Ecological impact assessment of climate change and habitat loss on wetland vertebrate assemblages of the Great Barrier Reef catchment and the influence of survey bias. Issue 10 (24th March 2021)

• Record Type: Journal Article
• Authors: Canning, Adam D.; Waltham, Nathan J.
• Is Part Of: Ecology and evolution. Volume 11:Issue 10(2021)
• Page Start: 5244
• Page End: 5254
• Publication Date: 2021-03-24
• Subjects: climate change -- Great Barrier Reef -- species distribution modeling -- survey bias -- Wetland loss; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.7412
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: Wetlands are among the most vulnerable ecosystems, stressed by habitat loss and degradation from expanding and intensifying agricultural and urban areas. Climate change will exacerbate the impacts of habitat loss by altering temperature and rainfall patterns. Wetlands within Australia's Great Barrier Reef (GBR) catchment are not different, stressed by extensive cropping, urban expansion, and alteration for grazing. Understanding how stressors affect wildlife is essential for the effective management of biodiversity values and minimizing unintended consequences when trading off the multiple values wetlands support. Impact assessment is difficult, often relying on an aggregation of ad hoc observations that are spatially biased toward easily accessible areas, rather than systematic and randomized surveys. Using a large aggregate database of ad hoc observations, this study aimed to examine the influence of urban proximity on machine‐learning models predicting taxonomic richness and assemblage turnover, relative to other habitat, landscape, and climate variables, for vertebrates dwelling in the wetlands of the GBR catchment. The distance from the nearest city was, by substantial margins, the most influential factor in predicting the richness and assemblage turnover of all vertebrate groups, except fish. Richness and assemblage turnover was predicted to be greatest nearest the main urban centers. The extent of various wetland habitats was highly influential in predicting the richness of all groups, while climate (predominately the rainfall in the wettest quarter) was highly influential in predicting assemblage turnover for all groups. Bias of survey records toward urban centers strongly influenced our ability to model wetland‐affiliated vertebrates and may obscure our understanding of how vertebrates respond to habitat loss and climate change. This reinforces the need for randomized and systematic surveys to supplement existing ad hoc surveys. We urge modelers in other jurisdictions to better portray the potential influence of survey biases when modeling species distributions. Abstract : We show that, when using a large citizen science biodiversity, modeling the distributions of vertebrate species richness and assemblages within Australia's Great Barrier Reef catchment is heavily influenced by the biased collection of data nearest to cities. While citizen science can be a useful supplement to existing data, it should not be a replacement for randomized and systematic ecological surveys. Failing to understand how species change with wetland habitat extent and climate means that it will be difficult for managers to understand the consequences of climate change or outcomes expected from wetland restoration.