ANALYSIS OF THE FINE ROOT BIOMASS FROM STAND DATA IN THE PACIFIC NORTHWEST

EPA Science Inventory

High spatial variability of fine roots in natural forest stands makes accurate estimates of stand-level fine root biomass difficult and expensive to obtain by standard coring methods. This study uses aboveground tree metrics and spatial relationships to improve core-based estima...

RPA Data Wiz users guide, version 1.0

Treesearch

Scott A. Pugh

2004-01-01

RPA Data Wiz is a computer application use to create summary tables, graphs, and maps of Resource Planning Act (RPA) Assessment forest information (English or metric units). Volumes for growing stock, live cull, dead salvable, netgrowth, and mortality can be estimated. Acreage, biomass, and tree count estimates are also available.

Building structural similarity database for metric learning

NASA Astrophysics Data System (ADS)

Jin, Guoxin; Pappas, Thrasyvoulos N.

2015-03-01

We propose a new approach for constructing databases for training and testing similarity metrics for structurally lossless image compression. Our focus is on structural texture similarity (STSIM) metrics and the matched-texture compression (MTC) approach. We first discuss the metric requirements for structurally lossless compression, which differ from those of other applications such as image retrieval, classification, and understanding. We identify "interchangeability" as the key requirement for metric performance, and partition the domain of "identical" textures into three regions, of "highest," "high," and "good" similarity. We design two subjective tests for data collection, the first relies on ViSiProG to build a database of "identical" clusters, and the second builds a database of image pairs with the "highest," "high," "good," and "bad" similarity labels. The data for the subjective tests is generated during the MTC encoding process, and consist of pairs of candidate and target image blocks. The context of the surrounding image is critical for training the metrics to detect lighting discontinuities, spatial misalignments, and other border artifacts that have a noticeable effect on perceptual quality. The identical texture clusters are then used for training and testing two STSIM metrics. The labelled image pair database will be used in future research.

Getting the message across: using ecological integrity to communicate with resource managers

USGS Publications Warehouse

Mitchell, Brian R.; Tierney, Geraldine L.; Schweiger, E. William; Miller, Kathryn M.; Faber-Langendoen, Don; Grace, James B.

2014-01-01

This chapter describes and illustrates how concepts of ecological integrity, thresholds, and reference conditions can be integrated into a research and monitoring framework for natural resource management. Ecological integrity has been defined as a measure of the composition, structure, and function of an ecosystem in relation to the system’s natural or historical range of variation, as well as perturbations caused by natural or anthropogenic agents of change. Using ecological integrity to communicate with managers requires five steps, often implemented iteratively: (1) document the scale of the project and the current conceptual understanding and reference conditions of the ecosystem, (2) select appropriate metrics representing integrity, (3) define externally verified assessment points (metric values that signify an ecological change or need for management action) for the metrics, (4) collect data and calculate metric scores, and (5) summarize the status of the ecosystem using a variety of reporting methods. While we present the steps linearly for conceptual clarity, actual implementation of this approach may require addressing the steps in a different order or revisiting steps (such as metric selection) multiple times as data are collected. Knowledge of relevant ecological thresholds is important when metrics are selected, because thresholds identify where small changes in an environmental driver produce large responses in the ecosystem. Metrics with thresholds at or just beyond the limits of a system’s range of natural variability can be excellent, since moving beyond the normal range produces a marked change in their values. Alternatively, metrics with thresholds within but near the edge of the range of natural variability can serve as harbingers of potential change. Identifying thresholds also contributes to decisions about selection of assessment points. In particular, if there is a significant resistance to perturbation in an ecosystem, with threshold behavior not occurring until well beyond the historical range of variation, this may provide a scientific basis for shifting an ecological assessment point beyond the historical range. We present two case studies using ongoing monitoring by the US National Park Service Vital Signs program that illustrate the use of an ecological integrity approach to communicate ecosystem status to resource managers. The Wetland Ecological Integrity in Rocky Mountain National Park case study uses an analytical approach that specifically incorporates threshold detection into the process of establishing assessment points. The Forest Ecological Integrity of Northeastern National Parks case study describes a method for reporting ecological integrity to resource managers and other decision makers. We believe our approach has the potential for wide applicability for natural resource management.

Multiple metrics of diversity have different effects on temperate forest functioning over succession.

PubMed

Yuan, Zuoqiang; Wang, Shaopeng; Gazol, Antonio; Mellard, Jarad; Lin, Fei; Ye, Ji; Hao, Zhanqing; Wang, Xugao; Loreau, Michel

2016-12-01

Biodiversity can be measured by taxonomic, phylogenetic, and functional diversity. How ecosystem functioning depends on these measures of diversity can vary from site to site and depends on successional stage. Here, we measured taxonomic, phylogenetic, and functional diversity, and examined their relationship with biomass in two successional stages of the broad-leaved Korean pine forest in northeastern China. Functional diversity was calculated from six plant traits, and aboveground biomass (AGB) and coarse woody productivity (CWP) were estimated using data from three forest censuses (10 years) in two large fully mapped forest plots (25 and 5 ha). 11 of the 12 regressions between biomass variables (AGB and CWP) and indices of diversity showed significant positive relationships, especially those with phylogenetic diversity. The mean tree diversity-biomass regressions increased from 0.11 in secondary forest to 0.31 in old-growth forest, implying a stronger biodiversity effect in more mature forest. Multi-model selection results showed that models including species richness, phylogenetic diversity, and single functional traits explained more variation in forest biomass than other candidate models. The models with a single functional trait, i.e., leaf area in secondary forest and wood density in mature forest, provided better explanations for forest biomass than models that combined all six functional traits. This finding may reflect different strategies in growth and resource acquisition in secondary and old-growth forests.

A deformation of Sasakian structure in the presence of torsion and supergravity solutions

NASA Astrophysics Data System (ADS)

Houri, Tsuyoshi; Takeuchi, Hiroshi; Yasui, Yukinori

2013-07-01

A deformation of Sasakian structure in the presence of totally skew-symmetric torsion is discussed on odd-dimensional manifolds whose metric cones are Kähler with torsion. It is shown that such a geometry inherits similar properties to those of Sasakian geometry. As their example, we present an explicit expression of local metrics. It is also demonstrated that our example of the metrics admits the existence of hidden symmetry described by non-trivial odd-rank generalized closed conformal Killing-Yano tensors. Furthermore, using these metrics as an ansatz, we construct exact solutions in five-dimensional minimal gauged/ungauged supergravity and 11-dimensional supergravity. Finally, the global structures of the solutions are discussed. We obtain regular metrics on compact manifolds in five dimensions, which give natural generalizations of Sasaki-Einstein manifolds Yp, q and La, b, c. We also briefly discuss regular metrics on non-compact manifolds in 11 dimensions.

Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

USGS Publications Warehouse

Wedding, L.M.; Christopher, L.A.; Pittman, S.J.; Friedlander, A.M.; Jorgensen, S.

2011-01-01

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change. ?? Inter-Research 2011.

Long term repeated fire disturbance alters soil bacterial diversity but not the abundance in an Australian wet sclerophyll forest.

PubMed

Shen, Ju-pei; Chen, C R; Lewis, Tom

2016-01-20

Effects of fire on biogeochemical cycling in terrestrial ecosystem are widely acknowledged, while few studies have focused on the bacterial community under the disturbance of long-term frequent prescribed fire. In this study, three treatments (burning every two years (B2), burning every four years (B4) and no burning (B0)) were applied for 38 years in an Australian wet sclerophyll forest. Results showed that bacterial alpha diversity (i.e. bacterial OTU) in the top soil (0-10 cm) was significantly higher in the B2 treatment compared with the B0 and B4 treatments. Non-metric multidimensional analysis (NMDS) of bacterial community showed clear separation of the soil bacterial community structure among different fire frequency regimes and between the depths. Different frequency fire did not have a substantial effect on bacterial composition at phylum level or bacterial 16S rRNA gene abundance. Soil pH and C:N ratio were the major drivers for bacterial community structure in the most frequent fire treatment (B2), while other factors (EC, DOC, DON, MBC, NH4(+), TC and TN) were significant in the less frequent burning and no burning treatments (B4 and B0). This study suggested that burning had a dramatic impact on bacterial diversity but not abundance with more frequent fire.

Long term repeated fire disturbance alters soil bacterial diversity but not the abundance in an Australian wet sclerophyll forest

PubMed Central

Shen, Ju-pei; Chen, C. R.; Lewis, Tom

2016-01-01

Effects of fire on biogeochemical cycling in terrestrial ecosystem are widely acknowledged, while few studies have focused on the bacterial community under the disturbance of long-term frequent prescribed fire. In this study, three treatments (burning every two years (B2), burning every four years (B4) and no burning (B0)) were applied for 38 years in an Australian wet sclerophyll forest. Results showed that bacterial alpha diversity (i.e. bacterial OTU) in the top soil (0–10 cm) was significantly higher in the B2 treatment compared with the B0 and B4 treatments. Non-metric multidimensional analysis (NMDS) of bacterial community showed clear separation of the soil bacterial community structure among different fire frequency regimes and between the depths. Different frequency fire did not have a substantial effect on bacterial composition at phylum level or bacterial 16S rRNA gene abundance. Soil pH and C:N ratio were the major drivers for bacterial community structure in the most frequent fire treatment (B2), while other factors (EC, DOC, DON, MBC, NH4+, TC and TN) were significant in the less frequent burning and no burning treatments (B4 and B0). This study suggested that burning had a dramatic impact on bacterial diversity but not abundance with more frequent fire. PMID:26787458

Plant traits determine forest flammability

NASA Astrophysics Data System (ADS)

Zylstra, Philip; Bradstock, Ross

2016-04-01

Carbon and nutrient cycles in forest ecosystems are influenced by their inherent flammability - a property determined by the traits of the component plant species that form the fuel and influence the micro climate of a fire. In the absence of a model capable of explaining the complexity of such a system however, flammability is frequently represented by simple metrics such as surface fuel load. The implications of modelling fire - flammability feedbacks using surface fuel load were examined and compared to a biophysical, mechanistic model (Forest Flammability Model) that incorporates the influence of structural plant traits (e.g. crown shape and spacing) and leaf traits (e.g. thickness, dimensions and moisture). Fuels burn with values of combustibility modelled from leaf traits, transferring convective heat along vectors defined by flame angle and with plume temperatures that decrease with distance from the flame. Flames are re-calculated in one-second time-steps, with new leaves within the plant, neighbouring plants or higher strata ignited when the modelled time to ignition is reached, and other leaves extinguishing when their modelled flame duration is exceeded. The relative influence of surface fuels, vegetation structure and plant leaf traits were examined by comparing flame heights modelled using three treatments that successively added these components within the FFM. Validation was performed across a diverse range of eucalypt forests burnt under widely varying conditions during a forest fire in the Brindabella Ranges west of Canberra (ACT) in 2003. Flame heights ranged from 10 cm to more than 20 m, with an average of 4 m. When modelled from surface fuels alone, flame heights were on average 1.5m smaller than observed values, and were predicted within the error range 28% of the time. The addition of plant structure produced predicted flame heights that were on average 1.5m larger than observed, but were correct 53% of the time. The over-prediction in this case was the result of a small number of large errors, where higher strata such as forest canopy were modelled to ignite but did not. The addition of leaf traits largely addressed this error, so that the mean flame height over-prediction was reduced to 0.3m and the fully parameterised FFM gave correct predictions 62% of the time. When small (<1m) flames were excluded, the fully parameterised model correctly predicted flame heights 12 times more often than could be predicted using surface fuels alone, and the Mean Absolute Error was 4 times smaller. The inadequate consideration of plant traits within a mechanistic framework introduces significant error to forest fire behaviour modelling. The FFM provides a solution to this, and an avenue by which plant trait information can be used to better inform Global Vegetation Models and decision-making tools used to mitigate the impacts of fire.

Effect of mesohabitats on responses of invertebrate community structure in streams under different land uses.

PubMed

da Silva, Marcos Vinícius Dias; Rosa, Beatriz F J V; Alves, Roberto G

2015-11-01

Riparian vegetation is one of the most important abiotic components determining the water flow pattern in lotic ecosystems, influencing the composition, richness, and diversity of invertebrates. We have identified whether differences in the structure of the assemblages of invertebrates between riffles and pools may influence the responses of fauna to the effects of land use. In addition, we investigated which fauna metrics are responsible for the differentiation between riffles and pools in streams subject to different land uses. During the dry season of 2012, the main substrates of riffles and pools were sampled (Surber collector) from nine streams within forest, pasture, and urban areas. Principal component analysis (PCA) and Permanova showed differences in the set of environmental variables between streams and mesohabitats. The first PCA axis distinguished the forest and pasture streams from the urban area streams and was related to variables indicative of nutrient enrichment and land use, while the second axis was formed by velocity flow and by the quantities of ultrafine and coarse sand, which distinguished the riffles and pools of the streams. The faunal composition distinguished the streams in pasture and forest areas from the urban streams. Riffles and pools were not concordant in the representation of the invertebrate fauna, indicating the importance of sampling both mesohabitats in the types of streams investigated. The richness, taxonomic composition, and relative abundance of families of Ephemeroptera, Plecoptera, and Trichoptera showed robust responses in riffles to the effects of environmental changes, while in pools, only the richness showed a significant response. It was possibly concluded that riffles were more sensitive in detecting the effects of land use. The information from this study help to understand how the community of invertebrates and the types of habitats in streams may be affected by anthropogenic impacts.

Protected areas and agricultural expansion: Biodiversity conservation versus economic growth in the Southeast of Brazil.

PubMed

Moraes, Mayra Cristina Prado de; Mello, Kaline de; Toppa, Rogério Hartung

2017-03-01

The conversion of natural ecosystems to agricultural land and urban areas plays a threat to the protected areas and the natural ecosystems conservation. The aim of this paper is to provide an analysis of the agricultural expansion and its impact on the landscape spatial and temporal patterns in a buffer zone of a protected area located in the transition zone between the Atlantic Forest and Cerrado, in the State of São Paulo, Brazil. The land use and land cover were mapped between 1971 and 2008 and landscape metrics were calculated to provide a spatiotemporal analysis of the forest structure and the expansion of the croplands. The results showed that the landscape patterns were affected by the economic cycles. The predominant crop surrounding the protected area is sugar cane, which increased by 39% during this period, followed by citrus. This landscape change is connected to the Brazilian oil crisis in 1973. The rapid expansion of sugar cane was largely driven by Brazil's biofuel program, the "Proálcool" (pro-alcohol), a project in 1975 that mixed ethanol with gas for automotive fuel. The forest loss occurred mainly between 1971 and 1988, decreasing the forest cover from 17% in 1971 to 12.7% in 2008. Most of the forest patches are smaller than 50 ha and has low connectivity. Throughout the years, the fragments in the buffer zone have become smaller and with an elongated shape, and the park has become isolated. This forest fragmentation process and the predominance of monoculture lands in the buffer zone threaten the protected areas, and can represent a barrier for these areas to provide the effective biodiversity conservation. The measures proposed are necessary to ensure the capability of this ecosystem to sustain its original biodiversity. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Fish-Based Index of Biotic Integrity for the Assessment of Streams Located in a Sugarcane-Dominated Landscape in Southeastern Brazil.

PubMed

dos Santos, Fernanda Bastos; Esteves, Katharina Eichbaum

2015-08-01

A multimetric, fish-based Index of Biotic Integrity (IBI) was developed and tested to assess the ecological status of streams with different riparian conditions in the Piracicaba River Basin. Nine streams with three categories of riparian zone preservation were selected: native forest (NF) with preserved forest, secondary forest (SF) with forest in an advanced state of regeneration and surrounded by sugarcane plantations, and sugarcane (SC) without riparian vegetation and surrounded by SC crops. A continuous scoring system was employed, and candidate metrics were tested for range, responsiveness, and redundancy, resulting in the selection of eight metrics to compose the index. The final IBI score was positively correlated with an Environmental Index both in the dry (Spearman's rho = 0.76; P = 0.01) and rainy seasons (Spearman's rho = 0.66; P = 0.04), suggesting that this IBI is a suitable tool for the assessment of the biological conditions of these streams. The highest IBI values were observed in the rainy season at the NF and SF sites, with significant differences between the NF and SC sites (Kruskal-Wallis test: P = 0.03). The results indicated some variability in the biological integrity at SF and SC sites, suggesting a relationship with the intensity of the management of this crop. Patterns were consistent with other studies that have shown the effects of agriculture on the environmental quality of streams, which indicate the importance of the riparian zone to the maintenance of ecosystem integrity and supports the use of the IBI for biological monitoring in similar regions.

A Fish-Based Index of Biotic Integrity for the Assessment of Streams Located in a Sugarcane-Dominated Landscape in Southeastern Brazil

NASA Astrophysics Data System (ADS)

dos Santos, Fernanda Bastos; Esteves, Katharina Eichbaum

2015-08-01

A multimetric, fish-based Index of Biotic Integrity (IBI) was developed and tested to assess the ecological status of streams with different riparian conditions in the Piracicaba River Basin. Nine streams with three categories of riparian zone preservation were selected: native forest (NF) with preserved forest, secondary forest (SF) with forest in an advanced state of regeneration and surrounded by sugarcane plantations, and sugarcane (SC) without riparian vegetation and surrounded by SC crops. A continuous scoring system was employed, and candidate metrics were tested for range, responsiveness, and redundancy, resulting in the selection of eight metrics to compose the index. The final IBI score was positively correlated with an Environmental Index both in the dry (Spearman's rho = 0.76; P = 0.01) and rainy seasons (Spearman's rho = 0.66; P = 0.04), suggesting that this IBI is a suitable tool for the assessment of the biological conditions of these streams. The highest IBI values were observed in the rainy season at the NF and SF sites, with significant differences between the NF and SC sites (Kruskal-Wallis test: P = 0.03). The results indicated some variability in the biological integrity at SF and SC sites, suggesting a relationship with the intensity of the management of this crop. Patterns were consistent with other studies that have shown the effects of agriculture on the environmental quality of streams, which indicate the importance of the riparian zone to the maintenance of ecosystem integrity and supports the use of the IBI for biological monitoring in similar regions.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks.

