Assessment and protective strategy of black muntjac habitat in Zhejiang, China

Habitat degradation and loss had been widely recognized as the main cause for the decline of wildlife population. Habitat assessment can provide essential information for wildlife refuge design and management. In this article, a systematic study on the black muntjac distribution, habitat quality, and spatial pattern was conducted. Initially, the main factors that influence the black muntjac habitat quality were identified, and habitat assessment criteria were set up. The vegetation, topographic, river, road, and village maps were then digitized by the geographical information system (GIS). Finally, the habitat distribution and quality were assessed based on the combination of vegetation, elevation, river system, and impact of human activities. The result showed that the potential habitat for black muntjac covered an area of 3172.6 hm2, and 501.5 hm2 of habitat in the Jiulong Mountain Natural Reserve was lost because of the degradation caused by human activities. The existing suitable habitat is 2671.1 hm2, mostly distributed in Shangliaokeng, Jiulongshan, Neibeiping, Waijiulong, and Dayanqian in Gutian, Zhejiang Province, China.     

Biotic factors and occurrence of Lutzomyia longipalpis in endemic area of visceral leishmaniasis, Mato Grosso do Sul, Brazil

The relationships between environmental exposure to risk agents and health conditions have been studied with the aid of remote sensing imagery, a tool particularly useful in the study of vegetation cover. This study aims to evaluate the influence of environmental variables on the spatial distribution of the abundance of Lutzomyia longipalpis and the reported canine and human visceral leishmaniasis (VL) cases at an urban area of Campo Grande, state of Mato Grosso do Sul. The sandfly captures were performed in 13 residences that were selected by raffle considering four residences or collection station for buffer. These buffers were generated from the central house with about 50, 100 and 200 m from it in an endemic area of VL. The abundance of sandflies and human and canine cases were georreferenced using the GIS software PCI Geomatica. The normalized difference vegetation index (NDVI) and percentage of land covered by vegetation were the environmental variables extracted from a remote sensing IKONOS-2 image. The average NDVI was considered as the complexity of habitat and the standard deviation as the heterogeneity of habitat. One thousand three hundred sixty-seven specimens were collected during the catch. We found a significant positive linear correlation between the abundance of sandflies and the percentage of vegetation cover and average NDVI. However, there was no significant association between habitat heterogeneity and the abundance of these flies.     

Assessment and protective strategy of black muntjac habitat in Zhejiang, China

Habitat degradation and loss had been widely recognized as the main cause for the decline of wildlife population. Habitat assessment can provide essential information for wildlife refuge design and management. In this article, a systematic study on the black muntjac distribution, habitat quality, and spatial pattern was conducted. Initially, the main factors that influence the black muntjac habitat quality were identified, and habitat assessment criteria were set up. The vegetation, topographic, river, road, and village maps were then digitized by the geographical information system (GIS). Finally, the habitat distribution and quality were assessed based on the combination of vegetation, elevation, river system, and impact of human activities. The result showed that the potential habitat for black muntjac covered an area of 3172.6 hm², and 501.5 hm² of habitat in the Jiulong Mountain Natural Reserve was lost because of the degradation caused by human activities. The existing suitable habitat is 2671.1 hm², mostly distributed in Shangliaokeng, Jiulongshan, Neibeiping, Waijiulong, and Dayanqian in Gutian, Zhejiang Province, China.     

Spatial relationships between NDVI and topographic factors at multiple scales in a watershed of the Minjiang River,China

Improvement in vegetation cover in the upper reaches of the Minjiang River protects major freshwater sources and constructs ecological barriers in the upstream of Yangtze River located in southwest China. However, the spatially varying relationships between normalized difference vegetation index (NDVI) and topographic factors at multiple scales remain unclear. In this study, the two-dimensional discrete wavelet transform (2D-DWT) and geographically weighted regression (GWR) were combined to build a framework for examining the complex spatial relationships between NDVI and topographic factors at multiple scales. Based on the gridded datasets of NDVI and digital elevation model (DEM) of a small watershed located in the upper reaches of the Minjiang River situated in southwest China, the influence of topographic factors on NDVI variation in each grid and which topographic variables correlated most with the NDVI at each location were analyzed in this study. The grid data were decomposed into smooth and detail components using 2D-DWT. The results revealed that elevation, slope, and aspect exhibited different scale effects on NDVI in different wavelet components. In the smooth components, the spatial correlation of NDVI with elevation, slope, and south-facing index (SFI) of aspect increased with the decomposition scale, whereas topographic factors had different degrees of influence on NDVI. Elevation was found to be the most important topographic factor that determined the spatial distribution of NDVI on both sides of the valley, and SFI exhibited the highest effect on NDVI when elevation was higher than 2500 m. In the detail components, the spatial distribution of the most important topographic factor affecting the NDVI was not evident at a smaller scale, whereas it became obvious at 480 m scale. SFI was found to be more important than elevation and slope at a larger scale. These results will help in understanding the complex relationship between NDVI and topographic factors and determining the appropriate topographic location for ecological restoration.     

