Methods for improving species distribution models in data-poor areas: example of sub-Antarctic benthic species on the Kerguelen Plateau

Guillaumot, Charlène; Martin, Alexis; Eléaume, Marc; Saucède, Thomas

doi:10.3354/meps12538

Cited by 11 publications

(28 citation statements)

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“…The paucity of available data is a major limitation to analyses that are restricted to presence‐only data models, usually considered less reliable and less efficient than presence–absence or abundance data models (Brotons et al., ). In addition, presence‐only datasets can be heterogeneous in space and time (compilation of 150 years of sampling in the present case study), which can influence modeling performances (Guillaumot et al., in press; Newbold, ; Tessarolo et al., ). SDM performed with spatially biased presence‐only data must consider these limitations and apply appropriate algorithms, protocols, and corrections (Barbet‐Massin et al., ; Guillaumot et al., in press; Phillips et al., ; Proosdij et al., ).…”

Section: Discussionmentioning

confidence: 99%

“…Sampling bias, data availability, quality, and heterogeneous distribution are common issues (Guillera‐Arroita et al., ; Robinson et al., ; Tessarolo, Rangel, Araújo, & Hortal, ). However, protocols have been developed to address these methodological issues and provide robust and relevant distribution predictions (Barbet‐Massin, Jiguet, Albert, & Thuiller, ; Guillaumot, Martin, Eléaume, & Saucède, in press; Phillips et al., ).…”

Section: Introductionmentioning

confidence: 99%

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Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes

Guillaumot

Fabri‐Ruiz

Martin

et al. 2018

Ecology and Evolution

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Marine life of the Southern Ocean has been facing environmental changes and the direct impact of human activities during the past decades. Benthic communities have particularly been affected by such changes although we only slowly understand the effect of environmental changes on species physiology, biogeography, and distribution. Species distribution models (SDM) can help explore species geographic responses to main environmental changes. In this work, we modeled the distribution of four echinoid species with contrasting ecological niches. Models developed for [2005–2012] were projected to different time periods, and the magnitude of distribution range shifts was assessed for recent‐past conditions [1955–1974] and for the future, under scenario RCP 8.5 for [2050–2099]. Our results suggest that species distribution shifts are expected to be more important in a near future compared to the past. The geographic response of species may vary between poleward shift, latitudinal reduction, and local extinction. Species with broad ecological niches and not limited by biogeographic barriers would be the least affected by environmental changes, in contrast to endemic species, restricted to coastal areas, which are predicted to be more sensitive.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes

Guillaumot

Fabri‐Ruiz

Martin

et al. 2018

Ecology and Evolution

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“…org; Assis et al 2018) and the NOAA's portal (https:// psl.noaa.gov/ipcc/ocn). The relevance of using future predictions based on global assessment scenarios for marine studies has been widely questioned (Flato et al 2014, Frölicher et al 2016, de la Hoz et al 2018, including their use in SDMs, given that climate models mainly rely on untestable assumptions (Beaumont et al 2008, Gotelli & Stanton-Geddes 2015, Freer et al 2018, future layers are not always available for oceanographic studies (Fabri-Ruiz 2018, Guillaumot et al 2018aGuillaumot et al , 2018b, discrepancies between present observations and future predictions can be problematic (Jiménez-Valverde et al 2021) and models are based on a representation of the climate system that has a complex cascading effect on ecological processes (Cavanagh et al 2017). Cavanagh et al (2017) examined how well IPCC-class models reproduced sea-ice conditions.…”

Section: Environmental Datasets: Cartographic Projectionsmentioning

confidence: 99%

“…All of these side effects were reviewed in detail by Newbold (2010). The impacts on species niche definition and SDM predictions have been reported in many works (Ensing et al 2012, Lahoz-Monfort et al 2014, Monk 2014, Aguiar et al 2015, Tessarolo et al 2017, Guillaumot et al 2018a) that all advise us to thoroughly check datasets for quality management prior to running models.…”

Section: Occurrence Datasets: Historical Compilationmentioning

confidence: 99%

Species distribution modelling of the Southern Ocean benthos: a review on methods, cautions and solutions

