Modelling avian biodiversity using raw,unclassified satellite imagery

Applications of remote sensing for biodiversity conservation typically rely on image classifications that do not capture variability within coarse land cover classes. Here, we compare two measures derived from unclassified remotely sensed data, a measure of habitat heterogeneity and a measure of habitat composition, for explaining bird species richness and the spatial distribution of 10 species in a semi-arid landscape of New Mexico. We surveyed bird abundance from 1996 to 1998 at 42 plots located in the McGregor Range of Fort Bliss Army Reserve. Normalized Difference Vegetation Index values of two May 1997 Landsat scenes were the basis for among-pixel habitat heterogeneity (image texture), and we used the raw imagery to decompose each pixel into different habitat components (spectral mixture analysis). We used model averaging to relate measures of avian biodiversity to measures of image texture and spectral mixture analysis fractions. Measures of habitat heterogeneity, particularly angular second moment and standard deviation, provide higher explanatory power for bird species richness and the abundance of most species than measures of habitat composition. Using image texture, alone or in combination with other classified imagery-based approaches, for monitoring statuses and trends in biological diversity can greatly improve conservation efforts and habitat management.     

Can we predict butterfly diversity along an elevation gradient from space?

An important challenge in ecology is to predict patterns of biodiversity across eco‐geographical gradients. This is particularly relevant in areas that are inaccessible, but are of high research and conservation value, such as mountains. Potentially, remotely‐sensed vegetation indices derived from satellite images can help in predicting species diversity in vast and remote areas via their relationship with two of the major factors that are known to affect biodiversity: productivity and spatial heterogeneity in productivity. Here, we examined whether the Normalized Difference Vegetation Index (NDVI) can be used effectively to predict changes in butterfly richness, range size rarity and beta diversity along an elevation gradient. We examined the relationship between butterfly diversity and both the mean NDVI within elevation belts (a surrogate of productivity) and the variability in NDVI within and among elevation belts (surrogates for spatial heterogeneity in productivity). We calculated NDVI at three spatial extents, using a high spatial resolution QuickBird satellite image. We obtained data on butterfly richness, rarity and beta diversity by field sampling 100 m quadrats and transects between 500 and 2200 m in Mt Hermon, Israel. We found that the variability in NDVI, as measured both within and among adjacent elevation belts, was strongly and significantly correlated with butterfly richness. Butterfly range size rarity was strongly correlated with the mean and the standard deviation of NDVI within belts. In our system it appears that it is spatial heterogeneity in productivity rather than productivity per se that explained butterfly richness. These results suggest that remotely‐sensed data can provide a useful tool for assessing spatial patterns of butterfly richness in inaccessible areas. The results further indicate the importance of considering spatial heterogeneity in productivity along elevation gradients, which has no lesser importance than productivity in shaping richness and rarity, especially at the local scale.     

Different responses of avian feeding guilds to spatial and environmental factors across an elevation gradient in the central Himalaya

Although elevational patterns of species richness have been well documented, how the drivers of richness gradients vary across ecological guilds has rarely been reported. Here, we examined the effects of spatial factors (area and mid‐domain effect; MDE) and environmental factors, including metrics of climate, productivity, and plant species richness on the richness of breeding birds across different ecological guilds defined by diet and foraging strategy. We surveyed 12 elevation bands at intervals of 300 m between 1,800 and 5,400 m a.s.l using line‐transect methods throughout the wet season in the central Himalaya, China. Multiple regression models and hierarchical partitioning were used to assess the relative importance of spatial and environmental factors on overall bird richness and guild richness (i.e., the richness of species within each guild). Our results showed that richness for all birds and most guilds displayed hump‐shaped elevational trends, which peaked at an elevation of 3,300–3,600 m, although richness of ground‐feeding birds peaked at a higher elevation band (4,200–4,500 m). The Normalized Difference Vegetation Index (NDVI)—an index of primary productivity—and habitat heterogeneity were important factors in explaining overall bird richness as well as that of insectivores and omnivores, with geometric constraints (i.e., the MDE) of secondary importance. Granivore richness was not related to primary production but rather to open habitats (granivores were negatively influenced by habitat heterogeneity), where seeds might be abundant. Our findings provide direct evidence that the richness–environment relationship is often guild‐specific. Taken together, our study highlights the importance of considering how the effects of environmental and spatial factors on patterns of species richness may differ across ecological guilds, potentially leading to a deeper understanding of elevational diversity gradients and their implications for biodiversity conservation.     

