Long‐term monitoring in endangered woodlands shows effects of multi‐scale drivers on bird occupancy

Abstract

Aims The effect of spatial scale on the location and abundance of species has long been a major topic of interest in ecology. Accounting for key drivers at multiple scales is critical for rigorous description of patterns of species distribution and biodiversity change. We quantified the effects of potential drivers of bird occupancy across a geographically dispersed, but heavily disturbed and fragmented ecosystem. Location Threatened Box‐Gum Grassy Woodlands in south‐eastern Australia, which stretch across 9° of latitude (~900 km). Taxon Birds (Class Aves). Methods We grouped data from four monitoring studies of birds that spanned 10–22 years in Box‐Gum Grassy Woodlands. We then employed joint species distribution modelling to investigate multi‐species responses to environmental drivers measured at patch, landscape and regional scales, and selected combinations of all three. Results We show that in Box‐Gum Grassy Woodlands: vegetation structure influences bird occupancy beyond the presence of the despotic Noisy Miner (Manorina melanocephala); woodland cover is more important than vegetation productivity and topographic position; bird occupancy is sensitive to a combination of average climate, seasonality, and summer and winter extremes; and there is limited redundancy between drivers of bird occupancy at different scales. Species differ most in their response to presence of the Noisy Miner, high summer temperatures and nearby woodland cover. Main Conclusions Quantifying the influence of environmental drivers that act at different spatial scales is valuable for understanding patterns of bird species occurrence. Fine‐scale studies can benefit from considering the climate and biogeographical context in which the research occurs. Conversely, large‐scale studies should recognise that downscaling species occupancy projections from continental to patch scales requires careful consideration of the role of patch‐scale vegetation.

Imprints of historical and ecological factors in the phylogenetic structure of Australian Meliphagides assemblages

“…Small passerines (<60 g) are excluded from the sites that they occupy and only large‐bodied species remain in the presence of these strong interactors (Kutt et al, 2016; Thomson et al, 2015). It suggests that the presence of miners acts as a sieve and the composition of bird assemblages is homogenized where they occur (Hingee et al, 2022). In turn, these results evince that it is not straightforward to differentiate between patterns arising from environmental filtering processes from those arising from species interactions since, in some circumstances, the existence of strong competition (widespread community‐level displacement) generates an imprint similar to that expected if the environment exerts an overwhelming influence on community assembly.…”

No country for small birds: Potential positive association among medium‐sized, aggressive species in Australian bird communities

“…Some of them exert a negative influence on other species which end up being extirpated from the area. In turn, these winner species can interact positively as recent studies have reported (Hingee et al, 2022;Westgate et al, 2021). However, these positive associations may merely reflect shared ecological preferences and/or indirect effects.…”

A bird occupancy estimator for land practitioners in the NSW South Western Slopes bioregion

“…Our method for selecting environmental predictors of species occupancy followed Hingee et al . (2022) and is the topic of the Supporting Information (Appendix ). The model passed a number of diagnostic tests (Section 5.5 of Appendix : Model fitting and selection), suggesting that estimates of occupancy probability, and estimated uncertainty of these estimates, can be trusted when the modelling assumptions are satisfied.…”

“…The model accounted for interspecies correlation and imperfect detection (Tobler et al 2019). Our method for selecting environmental predictors of species occupancy followed Hingee et al (2022) and is the topic of the Supporting Information (Appendix S1-S3). The model passed a number of diagnostic tests (Section 5.5 of Appendix S1: Model fitting and selection), suggesting that estimates of occupancy probability, and estimated uncertainty of these estimates, can be trusted when the modelling Major site-scale predictors of species occupancy were the presence of the hyper-aggressive native honeyeater, the Noisy Miner (Manorina melanocephala), and whether the woodland area was planted versus remnant.…”