Abundance and diversity of small-bird assemblages in the Monte desert, Argentina

Assemblages of small bird species (<90 g body mass) from the Monte desert in Argentina were studied to analyze spatial and temporal variation in abundance and species richness. Mean species richness was higher during breeding season than in non-breeding season. The same pattern was observed in aerial insectivores, while granivores and substrate insectivores did not differ between breeding and non-breeding seasons. Overall bird abundance was similar across seasons. Species richness was positively correlated with bird abundance and negatively correlated with dominance; bird abundance and dominance were not correlated. These patterns could be explained by distinct responses of functional groups of birds; dominant species were granivores in the non-breeding season and aerial insectivores during the breeding season, and bird abundance in functional groups changed according to food supply. Most species are residents or regular migrants, while there are few nomadic and transient species. Predictable annual fluctuations in rainfall and resource availability should favor a migratory strategy more than nomadic movements. Similarly, breeding is strongly seasonal and most species start breeding when the first summer rains have generally not yet fallen. Finally, concordances in assemblage structure at local and regional scale suggest that similar mechanisms are acting on the local bird assemblages across the Monte.     

Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression

Scientific interpretation of the relationships between agricultural landscape patterns and urbanization is important for ecological planning and management. Ordinary least squares (OLS) regression is the primary statistical method in previous studies. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between several urbanization indicators (urbanization intensity index, distance to urban centers and distance to road) and changes in metrics describing agricultural landscape patterns (total area, patch density, perimeter area ratio distribution and aggregation index) at two block scales (5 km and 10 km). Results denoted that GWR was more powerful than OLS in interpreting relationships between agricultural landscape patterns and urbanization, since GWR was characterized by higher adjust R², lower Akaike Information Criterion values and reduced spatial autocorrelations in model residuals. Character and strength of the relationships identified by GWR varied spatially. In addition, GWR results were scale-dependent and scale effects were particularly significant in three aspects: kernel bandwidth of weight determination, block scale of pattern analysis, and window size of local variance analysis. Homogeneity and heterogeneity in the relationships between agricultural landscape patterns and urbanization were subject to the coupled influences of the three scale effects. We argue that the spatially varying relationships between agricultural landscape patterns and urbanization are not accidental but nearly universal. This study demonstrated that GWR has the potential to provide references for ecological planners and managers to address agricultural landscapes issues at all scales.     

Patterns of plant diversity in ironstone ranges in arid south western Australia

Patterns of plant diversity were examined across 24 ironstone ranges in arid south western Australia. The high levels of beta diversity displayed between ranges primarily resulted from high turnover of perennial species and was not influenced by the lower species richness on the more arid ranges. The variance in composition of the vegetation across the ranges was evenly distributed between the broad spatial pattern and environmental factors measuring climate gradients, local site variables and soil chemistry. In contrast broad scale spatial and climatic gradients were most important in explaining the variance in perennial species richness. Ranges along the boundary of the Arid Zone appear to have acted as refugia during the climatic cycles of the Tertiary with several hotspots of species endemism and taxa with distributions centered on these ranges. On the more arid ranges these specialist ironstone taxa are largely absent. The variation in richness of these specialists taxa was strongly influenced by patterns in soil chemistry in addition to the broad scale spatial and climate gradients. The concentration of the ironstone specialist taxa is largely coincidental with the most prospective areas for iron ore mining and this will provide considerable challenges in conserving these unique ecosystems.     

Exploring spatially varying and scale-dependent relationships between soil contamination and landscape patterns using geographically weighted regression

