Thirty years of vegetation change in the coastal Santa Cruz Mountains of Northern California detected using landsat satellite image analysis

The Santa Cruz Mountains is a coastal landscape with a history of extensive forest logging, and a future with projected climate warming that may alter vegetation cover and surface water runoff in new ways. Results from Landsat satellite image time-series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90 % of the (predominantly second-growth) evergreen forest locations sampled. The cumulative distribution of NDVI values in 2013 was significantly different and higher overall from the cumulative distribution of NDVI values in 1983. The extreme drought year of 2013 (and other previous years of low precipitation) did not affect average NDVI growth rates in most drainage basins of the study area, with the exception of four relatively small basins that had less than 30 % forested land cover. Notably different patterns of NDVI change were detected in areas burned by wildfires in recent years. Within the perimeters of the 2008 Summit Fire and the 2009 Lockheed Fire, NDVI showed notable declines from pre-fire levels to those calculated in 2013 Landsat imagery. In contrast to these recent fires, the burned area from the 1985 Lexington Fire showed the highest rate of NDVI increase (over 27 years of regrowth) of any relatively large contiguous area within the Santa Cruz Mountains.     

基于遥感的泾河流域植被覆盖格局分析

以MODIS遥感影像数据为数据源,应用遥感和GIS技术对泾河流域植被覆盖格局进行分析。结果表明:(1)泾河流域植被覆盖类型以退化草地和草地为主,二者占流域总面积的53.30%;地面覆盖程度较高的森林、疏林仅占流域总面积的9.83%,流域植被覆盖程度较低。(2)受自然环境条件和人类活动的影响,退化草地、稀疏灌丛、郁闭灌丛和疏林破碎化程度较为严重,对地面覆盖程度最低的退化草地除集中分布于流域北部外,主要零散分布于流域中、南部,其斑块形状复杂多样,数量最多,应成为流域植被恢复的重点。(3)各植被覆盖类型的斑快数量组成以小斑块所占比例最大,最小斑块比率均在50.0%以上;森林的斑块面积多样性最大,草地的斑块面积多样性最小。     

1980—2015年青藏高原植被变化研究

青藏高原地形复杂,气候类型独特,是北半球气候变化的调节器。全球气候变化直接影响植被变化,探讨植被变化对了解青藏高原的环境状况及环境保护与恢复具有重要意义。选取青藏高原作为研究区域,基于1980年和2015年的1 km土地利用数据利用转移矩阵研究植被的转换变化,利用1981—2015年的GIMMS-NDVI数据借助趋势分析法分析土地利用未变化区域的植被覆被变化,并通过相关分析法研究植被变化与气候因子的关系。研究表明:1980—2015年,青藏高原植被的转换变化表现为转入面积大于转出面积,植被面积整体增加。植被类型变化的主要表现形式为农作物和草地面积增加,乔木林地和灌木林面积减少;草地的面积变化最大,农作物、乔木林地和灌木林面积变化很小。从不同植被类型和生态分区来看,植被覆被变化表现为农作物面积较小,分布于半干旱地区,NDVI呈上升趋势;乔木林地位于东南部湿润半湿润地区,生长状况呈现退化趋势;灌木林位于东部边缘和东南部的湿润半湿润和半干旱地区,呈退化趋势;草地分布范围最大,生长情况趋于改善。近35年来,青藏高原的植被覆盖整体趋于好转,低覆盖度、干旱半干旱地区趋于改善,高覆盖度、湿润半湿润地区出现退化。研究时段内,青藏高原趋于暖湿化,NDVI变化与年平均气温、年降水量变化呈正相关,对降水变化更为敏感。不同植被类型对气候变化响应不同,农作物相关系数最高。乔木林地与气温和降水变化呈负相关,农作物和草地则呈正相关,灌木林与降水变化呈正相关,与气温变化呈负相关。     

Modis reflectance and active fire data for burn mapping and assessment at regional level

This paper presents an algorithm for rapid and accurate burn mapping that is applied here to the forest fires occurred in Galicia (northwest Spain) in August 2006, when nearly 930 km² were almost entirely burned over the course of eight days. The algorithm synergistically combines remotely-sensed reflectance and active fire data as measured by the MODIS (MODerate resolution Imaging Spectrometer) sensor on board Terra and Aqua NASA (National Aeronautics and Space Administration) satellites. Burned area data collected from this work was compared to official fires statistics from the Spanish Ministry of Environment and to perimeters that were derived using a high spatial resolution satellite image. In a later step, burn patches area analyzed using information from the National Forest Map (1:50,000) and some Geographical Information Systems (GIS) tools.     