祁连山南坡主要河谷NDVI时空变化及影响因素分析

为进一步保护祁连山生态环境及合理开发利用河流沿线的植被资源,该文基于MODIS数据的NDVI产品及DEM数据集,对祁连山南坡主要河流谷地2000—2018年植被生长季的NDVI时空分布特征进行了研究,并提取研究区的主要地形因子,分析其对河流谷地植被生长季NDVI的影响。结果表明:随着河流两侧缓冲区距离逐渐增大,各年份的NDVI值呈现先增加后平稳再减少的分布特点;2000—2018年研究区河谷NDVI的变化趋势基本一致,整体表现出2010年出现了近20年的峰值;祁连山南坡河流谷地NDVI值,从斜坡(16°~25°)至急坡(41°~45°)增加的速率最大,说明该区间为NDVI值突变区间。2000—2018年祁连山南坡主要河流谷地的NDVI时空分布,可能受地形、气温和降水等自然因素影响较大,其受人为干扰因素影响较小,其中降水并非影响研究区河谷植被NDVI分布的主导因素,而气温可能是影响研究区河谷植被NDVI分布的主导因素。在地形因子中,存在较适合植被生长的特定坡度区间,且太阳辐射能量的增加有利于植被的生长。     

黄河三角洲植被指数与地形要素的多尺度分析

结合地理信息系统和遥感技术, 研究了黄河三角洲植被指数NDVI与一系列地形要素间的尺度依赖关系, 从而检验在较大尺度上滨海生态系统植被分布格局是否存在水分再分配的调控作用。结果表明: 1)NDVI值在4种主要群落类型间差异显著, 这种显著差异是由滨海盐生植物的生境特点决定的; 2)地表高程在所有的10个粒度尺度上均与NDVI相关关系显著, 这种显著关系在小尺度上与地下水埋深有关, 而在大尺度上可能参与水分再分配过程; 3)在750 m粒度尺度附近存在水分再分配的调控作用, 在该尺度附近地形湿润度指数(TWI)和坡度与NDVI相关达到极显著, 而且其Moran’sI指数突然增大。黄河三角洲的植被地形关系表现为不同尺度上对土壤水分和盐分的调控, 在小尺度上地形因素通过土壤表面蒸发过程影响土壤水分与盐分, 而在大尺度上地形因素主要通过地表径流对土壤水分与盐分进行再分配。     

黄土高原归一化植被指数与自然环境因子的空间关联性——基于地理探测器

植被对改善黄土高原脆弱的生态环境有着关键作用,系统研究黄土高原归一化植被指数(NDVI)空间分布和环境因子的空间关联性,可为新时代黄土高原植被高质量建设提供科学依据。以黄土高原2000-2017年年均植被NDVI为研究对象,选取气候要素、地形因素、土壤类型和植被类型等自然环境因子,运用GIS和地理探测器技术手段,在剔除土地利用类型发生变化栅格的基础上,研究黄土高原年均NDVI与环境因子的空间关联性,结果表明:2000-2017年黄土高原年均NDVI值在0.016-0.72之间,呈地带性分布,由西北部向东南部逐渐升高,大于0.3的区域占50.23%;2000-2017年黄土高原年均植被NDVI分布具有空间异质性,且在不同植被区、地貌区、土壤区和气候区中,NDVI空间分布的主要环境驱动因子具有差异性。年均降雨量对NDVI空间分布具有强解释力,是黄土高原85.20%的区域植被生长的主要制约因子;约12.01%的区域主要受土壤类型影响,为中等解释力,其余区域的植被生长主要受年均气温,日照时数或海拔影响。建议综合考虑不同环境条件下植被NDVI的空间分布与环境影响因子的空间关联性,明确不同区域中植被NDVI的环境制约因子,以制约因子定植,在防止土壤干燥化、贫瘠化的前提下,提高植被覆盖率和生物多样性,以期促进黄土高原植被建设高质量发展。     

Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models

Ellenberg indicator values (EIV) have been widely used to estimate habitat variables from floristic data and to predict vegetation composition based on habitat properties. Geographical Information Systems (GIS) and Digital Elevation Models (DEM) are valuable tools for studying the relationships between topographic and ecological characters of river systems. A 3-meter resolution DEM was derived for a. 3-km-long break section of the Szum River (SE Poland) from a 1:10,000 topographic map. Data on the diversity and ecological requirements of the local vascular flora were obtained while making floristic charts for 32 sections of the river valley (each 200 m long) and physical and chemical soil measurements; next, the data were translated into EIV. The correlations of the primary and secondary topographic attributes of the valley, species richness, and EIV (adapted for the Polish vascular flora) were assessed for all species recognized in each valley section. The total area and proportion of a flat area, mean slope, slope curvature, solar radiation (SRAD), and topographic wetness index (TWI) are the most important factors influencing local flora richness and diversity. The highest correlations were found for three ecological indicators, namely light, soil moisture, and soil organic content. The DEM seems to be useful in determination of correlations between topographic and ecological attributes along a minor river valley.     

基于土地覆盖和NDVI变化的拉萨河流域生境质量评估

气候变化和人类活动导致的土地覆盖和植被变化都会对生境质量产生影响。青藏高原是众多珍稀高原动植物的栖息地,具有重要的生物多样性维持价值。拉萨河流域是青藏高原经济最发达、人口最密集的核心地区,人类活动对生境质量带来的胁迫和压力持续增加。为揭示近些年来土地覆盖和植被变化对拉萨河流域生境质量的影响,选择生长季NDVI作为植被变化的指示因子,通过对不同植被类型各年份的生境适宜度进行修正,利用In VEST模型评估了拉萨河流域1990—2015年的生境质量时空变化。研究结果表明,1990—2015年拉萨河流域土地覆盖变化整体相对较小,其中人工表面和湿地面积增幅相对较大,分别为82.65%和32.40%;土地覆盖变化的转移方向主要为稀疏草地转化为草原和草甸、耕地转化为人工表面以及冰川/积雪转化为荒地。植被变化方面,1990—2000年,除流域中上游的裸岩、裸土地区和念青唐古拉山地区外,流域NDVI整体有较显著上升;而2000年以后略有下降。从生境质量的空间分布来看,高质量生境主要分布在流域下游、念青唐古拉山南侧河谷地区以及拉萨河源头等地区,低质量生境主要分布在拉萨市市辖区及周边、林周县县城及周边,以及流域中上游的荒地等地区。从时间变化上来看,1990—2000年,拉萨河流域整体生境质量指数从0.51上升到0.57; 2010年和2015年整体生境质量指数分别为0.56和0.55,较2000年略有下降。相比于土地覆盖变化,NDVI对生境质量变化的影响更为显著。     

Normalized difference vegetation index (NDVI) as a predictor of forage availability for ungulates in forest and field habitats

Quantifying available plant biomass is a crucial step towards improving our understanding of herbivore ecology and trophic interactions. Thanks to the development of satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI), ecologists have been provided with indirect estimates of primary production at various temporal and spatial scales. When it comes to forested ecosystems, most mammalian herbivores predominantly rely on the ground vegetation, yet little is known regarding the suitability of NDVI to predict this component of forest vegetation cover. This study compares the relationship between NDVI and ground vegetation biomass in two contrasting habitats (field and forest) in Eastern Poland over the spring and summer seasons (2007–2008). Results indicate that seasonality shapes the relationship between NDVI and ground vegetation biomass for each habitat type. In the field habitat, NDVI and ground vegetation biomass were positively related, with a stronger correlation between the two variables occurring in summer. In the forest habitat, a switch in the direction of the correlation between biomass and NDVI (from positive in spring to negative in summer) was detected. The timing of the switch was related to the timing of full development of tree and shrub leaves (late May–early June). This suggests that the usefulness of NDVI as a predictor of ground vegetation biomass is dependent upon the habitat considered and the targeted season.     

