Challenges and opportunities of species distribution modelling of terrestrial arthropod predators

Abstract

AimSpecies distribution models (SDMs) have emerged as essential tools in the equipment of many ecologists, useful to explore species distributions in space and time and answering an assortment of questions related to biogeography, climate change biology and conservation biology. Historically, most SDM research concentrated on well‐known organisms, especially vertebrates. In recent years, these tools are becoming increasingly important for predicting the distribution of understudied invertebrate taxa. Here, we reviewed the literature published on main terrestrial arthropod predators (ants, ground beetles and spiders) to explore some of the challenges and opportunities of species distribution modelling in mega‐diverse arthropod groups.LocationGlobal.MethodsSystematic mapping of the literature and bibliometric analysis.ResultsMost SDM studies of animals to date have focused either on broad samples of vertebrates or on arthropod species that are charismatic (e.g. butterflies) or economically important (e.g. vectors of disease, crop pests and pollinators). We show that the use of SDMs to map the geography of terrestrial arthropod predators is a nascent phenomenon, with a near‐exponential growth in the number of studies over the past ten years and still limited collaborative networks among researchers. There is a bias in studies towards charismatic species and geographical areas that hold lower levels of diversity but greater availability of data, such as Europe and North America.ConclusionsArthropods pose particular modelling challenges that add to the ones already present for vertebrates, but they should also offer opportunities for future SDM research as data and new methods are made available. To overcome data limitations, we illustrate the potential of modern data sources and new modelling approaches. We discuss areas of research where SDMs may be combined with dispersal models and increasingly available phylogenetic and functional data to understand evolutionary changes in ranges and range‐limiting traits over past and contemporary time‐scales.

Climate change will redefine taxonomic, functional, and phylogenetic diversity patterns of Odonata in space and time

“…Therefore, further research about ecology, physiology, and behaviour can benefit our knowledge about these freshwater insects and favour the design of efficient and effective conservation strategies. Further investigations based on mechanistic models (Chichorro et al, 2022) or high-resolution physiological and dispersal traits (Buckley & Kingsolver, 2012;Mammola et al, 2021b) could be useful to better identify key traits associated with climate-induced species range shifts and potentially even extinction risk. Our results might be substantially improved by including into the models traits directly linked with the dispersal ability (e.g., GPS-tracking, flight muscle mass, wing loading and shape) as well as traits and distribution of the larval stages, since most of the life of these insects is spent underwater [e.g., in Anax imperator (Leach, 1815) the life span is two years in larvae and eight to nine weeks in adults (Corbet, 1957)].…”

“…To model species distribution, we used Species Distribution Models (SDMs), mainstream analytical tools in ecological and biogeographical research (Peterson et al, 2011;Franklin, 2010;Guisan and Thuiller, 2005), including to predict arthropod distributions (Mammola et al, 2021b). In short, distribution modelling refers to the practice of using an algorithm to infer a relationship between the occurrences for a given species (e.g., georeferenced points) and environmental predictors (e.g., climatic variables, topographic parameters, habitat type), forecasting its potential distribution in space and/or time.…”

A tale of two crickets: global climate and local competition shape the distribution of European Oecanthus species (Orthoptera, Gryllidae)

“…The identification of biotic interactions is particularly difficult at large scales and when considering proxies that may be effectively estimated in a spatially explicit way, and thus mapped in order to be integrated within SDMs (Pellissier et al 2010, Blois et al 2013, Wisz et al 2013. Moreover, while SDMs have been extensively applied for a variety of organisms in the last decades, published studies are heavily taxonbiased towards vertebrates, thus leaving huge gaps in our comprehension of animals' responses to climate change (see Mammola et al 2021). Arthropods are excellent models to test hypotheses on climate change and on how species' distributions are shaped by different factors across spatial scales (Vanhanen et al 2007, Høye 2020, as most species are strongly dependant on specific climatic conditions, so that they may readily respond to environmental alterations (Feldmeier et al 2018, Mammola et al 2021).…”

“…Moreover, while SDMs have been extensively applied for a variety of organisms in the last decades, published studies are heavily taxonbiased towards vertebrates, thus leaving huge gaps in our comprehension of animals' responses to climate change (see Mammola et al 2021). Arthropods are excellent models to test hypotheses on climate change and on how species' distributions are shaped by different factors across spatial scales (Vanhanen et al 2007, Høye 2020, as most species are strongly dependant on specific climatic conditions, so that they may readily respond to environmental alterations (Feldmeier et al 2018, Mammola et al 2021). Yet, our current knowledge gap about the detailed array of biotic and abiotic drivers of insect distributions, as well as the scarce availability of presence records for most species, hamper the effective use of SDMs for the study of insects (Lobo 2016).…”

“…The high spatial resolution at which arthropods, such as insects, mostly use and perceive their environment (e.g., at the microhabitat scale) also makes biotic interactions likely relevant when assessing a species' environmental preferences at local scales, as interspecific interactions such as competition, predation or facilitation may lose importance when upscaled to large geographical extents (Newbold 2010, Warren et al 2010). Yet, very few studies have applied SDMs to the study of arthropod responses to climate change, and even fewer have integrated biotic interactions within their framework (Hortal et al 2010, Warren et al 2010, Taucare-Ríos et al 2016, Mammola et al 2021. Even within Arthropods, strong taxonomical biases in research efforts occur, with most studies being conducted on charismatic or aesthetically appreciated taxa such as Lepidoptera and large Arachnids, while other groups are poorly covered, (e.g., ground beetles -Carabidae -and Orthoptera; Høye 2020, Mammola et al 2021, Koot et al 2022.…”