Marine Species Distribution Models Research Articles

Travelling away from home? Joining global change and recovery scenarios to anticipate the marine distribution of diadromous fish

Species Distribution Models (SDM) are useful tools providing results that can be extrapolated to anticipate species range shifts, under climate change scenarios. SDM studies integrating spatial constraints are significantly lacking in the marine environment, leading to optimistic predictions. This is particularly true for anadromous species in which marine distributions can be driven by their affinity to their natal rivers. Acipenser sturio is a critically endangered anadromous fish for which two stocked populations are currently maintained in the Gironde-Garonne-Dordogne (France) and Elbe (Germany) river systems. Benefiting from bycatch reports of A. sturio, we applied a SDM process that explicitly considers distance to home when evaluating habitat suitability. More precisely, we included the variable ‘distance to mouth of the natal river system’ into SDM inputs to test and characterize its influence on the marine distribution of A. sturio. We used this model to obtain the marine distribution under current climatic conditions with the two source populations and under population recovery scenarios (functional populations hypothesized to exist in ten currently unoccupied river systems). We projected the model under future conditions with two climatic scenarios (RCP 4.5 and 8.5) and three time slices over the 2023–2099 period. Constrained-ranges of both existing and hypothetical populations are projected to expand in the future. We observed an overall increase of habitat suitability, with new suitable sectors localized further from natal river mouths. By informing on the suitable marine surface that each hypothetical population holds and adds to the existing ones, our approach aims at informing about the feasibility of species recovery and marine habitats protection strategies. Our findings highlight the need for including dispersal information in marine SDM. The application of our dispersal-constrained approach may be considered for other less-well-known species for which dispersal point sources are identifiable, such as other diadromous species in different study areas.

From the modeling of diadromous species’ marine distributions to the characterization of their current and future marine habitats

IntroductionMany diadromous fish species are currently facing the threat of generalized population extirpations across their range, and conservation efforts implemented primarily within the continental domain may not be sufficient to ensure their viability. In consequence, better understanding the use of the marine environment by these species turned out to be critical.Material and methodWe developed marine species distribution models for two species, Allis shad (Alosa alosa) and the European flounder (Platichthys flesus), and proposed a way to interpret the habitat suitability from a more functional perspective. Our approach defined marine habitats as highly suitable environments that remained with a high potential through the species life stage duration at sea. First, a species-specific probabilistic threshold was applied to select for highly suitable environments each year of the simulations. Then, annual maps of high suitability were combined into recurrence maps showing areas were the environmental conditions remained the most suitable across the life at sea of the given species, these areas being called ‘marine habitats’. We applied this approach to study the current and future marine habitats of Allis shad and European flounder under climate change scenarios.ResultsThe main current marine habitats of these species were coastal, primarily in the Bay of Biscay for Allis shad and in the English Channel-North Sea for European flounder. These habitats are expected to experience minimal changes by mid-century, and the species may even benefit from new habitats at higher latitudes. However, the European flounder is likely to face greater challenges in the central part of its range by the end of the century, as potential spawning grounds may be threatened.DiscussionThis study provided a way to rethink ‘traditional’ suitability maps by integrating basic knowledge on the diadromous species life at sea. Our findings were part of a larger effort to link continental and marine habitats in improving management of diadromous species.

Uncertainty in Marine Species Distribution Modelling: Trying to Locate Invasion Hotspots for Pterois miles in the Eastern Mediterranean Sea

Biological invasions are considered among the largest threats to native biodiversity. The Mediterranean Sea, connecting the Indo-Pacific and Atlantic oceans, is characterized as a global marine invasion hotspot, due to a multitude of human pathways and vectors such as shipping, aquaculture, tourism, and the opening of the Suez Canal, which have led to the introduction of nearly 700 alien species into the Mediterranean Sea. Among the species introduced, the lionfish Pterois miles could be considered the fastest spreading invasive fish species of the last decade (2012–2022) and has been recorded in all countries of the eastern Mediterranean Sea, reaching as far north as Croatia. Here, we present a Bayesian additive regression tree modelling framework for an updated species distribution modelling invasion map under current and future climate conditions. All climate uncertainty sources have been used, as these are available from the Bio-Oracle, the unique marine predictors database. Important outputs of the current approach are the model’s inadequacy to accurately predict the most recent expansion of species in the Adriatic Sea, and the uncertainty estimation, that are high in areas with confirmed occurrence of individuals, in simulations that can help the decision makers and policy officers understand model limitations and take more informed actions.

Improving the Predictive Power of Marine Species Distribution Models by Incorporation of Modelled Prey Data

Improving the Predictive Power of Marine Species Distribution Models by Incorporation of Modelled Prey Data

Improving the Predictive Power of Marine Species Distribution Models by Incorporation of Modelled Prey Data

Improving the Predictive Power of Marine Species Distribution Models by Incorporation of Modelled Prey Data

Terrestrial or marine species distribution model: Why not both? A case study with seabirds.