Geostatistical modelling of regional bird species richness: exploring environmental proxies for conservation purpose

Identifying spatial patterns in species diversity represents an essential task to be accounted for when establishing conservation strategies or monitoring programs. Predicting patterns of species richness by a model-based approach has recently been recognised as a significant component of conservation planning. Finding those environmental predictors which are related to these patterns is crucial since they may represent surrogates of biodiversity, indicating in a fast and cheap way the spatial location of biodiversity hotspots and, consequently, where conservation efforts should be addressed. Predictive models based on classical multiple linear regression or generalised linear models crowded the recent ecological literature. However, very often, problems related with spatial autocorrelation in observed data were not adequately considered. Here, a spatially-explicit data-set on birds presence and distribution across the whole Tuscany region was analysed. Species richness was calculated within 1 × 1 km grid cells and 10 environmental predictors (e.g. altitude, habitat diversity and satellite-derived landscape heterogeneity indices) were included in the analysis. Integrating spatial components of variation with predictive ecological factors, i.e. using geostatistical models, a general model of bird species richness was developed and used to obtain predictive regional maps of bird diversity hotspots. A meaningful subset of environmental predictors, namely habitat productivity, habitat heterogeneity, combined with topographic and geographic information, were included in the final geostatistical model. Conservation strategies based on the predicted hotspots as well as directions for increasing sampling effort efficiency could be extrapolated by the proposed model.     

Geographical patterns of persistence in duck guilds

Geographical gradients of persistence in community structure have been suggested to be causally related to underlying gradients of species diversity, environmental variability and/or productivity. In order to test whether the persistence of breeding duck communities was dependent on any one of these three factors, thirty-three years of census data from the Canadian prairie and boreal forest regions was examined along geographical gradients of wetland habitat variability and productivity. For breeding ducks, locally derived patterns of persistence were generally independent of local habitat conditions. Persistence appeared to be related more to patterns of emigration and immigration in response to climatic conditions (i.e., drought) in the southern prairies than to local species richness, wetland habitat variability or productivity. It is suggested, therefore, that analyses of community persistence derived at small spatial scales may be of limited value if the structure of communities is not regulated by local conditions.     

Elevational gradients in species abundance,assemblage structure and energy use of rainforest birds in the Australian Wet Tropics bioregion

Elevational patterns of species richness, local abundance and assemblage structure of rainforest birds of north‐eastern Australia were explored using data from extensive standardized surveys throughout the region. Eighty‐two species of birds were recorded with strong turnover in assemblage structure across the elevational gradient and high levels of regional endemism in the uplands. Both species richness and bird abundance exhibited a humped‐shaped pattern with elevation with the highest values being between 600 and 800 m elevation. While much of the variability in species richness could be explained by the species–area relationship, analyses of net primary productivity (NPP) and total daily energy consumption of the bird community (energy use) suggest that ecosystem energy flow or constraints may be a significant determinant of species richness. Species richness is positively correlated with local bird abundance which itself is closely related to total energy use of the bird community. We suggest the hypothesis that lower NPP limits bird abundance and energy use in the uplands (>500 m) and that low bird energy use and species richness in the lowlands is limited by a seasonal bottleneck in available primary productivity and/or a species pool previously truncated by an extinction filter imposed by the almost complete disappearance of rainforest in the lowlands during the glacial maxima. We suggest that some of the previously predicted impacts of global warming on biodiversity in the uplands may be partially ameliorated by increases in NPP because of increasing temperatures. However, these relationships are complex and require further data specifically in regard to direct estimates of primary productivity and detailed estimates of energy flow within the assemblage.     

