土地利用/覆被变化扎龙湿地蒸散发量及生态需水量的遥感估算

地表蒸散发量是影响湿地水热平衡的主要因素,也是水分损失的主要途径,对湿地生态需水量的合理确定和水资源的有效管理具有重要意义。借助遥感和GIS技术,利用2002、2010、2016年34景Landsat影像,基于时序NDVI数据对湿地下垫面物候特征的定量表征,准确获取了扎龙湿地保护区3个时期土地利用/覆被的动态变化信息。选用物理基础较好且应用广泛的SEBAL模型,估算了湿地的瞬时蒸散发量,并结合站点气象数据,实现了湿地蒸散发量在时间尺度上的扩展,分别得到日、月、年尺度的湿地蒸散发量,深入探究了扎龙湿地蒸散发的时空分布特征;最后从湿地湖泡需水量、植物需水量及生物栖息地需水量3个方面,定量估算出扎龙湿地3个时期的现状生态需水量。研究发现：扎龙湿地的土地覆被类型主要以芦苇沼泽、草地和耕地为主,其中芦苇沼泽分布占绝对优势,且2002-2016年持续增加了205.82 km²;草地、耕地呈持续减少态势,分别减少了119.35 km²和95.96km²,表明2002-2016年扎龙湿地生态系统呈恢复态势;湿地保护区蒸散发量年内均大致呈单峰型分布,符合夏季 > 春季 > 秋季 > 冬季的规律,在年际上呈现明显的递增趋势,年蒸散发量由2002年的518.87mm增加到2016年的625.98mm,增加了20.64%。为满足湿地内的生态消耗,总体上2002-2016年湿地的生态需水量也相应的增加,保护区适宜生态需水量的变动范围为5.40亿-7.08亿m³,可以维持湿地湖泊、植被、动植物栖息地的健康态势。维持核心区健康状态的最小生态需水量变化范围为2.71亿-3.32亿m³。随着遥感数据时空分辨率的提高,基于蒸散发量反演的湿地生态需水量估算将更加实用和准确,为湿地保护区制定科学合理的补水方案提供有效的技术支撑。     

Estimation of primary production of subhumid rangelands from remote sensing data

Abstract. Above‐ground Net Primary Production (ANPP) is the main determinant of forage availability and hence of stocking density. A tool to track the seasonal and interannual changes in ANPP at the paddock level will be very important for livestock management. We studied the relationship between field ANPP data and the Normalized Difference Vegetation Index (NDVI) for rangelands of the Flooding Pampa of Argentina using spectral data provided by sensors on board of two satellites: NOAA/AVHRR and Landsat TM. The relationship between NDVI and ANPP was linear both for data derived from NOAA/AVHRR and Landsat TM. Changes in ANPP accounted for a large proportion of the temporal and spatial variation of NDVI: 71% of NOAA/AVHRR data and 74% of Landsat TM data. By inverting these models, ANPP may be inferred from NDVI data at a seasonal and paddock scale. NOAA/AVHRR data captured better the seasonal variation in ANPP and were less sensitive to local variations than Landsat TM data. In contrast, Landsat TM data were more sensitive to inter‐site differences in primary production, except for the winter months. Thus, combining information from these two sources offers a good alternative for monitoring rangeland production at high temporal and spatial resolution.     

Large-scale patterns of Nodularia spumigena blooms in Pyramid Lake,Nevada, determined from Landsat imagery: 1972–1986

