Integrating the effects of area, isolation, and habitat heterogeneity on species diversity: a unification of island biogeography and niche theory

We present an analytical model that unifies two of the most influential theories in community ecology, namely, island biogeography and niche theory. Our model captures the main elements of both theories by incorporating the combined effects of area, isolation, stochastic colonization and extinction processes, habitat heterogeneity, and niche partitioning in a unified, demographically based framework. While classical niche theory predicts a positive relationship between species richness and habitat heterogeneity, our unified model demonstrates that area limitation and dispersal limitation (the main elements of island biogeography) may create unimodal and even negative relationships between species richness and habitat heterogeneity. We attribute this finding to the fact that increasing heterogeneity increases the potential number of species that may exist in a given area (as predicted by niche theory) but simultaneously reduces the amount of suitable area available for each species and, thus, increases the likelihood of stochastic extinction. Area limitation, dispersal limitation, and low reproduction rates intensify the latter effect by increasing the likelihood of stochastic extinction. These analytical results demonstrate that the integration of island biogeography and niche theory provides new insights about the mechanisms that regulate the diversity of ecological communities and generates unexpected predictions that could not be attained from any single theory.     

Plants on small islands revisited: the effects of spatial scale and habitat quality on the species–area relationship

Understanding how species diversity is related to sampling area and spatial scale is central to ecology and biogeography. Small islands and small sampling units support fewer species than larger ones. However, the factors influencing species richness may not be consistent across scales. Richness at local scales is primarily affected by small‐scale environmental factors, stochasticity and the richness at the island scale. Richness at whole‐island scale, however, is usually strongly related to island area, isolation and habitat diversity. Despite these contrasting drivers at local and island scales, island species–area relationships (SARs) are often constructed based on richness sampled at the local scale. Whether local scale samples adequately predict richness at the island scale and how local scale samples influence the island SAR remains poorly understood. We investigated the effects of different sampling scales on the SAR of trees on 60 small islands in the Raja Ampat archipelago (Indonesia) using standardised transects and a hierarchically nested sampling design. We compared species richness at different grain sizes ranging from single (sub)transects to whole islands and tested whether the shape of the SAR changed with sampling scale. We then determined the importance of island area, isolation, shape and habitat quality at each scale on species richness. We found strong support for scale dependency of the SAR. The SAR changed from exponential shape at local sampling scales to sigmoidal shape at the island scale indicating variation of species richness independent of area for small islands and hence the presence of a small‐island effect. Island area was the most important variable explaining species richness at all scales, but habitat quality was also important at local scales. We conclude that the SAR and drivers of species richness are influenced by sampling scale, and that the sampling design for assessing the island SARs therefore requires careful consideration.     

Spatial patterns in species–area relationships and species distribution in a West African forest–savanna mosaic

Aim To investigate the relationship between the slope z of the species–area relationship (SAR) and the intensity of spatial patterns in species number and dissimilarity for woody plants with different modes of seed dispersal. According to island theory we expect, for any given archipelago, steeper slopes and more pronounced spatial patterns for groups of less dispersive species. Location Ivory Coast, West Africa. Methods In a West African forest–savanna mosaic we collected presence–absence data for woody plant species in 49 forest islands. The parameters of the SARs were fitted by nonlinear regressions and then compared for plant species aggregated according to their mode of seed dispersal. We used the Mantel test to calculate the intensity of spatial patterns in species number, i.e. residual deviation from SAR, and species dissimilarity. Results The z‐value for bird‐dispersed species was lower (0.11) than that for wind‐dispersed species (0.27), with mammal‐dispersed species taking an intermediate value (0.16). This result suggests that, as a group, bird‐dispersed species are better colonizers. The spatial pattern in species number as well as species similarity was more pronounced for bird‐ compared with wind‐dispersed species. Main conclusions The standard interpretation of the theory of island biogeography claims that shallow slopes in the SAR imply low isolation of islands, i.e. good dispersal abilities of species. The results of our study appear to contradict this statement. The contradiction can eventually be resolved by a more detailed account of the colonization process, i.e. by distinguishing between dispersal and consecutive establishment of populations.     