2021

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Species distribution modelling studies the relationship between species occurrence records and their environmental setting, providing a valuable approach to predicting species distribution in the Southern Ocean (SO), a challenging region to investigate due to its remoteness and extreme weather and sea conditions. The specificity of SO studies, including restricted field access and sampling, the paucity of observations and difficulties in conducting biological experiments, limit the performance of species distribution models. In this review, we discuss some issues that may influence model performance when preparing datasets and calibrating models, namely the selection and quality of environmental descriptors, the spatial and temporal biases that may affect the quality of occurrence data, the choice of modelling algorithms and the spatial scale and limits of the projection area. We stress the importance of evaluating and communicating model uncertainties, and the most common evaluation metrics are reviewed and discussed accordingly. Based on a selection of case studies on SO benthic invertebrates, we highlight important cautions to take and pitfalls to avoid when modelling the distribution of SO species, and we provide some guidelines along with potential methods and original solutions that can be used for improving model performance.

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“…The echinoid Abatus cordatus (Verrill 1876) is endemic to the Kerguelen oceanic plateau and common in coastal benthic habitats of the Kerguelen Islands. It is reported in the northern Kerguelen plateau, and around Heard and Kerguelen islands but most records are from shallow, coastal areas of the Kerguelen Islands where dense populations are commonly observed (Agassiz, 1881;De Ridder et al, 1992;David et al, 2005;Guillaumot et al, 2016Guillaumot et al, , 2018bGuillaumot et al, , 2018aHibberd and Moore, 2009;Mespoulhé, 1992;Poulin, 1996 ). This makes the species particularly at risk considering the synergetic effects of the multiple factors (temperature variations, significant shifts in coastal currents, sedimentation rates and phytoplanktonic blooms) affecting coastal marine communities at high latitudes (Gutt et al, 2018;Stenni et al, 2017;Waller et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Individual-based model of population dynamics in a sea urchin of the Kerguelen Plateau (Southern Ocean), Abatus cordatus, under changing environmental conditions

Arnould-Pétré

Guillaumot

Danis

et al. 2021

Ecological Modelling

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The Kerguelen Islands are part of the French Southern Territories, located at the limit of the Indian and Southern oceans. They are highly impacted by climate change, and coastal marine areas are particularly at risk. Assessing the responses of species and populations to environmental change is challenging in such areas for which ecological modelling can constitute a helpful approach. In the present work, a DEB-IBM model (Dynamic Energy Budget -Individual-Based Model) was generated to simulate and predict population dynamics in an endemic and common benthic species of shallow marine habitats of the Kerguelen Islands, the sea urchin Abatus cordatus. The model relies on a dynamic energy budget model (DEB) developed at the individual level. Upscaled to an individual-based population model (IBM), it then enables to model population dynamics through time as a result of individual physiological responses to environmental variations. The model was successfully built for a reference site to simulate the response of populations to variations in food resources and temperature. Then, it was implemented to model population dynamics at other sites and for the different IPCC climate change scenarios RCP 2.6 and 8.5. Under present-day conditions, models predict a more determinant effect of food resources on population densities, and on juvenile densities in particular, relative to temperature. In contrast, simulations predict a sharp decline in population densities under conditions of IPCC scenarios RCP 2.6 and RCP 8.5 with a determinant effect of water warming leading to the extinction of most vulnerable populations after a 30-year simulation time due to high mortality levels associated with peaks of high temperatures. Such a dynamic model is here applied for the first time to a Southern Ocean benthic and brooding species and offers interesting prospects for Antarctic and sub-Antarctic biodiversity research. It could constitute a useful tool to support conservation studies in these remote regions where access and bio-monitoring represent challenging issues.

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Methods for improving species distribution models in data-poor areas: example of sub-Antarctic benthic species on the Kerguelen Plateau

Cited by 11 publications

References 75 publications

Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes

Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes

Species distribution modelling of the Southern Ocean benthos: a review on methods, cautions and solutions

Individual-based model of population dynamics in a sea urchin of the Kerguelen Plateau (Southern Ocean), Abatus cordatus, under changing environmental conditions

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