2022
DOI: 10.1016/j.isci.2022.105538
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Understanding global and regional patterns of termite diversity and regional functional traits

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Cited by 13 publications
(12 citation statements)
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“…The contribution of termites to plant litter decomposition is diversity and abundance dependent (Zanne et al., 2022). Termite diversity and abundance peak in the tropics are high in some areas of subtropics but not in temperate and northern regions (Lavelle et al., 2022; Liu et al., 2022). The Termitidae, for example, are litter‐feeders with high diversity in tropical forests (Eggleton & Tayasu, 2001), well adapted to breaking down organic matter (Bignell, 2019; Hogan et al., 1988).…”
Section: Discussionmentioning
confidence: 99%
“…The contribution of termites to plant litter decomposition is diversity and abundance dependent (Zanne et al., 2022). Termite diversity and abundance peak in the tropics are high in some areas of subtropics but not in temperate and northern regions (Lavelle et al., 2022; Liu et al., 2022). The Termitidae, for example, are litter‐feeders with high diversity in tropical forests (Eggleton & Tayasu, 2001), well adapted to breaking down organic matter (Bignell, 2019; Hogan et al., 1988).…”
Section: Discussionmentioning
confidence: 99%
“…Interpolations provide another approach to assessing patterns of diversity when insufficient data are available for species-level assessments. In interpolations, species-level data are not required; instead, representative site-based assessments are needed to cross-reference with present species using modelling approaches i.e., [ 11 , 12 ]. In these approaches, diversity can be modelled as a baseline for prioritisation or for the targeted assessment of areas with potentially high diversity.…”
Section: Bridging the Gapsmentioning
confidence: 99%
“…Given the paucity of data for most insects (and many other taxa), different approaches have been applied to circumvent issues in existing studies aiming to map richness across continents. These include interpolating richness by modelling it directly as a function of ecological drivers (termites, bees, Collembola: Liu et al, 2022;Orr et al, 2021;Potapov et al, 2023, respectively), species-level modelling within MCPs to delimit ranges, or modelling following the building of a comprehensive point based database (ants: Kass et al, 2022). Even for smaller regions, where there is high diversity, filtering suitable habitat within a polygon provides a much more targeted and realistic understanding of species ranges (Chesshire et al, 2023), and in all of these studies the impact of data biases were limited either through interpolation of richness for data poor regions, or via aggregation of further data followed by modelling, and in all of them habitat filters were applied to ensure that analyses were accurate.…”
Section: Measuring Diversity In the Face Of Biasesmentioning
confidence: 99%
“…If sufficient data are available either models or filtered convex polygons can be used to map species ranges. Whereas when insufficient data are available and richness is mapped (Liu et al, 2022;Orr et al, 2021;Potapov et al, 2023), inventories of species richness are used and richness itself is reprojected using models. These approaches can reproject richness patterns to a reasonable degree, if sufficient inventories have been carried out across all major environmental conditions, and assuming that biogeographic differences will not influence overall richness patterns.…”
Section: Using Data To Enable Conservation Planningmentioning
confidence: 99%