Are richness patterns of common and rare species equally well explained by environmental variables?

We investigated relationships between richness patterns of rare and common grassland species and environmental factors, focussing on comparing the degree to which the richness patterns of rare and common species are determined by simple environmental variables. Using data collected in the Machair grassland of the Outer Hebrides of Scotland, we fitted spatial regression models using a suite of grazing, soil physicochemical and microtopographic covariates, to nested sub‐assemblages of vascular and non‐vascular species ranked according to rarity. As expected, we found that common species drive richness patterns, but rare vascular species had significantly stronger affinity for high richness areas. After correcting for the prevalence of individual species distributions, we found differences between common and rare species in 1) the amount of variation explained: richness patterns of common species were better summarised by simple environmental variables, 2) the associations of environmental variables with richness showed systematic trends between common and rare species with coefficient sign reversal for several factors, and 3) richness associations with rare environments: richness patterns of rare vascular species significantly matched rare environments but those of non‐vascular species did not. Richness patterns of rare species, at least in this system, may be intrinsically less predictable than those of common species.     

Phylogenetic distance–decay patterns are not explained by local community assembly processes in freshwater lake microbial communities

While water and sediment microbial communities exhibit pronounced spatio-temporal patterns in freshwater lakes, the underlying drivers are yet poorly understood. Here, we evaluated the importance of spatial and temporal variation in abiotic environmental factors for bacterial and microeukaryotic community assembly and distance–decay relationships in water and sediment niches in Hongze Lake. By sampling across the whole lake during both Autumn and Spring sampling time points, we show that only bacterial sediment communities were governed by deterministic community assembly processes due to abiotic environmental drivers. Nevertheless, consistent distance–decay relationships were found with both bacterial and microeukaryotic communities, which were relatively stable with both sampling time points. Our results suggest that spatio-temporal variation in environmental factors was important in explaining mainly bacterial community assembly in the sediment, possibly due lesser disturbance. However, clear distance–decay patterns emerged also when the community assembly was stochastic. Together, these results suggest that abiotic environmental factors do not clearly drive the spatial structuring of lake microbial communities, highlighting the need to understand the role of other potential drivers, such as spatial heterogeneity and biotic species interactions.     

Multivariate geostatistical methods for analysis of relationships between ecological indicators and environmental factors at multiple spatial scales

As all biodiversity-related variables, ecological indicators are influenced by environmental factors working at different spatial scales. However, assessing the relationship between environmental factors and ecological indicators is limited to a set of spatial scales determined a priori. This a priori assumption can hide important relationships, especially for ecological indicators with a complex spatial structure that can be driven, for example, by the influence of multiple pollutants with different dispersion ranges or by the influence of local and regional factors such as land-cover and climate. To relate ecological indicators and environmental factors without assuming a priori spatial scales of analysis, we used a Linear Model of Coregionalization. This method has been used in literature to analyze the joint distribution of biodiversity variables. Here we show that it can be used to gain insight into spatial patterns of relationships between ecological indicators and underlying environmental factors. We applied this method to a region of south-west Europe, relating data from land-cover, altitude and climate with an ecological indicator, the abundance of fruticose lichen species, known to be very sensitive to multiple environmental factors. Based on variogram analysis we identified distinct spatial scales of relationships between the ecological indicator and environmental factors. For each spatial scale we described relationships using Principal Component Analysis applied to the coregionalization matrices. This way we could assess how strong the relationship between each environmental factor and ecological indicator at each spatial scale was: at medium scales (c. 15 km) open spaces areas (a proxy for particle emissions) were more important; at larger scales (c. 45 km) open spaces, artificial areas (a proxy for gaseous pollutants) and also climate were preponderant. Thus, multivariate geostatistics provided a tool to improve knowledge on relationships between ecological indicators and environmental factors at multiple spatial scales without setting a priori spatial scales of analysis.     

