Modelling geographical patterns in species richness using eigenvector-based spatial filters

Aim To test the mechanisms driving bird species richness at broad spatial scales using eigenvector‐based spatial filtering. Location South America. Methods An eigenvector‐based spatial filtering was applied to evaluate spatial patterns in South American bird species richness, taking into account spatial autocorrelation in the data. The method consists of using the geographical coordinates of a region, based on eigenanalyses of geographical distances, to establish a set of spatial filters (eigenvectors) expressing the spatial structure of the region at different spatial scales. These filters can then be used as predictors in multiple and partial regression analyses, taking into account spatial autocorrelation. Autocorrelation in filters and in the regression residuals can be used as stopping rules to define which filters will be used in the analyses. Results Environmental component alone explained 8% of variation in richness, whereas 77% of the variation could be attributed to an interaction between environment and geography expressed by the filters (which include mainly broad‐scale climatic factors). Regression coefficients of environmental component were highest for AET. These results were unbiased by short‐scale spatial autocorrelation. Also, there was a significant interaction between topographic heterogeneity and minimum temperature. Conclusion Eigenvector‐based spatial filtering is a simple and suitable statistical protocol that can be used to analyse patterns in species richness taking into account spatial autocorrelation at different spatial scales. The results for South American birds are consistent with the climatic hypothesis, in general, and energy hypothesis, in particular. Habitat heterogeneity also has a significant effect on variation in species richness in warm tropical regions.     

Effect of forest fragmentation on bird species richness in Papua New Guinea

Tropical forests worldwide are being fragmented at a rapid rate, causing a tremendous loss of biodiversity. Determining the impacts of forest disturbance and fragmentation on tropical biotas is therefore a central goal of conservation biology. We focused on bird communities in the interior (>100 m from forest edge) of forest fragments (300, 600, and 1200 ha) in the lowlands of Papua New Guinea and compared them with those in continuous forest. We surveyed bird communities using point counts, mist‐netting, and random walks, and measured habitat and microclimate characteristics at each site. We also surveyed leaf‐dwelling arthropods, butterflies, and ants, and obtained diet samples from birds to examine food availability and food preferences. We recorded significantly fewer bird species per point in the 300‐ha forest fragment than in other study sites. Overall, we recorded 80, 84, and 88 species, respectively, in forest fragments, and 102 in continuous forest. Frugivores (especially large frugivores) and insectivores had lower species richness in forest fragments than continuous forest. Our results did not support the food scarcity hypothesis, that is, the decline of insectivorous birds in forest fragments is caused by an impoverished invertebrate prey base. We also found no significant differences among forest fragments and continuous forest in microclimates of forest interiors. Rather, we found that microhabitats preferred by sensitive birds (i.e., 30% of species with the strongest preferences for continuous forest) were less common in forest fragments (19%–31% of points) than in continuous forest (86% of points). Our results suggest that changes in microhabitats may make forest fragments unsuitable for sensitive species. However, limited dispersal capabilities could also make some species of birds less likely to disperse and occupy fragments. In addition, impoverished food resources, size of the forest fragment, or hunting pressure could contribute to the absence of large frugivorous birds in forest fragments. The forest fragments in our study, preserved as village‐based protected areas, were not large enough to sustain the bird communities found in continuous forest. However, because these fragments still contained numerous bird species, preservation of such areas can be an important component of management strategies to conserve rainforests and birds in Papua New Guinea.     

次生林不同类型森林边缘的鸟类物种丰富度及个体多度比较

边缘效应对动物的分布及行为会产生一定的影响,在鸟类生态学研究中已证实某些鸟类在森林内部和森林边缘区域存在着物种丰富度和个体多度的差异。于1999至2001年的春夏季,在吉林省左家自然保护区对阔叶林/农田边缘、阔叶林/灌丛边缘及阔叶林/针叶林边缘3种不同类型边缘地带的鸟类物种丰富度及个体多度进行了比较研究。结果表明,不同年间鸟类物种丰富度无显著变化,但个体多度存在着一定的波动。不同类型森林边缘的鸟类物种丰富度存在着一定的差异,阔叶林/灌丛边缘的鸟类物种丰富度最高,而阔叶林/针叶林边缘的鸟类物种丰富度最低。鸟类个体多度的总体趋势在3种不同类型的边缘差异不显著,但存在种间差异,灰椋鸟、灰头啄木鸟和喜鹊在阔叶林/农田边缘的个体多度最高,斑啄木鸟、黄胸、三道眉草和日本树莺在阔叶林/灌丛边缘的个体多度最高,而沼泽山雀、冕柳莺和山在阔叶林/针叶林边缘的个体多度最高。     