PubMed

Campbell, J Elliott; Moen, Jeremie C; Ney, Richard A; Schnoor, Jerald L

2008-03-01

Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0 million metric tons of carbon per year for the GIS and regression approaches respectively.

The role of spring and autumn phenological switches on spatiotemporal variation in temperate and boreal forest C balance: A FLUXNET synthesis

NASA Astrophysics Data System (ADS)

Richardson, A. D.; Reichstein, M.; Piao, S.; Ciais, P.; Luyssaert, S.; Stockli, R.; Friedl, M.; Gobron, N.; Fluxnet Site Pis, 21

2009-04-01

In temperate and boreal ecosystems, phenological transitions (particularly the timing of spring onset and autumn senescence) are thought to represent a major control on spatial and temporal variation in forest carbon sequestration. To investigate these patterns, we analyzed 153 site-years of data from the FLUXNET ‘La Thuile' database. Eddy covariance measurements of surface-atmosphere exchanges of carbon and water from 21 research sites at latitudes from 36°N to 67°N were used in the synthesis. We defined a range of phenological indicators based on the first (spring) and last (autumn) dates of (1) C source/sink transitions (‘carbon uptake period'); (2) measurable photosynthetic uptake (‘physiologically active period'); (3) relative thresholds for latent heat (evapotranspiration) flux; (4) phenological thresholds derived from a range of remote sensing products (JRC fAPAR, MOD12Q2, and the PROGNOSTIC model with MODIS data assimilation); and (5) a climatological metric based on the date where soil temperature equals mean annual air temperature. We then tested whether site-level flux anomalies were significantly correlated with phenological anomalies across these metrics, and whether the slopes of these relationships (representing the sensitivity to phenological variation) differed between deciduous broadleaf (DBF) and evergreen needleleaf (ENF) forests. Within sites, interannual variation in most phenological metrics was about 5-10 d, compared to 10-30 d across sites. Both spatial and temporal phenological variation were consistently larger at ENF, compared to DBF, sites. Averaged across metrics, phenological variability was roughly comparable in spring and autumn, both across (17 d) and within (9 d) sites. However, patterns of interannual variation in fluxes were less well explained by the derived phenological metrics than were patterns of spatial variation in fluxes. Also, the observed pattern strongly depended on the metric used, with flux-derived metrics generally explaining more, and remote sensing-derived metrics generally explaining less, of the variation in flux anomalies. We found that GPP (gross primary productivity) was consistently more sensitive (both in terms of magnitude and statistical significance; ≈3 g C m-2 d-1 for DBF and ≈2 g C m-2 d-1 for ENF) to phenology than was Reco (ecosystem respiration), which meant that NEP (net ecosystem productivity) tended to be increased both by earlier springs and later autumns. Without exception, when the difference between DBF and ENF in the sensitivity to phenological anomalies was statistically significant, DBF sensitivity was always larger in absolute magnitude than ENF sensitivity. Phenology explained a much larger fraction of the variation in fluxes across sites compared to within sites. Across sites, the rate of increase in GPP with an "exta" day in spring (≈10 g C m-2 d-1) was much larger than in autumn (≈3 g C m-2 d-1). Furthermore, a one-day increase in growing season length across sites increased annual NEP by just ≈2 g C m-2 d-1; this resulted from an increase in GPP of ≈6 g C m-2 d-1 being offset by an increase in RE of ≈4 g C m-2 d-1. In general, there was no statistically significant difference between DBF and ENF in the sensitivity to spatial variation in phenology for either NEP or the component fluxes GPP and Reco. In relation to both within- and across-site variation in phenology and fluxes, the results obtained tended to depend on the phenological metric used, i.e. definition of "start" and "end" of growing season, emphasizing the need for improved understanding of the relationships between these different metrics and ecosystem processes. Furthermore, the differences in flux-phenology relationships in the context of spatial and temporal variation in phenology raise questions about using results from either short-term or space-for-time studies to anticipate responses to future climate change.

Time Series of Tropical-Forest Structure from TanDEM-X, Transformed to Time Series of Biomass by MODIS

NASA Astrophysics Data System (ADS)

Treuhaft, R. N.; Baccini, A.; Goncalves, F. G.; Lei, Y.; Keller, M.; Walker, W. S.

2017-12-01

Tropical forests account for about 50% of the world's forested biomass, and play a critical role in the control of atmospheric carbon dioxide. Large-scale (1000's of km) changes in forest structure and biomass bear on global carbon source-sink dynamics, while small-scale (< 100 m) changes bear on deforestation and degradation monitoring. After describing the interferometric SAR (InSAR) phase-height observation, we show forest phase-height time series from the TanDEM-X radar interferometer at X-band (3 cm), taken with monthly and sub-hectare temporal and spatial resolution, respectively. The measurements were taken with more than 30 TanDEM-X passes over Tapajós National Forest in the Brazilian Amazon between 2011 and 2014. The transformation of phase-height rates into aboveground biomass (AGB) rates is based on the idea that the change in AGB due to a change in phase-height depends on the plot's AGB. Plots with higher AGB will produce more AGB for a given increase in height or phase-height. Postulating a power-law dependence of plot-level mass density on physical height, we previously found that the best conversion factors for transforming phase-height rate to AGB rate were indeed dependent on AGB. For 78 plots, we demonstrated AGB rates from InSAR phase-height rates using AGB from field measurements. For regional modeling of the Amazon Basin, field measurements of AGB, to specify the conversion factors, is impractical. Conversion factors from InSAR phase-height rate to AGB rate in this talk will be based on AGB derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). AGB measurement from MODIS is based on the spectral reflectance of 7 bands from the visible to short wave infrared, and auxiliary metrics describing the variance in reflectance. The mapping of MODIS reflectance to AGB is enabled by training a machine learning algorithm with lidar-derived AGB data, which are in turn trained by field measurements for small areas. The performance of TanDEM-X AGB rate from MODIS-derived conversion factors will be compared to that derived from field-based conversion factors. We will also attempt to improve phase-height rate to AGB rate transformation by deriving improved models of mass density dependences on height, based on the aggregation of single-stem allometrics.

Bird Communities and Environmental Correlates in Southern Oregon and Northern California, USA.

PubMed

Stephens, Jaime L; Dinger, Eric C; Alexander, John D; Mohren, Sean R; Ralph, C John; Sarr, Daniel A

2016-01-01

We examined avian community ecology in the Klamath Ecoregion and determined that individual bird species co-exist spatially to form 29 statistically distinguishable bird groups. We identified climate, geography, and vegetation metrics that are correlated with these 29 bird groups at three scales: Klamath Ecoregion, vegetation formation (agriculture, conifer, mixed conifer/hardwood, shrubland), and National Park Service unit. Two climate variables (breeding season mean temperature and temperature range) and one geography variable (elevation) were correlated at all scales, suggesting that for some vegetation formations and park units there is sufficient variation in climate and geography to be an important driver of bird communities, a level of variation we expected only at the broader scale. We found vegetation to be important at all scales, with coarse metrics (environmental site potential and existing vegetation formation) meaningful across all scales and structural vegetation patterns (e.g. succession, disturbance) important only at the scale of vegetation formation or park unit. Additionally, we examined how well six National Park Service units represent bird communities in the broader Klamath Ecoregion. Park units are inclusive of most bird communities with the exception of the oak woodland community; mature conifer forests are well represented, primarily associated with conifer canopy and lacking multi-layered structure. Identifying environmental factors that shape bird communities at three scales within this region is important; such insights can inform local and regional land management decisions necessary to ensure bird conservation in this globally significant region.

Bird Communities and Environmental Correlates in Southern Oregon and Northern California, USA

PubMed Central

Dinger, Eric C.; Alexander, John D.; Mohren, Sean R.; Ralph, C. John; Sarr, Daniel A.

2016-01-01

We examined avian community ecology in the Klamath Ecoregion and determined that individual bird species co-exist spatially to form 29 statistically distinguishable bird groups. We identified climate, geography, and vegetation metrics that are correlated with these 29 bird groups at three scales: Klamath Ecoregion, vegetation formation (agriculture, conifer, mixed conifer/hardwood, shrubland), and National Park Service unit. Two climate variables (breeding season mean temperature and temperature range) and one geography variable (elevation) were correlated at all scales, suggesting that for some vegetation formations and park units there is sufficient variation in climate and geography to be an important driver of bird communities, a level of variation we expected only at the broader scale. We found vegetation to be important at all scales, with coarse metrics (environmental site potential and existing vegetation formation) meaningful across all scales and structural vegetation patterns (e.g. succession, disturbance) important only at the scale of vegetation formation or park unit. Additionally, we examined how well six National Park Service units represent bird communities in the broader Klamath Ecoregion. Park units are inclusive of most bird communities with the exception of the oak woodland community; mature conifer forests are well represented, primarily associated with conifer canopy and lacking multi-layered structure. Identifying environmental factors that shape bird communities at three scales within this region is important; such insights can inform local and regional land management decisions necessary to ensure bird conservation in this globally significant region. PMID:27732625

Parsimony in landscape metrics: Strength, universality, and consistency

Treesearch

Samuel A. Cushman; Kevin McGarigal; Maile C. Neel

2008-01-01

Ecologists can be overwhelmed by the number of metrics available to quantify landscape structure. Clarification of interrelationships and redundancy is needed to guide metric selection and interpretation for the purpose of landscape monitoring. In this study we identified independent components of class- and landscape-level structure in multiple landscapes in each of...

Mapping spatial distribution of forest age in China

NASA Astrophysics Data System (ADS)

Zhang, Yuan; Yao, Yitong; Wang, Xuhui; Liu, Yongwen; Piao, Shilong

2017-03-01

Forest stand age is a meaningful metric, which reflects the past disturbance legacy, provides guidelines for forest management practices, and is an important factor in qualifying forest carbon cycles and carbon sequestration potential. Reliable large-scale forest stand age information with high spatial resolutions, however, is difficult to obtain. In this study, we developed a top-down method to downscale the provincial statistics of national forest inventory data into 1 km stand age map using climate data and light detection and ranging-derived forest height. We find that the distribution of forest stand age in China is highly heterogeneous across the country, with a mean value of 42.6 years old. The relatively young stand age for Chinese forests is mostly due to the large proportion of newly planted forests (0-40 years old), which are more prevailing in south China. Older forests (stand age > 60 years old) are more frequently found in east Qinghai-Tibetan Plateau and the central mountain areas of west and northeast China, where human activities are less intensive. Among the 15 forest types, forests dominated by species of Taxodiaceae, with the exception of Cunninghamia lanceolata stands, have the oldest mean stand age (136 years), whereas Pinus massoniana forests are the youngest (18 years). We further identified uncertainties associated with our forest age map, which are high in west and northeast China. Our work documents the distribution of forest stand age in China at a high resolution which is useful for carbon cycle modeling and the sustainable use of China's forest resources.

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

USGS Publications Warehouse

Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

2016-01-01

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.

PubMed

Lavdas, Ioannis; Glocker, Ben; Kamnitsas, Konstantinos; Rueckert, Daniel; Mair, Henrietta; Sandhu, Amandeep; Taylor, Stuart A; Aboagye, Eric O; Rockall, Andrea G

2017-10-01

As part of a program to implement automatic lesion detection methods for whole body magnetic resonance imaging (MRI) in oncology, we have developed, evaluated, and compared three algorithms for fully automatic, multiorgan segmentation in healthy volunteers. The first algorithm is based on classification forests (CFs), the second is based on 3D convolutional neural networks (CNNs) and the third algorithm is based on a multi-atlas (MA) approach. We examined data from 51 healthy volunteers, scanned prospectively with a standardized, multiparametric whole body MRI protocol at 1.5 T. The study was approved by the local ethics committee and written consent was obtained from the participants. MRI data were used as input data to the algorithms, while training was based on manual annotation of the anatomies of interest by clinical MRI experts. Fivefold cross-validation experiments were run on 34 artifact-free subjects. We report three overlap and three surface distance metrics to evaluate the agreement between the automatic and manual segmentations, namely the dice similarity coefficient (DSC), recall (RE), precision (PR), average surface distance (ASD), root-mean-square surface distance (RMSSD), and Hausdorff distance (HD). Analysis of variances was used to compare pooled label metrics between the three algorithms and the DSC on a 'per-organ' basis. A Mann-Whitney U test was used to compare the pooled metrics between CFs and CNNs and the DSC on a 'per-organ' basis, when using different imaging combinations as input for training. All three algorithms resulted in robust segmenters that were effectively trained using a relatively small number of datasets, an important consideration in the clinical setting. Mean overlap metrics for all the segmented structures were: CFs: DSC = 0.70 ± 0.18, RE = 0.73 ± 0.18, PR = 0.71 ± 0.14, CNNs: DSC = 0.81 ± 0.13, RE = 0.83 ± 0.14, PR = 0.82 ± 0.10, MA: DSC = 0.71 ± 0.22, RE = 0.70 ± 0.34, PR = 0.77 ± 0.15. Mean surface distance metrics for all the segmented structures were: CFs: ASD = 13.5 ± 11.3 mm, RMSSD = 34.6 ± 37.6 mm and HD = 185.7 ± 194.0 mm, CNNs; ASD = 5.48 ± 4.84 mm, RMSSD = 17.0 ± 13.3 mm and HD = 199.0 ± 101.2 mm, MA: ASD = 4.22 ± 2.42 mm, RMSSD = 6.13 ± 2.55 mm, and HD = 38.9 ± 28.9 mm. The pooled performance of CFs improved when all imaging combinations (T2w + T1w + DWI) were used as input, while the performance of CNNs deteriorated, but in neither case, significantly. CNNs with T2w images as input, performed significantly better than CFs with all imaging combinations as input for all anatomical labels, except for the bladder. Three state-of-the-art algorithms were developed and used to automatically segment major organs and bones in whole body MRI; good agreement to manual segmentations performed by clinical MRI experts was observed. CNNs perform favorably, when using T2w volumes as input. Using multimodal MRI data as input to CNNs did not improve the segmentation performance. © 2017 American Association of Physicists in Medicine.

Evaluating factors that predict the structure of a commensalistic epiphyte–phorophyte network

PubMed Central

Sáyago, Roberto; Lopezaraiza-Mikel, Martha; Quesada, Mauricio; Álvarez-Añorve, Mariana Yolotl; Cascante-Marín, Alfredo; Bastida, Jesus Ma.

2013-01-01

A central issue in ecology is the understanding of the establishment of biotic interactions. We studied the factors that affect the assembly of the commensalistic interactions between vascular epiphytes and their host plants. We used an analytical approach that considers all individuals and species of epiphytic bromeliads and woody hosts and non-hosts at study plots. We built models of interaction probabilities among species to assess if host traits and abundance and spatial overlap of species predict the quantitative epiphyte–host network. Species abundance, species spatial overlap and host size largely predicted pairwise interactions and several network metrics. Wood density and bark texture of hosts also contributed to explain network structure. Epiphytes were more common on large hosts, on abundant woody species, with denser wood and/or rougher bark. The network had a low level of specialization, although several interactions were more frequent than expected by the models. We did not detect a phylogenetic signal on the network structure. The effect of host size on the establishment of epiphytes indicates that mature forests are necessary to preserve diverse bromeliad communities. PMID:23407832

Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

NASA Astrophysics Data System (ADS)

Krishnamurthy, Narayanan; Maddali, Siddharth; Romanov, Vyacheslav; Hawk, Jeffrey

We present some structural properties of multi-component steel alloys as predicted by a random forest machine-learning model. These non-parametric models are trained on high-dimensional data sets defined by features such as chemical composition, pre-processing temperatures and environmental influences, the latter of which are based upon standardized testing procedures for tensile, creep and rupture properties as defined by the American Society of Testing and Materials (ASTM). We quantify the goodness of fit of these models as well as the inferred relative importance of each of these features, all with a conveniently defined metric and scale. The models are tested with synthetic data points, generated subject to the appropriate mathematical constraints for the various features. By this we highlight possible trends in the increase or degradation of the structural properties with perturbations in the features of importance. This work is presented as part of the Data Science Initiative at the National Energy Technology Laboratory, directed specifically towards the computational design of steel alloys.

Forest resilience to drought varies across biomes.

PubMed

Gazol, Antonio; Camarero, Jesus Julio; Vicente-Serrano, Sergio M; Sánchez-Salguero, Raúl; Gutiérrez, Emilia; de Luis, Martin; Sangüesa-Barreda, Gabriel; Novak, Klemen; Rozas, Vicente; Tíscar, Pedro A; Linares, Juan C; Martín-Hernández, Natalia; Martínez Del Castillo, Edurne; Ribas, Montse; García-González, Ignacio; Silla, Fernando; Camisón, Alvaro; Génova, Mar; Olano, José M; Longares, Luis A; Hevia, Andrea; Tomás-Burguera, Miquel; Galván, J Diego

2018-05-01

Forecasted increase drought frequency and severity may drive worldwide declines in forest productivity. Species-level responses to a drier world are likely to be influenced by their functional traits. Here, we analyse forest resilience to drought using an extensive network of tree-ring width data and satellite imagery. We compiled proxies of forest growth and productivity (TRWi, absolutely dated ring-width indices; NDVI, Normalized Difference Vegetation Index) for 11 tree species and 502 forests in Spain corresponding to Mediterranean, temperate, and continental biomes. Four different components of forest resilience to drought were calculated based on TRWi and NDVI data before, during, and after four major droughts (1986, 1994-1995, 1999, and 2005), and pointed out that TRWi data were more sensitive metrics of forest resilience to drought than NDVI data. Resilience was related to both drought severity and forest composition. Evergreen gymnosperms dominating semi-arid Mediterranean forests showed the lowest resistance to drought, but higher recovery than deciduous angiosperms dominating humid temperate forests. Moreover, semi-arid gymnosperm forests presented a negative temporal trend in the resistance to drought, but this pattern was absent in continental and temperate forests. Although gymnosperms in dry Mediterranean forests showed a faster recovery after drought, their recovery potential could be constrained if droughts become more frequent. Conversely, angiosperms and gymnosperms inhabiting temperate and continental sites might have problems to recover after more intense droughts since they resist drought but are less able to recover afterwards. © 2018 John Wiley & Sons Ltd.