Species reliant on both the terrestrial and marine realms present a challenge for conventional species distribution models (SDMs). For such species, standard single‐realm SDMs may omit key information that could result in decreased model accuracy and performance. Existing approaches to habitat suitability modeling typically do not effectively combine information from multiple realms; this methodological gap can ultimately hamper management efforts for groups such as seabirds, seals, and turtles. This study, for the first time, jointly incorporates both terrestrial information and marine information into a single species distribution model framework. We do this by sampling nearby marine conditions for a given terrestrial point and vice versa using parameters set by each species’ mean maximum foraging distance and then use standard SDM methods to generate habitat suitability predictions; therefore, our method does not rely on post hoc combination of several different models. Using three seabird species with very different ecologies, we investigate whether this new multi‐realm approach can improve our ability to identify suitable habitats for these species. Results show that incorporating terrestrial information into marine SDMs, or vice versa, generally improves model performance, sometimes drastically. However, there is considerable variability between species in the level of improvement as well as in the particular method that produces the most improvement. Our approach provides a repeatable and transparent method to combine information from multiple ecological realms in a single SDM framework. Important advantages over existing solutions include the opportunity to, firstly, easily combine terrestrial and marine information for species that forage large distances inland or out to sea and, secondly, consider interactions between terrestrial and marine variables.

Can seedlings' physiological information improve vegetation distribution predictions at local scales?

Physiological information has been successfully included in marine Species Distribution Models (SDM) before, but few have considered a previous development stage that could have affected the present-day distribution of the species at local scales. The aim of this study is to analyze the inclusion of physiological information of seedling survival on a correlative SDM based on adult present-day presences. The species were the invasive shrub Baccharis halimifolia and the native saltmarsh Juncus maritimus. For each species, five SDM were established using different approaches: using only experimentally derived physiological data, a correlative model with environmental predictors, additive combinations of presence/absence maps derived from the previous models, and a correlative model with the physiological data as a predictor variable. For B. halimifolia, the inclusion of the physiological data as a predictor variable yielded better results than with the other approaches; with J maritimus, this inclusion achieved an accuracy as high as the model with only environmental variables as predictors. The additive combinations generated less accurate models but offered possible advantages in future specialized studies. The results for B. halimifolia could extrapolate to other invasive species that rely on spreading high amounts of individuals and are more vulnerable in their early stages than in their growing and adult phases. Thus, this approach can improve the capacity for mapping invasive species’ distributions at local scales, and the conservation efforts to control biological invasions in estuaries and coastal ecosystems.

Combining fisheries surveys to inform marine species distribution modelling

Abstract Ecosystem-scale examination of fish communities typically involves creating spatio-temporally explicit relative abundance distribution maps using data from multiple fishery-independent surveys. However, sampling performance varies by vessel and sampling gear, which may influence estimated species distribution patterns. Using GAMMs, the effect of different gear–vessel combinations on relative abundance estimates at length was investigated using European fisheries-independent groundfish survey data. We constructed a modelling framework for evaluating relative efficiency of multiple gear–vessel combinations. 19 northeast Atlantic surveys for 254 species-length combinations were examined. Space-time variables explained most of the variation in catches for 181/254 species-length cases, indicating that for many species, models successfully characterized distribution patterns when combining data from disparate surveys. Variables controlling for gear efficiency explained substantial variation in catches for 127/254 species-length data sets. Models that fail to control for gear efficiencies across surveys can mask changes in the spatial distribution of species. Estimated relative differences in catch efficiencies grouped strongly by gear type, but did not exhibit a clear pattern across species’ functional forms, suggesting difficulty in predicting the potential impact of gear efficiency differences when combining survey data to assess species’ distributions and highlighting the importance of modelling approaches that can control for gear differences.

Assessing effects of genetic, environmental, and biotic gradients in species distribution modelling

Abstract To develop more reliable marine species distribution models (SDMs), we examine how genetic, climatic, and biotic interaction gradients give rise to prediction error in marine SDM. Genetic lineages with distinct ecological requirements spanning genetic gradients have yet to be treated separately in marine SDM, which are often constrained to modeling the potential distribution of one biological unit (e.g. lineage or species) at a time. By comparing SDM performance for the whole species or where observation and predictions were partitioned among geographically discontinuous genetic lineages, we first identified the appropriate biological unit for modeling sea scallop. Prediction errors, in particular contiguous omissions at the northern range margins were effectively halved in genetic lineage SDM (Total error=15%) verses whole species SDM. Remaining SDM prediction error was strongly associated with: i) Sharp climatic gradients (abrupt and persistent spatial shifts in limiting temperatures) found within continental shelf breaks and bottom channels. ii) A biotic gradient in the predation of sea scallop juveniles by the sand star within the Hudson Shelf USA. Our findings highlight how the accuracy of marine SDM is dependent on capturing the appropriate biological unit for modeling (e.g. lineages rather than species) and adequately resolving limiting abiotic and biotic interaction gradients.