Magnitude and long-term periodicity of summer-autumn blooms of the nitrogen-fixing cyanobacterium, Nodularia spumigena, were characterized for hyposaline Pyramid Lake, Nevada, from Landsat MSS band 3 film negatives. Predicted lakewide mean chlorophyll a concentrations for Landsat overpasses during the July–October Nodularia bloom season ranged from 27 to 72 mg m^–3 with an overall average concentration of 32 ± 7 mg m^–3 between 1972 and 1986. Nodularia blooms were usually annual events. Blooms were not observed on Landsat images in only three of 15 years (1973, 1980, 1982) and midsummer calcium carbonate whitings occurred in two of these years (1973, 1980). Magnitude of Nodularia blooms was highly variable among years and very large blooms, where maximum mean chlorophyll a concentration exceeded one standard deviation of the 15 year overall mean (> 39 mg m^–3) appeared in 1974, 1975, 1977, 1979, 1984, 1985 and 1986. Very large early-July blooms always occurred during or following years of above average fluvial discharge to Pyramid Lake (1984–1986) and were associated with meromixis produced by the large influx of freshwater.Several problems arise using Landsat remote sensing to estimate magnitude and periodicity of scum-forming blue-green algal blooms. These complications may reduce accuracy and precision of phytoplankton biomass estimates made from Landsat images. Nevertheless, Landsat remote sensing enabled us to quantify relative bloom magnitude with limited collection of ground-based data and at a large-scale temporal and spatial resolution not possible using alternative methodologies.     

Upscaling leaf area index in an Arctic landscape through multiscale observations

Monitoring and understanding global change requires a detailed focus on upscaling, the process for extrapolating from the site‐specific scale to the smallest scale resolved in regional or global models or earth observing systems. Leaf area index (LAI) is one of the most sensitive determinants of plant production and can vary by an order of magnitude over short distances. The landscape distribution of LAI is generally determined by remote sensing of surface reflectance (e.g. normalized difference vegetation index, NDVI) but the mismatch in scales between ground and satellite measurements complicates LAI upscaling. Here, we describe a series of measurements to quantify the spatial distribution of LAI in a sub‐Arctic landscape and then describe the upscaling process and its associated errors. Working from a fine‐scale harvest LAI–NDVI relationship, we collected NDVI data over a 500 m × 500 m catchment in the Swedish Arctic, at resolutions from 0.2 to 9.0 m in a nested sampling design. NDVI scaled linearly, so that NDVI at any scale was a simple average of multiple NDVI measurements taken at finer scales. The LAI–NDVI relationship was scale invariant from 1.5 to 9.0 m resolution. Thus, a single exponential LAI–NDVI relationship was valid at all these scales, with similar prediction errors. Vegetation patches were of a scale of ～0.5 m and at measurement scales coarser than this, there was a sharp drop in LAI variance. Landsat NDVI data for the study catchment correlated significantly, but poorly, with ground‐based measurements. A variety of techniques were used to construct LAI maps, including interpolation by inverse distance weighting, ordinary Kriging, External Drift Kriging using Landsat data, and direct estimation from a Landsat NDVI–LAI calibration. All methods produced similar LAI estimates and overall errors. However, Kriging approaches also generated maps of LAI estimation error based on semivariograms. The spatial variability of this Arctic landscape was such that local measurements assimilated by Kriging approaches had a limited spatial influence. Over scales >50 m, interpolation error was of similar magnitude to the error in the Landsat NDVI calibration. The characterisation of LAI spatial error in this study is a key step towards developing spatio‐temporal data assimilation systems for assessing C cycling in terrestrial ecosystems by combining models with field and remotely sensed data.     

Physiological stress and refuge behavior by African elephants

Physiological stress responses allow individuals to adapt to changes in their status or surroundings, but chronic exposure to stressors could have detrimental effects. Increased stress hormone secretion leads to short-term escape behavior; however, no studies have assessed the potential of longer-term escape behavior, when individuals are in a chronic physiological state. Such refuge behavior is likely to take two forms, where an individual or population restricts its space use patterns spatially (spatial refuge hypothesis), or alters its use of space temporally (temporal refuge hypothesis). We tested the spatial and temporal refuge hypotheses by comparing space use patterns among three African elephant populations maintaining different fecal glucocorticoid metabolite (FGM) concentrations. In support of the spatial refuge hypothesis, the elephant population that maintained elevated FGM concentrations (iSimangaliso) used 20% less of its reserve than did an elephant population with lower FGM concentrations (Pilanesberg) in a reserve of similar size, and 43% less than elephants in the smaller Phinda reserve. We found mixed support for the temporal refuge hypothesis; home range sizes in the iSimangaliso population did not differ by day compared to nighttime, but elephants used areas within their home ranges differently between day and night. Elephants in all three reserves generally selected forest and woodland habitats over grasslands, but elephants in iSimangaliso selected exotic forest plantations over native habitat types. Our findings suggest that chronic stress is associated with restricted space use and altered habitat preferences that resemble a facultative refuge behavioral response. Elephants can maintain elevated FGM levels for ≥ 6 years following translocation, during which they exhibit refuge behavior that is likely a result of human disturbance and habitat conditions. Wildlife managers planning to translocate animals, or to initiate other management activities that could result in chronic stress responses, should consider the potential for, and consequences of, refuge behavior.     