island biogeography of Day Geckos (Phelsuma) in the Indian Ocean

Summary Step-wise multiple regression was employed to probe the determinants of species diversity of day geckos (Phelsuma) in the Indian Ocean. Independent variables were area, elevation, and two measures of isolation. Distance from Madagascar and island height (an indicator of habitat diversity) were the two most important predictors of species richness. Similar studies on other taxa rarely find isolation to be a major factor. The relatively poor dispersal abilities of reptiles may explain why isolation, rather than attributes of the islands, are more important in this case. The regressions also indicate that habitat diversity (assumed to correlate with maximum island elevation) is more important than area per se in determining species diversity. These results agree with predictions of the equilibrium theory of island biogeography, but historical processes have also greatly influenced species richness.     

Species–area relationships of butterflies in Europe and species richness forecasting

Species–area relationships (SARs) of European butterfly species (Rhopalocera) appear to follow power functions with Mediterranean butterflies having a much higher slope value (z=0.49) compared to the slope for the northern and eastern European countries (z=0.10). A simulated process of species extinction by a stepwise density dependent random elimination of species affected species–area patterns differently. For Mediterranean countries SAR slopes decreased, for other European countries slopes increased during the extinction process. Comparisons of species numbers before and after extinction with those predicted by a classical SAR approach differed widely and revealed that SARs are not able to predict future species numbers at local scales. For Mediterranean countries the classical SAR approach underestimated the number of species remaining after simulated extinction, for all other European countries SARs highly overestimated species numbers. These contrasting patterns indicate that changes in SAR patterns do not unequivocally point to changes in species diversity or community structure as assumed by current theory. On the other hand, the results strongly indicate that simplified applications of SARs for forecasting might give misimpressions about species loss and future biodiversity if the initial community structure, especially relative densities and numbers of species with restricted range size, are not taken into account.     

Global pattern and local variation in species–area relationships

Aim We conducted a meta‐analysis of species–area relationships (SARs) by combining several data sets and important covariates such as types of islands, taxonomic groups, latitude and spatial extent, in a hierarchical model framework to study global pattern and local variation in SARs and its consequences for prediction. Location One thousand nine hundred and eighteen islands from 94 SAR studies from around the world. Methods We developed a generalization of the power‐law SAR model, the HSARX model, which allows: (1) the inclusion of multiple focal parameters (intercept, slope, within‐study variance), (2) use of multiple effect modifiers based on a collection of SAR studies, and (3) modelling of the between‐ and within‐study variability. Results The global pattern in the SAR was the average of local SARs and had wide confidence intervals. The global SAR slope was 0.228 with 90% confidence limits of 0.059 and 0.412. The intercept, slope and within‐study variability of local SARs showed great heterogeneity as a result of the interaction of modifying covariates. Confidence intervals for these SAR parameters were narrower when other covariates in addition to area were accounted for, thus increasing the accuracy of the predictions for species richness. The significant effect of latitude and the interaction of latitude, taxa and island type on the SAR slope indicated that the ‘typical’ latitudinal diversity gradient can be reversed in isolated systems. Main conclusions The power‐law relationship underlying the HSARX model provides a good fit for non‐nested SARs across vastly different spatial scales by taking into account other covariates. The HSARX framework allows researchers to explore the complex interactions among SAR parameters and modifying variables, to explicitly study the scale dependence, and to make robust predictions on multiple levels (island, study, global) with associated prediction intervals. From a prediction perspective, it is not the global pattern but the local variation that matters.     

