Fine-Tuned Ecological Niche Models Unveil Climatic Suitability and Association with Vegetation Groups for Selected Chaetocnema Species in South Africa (Coleoptera: Chrysomelidae)

Francesco Cerasoli,Paola D’Alessandro,Maurizio Biondi

doi:10.3390/d14020100

Abstract

Despite beetles (Coleoptera) representing most existing animal species, the ecological and biogeographical factors shaping their distribution are still unclear in many regions. We implemented state-of-the-art ecological niche models (ENMs) and niche overlap analysis to investigate climate–occurrence patterns for five flea beetle species of the genus Chaetocnema in South Africa (C. brincki, C. danielssoni, C. darwini, C. gahani, and C. natalensis). ENMs were fitted through Maxent and Random Forests, testing various parameterizations. For each species, tuned ENMs attaining good discrimination on spatially independent test data were selected to predict suitability across the study region and individuate its main climatic drivers. Percentage coverage of climatically suitable areas by seventeen Afrotropical vegetation formations was also computed. Predicted suitable areas do not extend far away from known presence localities, except for C. brincki and C. gahani in north-eastern South Africa. Temperate grasslands and shrublands cover most of suitable areas for C. brincki and C. gahani, along with warm temperate forests, as well as for C. danielssoni, in this case being followed by tropical flooded and swamp forests. Climatic suitability for C. darwini mainly relates to the Mediterranean grasslands and scrublands of the southern coastal region, while suitable areas for C. natalensis encompass various vegetation formations, coherently with its wide distribution. The environmental niche of C. danielssoni significantly overlaps with those of the wide-ranging C. darwini and C. natalensis, suggesting that historical factors, rather than low climatic tolerance, has determined its restricted distribution in the Western Cape Province. Maxent and Random Forests were confirmed to be of great help in disentangling the environment–occurrence relationships and in predicting suitability for the target species outside their known range, but they need to be properly tuned to perform at their best.

Highlights

Insects are by far the most diversified animal class, with more than one million species already described and at least 5 million ones estimated to currently exist [1]
In terms of chorotypes, C. brincki belongs to the South-East African chorotype, C. darwini and C. natalensis share the Southern African chorotype, C. danielssoni is a South-West Afrotropical species, while C. gahani falls into the Eastern Afrotropical chorotype [24,32]
The alphahull-based extents of occurrence (EOO) estimated for Chaetocnema brincki (Figure 3a) and C. gahani (Figure 3d) span eastern Lesotho and the South African region, located between the latter and Swaziland, which is partially included in the MaputalandPondoland-Albany biodiversity hotspot [24], with the range of the former species entirely nested within that of the latter

Summary

Introduction

Insects are by far the most diversified animal class, with more than one million species already described and at least 5 million ones estimated to currently exist [1] Their astonishing morphological and functional diversity translates into fundamental ecological roles, spanning from plant pollination to nutrient recycling within different environmental matrices (e.g., soil, freshwaters), to food supply for secondary consumers and pests’ biocontrol [2,3,4]. Despite their invaluable importance for the maintenance of the ecological processes shaping the Earth’s biodiversity, large knowledge gaps still affect the taxonomy (i.e., Linnean shortfall) and biogeography (i.e., Wallacean shortfall) of several insect taxa [5]. Lack of comprehensive occurrence data in these regions is likely limiting our understanding of the ecological drivers constraining the current distribution of several beetle species, which in turn is detrimental to the task of limiting the above-mentioned

Methods

Results

Discussion

Conclusion