Analysis of land cover and landscape change patterns in Ebinur Lake Wetland National Nature Reserve,China from 1972 to 2013

For effective monitoring and protection, researchers need to analyze the trends and causes of landscape pattern change in wetlands. The present study used Geographic Information System and remote sensing technology to analyze temporal and spatial dynamics of landscape pattern and related driving forces in the Ebinur Lake Wetland National Nature Reserve (ELWNNR) in China. We used Landsat images from 1972, 1998, 2007 and 2013, and classified the landscape into six types of land cover: water body, wetland, vegetation, salinized land, desert, and other objects (i.e., Gobi and Mountain). Landscape transition matrices and change pattern analysis were used understand wetland dynamics. Our results showed that land cover had changed dramatically during 1972–2013. The spatial extent of much of the wetland areas in the ELWNNR had reduced gradually from 1972 to 2007, and wetland loss occurred more rapidly after 2007. From 1972 to 2013, 415.8 km² of wetland area had been lost and only 250.1 km² wetland area had expanded, which represents a 22% decrease in wetland area in the ELWNNR. At the same time, the landscape pattern experienced diverse changes in the Nature Reserve. The high-density human population of the region has an intensive effect on the region. Wetlands in the nature reserve have also changed with recent rapid development in the region. This study may provide scientific information for developing effective and sustainable conservation plans for the ELWNNR.     

基于带宽优选地理加权回归模型的深圳市植被碳储量反演

植被碳储量估测是自然资源监测的重要内容,遥感技术结合地面样地进行反演可以获得区域范围内植被碳储量的空间连续分布,弥补了传统人工抽样调查估测的不足。然而,现有的参数和非参数遥感估测模型大多忽略了样地数据的变异与空间自相关关系。研究以Landsat 8 OLI影像为数据源提取遥感变量,结合植被碳储量实测调查数据,利用最小信息准则(AICc)、最大空间自相关距离(MSAD)和交叉验证(CV)分别确定最优带宽,组合Gaussian、Bi-square和Exponential核函数构建地理加权回归(GWR)模型估算深圳市植被碳储量,并与多元线性回归(MLR)进行比较,选择最优模型绘制深圳市植被碳储量空间分布图。研究结果表明,GWR模型整体精度优于MLR模型,GWR模型的决定系数(R~2)均高于MLR模型,且均方根误差(RMSE)和平均绝对误差(MAE)显著降低。带宽和核函数的选择对GWR模型估测结果产生了显著影响。以CV确定带宽、Exponential为核函数组合构建的GWR模型效果最佳,其R~2为0.697,RMSE为10.437 Mg C/hm~2,相比其它模型精度上升了13.87%—32....     