Does climate determine broad‐scale patterns of species richness? A test of the causal link by natural experiment

Aim Broad‐scale spatial patterns of species richness are very strongly correlated with climatic variables. If there is a causal link, i.e. if climate directly or indirectly determines patterns of richness, then when the climatic variables change, richness should change in the manner that spatial correlations between richness and climate would predict. The present study tests this prediction using seasonal changes in climatic variables and bird richness. Location We used a grid of equal area quadrats (37 000 km²) covering North and Central America as far south as Nicaragua. Methods Summer and winter bird distribution data were drawn from monographs and field guides. Climatic data came from published sources. We also used remotely sensed NDVI (normalized difference vegetation index — a measure of greenness). Results Bird species richness changes temporally (between summer and winter) in a manner that is close to, but statistically distinguishable from, the change one would predict from models relating the spatial variation in richness at a single time to climatic variables. If one further takes into account the seasonal changes in NDVI and within‐season variability of temperature and precipitation, then winter and summer richness follow congruent, statistically indistinguishable patterns. Main conclusions Our results are consistent with the hypothesis that climatic variables (temperature and precipitation) and vegetation cover directly or indirectly influence patterns of bird species richness.     

Dissecting NDVI–species richness relationships in Hawaiian dry forests

Aim A growing body of research has used the normalized difference vegetation index (NDVI) as a proxy for productivity to predict species richness. Yet the mechanisms that produce the relationship between NDVI and species richness remain unclear because of correlated biotic and abiotic factors that influence NDVI. In this study we investigated different biotic and abiotic effects that potentially drive plant species richness–productivity relationships. Location Hawaiian Islands, USA. Methods We quantified woody plant species richness, structure (density, basal area and canopy height), and species composition along a precipitation gradient of 14 Hawaiian dry forest plots. We then used structural equation models combined with 10 years of satellite data to disentangle the effects of precipitation, structure and NDVI‐estimated productivity on species richness. Results Underlying the simple correlation between NDVI and species richness was the indirect effect of precipitation and direct effect of forest structure. The best‐fit model showed there was no direct effect of NDVI on species richness. Main conclusions Our results demonstrate that complex relationships drive simple correlations between species richness and productivity. Considering the mechanisms and underlying factors driving NDVI–species richness relationships could improve predictions of species diversity as satellite measures of productivity have an increasingly important role in habitat mapping, species distribution modelling and predictions for global change.     

The effect of energy and seasonality on avian species richness and community composition

We analyzed geographic patterns of richness in both the breeding and winter season in relation to a remotely sensed index of seasonal production (normalized difference vegetation index [NDVI]) and to measures of habitat heterogeneity at four different spatial resolutions. The relationship between avian richness and NDVI was consistent between seasons, suggesting that the way in which available energy is converted to bird species is similar at these ecologically distinct times of year. The number and proportion of migrant species in breeding communities also increased predictably with the degree of seasonality. The NDVI was a much better predictor of seasonal richness at finer spatial scales, whereas habitat heterogeneity best predicted richness at coarser spatial resolutions. While we find strong support for a positive relationship between available energy and species richness, seasonal NDVI explained at most 61% of the variation in richness. Seasonal NDVI and habitat heterogeneity together explain up to 69% of the variation in richness.     

宏生态尺度上景观破碎化对物种丰富度的影响

生物多样性的地理格局及其形成机制是宏生态学与生物地理学的研究热点。大量研究表明,景观尺度上的生境破碎化对物种多样性的分布格局具有重要作用,但目前尚不清楚这种作用是否足以在宏生态尺度上对生物多样性地理格局产生显著影响。利用中国大陆鸟类和哺乳动物的物种分布数据,在100 km×100 km网格的基础上生成了这两个类群生物的物种丰富度地理格局,进一步利用普通最小二乘法模型和空间自回归模型研究了物种丰富度与气候、生境异质性、景观破碎化的相关关系。结果表明,景观破碎化因子与鸟类和哺乳动物的物种丰富度都具有显著的关联关系,其方差贡献率可达约30%—50%(非空间模型)和60%—80%(空间模型),略低于或接近于气候和生境异质性因子。方差分解结果显示,景观破碎化因子与气候和生境异质性因子的方差贡献率的重叠部分达20%—40%。相对鸟类而言,景观破碎化对哺乳动物物种丰富度的地理格局具有更高的解释率。     

