Dataset Information

A global model of island species-area relationships.

ABSTRACT: The increase in species richness with island area (ISAR) is a well-established global pattern, commonly described by the power model, the parameters of which are hypothesized to vary with system isolation and to be indicative of ecological process regimes. We tested a structural equation model of ISAR parameter variation as a function of taxon, isolation, and archipelago configuration, using a globally distributed dataset of 151 ISARs encompassing a range of taxa and archipelago types. The resulting models revealed a negative relationship between ISAR intercept and slope as a function of archipelago species richness, in turn shaped by taxon differences and by the amount and disposition of archipelago area. These results suggest that local-scale (intra-archipelago) processes have a substantial role in determining ISAR form, obscuring the diversity patterns predicted by island theory as a function of archipelago isolation. These findings have implications for the use and interpretation of ISARs as a tool within biogeography, ecology, and conservation.

SUBMITTER: Matthews TJ

PROVIDER: S-EPMC7056938 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

A global model of island species-area relationships.

Matthews Thomas J TJ Rigal François F Triantis Kostas A KA Whittaker Robert J RJ

Proceedings of the National Academy of Sciences of the United States of America 20190530 25

The increase in species richness with island area (ISAR) is a well-established global pattern, commonly described by the power model, the parameters of which are hypothesized to vary with system isolation and to be indicative of ecological process regimes. We tested a structural equation model of ISAR parameter variation as a function of taxon, isolation, and archipelago configuration, using a globally distributed dataset of 151 ISARs encompassing a range of taxa and archipelago types. The resul ...[more]

PMID: 31147465

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Project description:AimTo define biome-scale hotspots of phylogenetic and functional mammalian biodiversity (PD and FD, respectively) and compare them to 'classical' hotspots based on species richness (SR) only.LocationGlobal.MethodsSR, PD & FD were computed for 782 terrestrial ecoregions using distribution ranges of 4616 mammalian species. We used a set of comprehensive diversity indices unified by a recent framework that incorporates the species relative coverage in each ecoregion. We build large-scale multifaceted diversity-area relationships to rank ecoregions according to their levels of biodiversity while accounting for the effect of area on each diversity facet. Finally we defined hotspots as the top-ranked ecoregions.ResultsWhile ignoring species relative coverage led to a relative good congruence between biome top ranked SR, PD and FD hotspots, ecoregions harboring a rich and abundantly represented evolutionary history and functional diversity did not match with top ranked ecoregions defined by species richness. More importantly PD and FD hotspots showed important spatial mismatches. We also found that FD and PD generally reached their maximum values faster than species richness as a function of area.Main conclusionsThe fact that PD/FD reach faster their maximal value than SR may suggest that the two former facets might be less vulnerable to habitat loss than the latter. While this point is expected, it is the first time that it is quantified at global scale and should have important consequences in conservation. Incorporating species relative coverage into the delineation of multifaceted hotspots of diversity lead to weak congruence between SR, PD and FD hotspots. This means that maximizing species number may fail at preserving those nodes (in the phylogenetic or functional tree) that are relatively abundant in the ecoregion. As a consequence it may be of prime importance to adopt a multifaceted biodiversity perspective to inform conservation strategies at global scale.

Project description:BackgroundThe positive relationship between habitat area and species number is considered a fundamental rule in ecology. This relationship predicts that the link number of species interactions increases with habitat area, and structure is related to habitat area. Biological invasions can affect species interactions and area relationships. However, how these relationships change at different spatial scales has remained unexplored. We analysed understory plant-pollinator networks in seven temperate forest sites at 20 spatial scales (radius 120-2020 m) to clarify scale-associated relationships between forest area and plant-pollinator networks.ResultsThe pooled data described interactions between 18 plant (including an exotic) and 89 pollinator (including an exotic) species. The total number of species and the number of interaction links between plant and pollinator species were negatively correlated with forest area, with the highest correlation coefficient at radii of 1520 and 1620 m, respectively. These results are not concordant with the pattern predicted by species-area relationships. However, when associations with exotic species were excluded, the total number of species and the number of interaction links were positively correlated with forest area (the highest correlation coefficient at a radius of 820 m). The network structure, i.e., connectance and nestedness, was also related to forest area (the highest correlation coefficients at radii of 720-820 m), when associations with exotics were excluded. In the study area, the exotic plant species Alliaria petiolata, which has invaded relatively small forest patches surrounded by agricultural fields, may have supported more native pollinator species than initially expected. Therefore, this invasive plant may have altered the original relationships between forest area and plant-pollinator networks.ConclusionsOur results demonstrate scale-dependent effects of forest area on the size and structure of plant-pollinator networks. We also suggest that a single exotic plant species can impact plant-pollinator networks, even in temperate continental habitats.

Project description:Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Dataset Information

A global model of island species-area relationships.

Publications

A global model of island species-area relationships.

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