Towards an integrative understanding of soil biodiversity

Soil is one of the most biodiverse terrestrial habitats. Yet, we lack an integrative conceptual framework for understanding the patterns and mechanisms driving soil biodiversity. One of the underlying reasons for our poor understanding of soil biodiversity patterns relates to whether key biodiversity theories (historically developed for aboveground and aquatic organisms) are applicable to patterns of soil biodiversity. Here, we present a systematic literature review to investigate whether and how key biodiversity theories (species–energy relationship, theory of island biogeography, metacommunity theory, niche theory and neutral theory) can explain observed patterns of soil biodiversity. We then discuss two spatial compartments nested within soil at which biodiversity theories can be applied to acknowledge the scale‐dependent nature of soil biodiversity.     

Direct and indirect effects of area,energy and habitat heterogeneity on breeding bird communities

Aim To compare the ability of island biogeography theory, niche theory and species–energy theory to explain patterns of species richness and density for breeding bird communities across islands with contrasting characteristics. Location Thirty forested islands in two freshwater lakes in the boreal forest zone of northern Sweden (65°55′ N to 66°09′ N; 17°43′ E to 17°55′ E). Methods We performed bird censuses on 30 lake islands that have each previously been well characterized in terms of size, isolation, habitat heterogeneity (plant diversity and forest age), net primary productivity (NPP), and invertebrate prey abundance. To test the relative abilities of island biogeography theory, niche theory and species–energy theory to describe bird community patterns, we used both traditional statistical approaches (linear and multiple regressions) and structural equation modelling (SEM; in which both direct and indirect influences can be quantified). Results Using regression‐based approaches, area and bird abundance were the two most important predictors of bird species richness. However, when the data were analysed by SEM, area was not found to exert a direct effect on bird species richness. Instead, terrestrial prey abundance was the strongest predictor of bird abundance, and bird abundance in combination with NPP was the best predictor of bird species richness. Area was only of indirect importance through its positive effect on terrestrial prey abundance, but habitat heterogeneity and spatial subsidies (emerging aquatic insects) also showed important indirect influences. Thus, our results provided the strongest support for species–energy theory. Main conclusions Our results suggest that, by using statistical approaches that allow for analyses of both direct and indirect influences, a seemingly direct influence of area on species richness can be explained by greater energy availability on larger islands. As such, animal community patterns that seem to be in line with island biogeography theory may be primarily driven by energy availability. Our results also point to the need to consider several aspects of habitat quality (e.g. heterogeneity, NPP, prey availability and spatial subsidies) for successful management of breeding bird diversity at local spatial scales and in fragmented or insular habitats.     

Predator-dependent species-area relationships

In addition to having a positive effect on species richness (species-area relationships [SARs]), habitat area can influence the presence of predators, which can indirectly influence prey richness. While these direct and indirect effects of area on richness occur simultaneously, no research has examined how predation might contribute to SAR variation. We extend MacArthur and Wilson's equilibrium theory of island biogeography by including predation-induced shifts in prey extinction and predict that predators will reduce slopes of prey SARs. We provide support for this with data from two insular ecosystems: orthopteran richness in Ozark glades (rocky herbaceous communities within a forested matrix) with and without insectivorous lizards and zooplankton richness in freshwater ponds with and without zooplanktivorous fishes. Our results emphasize that anthropogenic activities yield simultaneous changes in processes altering diversity and that it is critical that we understand how these components of anthropogenic change interact to impact diversity.     

The latitudinal gradient of species-area relationships for vascular plants of North America

The species-area relationship (SAR), describing the increase in species richness with increasing area, and the latitudinal diversity gradient (LDG), describing the decrease in species richness with increasing latitude, are the oldest and most robust patterns in biogeography, yet connections between them remain poorly understood. Here, using 1,742 floras covering the entirety of North America north of Mexico (NAM) and including all of NAM's native species of vascular plants, we show that the slope of the SAR consistently decreases with increasing latitude. This trend is general and holds for subsets of the floras in eastern and western NAM. The southernmost latitudinal quarter of NAM exhibits SARs more than twice as steep as those of the northernmost quarter for both eastern and western regions. This decrease in SAR slope with increasing latitude is consistent with the environmental texture hypothesis and Rapoport's rule, and it suggests that more detailed studies of species endemism in relation to environmental and historical factors will yield significant insights into the underlying causes of SAR and LDG patterns.     