Functional dependence underlies a positive plant-grasshopper richness relationship

A central focus of ecology is identifying the factors that shape spatial patterns of species diversity and this is particularly relevant in an era of global change. Positive relationships between plant and consumer diversity are common, but could be driven by direct responses of each trophic level to underlying environmental gradients, or indirectly where changes in environmental conditions propagate through food webs. Here we use structural equation modeling to examine the relative importance of soil resource availability and disturbance (fire) in mediating relationships between plant and grasshopper richness in insular grasslands. We found a positive relationship between plant and consumer richness that became stronger after accounting for disturbance, despite unique responses of plants and consumers to the two environmental gradients. Plant richness responded to an underlying gradient in soil resource availability. Time since the last fire had a direct positive effect on grasshopper richness but had no effect on plant richness. This work supports that plant and consumer richness are functionally linked, rather than having similar responses to environmental gradients. By disentangling the direct and indirect processes underlying a positive relationship between plant and consumer diversity in a natural system that spans multiple environmental gradients, we demonstrate the importance of investigating biodiversity through explicit multivariate models.     

三江平原农田地表和地下土壤螨类丰富度与环境因子的空间关联性

地表和地下土壤动物群落空间格局及其与环境因子的空间作用关系,是揭示地表-地下生态系统格局与过程及生物多样性维持机制的重要基础。于2011年在三江平原农田生态系统,在50m×50m的空间尺度内,基于地统计空间分析方法,揭示地表和地下土壤螨群落及不同螨类物种丰富度的空间格局,并分析这种空间格局与土壤含水量、土壤p H值及大豆株高空间格局的空间关联性。半方差函数和普通克里格插值表明,8月份地表、地下和10月份地下螨群落及这些群落内大部分螨类物种在特定空间尺度内形成集群,表现为空间异质性特征,且这种空间分异多由结构性因素或结构性因素和随机性因素共同调控。交叉方差函数表明,土壤螨群落和不同螨类物种的空间格局与环境因子的空间格局在多种尺度上表现出复杂的空间关联性(正的或负的)。但简单Mantel检验仅发现8月份地表中气门亚目未定种1(Mesostigmata unidentified sp.1)和大豆株高存在明显的正的空间关联性。研究结果表明地下螨群落和生长季节的地表螨群落具有明显的空间异质性结构,地表和地下螨群落及大多数螨类物种丰富度与土壤含水量、土壤p H值及大豆株高的空间关联性并不显著。促进地表-地下生态系统土壤动物群落空间格局研究,为地表-地下格局与过程研究奠定基础。     

Negative native–exotic diversity relationship in oak savannas explained by human influence and climate

Recent research has proposed a scale-dependence to relationships between native diversity and exotic invasions. At fine spatial scales, native–exotic richness relationships should be negative as higher native richness confers resistance to invasion. At broad scales, relationships should be positive if natives and exotics respond similarly to extrinsic factors. Yet few studies have examined both native and exotic richness patterns across gradients of human influence, where impacts could affect native and exotic species differently. We examined native–exotic richness relationships and extrinsic drivers of plant species richness and distributions across an urban development gradient in remnant oak savanna patches. In sharp contrast to most reported results, we found a negative relationship at the regional scale, and no relationship at the local scale. The negative regional-scale relationship was best explained by extrinsic factors, surrounding road density and climate, affecting natives and exotics in opposite ways, rather than a direct effect of native on exotic richness, or vice versa. Models of individual species distributions also support the result that road density and climate have largely opposite effects on native and exotic species, although simple life history traits (life form, dispersal mode) do not predict which habitat characteristics are important for particular species. Roads likely influence distributions and species richness by increasing both exotic propagule pressure and disturbance to native species. Climate may partially explain the negative relationship due to differing climatic preferences within the native and exotic species pools. As gradients of human influence are increasingly common, negative broad-scale native–exotic richness relationships may be frequent in such landscapes.     