The Influence of Roads and Buffer Depth on Habitat Core Areas and Connectivity in the NE USA

NASA Astrophysics Data System (ADS)

Jantz, P.; Goetz, S.

2006-12-01

Land development pressures that threaten habitat core areas and connectivity are intensifying across the nation and extending beyond urbanized areas in the form of rural residential development. This is particularly true in the temperate forests of the northeastern U.S. If current trends continue, increased conversion and fragmentation of many roadless areas by exurban development is likely, exacerbating the likelihood of local species extinctions and complicating efforts to preserve intact functional ecosystems. We used a suite of nationally available data sets to identify roadless areas of the northeastern USA including impervious cover (urbanized and developed areas), road networks (and derived density), and forest cover (canopy density). We analyzed the influence of different types of unimproved roads and amount of forest cover on identification of the extent and configuration of roadless areas, and then assessed these areas in terms of land ownership (public, private) and management (parks, refuges, multi-use, etc.). We also derived patch connectivity metrics using a graph theory approach, making use of cost surfaces that accounted for the above variables and associated landscape metrics. Our results suggest a starting point for the construction of a more comprehensive and ecologically functional reserve network for the region. Because the data sets we used are available nationally, similar analyses could be conducted to assess the extent and status of roadless areas nationally or for other specific regions.

Relationship Between Landcover Pattern and Surface Net Radiation in AN Coastal City

NASA Astrophysics Data System (ADS)

Zhao, X.; Liu, L.; Liu, X.; Zhao, Y.

2016-06-01

Taking Xiamen city as the study area this research first retrieved surface net radiation using meteorological data and Landsat 5 TM images of the four seasons in the year 2009. Meanwhile the 65 different landscape metrics of each analysis unit were acquired using landscape analysis method. Then the most effective landscape metrics affecting surface net radiation were determined by correlation analysis, partial correlation analysis, stepwise regression method, etc. At both class and landscape levels, this paper comprehensively analyzed the temporal and spatial variations of the surface net radiation as well as the effects of land cover pattern on it in Xiamen from a multi-seasonal perspective. The results showed that the spatial composition of land cover pattern shows significant influence on surface net radiation while the spatial allocation of land cover pattern does not. The proportions of bare land and forest land are effective and important factors which affect the changes of surface net radiation all the year round. Moreover, the proportion of forest land is more capable for explaining surface net radiation than the proportion of bare land. So the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This study is helpful in exploring the formation and evolution mechanism of urban heat island. It also gave theoretical hints and realistic guidance for urban planning and sustainable development.

Unprecedented remote sensing data over King and Rim megafires in the Sierra Nevada Mountains of California.

PubMed

Stavros, E Natasha; Tane, Zachary; Kane, Van R; Veraverbeke, Sander; McGaughey, Robert J; Lutz, James A; Ramirez, Carlos; Schimel, David

2016-11-01

Megafires have lasting social, ecological, and economic impacts and are increasing in the western contiguous United States. Because of their infrequent nature, there is a limited sample of megafires to investigate their unique behavior, drivers, and relationship to forest management practices. One approach is to characterize critical information pre-, during, and post-fire using remote sensing. In August 2013, the Rim Fire burned 104,131 ha and in September 2014, the King Fire burned 39,545 ha. Both fires occurred in California's Sierra Nevada. The areas burned by these fires were fortuitously surveyed by airborne campaigns, which provided the most recent remote sensing technologies not currently available from satellite. Technologies include an imaging spectrometer spanning the visible to shortwave infrared (0.38-2.5 μm), a multispectral, high-spatial resolution thermal infrared (3.5-13 μm) spectroradiometer, and Light Detection and Ranging that provide spatial resolutions of pixels from 1 × 1 m to 35 × 35 m. Because of the unique information inherently derived from these technologies before the fires, the areas were subsequently surveyed after the fires. We processed and provide free dissemination of these airborne datasets as products of surface reflectance, spectral metrics and forest structural metrics ( http://dx.doi.org/10.3334/ORNLDAAC/1288). These data products provide a unique opportunity to study relationships among and between remote sensing observations and fuel and fire characteristics (e.g., fuel type, condition, structure, and fire severity). The novelty of these data is not only in the unprecedented types of information available from them before, during, and after two megafires, but also in the synergistic use of multiple state of the art technologies for characterizing the environment. The synergy of these data can provide novel information that can improve maps of fuel type, structure, abundance, and condition that may improve predictions of megafire behavior and effects, thus aiding management before, during, and after such events. Key questions that these data could address include: What drives, extinguishes, and results from megafires? How does megafire behavior relate to fire and fuel management? How does the size and severity of a megafire affect the ecological recovery of the system? © 2016 by the Ecological Society of America.

Evaluating the utility and seasonality of NDVI values for assessing post-disturbance recovery in a subalpine forest.

PubMed

Buma, Brian

2012-06-01

Forest disturbances around the world have the potential to alter forest type and cover, with impacts on diversity, carbon storage, and landscape composition. These disturbances, especially fire, are common and often large, making ground investigation of forest recovery difficult. Remote sensing offers a means to monitor forest recovery in real time, over the entire landscape. Typically, recovery monitoring via remote sensing consists of measuring vegetation indices (e.g., NDVI) or index-derived metrics, with the assumption that recovery in NDVI (for example) is a meaningful measure of ecosystem recovery. This study tests that assumption using MODIS 16-day imagery from 2000 to 2010 in the area of the Colorado's Routt National Forest Hinman burn (2002) and seedling density counts taken in the same area. Results indicate that NDVI is rarely correlated with forest recovery, and is dominated by annual and perennial forb cover, although topography complicates analysis. Utility of NDVI as a means to delineate areas of recovery or non-recovery are in doubt, as bootstrapped analysis indicates distinguishing power only slightly better than random. NDVI in revegetation analyses should carefully consider the ecology and seasonal patterns of the system in question.

Effects of metric hierarchy and rhyme predictability on word duration in The Cat in the Hat.

PubMed

Breen, Mara

2018-05-01

Word durations convey many types of linguistic information, including intrinsic lexical features like length and frequency and contextual features like syntactic and semantic structure. The current study was designed to investigate whether hierarchical metric structure and rhyme predictability account for durational variation over and above other features in productions of a rhyming, metrically-regular children's book: The Cat in the Hat (Dr. Seuss, 1957). One-syllable word durations and inter-onset intervals were modeled as functions of segment number, lexical frequency, word class, syntactic structure, repetition, and font emphasis. Consistent with prior work, factors predicting longer word durations and inter-onset intervals included more phonemes, lower frequency, first mention, alignment with a syntactic boundary, and capitalization. A model parameter corresponding to metric grid height improved model fit of word durations and inter-onset intervals. Specifically, speakers realized five levels of metric hierarchy with inter-onset intervals such that interval duration increased linearly with increased height in the metric hierarchy. Conversely, speakers realized only three levels of metric hierarchy with word duration, demonstrating that they shortened the highly predictable rhyme resolutions. These results further understanding of the factors that affect spoken word duration, and demonstrate the myriad cues that children receive about linguistic structure from nursery rhymes. Copyright © 2018 Elsevier B.V. All rights reserved.

Ponderosa pine resin defenses and growth: Metrics matter

Treesearch

Sharon Hood; Anna Sala

2015-01-01

Bark beetles (Coleoptera: Curculionidae, Scolytinae) cause widespread tree mortality in coniferous forests worldwide. Constitutive and induced host defenses are important factors in an individual tree’s ability to survive an attack and in bottom-up regulation of bark beetle population dynamics, yet quantifying defense levels is often difficult. For example, in...

Evidence of biotic resistance to invasions in forests of the Eastern USA

Treesearch

Basil V. Iannone III; Kevin M. Potter; Kelly-Ann Dixon Hamil; Whitney Huang; Hao Zhang; Qinfeng Guo; Christopher M. Oswalt; Christopher W. Woodall; Songlin Fei

2016-01-01

Context Detecting biotic resistance to biological invasions across large geographic areas may require acknowledging multiple metrics of niche usage and potential spatial heterogeneity in associations between invasive and native species diversity and dominance.Objectives Determine (1) if native communities are ...

BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation

Treesearch

M. Pfeifer; Tamara Heartsill Scalley

2014-01-01

Habitat fragmentation studies have produced complex results that are challenging to synthesize. Inconsistencies among studies may result from variation in the choice of landscape metrics and response variables, which is often compounded by a lack of key statistical or methodological information. Collating primary datasets on biodiversity responses to fragmentation in a...

Cradle-to-grave life cycle assessment of syngas electricity from woody biomass residues

Treesearch

Hongmei Gu; Richard Bergman

2017-01-01

Forest restoration and fire suppression activities in the western United States have resulted in large volumes of low-to-no value residues. An environmental assessment would enable greater use while maintaining environmental sustainability of these residues for energy products. One internationally accepted sustainable metric tool that can assess environmental impacts...

Brooklyn's urban forest

Treesearch

David J. Nowak; Daniel E. Crane; Jack C. Stevens; Myriam Ibarra

2002-01-01

An assessment of trees in Brooklyn, New York, reveal that this borough has approximately 610,000 trees with canopies that cover 11.4 percent of the area. The most common trees are estimated to be tree of heaven, white mulberry, black locust, Norway maple and black cherry. Brooklyn's trees currently store approximately 172,000 metric tons of carbon with an...

Different slopes of a mountain can determine the structure of ferns and lycophytes communities in a tropical forest of Brazil.

PubMed

Nettesheim, Felipe C; Damasceno, Elaine R; Sylvestre, Lana S

2014-03-01

A community of Ferns and Lycophytes was investigated by comparing the occurrence of species on different slopes of a paleoisland in Southeastern Brazil. Our goal was to evaluate the hypothesis that slopes with different geographic orientations determine a differentiation of Atlantic Forest ferns and lycophytes community. We recorded these plants at slopes turned towards the continent and at slopes turned towards the open sea. Analysis consisted of a preliminary assessment on fern beta diversity, a Non Metric Multidimensional Scaling (NMDS) and a Student t-test to confirm if sites sampling units ordination was different at each axis. We further used the Pearson coefficient to relate fern species to the differentiation pattern and again Student's t-test to determine if richness, plant cover and abundance varied between the two sites. There was a relatively low number of shared species between the two sites and ferns and lycophytes community variation was confirmed. Some species were detected as indicators of the community variation but we were unable to detect richness, plant cover or abundance differences. Despite the evidence of this variation between the slopes, further works are needed to evaluate which processes are contributing to determine this pattern.

Characterising the Geomorphology of Forested Floodplains Using High Resolution Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Sear, D. A.; Brasington, J.; Darby, S. E.

2007-12-01

Forested floodplain environments represent the undisturbed land cover of most temperate and tropical river systems, but they are under threat from human resource management (Hughes et al., 2005, FLOBAR II Project report). A scientific understanding of forest floodplain processes therefore has relevance to ecosystem conservation and restoration, and the interpretation of pre-historic river and floodplain evolution. Empirical research has highlighted how overbank flows are relatively shallow and strongly modified by floodplain topography and the presence of vegetation and organic debris on the woodland floor [Jeffries et al., 2003, Geomorphology, 51, 61-80; Millington and Sear, 2007, Earth. Surf. Proc. Landforms, 32, doi: 10.1002/esp.1552]. In such instances flow blockage and diversions are common, and there is the possibility of frequent switches from sub-critical to locally super-critical flow. Such conditions also favour turbulence generation, both by wakes and by shear. Consequently, the floodplain terrain (where we take 'terrain' to include the underlying topography, root structures, and organic debris) plays a key role in modulating the processes of erosion and sedimentation that underpin the physical habitat diversity and hydraulic characteristics of complex wooded floodplain surfaces. However, despite the importance of these issues, as yet there are no formal, quantitative, descriptions of the highly complex and spatially diverse micro- and meso-topography that appears to be characteristic of forested floodplain surfaces. To address this gap, we have undertaken detailed surveys on a small floodplain reach within the Highland Water Research Catchment (HWRC: see http://www.geog.soton.ac.uk/research/nfrc/default.asp), which is a UK national reference site for lowland floodplain forest streams. This involved the deployment of a Leica ScanStation terrestrial laser-scanner from 14 setups and ranges of less than 30 m to acquire an extremely high resolution, accurate (185 million xyz observations, with absolute mean registration errors of 2 mm) 3-d point cloud model of the floodplain. These raw data were processed using a combination of Leica CYCLONE and bespoke filtering algorithms to construct a multi-resolution DTM of the forested floodplain at hitherto unprecedented detail (median point density ~4500 pts m-2). A key point is that the extreme precision and point density permit relevant features of the terrain (micro-topography, protruding roots, branches and stems, and surficial debris) that contribute to the floodplain roughness, to be readily and directly be incorporated in the DTM as topographic features. To characterise the morphology of the floodplain surface we have used the DTM to analyse a range of floodplain morphometric indices, in particular focusing on derivative surface roughness metrics (including roughness height) which are relevant in the parameterization of flow resistance. These are analysed at the floodplain scale to show the spatial distribution of roughness, and at a patch scale selected from a simple classification of floodplain surface. The analysis demonstrates spatial variability in roughness metrics at both scales, which have implications for parameterising flow resistance in models of wooded floodplains.

A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion.

PubMed

Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit

2017-05-01

Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.

Effects of landscape change on fish assemblage structure in a rapidly growing metropolitan area in North Carolina, USA

USGS Publications Warehouse

Kennen, J.G.; Chang, M.; Tracy, B.H.

2005-01-01

We evaluated a comprehensive set of natural and land-use attributes that represent the major facets of urban development at fish monitoring sites in the rapidly growing Raleigh-Durham, North Carolina metropolitan area. We used principal component and correlation analysis to obtain a nonredundant subset of variables that extracted most variation in the complete set. With this subset of variables, we assessed the effect of urban growth on fish assemblage structure. We evaluated variation in fish assemblage structure with nonmetric multidimensional scaling (NMDS). We used correlation analysis to identify the most important environmental and landscape variables associated with significant NMDS axes. The second NMDS axis is related to many indices of land-use/land-cover change and habitat. Significant correlations with proportion of largest forest patch to total patch size (r = -0.460, P < 0.01), diversity of patch types (r = 0.554, P < 0.001), and population density (r = 0.385, P < 0.05) helped identify NMDS axis 2 as a disturbance gradient. Positive and negative correlations between the abundance of redbreast sunfish Lepomis auritus and bluehead chub Nocomis leptocephalus, respectively, and NMDS axis 2 also were evident. The North Carolina index of biotic integrity and many of its component metrics were highly correlated with urbanization. These results indicate that aquatic ecosystem integrity would be optimized by a comprehensive integrated management strategy that includes the preservation of landscape function by maximizing the conservation of contiguous tracts of forested lands and vegetative cover in watersheds. ?? 2005 by the American Fisheries Society.

Drought and Fragmentation Impacts on Forest Evapotranspiration in Southwestern Amazonia

NASA Astrophysics Data System (ADS)

Numata, I.; Khand, K.; Kjaersgaard, J.

2017-12-01

We assessed the effects of forest fragmentation and drought on forest evapotranspiration (ET) estimated using the energy balance-based model METRIC with Landsat imagery in Rondônia and Acre in the southwestern Amazon. Forest ET estimates were produced for the dry seasons (June-August) of 2009-2011 thus including the 2010 drought period to quantify its impact by comparing to pre- and post-drought years. Furthermore, we tested forest edge distance, edge density, shape index, and area/edge ratio of forest fragments as fragmentation variables. The 2010 drought year showed the lowest monthly forest ET in August and September in both Rondônia and Acre within the study time period. However, part of the decline of forest ET in Acre during this period appeared to be due to less incoming solar radiation caused by atmospheric contamination from fires in addition to inadequate moisture availability. Lingering impacts of the drought on forest ET were observed in 2011, the post-drought year. Both sites showed lower forest ET in the late dry season in 2011 compared to 2009, the pre-drought year. Among forest fragmentation variables, edge distance presented significant impacts on forest ET in the drought and post-drought years (p<0.05), whereas the other variables were not significant. The magnitude of ET changes along edge distance becomes even greater in the drought year (2010) and the post-drought year (2011) in the month of August.

Mapping Disturbance Dynamics in Wet Sclerophyll Forests Using Time Series Landsat

NASA Astrophysics Data System (ADS)

Haywood, A.; Verbesselt, J.; Baker, P. J.

2016-06-01

In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat time series data. We analysed a representative State forest within the Central Highlands which has been exposed to a range of disturbances over the last 30 years, including timber harvesting (clearfell, selective and thinning) and fire (wildfire and prescribed burning). We fitted spectral time series models to annual normal burn ratio (NBR) and Tasseled Cap Indices (TCI), from which we extracted a range of disturbance and recovery metrics. With these metrics, three hierarchical random forest models were trained to 1) distinguish acute-severity disturbances from low-severity disturbances; 2a) attribute the disturbance agents most likely within the acute-severity class; 2b) and attribute the disturbance agents most likely within the low-severity class. Disturbance types (acute severity and low-severity) were successfully mapped with an overall accuracy of 72.9 %, and the individual disturbance types were successfully attributed with overall accuracies ranging from 53.2 % to 64.3 %. Low-severity disturbance agents were successfully mapped with an overall accuracy of 80.2 %, and individual agents were successfully attributed with overall accuracies ranging from 25.5 % to 95.1. Acute-severity disturbance agents were successfully mapped with an overall accuracy of 95.4 %, and individual agents were successfully attributed with overall accuracies ranging from 94.2 % to 95.2 %. Spectral metrics describing the disturbance magnitude were more important for distinguishing the disturbance agents than the post-disturbance response slope. Spectral changes associated with planned burning disturbances had generally lower magnitudes than selective harvesting. This study demonstrates the potential of landsat time series mapping for fire and timber harvesting disturbances at the agent level and highlights the need for distinguishing between agents to fully capture their impacts on ecosystem processes.

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

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

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE PAGES

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; ...

2015-10-09

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

The Optimizer Topology Characteristics in Seismic Hazards

NASA Astrophysics Data System (ADS)

Sengor, T.

