Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four ‘virtual’ species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.

Article impact statement: Protected areas are needed to facilitate waterbird distribution change in response to climate warming in the Western Palearctic.

Wetland bird species have been declining in population size worldwide as climate warming and land-use change affect their suitable habitats. We used species distribution models (SDMs) to predict changes in range dynamics for 64 non-passerine wetland birds breeding in Europe, including range size, position of centroid, and margins. We fitted the SDMs with data collected for the first European Breeding Bird Atlas (EBBA1) and climate and land-use data to predict distributional changes over a century (the 1970s–2070s). The predicted annual changes were then compared to observed annual changes in range size and range centroid over a time period of 30 years using data from the second European Breeding Bird Atlas (EBBA2). Our models successfully predicted ca. 75% of the 64 bird species to contract their breeding range in the future, while the remaining species (mostly southerly breeding species) were predicted to expand their breeding ranges northward. The northern margins of southerly species and southern margins of northerly species, both, predicted to shift northward. Predicted changes in range size and shifts in range centroids were broadly positively associated with the observed changes, although some species deviated markedly from the predictions. The predicted average shift in core distributions was ca. 5 km/year towards the north (5% Northeast, 45% North, and 40% Northwest), compared to a slower observed average shift of ca. 3.9 km/year. Predicted changes in range centroids were generally larger than observed changes, which suggests that bird distribution changes may lag behind environmental changes leading to “climate debt. We suggest that predictions of SDMs should be viewed as qualitative rather than quantitative outcomes, indicating that care should be taken concerning single species. Still, our results highlight the urgent need for management actions such as wetland creation and restoration to improve wetland birds' resilience to the expected environmental changes in the future.

Few empirical studies have quantified relationships between changing weather and migratory songbirds, but such studies are vital in a time of rapid climate change. Climate change has critical consequences for avian breeding ecology, geographic ranges, and migration phenology. Changing precipitation and temperature patterns affect habitat, food resources, and other aspects of birds’ life history strategies. Such changes may disproportionately affect species confined to rare or declining ecosystems, such as temperate grasslands, which are among the most altered and endangered ecosystems globally. We examined the influence of changing weather on the dickcissel (Spiza americana), a migratory songbird of conservation concern that is an obligate grassland specialist. Our study area in the North American Great Plains features high historic weather variability, where climate change is now driving higher precipitation and temperatures as well as higher frequencies of extreme weather events including flooding and droughts. Dickcissels share their breeding grounds with brown-headed cowbirds (Molothrus ater), brood parasites that lay their eggs in the nests of other songbirds, reducing dickcissel productivity. We used 9 years of capture-recapture data collected over an 18-year period to test the hypothesis that increasing precipitation on dickcissels’ riparian breeding grounds is associated with abundance declines and increasing vulnerability to cowbird parasitism. Dickcissels declined with increasing June precipitation, whereas cowbirds, by contrast, increased. Dickcissel productivity appeared to be extremely low, with a 3:1 ratio of breeding male to female dickcissels likely undermining reproductive success. Our findings suggest that increasing precipitation predicted by climate change models in this region may drive future declines of dickcissels and other songbirds. Drivers of these declines may include habitat and food resource loss related to flooding and higher frequency precipitation events as well as increased parasitism pressure by cowbirds. Positive correlations of June-July precipitation, temperature, and time since grazing with dickcissel productivity did not mitigate dickcissels’ declining trend in this ecosystem. These findings highlight the importance of empirical research on the effects of increasing precipitation and brood parasitism vulnerability on migratory songbird conservation to inform adaptive management under climate change.