Regional variation in the historical components of global avian species richness

Aim Using a global data base of the distribution of extant bird species, we examine the evidence for spatial variation in the evolutionary origins of contemporary avian diversity. In particular, we assess the possible role of the timing of mountain uplift in promoting diversification in different regions. Location Global. Methods We mapped the distribution of avian richness at four taxonomic levels on an equal‐area 1° grid. We examined the relationships between richness at successive taxonomic levels (e.g. species richness vs. genus richness). We mapped the residuals from linear regressions of these relationships to identify areas that are exceptional in the number of lower taxa relative to the number of higher taxa. We use generalized least squares models to test the influence of elevation range and temperature on lower‐taxon richness relative to higher‐taxon richness. Results Peaks of species richness in the Neotropics were congruent with patterns of generic richness, whilst peaks in Australia and the Himalayas were congruent with patterns of both genus and family richness. Hotspots in the Afrotropics did not reflect higher‐taxon patterns. Regional differences in the relationship between richness at successive taxonomic levels revealed variation in patterns of taxon co‐occurrence. Species and genus co‐occurrence was positively associated with elevational range across much of the world. Taxon occurrence in the Neotropics was associated with a positive interaction between elevational range and temperature. Conclusions These results demonstrate that contemporary patterns of richness show different associations with higher‐taxon richness in different regions, which implies that the timing of historical effects on these contemporary patterns varies across regions. We suggest that this is due to dispersal limitation and phylogenetic constraints on physiological tolerance limits promoting diversification. We speculate that diversification rates respond to long‐term changes in the Earth's topography, and that the role of tropical mountain ranges is implicated as a correlate of contemporary diversity, and a source of diversification across avian evolutionary history.     

中国大陆鸟类和兽类物种多样性的空间变异

生物多样性科学的研究重心之一是大尺度生物多样性空间分布规律及其形成机制。中国是世界上物种特丰富国家之一,了解我国物种多样性在空间上的变异情况,对于进一步认识大尺度上的生物多样性有重要意义。我们收集了全国205个自然保护区的鸟类和兽类物种分布信息,以G-F指数作为物种多样性的测度指标,利用地统计学方法分析了大陆鸟类和兽类物种多样性的空间变异特征。G-F指数是一种基于香农-威纳指数的信息测度,测度了研究地区环境分化程度和实际利用这种生态环境分化的生物类群多样性, 是一种对共同起源,相似生境需求的物种类群多样性的标准化多样性测度。结果发现,在东部季风区、西北干旱区和青藏高寒区内我国大陆鸟类多样性变异大部分都是由随机因素所引起的。兽类多样性的分布,在东部季风区和西北干旱区内是由随机因素所产生的,而在青藏高寒区,兽类多样性的总变异中99.9%是由空间依赖性所引起的,主要表现在71,492~1,020,000m空间尺度上,其分布表现出了强空间相关性。据此,大尺度上的物种多样性空间分布具有特定的规律,在生物多样性的保护行动中应加以考虑。     

Variation in plant species richness of different life forms along a subtropical elevation gradient in the Himalayas, east Nepal

Aim To explore the variation in species richness along a subtropical elevation gradient, and evaluate how climatic variables explain the richness of the different life forms such as trees, shrubs, climbers, herbs and ferns. Location The study was made in a subtropical to warm temperate region in the south‐eastern part of Nepal, between 100 and 1500 m above sea level (a.s.l.). Methods The number of species was counted in six plots (50 × 20 m) in each of the 15 100 m elevation bands covering the main physiognomic structures along an imaginary transect. Each species recorded was assigned to a life form. Potential evapotranspiration (PET, i.e. energy), mean annual rainfall (MAR), and their ratio (MI = moisture index) were evaluated as explanatory variables by means of generalized linear models (GLM). Each variable was tested individually, and in addition MAR and PET were used to test the water‐energy dynamics model for each life form. Results The richness of herbaceous species, including herbaceous climbers, was unrelated to any of the climate variables. PET was strongly negatively correlated with elevation, and the following relationships were found between increasing PET and richness: (i) shrubs, trees and total species (sum of all life forms) showed unimodal responses (ii) ferns decreased monotonically, and (iii) woody climbers increased monotonically. Richness of all woody groups increased monotonically with MAR and MI. The water‐energy dynamics model explained 63% of the variation in shrubs, 67% for trees and 70% for woody species combined. Main conclusions For the various herbaceous life forms (forbs, grasses, and herbaceous climbers) we found no significant statistical trends, whereas for woody life forms (trees, shrubs, and woody climbers) significant relationships were found with climate. E.M. O’Brien's macro‐scale model based on water‐energy dynamics was found to explain woody species richness at a finer scale along this elevational‐climatic gradient.     

Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness

Broad‐scale variation in taxonomic richness is strongly correlated with climate. Many mechanisms have been hypothesized to explain these patterns; however, testable predictions that would distinguish among them have rarely been derived. Here, we examine several prominent hypotheses for climate–richness relationships, deriving and testing predictions based on their hypothesized mechanisms. The ‘energy–richness hypothesis’ (also called the ‘more individuals hypothesis’) postulates that more productive areas have more individuals and therefore more species. More productive areas do often have more species, but extant data are not consistent with the expected causal relationship from energy to numbers of individuals to numbers of species. We reject the energy–richness hypothesis in its standard form and consider some proposed modifications. The ‘physiological tolerance hypothesis’ postulates that richness varies according to the tolerances of individual species for different sets of climatic conditions. This hypothesis predicts that more combinations of physiological parameters can survive under warm and wet than cold or dry conditions. Data are qualitatively consistent with this prediction, but are inconsistent with the prediction that species should fill climatically suitable areas. Finally, the ‘speciation rate hypothesis’ postulates that speciation rates should vary with climate, due either to faster evolutionary rates or stronger biotic interactions increasing the opportunity for evolutionary diversification in some regions. The biotic interactions mechanism also has the potential to amplify shallower, underlying gradients in richness. Tests of speciation rate hypotheses are few (to date), and their results are mixed.     

Partitioning sources of variation in vertebrate species richness

Aim To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location Maine, USA. Methods We delineated the ranges within Maine (86,156 km²) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad‐scale (spatially autocorrelated) and fine‐scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that could be explained by the relative contribution of each environmental variable. Results In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84–82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad‐scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.     

Proportion of exotics and relatedness of host species mediate the positive effect of plant richness on the species richness of fruit flies

1. All else being equal, the greater the local species richness of plants, the greater the number of associated herbivore species. Because most herbivore insects feed on a subset of closely related plant species, plant phylogenetic diversity is expected to play a key role in determining the number of herbivore species. What is not well known, however, is how an increase in the species richness of exotic plants affects the species richness of herbivores. 2. In this study, we used plant–fruit fly interactions to investigate the influence of the proportion and species richness of exotic host plants on the species richness of herbivorous insects. We also tested whether the phylogenetic diversity of host plants increases when the number of exotic plant species increases. 3. We found that the species richness of fruit flies is more accurately predicted by the richness of native host plants than by total plant species richness (including both native and exotic species). The proportion of exotic host species and the phylogenetic diversity of host plants had negative and positive effects, respectively, on the species richness of fruit flies. 4. Our findings suggest that a positive effect of plant richness on herbivore richness occurs only when an increase in plant diversity involves plant species with which native herbivores share some evolutionary history.     

Native and alien plant species richness in relation to spatial heterogeneity on a regional scale in Germany

Aim The aim of our study was to reveal relationships between richness patterns of native vs. alien plant species and spatial heterogeneity across varying landscape patterns at a regional scale. Location The study was carried out in the administrative district of Dessau (Germany), covering around 4000 km². Methods Data on plant distribution of the German vascular flora available in grid cells covering 5′ longitude and 3′ latitude (c. 32 km²) were divided into three status groups: native plants, archaeophytes (pre 1500 AD aliens) and neophytes (post 1500 AD aliens). Land use and abiotic data layers were intersected with 125 grid cells comprising the selected area. Using novel landscape ecological methods, we calculated 38 indices of landscape composition and configuration for each grid cell. Principal components analysis (PCA) with a set of 29 selected, low correlated landscape indices was followed by multiple linear regression analysis. Results PCA reduced 29 indices to eight principal components (PCs) that explained 80% cumulative variance. Multiple linear regression analysis was highly significant and explained 41% to 60% variance in plant species distribution (adjusted R²) with three significant PCs (tested for spatial autocorrelation) expressing moderate to high disturbance levels and high spatial heterogeneity. Comparing the significance of the PCs for the species groups, native plant species richness is most strongly associated with riverine ecosystems, followed by urban ecosystems, and then small‐scale rural ecosystems. Archaeophyte and neophyte richness are most strongly associated with urban ecosystems, followed by small‐scale rural ecosystems and riverine ecosystems for archaeophytes, and riverine ecosystems and small‐scale rural ecosystems for neophytes. Main conclusions Our overall results suggest that species richness of native and alien plants increases with moderate levels of natural and/or anthropogenic disturbances, coupled with high levels of habitat and structural heterogeneity in urban, riverine, and small‐scale rural ecosystems. Despite differences in the order of relevance of PCs for the three plant groups, we conclude that at the regional scale species richness patterns of native plants as well as alien plants are promoted by similar factors.     