A framework for conservation area designation utilizing an ecotope concept and its application to a mountainous national park in Korea

This study focused on establishing a framework for the designation of a conservation area reflecting an ecotope concept, and its application to Korea’s Seoraksan National Park. Taking into consideration the mountainous topography of the study area, the watershed was chosen as the planning unit, and ecotope mapping was carried out to identify topographic and biological features. For the evaluation of the state of recent use, the trail index and the distribution status of tour and management facilities were used. These features were processed using Marxan with Zones. As a result, the optimal solution of scenario 1 was selected as the final one following detailed verification of the area ratio and grouping of the Park Nature Conservation Area (zone A, 76.7%) and the Park Nature Environment Area (I) (zone B, 14.3%), the inclusion ratio of biotope grade I (95.2%) and the satisfied shortfall value of the conservation indicators. In the overlap analysis between the optimal solution and recent zonation, most of the features included in the suggested scenario were found to be correctly distributed according to the intensity of conservation. Furthermore, the northern parts of the watershed which include sub-alpine vegetation with the Baekdudaegan ridge as its ecological axis was newly separated into the Park Conservation Area. This verification confirmed the improvement of recent zonation through the concrete criteria of ecotope mapping.     

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 × 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike’s Information Criterion corrected for small sample size (AIC_c), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions.     

Mapping forest vegetation patterns in an Atlantic-Mediterranean transitional area by integration of ordination and geostatistical techniques

Aims Forest vegetation variability may be explained by the complex interplay among several spatial structuring factors, including climate and topography. We modelled the spatial variability of forest vegetation assemblages and significant environmental variables along a complex environmental gradient or coenocline to produce a detailed cartographic database portraying the distribution of forests along it.Methods We combined an analysis of ordination coenoclines with kriging over 772 field data plots from the third Spanish National Forest Inventory in an Atlantic–Mediterranean transitional area (northern Spain).Important findings The best fitted empirical semivariogram revealed a strong spatial structure of forest species composition along the complex environmental gradient considered (the climatic–topographic gradient from north to south). The steady and gradual increase of semivariance with a marked lag distance indicates a gradual turnover of forest assemblages according to the climatic–topographic variations (regional or local). Two changes in the slope of the semivariogram suggest the existence of two different scales of spatial variation. The interpolation map by Kriging of forest vegetation assemblages along the main coenocline shows a clear spatial distribution pattern of trees and shrubs in accordance with the spatial variation of significant environmental variables. We concluded that the multivariate geostatistical approach is a suitable technique for spatial analysis of forest systems employing data from national forest inventories based on a regular network of field plots. The development of an assortment of maps describing changes in vegetation assemblages and variation in environmental variables is expected to be a suitable tool for an integrated forest management and planning.     

Multivariate approach to the classification and ordination of the forest ecosystem of Nandiar valley western Himalayas

QuestionsDoes the vegetation composition of the forests of Nandiar Valley correlate with climatic, topographic and edaphic variables? Is it possible to identify plant communities through indicator species in relation to environmental gradients? Can this approach of classification and ordination will be helpful for conservation planning?LocationForests of Nandiar Valley, Moist temperate Western Himalayas Pakistan.MethodsEighty stands were selected for quantitative and qualitative characteristic of vegetation between an elevations of 525–3817 m. Species composition was recorded by using 400 m long transects. GPS, climatic, edaphic and topographic data were recorded for each sampling site. The relationship between habitat types, species composition and distribution along with climatic, edaphic and topographic variables were analyzed using TWINSPAN, Cluster analysis and DCA ordination.ResultsSum 325 vascular plants species belonging to 97 families were recorded. Diversity index and species richness was maximum in the moist temperate zone. Classification and ordination showed that the variance in species data was 7.07. Two-ways indicator species analysis classified the vegetation into eight plant communities. Indicator species analysis revealed that slope aspect, wind speed, temperature, dew point, wet bulb, pH, organic matter and phosphorous were the strongest parameters (p ≤ 0.05) determining plant community composition and indicator species in each habitat. The results also show the strength of the environment – species relationship using Monte Carlo procedures. DCA ordination grouped different species having similar habitat and habitats having common species.ConclusionsThe multivariate analysis of the vegetation along with environmental variables of Nandiar valley confirmed the indicators of each sort of vegetation communities/microclimatic zones which could further be used in conservation planning and management not only in studied area but also in the adjacent regions as well as in the areas exhibit similar sort of climatic, edaphic and topographic conditions.     

