Sampling and modelling rare species: Conceptual guidelines for the neglected majority

Abstract

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade‐offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species‐targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much‐needed guide through the ever‐increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

From design to analysis: A roadmap for predicting distributions of rare species

“…Distinguishing among these categories of rarity is important to analyze and understand the drivers of the distribution and abundance of rare species, their importance for communities and ecosystems, and for the design of efficient conservation policies (Gaston, 1994). Rabinowitz' framework is used by Jeliazkov et al (2022) to build a roadmap of sampling designs, field methods and modelling approaches tailored to the distribution of rare species.…”

“…One category of rare species corresponds to being geographically widespread but occurring at low abundance within its range. For such species Jeliazkov et al (2022) contrast a design‐based sampling design – the simplest one being random sampling in the geographical space – to convenience sampling, such as done when sampling is done close to roads or in habitats believed to be important for these rare species. The former approach will lead to unbiased estimation of species distributions and their drivers, but with many rare species would require very large resources to be precise enough to be useful for, e.g., modelling or making conservation plans.…”

“…The former approach will lead to unbiased estimation of species distributions and their drivers, but with many rare species would require very large resources to be precise enough to be useful for, e.g., modelling or making conservation plans. Jeliazkov et al (2022) mention as an example the UK plants countryside survey – a survey based on stratified random sampling – which missed a large proportion of rare species. Convenience sampling may lead to more precise models of distributions but such models are likely to be biased and miss important aspects of the distribution, for example, if rare species are also found in microhabitats not sampled.…”

“…A better understanding of the distribution of rare species may therefore help assessing the effectiveness of management plans, ideally considering diverse taxonomic groups as hotspots of rare species for one group may not coincide with hotspots for another group. Jeliazkov et al (2022) list various field methods that can provide complementary approaches to sampling diverse taxonomic groups, from eDNA to different kinds of traps. Hierarchical models with different submodels adapted to each group and field methods may then provide an integrated view of rarity less dependent on taxonomy, and therefore a more complete approach to conservation.…”

“…Small sample sizes, heterogeneity of rarity patterns (Rabinowitz, 1981) and spatio‐temporal changes are challenges that can easily lead to untrustworthy conclusions. Jeliazkov et al (2022) have given us a very timely roadmap to the different decisions that one needs to consider if we are to better understand the distribution of rare species, and ultimately how we can develop reliable predictive models that can help us sustainably managing their future.…”