2015-12-01

The characteristic data of the natural phenomena are questioned in a topological space approach to illuminate whether there is an algorithm behind them bringing the situation of physics of phenomena to optimized states even if they are hazards. The optimized code designing the hazard on a topological structure mashes the metric of the phenomena. The deviations in the metric of different phenomena push and/or pull the fold of the other suitable phenomena. For example if the metric of a specific phenomenon A fits to the metric of another specific phenomenon B after variation processes generated with the deviation of the metric of previous phenomenon A. Defining manifold processes covering the metric characteristics of each of every phenomenon is possible for all the physical events; i.e., natural hazards. There are suitable folds in those manifold groups so that each subfold fits to the metric characteristics of one of the natural hazard category at least. Some variation algorithms on those metric structures prepare a gauge effect bringing the long time stability of Earth for largely scaled periods. The realization of that stability depends on some specific conditions. These specific conditions are called optimized codes. The analytical basics of processes in topological structures are developed in [1]. The codes are generated according to the structures in [2]. Some optimized codes are derived related to the seismicity of NAF beginning from the quakes of the year 1999. References1. Taner SENGOR, "Topological theory and analytical configuration for a universal community model," Procedia- Social and Behavioral Sciences, Vol. 81, pp. 188-194, 28 June 2013, 2. Taner SENGOR, "Seismic-Climatic-Hazardous Events Estimation Processes via the Coupling Structures in Conserving Energy Topologies of the Earth," The 2014 AGU Fall Meeting, Abstract no.: 31374, ABD.

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS.

PubMed

Reddy, C Sudhakar; Jha, C S; Dadhwal, V K

2013-05-01

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924-1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km(2) (52.5 %), 56,661.1 km(2) (36.4 %), 51,642.3 km(2) (33.2 %), 49,773 km(2) (32 %) and 48,669.4 km(2) (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 % year(-1) during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km(2)) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.

Optimizing prescribed fire allocation for managing fire risk in central Catalonia.

PubMed

Alcasena, Fermín J; Ager, Alan A; Salis, Michele; Day, Michelle A; Vega-Garcia, Cristina

2018-04-15

We used spatial optimization to allocate and prioritize prescribed fire treatments in the fire-prone Bages County, central Catalonia (northeastern Spain). The goal of this study was to identify suitable strategic locations on forest lands for fuel treatments in order to: 1) disrupt major fire movements, 2) reduce ember emissions, and 3) reduce the likelihood of large fires burning into residential communities. We first modeled fire spread, hazard and exposure metrics under historical extreme fire weather conditions, including node influence grid for surface fire pathways, crown fraction burned and fire transmission to residential structures. Then, we performed an optimization analysis on individual planning areas to identify production possibility frontiers for addressing fire exposure and explore alternative prescribed fire treatment configurations. The results revealed strong trade-offs among different fire exposure metrics, showed treatment mosaics that optimize the allocation of prescribed fire, and identified specific opportunities to achieve multiple objectives. Our methods can contribute to improving the efficiency of prescribed fire treatment investments and wildfire management programs aimed at creating fire resilient ecosystems, facilitating safe and efficient fire suppression, and safeguarding rural communities from catastrophic wildfires. The analysis framework can be used to optimally allocate prescribed fire in other fire-prone areas within the Mediterranean region and elsewhere. Copyright © 2017 Elsevier B.V. All rights reserved.

Interactive effects of deer exclusion and exotic plant removal on deciduous forest understory communities

USGS Publications Warehouse

Bourg, Norman; McShea, William J.; Herrmann, Valentine; Stewart, Chad M.

2017-01-01

Mammalian herbivory and exotic plant species interactions are an important ongoing research topic, due to their presumed impacts on native biodiversity. The extent to which these interactions affect forest understory plant community composition and persistence was the subject of our study. We conducted a 5-year, 2 × 2 factorial experiment in three mid-Atlantic US deciduous forests with high densities of white-tailed deer (Odocoileus virginianus) and exotic understory plants. We predicted: (i) only deer exclusion and exotic plant removal in tandem would increase native plant species metrics; and (ii) deer exclusion alone would decrease exotic plant abundance over time. Treatments combining exotic invasive plant removal and deer exclusion for plots with high initial cover, while not differing from fenced or exotic removal only plots, were the only ones to exhibit positive richness responses by native herbaceous plants compared to control plots. Woody seedling metrics were not affected by any treatments. Deer exclusion caused significant increases in abundance and richness of native woody species >30 cm in height. Abundance changes in two focal members of the native sapling community showed that oaks (Quercus spp.) increased only with combined exotic removal and deer exclusion, while shade-tolerant maples (Acer spp.) showed no changes. We also found significant declines in invasive Japanese stiltgrass (Microstegium vimineum) abundance in deer-excluded plots. Our study demonstrates alien invasive plants and deer impact different components and life-history stages of the forest plant community, and controlling both is needed to enhance understory richness and abundance. Alien plant removal combined with deer exclusion will most benefit native herbaceous species richness under high invasive cover conditions while neither action may impact native woody seedlings. For larger native woody species, only deer exclusion is needed for such increases. Deer exclusion directly facilitated declines in invasive species abundance. Resource managers should consider addressing both factors to achieve their forest management goals.

Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan'an City, China.

PubMed

Zhang, Xinping; Wang, Dexiang; Hao, Hongke; Zhang, Fangfang; Hu, Youning

2017-07-26

In this study Yan'an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990-2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990-2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon's diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment.

Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan’an City, China

PubMed Central

Zhang, Xinping; Hao, Hongke; Zhang, Fangfang; Hu, Youning

2017-01-01

In this study Yan’an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990–2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990–2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon’s diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment. PMID:28933770

Quantifying post-fire fallen trees using multi-temporal lidar

NASA Astrophysics Data System (ADS)

Bohlin, Inka; Olsson, Håkan; Bohlin, Jonas; Granström, Anders

2017-12-01

Massive tree-felling due to root damage is a common fire effect on burnt areas in Scandinavia, but has so far not been analyzed in detail. Here we explore if pre- and post-fire lidar data can be used to estimate the proportion of fallen trees. The study was carried out within a large (14,000 ha) area in central Sweden burnt in August 2014, where we had access to airborne lidar data from both 2011 and 2015. Three data-sets of predictor variables were tested: POST (post-fire lidar metrics), DIF (difference between post- and pre-fire lidar metrics) and combination of those two (POST_DIF). Fractional logistic regression was used to predict the proportion of fallen trees. Training data consisted of 61 plots, where the number of fallen and standing trees was calculated both in the field and with interpretation of drone images. The accuracy of the best model was tested based on 100 randomly selected validation plots with a size of 25 × 25 m. Our results showed that multi-temporal lidar together with field-collected training data can be used for quantifying post-fire tree felling over large areas. Several height-, density- and intensity metrics correlated with the proportion of fallen trees. The best model combined metrics from both datasets (POST_DIF), resulting in a RMSE of 0.11. Results were slightly poorer in the validation plots with RMSE of 0.18 using pixel size of 12.5 m and RMSE of 0.15 using pixel size of 6.25 m. Our model performed least well for stands that had been exposed to high-intensity crown fire. This was likely due to the low amount of echoes from the standing black tree skeletons. Wall-to-wall maps produced with this model can be used for landscape level analysis of fire effects and to explore the relationship between fallen trees and forest structure, soil type, fire intensity or topography.

Landscape, Environmental and Social Predictors of Hantavirus Risk in São Paulo, Brazil

PubMed Central

Uriarte, Maria; Tambosi, Leandro Reverberi; Prado, Amanda; Pardini, Renata; D´Andrea, Paulo Sérgio; Metzger, Jean Paul

2016-01-01

Hantavirus Pulmonary Syndrome (HPS) is a disease caused by Hantavirus, which are negative-sense RNA viruses in the family Bunyaviridae that are highly virulent to humans. Numerous factors modify risk of Hantavirus transmission and consequent HPS risk. Human-driven landscape change can foster transmission risk by increasing numbers of habitat generalist rodent species that serve as the principal reservoir host. Climate can also affect rodent population dynamics and Hantavirus survival, and a number of social factors can influence probability of HPS transmission to humans. Evaluating contributions of these factors to HPS risk may enable predictions of future outbreaks, and is critical to development of effective public health strategies. Here we rely on a Bayesian model to quantify associations between annual HPS incidence across the state of São Paulo, Brazil (1993–2012) and climate variables (annual precipitation, annual mean temperature), landscape structure metrics (proportion of native habitat cover, number of forest fragments, proportion of area planted with sugarcane), and social factors (number of men older than 14 years and Human Development Index). We built separate models for the main two biomes of the state (cerrado and Atlantic forest). In both biomes Hantavirus risk increased with proportion of land cultivated for sugarcane and HDI, but proportion of forest cover, annual mean temperature, and population at risk also showed positive relationships in the Atlantic forest. Our analysis provides the first evidence that social, landscape, and climate factors are associated with HPS incidence in the Neotropics. Our risk map can be used to support the adoption of preventive measures and optimize the allocation of resources to avoid disease propagation, especially in municipalities that show medium to high HPS risk (> 5% of risk), and aimed at sugarcane workers, minimizing the risk of future HPS outbreaks. PMID:27780250

Use of waveform lidar and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest

USGS Publications Warehouse

Anderson, J.E.; Ducey, Mark J.; Fast, A.; Martin, M.E.; Lepine, L.; Smith, M.-L.; Lee, T.D.; Dubayah, R.O.; Hofton, M.A.; Hyde, P.; Peterson, Birgit; Blair, J.B.

2011-01-01

Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASA's Laser Vegetation Imaging Sensor (LVIS). This flight occurred 20 months after an ice storm damaged millions of hectares of forestland in northeastern North America. Lidar measurements of the amplitude and intensity of ground energy returns appeared to readily detect areas of moderate to severe ice storm damage associated with the worst damage. Southern through eastern aspects on side slopes were particularly susceptible to higher levels of damage, in large part overlapping tracts of forest that had suffered the highest levels of wind damage from the 1938 hurricane and containing the highest levels of sugar maple basal area and biomass. The levels of sugar maple abundance were determined through analysis of the 1997 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) high resolution spectral imagery and inventory of USFS Northern Research Station field plots. We found a relationship between field measurements of stem volume losses and the LVIS metric of mean canopy height (r2 = 0.66; root mean square errors = 5.7 m3/ha, p < 0.0001) in areas that had been subjected to moderate-to-severe ice storm damage, accurately documenting the short-term outcome of a single disturbance event.

Impact of anthropogenic climate change on wildfire across western US forests.

PubMed

Abatzoglou, John T; Williams, A Park

2016-10-18

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Park Williams, A.

2016-10-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ˜55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Multidimensional trade-offs in species responses to disturbance: implications for diversity in a subtropical forest.

PubMed

Uriarte, María; Clark, James S; Zimmerman, Jess K; Comita, Liza S; Forero-Montaña, Jimena; Thompson, Jill

2012-01-01

Species employ diverse strategies to cope with natural disturbance, but the importance of these strategies for maintaining tree species diversity in forests has been debated. Mechanisms that have the potential to promote tree species coexistence in the context of repeated disturbance include life history trade-offs in colonization and competitive ability or in species' ability to survive at low resource conditions and exploit the temporary resource-rich conditions often generated in the wake of disturbance (successional niche). Quantifying these trade-offs requires long-term forest monitoring and modeling. We developed a hierarchical Bayes model to investigate the strategies tree species employ to withstand and recover from hurricane disturbance and the life history trade-offs that may facilitate species coexistence in forests subject to repeated hurricane disturbance. Unlike previous approaches, our model accommodates temporal variation in process error and observations from multiple sources. We parameterized the model using growth and mortality data from four censuses of a 16-ha plot taken every five years (1990-2005), together with damage data collected after two hurricanes and annual seed production data (1992-2005). Species' susceptibilities to hurricane damage as reflected by changes in diameter growth and fecundity immediately following a storm were weak, highly variable, and unpredictable using traditional life history groupings. The lower crowding conditions (e.g., high light) generated in the wake of storms, however, led to greater gains in growth and fecundity for pioneer and secondary-forest species than for shade-tolerant species, in accordance with expectation of life history. We found moderate trade-offs between survival in high crowding conditions, a metric of competitive ability, and long-distance colonization. We also uncovered a strong trade-off between mean species fecundity in low crowding conditions, a metric of recovery potential, and competitive ability. Trade-offs in competitive and colonization ability, in addition to successional niche processes, are likely to contribute to species persistence in these hurricane-impacted forests. The strategies species employ to cope with hurricane damage depend on the degree to which species rely on sprouting, repair of adult damage, changes in demographic rates in response to enhanced resource availability after storms, or long-distance dispersal as recovery mechanisms.

Ethanol accumulation during severe drought may signal tree vulnerability to detection and attack by bark beetles

Treesearch

Rick G. Kelsey; D. Gallego; F.J. Sánchez-Garcia; J.A. Pajares

2014-01-01

Tree mortality from temperature-driven drought is occurring in forests around the world, often in conjunction with bark beetle outbreaks when carbon allocation to tree defense declines. Physiological metrics for detecting stressed trees with enhanced vulnerability prior to bark beetle attacks remain elusive. Ethanol, water, monoterpene concentrations, and composition...

Quantitative metrics for assessing predicted climate change pressure on North American tree species

Treesearch

Kevin M. Potter; William W. Hargrove

2013-01-01

Changing climate may pose a threat to forest tree species, forcing three potential population-level responses: toleration/adaptation, movement to suitable environmental conditions, or local extirpation. Assessments that prioritize and classify tree species for management and conservation activities in the face of climate change will need to incorporate estimates of the...

Oxygen production by urban trees in the United States

Treesearch

David J. Nowak; Robert Hoehn; Daniel E. Crane

2007-01-01

Urban forests in the coterminous United States are estimated to produce ≈61 million metric tons (67 million tons) of oxygen annually, enough oxygen to offset the annual oxygen consumption of approximately two-thirds of the U.S. opulation. Although oxygen production is often cited as a significant benefit of trees, this benefit is relatively insignificant and...

Atmospheric carbon reduction by urban trees

Treesearch

David J. Nowak

1993-01-01

Trees, because they sequester atmospheric carbon through their growth process and conserve energy in urban areas, have been suggested as one means to combat increasing levels of atmospheric carbon. Analysis of the urban forest in Oakland, California (21% tree cover), reveals a tree carbon storage level of 11.0 metric tons/hectare. Trees in the area of the 1991 fire in...

A new method for evaluating forest thinning: growth dominance in managed Pinus resinosa stands

Treesearch

John B. Bradford; Anthony W. D' Amato; Brian J. Palik; Shawn Fraver

2010-01-01

Growth dominance is a relatively new, simple, quantitative metric of within-stand individual tree growth patterns, and is defined as positive when larger trees in the stand display proportionally greater growth than smaller trees, and negative when smaller trees display proportionally greater growth than larger trees. We examined long-term silvicultural experiments in...

Water use assessments supporting company-specific growth and sustainability goals

Treesearch

John Beebe

2016-01-01

In areas with increasing demand for water, addressing water use objectives has long been a primary environmental objective and key concern among industrial water users including paper mills and other forest product companies. However, in recent years, water use metrics and related information (including population change, climate information, and land use...

Comparing techniques for estimating flame temperature of prescribed fires

Treesearch

Deborah K. Kennard; Kenneth W. Outcalt; David Jones; Joseph J. O' Brien

2005-01-01

A variety of techniques that estimate temperature and/or heat output during fires are available. We assessed the predictive ability of metal and tile pyrometers, calorimeters of different sizes, and fuel consumption to time-temperature metrics derived from thick and thin thermocouples at 140 points distributed over 9 management-scale burns in a longleaf pine forest in...

The evaluation of meta-analysis techniques for quantifying prescribed fire effects on fuel loadings.

Treesearch

Karen E. Kopper; Donald McKenzie; David L. Peterson

2009-01-01

Models and effect-size metrics for meta-analysis were compared in four separate meta-analyses quantifying surface fuels after prescribed fires in ponderosa pine (Pinus ponderosa Dougl. ex Laws.) forests of the Western United States. An aggregated data set was compiled from eight published reports that contained data from 65 fire treatment units....

Impacts of changes in land use and fragmentation patterns on Atlantic coastal forests in northern Spain.

PubMed

Teixido, Alberto L; Quintanilla, Luis G; Carreño, Francisco; Gutiérrez, David

2010-01-01

Changes in forested landscapes may have important consequences for ecosystem services and biodiversity conservation. In northern Spain, major changes in land use occurred during the second half of the 20th century, but their impacts on forests have not been quantified. We evaluated the dynamics of landscape and forest distribution patterns between 1957 and 2003 in Fragas do Eume Natural Park (northwestern Spain). We used orthoimages and a set of standard landscape metrics to determine transitions between land cover classes and to examine forest distribution patterns. Eucalypt plantations showed the greatest increase in area (197%) over time. Furthermore, transitions to eucalypt plantations were found in all major land cover classes. Forest showed a net decline of 20% in total area and represented 30% of the landscape area in 2003. Forest losses were mainly due to eucalypt plantations and the building of a water reservoir, while forest gains were due to increases in shrubland, meadows and cultivated fields which had been recolonised. Forest patch size and core area decreased, and edge length increased over time. In turn, increases were obtained in mean distance between forest patches, and in adjacency to eucalypt plantations and to a water reservoir. These results suggest an increase in forest fragmentation from 1957 to 2003, as well as a change in the nature of the habitat surrounding forest patches. This study shows that land use changes, mostly from eucalypt plantation intensification, negatively affected forested habitats, although some regeneration was ongoing through ecological succession from land abandonment. Copyright 2009 Elsevier Ltd. All rights reserved.

Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

PubMed

Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

2014-01-01

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

Landscape characteristics affecting streams in urbanizing regions of the Delaware River Basin (New Jersey, New York, and Pennsylvania, U.S.)

USGS Publications Warehouse

Riva-Murray, K.; Riemann, R.; Murdoch, P.; Fischer, J.M.; Brightbill, R.