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S‐SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location Two study areas in the Alps of Switzerland. Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S‐SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S‐SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump‐shaped pattern of SR observed along the elevational gradient. The S‐SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S‐SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S‐SDM approaches fail to appropriately reproduce the observed hump‐shaped patterns of SR along the elevational gradient. Main conclusions Macroecological approach and S‐SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S‐SDM by MEM predictions.     

Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna

Aim This article aims to test for and explore spatial nonstationarity in the relationship between avian species richness and a set of explanatory variables to further the understanding of species diversity variation. Location Sub‐Saharan Africa. Methods Geographically weighted regression was used to study the relationship between species richness of the endemic avifauna of sub‐Saharan Africa and a set of perceived environmental determinants, comprising the variables of temperature, precipitation and normalized difference vegetation index. Results The relationships between species richness and the explanatory variables were found to be significantly spatially variable and scale‐dependent. At local scales > 90% of the variation was explained, but this declined at coarser scales, with the greatest sensitivity to scale variation evident for narrow ranging species. The complex spatial pattern in regression model parameter estimates also gave rise to a spatial variation in scale effects. Main conclusions Relationships between environmental variables are generally assumed to be spatially stationary and conventional, global, regression techniques are therefore used in their modelling. This assumption was not satisfied in this study, with the relationships varying significantly in space. In such circumstances the average impression provided by a global model may not accurately represent conditions locally. Spatial nonstationarity in the relationship has important implications, especially for studies of species diversity patterns and their scaling.     

Fine-scale spatial variation in plant species richness and its relationship to environmental conditions in coastal marshlands

Previous studies have shown that variations in environmental conditions play a major role in explaining variations in plant species richness at community and landscape scales. In this study, we considered the degree to which fine-scale spatial variations in richness could be related to fine-scale variations in abiotic and biotic factors. To examine spatial variation in richness, grids of 1 m² plots were laid out at five sites within a coastal riverine wetland landscape. At each site, a 5 × 7 array of plots was established adjacent to the river’s edge with plots one meter apart. In addition to the estimation of species richness, environmental measurements included sediment salinity, plot microelevation, percent of plot recently disturbed, and estimated community biomass. Our analysis strategy was to combine the use of structural equation modeling (path modeling) with an assessment of spatial association. Mantel’s tests revealed significant spatial autocorrelation in species richness at four of the five sites sampled, indicating that richness in a plot correlated with the richness of nearby plots. We subsequently considered the degree to which spatial autocorrelations in richness could be explained by spatial autocorrelations in environmental conditions. Once data were corrected for environmental correlations, spatial autocorrelation in residual species richness could not be detected at any site. Based on these results, we conclude that in this coastal wetland, there appears to be a fine-scale mapping of diversity to microgradients in environmental conditions.     

Breeding bird species richness in Taiwan: distribution on gradients of elevation, primary productivity and urbanization

Aim To examine the richness of breeding bird species in relation to elevation, primary productivity and urbanization. Location The island of Taiwan (120°–122° E, 22°–25° N). Methods We arranged bird species richness (BSR) data from 288 bird censuses undertaken in Taiwan into a 2 × 2 km quadrat system and calculated average values of elevation, primary productivity [surrogated by normalized difference vegetation index (NDVI)], and urbanization (surrogated by road density and percentage of built area) for each 2 × 2 km quadrat. Results Bird species richness showed a hump‐shaped relationship with elevation. It increased with elevation from sea level (10–64 species per 2 × 2 km quadrat), peaked around 2000 m (43–76 species), and then decreased with elevation towards its minimum at the highest elevation. Road density and percentage of built area decreased with elevation, and NDVI showed a hump‐shaped relationship with elevation and inverse relationships with road density and percentage of built area. BSR increased with NDVI and decreased with road density and percentage of built area. Linear and cubic terms of elevation together explained 31.3% of the variance in BSR, and road density explained additional 3.4%. The explanatory power of NDVI on BSR was insignificant after the effects of elevation and road density had been justified. Main conclusions We argue that urbanization plays an important role in the BSR of Taiwan. Urbanization might indirectly decrease BSR through decreasing primary productivity and therefore change the hypothetical inverse relationship between BSR and elevation into a hump‐shaped relationship. We also propose a time hypothesis that the biotic communities in the mid‐elevation zone of Taiwan had relatively longer periods of existence during the Pleistocene glacial cycles, which might be one underlying process of the observed hump‐shaped relationship between species diversity and elevation.