基于物种分布的森林生态系统类型自然保护区功能区划评价——以河南连康山国家级自然保护区为例

森林生态系统类型自然保护区是我国最主要的自然保护区类型,该类型自然保护区通常具有复杂多样的保护对象,因此对其进行功能区划需全面考虑各种保护对象的需求。评价森林生态系统类型的自然保护区功能区划有利于提高自然保护区的保护有效性。以属于森林生态系统类型自然保护区的河南连康山国家级自然保护区功能区划为研究对象,于2016年12月至2018年12月在该自然保护区内进行样线和红外相机调查,获取白冠长尾雉及与白冠长尾雉存在种间相互作用物种的分布点数据,结合收集的环境数据,采用MaxEnt模型对白冠长尾雉（Syrmaticus reevesii）和与白冠长尾雉存在种间相互作用物种的分布进行预测,进而分析物种与该自然保护区功能区划的空间关系,及自然保护区内野生动物分布与人为干扰强度的空间关系,评估连康山国家级自然保护区现有功能区划对白冠长尾雉和与白冠长尾雉存在种间相互作用物种的保护有效性。结果表明,保护区内高保护价值区域面积为33.84 km²,核心区、缓冲区和实验区内高保护价值区域面积分别占保护区总面积的18.96%、3.84%和9.19%,自然保护区内高保护价值区域面积比例偏低。保护区现有功能区划并不能充分满足保护白冠长尾雉栖息地的需要,且核心区、缓冲区和实验区面临不同程度的人为干扰的影响,这对保护区内重点保护对象的生存产生潜在威胁。因此,结合保护区内保护价值与人为干扰分布现状,针对白冠长尾雉及相关物种的受胁情况提出两种不同的保护区功能区划优化方案,在不降低连康山国家级自然保护区面积的前提下,提高核心保护区白冠长尾雉及相关物种适宜栖息地面积的比例,同时降低保护区内人为干扰强度。本研究可为该保护区保护白冠长尾雉提供决策依据,并为其他以野生动物为保护目标的保护区功能区划优化提供指导方法。     

Modelling habitat and planning surveillance using Landsat imagery: a case study using Imported Red Fire ants

This paper presents a Bayesian mixture model approach for detecting areas of habitat that are suitable for S. invicta infestation, aiding the ongoing surveillance for early detection of these exotic pests. We show that Landsat imagery is an affordable and valuable tool to assist in determining an informed surveillance strategy. In this paper, we use Landsat band 3 (visible red), Landsat band 6 (mid infrared) and a soil brightness index, in various combinations, to assess the probability that the area associated with each pixel is habitable terrain, either in a multivariate analysis, or as a univariate spatial temporal model. The multivariate analysis allows researchers to create meaningful clusters that reflect the sometimes complex combinations of conditions of conditions that form suitable habitat, rather then relying on single derived indices.     

Regional scale relationships between ecosystem structure and functioning: the case of the Patagonian steppes

Aims 1. To characterize ecosystem functioning by focusing on above‐ground net primary production (ANPP), and 2. to relate the spatial heterogeneity of both functional and structural attributes of vegetation to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location Western portion of the Patagonian steppes in Argentina (39°30′ S to 45°27′ S). Methods We used remotely‐sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (ANPP and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP. We built an empirical relationship between the Landsat TM‐derived normalized difference vegetation index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PCs)). Results PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes. Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semideserts, latitude and, to a lesser extent, the number of PCs within an 8 × 8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8 × 8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes. Main conclusions Our results suggest that the spatial and temporal patterns of ecosystem functioning described from ANPP result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely‐sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification.     

The use of stable isotopes to trace small-scale movements by small fish species

Valuable biological information can be obtained by monitoring the movement of organisms. However, the choice of monitoring method becomes highly restricted when following small organisms (<100 mm), especially in aquatic ecosystems. Stable isotopes are being increasingly used in this respect but rarely at the local spatial scale, i.e. 10–1000 s of metres. We sought to identify movement of small fishes between a main river channel and its tributary. Little overlap in isotope baseline was detected between the two channels despite some temporal variability in δ¹⁵N of baseline indicator organisms in the main river. The individuals of two small cyprinid fish species (Leuciscus souffia and Alburnoides bipunctatus) of all the size classes (40–100 mm) caught within the tributary showed considerable heterogeneity in δ¹⁵N values. Classification and discriminant analysis on isotope-derived data distinguished two significantly different groups. Moreover, this result was supported by further sampling of fish caught in the main river (in May and December 2006). Alternative hypotheses, such as dietary differences, biological factors, temporal shifts and spatial differences in diet, did not explain δ¹⁵N variability. This application of stable isotopes at a relatively small spatial and temporal scales further demonstrates its potential as a tool for ecologists.     