Landscape pattern is an important determinant of soil contamination at multiple scales, and a proper understanding of their relationship is essential for alleviating soil contamination and making decisions for land planners. Both soil contamination and landscape patterns are heterogeneous across spaces and scale-dependent, but most studies were carried out on a single scale and used the conventional multivariate analyses (e.g. correlation analysis, ordinary least squared regression-OLS) that ignored the issue of spatial autocorrelation. To move forward, this paper examined spatially varying relationships between agricultural soil trace metal contamination and landscape patterns at three block scales (i.e. 5 km × 5  km, 10 km × 10 km, 15 km × 15 km) in the Pearl River Delta (PRD), south China, using geographically weighted regression (GWR). This paper found that GWR performed better than OLS in terms of increasing R square of the model, lowering Akaike Information Criterion values and reducing spatial autocorrelation. GWR results revealed great spatial variations in the relationships across scales, with an increasing explanatory power of the model from small to large block scales. Despite a few negative correlations, more positive correlations were found between soil contamination and different aspects of landscape patterns of water, urban land and the whole landscape (i.e. the proportion, mean patch area, the degree of landscape fragmentation, landscape-level structural complexity, aggregation/connectivity, road density and river density). Similarly, more negative correlations were found between soil contamination and landscape patterns of forest and the distance to the river and industry land (p < 0.05). Furthermore, most significant correlations between soil contamination and landscape variables occurred in the western PRD across scales, which could be explained by the prevailing wind, the distribution of pollutant sources and the pathway of trace metal inputs.     

Habitat selection and partitioning of the Black-bellied Sandgrouse (Pterocles orientalis), the Stone Curlew (Burhinus oedicnemus) and the Cream-coloured Courser (Cursorius cursor) in arid areas of North Africa

Niche theory predicts that coexisting species with similar trophic requirements should demonstrate resource partitioning, particularly where resources are scarce. Conversely, this is not expected between species that do not share primary resources. This study analyses the patterns of spatial coexistence and habitat selection, on two spatial scales, of three species of semidesert regions in Morocco: the Black-bellied Sandgrouse (Pterocles orientalis), the Stone Curlew (Burhinus oedicnemus) and the Cream-coloured Courser (Cursorius cursor). Co-occurrence analysis results point to between-species segregation on a macrohabitat scale. Hotelling's T test of the species-presence data showed a pattern of macrohabitat selection that diverged from habitat availability for the three species with differences among them. Both the classification tree and the pattern of microhabitat selection obtained by model averaging showed scant overlap between the Sandgrouse and the Courser, suggesting habitat partitioning between them on a fine scale. Our results confirm spatial segregation of the three species, especially between species with different trophic strategies: the Sandgrouse versus the Stone Curlew and the Courser. The latter two species were best segregated on a microhabitat scale, supporting the conclusions that macro- and microhabitat selection are major factors in bird community configuration in arid ecosystems and contributing to reduce potential competition.     

Grazing effects on patchy dryland vegetation in northern Patagonia

In this study the spatial patterns and dynamics of vegetation patches along a grazing gradient in the steppe ofLarrea divaricataandStipaspp. in NE Patagonia (Argentina) are described. A general effect of grazing is the reduction of total plant cover resulting from the decrease in cover of perennial grasses (Stipa speciosa, Poa ligularis, Stipa tenuis) and some tall shrubs (Chuquiraga hystrix, Bougainvillea spinosa, Lycium chilense). Dwarf shrubs (Nassauvia fueguianaandJunellia seriphioides) increase their cover under medium and/or high grazing pressures. Plant species are spatially grouped into patches which alternate with areas of bare soil. Eleven types of vegetation patch differing in the dominant plant functional type or species, floristic richness and size were identified with different relative frequency along the grazing gradient. Based on these results, it is postulated that grazing forces the replacement of large patches dominated by tall shrubs with high species richness, byLarrea divaricatapatches or small dwarf shrub patches with low species richness and the extinction of grass patches. This results from: (1) disruption of local balances of species deletions and additions; (2) fragmentation of large patches; and (3) formation of new vegetation patches. These changes lead to differing plant spatial organization and heterogeneity along the grazing gradient which may be described by characteristic arrays of vegetation patches.     

Exploring population spatial concentrations in Northern Ireland by community background and other characteristics: an application of geographically weighted spatial statistics