Global macroecology of bird assemblages in urbanized and semi‐natural ecosystems

Aim Despite the increasing pace of urbanization, little is known about how this process affects biodiversity globally. We investigate macroecological patterns of bird assemblages in urbanized areas relative to semi‐natural ecosystems. Location World‐wide. Methods We use a database of quantitative bird surveys to compare key assemblage structure parameters for plots in urbanized and semi‐natural ecosystems controlling for spatial autocorrelation and survey methodology. We use the term ‘urbanized’ instead of ‘urban’ ecosystems as many of the plots were not located in the centre of towns but in remnant habitat patches within conurbations. Results Some macroecological relationships were conserved in urbanized landscapes. Species–area, species–abundance and species–biomass relationships did not differ significantly between urbanized and non‐urbanized environments. However, there were differences in the relationships between productivity and assemblage structure. In forests, species richness increased with productivity; in both forests and open habitats, the evenness of species abundances declined as productivity increased. Among urbanized plots, instead, both species richness and the evenness of species abundances were independent of variation in productivity. Main conclusions Remnant habitats within urbanized areas are subject to many ecological alterations, yet key macroecological patterns differ remarkably little in urbanized versus non‐urbanized plots. Our results support the need for increased conservation activities in urbanized landscapes, particularly given the additional benefits of local experiences of biodiversity for the human population. With increasing urbanization world‐wide, broad‐scale efforts are needed to understand and manage the effects of this driver of change on biodiversity.     

Patterns of herbivore species richness in Kenya and current ecoclimatic stability

The increased attention to biodiversity worldwide has stimulatedinterest in understanding biophysical factors associated with indicators ofbiodiversity such as species richness. Although levels of biodiversity may seemto be equivalent in different areas, high species richness may be caused byaccumulation of species over a long time in places where environmentalconditions remained stable and predictable. The advanced very high resolutionradiometer (AVHRR)–normalized difference vegetation index (NDVI) has beenestablished to be a good proxy for studying interannual climate variability aswell as regional drought condition. In this study, I examined the relationshipbetween large herbivore species richness and AVHRR–NDVI derivedclimatic-variability indices, interannual average NDVI and coefficient ofvariation of NDVI at a regional spatial scale in Kenya. Regions with a relativelylow coefficient of variation of NDVI and high interannual average NDVIcharacterize current ecoclimatic stability. By contrast, a high coefficient ofvariation of NDVI and relatively low interannual average NDVI characterizeecoclimatic instability (drought risk). Statistical analyses revealed that a highinterannual average NDVI increases species richness, whereas a high coefficient ofvariation of NDVI lowers species richness. This indicates that maximum numbers ofspecies are found in regions with current ecoclimatic stability. Understandingsuch relationships can help in explaining spatial distribution of speciesrichness and predicting global changes resulting from human impacts on theenvironment.     

Perennial Agroenergy Feedstocks as En Route Habitat for Spring Migratory Birds

Increased production of bioenergy crops in North America is projected to exacerbate already heavy demands upon existing agricultural landscapes with potential to impact biodiversity negatively. Grassland specialist birds are an imperilled avifauna for which perennial-based, next-generation agroenergy feedstocks may provide suitable habitat. We take a multi-scaled spatial approach to evaluate the ability of two candidate second-generation agroenergy feedstocks (switchgrass, Panicum virgatum, and mixed grass–forb plantings) to act as spring migratory stopover habitat for birds. In total, we detected 35 bird species in mixed grass–forb plantings and switchgrass plantings, including grassland specialists and species of state and national conservation concern (e.g., Henslow’s Sparrow, Ammodramus henslowii). Some evidence indicated that patches with higher arthropod food availability attracted a greater diversity of migrant bird species, but species richness, total bird abundance, and the abundance of grassland specialist species were similar in fields planted with either feedstock. Species richness per unit area (species density) was relatively higher in switchgrass fields. The percent land cover of forest in landscapes surrounding study fields was negatively associated with bird species richness and species density. Habitat patch size and within-patch vegetation structure were unimportant in predicting the diversity or abundance of spring en route bird assemblages. Our results demonstrate that both switchgrass and mixed grass–forb plantings can attract diverse assemblages of migrant birds. As such, industrialized production of these feedstocks as agroenergy crops has the potential to provide a source of en route habitat for birds, particularly where fields are located in relatively unforested landscapes. Because industrialization of cellulosic biomass production will favor as yet unknown harvest and management regimes, predicting the ultimate value of perennial-based biomass plantings for spring migrants remains difficult.     