Temporal variability of forest fires in eastern Amazonia

Widespread occurrence of fires in Amazonian forests is known to be associated with extreme droughts, but historical data on the location and extent of forest fires are fundamental to determining the degree to which climate conditions and droughts have affected fire occurrence in the region. We used remote sensing to derive a 23-year time series of annual landscape-level burn scars in a fragmented forest of the eastern Amazon. Our burn scar data set is based on a new routine developed for the Carnegie Landsat Analysis System (CLAS), called CLAS-BURN, to calculate a physically based burn scar index (BSI) with an overall accuracy of 93% (Kappa coefficient 0.84). This index uses sub-pixel cover fractions of photosynthetic vegetation, non-photosynthetic vegetation, and shade/burn scar spectral end members. From 23 consecutive Landsat images processed with the CLAS-BURN algorithm, we quantified fire frequencies, the variation in fire return intervals, and rates of conversion of burned forest to other land uses in a 32 400 km2 area. From 1983 to 2007, 15% of the forest burned; 38% of these burned forests were subsequently deforested, representing 19% of the area cleared during the period of observation. While 72% of the fire-affected forest burned only once during the 23-year study period, 20% burned twice, 6% burned three times, and 2% burned four or more times, with the maximum of seven times. These frequencies suggest that the current fire return interval is 5-11 times more frequent than the estimated natural fire regime. Our results also quantify the substantial influence of climate and extreme droughts caused by a strong El Ni?o Southern Oscillation (ENSO) on the extent and likelihood of returning forest fires mainly in fragmented landscapes. These results are an important indication of the role of future warmer climate and deforestation in enhancing emissions from more frequently burned forests in the Amazon.     

Ten years of land cover change on the California coast detected using landsat satellite image analysis: part 1—Marin and San Francisco counties

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

Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data

Obtaining quantitative information about the recovery of fire-affected ecosystems is of utmost importance from the management and decision-making point of view. Nowadays the concern about natural environment protection and recovery is much greater than in the past. However, the resources and tools available for its management are still not sufficient. Thus, attention and precision is needed when decisions must be taken. Quantitative estimates on how the vegetation is recovering after a fire can be of help for evaluating the necessity of human intervention on the fire-affected ecosystem, and their importance will grow as the problem of forest fires, climate change and desertification increases.This article performs a comparison of methods to extract quantitative estimates of vegetation cover regrowth with Landsat TM and ETM+ data in an area that burned during the summer of 1998 in the Liguria region (Italy). In order to eliminate possible sources of error, a thorough pre-processing was carried out, including a careful geometric correction (reaching RMSE lower than 0.3 pixels), a topographic correction by means of a constrained Minnaert model and a combination of absolute and relative atmospheric correction methods. Pseudo Invariant Features (PIF) were identified by implementing an automated selection method based in temporal Principal Component Analysis (PCA), which has been called multi-Temporal n-Dimensional Principal Component Analysis (mT-nD-PCA).Spectral Mixture Analysis (SMA) was compared against quantitative vegetation indices which are based on well known traditional vegetation indices like Normalized Difference Vegetation Index (NDVI) and Modified Soil Adjusted Vegetation Index (MSAVI). Accuracy assessment was performed by regressing vegetation cover results obtained with each method against field data gathered during the fieldwork campaign carried out in the study area. Results obtained showed how vegetation cover fractions extracted from the NDVI based quantitative index were the most accurate, being superior to the rest of the techniques applied, including SMA.     