Information on how populations are spatially concentrated by different characteristics is a key means of guiding government policies in a variety of contexts, in addition to being of substantial academic interest. In particular, to reduce inequalities between groups, it is necessary to understand the characteristics of these groups in terms of their composition and their geographical structure. This article explores the degree to which the population of Northern Ireland is spatially concentrated by a range of characteristics. There is a long history of interest in residential segregation by religion in Northern Ireland; this article assesses population concentration not only by community background (‘religion or religion brought up in’) but also by housing tenure, employment and other socioeconomic and demographic characteristics. The spatial structure of geographical variables can be captured by a range of spatial statistics including Moran's I. Such approaches utilise information on connections between observations or the distances between them. While such approaches are conceptually an improvement on standard aspatial statistics, a logical further step is to compute statistics on a local basis on the grounds that most real-world properties are not spatially homogenous and, therefore, global measures may mask much variation. In population geography, which provides the substantive focus for this article, there are still relatively few studies that assess in depth the application of geographically weighted statistics for exploring population characteristics individually and for exploring relations between variables. This article demonstrates the value of such approaches by using a variety of geographically weighted statistical measures to explore outputs from the 2001 Census of Population of Northern Ireland. A key objective is to assess the degree to which the population is spatially divided, as judged by the selected variables. In other words, do people cluster more strongly with others who share their community background or others who have a similar socioeconomic status in some respect? The analysis demonstrates how geographically weighted statistics can be used to explore the degree to which single socioeconomic and demographic variables and relations between such variables differ at different spatial scales and at different geographical locations. For example, the results show that there are regions comprising neighbouring areas with large proportions of people from the same community background, but with variable unemployment levels, while in other areas the first case holds true but unemployment levels are consistently low. The analysis supports the contention that geographical variations in population characteristics are the norm, and these cannot be captured without using local methods. An additional methodological contribution relates to the treatment of counts expressed as percentages.     

Temporal and spatial patterns of tenebrionid beetle diversity in NW Patagonia, Argentina

Spatial and temporal variation in abundance, richness and composition of Tenebrionidae beetle assemblages were described for north-western Patagonia. Beetles were collected using 450 pitfall traps arranged in 50 plots across an area of about 22,500 km² representative of the Subantarctic-Patagonian transition of Argentina. The study area included three different habitats: forest, scrub, and steppe. Beetles were trapped at five, eight day sampling periods in spring-summer between November 2004 and March 2006. A total of 30 species and 938 individuals were collected. Total abundance was higher in November and January than in March, and species richness did not change among samplings. Species richness was greater in the steppe than scrub. Assemblages differed between the northern and southern transects. There was little correlation between the measured environmental variables and species composition. Historical factors might explain the observed patterns, but other environmental variables such as soil characteristics may be more informative in explaining the present distribution of tenebrionid species.     

Relationship between species richness of small mammals and primary productivity of arid and semi-arid grasslands in north China

We studied the relationship between primary productivity and species richness of small mammals at both large and small spatial scales in the arid and semi-arid grasslands of north China. The productivity (x)–species richness (y) pattern at a large spatial scale can be described by a unimodal quadratic regression curve (y=7·41+0·1^*x−0·0003^*x²,p =0·008, r²=0·788). At a small spatial scale, however, neither linear nor quadratic regression fit the data for 1980 and 1994 (p>0·25). Primary productivity may not be an appropriate predictor of the species richness of small mammals at a small spatial scale. We conclude, therefore, that the primary productivity–species richness pattern of small mammals may be scale-dependent in the arid and semi-arid grasslands of north China. Landscape complexity should be considered in future studies of productivity–richness relationships.     

Functional ecology of a narrow endemic plant and a widespread congener from semiarid Spain

We compared physiological and morphological traits of Thymus loscosii, a rare endemic of semiarid Spain, and Thymus vulgaris, a widespread Mediterranean species, over a precipitation gradient, and measured the spatial patterns of both species. Our results do not provide evidence for a congruent suite of traits associated with rarity in T. loscosii, since this species showed some traits reported in rare species (lower height and biomass), but exhibited better performance under severe climatic conditions (higher photochemical efficiency and quantum yield during winter) and higher values of traits conferring competitive abilities (SLA and LAR). T. loscosii did not show either lower phenotypic variability or better performance than its congener along the precipitation gradient. The two thymes were spatially dissociated when they co-occurred and the spatial pattern of T. loscosii changed from clumped in the presence of its congener to random when it was the only thyme, suggesting competition between the two species. These results suggest that T. loscosii is not a habitat-specialist and may behave as a refuge endemic. Its reduced distribution may be linked to a limited competitive ability that is not associated with the vegetative traits explored, although other causes like habitat degradation and genetic or reproductive constraints might also be important to explain its limited distribution.     