Predator Assemblage Structure and Temporal Variability of Species Richness and Abundance in Forests of High Tree Diversity

Predators significantly affect ecosystem functions, but our understanding of to what extent findings can be transferred from experiments and low‐diversity systems to highly diverse, natural ecosystems is limited. With a particular threat of biodiversity loss at higher trophic levels, however, knowledge of spatial and temporal patterns in predator assemblages and their interrelations with lower trophic levels is essential for assessing effects of trophic interactions and advancing biodiversity conservation in these ecosystems. We analyzed spatial and temporal variability of spider assemblages in tree species‐rich subtropical forests in China, across 27 study plots varying in woody plant diversity and stand age. Despite effects of woody plant richness on spider assemblage structure, neither habitat specificity nor temporal variability of spider richness and abundance were influenced. Rather, variability increased with forest age, probably related to successional changes in spider assemblages. Our results indicate that woody plant richness and theory predicting increasing predator diversity with increasing plant diversity do not necessarily play a major role for spatial and temporal dynamics of predator assemblages in such plant species‐rich forests. Diversity effects on biotic or abiotic habitat conditions might be less pronounced across our gradient from medium to high plant diversity than in previously studied less diverse systems, and bottom‐up effects might level out at high plant diversity. Instead, our study highlights the importance of overall (diversity‐independent) environmental heterogeneity in shaping spider assemblages and, as indicated by a high species turnover between plots, as a crucial factor for biodiversity conservation at a regional scale in these subtropical forests.     

Primary productivity and species richness: relationships among functional guilds, residency groups and vagility classes at multiple spatial scales

One of the major determinants of species richness is the amount of energy available, often measured as primary productivity. Heterogeneity of environmental variables has also been found to influence species richness. Predicting species distributions across landscapes and identifying areas that have high species richness, or vulnerable groups of species, is useful for land management. Remotely sensed data may help identify such areas, with the Normalized Difference Vegetation Index (NDVI) providing an estimate of primary productivity. We examined the relationship between maximum productivity (NDVI), heterogeneity of productivity, and species richness of birds and butterflies at multiple spatial scales. We also explored relationships between productivity, functional guilds and residency groups of birds, and vagility classes of butterflies. Positive linear relationships between maximum NDVI and number of functional guilds of birds were found at two spatial scales. We also found positive linear relationships between maximum NDVI and species richness of neotropical migrant birds at two scales. Heterogeneity of NDVI, by contrast, was negatively associated with number of functional guilds of birds and species richness of resident birds. Maximum NDVI was associated with species richness of all butterflies and of the most vagile butterflies. No association was found between heterogeneity of NDVI and species richness of butterflies. In the Great Basin, where high greenness and availability of water correspond to areas of high species richness and maximum NDVI, our results suggest that NDVI can provide a reliable basis for stratifying surveys of biodiversity, by highlighting areas of potentially high biodiversity across large areas. Measures of heterogeneity of NDVI appear to be less useful in explaining species richness.     