Predicting community structure in snakes on Eastern Nearctic islands using ecological neutral theory and phylogenetic methods

Predicting species presence and richness on islands is important for understanding the origins of communities and how likely it is that species will disperse and resist extinction. The equilibrium theory of island biogeography (ETIB) and, as a simple model of sampling abundances, the unified neutral theory of biodiversity (UNTB), predict that in situations where mainland to island migration is high, species-abundance relationships explain the presence of taxa on islands. Thus, more abundant mainland species should have a higher probability of occurring on adjacent islands. In contrast to UNTB, if certain groups have traits that permit them to disperse to islands better than other taxa, then phylogeny may be more predictive of which taxa will occur on islands. Taking surveys of 54 island snake communities in the Eastern Nearctic along with mainland communities that have abundance data for each species, we use phylogenetic assembly methods and UNTB estimates to predict island communities. Species richness is predicted by island area, whereas turnover from the mainland to island communities is random with respect to phylogeny. Community structure appears to be ecologically neutral and abundance on the mainland is the best predictor of presence on islands. With regard to young and proximate islands, where allopatric or cladogenetic speciation is not a factor, we find that simple neutral models following UNTB and ETIB predict the structure of island communities.     

Ecospace: A unified framework for understanding variation in terrestrial biodiversity

Understanding patterns in biodiversity is a core ambition in ecological research. Existing ecological theories focusing on individual species, populations, communities, or niches aid in understanding the determinants of biodiversity patterns, yet very few general models for biodiversity have emerged from simplistic approaches. We propose that a systematic, low-dimensional representation of environmental space with building blocks adopted from gradient, niche, metapopulation and assembly theory may unite old and new aspects of biodiversity theory and improve our understanding of variation in terrestrial biodiversity.We propose the term ecospace to cover the local conditions and resources underlying diversity. Our definition of ecospace encompasses abiotic position, biotic expansion and spatiotemporal continuity, which all affect the biodiversity of a biotope (α-diversity). Position refers to placement along abiotic gradients such as temperature, soil pH and fertility, leading to environmental filtering known from classical community theory. Expansion represents the build-up and diversification of organic matter that are not strictly given by position. Continuity refers to the spatiotemporal extension of position and expansion.Biodiversity is scale dependent. The contribution of one biotope to large scale diversity must be estimated by considering its unique contribution to the species richness of the surrounding landscape or region or to the biodiversity of the entire planet. In addition to the relationship between ecospace and biotope richness (α-diversity), we also propose a relation between the uniqueness of the biotope ecospace and the unique contribution of species to the surrounding larger-scale richness.Whereas the impacts of ecospace position and continuity on biodiversity have been studied in isolation, studies comparing or combining them are rare. Furthermore, biotic expansion has never been fully developed as a determinant of biodiversity, ignoring the megadiverse carbon-depending groups of insects and fungi. Precursors of the ecospace concept have been presented over the last 70 years, but they were never fully developed conceptually for terrestrial biodiversity or applied to prediction of biodiversity.Ecospace unites classical and – at times – contradicting theories such as niche theory, island biogeography theory and a suite of community assembly theories into one framework for further development of a general theory of terrestrial biodiversity.     