Inconsistent definitions of "urban" result in different conclusions about the size of urban carbon and nitrogen stocks

There is conflicting evidence about the importance of urban soils and vegetation in regional C budgets that is caused, in part, by inconsistent definitions of "urban" land use. We quantified urban ecosystem contributions to C stocks in the Boston (Massachusetts, USA) Metropolitan Statistical Area (MSA) using several alternative urban definitions. Development altered aboveground and belowground C and N stocks, and the sign and magnitude of these changes varied by land use and development intensity. Aboveground biomass (live trees, dbh > or = 5 cm) for the MSA was 7.2 +/- 0.4 kg C/m2 (mean +/- SE), reflecting a high proportion of forest cover. Vegetation C was highest in forest (11.6 +/- 0.5 kg C/m2), followed by residential (4.6 +/- 0.5 kg C/m2), and then other developed (2.0 +/- 0.4 kg C/m2) land uses. Soil C (0-10 cm depth) followed the same pattern of decreasing C concentration from forest, to residential, to other developed land uses (4.1 +/- 0.1, 4.0 +/- 0.2, and 3.3 +/- 0.2 kg C/m2, respectively). Within a land use type, urban areas (which we defined as > 25% impervious surface area [ISA] within a 1-km(2) moving window) generally contained less vegetation C, but slightly more soil C, than nonurban areas. Soil N concentrations were higher in urban areas than nonurban areas of the same land use type, except for residential areas, which had similarly high soil N concentrations. When we compared our definition of urban to other commonly used urban extents (U.S. Census Bureau, Global Rural-Urban Mapping Project [GRUMP], and the MSA itself), we found that urban soil (1 m depth) and vegetation C stocks spanned a wide range, from 14.4 +/- 0.8 to 54.5 +/- 3.4 Tg C and from 4.2 +/- 0.4 to 27.3 +/- 3.2 Tg C, respectively. Conclusions about the importance of urban soils and vegetation to regional C and N stocks are very sensitive to the definition of urban used by the investigators. Urban areas, regardless of definition, are rapidly expanding in their extent; a systematic understanding of how our development patterns influence ecosystems is necessary to inform future development choices.     

南疆西部不同植被类型NDVI对风沙灾害的响应

不同植被类型对风沙灾害的响应研究有助于风沙灾害的遥感监测评估和防灾减灾工作。采用传统统计学和空间自相关方法,利用MODIS的每日反射率和土地类型产品,分析了风沙灾害后南疆西部不同植被类型NDVI的变化规律及其空间分布特征。结果表明：风沙灾害后,研究区不同植被类型NDVI的差异在增大,NDVI变化值在一0．3865~0．4148之间,NDVI减小的面积占整个研究区面积的54．98％,变异系数增大值在2．44％～36．75％之间;受到风沙灾害的影响,研究区植被NDVI全局Moran’SI系数从0．7982减小到0．6786,但在空间上仍存在显著的正相关性,具有显著的空间集聚特征;由NDVI差值的局部空间自相关指标集聚图以及不同植被类型NDVI差值的空间关联区域面积百分比,可以发现落叶针叶林和裸地或低植被覆盖地受风沙灾害的影响较小,郁闭灌丛和作物受风沙灾害的影响较大。上述关于风沙灾害后南疆西部不同植被类型的变化及其空间格局的研究结果,不仅证明了防护林的风沙阻挡作用,也可以为风沙灾害的防治工作提供参考依据。     

Human influence on California fire regimes.

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.     

基于MODIS时序数据北回归线(云南段)地区植被物候时空变化及其对气候响应分析

植被物候作为自然界规律性、周期性事件,对开展全球气候变化、植被长势观测等研究具有重要价值。以北回归线(云南段)穿过的县域为研究区,基于长时间序列MODIS EVI(Enhanced Vegetation Index,EVI)、土地利用类型和气候因子数据,采用S-G滤波、动态阈值、相关分析等方法分析19 a(2001—2019年)间植被物候的时空分布特征及其对水热因子的响应。结果表明,(1)海拔和地势起伏在物候地域分异中作用显著,植被物候存在明显的垂直地带性分布特征。山地与河谷、坝子、低海拔区的物候值差异较大,山地地区的植被生长季开始期(Start of Season,SOS)在192—240 d,生长季结束期(End of Season,EOS)在次年144—192 d,生长季长度(Length of Season,LOS)为272—304 d;河谷、坝子、东部低海拔地区的植被SOS在80—112 d,EOS在337至次年17 d,LOS在224—256 d。(2)19 a间植被物候年际变化总体特征为SOS显著提前(R²=0.51,P=0.001<0.05),平均提前1.14 d·(10 a)^?1;EOS推迟(R²=0.01,P=0.756>0.05),平均推迟0.07 d·(10 a)^?1;LOS显著延长(R²=0.47,P=0.001<0.05),平均延长1.07 d·(10 a)^?1。(3)不同植被类型的物候期及其变化趋势不同,研究区森林植被生长期最长,草地次之,耕地最短;19 a间SOS、EOS、LOS变化最大的分别是常绿阔叶林(?1.68 d·(10 a)^?1)、耕地(1.25 d·(10 a)^?1)、木本热带稀树草原(1.28 d·(10 a)^?1)。(4)水热组合对植被生长影响显著,河谷、坝子、东部低海拔地区的植被SOS、EOS分别主要受2月降水(负相关)和4月气温(正相关)、9月降水和气温(正相关)影响,山地地区植被SOS、EOS分别主要受6月降水(正相关)和5月气温(正相关)、5月降水(正相关)和4月气温(正相关)影响。     

