Knowing if a forest disturbance is caused by timber harvest or a natural event is crucial for carbon cycle assessments, econometric analyses of timber harvesting, and other research questions. However, while remote sensing of forest disturbance in general is very well developed, discerning between different types of forest disturbances remains challenging. In this work, we developed an algorithm to separate windfall disturbance from clear-cut harvesting using Landsat data. The method first extracts training data primarily based on Tasseled Cap transformed bands and histogram thresholds with minimal user input. We then used a support-vector machine classifier to separate disturbed areas into 'windfall' and 'clear-cut harvests'.Wetested our algorithmin the temperate forest zone of European Russia and the southern boreal forest zone of the United States. The forest-cover change classifications were highly accurate (~90%) and windfall classification accuracies were greater than 75% in both study areas. Accuracieswere generally higher for larger disturbance patches. At the Russia study site about 60% of all disturbances were caused by windfall, versus 40% at the U.S. study site. Given the similar levels of accuracy in both locations and the ease of application, the algorithm has the potential to fill a research gap in mapping wind disturbance using Landsat data in both temperate and boreal forests that are subject to frequent wind events.
File: Baumann_etal_2014_RSE.pdf
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Old-growth forests around the world are vanishing rapidly and have been lost almost completely from the European temperate forest region. Poor management practices, often triggered by socioeconomic and institutional change, are the main causes of loss. Recent trends in old-growth forest cover in Romania, where some of the last remaining tracts of these forests within Europe are located, are revealed by satellite image analysis. Forest cover declined by 1.3 % from 2000 to 2010. Romania's protected area network has been expanded substantially since the country's accession to the European Union in 2007, and most of the remaining old-growth forests now are located within protected areas. Surprisingly though, 72% of the old-growth forest disturbances are found within protected areas, highlighting the threats still facing these forests. It appears that logging in old-growth forests is, at least in part, related to institutional reforms, insuf?cient protection and ownership changes since the collapse of communism in 1989. The majority of harvesting activities in old-growth forest areas are in accordance with the law. Without improvements to their governance, the future of Romania's old-growth forests and the important
File: Knorn_EnvCons_2013_0.pdf
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The breakdown of socialismcausedmassive socio-economic and institutional changes thatled to substantial agricultural land abandonment. The goal of our study was to identify the determinants of agricultural land abandonment in post-Soviet Russia during the ?rst decade of transition from a state-controlled economy to a market-driven economy (1990-2000). We analyzed the determinants of agricultural land abandonment for approximately 150,550 km2 of land area in the provinces (oblasts) of Kaluga, Rjazan, Smolensk, Tula and Vladimir in European Russia. Based on the economic assumptions of pro?t maximization, we integrated maps of abandoned agricultural land from ?ve ?185 kmx 185 km Landsat TM/ETM+ footprints with socio-economic, environmental and geographic variables, and we estimated logistic regressions at the pixel level to identify the determinants of agricultural land abandonment. Our results showed that a higher likelihood of agricultural land abandonment was signi?cantly associated with lower average grain yields in the late 1980s and with higher distances from the nearest settlements, municipality centers, and settlements withmore than 500 citizens. Hierarchical partitioning showed that the average grain yields in the late 1980s had the greatest power to explain agricultural land abandonment in our models, followed by the locational attributes of the agricultural land. We hypothesize that the termination of 90% of state subsidies for agriculture from 1990 to 2000 was an important underlying cause for the decrease of cultivation in economically and environmentally marginal agriculture areas. Thus, whereas the spatial patterns corresponded to the land rent theory of von Thuenen, it was primarily the macro-scale driving forces that fostered agricultural abandonment. Our study highlighted the value of spatially explicit statistical models for studying the determinants of land-use and land-cover change in large areas.
File: Prishchepov2.pdf
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Land-use and land-cover change (LULCC) is the main cause of the global biodiversity crisis and protected areas are critical to prevent habitat loss. Rapid changes in institutional and socio-economic conditions, such as the collapse of the former Soviet Union in 1991, often trigger widespread LULCC. Yet, it is unclear how effective protected areas are in safeguarding habitat within them during such periods of rapid LULCC. Our goal here was to map changes in forest cover and agricultural lands from 1984 to 2010 in order to assess the effectiveness of two strictly protected areas, Oksky and Mordovsky State Nature Reserves, in temperate European Russia. We analyzed dense time series of Landsat images for three Landsat footprints and applied a support vector machine classification and trajectory-based change detection to map forest disturbance. We then used matching statistics to quantify the effectiveness of the protected areas. Our analyses highlighted considerable post-Soviet LULCC in European Russia. The LULCC maps revealed disturbances on 5.02% of the total forest area, with strongly declining disturbance rates in post-Soviet times. We also found that 39.89% of the agricultural land used in 1988 was abandoned after 1991, leading to widespread forest regrowth. Oksky and Mordovsky State Nature Reserves had a significantly lower probability of forest disturbance (? 0.1 to ? 3.5% lower) in comparison to their surrounding areas. This suggests that protected areas were relatively effective in limiting human-induced forest disturbance in European Russia, despite lower levels of control and an eroding infrastructure for nature protection. Moreover, we found drastic land-cover changes, particularly forest regrowth, in the surroundings of these protected areas, highlighting conservation opportunities. Protected areas can play a key role in biodiversity conservation during periods of rapid LULCC, and remote sensing coupled with matching statistics provide important tools for monitoring the success and failure of conservation efforts.
