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Springer, Landscape Ecology, 9(37), p. 2363-2382, 2022

DOI: 10.1007/s10980-022-01417-9

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Traits influence reptile responses to fire in a fragmented agricultural landscape

Journal article published in 2022 by J. Lazzari ORCID, C. F. Sato ORCID, D. A. Driscoll ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Context Habitat loss and fragmentation can interact with other threats, including altered fire regimes, and responses to these effects can be mediated by functional traits. Objectives To determine how richness and abundance of reptile trait groups respond to habitat fragmentation, patch isolation and fire. Methods We surveyed reptiles in 30 sites over 3 years. Sites in remnant patches in farmland were adjacent to a conservation park with either recently burnt or long-unburnt habitat. The remnant patches were stratified by distance from the reserve. Sites were spatially paired, and we experimentally burnt one of each pair in farmland. Trait groups included size, reproduction, habitat position, diet, and activity period. Results None of the trait groups benefited from experimental burns, while the burns reduced abundance of viviparous, small, and above-ground species. Species richness was lower in isolated sites than in sites close to the conservation park, while generalist trait groups appeared unaffected by patch isolation. Large-sized reptiles had higher abundance in remnants. There was not more rapid colonisation of burnt sites near recently burnt conservation park. Instead, low initial abundance may have been caused by fire in combination with drought, with high rainfall during the study allowing recovery and spill-over into adjacent remnants. Conclusions Landscape structure appears to interact with natural fires, restoration burns and longer-term climatic trends to influence the abundance and distribution of reptiles. Traits mediate responses, enabling us to formulate a set of testable mechanistic hypotheses, which illustrates a pathway to generalisation and prediction.