Spatial structure analysis of a reptile community with airborne LiDAR data

The analysis of the spatial structure of animal communities requires spatial data to determine the distribution of individuals and their limiting factors. New technologies like very precise GPS as well as satellite imagery and aerial photographs of very high spatial resolution are now available. Data from airborne LiDAR (Light Detection and Ranging) sensors can provide digital models of ground and vegetation surfaces with pixel sizes of less than 1 m. We present the first study in terrestrial herpetology using LiDAR data. We aim to identify the spatial patterns of a community of four species of lizards (Lacerta schreiberi, Timon lepidus, Podarcis bocagei, and P. hispanica), and to determine how the habitat is influencing the distribution of the species spatially. The study area is located in Northern Portugal. The position of each lizard was recorded during 16 surveys of 1 h with a very precise GPS (error < 1 m). LiDAR data provided digital models of surface, terrain, and normalised height. From these data, we derived slope, ruggedness, orientation, and hill-shading variables. We applied spatial statistics to determine the spatial structure of the community. We computed Maxent ecological niche models to determine the importance of environmental variables. The community and its species presented a clustered distribution. We identified 14 clusters, composed of 1–3 species. Species records showed two distribution patterns, with clusters associated with steep and flat areas. Cluster outliers had the same patterns. Juveniles and subadults were associated with areas of low quality, while sexes used space in similar ways. Maxent models identified suitable habitats across the study area for two species and in the flat areas for the other two species. LiDAR allowed us to understand the local distributions of a lizard community. Remotely sensed data and LiDAR are giving new insights into the study of species ecology. Images of higher spatial resolutions are necessary to map important factors such as refuges.     

水热条件共同驱动新疆湿地植物丰富度空间分布格局

在地理空间尺度上,气候因素（如热量、降水量等）一直被认为是物种多样性的主要驱动因素。然而,气候因素能否解释湿地植物多样性格局仍不清楚。研究探讨了环境因素尤其水分和热量条件对湿地物种分布的影响,具体包括经度、纬度、海拔、年平均降水量、年平均气温、年平均蒸发量和年平均日照时数总计7个指标,研究对象涉及新疆3个二级流域的26处湿地公园,应用结构方程模型分析了各指标对湿地植物丰富度影响的相对大小及其相互作用关系。另外,还利用莫兰指数（Moran’s I）对各变量残差进行了空间相关性分析,以评估空间相关性的影响。结果表明：（1）结构方程模型总计解释了41.8%的物种丰富度变异,以年平均降水量对物种丰富度总效应最高,为0.47,其次是年平均日照时数,为-0.42,其中年平均降水量为正效应,年平均日照时数为负效应。其他各指标对物种丰富度的效应均不显著。（2）年平均降水量对植物丰富度的影响主要表现为直接效应,占总效应的92.86%,年平均日照时数对植物丰富度的影响主要是间接效应,占总效应的54.76%。（3）空间相关性分析表明年平均降水量和年平均日照时数的残差均不存在空间相关性,莫兰指数在-0.15～...     

Relationship between landscape heterogeneity and plant species richness on the Mexican Pacific coast

The present study aims to use landscape heterogeneity as a predictor of plant species richness in a tropical dry landscape area in the coast of Michoacán, Mexico. To understand the relationship between species richness and landscape, a three-step approach was followed: first, landscape spatial heterogeneity was measured by classifying landscape types according to their attributes (i.e., environmental, soil and topographic variables). Second, several diversity standard indices were used to explore biological diversity and to select the best one explaining the relationship between landscape heterogeneity and plant species richness, for this study area. Third, from the obtained results it was possible to calculate biodiversity values on the basis of landscape heterogeneity. The results indicate that it is possible to predict more than 61% of species richness through an indicator of landscape heterogeneity (H′; Shannon–Weaver diversity index). This procedure may be useful in terms of land use, conservation, and management of protected areas, mainly in areas with high biodiversity but with limited biological data, since it allows to obtain an approximation of the spatial distribution of species richness, even with scarce biological information.     

Effects of dune stabilization on vegetation characteristics and soil properties at multiple scales in Horqin Sandy Land, Northern China

Ecological patterns and processes in dune ecosystems have been a research focus in recent years, however information on how dune stabilization influences vegetation and soil at different spatial scales...     