File: Sieber_etal_2013_RSE.pdf
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For decades, ecologists have measured habitat attributes in the field to understand and predict patterns of animal distribution and abundance. However, the scale of inference possible from field measured data is typically limited because large-scale data collection is rarely feasible. This is problematic given that conservation and management typical require data that are fine grained yet broad in extent. Recent advances in remote sensing methodology offer alternative tools for efficiently characterizing wildlife habitat across broad areas. We explored the use of remotely sensed image texture, which is a surrogate for vegetation structure, calculated from both an air photo and from a Landsat TM satellite image, compared with field-measured vegetation structure, characterized by foliage-height diversity and horizontal vegetation structure, to predict avian density and species richness within grassland, savanna, and woodland habitats at Fort McCoy Military Installation, Wisconsin, USA. Image texture calculated from the air photo best predicted density of a grassland associated species, grasshopper sparrow (Ammodramus savannarum), within grassland habitat (R2 = 0.52, p-value ,0.001), and avian species richness among habitats (R2 = 0.54, p-value ,0.001). Density of field sparrow (Spizella pusilla), a savanna associated species, was not particularly well captured by either field-measured or remotely sensed vegetation structure variables, but was best predicted by air photo image texture (R2 = 0.13, p-value = 0.002). Density of ovenbird (Seiurus aurocapillus), a woodland associated species, was best predicted by pixel-level satellite data (mean NDVI, R2 = 0.54, p-value ,0.001). Surprisingly and interestingly, remotely sensed vegetation structure measures (i.e., image texture) were often better predictors of avian density and species richness than field-measured vegetation structure, and thus show promise as a valuable tool for mapping habitat quality and characterizing biodiversity across broad areas.
File: Wood-2013-PLOS-One.pdf
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Identifying and protecting ''keystone structures'' is essential to maintain biodiversity in an increasingly human-dominated world. Sacred forests, i.e. natural areas protected by local people for cultural or religious regions, may be keystone structures for forest birds in the Greater Himalayas, but there is limited understanding of their use by bird communities. We surveyed birds and their habitat in and adjacent to six Tibetan sacred forests in northwest Yunnan China, a biodiversity hotspot. Our goal was to understand the ecological and conservation role of these remnant forest patches for forest birds. We found that sacred forests supported a different bird community than the surrounding matrix, and had higher bird species richness at plot, patch, and landscape scales. While we encountered a homogeneous matrix bird community outside the scared forests, the sacred forests themselves exhibited high heterogeneity, and supported at least two distinct bird communities. While bird community composition was primarily driven by the vegetation vertical structure, plots with the largest-diameter trees and native bamboo groves had the highest bird diversity, indicating that protecting forest ecosystems with old-growth characteristics is important for Himalayan forest birds. Finally, we found an increased bird use of the sacred forests and their edges during 2010, a severe drought year in Yunnan, indicating that sacred forests may serve as refuges during extreme weather years. Our results strongly indicate that sacred forests represent an important opportunity for Himalayan bird conservation because they protect a variety of habitat niches and increase bird diversity at multiple spatial scales.
File: Brandt-etal-BioCons-2013.pdf
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Worldwide, changing climates and land use practices are escalating woody-plants encroachment into grasslands, reducing biodiversity and altering ecosystem functions. The loss of alpine grasslands is a major conservation concern as they harbor many rare and endemic species. Alpine meadows in Northwest Yunnan, China, represent a global biodiversity hotspot with high species richness, beta diversity, and endemism. Shrubs have expanded greatly in the region and threaten alpine meadow biodiversity. To measure rates of meadow loss due to shrub encroachment and identify its mechanisms, we reconstructed alpine land cover, climate, and land use change from 1950 to 2009 across Northwest Yunnan using satellite data, ground surveys, and interviews. Between 1990 and 2009, at least 39% of the alpine meadows converted to woody shrubs. The patterns of change suggest that a regime shift is occurring. Despite multiple perturbations to the climate and land use systems starting in the 1950s, alpine meadows remained resilient to shrub expansion until the late 1980s. Shrublands rapidly expanded then due to feedback mechanisms involving climate, woody cover, and grazing. Fire may no longer be an effective tool for controlling shrub expansion. This regime shift threatens both endemic meadow biodiversity and local livelihoods. More generally, these trends serve as a warning sign for the greater Himalayan region where similar vegetation changes could greatly affect livelihoods, hydrology, and climate.