2010-01-01

Widespread and increasing urbanization has resulted in the need to assess, monitor, and understand its effects on stream water quality. Identifying relations between stream ecological condition and urban intensity indicators such as impervious surface provides important, but insufficient information to effectively address planning and management needs in such areas. In this study we investigate those specific landscape metrics which are functionally linked to indicators of stream ecological condition, and in particular, identify those characteristics that exacerbate or mitigate changes in ecological condition over and above impervious surface. The approach used addresses challenges associated with redundancy of landscape metrics, and links landscape pattern and composition to an indicator of stream ecological condition across a broad area of the eastern United States. Macroinvertebrate samples were collected during 2000-2001 from forty-two sites in the Delaware River Basin, and landscape data of high spatial and thematic resolution were obtained from photointerpretation of 1999 imagery. An ordination-derived 'biotic score' was positively correlated with assemblage tolerance, and with urban-related chemical characteristics such as chloride concentration and an index of potential pesticide toxicity. Impervious surface explained 56% of the variation in biotic score, but the variation explained increased to as high as 83% with the incorporation of a second land use, cover, or configuration metric at catchment or riparian scales. These include land use class-specific cover metrics such as percent of urban land with tree cover, forest fragmentation metrics such as aggregation index, riparian metrics such as percent tree cover, and metrics related to urban aggregation. Study results indicate that these metrics will be important to monitor in urbanizing areas in addition to impervious surface. ?? 2010 US Government.

Ecological and environmental transition across the forested-to-open bog ecotone in a west Siberian peatland.

PubMed

Ratcliffe, Joshua L; Creevy, Angela; Andersen, Roxane; Zarov, Evgeny; Gaffney, Paul P J; Taggart, Mark A; Mazei, Yuri; Tsyganov, Andrey N; Rowson, James G; Lapshina, Elena D; Payne, Richard J

2017-12-31

Climate change may cause increasing tree cover in boreal peatlands, and the impacts of this encroachment will be noted first at forested-to-open bog ecotones. We investigate key metrics of ecosystem function in five such ecotones at a peatland complex in Western Siberia. Stratigraphic analysis of three cores from one of these transects shows that the ecotone has been dynamic over time with evidence for recent expansion of forested peatland. We observed that the two alternative states for northern boreal peatlands (forested/open) clearly support distinct plant and microbial communities. These in turn drive and respond to a number of feedback mechanisms. This has led to steep ecological gradients across the ecotones. Tree cover was associated with lower water tables and pH, along with higher bulk density, aquatic carbon concentrations, and electrical conductivity. We propose that the conditions found in the forested peatland of Western Siberia make the carbon sink more vulnerable to warmer and drier conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiscale Path Metrics for the Analysis of Discrete Geometric Structures

DTIC Science & Technology

2017-11-30

Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release

Diversity of fruit-feeding butterflies in a mountaintop archipelago of rainforest.

PubMed

Pereira, Geanne Carla Novais; Coelho, Marcel Serra; Beirão, Marina do Vale; Braga, Rodrigo Fagundes; Fernandes, Geraldo Wilson

2017-01-01

We provide the first description of the effects of local vegetation and landscape structure on the fruit-feeding butterfly community of a natural archipelago of montane rainforest islands in the Serra do Espinhaço, southeastern Brazil. Butterflies were collected with bait traps in eleven forest islands through both dry and rainy seasons for two consecutive years. The influence of local and landscape parameters and seasonality on butterfly species richness, abundance and composition were analyzed. We also examined the partitioning and decomposition of temporal and spatial beta diversity. Five hundred and twelve fruit-feeding butterflies belonging to thirty-four species were recorded. Butterfly species richness and abundance were higher on islands with greater canopy openness in the dry season. On the other hand, islands with greater understory coverage hosted higher species richness in the rainy season. Instead, the butterfly species richness was higher with lower understory coverage in the dry season. Butterfly abundance was not influenced by understory cover. The landscape metrics of area and isolation had no effect on species richness and abundance. The composition of butterfly communities in the forest islands was not randomly structured. The butterfly communities were dependent on local and landscape effects, and the mechanism of turnover was the main source of variation in β diversity. The preservation of this mountain rainforest island complex is vital for the maintenance of fruit-feeding butterfly community; one island does not reflect the diversity found in the whole archipelago.

Diversity of fruit-feeding butterflies in a mountaintop archipelago of rainforest

PubMed Central

Pereira, Geanne Carla Novais; Beirão, Marina do Vale; Braga, Rodrigo Fagundes; Fernandes, Geraldo Wilson

2017-01-01

We provide the first description of the effects of local vegetation and landscape structure on the fruit-feeding butterfly community of a natural archipelago of montane rainforest islands in the Serra do Espinhaço, southeastern Brazil. Butterflies were collected with bait traps in eleven forest islands through both dry and rainy seasons for two consecutive years. The influence of local and landscape parameters and seasonality on butterfly species richness, abundance and composition were analyzed. We also examined the partitioning and decomposition of temporal and spatial beta diversity. Five hundred and twelve fruit-feeding butterflies belonging to thirty-four species were recorded. Butterfly species richness and abundance were higher on islands with greater canopy openness in the dry season. On the other hand, islands with greater understory coverage hosted higher species richness in the rainy season. Instead, the butterfly species richness was higher with lower understory coverage in the dry season. Butterfly abundance was not influenced by understory cover. The landscape metrics of area and isolation had no effect on species richness and abundance. The composition of butterfly communities in the forest islands was not randomly structured. The butterfly communities were dependent on local and landscape effects, and the mechanism of turnover was the main source of variation in β diversity. The preservation of this mountain rainforest island complex is vital for the maintenance of fruit-feeding butterfly community; one island does not reflect the diversity found in the whole archipelago. PMID:28666003

Ecological Impacts of Deforestation and Forest Degradation in the Peat Swamp Forests of Northwestern Borneo

NASA Astrophysics Data System (ADS)

Nguyen, Ha Thanh

Tropical peatlands have some of the highest carbon densities of any ecosystem and are under enormous development pressure. This dissertation aimed to provide better estimates of the scales and trends of ecological impacts from tropical peatland deforestation and degradation across more than 7,000 hectares of both intact and disturbed peatlands in northwestern Borneo. We combined direct field sampling and airborne Light Detection And Ranging (LiDAR) data to empirically quantify forest structures and aboveground live biomass across a largely intact tropical peat dome. The observed biomass density of 217.7 +/- 28.3 Mg C hectare-1 was very high, exceeding many other tropical rainforests. The canopy trees were 65m in height, comprising 81% of the aboveground biomass. Stem density was observed to increase across the 4m elevational gradient from the dome margin to interior with decreasing stem height, crown area and crown roughness. We also developed and implemented a multi-temporal, Landsat resolution change detection algorithm for identify disturbance events and assessing forest trends in aseasonal tropical peatlands. The final map product achieved more than 92% user's and producer's accuracy, revealing that after more than 25 years of management and disturbances, only 40% of the area was intact forest. Using a chronosequence approach, with a space for time substitution, we then examined the temporal dynamics of peatlands and their recovery from disturbance. We observed widespread arrested succession in previously logged peatlands consistent with hydrological limits on regeneration and degraded peat quality following canopy removal. We showed that clear-cutting, selective logging and drainage could lead to different modes of regeneration and found that statistics of the Enhanced Vegetation Index and LiDAR height metrics could serve as indicators of harvesting intensity, impacts, and regeneration stage. Long-term, continuous monitoring of the hydrology and ecology of peatland can provide key insights regarding best management practices, restoration, and conservation priorities for this unique and rapidly disappearing ecosystem.

The importance of forest structure to biodiversity–productivity relationships

PubMed Central

Huth, Andreas

2017-01-01

While various relationships between productivity and biodiversity are found in forests, the processes underlying these relationships remain unclear and theory struggles to coherently explain them. In this work, we analyse diversity–productivity relationships through an examination of forest structure (described by basal area and tree height heterogeneity). We use a new modelling approach, called ‘forest factory’, which generates various forest stands and calculates their annual productivity (above-ground wood increment). Analysing approximately 300 000 forest stands, we find that mean forest productivity does not increase with species diversity. Instead forest structure emerges as the key variable. Similar patterns can be observed by analysing 5054 forest plots of the German National Forest Inventory. Furthermore, we group the forest stands into nine forest structure classes, in which we find increasing, decreasing, invariant and even bell-shaped relationships between productivity and diversity. In addition, we introduce a new index, called optimal species distribution, which describes the ratio of realized to the maximal possible productivity (by shuffling species identities). The optimal species distribution and forest structure indices explain the obtained productivity values quite well (R2 between 0.7 and 0.95), whereby the influence of these attributes varies within the nine forest structure classes. PMID:28280550

Fuel Treatment Effects on Water Use Efficiency in Western Pine Forests Under Fire Suppression Evaluated Using Tree Ring Carbon Isotopes

NASA Astrophysics Data System (ADS)

Taylor, A. H.; Belmecheri, S.; Harris, L. B.

2016-12-01

We identified variation on water use efficiency interpreted from carbon 13 in tree ring cellulose in dense ponderosa pines forests in Washington and Arizona. Historically, these forests burned every decade until fires were suppressed beginning in the early twentieth century. The reduction in fire caused large increases in forest density and forest biomass and potential for intense fire. Forests with hazardous fuels are common in the western United States and these types of forests are treated with mechanical thinning and mechanical thinning and burning to reduce hazardous fuels and fire intensity. At each site we extracted tree ring samples from five trees in each treatment type and a control to identify the effects of fuel treatment of concentration of carbon 13 in tree ring cellulose. Water use efficiency as measured by carbon 13 increased after fuel treatments. Treatment effects were larger for the mechanical plus burn treatment than for the mechanical treatment in each study area compared to the control stands Our results suggest that fuel treatments reduce sensitivity of tree growth to climate and increase water use efficiency. Since tree ring carbon 13 is related to plant productivity, carbon 13 in tree rings can be used as a metric of change in ecosystem function for evaluating fuel treatments.

Threshold Responses of Forest Birds to Landscape Changes around Exurban Development

PubMed Central

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

2013-01-01

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

Long-lasting effects of land use history on soil fungal communities in second-growth tropical rain forests.

PubMed

Bachelot, Benedicte; Uriarte, María; Zimmerman, Jess K; Thompson, Jill; Leff, Jonathan W; Asiaii, Ava; Koshner, Jenny; McGuire, Krista

2016-09-01

Our understanding of the long-lasting effects of human land use on soil fungal communities in tropical forests is limited. Yet, over 70% of all remaining tropical forests are growing in former agricultural or logged areas. We investigated the relationship among land use history, biotic and abiotic factors, and soil fungal community composition and diversity in a second-growth tropical forest in Puerto Rico. We coupled high-throughput DNA sequencing with tree community and environmental data to determine whether land use history had an effect on soil fungal community descriptors. We also investigated the biotic and abiotic factors that underlie such differences and asked whether the relative importance of biotic (tree diversity, basal tree area, and litterfall biomass) and abiotic (soil type, pH, iron, and total carbon, water flow, and canopy openness) factors in structuring soil fungal communities differed according to land use history. We demonstrated long-lasting effects of land use history on soil fungal communities. At our research site, most of the explained variation in soil fungal composition (R 2  = 18.6%), richness (R 2  = 11.4%), and evenness (R 2  = 10%) was associated with edaphic factors. Areas previously subject to both logging and farming had a soil fungal community with lower beta diversity and greater evenness of fungal operational taxonomic units (OTUs) than areas subject to light logging. Yet, fungal richness was similar between the two areas of historical land use. Together, these results suggest that fungal communities in disturbed areas are more homogeneous and diverse than in areas subject to light logging. Edaphic factors were the most strongly correlated with soil fungal composition, especially in areas subject to light logging, where soils are more heterogenous. High functional tree diversity in areas subject to both logging and farming led to stronger correlations between biotic factors and fungal composition than in areas subject to light logging. In contrast, fungal richness and evenness were more strongly correlated with biotic factors in areas of light logging, suggesting that these metrics might reflect long-term associations in old-growth forests. The large amount of unexplained variance in fungal composition suggests that these communities are structured by both stochastic and niche assemblage processes. © 2016 by the Ecological Society of America.

Seasonality in the dung beetle community in a Brazilian tropical dry forest: Do small changes make a difference?

PubMed

Medina, Anderson Matos; Lopes, Priscila Paixão

2014-01-01

Dung beetle (Coleoptera: Scarabaeoidea: Scarabaeinae) activity is influenced by rainfall seasonality. We hypothesized that rainfall might also play a major role in regulating the community structure of this group. In this study, we describe seasonal changes in the richness, composition, and structure of the Scarabaeinae community in a Brazilian tropical dry forest. A fragment of arboreal Caatinga was sampled using baited pitfall traps during the early dry season (EDS), late dry season (LDS), early wet season (EWS), and middle wet season (MWS). We compared the dung beetle community in each season in relationship to species richness, rank-dominance, curves, and composition. We collected 1352 Scarabaeinae individuals , belonging to 15 species. Dichotomius aff. laevicollis Felsche (Coleoptera: Scarabaeidae) was the dominant species, representing 73.89% of the individuals. There were no seasonal changes in the rank dominance curves; all had a single dominant species and a few species with low abundance, typical for arid areas. Estimated richness was highest in MWS, followed by EWS. Dry-season samples (EDS and LDS) had lower richness, with no significant difference between the dry seasons. Although species richness increased as the habitat became wetter, the difference between the wet and dry seasons was small, which differs completely from the findings of other studies in Neotropical dry forests, where almost all species cease activities in the dry season. Species composition changes were found in non-metric multidimensional scaling and sustained by analysis of similarity. All the seasons had pairwise differences in composition, with the exception of EDS and MWS, which indicates that the dung beetle community in this fragment requires more than three months of drought to trigger changes in species composition; this is probably due to small changes in the forest canopy. There was no difference in composition between EDS and MWS. As in other tropical dry forests, although to a lesser extent, the dung beetle community of this fragment responded to rainfall seasonality with changes in species composition and reduced species richness. Such responses, even to this lesser extent, may occur because of small changes in tree cover and minor microclimate changes. This is an open access paper. We use the Creative Commons Attribution 3.0 license that permits unrestricted use, provided that the paper is properly attributed.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Variation in mangrove forest structure and sediment characteristics in Bocas del Toro, Panama

USGS Publications Warehouse

Lovelock, C.E.; Feller, Ilka C.; McKee, K.L.; Thompson, R.

2005-01-01

Mangrove forest structure and sediment characteristics were examined in the extensive mangroves of Bocas del Toro, Republic of Panama. Forest structure was characterized to determine if spatial vegetation patterns were repeated over the Bocas del Toro landscape. Using a series of permanent plots and transects we found that the forests of Bocas del Toro were dominated by Rhizophora mangle with very few individuals of Avicennia germinans and Laguncularia racemosa. Despite this low species diversity, there was large variation in forest structure and in edaphic conditions (salinity, concentration of available phosphorus, Eh and sulphide concentration). Aboveground biomass varied 20-fold, from 6.8 Mg ha-1 in dwarf forests to 194.3 Mg ha-1 in the forests fringing the land. But variation in forest structure was predictable across the intertidal zone. There was a strong tree height gradient from seaward fringe (mean tree height 3.9 m), decreasing in stature in the interior dwarf forests (mean tree height 0.7 m), and increasing in stature in forests adjacent to the terrestrial forest (mean tree height 4.1 m). The predictable variation in forest structure emerges due to the complex interactions among edaphic and plant factors. Identifying predictable patterns in forest structure will aid in scaling up the ecosystem services provided by mangrove forests in coastal landscapes. Copyright 2005 College of Arts and Sciences.

Manifold Preserving: An Intrinsic Approach for Semisupervised Distance Metric Learning.

PubMed

Ying, Shihui; Wen, Zhijie; Shi, Jun; Peng, Yaxin; Peng, Jigen; Qiao, Hong

2017-05-18

In this paper, we address the semisupervised distance metric learning problem and its applications in classification and image retrieval. First, we formulate a semisupervised distance metric learning model by considering the metric information of inner classes and interclasses. In this model, an adaptive parameter is designed to balance the inner metrics and intermetrics by using data structure. Second, we convert the model to a minimization problem whose variable is symmetric positive-definite matrix. Third, in implementation, we deduce an intrinsic steepest descent method, which assures that the metric matrix is strictly symmetric positive-definite at each iteration, with the manifold structure of the symmetric positive-definite matrix manifold. Finally, we test the proposed algorithm on conventional data sets, and compare it with other four representative methods. The numerical results validate that the proposed method significantly improves the classification with the same computational efficiency.

Cross-cultural differences in meter perception.

PubMed

Kalender, Beste; Trehub, Sandra E; Schellenberg, E Glenn

2013-03-01

We examined the influence of incidental exposure to varied metrical patterns from different musical cultures on the perception of complex metrical structures from an unfamiliar musical culture. Adults who were familiar with Western music only (i.e., simple meters) and those who also had limited familiarity with non-Western music were tested on their perception of metrical organization in unfamiliar (Turkish) music with simple and complex meters. Adults who were familiar with Western music detected meter-violating changes in Turkish music with simple meter but not in Turkish music with complex meter. Adults with some exposure to non-Western music that was unmetered or metrically complex detected meter-violating changes in Turkish music with both simple and complex meters, but they performed better on patterns with a simple meter. The implication is that familiarity with varied metrical structures, including those with a non-isochronous tactus, enhances sensitivity to the metrical organization of unfamiliar music.

Light cone structure near null infinity of the Kerr metric

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

Bai Shan; Shang Yu; Graduate School of Chinese Academy of Sciences, Beijing, 100080

2007-02-15

Motivated by our attempt to understand the question of angular momentum of a relativistic rotating source carried away by gravitational waves, in the asymptotic regime near future null infinity of the Kerr metric, a family of null hypersurfaces intersecting null infinity in shearfree (good) cuts are constructed by means of asymptotic expansion of the eikonal equation. The geometry of the null hypersurfaces as well as the asymptotic structure of the Kerr metric near null infinity are studied. To the lowest order in angular momentum, the Bondi-Sachs form of the Kerr metric is worked out. The Newman-Unti formalism is then furthermore » developed, with which the Newman-Penrose constants of the Kerr metric are computed and shown to be zero. Possible physical implications of the vanishing of the Newman-Penrose constants of the Kerr metric are also briefly discussed.« less

Local Topography Effect on Plant Area Index Profile Calculation from Small Footprint Airborne Laser Scanning

NASA Astrophysics Data System (ADS)

Liu, J.; Wang, T.; Skidmore, A. K.; Heurich, M.