广东省NDVI时空变化特征及其对气候因子的响应

广东省植被类型丰富、气候条件复杂,开展气候因子对植被的影响研究,对于全省保护生态环境、应对气候变化具有重要意义。利用MODIS NDVI数据和地面气象观测数据,基于变化趋势分析、空间自相关分析、相关性分析等方法,研究广东省NDVI时空分布特征及其对气温、降水、日照时数等气候因子的响应。结果表明,2000—2018年广东省NDVI平均值为0.62,总体呈上升趋势,平均年增长值为0.005 3,正增长区面积占比达94.50%。全省73.72%的区域植被呈现显著空间集聚性,其中高值集聚区面积占比48.19%,低值集聚区面积占比25.53%。不同类型植被的NDVI均呈增加趋势,其中常绿阔叶林、常绿针叶林、混交林的NDVI平均值最大,而农田、矮树灌木、混交林平均年增长值最大。NDVI具有明显的季节变化规律,夏季NDVI值最大、年增长值最小,冬季NDVI值最小、年增长值最大。年内NDVI最低值出现在2月,最高值出现在9月。月平均NDVI与气温、降水、日照时数相关性显著,其最大相关系数分别为0.863 7、0.639 4、0.605 7。NDVI对日照时数的响应不存在滞后,对气温存在1个月的滞后,对降水存在1—2个月的滞后。日照时数对NDVI的影响仅持续1个月左右,温度、降水对NDVI的影响可持续4—5个月。     

A Conservation Gap Analysis of Brazil''s Amazonian Vegetation

Vegetation types lacking protection in the existing conservation units of the nine states in the Brazilian Legal Amazon were identified, and locations were noted where these vegetation types could be protected. Maps of vegetation, protected areas, and semi-protected areas, such as Amerindian and forestry reserves, were digitized and overlaid using a geographic information system. There are 28 natural vegetation types in the Brazilian Legal Amazon. Locations of new areas for protection were selected using a minimum criterion of protecting at least one example of each vegetation type in each state (here called "vegetation zones"). There are 111 vegetation zones in the Legal Amazon, of which only 37 (33%) have some portion of their area protected. There are few protected areas in the most heavily deforested states along the southeastern fringe of the forest. In Maranhão, where 60% of the original forest had been lost by 1990, only one of 10 vegetation types is protected. Negotiating agreements with indigenous tribes, and to a lesser extent with extractivists who harvest nontimber products from the forest, represents a major opportunity to increase significantly the area and representativeness of the conservation units. Additional conservation units need to be established quickly before rapidly increasing deforestation and land prices preclude this opportunity; otherwise, some vegetation types may virtually disappear.     

