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Community Ecology

, Volume 11, Issue 2, pp 179–186 | Cite as

Identifying the drivers of pond biodiversity: the agony of model selection

  • M. GioriaEmail author
  • G. Bacaro
  • J. Feehan
Article
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Abstract

Ponds contribute substantially to the maintenance of regional biodiversity. Despite a growing body of literature on biotic-abiotic relationships in ponds, only few generalizations have been made. The difficulty in identifying the main drivers of pond biodiversity has been typically attributed to the heterogeneity of the local and regional conditions characterizing ponds. However, little is known on how the use of different analytical approaches and community response variables affects the results of analysis of community patterns in ponds. Here, we used a range of methods to model the response of water beetle and plant community data (species richness and composition) to a set of 12 environmental and management variables in 45 farmland ponds. The strength of biotic-abiotic relationships and the contribution of each variable to the overall explained variance in the reduced models varied substantially, for both plants and beetles, depending on the method used to analyze the data. Models of species richness included a lower number of variables and explained a larger amount of variation compared to models of species composition, reflecting the higher complexity characterizing multispecies response matrices. Only two variables were never selected by any of the model, indicative of the heterogeneity characterizing pond ecosystems, while some models failed to select important variables. Based on our findings, we recommend the use of multiple modeling approaches when attempting to identify the principal determinants of biodiversity for each response variable, including at least a non-parametric approach, as well as the use of both species richness and composition as the response variables. The results of this modeling exercise are discussed in relation to their practical use in the formulation of conservation strategies.

Keywords

Forward selection Multivariate analysis Species richness Water beetle Wetland plant 

Abbreviations

AIC

Akaike Information Criterion

BIC

Bayesian Information Criterion

CCA

Canonical Correspondence Analysis

FP

Forward Procedure of variable selection

GLM

Generalized Linear Model

DISTLM

Distance-based Linear regression model

BIO-ENV

Permutational multivariate model of biotic-abiotic relationships

PERMANOVA

PERmutational Multivariate ANalysis Of VAriance

VIF

Variance Inflation Factor

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© Akadémiai Kiadó, Budapest 2010

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.School of Agriculture, Food Science and Veterinary MedicineUniversity College DublinBelfield, Dublin 4Ireland
  2. 2.BIOCONNET, Biodiversity and Conservation Network, Department of Environmental Science “G. Sarfatti”University of SienaSienaItaly

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