Resistance of mound-building termites to anthropogenic land-use change

Davies, Andrew B, Brodrick, Philip G, Parr, Catherine L ORCID: 0000-0003-1627-763X and Asner, Gregory P (2020) Resistance of mound-building termites to anthropogenic land-use change. ENVIRONMENTAL RESEARCH LETTERS, 15 (9). 094038-094038.

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Abstract

<jats:title>Abstract</jats:title> <jats:p>Humans pose a major threat to many species through land-use change in virtually every habitat. However, the extent of this threat is largely unknown for invertebrates due to challenges with investigating their distributions at large scales. This knowledge gap is particularly troublesome for soil macrofauna because of the critical roles many of these organisms perform as ecosystem engineers. We used a combination of high-resolution airborne Light Detection and Ranging and deep learning models to map the distribution of the ecologically important termite genus <jats:italic>Macrotermes</jats:italic> across a South African savanna land-use gradient, quantifying the effects of land-use change on patterns of mound densities, heights and spatial patterning. Despite significant anthropogenic alteration to landscapes, termite mounds persisted and shared a number of similarities to mounds in untransformed areas. Mean mound height was not substantially reduced in transformed landscapes, and over-dispersion of mounds at localized scales was conserved. However, mound densities were partially reduced, and height distributions in transformed areas differed to those in protected areas. Our findings suggest that mound-building termites persist even in areas of relatively high human disturbance, but also highlight important differences in termite distributions that could lead to reductions in ecosystem services provided by termites in human-modified landscapes. The persistence of at least half of mounds in human-modified landscapes could serve as starting points for savanna restoration.</jats:p>

Item Type:	Article
Uncontrolled Keywords:	convolutional neural networks, deep learning, LiDAR, Macrotermes, savanna, South Africa, termite mounds
Depositing User:	Symplectic Admin
Date Deposited:	14 Jul 2020 09:52
Last Modified:	18 Jan 2023 23:46
DOI:	10.1088/1748-9326/aba0ff
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3093546