Refining Biodiversity Conservation Priorities

Abstract:  Although there is widespread agreement about conservation priorities at large scales (i.e., biodiversity hotspots), their boundaries remain too coarse for setting practical conservation goals. Refining hotspot conservation means identifying specific locations (individual habitat patches) of realistic size and scale for managers to protect and politicians to support. Because hotspots have lost most of their original habitat, species endemic to them rely on what remains. The issue now becomes identifying where this habitat is and these species are. We accomplished this by using straightforward remote sensing and GIS techniques, identifying specific locations in Brazil's Atlantic Forest hotspot important for bird conservation. Our method requires a regional map of current forest cover, so we explored six popular products for mapping and quantifying forest: MODIS continuous fields and a MODIS land cover (preclassified products), AVHRR, SPOT VGT, MODIS (satellite images), and a GeoCover Landsat thematic mapper mosaic (jpg). We compared subsets of these forest covers against a forest map based on a Landsat enhanced thematic mapper. The SPOT VGT forest cover predicted forest area and location well, so we combined it with elevation data to refine coarse distribution maps for forest endemic birds. Stacking these species distribution maps enabled identification of the subregion richest in threatened birds—the lowland forests of Rio de Janeiro State. We highlighted eight priority fragments, focusing on one with finer resolved imagery for detailed study. This method allows prioritization of areas for conservation from a region >1 million km² to forest fragments of tens of square kilometers. To set priorities for biodiversity conservation, coarse biological information is sufficient. Hence, our method is attractive for tropical and biologically rich locations, where species location information is sparse.     

Synergistic Interactions between Habitat Fragmentation and Fire in Evergreen Tropical Forests

Abstract: The growing prevalence of fragmentation and fire in tropical forests makes it imperative to quantify changes in these disturbances and to understand the ways in which they interact across the landscape. I used a multitemporal series of Landsat images to study the incidence and coincidence of fire and fragmentation in two areas of Pará state in the eastern Brazilian Amazon: Tailândia and Paragominase. In both areas, deforestation and forest fires were quantified for time series of 6–10 years. The Tailândia study area typifies a landscape with the herringbone pattern of government-settled colonists, and the Paragominas area is dominated by large cattle ranches. In both areas, over 90% of the forests affected by fire were associated with forest edges. Although most burned forest occurred within 500 m of forest edges, some fires occurred in deep forest, several kilometers from any edge. The obvious synergism between forest fragmentation and fire poses serious risks to tropical ecosystems and has important implications for land management.     

Synthesizing habitat connectivity analyses of a globally important human-dominated tiger-conservation landscape

As ecological data and associated analyses become more widely available, synthesizing results for effective communication with stakeholders is essential. In the case of wildlife corridors, managers in human-dominated landscapes need to identify both the locations of corridors and multiple stakeholders for effective oversight. We synthesized five independent studies of tiger (Panthera tigris) connectivity in central India, a global priority landscape for tiger conservation, to quantify agreement on landscape permeability for tiger movement and potential movement pathways. We used the latter analysis to identify connectivity areas on which studies agreed and stakeholders associated with these areas to determine relevant participants in corridor management. Three or more of the five studies’ resistance layers agreed in 63% of the study area. Areas in which all studies agree on resistance were of primarily low (66%, e.g., forest) and high (24%, e.g., urban) resistance. Agreement was lower in intermediate resistance areas (e.g., agriculture). Despite these differences, the studies largely agreed on areas with high levels of potential movement: >40% of high average (top 20%) current-flow pixels were also in the top 20% of current-flow agreement pixels (measured by low variation), indicating consensus connectivity areas (CCAs) as conservation priorities. Roughly 70% of the CCAs fell within village administrative boundaries, and 100% overlapped forest department management boundaries, suggesting that people live and use forests within these priority areas. Over 16% of total CCAs’ area was within 1 km of linear infrastructure (437 road, 170 railway, 179 transmission line, and 339 canal crossings; 105 mines within 1 km of CCAs). In 2019, 78% of forest land diversions for infrastructure and mining in Madhya Pradesh (which comprises most of the study region) took place in districts with CCAs. Acute competition for land in this landscape with globally important wildlife corridors calls for an effective comanagement strategy involving local communities, forest departments, and infrastructure planners.     

大兴安岭火烧迹地土壤动物的群落多样行

以大兴安岭地区不同年份火烧迹地土壤动物为研究对象,对火烧后不同恢复时间土壤动物群落多样性及相关指数的变化进行分析.结果表明,大型土壤动物的个体数、DIC指数、丰富度指数及优势度指数变化趋势均表现为火烧恢复初期迅速增加,然后缓慢增加并逐渐接近对比样地值;如果不考虑8 a迹地数据极大值的影响,中小型土壤动物的个体数、DIC指数、丰富度指数及优势度指数也大致呈现火烧恢复初期迅速增加,然后缓慢增长的趋势;在垂直方向上,大型土壤动物DIC指数、个体数及丰富度指数在0～5 cm最大,向上、向下减少,而中小型土壤动物的各项指数都是凋落物层最大,向下迅速减小;相关分析表明,大型和中小型土壤动物的个体数和丰富度指数与DIC指数都具有极高的相关性;群落相似性分析显示,各火烧迹地间土壤动物群落具有较高的相似性.图1表3参26     