Mapping and monitoring of coastal wetlands of Çukurova Delta in the Eastern Mediterranean region

The aim of this research was to link vegetation characteristics, such as spatial and temporal distribution, and environmental variables, with land cover information derived from remotely sensed satellite images of the Eastern Mediterranean coastal wetlands of Turkey. The research method was based on (i) recording land cover characteristics by means of a vegetation indicator, and (ii) classifying and mapping coastal wetlands utilizing a Landsat Thematic Mapper (TM) image of Çukurova Deltas in Turkey. Vegetation characteristics of various habitats, such as sand dunes, salt marshes, salty plains and afforestation areas, were identified by field surveys. A Landsat TM image of 4 July 1993 was pre-processed and then classified using the Maximum Likelihood (ML) algorithm and Artificial Neural Networks (ANN). As a result of this supervised classification, the land cover types were classified with a largest accuracy of 90.2% by ANN. The classified satellite sensor imagery was linked to vegetation and bird census data, which were available through literature in a Geographical Information System (GIS) environment to determine the spatial distribution of plant and bird biodiversity in this coastal wetland. The resulting data provide an important baseline for further investigations such as monitoring, change detections and designing conservation policies in this coastal ecosystem.     

基于多源遥感数据的草地净初级生产力质量评价

植被净初级生产力NPP(Net Primary Production)的遥感估算与分析对全球生态系统具有重要指导意义,不同尺度的遥感影像上占主导地位的地物景观信息是不同的,现代生态研究多尺度分析至关重要。以青海省海北藏族自治州为研究区,使用Landsat 8 OLI遥感影像、天宫二号宽波段成像仪影像、融合影像(Landsat8 OLI影像和天宫二号宽波段成像仪影像融合)联同MODIS影像,作为CASA模型的输入参数,探究不同尺度下的研究区域NPP的空间分布情况,并对比分析不同数据源数据在估算NPP时的精度。结果表明:(1)Landsat 8 OLI数据的NPP值位于150—200 g C m^-2 a^-1所占比例最高;天宫二号宽波段成像仪影像数据和融合后影像的NPP值位于50—100 g C m^-2 a^-1所占比例最高;MODIS数据的NPP值位于小于50 g C m^-2 a^-1比例最高。(2)天宫二号宽波段成像仪影像数据的均方根误差(RMSE)、平均绝对误...     

Habitat selection and feeding ecology of the cheetah (Acinonyx jubatus) in thicket vegetation: is the cheetah a savanna specialist?

Habitat selection and feeding ecology of a reintroduced population of cheetahs Acinonyx jubatus were studied in a 16 000 ha game reserve in the Eastern Cape Province (South Africa). Seventy per cent of the reserve is characterized by very dense thicket vegetation (valley bushveld) and the remainder is open and savanna-like. The results illustrated a strong effect of sex and group size on the behaviour of cheetahs. The coalition (three adult males) killed significantly larger animals (55% of kills weighed more than 65 kg) than single female cheetahs (less than 2% of kills weighed more than 65 kg). Female cheetahs showed temporal and spatial avoidance of lions by hunting at dawn and dusk and positioning their home ranges [95% utilization distribution (UDs)] significantly farther from the pride of lions than did the coalition. The coalition hunted earlier and later than female cheetahs, and 46% of their kills were made in darkness. In addition, their home range overlapped that of the lions and they showed neither temporal nor spatial avoidance of the lions. The rates of kleptoparasitism were lower and the kill retention times were longer than those reported elsewhere in Africa, and it is suggested that this is a consequence of the cover provided by the thicket vegetation and prey size. The home ranges (95% UDs) of female cheetahs incorporated more thicket vegetation than that of the coalition, indicating that the coalition is less susceptible to predation than single females. These data suggest that cheetahs possess greater behavioural flexibility than previously reported, that they can hunt successfully in thicket vegetation, sometimes in darkness, that they are not restricted to killing small to medium-sized prey, and that they may not be savanna specialists.     

