Shifted distribution baselines: neglecting long-term biodiversity records risks overlooking potentially suitable habitat for conservation management

Abstract

Setting appropriate conservation measures to halt the loss of biodiversity requires a good understanding of species’ habitat requirements and potential distribution. Recent (past few decades) ecological data are typically used to estimate and understand species’ ecological niche. However, historical local extinctions may have truncated species-environment relationships, resulting in a biased perception of species’ habitat preferences. This may result in incorrect assessments of the area potentially available for their conservation. Incorporating long-term (centuries-old) occurrence records with recent records may provide better information on species-environment relationships and improve the modeling and understanding of habitat suitability. We test whether neglecting long-term occurrence records leads to an underestimation of species’ historical niche and potential distribution and identify which species are more vulnerable to this effect. We compare outputs of species distribution models and niche hypervolumes built using recent records only with those built using both recent and long-term (post-1500) records, for a set of 34 large mammal species in South Africa. We find that, while using recent records only is adequate for some species, adding historical records in the analyses impacts estimates of the niche and habitat suitability for fourteen species (41%) in our dataset, and that this effect is significantly higher for carnivores. These results show that neglecting long-term biodiversity records in spatial analyses risks misunderstanding, and generally underestimating, species’ niche, which in turn may lead to ill-informed management decisions, with significant implications for the effectiveness of conservation efforts.

Exploring snake occurrence records: Spatial biases and marginal gains from accessible social media

“…The lack of records in the critical snake hotspots mirrors investigations into other taxonomic groups (Yesson et al, 2007; Amano, Lamming & Sutherland, 2016; Roll et al, 2017). The identified gaps in GBIF records support efforts to make use of more diverse data sources: by filling gaps in GBIF coverage and boosting sample sizes, supplementary data sources could reduce the chances of underestimating species distributions and ecological niches (Beck et al, 2013; Monsarrat et al, 2019). However, while our efforts to retrieve occurrence records from social media were successful, the quantity of records was insufficient to make significant impacts on distribution models.…”

“…Discovering ways to fill data gaps (e.g., Callaghan et al, 2019) without having to fund additional surveying efforts would be valuable at a time when natural history investigations are under appreciated but macro-ecological questions are popular (Ríos-Saldaña, Delibes-Mateos & Ferreira, 2018; McCallen et al, 2019). Overcoming data deficiencies should be prioritised; delays could result in occurrence data derived from distributions defined by human activity (realised niche), rather than the climatic or absolute niche of a species (Monsarrat et al, 2019). Improvements in occurrence data may help identify current distributions, but unstructured occurrence data cannot help quantify population trends sorely needed for many reptile species (Bland & Böhm, 2016; Bayraktarov et al, 2019).…”

“…The utility of a species distribution model is dependent on the underlying species occurrence data used in constructing the model. Gaps and incomplete data can lead to misidentifying the target species’ niche (Monsarrat et al, 2019). Underestimating species distributions can further mask the impacts of human activity on distributions, contributing to shifting baseline syndrome where progressively eroded species distributions or populations are accepted as normal or healthy (Cromsigt, Kerley & Kowalczyk, 2012).…”

The Protected Area Paradox and refugee species: The giant panda and baselines shifted towards conserving species in marginal habitats

“…The first, and perhaps biggest, challenge is to overcome the shifted baselines of conservation managers and scientists. Monsarrat, Novellie, Rushworth, and Kerley (2019) recently showed that neglecting historical range data underestimates conservation opportunities, ecological niches and habitat usage for species, and that this is relatively common (34% of their admittedly small sample of 34 large mammal species) and biased towards carnivores. These shifted baselines hinder the critical assessment of current conservation efforts, and the exploration of alternative approaches, this through the identification of optimal habitats and testing hypotheses around refugee species status, following the process outlined by Kerley et al (2012).…”

Relationships between survival and habitat suitability of semi‐aquatic mammals

“…Habitat suitability models (HSMs) and species distribution models (SDMs) have become popular research tools for spatial ecology, population ecology, and biodiversity conservation (Evcin, Kucuk, & Akturk, 2019; Mohammadi, Ebrahimi, Shahriari Moghadam, & Bosso, 2019; Monsarrat, Novellie, Rushworth, & Kerley, 2019). Although these two models may differ in spatial scopes, with the latter covering a larger spatial extent that may include the entire geographic range of species, HSMs and SDMs are often based on ecological niche theory (Elith & Leathwick, 2009; Hirzel & Le Lay, 2008).…”