Disentangling scale dependencies in species environmental niches and distributions

Understanding species’ responses to environmental conditions, and how these ­species–environment associations shape spatial distributions, are longstanding goals in ecology and biogeography. However, an essential component of species–environment relationships – the spatial unit, or grain, at which they operate – remains unresolved. We identify three components of scale‐dependence in analyses of species–environment associations: 1) response grain, the grain at which species respond most strongly to their environment; 2) environment spatial structure, the pattern of spatial autocorrelation intrinsic to an environmental factor; and 3) analysis grain, the grain at which analyses are conducted and ecological inferences are made. We introduce a novel conceptual framework that defines these scale components in the context of analyzing species–environment relationships, and provide theoretical examples of their interactions for species with various ecological attributes. We then use a virtual species approach to investigate the impacts of each component on common methods of measuring and predicting species–environment relationships. We find that environment spatial structure has a substantial impact on the ability of even simple, univariate species distribution models (SDMs) to recover known species–­environment associations at coarse analysis grains. For simulated environments with ‘fine’ and ‘intermediate’ spatial structure, model explanatory power, and the frequency with which simple SDMs correctly estimated a virtual species’ response to the simulated environment, dramatically declined as analysis grain increased. Informed by these results, we use a scaling analysis to identify maximum analysis grains for individual environmental factors, and a scale optimization procedure to determine the grain of maximum predictive accuracy. Implementing these analysis grain thresholds and model performance standards in an example east African study system yields more accurate distribution predictions, compared to SDMs independently constructed at arbitrary analysis grains. Finally, we integrate our conceptual framework with virtual and empirical results to provide practical recommendations for researchers asking common questions about species–environment relationships.     

Tree spatial patterns and environmental relationships in the forest–alpine tundra ecotone at Niwot Ridge,Colorado, USA

Forest–alpine tundra ecotones (FTEs) are dynamic transition zones between forest and alpine tundra ecosystems that play an important role in regulating ecological processes, which are in turn directly influenced by the spatial patterns of trees and environmental constraints such as topography and climate. Our objectives were to characterize the spatial patterns of tree species and size classes, determine whether spatial patterns of trees differed among three FTE types, and examine FTE- and tree-environmental relationships in our study area on Niwot Ridge, CO, USA. Overall, spatial aggregation was more extensive for seedlings than saplings or trees. Distributions were largely random in limber pine but were highly aggregated in Engelmann spruce and especially subalpine fir, reflecting these species’ relative shade tolerance and expected sequence of establishment following disturbance. Fragmented and patchy tree distributions were observed in the FTE with the most heterogeneous topography, characterized by high relief and associated physical disturbances. The least patchy distributions were associated with the FTE containing a relative absence of disturbance. Intermediate levels of tree aggregation were associated with low topographic relief and presence of meadows and wetlands. Our results emphasize the importance of spatial structure as an initial controlling factor of vegetation pattern in FTEs occurring in the same landscape.     

Spatial distribution of the basidiocarps of aphyllophoraceous fungi in a tropical rainforest on Borneo Island, Malaysia

The spatial distribution of basidiocarps provides much information on the dispersal abilities, habitat preferences, and inter- and intraspecific interactions of aphyllophoraceous fungi. To reveal the spatial distribution and resource utilization patterns of aphyllophoraceous fungi in Malaysia, we conducted field observations in a primary forest in 2006 and analyzed the relationships between the abundance of eight dominant fungal species and various environmental factors. The topographical characteristics were significantly patchily distributed at the 100-m scale, whereas woody debris and most fungal species were distributed randomly. Although the dominant fungal species differed among the decay classes and diameters of the woody debris, the abundance of a few dominant species was significantly correlated with environmental factors. Although the latter factors might affect the spatial distribution of these fungi, the effects appear to be so small that they would not create an aggregated distribution at a few 100-m scales.     