Spatio-temporal co-occurrence of cougars (Felis concolor), wolves (Canis lupus) and their prey during winter: a comparison of two analytical methods

Aims To examine the spatio‐temporal co‐occurrence of cougars (Felis concolor), wolves (Canis lupus), and their prey during winter using monthly (November–March) species–environment relationship models. In addition, to contrast predictions across two methods: logistic regression and Geographic Information System (GIS) image correlation. Location The eastern front ranges of the Canadian Rocky Mountains (south‐central Alberta), approximately 100 km west of Calgary, including portions of Banff National Park and Kananaskis Country. Methods Snow‐tracking data were collected simultaneously for cougars, wolves, elk (Cervus elaphus), and deer (Odocoileus virginianus and O. hemionus) between November and March, 1997–2000. Track data were synthesized in a GIS. Logistic regression and Akaike's information criterion (AIC) were used to select optimal environmental relationship models for each species. We first examined co‐occurrence by iteratively using each species as a dependent variable (presence/absence) in a logistic regression analysis and using all other species track‐density estimates as independent variables. We built predictive surfaces in a GIS using the exponent form of the logistic regression models, and assessed model accuracy with a receiver operating characteristic curve. We then re‐examined co‐occurrence using pairwise correlations of species probability surfaces by month. The correlation results were compared with logistic regression results to illuminate mechanisms of co‐occurrence and to investigate predictive consistency across the two methods. Results Cougars showed a trend in distribution from higher elevation and less rugged terrain in December, to lower elevation and more rugged terrain in March. This trend differed from that for wolves, which showed a more stable affinity for low elevation and less rugged valley bottoms across all months. The logistic regression models indicated variable positive and negative associations of cougars with wolves by month, and changes in prey associations over time. Notably, there was a shift in co‐occurrence for both predators from elk to deer in March. We found high predictive accuracy for all probability surfaces, except for the month of January. Our image comparison showed that spatial co‐occurrence amongst all species increased over winter, except that wolves and cougars were negatively correlated in February. Combining the results of each approach we found that cougars and wolves converged spatially over winter at the landscape scale (i.e. the valley), while showing more discrete use of that space over time and by habitat attributes (e.g. forest cover, topographic complexity, and prey track density). Main conclusions In the Rocky Mountains, the spatial distributions of cougars and wolves converged into the valley floor as winter progressed. Cougars were distinct from wolves and prey in the intensity of this shift. We determined that a comparison of predictive surfaces alone fails to explain species co‐occurrence. The surfaces must be coupled with investigation of respective species–environment models to account for temporal changes in associations. We suggest that the two approaches represent different ecological scales: image comparison may be best for landscape‐ (valley) level analysis, while logistic regression is best for site‐level analysis. Ultimately, both approaches were critical to our analysis. Finally, the variability observed over time suggested that annual and seasonal models may obscure important ecological patterns and processes, especially for cougars.     

Mapping Current and Potential Distribution of Non-Native Prosopis juliflora in the Afar Region of Ethiopia

We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m² spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km² in the Afar region (AUC  = 0.94), while the potential habitat for future infestations is 5,024 km² (AUC  = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.     

鄂尔多斯植被盖度分布与环境因素的关系

 从植被指数分布与气象因素、地质地层和地质水文的关系入手, 利用遥感解译和地理信息系统的空间分析功能, 分析了不同尺度下, 气候因素、地质水文因素、基质和地貌等对鄂尔多斯高原植被盖度分布的影响。指出: 在区域尺度上, 研究区植被盖度分布主要受降水影响, 植被盖度呈从东南到西北逐渐减少的趋势; 高盖度植被主要分布在冲洪积地貌和丘陵地貌区。局部分析, 库布齐沙漠东向延伸的存在与发展与区域型断层的存在有密切的联系; 毛乌素沙地中的高盖度植被分布受地形和基质岩性组合的综合影响, 主要分布在第四系湖积物和第四系冲积物等渗水性差的基质上, 尤其集中分布于凹陷的湖相沉积。