空间约束背景下海岸带湿地保护边界研究

湿地保护边界划定是维护湿地可持续发展的基础前提,也是协调湿地保护与农地利用、城镇发展土地配置与空间布局的必经途径。研究从湿地保护边界的"源-汇"生态景观互动视角着眼,明晰了湿地保护源及保护优先等级,建构了空间约束评价与生态断界来刻画汇景观空间层次分异,借助最小累积阻力模型测度与划分了湿地保护边界及其类型。研究发现:(1)基于多重因素的空间约束评价与湿地生态断界的划分,通过最小阻力模型有效地刻画外部因子集成对湿地保护的限制及差异,以量化方式描绘湿地保护所处阻力最小地带,为湿地保护边界划分提供了新的思路。(2)杭州湾南岸生态断界与中高约束的区域占据研究区52.69%比例,无约束地域仅为12.79%,奠定了综合因素空间约束强势的基本格局。加之低度约束区域占据34.53%,显示杭州湾南岸区域多介于高低空间约束性势转换或过渡阶段,压缩了湿地保护的空间。(3)研究划分湿地保护边界范围与缓冲区带为49.11、24.07km~2,面积总和仅占据杭州湾南岸5.47%,湿地保护拓展和弹性调整空间极为有限。除生态断界提供湿地保护的天然边界外,湿地保护界限表现为保育林区、农地延伸型和水源保护型三类。     

Interaction of ion tracks in spatial and temporal proximity

In the present work, a systematic analysis of the impact of spatial and temporal proximity of ion tracks on the yield of higher-order radiolytic species as well as of DNA damage patterns is presented. This potential impact may be of concern when laser-driven particle accelerators are used for ion radiation therapy. The biophysical Monte Carlo track structure code PARTRAC was used and, to this end, extended in two aspects: first, the temporal information about track evolution has been included in the track structure module and, second, the simulation code has been modified to enable parallel multiple track processing during simulation of subsequent modelling stages. Depending on the spatial and temporal separation between ion-track pairs, the yield of chemical species has been calculated for incident protons with start energies of 20 MeV, for He²⁺ ions with start energies of 1 and 20 MeV, and for 60 MeV C⁶⁺ ions. Provided the overlap of the considered ion tracks is sufficient in all four dimensions (space and time), the yield of hydroxyl radicals was found to be reduced compared to that of single tracks, for all considered ion types. The biological endpoints investigated were base damages, single-strand breaks, double-strand breaks, and clustered lesions for incident pairs of protons and He²⁺ ions, each with start energies of 20 MeV. The yield of clustered lesions produced by 20 MeV protons turned out to be influenced by the spatial separation of the proton pair; in contrast, no influence was found for different start times of the protons. The yield of single-strand breaks and base hits was found neither to depend on the spatial separation nor on the temporal separation between the incident protons. For incident 20 MeV He²⁺ ions, however, a dependence on the spatial and temporal separation of the ion pair was found for all considered biological endpoints. Nevertheless, spatial proximity conditions where such intertrack effects were obtained are not met in the case of tumour radiation therapy; thus, no impact on radiation effects due to short pulse duration of laser-driven accelerators can be expected from alterations during the chemical stage.     

The role of livestock movements in the spread of Rift Valley fever virus in animals and humans in Mayotte, 2018–19

Rift Valley fever (RVF) is a vector-borne viral disease of major animal and public health importance. In 2018–19, it caused an epidemic in both livestock and human populations of the island of Mayotte. Using Bayesian modelling approaches, we assessed the spatio-temporal pattern of RVF virus (RVFV) infection in livestock and human populations across the island, and factors shaping it. First, we assessed if (i) livestock movements, (ii) spatial proximity from communes with infected animals, and (iii) livestock density were associated with the temporal sequence of RVFV introduction into Mayotte communes’ livestock populations. Second, we assessed whether the rate of human infection was associated with (a) spatial proximity from and (b) livestock density of communes with infected animals. Our analyses showed that the temporal sequence of RVFV introduction into communes’ livestock populations was associated with livestock movements and spatial proximity from communes with infected animals, with livestock movements being associated with the best model fit. Moreover, the pattern of human cases was associated with their spatial proximity from communes with infected animals, with the risk of human infection sharply increasing if livestock in the same or close communes were infected. This study highlights the importance of understanding livestock movement networks in informing the design of risk-based RVF surveillance programs.     