中国阿勒泰地区鸟类物种编目、丰富度格局和区系组成

中国阿勒泰地区位于新疆北部, 与哈萨克斯坦、俄罗斯、蒙古国交界, 该区包含阿尔泰山及山前荒漠和绿洲, 属于全球200个生物多样性最丰富和最具代表性生态区之一的阿尔泰-萨彦岭生物热点地区。阿勒泰地区生境多样, 鸟类物种资源丰富。尽管以往曾在阿勒泰地区进行过一些鸟类调查, 但对于该地区不同景观和生境类型中鸟类物种丰富度和分布尚无详尽报道。本文通过2013-2016年在中国境内阿尔泰山及山前平原地区对不同生境类型中的鸟类进行实地调查, 并总结文献资料及观鸟爱好者的记录数据, 重新整理了阿勒泰地区鸟类名录及地理分布, 分析了鸟类的物种组成、区系成分; 通过鸟类分布位点数据, 选取气候、土地覆被类型、人类足迹指数及地形共4类环境因子作为自变量建立MaxEnt生态位模型, 通过模拟77种鸟类的适宜分布区并叠加分布图层, 获得了阿勒泰地区的鸟类物种丰富度分布格局。结果表明: 阿勒泰共记录鸟类344种, 隶属19目55科149属, 其中雀形目163种。在垂直海拔带上, 鸟类物种数分别为高山裸岩带24种, 高山草甸带35种, 山地森林草原带172种, 低山灌木带130种, 荒漠草原带84种, 平原绿洲带173种, 以及各海拔带的湿地与水域生境中水鸟92种; 在区系成分上, 以北方型鸟类为主(170种, 占49.4%), 其次为广布种(93种, 占27.0%)。阿尔泰山地的鸟类区系呈现出西伯利亚动物区系特征, 山前平原地区呈现蒙新区分布特征, 因此, 阿勒泰地区动物地理区系属于古北界欧洲-西伯利亚亚界阿尔泰-萨彦岭区阿尔泰亚区; 山前平原地区属于古北界中亚亚界蒙新区西部荒漠亚区。MaxEnt模型推测阿勒泰地区山前平原绿洲地区、山地森林草原带和低山灌木带具有较高的鸟类物种丰富度, 尤其是额尔齐斯河流域下游的绿洲带宽阔, 鸟类物种丰富, 而高山区和荒漠生境中鸟类物种相对较少。模型预测的结果与实际调查情况相符。阿勒泰地区应采用生态友好的经济发展策略, 加强对乔木和灌木的保护, 这有助于维持较高的鸟类物种多样性。此外, 降低生境破碎化不仅对该地区物种保护有重要作用, 也对维持阿尔泰-萨彦岭生物热点地区的山地鸟类多样性有重要意义。     

Elevational gradients in bird diversity in the Eastern Himalaya: an evaluation of distribution patterns and their underlying mechanisms

Background

Understanding diversity patterns and the mechanisms underlying those patterns along elevational gradients is critically important for conservation efforts in montane ecosystems, especially those that are biodiversity hotspots. Despite recent advances, consensus on the underlying causes, or even the relative influence of a suite of factors on elevational diversity patterns has remained elusive.

Methods and Principal Findings

We examined patterns of species richness, density and range size distribution of birds, and the suite of biotic and abiotic factors (primary productivity, habitat variables, climatic factors and geometric constraints) that governs diversity along a 4500-m elevational gradient in the Eastern Himalayan region, a biodiversity hotspot within the world''s tallest mountains. We used point count methods for sampling birds and quadrats for estimating vegetation at 22 sites along the elevational gradient. We found that species richness increased to approximately 2000 m, then declined. We found no evidence that geometric constraints influenced this pattern, whereas actual evapotranspiration (a surrogate for primary productivity) and various habitat variables (plant species richness, shrub density and basal area of trees) accounted for most of the variation in bird species richness. We also observed that ranges of most bird species were narrow along the elevation gradient. We find little evidence to support Rapoport''s rule for the birds of Sikkim region of the Himalaya.

Conclusions and Significance

This study in the Eastern Himalaya indicates that species richness of birds is highest at intermediate elevations along one of the most extensive elevational gradients ever examined. Additionally, primary productivity and factors associated with habitat accounted for most of the variation in avian species richness. The diversity peak at intermediate elevations and the narrow elevational ranges of most species suggest important conservation implications: not only should mid-elevation areas be conserved, but the entire gradient requires equal conservation attention.     

The role of fire in terrestrial vertebrate richness patterns

Productivity is strongly associated with terrestrial species richness patterns, although the mechanisms underpinning such patterns have long been debated. Despite considerable consumption of primary productivity by fire, its influence on global diversity has received relatively little study. Here we examine the sensitivity of terrestrial vertebrate biodiversity (amphibians, birds and mammals) to fire, while accounting for other drivers. We analyse global data on terrestrial vertebrate richness, net primary productivity, fire occurrence (fraction of productivity consumed) and additional influences unrelated to productivity (i.e., historical phylogenetic and area effects) on species richness. For birds, fire is associated with higher diversity, rivalling the effects of productivity on richness, and for mammals, fire's positive association with diversity is even stronger than productivity; for amphibians, in contrast, there are few clear associations. Our findings suggest an underappreciated role for fire in the generation of animal species richness and the conservation of global biodiversity.     

