Using biological records to infer long-term occupancy trends of mammals in the UK

Frazer G Coomber,Bethany R Smith,Tom A August,Colin A Harrower,Gary D Powney,Fiona Mathews

doi:10.1016/j.biocon.2021.109362

Abstract

Conservation action is usually triggered by detecting trends in species’ population size, geographical range, or occupancy (proportion of sites occupied). Robust estimates of these metrics are often required by policy makers and practitioners, yet many species lack dedicated monitoring schemes. An alternative source of data for trend estimation is provided by biological records, i.e., species presence information. In the UK, there are millions of such records, but biological trend assessments are often hindered by biases caused by the unstructured way in which they are collected. Recent advances in occupancy modelling that account for changes in survey effort and detectability over time mean that robust occupancy trends can now be estimated from these records. By grouping mammal species into survey assemblages — species likely to be recorded at the same time — and applying occupancy models, this study provides estimates of long-term (1970 to 2016) occupancy trends for 37 terrestrial mammal species from the UK. The inter-annual occupancy growth rates for these species ranged from -4.26% to 11.25%. This information was used to classify two species as strongly decreasing, five as decreasing, 12 as no change, 11 as increasing and seven as strongly increasing. Viewing the survey assemblages as a whole, the occupancy growth rates for small mammals were, on average, decreasing (-0.8% SD 1.57), whereas bats and deer (0.9% SD 1.30) were increasing (3.8% SD 3.25; 0.9% SD 1.30 respectively), and mid-sized mammals were stable (-0.3 SD 1.72). These results contribute much-needed information on a number of data deficient species, and provide evidence for prioritising conservation action.

Highlights

Assessments of a species’ extinction risk, conservation status, and responses to interventions, rely on the detection of trends in parameters such as abundance and distribution (Butchart et al, 2010; Maes et al, 2015)
Cross-species comparisons, which are needed to prioritise conservation action, are difficult because different metrics are applied to different taxa; density and abundance (e.g. Judge et al, 2014); raw count data (e.g. Wright et al, 2014); population indices, and occupancy
This study developed a method to group mammal species into survey as semblages enabling the inference of non-detections and creation of detection histories from biological records

Summary

Introduction

Assessments of a species’ extinction risk, conservation status, and responses to interventions, rely on the detection of trends in parameters such as abundance and distribution (Butchart et al, 2010; Maes et al, 2015). The huge repositories of biological records (e.g. eBird, GBIF, iRecord and NBN: Pocock et al, 2015; Sullivan et al, 2009; Telenius, 2011) that have primarily been collected opportunistically by citizen scientists present an opportunity to derive trend metrics to complement those obtained from systematic surveys. These presence-only records provide precise information across large spatial and temporal scales on where, and when, a species was recorded (Powney and Isaac, 2015). They can suffer from biases in temporal and spatial variability in recorder effort (Pre ndergast et al, 1993), imperfect detection (Chen et al, 2013), and se lective recording of species (Szabo et al, 2010), and these factors can hinder trend estimations

Methods

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Discussion

Conclusion