Examining Fragmentation and Loss of Primary Forest in the Southern Bahian Atlantic Forest of Brazil with Radar Imagery

Abstract: The Atlantic rainforest of southern Bahia is one of the last remnants of the lowland forest of eastern Brazil that once covered the entire coastal area from Rio Grande do Norte to Rio Grande do Sul ( lat 8°–28° S) and has been deforested to a small fraction of its original cover (1–12%). All recent vegetation surveys have been based on optical satellite data, which is hampered by cloud cover and by southern Bahia's intricate mix of forest patches with other tree crops, especially cocoa. We describe the application of radar remote-sensing data to distinguish forest patches from cocoa planted in the shade of natural-forest trees. Radar, unlike optical sensors, is not obstructed by cloud cover and can acquire information about forest structure by penetrating into the vegetation canopy. The vegetation map generated from radar data clearly separates forest patches based on the degree of structural disturbance such as the density of shaded trees, the openness of the canopy, and the density of the monodominant Erythyrina shaded trees. The structural classification based on the radar data, and shown on the map, can help researchers assess the degree of fragmentation of the original Atlantic coastal forest and delineate areas of less disturbance with higher potential for conservation of biodiversity. This information can then be applied to conservation planning, especially the design and monitoring of nature reserves and the modeling of biological corridors.     

Persistently highest risk areas for hantavirus pulmonary syndrome: potential sites for refugia.

Interannual variation in the number of cases of human disease caused by hantaviruses in North America has been hypothesized to reflect environmental changes that influence rodent reservoir populations. This hypothesis postulates that when cases are rare reservoir populations are geographically restricted in patches of suitable habitat. Identifying these sites, which is needed to test the hypothesis, has proven to be a challenge. Satellite imagery of the U.S. Southwest has shown associations among the likelihood of human hantaviral disease and increases in the rodent populations, as well as increased prevalence of Sin Nombre virus (SNV) in rodent populations. In this study we characterize local areas that had environmental signatures that persisted as predicted highest risk sites for human disease through much of the 1990s. These areas represent a small percentage (0.3%) of the region. Exploratory analyses indicate that these areas were not randomly distributed, but were associated with certain landscape characteristics. Characteristics of elevation, slope, aspect, and land cover were associated with persistent high risk. Using multivariate Poisson regression to control for confounding effects, sites with deciduous- or mixed-forest land cover on moderate to steep slopes (>5 degrees) above 2130 m elevation were associated with increasing numbers of years at highest risk. These are candidate locations for refugia. Sites associated with cleared ground or shrubland were less often associated with high risk compared to reference conditions. The seasonal patterns of vegetation growth in persistently high-risk areas were compared to matched locations using MODIS (moderate resolution imaging spectroradiometer) NDVI (normalized difference vegetation index) during a time of a severe drought in the region from 2002 to 2004. Despite the drought and regardless of land cover, the NDVI in persistently highest risk areas had an early onset, with significantly higher levels of green vegetation that lasted longer than at comparable sites. These observations identify locations that can be monitored for the abundance of P. maniculatus and presence of SNV. If these sites are refugia, we predict they will be occupied by infected deer mice when other monitored sites are unoccupied.     

Monitoring changes in forest and other land use forms in Istanbul

This study introduces the monitoring system to be established within this project, it aims to determine changes occurring within forested areas, settlement areas and other land use forms located at the peripheral area of Istanbul during consecutive decades. The first phase of the study was completed in 1998 and published, covering the period from 1984 to 1994. This study is the second phase of the first one and implemented to determine land use changes which have occurred on the same site from 1994 to 2000. Standard topographic maps with 1/25 000 scale, forest management maps with the same scale, results of the previous study, orthophoto maps of the year 2000 that were produced from aerial color photographs of the site with 1/5 000 scale, and 4-band IRS_LISS III multispectral satellite data for July 2000 were used as data. The changes in land use within the study area occurring during a six year period were studied.