Abstract

Across the planet, high-intensity farming has transformed native vegetation into monocultures, decreasing biodiversity on a landscape scale. Yet landscape-scale changes to biodiversity and community structure often emerge from processes operating at local scales. One common process that can explain changes in biodiversity and community structure is the creation of abrupt habitat edges, which, in turn, generate edge effects. Such effects, while incredibly common, can be highly variable across space and time; however, we currently lack a general analytical framework that can adequately capture such spatio-temporal variability. We extend previous approaches for estimating edge effects to a non-linear mixed modeling framework that captures such spatio-temporal heterogeneity and apply it to understand how agricultural land-uses alter wildlife communities. We trapped small mammals along a conservation-agriculture land-use interface extending 375 m into sugarcane plantations and conservation land-uses at three sites during dry and wet seasons in Swaziland, Africa. Sugarcane plantations had significant reductions in species richness and heterogeneity, and showed an increase in community similarity, suggesting a more homogenized small mammal community. Furthermore, our modeling framework identified strong variation in edge effects on communities across sites and seasons. Using small mammals as an indicator, intensive agricultural practices appear to create high-density communities of generalist species while isolating interior species in less than 225 m. These results illustrate how agricultural land-use can reduce diversity across the landscape and that effects can be masked or magnified, depending on local conditions. Taken together, our results emphasize the need to create or retain natural habitat features in agricultural mosaics.

Highlights

  • With human population growth as its catalyst, agricultural production has become the dominant land-use on the planet, responsible for altering and endangering wildlife communities on a massive scale [1,2,3]

  • We examined the F statistics, degrees of freedom (DF) and p-value of each parameter to determine its importance in explaining variation in the metric

  • We extended the models developed by Ewers and Didham [19] to allow for random intercepts and random coefficients

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Summary

Introduction

With human population growth as its catalyst, agricultural production has become the dominant land-use on the planet, responsible for altering and endangering wildlife communities on a massive scale [1,2,3]. High-intensity farming has transformed native vegetation into monocultures thereby decreasing biodiversity on a landscape scale over the last several decades [4,5]. This pattern has been especially evident over the last 40 years in Swaziland (52,233 ha of sugarcane cultivation in 2006/ 2007) [6] and eastern southern Africa (675,911 ha cultivation in 2009/2010) [7] where lowland savannahs have undergone continued conversion from native vegetation into sugarcane (Saccharum spp.) production [8,9]. Understanding the costs and benefits of habitat edges in agricultural landscapes remains an important issue in agricultural conservation [13]

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