2016-12-01

The plant area index (PAI) profile is a quantitative description of how plants (including leaves and woody materials) are distributed vertically, as a function of height. PAI profiles can be used for many applications including biomass estimation, radiative transfer modelling, fire fuel modelling and wildlife habitat assessment. With airborne laser scanning (ALS), forest structure underneath the canopy surface can be detected. PAI profiles can be calculated through estimates of the vertically resolved gap fraction from ALS data. In this process, a gridding or aggregation step is often involved. Most current research neglects local topographic change, and utilizes a height normalization algorithm to achieve a local or relative height, implying a flat local terrain assumption inside the grid or aggregation area. However, in mountainous forest, this assumption is often not valid. Therefore, in this research, the local topographic effect on the PAI profile calculation was studied. Small footprint discrete multi-return ALS data was acquired over the Bavarian Forest National Park under leaf-off and leaf-on conditions. Ground truth data, including tree height, canopy cover, DBH as well as digital hemispherical photos, were collected in 30 plots. These plots covered a wide range of forest structure, plant species, local topography condition and understory coverage. PAI profiles were calculated both with and without height normalization. The difference between height normalized and non-normalized profiles were evaluated with the coefficient of variation of root mean squared difference (CV-RMSD). The derived metric PAI values from PAI profiles were also evaluated with ground truth PAI from the hemispherical photos. Results showed that change in local topography had significant effects on the PAI profile. The CV-RMSD between PAI profile results calculated with or without height normalization ranged from 24.5% to 163.9%. Height normalization (neglecting topography change) can lead to offsets in the height of plant material that could potentially cause large errors and uncertainty when used in applications utilizing absolute height such as radiative transfer modeling and fire fuel modelling. This research demonstrates that when calculating the PAI profile from ALS, local topography has to be taken into account.

A Literature Survey and Experimental Evaluation of the State-of-the-Art in Uplift Modeling: A Stepping Stone Toward the Development of Prescriptive Analytics.

PubMed

Devriendt, Floris; Moldovan, Darie; Verbeke, Wouter

2018-03-01

Prescriptive analytics extends on predictive analytics by allowing to estimate an outcome in function of control variables, allowing as such to establish the required level of control variables for realizing a desired outcome. Uplift modeling is at the heart of prescriptive analytics and aims at estimating the net difference in an outcome resulting from a specific action or treatment that is applied. In this article, a structured and detailed literature survey on uplift modeling is provided by identifying and contrasting various groups of approaches. In addition, evaluation metrics for assessing the performance of uplift models are reviewed. An experimental evaluation on four real-world data sets provides further insight into their use. Uplift random forests are found to be consistently among the best performing techniques in terms of the Qini and Gini measures, although considerable variability in performance across the various data sets of the experiments is observed. In addition, uplift models are frequently observed to be unstable and display a strong variability in terms of performance across different folds in the cross-validation experimental setup. This potentially threatens their actual use for business applications. Moreover, it is found that the available evaluation metrics do not provide an intuitively understandable indication of the actual use and performance of a model. Specifically, existing evaluation metrics do not facilitate a comparison of uplift models and predictive models and evaluate performance either at an arbitrary cutoff or over the full spectrum of potential cutoffs. In conclusion, we highlight the instability of uplift models and the need for an application-oriented approach to assess uplift models as prime topics for further research.

Life-cycle GHG emissions of electricity from syngas produced by pyrolyzing woody biomass

Treesearch

Hongmei Gu; Richard Bergman

2015-01-01

Low-value residues from forest restoration activities in the western United States intended to mitigate effects from wildfire, climate change, and pests and disease need a sustainable market to improve the economic viability of treatment. Converting biomass into bioenergy is a potential solution. Life-cycle assessment (LCA) as a sustainable metric tool can assess the...

Using airborne laser altimetry to determine fuel models for estimating fire behavior

Treesearch

Carl A. Seielstad; Lloyd P. Queen

2003-01-01

Airborne laser altimetry provides an unprecedented view of the forest floor in timber fuel types and is a promising new tool for fuels assessments. It can be used to resolve two fuel models under closed canopies and may be effective for estimating coarse woody debris loads. A simple metric - obstacle density - provides the necessary quantification of fuel bed roughness...

Adjusting forest density estimates for surveyor bias in historical tree surveys

Treesearch

Brice B. Hanberry; Jian Yang; John M. Kabrick; Hong S. He

2012-01-01

The U.S. General Land Office surveys, conducted between the late 1700s to early 1900s, provide records of trees prior to widespread European and American colonial settlement. However, potential and documented surveyor bias raises questions about the reliability of historical tree density estimates and other metrics based on density estimated from these records. In this...

An improved canopy wind model for predicting wind adjustment factors and wildland fire behavior

Treesearch

W. J. Massman; J. M. Forthofer; M. A. Finney

2017-01-01

The ability to rapidly estimate wind speed beneath a forest canopy or near the ground surface in any vegetation is critical to practical wildland fire behavior models. The common metric of this wind speed is the "mid-flame" wind speed, UMF. However, the existing approach for estimating UMF has some significant shortcomings. These include the assumptions that...

Metric Selection for Ecosystem Restoration

DTIC Science & Technology

2013-06-01

focus on wetlands, submerged aquatic vegetation, oyster reefs, riparian forest, and wet prairie (Miner 2005). The objective of these Corps...of coastal habitats, Volume Two: Tools for monitoring coastal habitats. NOAA Coastal Ocean Program Decision Analysis Series No. 23. Silver Spring, MD...NOAA National Centers for Coastal Ocean Science. Thom, R. M., and K. F. Wellman. 1996. Planning aquatic ecosystem restoration monitoring programs

Amphibians as metrics of critical biological thresholds in forested headwater streams of the Pacific Northwest, U.S.A

Treesearch

Hartwell H. Welsh; Garth Hodgson

2008-01-01

1. Amphibians are recognized both for their sensitivity to environmental perturbations and for their usefulness as cost-effective biometrics of ecosystem integrity (=system health). 2. Twenty-three years of research in headwater streams in the Klamath-Siskiyou and North Coast Bioregions of the Pacific Northwest, U.S.A., showed distinct patterns in the...

Indicators of carbon storage in U.S. ecosystems: baseline for terrestrial carbon accounting.

PubMed

Negra, Christine; Sweedo, Caroline Cremer; Cavender-Bares, Kent; O'Malley, Robin

2008-01-01

Policymakers, program managers, and landowners need information about net terrestrial carbon sequestration in forests, croplands, grasslands, and shrublands to understand the cumulative effects of carbon trading programs, expanding biofuels production, and changing environmental conditions in addition to agricultural and forestry uses. Objective information systems that establish credible baselines and track changes in carbon storage can provide the accountability needed for carbon trading programs to achieve durable carbon sequestration and for biofuels initiatives to reduce net greenhouse gas emissions. A multi-sector stakeholder design process was used to produce a new indicator for the 2008 State of the Nation's Ecosystems report that presents metrics of carbon storage for major ecosystem types, specifically change in the amount of carbon gained or lost over time and the amount of carbon stored per unit area (carbon density). These metrics have been developed for national scale use, but are suitable for adaptation to multiple scales such as individual farm and forest parcels, carbon offset markets and integrated national and international assessments. To acquire the data necessary for a complete understanding of how much, and where, carbon is gained or lost by U.S. ecosystems, expansion and integration of monitoring programs will be required.

Long-term effects of prescribed fire on mixed conifer forest structure in the Sierra Nevada, California

Treesearch

Phillip J. Van Mantgem; Nathan L. Stephenson; Eric Knapp; John Barrles; Jon E. Keeley

2011-01-01

The capacity of prescribed fire to restore forest conditions is often judged by changes in forest structure within a few years following burning. However, prescribed fire might have longer-term effects on forest structure, potentially changing treatment assessments. We examined annual changes in forest structure in five 1 ha old-growth plots immediately before...

Mineral resources of the Cranberry Wilderness Study Area, Webster and Pocahontas Counties, West Virginia

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

Meissner, C.R. Jr.; Windolph, J.F. Jr.; Mory, P.C.

1981-01-01

The Cranberry Wilderness Study Area comprises 14,702 ha in the Monongahela National Forest, Webster and Pocahontas Counties, east-central West Virginia. The area is in the Yew Mountains of the Appalachian Plateaus and is at the eastern edge of the central Appalachian coal fields. Cranberry Glades, a peatland of botanical interest, lies at the southern end of the study area. All surface rights in the area are held by the US Forest Service; nearly 90% of the mineral rights are privately owned or subordinate to the surface rights. Bituminous coal of coking quality is the most economically important mineral resource inmore » the Cranberry Wilderness Study Area. Estimated resources in beds 35 cm thick or more are about 100 million metric tons in nine coal beds. Most measured-indicated coal, 70 cm thick or more (reserve base), is in a 7-km-wide east-west trending belt extending across the center of the study area. The estimated reserve base is 34,179 thousand metric tons. Estimated reserves in seven of the coal beds total 16,830 thousand metric tons and are recoverable by underground mining methods. Other mineral resources, all of which have a low potential for development in the study area, include peat, shale, and clay suitable for building brick and lightweight aggregate, sandstone for low-quality glass sand, and sandstone suitable for construction material. Evidence derived from drilling indicates little possibility for oil and gas in the study area. No evidence of economic metallic deposits was found during this investigation.« less

Beyond leaf color: Comparing camera-based phenological metrics with leaf biochemical, biophysical, and spectral properties throughout the growing season of a temperate deciduous forest

NASA Astrophysics Data System (ADS)

Yang, Xi; Tang, Jianwu; Mustard, John F.

2014-03-01

Plant phenology, a sensitive indicator of climate change, influences vegetation-atmosphere interactions by changing the carbon and water cycles from local to global scales. Camera-based phenological observations of the color changes of the vegetation canopy throughout the growing season have become popular in recent years. However, the linkages between camera phenological metrics and leaf biochemical, biophysical, and spectral properties are elusive. We measured key leaf properties including chlorophyll concentration and leaf reflectance on a weekly basis from June to November 2011 in a white oak forest on the island of Martha's Vineyard, Massachusetts, USA. Concurrently, we used a digital camera to automatically acquire daily pictures of the tree canopies. We found that there was a mismatch between the camera-based phenological metric for the canopy greenness (green chromatic coordinate, gcc) and the total chlorophyll and carotenoids concentration and leaf mass per area during late spring/early summer. The seasonal peak of gcc is approximately 20 days earlier than the peak of the total chlorophyll concentration. During the fall, both canopy and leaf redness were significantly correlated with the vegetation index for anthocyanin concentration, opening a new window to quantify vegetation senescence remotely. Satellite- and camera-based vegetation indices agreed well, suggesting that camera-based observations can be used as the ground validation for satellites. Using the high-temporal resolution dataset of leaf biochemical, biophysical, and spectral properties, our results show the strengths and potential uncertainties to use canopy color as the proxy of ecosystem functioning.

Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

NASA Technical Reports Server (NTRS)

Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

2016-01-01

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

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.

A landscape ecology approach to assessing development impacts in the tropics: A geothermal energy example in Hawaii

USGS Publications Warehouse

Griffith, J.A.; Trettin, C.C.; O'Neill, R. V.

2002-01-01

Geographic information systems (GIS) are increasingly being used in environmental impact assessments (EIA) because GIS is useful for analysing spatial impacts of various development scenarios. Spatially representing these impacts provides another tool for landscape ecology in environmental and geographical investigations by facilitating analysis of the effects of landscape patterns on ecological processes and examining change over time. Landscape ecological principles are applied in this study to a hypothetical geothermal development project on the Island of Hawaii. Some common landscape pattern metrics were used to analyse dispersed versus condensed development scenarios and their effect on landscape pattern. Indices of fragmentation and patch shape did not appreciably change with additional development. The amount of forest to open edge, however, greatly increased with the dispersed development scenario. In addition, landscape metrics showed that a human disturbance had a greater simplifying effect on patch shape and also increased fragmentation than a natural disturbance. The use of these landscape pattern metrics can advance the methodology of applying GIS to EIA.

Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

NASA Astrophysics Data System (ADS)

Gu, Huan

Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our ability to map forest structure, species gradient and growth rate occur in residential neighborhoods and along forest edges. Maps generated from this dissertation provide estimates of broad-scale spatial variations in forest structure, species distributions and growth to the city forest managers. The associated maps of uncertainty help managers understand the limitations of the maps and identify locations where the maps are more reliable and where more data are needed.

From the litter up and the sky down: Perspectives on urban forest structure and eco-hydrological processes (presentation)

EPA Science Inventory

The structure of the urban forest represents the complex product of local biophysical conditions, socio-economic milieu, people preferences and management with rare counterparts in rural forests. However, urban forest structure, as similarly observed in rural forests, affects key...

Detection of early warning signals of forest mortality in California

NASA Astrophysics Data System (ADS)

Liu, Y.; Kumar, M.; Katul, G. G.; Porporato, A. M.

2017-12-01

Massive forest mortality was observed in California during the most recent drought. Owing to complex interactions of physiological mechanisms under stress, prediction of climate-induced forest mortality using dynamic global vegetation models remains fraught with uncertainty. Given that forest ecosystems approaching mortality tend to exhibit reduction in resilience, we evaluate the time-varying resilience from time series of satellite images to detect early warning signals (EWSs) of mortality. Four metrics of EWSs are used: (1) low greenness, (2) high empirical autocorrelation of greenness, (3) high autocorrelation inferred using a Bayesian dynamic linear model considering the influence of seasonality and climate conditions, and (4) low recovery rate inferred from the drift term in the Langevin equation describing stochastic dynamics. Spatial accuracy and lead-time of these EWSs are evaluated by comparing the EWSs against observed mortality from aerial surveys conducted by the US Forest Service. Our results show that most forested areas in California that underwent mortality exhibit a EWS with a lead time of three months to two years ahead of observed mortality. Notably, EWS is also detected in some areas without mortality, suggesting reduced resilience during drought. Furthermore, the influence of the previous drought (2007-2009) may have propagated into the recent drought (2012-2016) through reduced resilience, hence contributing to the massive forest mortality observed recently. Methodologies developed in this study for detection of EWS will improve the near-term predictability of forest mortality, thus providing crucial information for forest and water resource management.

Impact of anthropogenic climate change on wildfire across western US forests

PubMed Central

Williams, A. Park

2016-01-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000–2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984–2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting. PMID:27791053

Climate limits across space and time on European forest structure

NASA Astrophysics Data System (ADS)

Moreno, A. L. S.; Neumann, M.; Hasenauer, H.

2017-12-01

The impact climate has on forests has been extensively studied. However, the large scale effect climate has on forest structures, such as average diameters, heights and basal area are understudied in a spatially explicit manner. The limits, tipping points and thresholds that climate places on forest structures dictate the services a forest may provide, the vulnerability of a forest to mortality and the potential value of the timber there within. The majority of current research either investigates climate impacts on forest pools and fluxes, on a tree physiological scale or on case studies that are used to extrapolate results and potential impacts. A spatially explicit study on how climate affects forest structure over a large region would give valuable information to stakeholders who are more concerned with ecosystem services that cannot be described by pools and fluxes but require spatially explicit information - such as biodiversity, habitat suitability, and market values. In this study, we quantified the limits that climate (maximum, minimum temperature and precipitation) places on 3 forest structures, diameter at breast height, height, and basal area throughout Europe. Our results show clear climatic zones of high and low upper limits for each forest structure variable studied. We also spatially analyzed how climate restricts the potential bio-physical upper limits and creates tipping points of each forest structure variable and which climate factors are most limiting. Further, we demonstrated how the climate change has affected 8 individual forests across Europe and then the continent as a whole. We find that diameter, height and basal area are limited by climate in different ways and that areas may have high upper limits in one structure and low upper limits in another limitted by different climate variables. We also found that even though individual forests may have increased their potential upper limit forest structure values, European forests as a whole have lost, on average, 5.0%, 1.7% and 6.5% in potential mean forest diameter, height and basal area, respectively.

Factors impacting stemflow generation in a European beech forest: Individual tree versus neighborhood properties

NASA Astrophysics Data System (ADS)

Metzger, Johanna Clara; Germer, Sonja; Hildebrandt, Anke

2017-04-01

The redistribution of precipitation by canopies changes the water flow dynamics to the forest floor. The spatial pattern of throughfall has been researched in a number of studies in different ecosystems. Yet, also stemflow substantially influences water input patterns, constituting a mean of 12% of gross precipitation for European beech as one of the most abundant tree species in Central Europe. While the initiation of stemflow depends mostly on precipitation event properties, stemflow amounts are strongly shaped by canopy structure. Stemflow research has mainly addressed the impact of single tree morphological variables. In previous studies, the impact of forest structure on area-based stemflow was studied comparing plots with different properties using few exemplary stemflow measurements. In non-homogeneous stands, this approach might not be accurate, as the variation of stand properties like tree density could change tree individual stemflow fluxes. To investigate this, a total measurement of all trees per plot is required. We hypothesize, that in addition to individual tree metrics, tree neighborhood relations have a significant impact on stemflow generation in a heterogeneous beech forest. Our study site is located in the pristine forest of the National Park Hainich, central Germany. It is heterogeneous in respect to tree density, species composition and tree age. We measured stemflow in an areal approach, for all trees on 11 subplots (each 10 m x 10 m) spaced evenly throughout a 1 ha plot. This involved overall 65 trees, which is 11% of the plot's trees. 27 precipitation events were recorded in spring and early summer of 2015 and 2016. Stand properties were surveyed, including diameter at breast height, height, position and species of a tree. From this data, we calculated neighborhood properties for each tree, as number, basal area, and relative height of neighboring trees within a radius of the plot's mean tree distance. Using linear mixed effects models, we identified the different factors, individual and neighborhood, which significantly explain stemflow amount per tree. Preliminary results show, that the main impact on stemflow in our heterogeneous beech forest is due to individual tree diameter at breast height, while neighborhood factors have a smaller influence. This work defines the most important factors for stemflow fluxes, using easy-to-acquire tree and stand information, which allows the robust extrapolation of stemflow measurements and the generation of a spatially discrete pattern of stemflow input to the soil. Because of the high local and temporal concentration of precipitation, stemflow fluxes could be a key factor in forest soil water dynamics. On the long run, the results shall enable us to directly link soil water content measurements with estimated stemflow volumes for individual trees to trace stemflow fluxes into and through the soil.

Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems

DOE PAGES

Brooks, Scott C.; Brandt, Craig C.; Griffiths, Natalie A.

2016-10-07

Nutrient spiraling is an important ecosystem process characterizing nutrient transport and uptake in streams. Various nutrient addition methods are used to estimate uptake metrics; however, uncertainty in the metrics is not often evaluated. A method was developed to quantify uncertainty in ambient and saturation nutrient uptake metrics estimated from saturating pulse nutrient additions (Tracer Additions for Spiraling Curve Characterization; TASCC). Using a Monte Carlo (MC) approach, the 95% confidence interval (CI) was estimated for ambient uptake lengths (S w-amb) and maximum areal uptake rates (U max) based on 100,000 datasets generated from each of four nitrogen and five phosphorous TASCCmore » experiments conducted seasonally in a forest stream in eastern Tennessee, U.S.A. Uncertainty estimates from the MC approach were compared to the CIs estimated from ordinary least squares (OLS) and non-linear least squares (NLS) models used to calculate S w-amb and U max, respectively, from the TASCC method. The CIs for Sw-amb and Umax were large, but were not consistently larger using the MC method. Despite the large CIs, significant differences (based on nonoverlapping CIs) in nutrient metrics among seasons were found with more significant differences using the OLS/NLS vs. the MC method. Lastly, we suggest that the MC approach is a robust way to estimate uncertainty, as the calculation of S w-amb and U max violates assumptions of OLS/NLS while the MC approach is free of these assumptions. The MC approach can be applied to other ecosystem metrics that are calculated from multiple parameters, providing a more robust estimate of these metrics and their associated uncertainties.« less

Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems

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

Brooks, Scott C.; Brandt, Craig C.; Griffiths, Natalie A.

Nutrient spiraling is an important ecosystem process characterizing nutrient transport and uptake in streams. Various nutrient addition methods are used to estimate uptake metrics; however, uncertainty in the metrics is not often evaluated. A method was developed to quantify uncertainty in ambient and saturation nutrient uptake metrics estimated from saturating pulse nutrient additions (Tracer Additions for Spiraling Curve Characterization; TASCC). Using a Monte Carlo (MC) approach, the 95% confidence interval (CI) was estimated for ambient uptake lengths (S w-amb) and maximum areal uptake rates (U max) based on 100,000 datasets generated from each of four nitrogen and five phosphorous TASCCmore » experiments conducted seasonally in a forest stream in eastern Tennessee, U.S.A. Uncertainty estimates from the MC approach were compared to the CIs estimated from ordinary least squares (OLS) and non-linear least squares (NLS) models used to calculate S w-amb and U max, respectively, from the TASCC method. The CIs for Sw-amb and Umax were large, but were not consistently larger using the MC method. Despite the large CIs, significant differences (based on nonoverlapping CIs) in nutrient metrics among seasons were found with more significant differences using the OLS/NLS vs. the MC method. Lastly, we suggest that the MC approach is a robust way to estimate uncertainty, as the calculation of S w-amb and U max violates assumptions of OLS/NLS while the MC approach is free of these assumptions. The MC approach can be applied to other ecosystem metrics that are calculated from multiple parameters, providing a more robust estimate of these metrics and their associated uncertainties.« less

Dominant forest tree mycorrhizal type mediates understory plant invasions

Treesearch

Insu Jo; Kevin M. Potter; Grant M. Domke; Songlin Fei

2017-01-01

Forest mycorrhizal type mediates nutrient dynamics, which in turn can influence forest community structure and processes. Using forest inventory data, we explored how dominant forest tree mycorrhizal type affects understory plant invasions with consideration of forest structure and soil properties. We found that arbuscular mycorrhizal (AM) dominant forests, which are...

Hearing a Melody in Different Ways: Multistability of Metrical Interpretation, Reflected in Rate Limits of Sensorimotor Synchronization

ERIC Educational Resources Information Center

Repp, Bruno H.

2007-01-01

Music commonly induces the feeling of a regular beat (i.e., a metrical structure) in listeners. However, musicians can also intentionally impose a beat (i.e., a metrical interpretation) on a metrically ambiguous passage. The present study aimed to provide objective evidence for this little-studied mental ability. Participants were prompted with…

Magic bases, metric ansaetze and generalized graph theories in the Virasoro master equation

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

Halpern, M.B.; Obers, N.A.

1991-11-15

The authors define a class of magic Lie group bases in which the Virasoro master equation admits a class of simple metric ansaetze (g{sub metric}), whose structure is visible in the high-level expansion. When a magic basis is real on compact g, the corresponding g{sub metric} is a large system of unitary, generically irrational conformal field theories. Examples in this class include the graph-theory ansatz SO(n){sub diag} in the Cartesian basis of So(n) and the ansatz SU(n){sub metric} in the Pauli-like basis of SU(n). A new phenomenon is observed in the high-level comparison of SU(n){sub metric}: Due to the trigonometricmore » structure constants of the Pauli-like basis, irrational central charge is clearly visible at finite order of the expansion. They also define the sine-area graphs of SU(n), which label the conformal field theories of SU(n){sub metric} and note that, in a similar fashion, each magic basis of g defines a generalize graph theory on g which labels the conformal field theories of g{sub metric}.« less

Shale gas development effects on the songbird community in a central Appalachian forest

USGS Publications Warehouse

Farwell, Laura S.; Wood, Petra; Sheehan, James; George, Gregory A.

2016-01-01

In the last decade, unconventional drilling for natural gas from the Marcellus-Utica shale has increased exponentially in the central Appalachians. This heavily forested region contains important breeding habitat for many neotropical migratory songbirds, including several species of conservation concern. Our goal was to examine effects of unconventional gas development on forest habitat and breeding songbirds at a predominantly forested site from 2008 to 2015. Construction of gas well pads and infrastructure (e.g., roads, pipelines) contributed to an overall 4.5% loss in forest cover at the site, a 12.4% loss in core forest, and a 51.7% increase in forest edge density. We evaluated the relationship between land-cover metrics and species richness within three avian guilds: forest-interior, early-successional, and synanthropic, in addition to abundances of 21 focal species. Land-cover impacts were evaluated at two spatial extents: a point-level within 100-m and 500-m buffers of each avian survey station, and a landscape-level across the study area (4326 ha). Although we observed variability in species-specific responses, we found distinct trends in long-term response among the three avian guilds. Forest-interior guild richness declined at all points across the site and at points impacted within 100 m by shale gas but did not change at unimpacted points. Early-successional and synanthropic guild richness increased at all points and at impacted points. Our results suggest that shale gas development has the potential to fragment regional forests and alter avian communities, and that efforts to minimize new development in core forests will reduce negative impacts to forest dependent species.

Impact of logging and forest conversion to oil palm plantations on soil bacterial communities in Borneo.

PubMed

Lee-Cruz, Larisa; Edwards, David P; Tripathi, Binu M; Adams, Jonathan M

2013-12-01

Tropical forests are being rapidly altered by logging and cleared for agriculture. Understanding the effects of these land use changes on soil bacteria, which constitute a large proportion of total biodiversity and perform important ecosystem functions, is a major conservation frontier. Here we studied the effects of logging history and forest conversion to oil palm plantations in Sabah, Borneo, on the soil bacterial community. We used paired-end Illumina sequencing of the 16S rRNA gene, V3 region, to compare the bacterial communities in primary, once-logged, and twice-logged forest and land converted to oil palm plantations. Bacteria were grouped into operational taxonomic units (OTUs) at the 97% similarity level, and OTU richness and local-scale α-diversity showed no difference between the various forest types and oil palm plantations. Focusing on the turnover of bacteria across space, true β-diversity was higher in oil palm plantation soil than in forest soil, whereas community dissimilarity-based metrics of β-diversity were only marginally different between habitats, suggesting that at large scales, oil palm plantation soil could have higher overall γ-diversity than forest soil, driven by a slightly more heterogeneous community across space. Clearance of primary and logged forest for oil palm plantations did, however, significantly impact the composition of soil bacterial communities, reflecting in part the loss of some forest bacteria, whereas primary and logged forests did not differ in composition. Overall, our results suggest that the soil bacteria of tropical forest are to some extent resilient or resistant to logging but that the impacts of forest conversion to oil palm plantations are more severe.

Influence of Forest-Canopy Morphology and Relief on Spectral Characteristics of Taiga Forests

NASA Astrophysics Data System (ADS)

Zhirin, V. M.; Knyazeva, S. V.; Eydlina, S. P.

2017-12-01

The article deals with the results of a statistical analysis reflecting tendencies (trends) of the relationship between spectral characteristics of taiga forests, indicators of the morphological structure of forest canopy and illumination of the territory. The study was carried out on the example of the model forest territory of the Priangarskiy taiga region of Eastern Siberia (Krasnoyarsk krai) using historical data (forest inventory 1992, Landsat 5 TM 16.06.1989) and the digital elevation model. This article describes a method for determining the quantitative indicator of morphological structure of forest canopy based on taxation data, and the authors propose to subdivide the morphological structure into high complexity, medium complexity, and relatively simple. As a result of the research, dependences of average values of spectral brightness in near and short-wave infrared channels of a Landsat 5 TM image for dark-coniferous, light-coniferous and deciduous forests from the degree of complexity of the forest-canopy structure are received. A high level of variance and maximum brightness average values are marked in green moss (hilocominosa) dark-coniferous and various-grass (larioherbosa) dark-coniferous forests and light-coniferous forests with a complex structure of canopy. The parvifoliate forests are characterized by high values of brightness in stands with a relatively simple structure of the canopy and by a small variance in brightness of any degree of the structure of the canopy complexity. The increase in brightness for the lit slopes in comparison with shaded ones in all stands with a difficult morphological canopy structure is revealed. However, the brightness values of the lit and shaded slopes do not differ for stands with a medium complexity of the structure. It is noted that, in addition to the indicator of the forest-canopy structure, the possible impact on increasing the variance of spectral brightness for the taxation plot has a variability of the slope ratio of "microslopes" inside the forest plot if it exceeds 60%.

Remotely sensed predictors of conifer tree mortality during severe drought

NASA Astrophysics Data System (ADS)

Brodrick, P. G.; Asner, G. P.

2017-11-01

Widespread, drought-induced forest mortality has been documented on every forested continent over the last two decades, yet early pre-mortality indicators of tree death remain poorly understood. Remotely sensed physiological-based measures offer a means for large-scale analysis to understand and predict drought-induced mortality. Here, we use laser-guided imaging spectroscopy from multiple years of aerial surveys to assess the impact of sustained canopy water loss on tree mortality. We analyze both gross canopy mortality in 2016 and the change in mortality between 2015 and 2016 in millions of sampled conifer forest locations throughout the Sierra Nevada mountains in California. On average, sustained water loss and gross mortality are strongly related, and year-to-year water loss within the drought indicates subsequent mortality. Both relationships are consistent after controlling for location and tree community composition, suggesting that these metrics may serve as indicators of mortality during a drought.

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

NASA Astrophysics Data System (ADS)

Huo, L. Z.; Boschetti, L.

2015-12-01

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

Infinitesimal Legendre symmetry in the Geometrothermodynamics programme

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

García-Peláez, D., E-mail: dgarciap@up.edu.mx; Universidad Panamericana, Tecoyotitla 366. Col. Ex Hacienda Guadalupe Chimalistac, 01050 México D.F., México; López-Monsalvo, C. S., E-mail: cesar.slm@correo.nucleares.unam.mx

2014-08-15

The work within the Geometrothermodynamics programme rests upon the metric structure for the thermodynamic phase-space. Such structure exhibits discrete Legendre symmetry. In this work, we study the class of metrics which are invariant along the infinitesimal generators of Legendre transformations. We solve the Legendre-Killing equation for a K-contact general metric. We consider the case with two thermodynamic degrees of freedom, i.e., when the dimension of the thermodynamic phase-space is five. For the generic form of contact metrics, the solution of the Legendre-Killing system is unique, with the sole restriction that the only independent metric function – Ω – should bemore » dragged along the orbits of the Legendre generator. We revisit the ideal gas in the light of this class of metrics. Imposing the vanishing of the scalar curvature for this system results in a further differential equation for the metric function Ω which is not compatible with the Legendre invariance constraint. This result does not allow us to use Quevedo's interpretation of the curvature scalar as a measure of thermodynamic interaction for this particular class.« less

High resolution remote sensing for reducing uncertainties in urban forest carbon offset life cycle assessments.

PubMed

Tigges, Jan; Lakes, Tobia

2017-10-04

Urban forests reduce greenhouse gas emissions by storing and sequestering considerable amounts of carbon. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging for long-term prognoses. Therefore, this review aims to identify uncertainties in urban forest carbon offset assessment and discuss the extent to which such uncertainties can be reduced by recent progress in high resolution remote sensing. We do this by performing an extensive literature review and a case study combining remote sensing and life cycle assessment of urban forest carbon offset in Berlin, Germany. Recent progress in high resolution remote sensing and methods is adequate for delivering more precise details on the urban tree canopy, individual tree metrics, species, and age structures compared to conventional land use/cover class approaches. These area-wide consistent details can update life cycle inventories for more precise future prognoses. Additional improvements in classification accuracy can be achieved by a higher number of features derived from remote sensing data of increasing resolution, but first studies on this subject indicated that a smart selection of features already provides sufficient data that avoids redundancies and enables more efficient data processing. Our case study from Berlin could use remotely sensed individual tree species as consistent inventory of a life cycle assessment. However, a lack of growth, mortality and planting data forced us to make assumptions, therefore creating uncertainty in the long-term prognoses. Regarding temporal changes and reliable long-term estimates, more attention is required to detect changes of gradual growth, pruning and abrupt changes in tree planting and mortality. As such, precise long-term urban ecological monitoring using high resolution remote sensing should be intensified, especially due to increasing climate change effects. This is important for calibrating and validating recent prognoses of urban forest carbon offset, which have so far scarcely addressed longer timeframes. Additionally, higher resolution remote sensing of urban forest carbon estimates can improve upscaling approaches, which should be extended to reach a more precise global estimate for the first time. Urban forest carbon offset can be made more relevant by making more standardized assessments available for science and professional practitioners, and the increasing availability of high resolution remote sensing data and the progress in data processing allows for precisely that.

Quantifying changes in total and pyrogenic carbon stocks across fire severity gradients using active wildfire incidents

NASA Astrophysics Data System (ADS)

Miesel, Jessica; Reiner, Alicia; Ewell, Carol; Maestrini, Bernardo; Dickinson, Matthew

2018-05-01

Positive feedbacks between wildfire emissions and climate are expected to increase in strength in the future; however, fires not only release carbon (C) from terrestrial to atmospheric pools, they also produce pyrogenic C (PyC) which contributes to longer-term C stability. Our objective was to quantify wildfire impacts on total C and PyC stocks in California mixed-conifer forest, and to investigate relationships between C and PyC stocks and changes across gradients of fire severity, using metrics derived from remote sensing and field observations. Our unique study accessed active wildfires to establish and measure plots within days before and after fire, prior to substantial erosion. We measured pre- and post-fire aboveground forest structure and woody fuels to calculate aboveground biomass, C and PyC, and collected forest floor and 0-5 cm mineral soil samples. Tree mortality increased with severity, but overstory C loss was minimal and limited primarily to foliage. Fire released 85% of understory and herbaceous C (comprising <1.0% of total ecosystem C). The greatest C losses occurred from downed wood and forest floor pools (19.3±5.1 Mg ha-1 and 25.9±3.2 Mg ha-1, respectively). Tree bark and downed wood contributed the greatest PyC gains (1.5±0.3 Mg ha-1 and 1.9±0.8 Mg ha-1, respectively), and PyC in tree bark showed non-significant positive trends with increasing severity. Overall PyC losses of 1.9±0.3 Mg ha-1 and 0.5±0.1 Mg ha-1 occurred from forest floor and 0-5 cm mineral soil, with no clear patterns across severity. Fire resulted in a net ecosystem PyC gain (0.96±0.98 Mg ha-1) across aboveground and belowground components of these forests, and there were no differences among severity levels. Carbon emissions represented only 21.6% of total forest C; however, extensive conversion of C from live to dead pools will contribute to large downed wood C pools susceptible to release in a subsequent fire, indicating that there may be a delayed relationship between fire severity and C emissions. This research advances understanding of forest C loss and stabilization as PyC in wildfires; however, poor relationships between C and PyC gains or losses and fire severity highlight the complexity of fire impacts on forest C.

Landscape structure and live fences in Andes Colombian agrosystems: upper basin of the Cane-Iguaque River.

PubMed

Otero, Javier; Onaindia, Miren

2009-12-01

Changes in land use have generated a new landscape configuration in the Andino orobiome (mountain range) of the tropical Andes, resulting in a mosaic of cultivation and pastures interrupted by small fragments of forest and live fences. This has resulted in an ongoing decrease in the biodiversity of this biome. In the upper basin of the Cane-Iguaque River (Villa de Levya-Boyacá, Colombia), located 2,600-3,000 m above the Cordillera Oriental, over three time periods in 1960, 1984, and 2004, we characterized the structure, patterns, and evolution of the overall landscape and of the live fences (used as tools in biodiversity conservation and considered to be desirable alternatives to nonlive fences in farming production systems) within an agricultural landscape. To do this, we interpreted high-resolution satellite images using a landscape ecology approach and applied landscape map metrics. We found that the natural forests have been transformed by pastures and cultivation, and that although live fences cover only a small portion of the total landscape (4.6%), they have an important effect on landscape structure and biodiversity. There has been an increase in live fences, especially between 1960 and 1984, as well as an increase in their density. However, there has been a reduction in the average length of live fences over the periods that we studied. This could be due in part to changes in the types of agricultural products that have been cultivated in recent years, with an increase in potatoes and a decrease in other vegetables, and also by resource extraction of timber and fuel wood. In the studied area, agricultural production was sustained while biodiversity conservation was improved by the use of live fences. Therefore, live fences should be considered not only as part of an agriculturally productive area, but also as an important element of a multi-functional landscape that contributes to the maintenance of biodiversity and provides resources of economic and ecological interest, decreasing the pressure on natural forest. Improving the network of live fences constitutes an important strategy for the sustainable management of the rural landscape of the Andino orobiome of Colombia and similar areas in the tropics.

