Showing papers by "Kostas A. Triantis published in 2019"

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.

sars: an R package for fitting, evaluating and comparing species–area relationship models

Abstract: The species–area relationship (SAR) constitutes one of the most general ecological patterns globally. A number of different SAR models have been proposed. Recent work has shown that no single model universally provides the best fit to empirical SAR datasets: multiple models may be of practical and theoretical interest. However, there are no software packages available that a) allow users to fit the full range of published SAR models, or b) provide functions to undertake a range of additional SAR-related analyses. To address these needs, we have developed the R package ‘sars’ that provides a wide variety of SAR-related functionality. The package provides functions to: a) fit 20 SAR models using non-linear and linear regression, b) calculate multi-model averaged curves using various information criteria, and c) generate confidence intervals using bootstrapping. Plotting functions allow users to depict and scrutinize the fits of individual models and multi-model averaged curves. The package also provides additional SAR functionality, including functions to fit, plot and evaluate the random placement model using a species–sites abundance matrix, and to fit the general dynamic model of oceanic island biogeography. The ‘sars’ R package will aid future SAR research by providing a comprehensive set of simple to use tools that enable in-depth exploration of SARs and SAR-related patterns. The package has been designed to allow other researchers to add new functions and models in the future and thus the package represents a resource for future SAR work that can be built on and expanded by workers in the field.

Beyond the Last Glacial Maximum: Island endemism is best explained by long‐lasting archipelago configurations

Abstract: Aim: To quantify the influence of past archipelago configuration on present-day insular biodiversity patterns, and to compare the role of long-lasting archipelago configurations over the Pleistocene to configurations of short duration such as at the Last Glacial Maximum (LGM) and the present-day. Location: 53 volcanic oceanic islands from 12 archipelagos worldwide—Azores, Canary Islands, Cook Islands, Galapagos, Gulf of Guinea, Hawaii, Madeira, Mascarenes, Pitcairn, Revillagigedo, Samoan Islands and Tristan da Cunha. Time period: The last 800 kyr, representing the nine most recent glacial–interglacial cycles. Major taxa studied: Land snails and angiosperms. Methods: Species richness data for land snails and angiosperms were compiled from existing literature and species checklists. We reconstructed archipelago configurations at the following sea levels: the present-day high interglacial sea level, the intermediate sea levels that are representative of the Pleistocene and the low sea levels of the LGM. We fitted two alternative linear mixed models for each archipelago configuration using the number of single-island endemic, multiple-island endemic and (non-endemic) native species as a response. Model performance was assessed based on the goodness-of-fit of the full model, the variance explained by archipelago configuration and model parsimony. Results: Single-island endemic richness in both taxonomic groups was best explained by intermediate palaeo-configuration (positively by area change, and negatively by palaeo-connectedness), whereas non-endemic native species richness was poorly explained by palaeo-configuration. Single-island endemic richness was better explained by intermediate archipelago configurations than by the archipelago configurations of the LGM or present-day. Main conclusions: Archipelago configurations at intermediate sea levels—which are representative of the Pleistocene—have left a stronger imprint on single-island endemic richness patterns on volcanic oceanic islands than extreme archipelago configurations that persisted for only a few thousand years (such as the LGM). In understanding ecological and evolutionary dynamics of insular biota it is essential to consider longer-lasting environmental conditions, rather than extreme situations alone.

Can additive beta-diversity be reliably partitioned into nestedness and turnover components?

Abstract: Aims: Quantifying β-diversity (differences in the composition of communities) is central to many ecological studies. There are many β-diversity metrics, falling mostly into two approaches: variance-based (e.g., the Sorensen index), or diversity partitioning (e.g., additive β-diversity). The former cannot be used when species–sites matrices are unavailable (which is often the case in island biogeography in particular) and only species richness data are provided. Recently, efforts have been made to partition additive β-diversity, a metric calculated using only α-diversity and γ-diversity, into nestedness and turnover components (termed here “richness-only β-diversity partitioning”). We set out to test whether this form of β-diversity partitioning generates interpretable results, comparable with metrics based on species incidence β-diversity partitioning. Location: Global. Time period: Present day. Major taxa studied: Multiple taxa. Methods: We first provide a brief review of β-diversity partitioning methods, with a particular focus on the development of richness-only β-diversity partitioning. Second, we use 254 empirical incidence matrices (provided with the paper) sourced from the literature to measure turnover and nestedness using incidence β-diversity partitioning, comparing the resulting values with those calculated using richness-only β-diversity. Results: We provide an account of the emergence of β-diversity partitioning, with particular reference to the analysis of richness-only datasets, and to the definition and usage of the relevant metrics. Analytically, we report weak correlations between turnover and nestedness calculated using the two different approaches. We show that this is because identical values of α-diversity and γ-diversity can correspond to incidence matrices with a range of different structures. Main conclusions: Our results demonstrate that the use of richness-only β-diversity partitioning to measure turnover and nestedness is problematic and can produce patterns unrelated to conventional measures of turnover and nestedness. We therefore recommend that more accurate definitions are adopted for these terms in future studies.