Assessing the influence of environmental gradients on seed mass variation in mountain grasslands using a spatial phylogenetic filtering approach

Several studies have demonstrated that seed mass is related to different environmental factors. However, they have taken no account of the joint effects of spatial and phylogenetic information. We analysed the distribution pattern of seed mass along an elevational gradient (1040–2380 m a.s.l.) at the community level in grasslands of the southern Alps. First, we tested the influence of environmental filters (climate and soil properties) in determining community-weighted seed mass variation in mountain grasslands. Second, we verified the relative roles of environmental filters in determining seed mass variation after accounting for spatial and phylogenetic autocorrelation with an eigenvector filtering approach. Temperature, soil fertility, and soil pH were the most important predictors for explaining seed mass variation; specifically, warmer, low fertility, and alkaline grasslands showed a greater seed mass. Inclusion of spatio-phylogenetic filters in the model increased its fit and the variance explained and reduced autocorrelation significantly but had substantial effects on the parameter estimates, with temperature and soil pH becoming insignificant. This effect may be ascribable to spatially structured phylogenetic patterns and could likely result from the common evolutionary histories shared by many species at sites with similar environmental conditions. Therefore, the observed patterns between community-weighted seed mass and both temperature and soil pH are not independent of phylogeny, but they are explained by the shared history within genera and families. Nevertheless, soil fertility remained the most important predictor for explaining seed mass variation. The results of this work contribute to better understanding the combined effects of environment and evolutionary factors for determining seed mass distributions in the spatial context of mountain grasslands. The observed relationships with climate and soil properties are particularly interesting because they are potentially relevant when modelling plant trait composition under changes in land use and climate.     

Modeling bird species distribution change in fire prone Mediterranean landscapes: incorporating species dispersal and landscape dynamics

Species distribution models (SDMs) have traditionally been founded on the assumption that species distributions are in equilibrium with environmental conditions and that these species–environment relationships can be used to estimate species responses to environmental changes. Insight into the validity of this assumption can be obtained from comparing the performance of correlative species distribution models with more complex hybrid approaches, i.e. correlative and process‐based models that explicitly include ecological processes, thereby accounting for mismatches between habitat suitability and species occupancy patterns. Here we compared the ability of correlative SDMs and hybrid models, which can accommodate non‐equilibrium situations arising from dispersal constraints, to reproduce the distribution dynamics of the ortolan bunting Emberiza hortulana in highly dynamic, early successional, fire driven Mediterranean landscapes. Whereas, habitat availability was derived from a correlative statistical SDM, occupancy was modeled using a hybrid approach combining a grid‐based, spatially‐explicit population model that explicitly included bird dispersal with the correlative model. We compared species occupancy patterns under the equilibrium assumption and different scenarios of species dispersal capabilities. To evaluate the predictive capability of the different models, we used independent species data collected in areas affected to different degree by fires. In accordance with the view that disturbance leads to a disparity between the suitable habitat and the occupancy patterns of the ortolan bunting, our results indicated that hybrid modeling approaches were superior to correlative models in predicting species spatial dynamics. Furthermore, hybrid models that incorporated short dispersal distances were more likely to reproduce the observed changes in ortolan bunting distribution patterns, suggesting that dispersal plays a key role in limiting the colonization of recently burnt areas. We conclude that SDMs used in a dynamic context can be significantly improved by using combined hybrid modeling approaches that explicitly account for interactions between key ecological constraints such as dispersal and habitat suitability that drive species response to environmental changes.     

Spatial distribution and habitats of useful plants: an initial assessment for conservation on an indigenous territory, Panama

In order to examine the spatial distribution of forest resources on local territories and to understand the factors controlling such distributions, we studied the spatial patterns of a group of 23 useful plant species on the territory of a Kuna community in the province of Darien, Panama. A stratified random sampling scheme was used to survey the distribution and abundance of the species across a 3500 ha area around the village. Data on the physical environment as well as the geographic coordinates of the sample plots were also obtained. A series of canonical analyses was conducted to evaluate the species–environment relationships and to identify spatial structures in the species distributions left unexplained by the environmental variables. Four distinct distribution patterns were identified among the species; these were most strongly explained by land-use, the degree of canopy closure and topography. Significant spatial structures, independent of the measured environmental variables, were related to anthropogenic pressure and an edaphic gradient, and the habitat associations of the individual species were described. The results obtained from this case study suggest that land-use dynamics may play a predominant role in structuring inhabited landscapes, and that diversity in distribution patterns and habitat associations will require a combination of spatially explicit management strategies to ensure the local resource base.     