A global model of island biogeography

Aim The goal of our study was to build a global model of island biogeography explaining bird species richness that combines MacArthur and Wilson's area–isolation theory with the species–energy theory. Location Global. Methods We assembled a global data set of 346 marine islands representing all types of climate, topography and degree of isolation on our planet, ranging in size from 10 ha to 800,000 km². We built a multiple regression model with the number of non‐marine breeding bird species as the dependent variable. Results We found that about 85–90% of the global variance in insular bird species richness can be explained by simple, contemporary abiotic factors. On a global scale, the three major predictors — area, average annual temperature and the distance separating the islands from the nearest continent — all have constraining (i.e. triangular rather than linear) relationships with insular bird species richness. We found that the slope of the species–area curve depends on both average annual temperature and total annual precipitation, but not on isolation. Insular isolation depends not only on the distance of an island from the continent, but also on the presence or absence of other neighbouring islands. Range in elevation — a surrogate for diversity of habitats — showed a positive correlation with bird diversity in warmer regions of the world, while its effect was negative in colder regions. We also propose a global statistical model to quantify the isolation‐reducing effect of neighbouring islands. Main conclusions The variation in avian richness among islands worldwide can be statistically explained by contemporary environmental variables. The equilibrium theory of island biogeography of MacArthur and Wilson and the species–energy theory are both only partly correct. Global variation in richness depends about equally upon area, climate (temperature and precipitation) and isolation. The slope of the species richness–area curve depends upon climate, but not on isolation, in contrast to MacArthur and Wilson's theory.     

Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation

The Theory of Island Biogeography (TIB) predicts how area and isolation influence species richness equilibrium on insular habitats. However, the TIB remains silent about functional trait composition and provides no information on the scaling of functional diversity with area, an observation that is now documented in many systems. To fill this gap, we develop a probabilistic approach to predict the distribution of a trait as a function of habitat area and isolation, extending the TIB beyond the traditional species–area relationship. We compare model predictions to the body‐size distribution of piscivorous and herbivorous fishes found on tropical reefs worldwide. We find that small and isolated reefs have a higher proportion of large‐sized species than large and connected reefs. We also find that knowledge of species body‐size and trophic position improves the predictions of fish occupancy on tropical reefs, supporting both the allometric and trophic theory of island biogeography. The integration of functional ecology to island biogeography is broadly applicable to any functional traits and provides a general probabilistic approach to study the scaling of trait distribution with habitat area and isolation.     

A unified model of island biogeography sheds light on the zone of radiation

Islands acquire species through immigration and speciation. Models of island biogeography should capture both processes; however quantitative island biogeography theory has either neglected speciation or treated it unrealistically. We introduce a model where the dominance of immigration on small and near islands gives way to an increasing role for speciation as island area and isolation increase. We examine the contribution of immigration and speciation to the avifauna of 35 archipelagoes and find, consistent with our model, that the zone of radiation comprises two regions: endemic species diverged from mainland sister-species at intermediate isolation and from insular sister-species at higher levels of isolation. Our model also predicts species-area curves in accord with existing research and makes new predictions about species ages and abundances. We argue that a paucity of data and theory on species abundances on isolated islands highlights the need for island biogeography to be reconnected with mainstream ecology.     

Lizard predation alters the effect of habitat area on the species richness of insect assemblages on Bahamian isles

Aim Anolis lizard invasions are a serious threat world‐wide, and information about how this invasive predator affects the diversity of prey assemblages is important for many strategic conservation goals. It is hypothesized that these predators reduce the slope of species–area relationships (SARs) of their prey assemblages. The effects of island area and predation by anolis lizards on the species richness of insular insect assemblages were investigated. Location Twenty‐four isles around Staniel Cay, Exuma Cays, Bahamas. Methods Flying insects were sampled using half‐sized Malaise traps for three consecutive days on each island in May 2007. First, the effect of island area on the probability of lizard presence was evaluated. Then, the effects of the presence–absence of predatory lizards on SARs were analysed for the overall insect assemblage and for the assemblages of five dominant insect orders. Results Our results indicated that anolis lizards occurred primarily on larger islands. The species richness of the overall insect assemblage and five dominant insect orders significantly increased with island area. The interaction between island area and predator presence–absence significantly affected the overall insect assemblage and Diptera and Hymenoptera assemblages (but not Coleoptera, Hemiptera and Lepidoptera assemblages). The presence of predators caused decreases in the slope of the SARs. Main conclusions The presence of predatory lizards strongly affects species richness of insular insect assemblages with the island area being a crucial determinant of the species richness. Therefore, the slope of the SAR can serve as a measure of the consequence of invasive predatory species on native insect assemblages.     