File: Brandt-et-al-BiolCons2013.pdf
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With limited resources for habitat conservation, the accurate identification of high-value avian habitat is crucial. Habitat structure affects avian biodiversity but is difficult to quantify over broad extents. Our goal was to identify which measures of vertical and horizontal habitat structure are most strongly related to patterns of avian biodiversity across the conterminous United States and to determine whether new measures of vertical structure are complementary to existing, primarily horizontal, measures. For 2,546 North American Breeding Bird Survey routes across the conterminous United States, we calculated canopy height and biomass from the National Biomass and Carbon Dataset (NBCD) as measures of vertical habitat structure and used land-cover composition and configuration metrics from the 2001 National Land Cover Database (NLCD) as measures of horizontal habitat structure. Avian species richness was calculated for each route for all birds and three habitat guilds. Avian species richness was significantly related to measures derived from both the NBCD and NLCD. The combination of horizontal and vertical habitat structure measures was most powerful, yielding high R2 values for nationwide models of forest (0.70) and grassland (0.48) bird species richness. New measures of vertical structure proved complementary to measures of horizontal structure. These data allow the efficient quantification of habitat structure over broad scales, thus informing better land management and bird conservation. Received 10 January 2013, accepted 30 September 2013.
File: culbert-etal-Auk-2013.pdf
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The demand for agricultural products continues to grow rapidly, but further agricultural expansion entails substantial environmental costs, making recultivating currently unused farmland an interesting alternative. The collapse of the Soviet Union in 1991 led to widespread abandonment of agricultural lands, but the extent and spatial patterns of abandonment are unclear. We quantified the extent of abandoned farmland, both croplands and pastures, across the region using MODIS NDVI satellite image time series from 2004-2006 and Support Vector Machines classifications. Abandoned farmland was widespread, totaling 52.5 million hectares, particularly in temperate European Russia (32 mill ha), Northern and Western Ukraine, and Belarus. Differences in abandonment rates among countries were striking, suggesting that institutional and socio-economic factors were more important in determining the amount of abandonment than biophysical conditions. Indeed, much abandoned farmland occurred in areas without major constraints for agriculture. Our map provides a basis for assessing the potential of Central and Eastern Europe's abandoned agricultural lands to contributing to food or bioenergy production, or carbon storage, as well as the environmental trade-offs and social constraints of recultivation.
File: alcantara-etal-ERL-2013_0.pdf
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Ecologists commonly collect data on vegetation structure, which is an important attribute for characterizing habitat. However, measuring vegetation structure across large areas is logistically dif?cult. Our goal was to evaluate the degree to which sample-point pixel values and image texture of remotely sensed data are asso- ciated with vegetation structure in a North American grassland-savanna-woodland mosaic. In the summers of 2008-2009 we collected vegetation structure measurements at 193 sample points from which we calculat- ed foliage-height diversity and horizontal vegetation structure at Fort McCoy Military Installation, Wisconsin, USA. We also calculated sample-point pixel values and ?rst- and second-order image texture measures, from two remotely sensed data sources: an infrared air photo (1-m resolution) and a Landsat TM satellite image (30-m resolution). We regressed foliage-height diversity against, and correlated horizontal vegetation struc- ture with, sample-point pixel values and texture measures within and among habitats. Within grasslands, sa- vanna, and woodland habitats, sample-point pixel values and image texture measures explained 26-60% of foliage-height diversity. Similarly, within habitats, sample-point pixel values and image texture measures were correlated with 40-70% of the variation of horizontal vegetation structure. Among habitats, the mean of the texture measure 'second-order contrast' from the air photo explained 79% of the variation in foliage- height diversity while '?rst-order variance' from the air photo was correlated with 73% of horizontal vegeta- tion structure. Our results suggest that sample-point pixel values and image texture measures calculated from remotely sensed data capture components of foliage-height diversity and horizontal vegetation struc- ture within and among grassland, savanna, and woodland habitats. Vegetation structure, which is a key com- ponent of animal habitat, can thus be mapped using remotely sensed data.
File: Wood2012Imagetexturemanuscript121516.pdf
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