The temporal and spatial relationship between NDVI and climatological parameters in Colorado

This paper describes the spatial and temporal relationship between AVHRR/NDVI (Normalized Difference Vegetation Index) and climatological parameters (temperature and precipitation), which, in some sense, is influenced by topographical factors and land-cover types in Colorado. The correlation coefficients and partial correlation coefficients have been computed pixel by pixel over Colorado in order to analyze the relationship. The temporal variation and correlation of AVHRR/NDVI, temperature and precipitation were analyzed with a sampling method. The study reveals that there exists a close correspondence between monthly NDVI and temperature, which has strong impact from temperature on the changes of NDVI in Colorado. The spatial changes of NDVI are not influenced obviously by the precipitation since these two variables are different from each other in time series in Colorado. The study clearly revealed the spatial variation and its distribution patterns of relationship between NDVI and climatic parameters (temperature and precipitation) in Colorado.     

The temporal and spatial relationship between NDVI and climatological parameters in Colorado

1 Introduction In recent years, many researchers have demonstrated that there are essential and evident correlations between NDVI and climatological parameters (temperature and precipitation). The analysis of correlation between climate forces and time-integrated NDVI over US Northern and Central Great Plains suggested that spatial and temporal variation of precipitation and potential evapotranspiration and growing degree days in growing season are the most important control on grassland…     

洪河自然保护区湿地主要植被类型物种多样性与表层土壤性质的相关性研究

对洪河湿地主要植被类型物种多样性特征、土壤性质特征及二者之间的相互关系进行了研究。结果表明:按沼泽—沼泽化草甸—湿草甸—灌丛草甸—岛状林的序列,物种丰富度呈逐渐增加的变化格局,物种多样性、均匀度呈先下降后上升的格局,优势度呈先上升后下降的格局;而土壤性质特征则呈不规则变化格局。植物物种多样性与土壤性质之间只有均匀度与速效氮之间存在着极显著正相关,其他均无显著相关。这说明在洪河湿地,土壤性质不是决定上述序列的植被类型的物种多样性的主要因素,而土壤速效氮含量是影响物种均匀度的关键因素,同时,对其他物种多样性特征也有一定影响。     

Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging

Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R² for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected.     

我国省域创新产出的空间特征和时空演化——基于探索性空间数据分析的实证

以我国31个省域作为空间观测单元,以专利申请受理数作为创新产出的衡量指标,对我国1997～2008年期间省域创新产出的空间分布进行了探索性空间数据分析(ESDA)。通过计算区位基尼系数和集中度指数,发现我国的创新活动显示了相当高水平的空间集中,并且这种集中程度在过去的十多年里表现出了稳定的增长趋势;对全局的Moran’s I统计分析表明:省际创新活动之间存在着显著的空间自相关(空间依赖性),证明了知识溢出的存在性和空间局限性;对局部的Moran’s I分析进一步揭示了省际创新活动水平的相关模式,Moran散点图刻画了创新活动的空间集聚模式及其时空演变态势。研究结果说明经过十几年的发展,我国省域创新活动的地域性特征十分显著。     

广州南沙湿地公园鸟类2014—2018年际动态及其对生境变化的响应

为了解广州南沙湿地鸟类迁徙规律,揭示鸟类整体迁徙动态变化,于2014年1月至2018年12月,连续在每月下旬日落前3 h采用样点法和样线法对南沙湿地公园鸟类群落多样性进行调查。结果显示：1) 2014—2018年共记录到鸟类139种,以冬候鸟为主。2）鸟类物种数年际波动较大,丰富度年际变化不明显,即鸟类种类在逐渐增加的同时,个体数量趋于稳定。3）鸟类月度变化呈现明显的候鸟迁徙规律,越冬期急速上升,繁殖期平缓。越冬水鸟迁飞时间有提前的趋势,且在富有食物来源的浅水滩涂地和在无瓣海桑等高大茂盛的红树林群落有更多种类与数量的水鸟分布。最后,建议在注重绿化连续性和整体性的同时,保护和管理鸟类的栖息环境,适当扩大滩涂地面积,增加红树林种植面积以及合理地围垦,科学维持浅水滩涂和红树林种植面积比例,吸引更多越冬候鸟。