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent.     

Bayesian image restoration models for combining expert knowledge on recording activity with species distribution data

Biological atlases are, for many species, the only source of information on their distribution over large geographical areas, and are widely used to inform models of the environmental distribution of species. Such data are not collected using standardized survey techniques, however, and spatial variations in coverage (the relative extent or completeness of records) may lead to variations in the probability that the species will be recorded at locations where it is present (the “recording probability”). If spatial patterns in recording probabilities are correlated with key environmental variables, then biased estimates of the relationships between environmental variables and species distributions may be obtained. We outline a general statistical framework for modelling the environmental distribution of species using, known as Bayesian Image Restoration (BIR). BIR can be used in combination with any species distribution model, but in addition allows us to account for spatial heterogeneity in recording probabilities by utilizing expert knowledge on spatial patterns in coverage. We illustrate the methodology by applying it to maps of the recorded distribution of two plant species in Germany, taken from the German atlas of vascular plants. We find that estimated spatial patterns in recording probabilities for both species are correlated with key environmental variables. Consequently, different relationships between the probability of presence of a species and environmental variables were obtained when the species distribution models were parameterised within a BIR framework. Care must be taken in the application of BIR, since the resulting inferences can depend strongly upon the modelling assumptions that are adopted. Nevertheless, we conclude that BIR has the potential to make better use of uncertain information on species distributions than conventional methods, and can be used to formally investigate the robustness of inferences on the environmental distribution of species to assumptions concerning spatial patterns in recording probabilities.     

Effect of Environmental and Temporal Factors on Patterns of Rarity of Ephemeroptera in Stream of the Brazilian Cerrado

Patterns of species’ abundance and occurrence over time and space allow division of species into (i) common species, which are abundant, but have a low diversity, and (ii) rare species, which are far more diverse and less abundant. Understanding the relationships among these two species groups and how they are affected by environmental conditions is a major challenge for ecologists, especially considering the distinction between local environmental factors and regional factors and variations in abundance over the course of the year. In this study, we focused on the long-term relationship between the abundance of rare and common ephemeropterans and abiotic factors on local and regional scales. Our hypotheses are that common species will be affected primarily by regional environmental variables (i), whereas rare species will be influenced more by temporal variation (ii). Together, both local and regional abiotic variables, plus temporal variation, best explained the abundance of the common species, whereas temporal variation was the best predictor of rare species. Considering the theoretical aspects and the empirical evidence, we discuss the results based on the plasticity of the common species and the life cycle of the rare ones. We believe that our findings reinforce the need for the deconstruction of communities for a deeper understanding of their relationships with abiotic variables and, in particular, the specific aspects of these relationships in the context of the different guilds of the community.     

Invasion patterns across multiple scales by Hieracium species over 25 years in tussock grasslands of New Zealand's South Island

Studying patterns of species invasions over time at multiple spatial scales may help us to elucidate important factors driving those patterns and how they change according to temporal or spatial resolution. Here we provide a large, long‐term, landscape‐scale study of the invasion of three Hieracium species using a dataset that encompasses vegetation change on 124 transects over 25 years across the lower eastern South Island of New Zealand. We investigated the relationships between key environmental and ecological factors and the invasion trajectories of H. lepidulum, H. pilosella and H. praealtum, at two spatial scales: (i) among‐transect colonization and (ii) within‐transect changes in frequency and per cent cover. Our results show that the colonization and spread of Hieracium species among and within transects reflect (i) the importance of initial environmental and biological conditions, (ii) that our sampling captured different periods of the invasion trajectories of each of the three species, and (iii) the effects of differences in life histories of the three species.     