Agriculture rivals biomes in predicting global species richness

Species–area relationships (SARs) provide an avenue to model patterns of species richness and have recently been shown to vary substantially across regions of different climate, vegetation, and land cover. Given that a large proportion of the globe has been converted to agriculture, and considering the large variety in agricultural management practices, a key question is whether global SARs vary across gradients of agricultural intensity. We developed SARs for mammals that account for geographic variation in biomes, land cover and a range of land‐use intensity indicators representing inputs (e.g. fertilizer, irrigation), outputs (e.g. yields) and system‐level measures of intensity (e.g. human appropriation of net primary productivity – HANPP). We systematically compared the resulting SARs in terms of their predictive ability. Our global SAR with a universal slope was significantly improved by the inclusion of any one of the three variable types: biomes, land cover, and land‐use intensity. The latter, in the form of human appropriation of net primary productivity (HANPP), performed as well as biomes and land‐cover in predicting species richness. Other land‐use intensity indicators had a lower predictive ability. Our main finding that land‐use intensity performs as well as biomes and land cover in predicting species richness emphasizes that human factors are on a par with environmental factors in predicting global patterns of biodiversity. While our broad‐scale study cannot establish causality, human activity is known to drive species richness at a local scale, and our findings suggest that this may hold true at a global scale. The ability of land‐use intensity to explain variation in SARs at a global scale had not previously been assessed. Our study suggests that the inclusion of land‐use intensity in SAR models allows us to better predict and understand species richness patterns.     

Vicariance and marine migration in continental island populations of a frog endemic to the Atlantic Coastal forest

The theory of island biogeography is most often studied in the context of oceanic islands where all island inhabitants are descendants from founding events involving migration from mainland source populations. Far fewer studies have considered predictions of island biogeography in the case of continental islands, where island formation typically splits continuous populations and thus vicariance also contributes to the diversity of island populations. We examined one such case on continental islands in southeastern Brazil, to determine how classic island biogeography predictions and past vicariance explain the population genetic diversity of Thoropa taophora, a frog endemic to the Atlantic Coastal Forest. We used nuclear microsatellite markers to examine the genetic diversity of coastal and island populations of this species. We found that island isolation has a role in shaping the genetic diversity of continental island species, with island populations being significantly less diverse than coastal populations. However, area of the island and distance from coast had no significant effect on genetic diversity. We also found no significant differences between migration among coastal populations and migration to and from islands. We discuss how vicariance and the effects of continued migration between coastal and island populations interact to shape evolutionary patterns on continental islands.     

Species‐area relationships of lemurs in a fragmented landscape in Madagascar

We used species‐area relationships (SARs) to investigate the effects of habitat loss on lemur biogeography. We measured species richness via visual surveys on line transects within 42 fragments of dry deciduous forest at the Ambanjabe field site in Ankarafantsika National Park, Madagascar. We measured human disturbance and habitat characteristics within 38 of the 42 fragments. We measured the distance between each fragment and the nearest settlement, continuous forest, and nearest neighboring fragment. We fit 10 candidate SAR models to the data using nonlinear least squares regression and compared them using Akaike's Information Criterion (AIC). To determine how habitat characteristics, as well as area, influenced species richness, we ran a hierarchical partitioning procedure to select which variables to include in generalized additive models (GAMs) and compared them using AIC. Contrary to expectations, we found that lemurs form convex SARs, without a “small island effect”, and with the power model being the most likely SAR model. Although we found that four variables (area, survey effort, and total human disturbance, and mean tree height) independently contributed greater than 10% of the variation in lemur species richness, only area was included in the most likely model. We suggest that the power model was the most likely SAR model and our inability to detect a “small island effect” are the result of Microcebus spp. being edge tolerant and capable of dispersing through matrix, scale issues in the study design, and low γ‐diversity in the landscape. However, more study is needed to determine what role human disturbance plays in influencing species richness in lemurs.