Partitioning the diversity of riverine fish: the roles of habitat types and non-native species

1. Quantifying how biological diversity is distributed in the landscape is one of the central themes of conservation ecology. For this purpose, landscape classifications are being intensively used in conservation planning and biodiversity management, although there is still little information about their efficacy. 2. I used data from 158 running water sites in Hungary to examine the contribution of six a priori established habitat types to regional level diversity of fish assemblages. Three community measures [species richness, diversity (Shannon, Simpson indices), assemblage composition] were examined at two assemblage levels (entire assemblage, the native assemblage). The relative role of non‐native species was quantified to examine their contribution to patterns in diversity in this strongly human influenced landscape. 3. Additive diversity partitioning revealed the primary importance of beta diversity (i.e. among‐site factors) to patterns in species richness. Landscape‐scale patterns in species richness were best explained by between‐habitat type (beta₂: 41.2%), followed by within‐habitat type (beta₁: 37.7%) and finally within‐site (alpha: 21.1%) diversity. Diversity indices showed patterns different from species richness, indicating the importance of relative abundance distributions on the results. Exclusion of non‐natives from the analysis gave similar results to the entire‐assemblage level analysis. 4. Canonical analysis of principal coordinates, complemented with indicator species analysis justified the separation of fish assemblages among the habitat types, although classification error was high. Multivariate dispersion, a measure of compositional beta diversity, showed significant differences among the habitat types. Contrary to species diversity (i.e. richness, diversity indices), patterns in compositional diversity were strongly influenced by the exclusion of non‐natives from the analyses. 5. This study is the first to quantify how running water habitat types contribute to fish diversity at the landscape scale and how non‐native species influence this pattern. These results on riverine fish assemblages support the hypothesis that environmental variability (i.e. the diversity of habitat types) is an indication of biodiversity and can be used in large‐scale conservation designs. The study emphasises the joint application of additive diversity partitioning and multivariate statistics when exploring the contribution of landscape components to the overall biodiversity of the landscape mosaic.     

Macro‐scale bird species richness patterns of the East Asian mainland and islands: energy,area and isolation

Aim To create a map of bird species richness (BSR) in East Asia and to examine the effect of area, isolation, primary productivity, topographic heterogeneity, and human population density on BSR. Location East Asia (from 70° E to 180° E longitude), including the eastern half of the Palaearctic Region, the entire Oriental Region, and the entire Wallacea Subregion. Methods The breeding ranges of 2406 terrestrial bird species were mapped and overlaid to create a species richness map. The BSR map was transformed into a 100 × 100 km quadrat system, and BSR was analysed in relation to land area, average normalized difference vegetation index (NDVI), elevation range, and average population density. Results In general, BSR declined from the Tropics to the Arctic. In mainland East Asia, however, BSR was highest around the Tropic of Cancer, and fluctuated between 30° and 50° N. Islands had lower BSR than adjacent mainland areas. The NDVI was strongly positively correlated with BSR in mainland areas and on islands. For mainland areas, NDVI explained 65% of the BSR variation, and topographic heterogeneity explained an additional 6% in ordinary least‐squares regression. On islands, NDVI explained 66% of BSR variation, island area explained 13%, and distance to mainland accounted for 1%. Main conclusions In East Asia, we suggest that primary productivity is the key factor underpinning patterns of BSR. Primary productivity sets the upper limits of the capacity of habitats to support bird species. In isolated areas such as islands and peninsulas, however, BSR might not reach the richness limits set by primary productivity because the degree of isolation and area size also can affect species richness. Other factors, such as spatial heterogeneity, biotic interactions, and perturbations, may also affect species richness. However, their effects are secondary and are not as strong as primary productivity, isolation, and area size.