Environmental and spatial processes influencing phytoplankton biomass along a reservoirs‐river‐floodplain lakes gradient: A metacommunity approach

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Patterns of spatial and temporal variation of macrofauna under boulders in a sheltered boulder field

Abstract Spatial and temporal patterns of abundance of animals and plants must be quantified before models to explain distributions can be developed. These patterns also provide essential data for measuring potential effects of environmental disturbances. Studies in many different habitats have shown that most organisms, particularly invertebrates, have highly variable and interactive patterns of abundance, with much variability at the smallest temporal and spatial scales. Intertidal boulder fields in New South Wales, Australia, support a diverse fauna, many species of which are relatively rare. These habitats are commonly found near rock‐platforms and in sheltered estuaries and are subjected to many human disturbances. Although there have been a few studies on the fauna in boulder fields, none has documented variability of the assemblage using multivariate and univariate techniques and most studies have not incorporated different spatial and temporal scales. This study quantifies spatial variation at three scales (metres, tens of metres alongshore and tens of metres upshore) and temporal variation at two scales (3 months and 2 years) of the assemblage of molluscs and echinoderms in a sheltered boulder field subjected to little natural or human disturbance. Multivariate analyses revealed that each site contained a distinct assemblage, mainly due to the relative abundances of a few species. Most species, those generally only found under boulders and common, widespread species, had considerable spatial variability in abundances, with more than 90% measured at the smallest scale, that is metre to metre within a site. Changes in abundances over 3 months or 2 years varied among species and sites in unpredictable ways. These data show that sampling designs to measure impacts on these fauna will need to be complex and must incorporate a number of spatial and temporal scales if they are to be able to detect impact against such a variable background.     

The ectomycorrhizal community structure in high mountain Norway spruce stands

The species composition of ectomycorrhizal (ECM) fungal communities can be strongly influenced by abiotic and biotic factors, which determine interactions among the species such as resource partitioning, disturbance, competition, or relationships with other organisms. To verify whether ectomycorrhization of the root tips and composition of the ECM community in Norway spruce vary according to site features and if ECM species peculiar to these environmental variables can be detected, ten comparable stands differing in bedrock pH and exposure were selected and studied. The results demonstrated that tips vitality and ectomycorrhization degree do not change significantly either on the same tree, or among trees growing in the same stand, whereas they differ greatly with bedrock pH and exposure, even if no spatial or temporal trend were found. ECM species composition revealed instead a significant connection with the two environmental features, with a few species significantly associated to them. The results suggest that pH/exposure patterns play a primary role in the adaptive selection of ECM species constituting the consortium.     

Species–environment relationships of mosses in New Zealand indigenous forest and shrubland ecosystems

Small and challenging to identify, bryophyte species are often under-represented in large-scale studies of vegetation patterns. Bryophyte occurrence is likely to be influenced by multiple processes and little is known about the relative importance of the different factors across diverse landscapes. Species–environment relationships of 15 common terrestrial moss species in native forests of South and Stewart islands, New Zealand, were examined. Models were developed for each species to test relationships between species distribution and 22 environmental predictors, using Generalised Regression Analysis and Spatial Prediction (GRASP). The New Zealand nationwide vegetation survey LUCAS, although showing several limitations, provided data to investigate factors that may influence bryophyte distribution along large gradients. Combined biotic (primarily total vegetation cover) and abiotic (mean annual temperature and rainfall) effects best contributed to distribution models of all but two moss species. Canopy tree species at a site were also important predictors in the spatial distribution of several individual moss species, possibly through altering the physical environment and resource availability, although both bryophytes and vascular plant species may be influenced independently by the same factors. The study highlights the importance of different factors influencing bryophyte distributions and identifies several factors controlling distributions that require further investigation.