Spatial and Temporal Patterns of Deforestation in Rio Cajarí Extrative Reserve,Amapá, Brazil

The Rio Cajarí Extractive Reserve (RCER) is a sustainable use protected area located in Southern Amapá state, Brazil. This protected area is home to traditional agro-extractive families, but has been increasingly invaded by commercial agriculture producers. In this work, we test the hypothesis that the RCER implementation has distinctly affected spatial patterns of deforestation and rates of bare soil and secondary forest formation by the social groups occupying the protected area and its surrounding area. Detailed maps of vegetation cover and deforestation were elaborated, based on Landsat TM images from 1991, 1998, 2007 and 2008 and Linear Spectral Mixture Models. Based on an extensive fieldwork, patches were classified according to the agents causing deforestation and characterized with ten explanatory variables. A discriminant function analysis was used to identify homogeneous groups based on the data. Results show increased rates and distinct spatial patterns of deforestation by three groups: extractivists, non traditional commercial agriculture producers, and a less representative group constituted of miners, cattle and timber producers. In all analyzed dates, clearings by the extrativist community presented the highest total area and smaller average sizes and were located in close proximity to villages. Deforestation patches by the non-traditional group were exclusively associated with ombrophilous forests; these presented higher average sizes and proximity indexes, and showed increased aggregation and large cluster formation. No significant differences were observed in deforestation patterns by the three groups inside or outside the reserve.     

Land surface phenology as an indicator of biodiversity patterns

With the rapid decline in biodiversity worldwide it is imperative to develop procedures for assessing changes in biodiversity across space. The synoptic view provided by imaging remote sensors constitutes a suitable approach for analyzing biodiversity from local to regional scales. A procedure based on the close relationship between floristic similarity and the similarity in land surface phenology was recently developed and successfully applied to assess diversity patterns using time series imagery acquired by the Moderate Resolution Imaging Spectro-radiometer (MODIS). However, as it depends on high temporal resolution remotely sensed data (e.g., MODIS), the procedure is constrained by the coarse spatial resolution characterizing these high temporal resolution data. Using an optimized technique for image fusion, we combined high temporal resolution data acquired by the MODIS sensor system with moderate spatial resolution data acquired by the Landsat TM/ETM+ sensor systems. Our results show that the MODIS/Landsat data fusion allows the characterization of land surface phenology at higher spatial resolutions, which better corresponded with information acquired within vegetation survey plots established in temperate montane forests located in Wolong Nature Reserve, Sichuan Province, China. As such, the procedure is useful for capturing changes in biodiversity induced by disturbances operating at large spatial scales and constitutes a suitable tool for monitoring and managing biodiversity.     

Desertification alters regional ecosystem–climate interactions

We studied the spatial patterns and temporal dynamics of vegetation structural responses to precipitation variation in grassland, transitional, and desertified‐shrubland ecosystems in an 800 km² region of Northern Chihuahua, USA. Airborne high‐fidelity imaging spectroscopy data collected from 1997 to 2001 provided spatially detailed measurements of photosynthetic and senescent canopy cover and bare soil extent. The observations were made following wintertime and summer monsoonal rains, which varied in magnitude by >300% over the study period, allowing an assessment of ecosystem responses to climate variation in the context of desertification. Desertification caused a persistent increase in both photosynthetic vegetation (PV) and bare soil cover, and a lasting decrease in nonphotosynthetic vegetation (NPV). We did not observe a change in the spatial variability of PV cover, but its temporal variation decreased substantially. In contrast, desertification caused the spatial variability of NPV to increase markedly, while its temporal variation did not change. Both the spatial and temporal variation of exposed bare surfaces decreased with desertification. Desertification appeared to be linked to a shift in seasonal precipitation use by vegetation from mainly summer to winter inputs, resulting in an apparent decoupling of vegetation responses to inter‐annual monsoonal variation. Higher winter rainfall led to decreased springtime spatial variability in the PV cover of desertified areas. Higher summer rainfall resulted in decreased PV cover variation in grassland, transition and desertified‐shrubland regions. The effects of desertification on NPV dynamics were more than three times greater than on PV or bare soil dynamics. Using remotely sensed PV and NPV as proxies for net primary production (NPP) and litter dynamics, respectively, we estimated that desertification decreases the temporal variability of NPP and increases spatial variation of litter production and loss. Quantitative studies of surface biological materials and ecosystem processes can now be measured with high ‘structural’ detail using imaging spectroscopy and shortwave‐infrared spectral mixture analysis.