Use of an integrated flow model to estimate ecologically relevant hydrologic characteristics at stream biomonitoring sites

USGS Publications Warehouse

Kennen, J.G.; Kauffman, L.J.; Ayers, M.A.; Wolock, D.M.; Colarullo, S.J.

2008-01-01

We developed an integrated hydroecological model to provide a comprehensive set of hydrologic variables representing five major components of the flow regime at 856 aquatic-invertebrate monitoring sites in New Jersey. The hydroecological model simulates streamflow by routing water that moves overland and through the subsurface from atmospheric delivery to the watershed outlet. Snow accumulation and melt, evapotranspiration, precipitation, withdrawals, discharges, pervious- and impervious-area runoff, and lake storage were accounted for in the water balance. We generated more than 78 flow variables, which describe the frequency, magnitude, duration, rate of change, and timing of flow events. Highly correlated variables were filtered by principal component analysis to obtain a non-redundant subset of variables that explain the majority of the variation in the complete set. This subset of variables was used to evaluate the effect of changes in the flow regime on aquatic-invertebrate assemblage structure at 856 biomonitoring sites. We used non-metric multidimensional scaling (NMS) to evaluate variation in aquatic-invertebrate assemblage structure across a disturbance gradient. We employed multiple linear regression (MLR) analysis to build a series of MLR models that identify the most important environmental and hydrologic variables driving the differences in the aquatic-invertebrate assemblages across the disturbance gradient. The first axis of NMS ordination was significantly related to many hydrologic, habitat, and land-use/land-cover variables, including the average number of annual storms producing runoff, ratio of 25-75% exceedance flow (flashiness), diversity of natural stream substrate, and the percentage of forested land near the stream channel (forest buffer). Modifications in the hydrologic regime as the result of changes in watershed land use appear to promote the retention of highly tolerant aquatic species; in contrast, species that are sensitive to hydrologic instability and other anthropogenic disturbance become much less prevalent. We also found strong relations between an index of invertebrate-assemblage impairment, its component metrics, and the primary disturbance gradient. The process-oriented watershed modeling approach used in this study provides a means to evaluate how natural landscape features interact with anthropogenic factors and assess their effects on flow characteristics and stream ecology. By combining watershed modeling and indirect ordination techniques, we were able to identify components of the hydrologic regime that have a considerable effect on aquatic-assemblage structure and help in developing short- and long-term management measures that mitigate the effects of anthropogenic disturbance in stream systems.

Bird diversity along a gradient of fragmented habitats of the Cerrado.

PubMed

Jesus, Shayana DE; Pedro, Wagner A; Bispo, Arthur A

2018-01-01

Understanding the factors that affect biodiversity is of central interest to ecology, and essential to species conservation and ecosystems management. We sampled bird communities in 17 forest fragments in the Cerrado biome, the Central-West region of Brazil. We aimed to know the communities structure pattern and the influence of geographical distance and environmental variables on them, along a gradient of fragmented habitats at both local and landscape scales. Eight structural variables of the fragments served as an environmental distance measurement at the local scale while five metrics served as an environmental distance measurement at the landscape scale. Species presence-absence data were used to calculate the dissimilarity index. Beta diversity was calculated using three indices (βsim, βnes and βsor), representing the spatial species turnover, nestedness and total beta diversity, respectively. Spatial species turnover was the predominant pattern in the structure of the communities. Variations in beta diversity were explained only by the environmental variables of the landscape with spatial configuration being more important than the composition. This fact indicates that, in Cerrado of Goiás avian communities structure, deterministic ecological processes associated to differences in species responses to landscape fragmentation are more important than stochastic processes driven by species dispersal.

Mapping growing stock volume and forest live biomass: a case study of the Polissya region of Ukraine

NASA Astrophysics Data System (ADS)

Bilous, Andrii; Myroniuk, Viktor; Holiaka, Dmytrii; Bilous, Svitlana; See, Linda; Schepaschenko, Dmitry

2017-10-01

Forest inventory and biomass mapping are important tasks that require inputs from multiple data sources. In this paper we implement two methods for the Ukrainian region of Polissya: random forest (RF) for tree species prediction and k-nearest neighbors (k-NN) for growing stock volume and biomass mapping. We examined the suitability of the five-band RapidEye satellite image to predict the distribution of six tree species. The accuracy of RF is quite high: ~99% for forest/non-forest mask and 89% for tree species prediction. Our results demonstrate that inclusion of elevation as a predictor variable in the RF model improved the performance of tree species classification. We evaluated different distance metrics for the k-NN method, including Euclidean or Mahalanobis distance, most similar neighbor (MSN), gradient nearest neighbor, and independent component analysis. The MSN with the four nearest neighbors (k = 4) is the most precise (according to the root-mean-square deviation) for predicting forest attributes across the study area. The k-NN method allowed us to estimate growing stock volume with an accuracy of 3 m3 ha-1 and for live biomass of about 2 t ha-1 over the study area.

Correlations between contouring similarity metrics and simulated treatment outcome for prostate radiotherapy

NASA Astrophysics Data System (ADS)

Roach, D.; Jameson, M. G.; Dowling, J. A.; Ebert, M. A.; Greer, P. B.; Kennedy, A. M.; Watt, S.; Holloway, L. C.

2018-02-01

Many similarity metrics exist for inter-observer contouring variation studies, however no correlation between metric choice and prostate cancer radiotherapy dosimetry has been explored. These correlations were investigated in this study. Two separate trials were undertaken, the first a thirty-five patient cohort with three observers, the second a five patient dataset with ten observers. Clinical and planning target volumes (CTV and PTV), rectum, and bladder were independently contoured by all observers in each trial. Structures were contoured on T2-weighted MRI and transferred onto CT following rigid registration for treatment planning in the first trial. Structures were contoured directly on CT in the second trial. STAPLE and majority voting volumes were generated as reference gold standard volumes for each structure for the two trials respectively. VMAT treatment plans (78 Gy to PTV) were simulated for observer and gold standard volumes, and dosimetry assessed using multiple radiobiological metrics. Correlations between contouring similarity metrics and dosimetry were calculated using Spearman’s rank correlation coefficient. No correlations were observed between contouring similarity metrics and dosimetry for CTV within either trial. Volume similarity correlated most strongly with radiobiological metrics for PTV in both trials, including TCPPoisson (ρ  =  0.57, 0.65), TCPLogit (ρ  =  0.39, 0.62), and EUD (ρ  =  0.43, 0.61) for each respective trial. Rectum and bladder metric correlations displayed no consistency for the two trials. PTV volume similarity was found to significantly correlate with rectum normal tissue complication probability (ρ  =  0.33, 0.48). Minimal to no correlations with dosimetry were observed for overlap or boundary contouring metrics. Future inter-observer contouring variation studies for prostate cancer should incorporate volume similarity to provide additional insights into dosimetry during analysis.

Neural processing of musical meter in musicians and non-musicians.

PubMed

Zhao, T Christina; Lam, H T Gloria; Sohi, Harkirat; Kuhl, Patricia K

2017-11-01

Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses indicated that the reduction was driven by responses to sounds that defined the structure (Standard), not by responses to Deviants. We argue that musicians maintain a more accurate and efficient mental model for metrical structures, which incorporates occasional disruptions using significantly fewer neural resources. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tropical secondary forest management influences frugivorous bat composition, abundance and fruit consumption in Chiapas, Mexico.

PubMed

Vleut, Ivar; Levy-Tacher, Samuel Israel; de Boer, Willem Frederik; Galindo-González, Jorge; Vazquez, Luis-Bernardo

2013-01-01

Most studies on frugivorous bat assemblages in secondary forests have concentrated on differences among successional stages, and have disregarded the effect of forest management. Secondary forest management practices alter the vegetation structure and fruit availability, important factors associated with differences in frugivorous bat assemblage structure, and fruit consumption and can therefore modify forest succession. Our objective was to elucidate factors (forest structural variables and fruit availability) determining bat diversity, abundance, composition and species-specific abundance of bats in (i) secondary forests managed by Lacandon farmers dominated by Ochroma pyramidale, in (ii) secondary forests without management, and in (iii) mature rain forests in Chiapas, Southern Mexico. Frugivorous bat species diversity (Shannon H') was similar between forest types. However, bat abundance was highest in rain forest and O. pyramidale forests. Bat species composition was different among forest types with more Carollia sowelli and Sturnira lilium captures in O. pyramidale forests. Overall, bat fruit consumption was dominated by early-successional shrubs, highest late-successional fruit consumption was found in rain forests and more bats consumed early-successional shrub fruits in O. pyramidale forests. Ochroma pyramidale forests presented a higher canopy openness, tree height, lower tree density and diversity of fruit than secondary forests. Tree density and canopy openness were negatively correlated with bat species diversity and bat abundance, but bat abundance increased with fruit abundance and tree height. Hence, secondary forest management alters forests' structural characteristics and resource availability, and shapes the frugivorous bat community structure, and thereby the fruit consumption by bats.

Dominant forest tree mycorrhizal type mediates understory plant invasions

Treesearch

Insu Jo; Kevin M. Potter; Grant M. Domke; Songlin Fei

2018-01-01

Forest mycorrhizal type mediates nutrient dynamics, which in turn can influence forest community structure and processes. Using forest inventory data, we explored how dominant forest tree myc- orrhizal type affects understory plant invasions with consideration of forest structure and soil properties. We found that arbuscular mycorrhizal (AM) dominant forests, which are...

Using LiDAR to Estimate Total Aboveground Biomass of Redwood Stands in the Jackson Demonstration State Forest, Mendocino, California

NASA Astrophysics Data System (ADS)

Rao, M.; Vuong, H.

2013-12-01

The overall objective of this study is to develop a method for estimating total aboveground biomass of redwood stands in Jackson Demonstration State Forest, Mendocino, California using airborne LiDAR data. LiDAR data owing to its vertical and horizontal accuracy are increasingly being used to characterize landscape features including ground surface elevation and canopy height. These LiDAR-derived metrics involving structural signatures at higher precision and accuracy can help better understand ecological processes at various spatial scales. Our study is focused on two major species of the forest: redwood (Sequoia semperirens [D.Don] Engl.) and Douglas-fir (Pseudotsuga mensiezii [Mirb.] Franco). Specifically, the objectives included linear regression models fitting tree diameter at breast height (dbh) to LiDAR derived height for each species. From 23 random points on the study area, field measurement (dbh and tree coordinate) were collected for more than 500 trees of Redwood and Douglas-fir over 0.2 ha- plots. The USFS-FUSION application software along with its LiDAR Data Viewer (LDV) were used to to extract Canopy Height Model (CHM) from which tree heights would be derived. Based on the LiDAR derived height and ground based dbh, a linear regression model was developed to predict dbh. The predicted dbh was used to estimate the biomass at the single tree level using Jenkin's formula (Jenkin et al 2003). The linear regression models were able to explain 65% of the variability associated with Redwood's dbh and 80% of that associated with Douglas-fir's dbh.

Presence and absence of bats across habitat scales in the Upper Coastal Plain of South Carolina.

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

Ford, W.Mark; Menzel, Jennifer M.; Menzel, Michael A.: Edwards, John W.

Abstract During 2001, we used active acoustical sampling (Anabat II) to survey foraging habitat relationships of bats on the Savannah River Site (SRS) in the upper Coastal Plain of South Carolina. Using an a priori information-theoretic approach, we conducted logistic regression analysis to examine presence of individual bat species relative to a suite of microhabitat, stand, and landscape-level features such as forest structural metrics, forest type, proximity to riparian zones and Carolina bay wetlands, insect abundance, and weather. There was considerable empirical support to suggest that the majority of the activity of bats across most of the 6 species occurredmore » at smaller, stand-level habitat scales that combine measures of habitat clutter (e.g., declining forest canopy cover and basal area), proximity to riparian zones, and insect abundance. Accordingly, we hypothesized that most foraging habitat relationships were more local than landscape across this relatively large area for generalist species of bats. The southeastern myotis (Myotis austroriparius) was the partial exception, as its presence was linked to proximity of Carolina bays (best approximating model) and bottomland hardwood communities (other models with empirical support). Efforts at SRS to promote open longleaf pine (Pinus palustris) and loblolly pine (P. taeda) savanna conditions and to actively restore degraded Carolina bay wetlands will be beneficial to bats. Accordingly, our results should provide managers better insight for crafting guidelines for bat habitat conservation that could be linked to widely accepted land management and environmental restoration practices for the region.« less

The relationship between the understory shrub component of coastal forests and the conservation of forest carnivores

Treesearch

Keith M. Slauson; William J. Zielinski

2007-01-01

The physical structure of vegetation is an important predictor of habitat for wildlife species. The coastal forests of the Redwood region are highly productive, supporting structurally-diverse forest habitats. The major elements of structural diversity in these forests include trees, shrubs, and herbaceous plants, which together create three-dimensional complexity. In...

Globalization and structural change in the U.S. forest sector: an evolving context for sustainable forest management

Treesearch

Peter Ince; Albert Schuler; Henry Spelter; William Luppold

2007-01-01

This report examines economic implications for sustainable forest management of globalization and related structural changes in the forest sector of the United States. Globalization has accelerated structural change in the U.S. forest sector, favored survival of larger and more capital-intensive enterprises, and altered historical patterns of resource use.

Properties of C-metric spaces

NASA Astrophysics Data System (ADS)

Croitoru, Anca; Apreutesei, Gabriela; Mastorakis, Nikos E.

2017-09-01

The subject of this paper belongs to the theory of approximate metrics [23]. An approximate metric on X is a real application defined on X × X that satisfies only a part of the metric axioms. In a recent paper [23], we introduced a new type of approximate metric, named C-metric, that is an application which satisfies only two metric axioms: symmetry and triangular inequality. The remarkable fact in a C-metric space is that a topological structure induced by the C-metric can be defined. The innovative idea of this paper is that we obtain some convergence properties of a C-metric space in the absence of a metric. In this paper we investigate C-metric spaces. The paper is divided into four sections. Section 1 is for Introduction. In Section 2 we recall some concepts and preliminary results. In Section 3 we present some properties of C-metric spaces, such as convergence properties, a canonical decomposition and a C-fixed point theorem. Finally, in Section 4 some conclusions are highlighted.

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

A spatio-temporal analysis of forest loss related to cocaine trafficking in Central America

NASA Astrophysics Data System (ADS)

Sesnie, Steven E.; Tellman, Beth; Wrathall, David; McSweeney, Kendra; Nielsen, Erik; Benessaiah, Karina; Wang, Ophelia; Rey, Luis

2017-05-01

A growing body of evidence suggests that criminal activities associated with drug trafficking networks are a progressively important driver of forest loss in Central America. However, the scale at which drug trafficking represents a driver of forest loss is not presently known. We estimated the degree to which narcotics trafficking may contribute to forest loss using an unsupervised spatial clustering of 15 spatial and temporal forest loss patch metrics developed from global forest change data. We distinguished anomalous forest loss from background loss patches for each country exhibiting potential ‘narco-capitalized’ signatures which showed a statistically significant dissimilarity from other patches in terms of size, timing, and rate of forest loss. We also compared annual anomalous forest loss with the number of cocaine shipments and volume of cocaine seized, lost, or delivered at country- and department-level. For Honduras, results from linear mixed effects models showed a highly significant relationship between anomalous forest loss and the timing of increased drug trafficking (F = 9.90, p = 0.009) that also differed significantly from temporal patterns of background forest loss (t-ratio = 2.98, p = 0.004). Other locations of high forest loss in Central America showed mixed results. The timing of increased trafficking was not significantly related to anomalous forest loss in Guatemala and Nicaragua, but significantly differed in patch size compared to background losses. We estimated that cocaine trafficking could account for between 15% and 30% of annual national forest loss in these three countries over the past decade, and 30% to 60% of loss occurred within nationally and internationally designated protected areas. Cocaine trafficking is likely to have severe and lasting consequences in terms of maintaining moist tropical forest cover in Central America. Addressing forest loss in these and other tropical locations will require a stronger linkage between national and international drug interdiction and conservation policies.

Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA

Treesearch

Thomas A. Spies; Eric White; Alan Ager; Jeffrey D. Kline; John P. Bolte; Emily K. Platt; Keith A. Olsen; Robert J. Pabst; Ana M. G. Barros; John D. Bailey; Susan Charnley; Anita T. Morzillo; Jennifer Koch; Michelle M. Steen-Adams; Peter H. Singleton; James Sulzman; Cynthia Schwartz; Blair Csuti

2017-01-01

Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern...

Effects of forest fires on visibility and air quality

Treesearch

Douglas G. Fox; Allen R. Riebau

2009-01-01

The U.S. Clean Air Act establishes the goal of preventing future and remedying existing visibility impairment in 156 Class I areas (national parks, wilderness areas, and wildlife refuges). A key element in implementing this goal is the Regional Haze Regulation (RHR). RHR is based on relating impaired visibility, using metrics of extinction (inverse megameters and/or ‘‘...

Nationwide disturbance attribution on NASA’s earth exchange: experiences in a high-end computing environment

Treesearch

J. Chris Toney; Karen G. Schleeweis; Jennifer Dungan; Andrew Michaelis; Todd Schroeder; Gretchen G. Moisen

2015-01-01

The North American Forest Dynamics (NAFD) project’s Attribution Team is completing nationwide processing of historic Landsat data to provide a comprehensive annual, wall-to-wall analysis of US disturbance history, with attribution, over the last 25+ years. Per-pixel time series analysis based on a new nonparametric curve fitting algorithm yields several metrics useful...

Ethanol production from SPORL-pretreated lodgepole pine : preliminary evaluation of mass balance and process energy efficiency

Treesearch

Junyong Zhu; Wenyuan Zhu; Patricia OBryan; Bruce S. Dien; Shen Tian; Roland Gleisner; X.J. Pan

2010-01-01

Lodgepole pine from forest thinnings is a potential feedstock for ethanol production. In this study, lodgepole pine was converted to ethanol with a yield of 276 L per metric ton of wood or 72% of theoretical yield. The lodgepole pine chips were directly subjected to sulfite pretreatment to overcome recalcitrance of lignocellulose (SPORL) pretreatment and then disk-...