Endangered at the edge of metropolis : using geospatial analysis to apply the IUCN red list criteria to Hong Kong ants

Abstract

Insects are a ubiquitous and essential part of the biosphere, but are largely absent from conservation research and action. Less than 1% of ant species globally have been assessed for placement on the IUCN Red List, the most widely used indicator of extinction risk. This troubling pattern is evident in most other insect taxa. This conservation gap has been bridged through development of new methods using species distribution modeling (SDM) to conduct local conservation assessments of the ants of Hong Kong. This mountainous subtropical region is home to a rich ant fauna (>300 spp.) despite its small area (1,104 km2) and high anthropogenic pressure, and is representative of the understudied Indomalayan biogeographic region. Proliferation of high quality global gridded GIS datasets has spurred a renaissance in biogeography, and are particularly useful for modeling global species distributions. However these data, often 1 km at the finest scale available, are too coarse for precise designation of conservation priority areas and regional SDM. Further, these global datasets may be inaccurate, as they do not incorporate locally relevant predictors and therefore likely underestimate fine scale climate variation. In Chapter 2, the development of a comprehensive set of 30 m resolution rasters for Hong Kong is described. The data include topographic variables, a vegetation index, and interpolated climate variables derived from weather station observations. Validation statistics that convey each climate variable's reliability are presented, the results are compared to a widely used global dataset, finding that the new models consistently reflect greater climatic variation. This is the first set of published environmental rasters specific to Hong Kong. Chapter 3 describes the approach developed to use this data to assess the conservation status of Hong Kong’s ant species. Hurdles to such insect conservation efforts include high species count, sparse occurrence data, and inability to estimate key metrics like population size. To circumvent this, spatially congruent recent and historical distribution data were leveraged to infer shifts in species’ abundance. Historical specimens were checked against newly identified material to ensure taxonomic consistency. New targeted climatic sampling increased confidence in species’ preferred habitats. With the high data quality achieved through these efforts, SDM was used to estimate range size and inform bulk conservation assessments. It was found that high elevation species are threatened disproportionately. Key priority areas for ant conservation were delimited by weighting and summing SDM predictions, and then compared to the existing protected areas. The newly developed Hong Kong geographic data will facilitate future environmental and ecological studies in this region of the world, where a spatial understanding of urbanization, introduced species pressure, and conservation efforts is critical. This work is a step toward greater representation of insects in conservation and is, to my knowledge, the first extensive assessment of a regional ant assemblage. Threatened species can now be targeted for investigation into the causes and consequences of their peril. Understanding the advantages and limitations of such high-throughput approaches will be needed as the scientific community works to include the bulk of Earth's biodiversity in conservation action.