Marine species distribution modelling and the effects of genetic isolation under climate change

AbstractAimCoral reefs are experiencing both an increasing frequency and intensity of anomalously warm ocean temperatures because of climate change. Studies show that the majority of coral populations will likely decline as temperatures continue to increase, although some previous species‐distribution models predict that ubiquitous species, such as the primary reef‐building coral species Porites lobata, will increase their distribution under projected climate change. These predictive models, however, assume that all individuals of a population are able to tolerate the entire range of environmental conditions within the species’ geographic range. The effects of genetic isolation and local adaptation are not considered in species‐distribution models that assume genetically contiguous populations. We aim to determine the effects of genetic isolation and local adaptation in species‐distribution modelling of the ubiquitous species P. lobata under three climate change scenarios by comparing contiguous and isolated subpopulations.LocationIndian and Pacific Oceans.MethodsWe ran a novel species‐distribution model for P. lobata, segregated as five geographically isolated regions across the Indian and Pacific Oceans, and examined the species response to three climate‐change scenarios (i.e., A2, A1B and B1, most recently considered as Representative Concentration Pathways 8.5, 6.0, and 4.5 Wm−2) by the year 2100.ResultsIn contrast with previous homogeneous species‐distribution models that predict a global expansion of P. lobata, (˜5 ± 1%), we predict major losses of suitable habitat for P. lobata in four of the five regions examined, particularly in the central Pacific Ocean (>99% ± <0.1% for all climate scenarios). Indeed, when geographic and genetic isolation were considered, our predictions suggested that P. lobata would lose between 50–52 ± 4% of its habitat, depending on the climate‐change scenario, mainly in the Pacific Ocean.Main conclusionsGenetic isolation will likely play a major role in the persistence of coral species under climate change, and small isolated populations may be more vulnerable to climate change than populations in large, highly connected regions.

Explicitly integrating a third dimension in marine species distribution modelling

Explicitly integrating a third dimension in marine species distribution modelling

Dynamic seascapes predict the marine occurrence of an endangered species: Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus

Summary Categorical landscapes are powerful environmental partitions that index complex biogeochemical processes that drive terrestrial species distributions. However, translating landscapes into seascapes requires that the dynamic nature of the fluid environment be reflected in spatial and temporal boundaries such that seascapes can be used in marine species distribution models and conservation decisions. A seascape product derived from satellite ocean colour and sea surface temperature partitioned mid‐Atlantic coastal waters on scales commensurate with the Atlantic Sturgeon migration. The seascapes were then matched with acoustic telemetry records of Atlantic Sturgeon to determine seascape selectivity. To test for selectivity, we used real‐time satellite seascape maps to normalize the sampling of an autonomous underwater vehicle that resampled similar geographic regions with time varying seascape classifications. Our findings suggest that Atlantic Sturgeon prefer one seascape class over those available in the coastal ocean, indicating selection for covarying environmental properties rather than geographical location. The recent listing of Atlantic Sturgeon as Endangered throughout much of their United States range has highlighted the need for improved understanding of marine habitat requirements to reduce interactions with anthropogenic stressors. Narrow dynamic migration corridors may enable seascapes to be used as a daily decision tool by industry and managers to reduce interactions with this imperilled species during coastal migrations.

Comparing the ecological relevance of four wave exposure models

Wave exposure is one of the main structuring forces in the marine environment. Methods that enable large scale quantification of environmental variables have become increasingly important for predicting marine communities in the context of spatial planning and coastal zone management. Existing methods range from cartographic solutions to numerical hydrodynamic simulations, and differ in the scale and spatial coverage of their outputs. Using a biological exposure index we compared the performance of four wave exposure models ranging from simple to more advanced techniques. All models were found to be related to the biological exposure index and their performance, measured as bootstrapped R2 distributions, overlapped. Qualitatively, there were differences in the spatial patterns indicating higher complexity with more advanced techniques. In order to create complex spatial patterns wave exposure models should include diffraction, especially in coastal areas rich in islands. The inclusion of wind strength and frequency, in addition to wind direction and bathymetry, further tended to increase the amount of explained variation. The large potential of high-resolution numerical models to explain the observed patterns of species distribution in complex coastal areas provide exciting opportunities for future research. Easy access to relevant wave exposure models will aid large scale habitat classification systems and the continuously growing field of marine species distribution modelling, ultimately serving marine spatial management and planning.

Species distribution modelling to support marine conservation planning: The next steps

Species distribution models (SDMs) offer great potential for inclusion into the toolbox of today's marine environmental manager, especially with regard to marine conservation and planning. The application of SDMs in the marine environment over recent years has been varied but there are still relatively few examples in comparison with terrestrial application, and this is especially true in deep-sea marine ecosystems. This short article builds upon two recent review articles concerning the application of species distribution modelling studies in the marine realm, offering additional practical considerations for discussion. Recommendations for progressing the improved application of SDMs to support marine conservation planning are given, including combining model outputs with other data layers, metadata standards and model error. SDMs have both an urgent and long term contribution to make to marine conservation planning globally, and it is hoped that this article, in combination with developing research on marine SDMs, will contribute to some much needed discussion and inform best practice and new research to enable these models to be of greater use to marine managers.

Bio‐ORACLE: a global environmental dataset for marine species distribution modelling

ABSTRACTAim The oceans harbour a great diversity of organisms whose distribution and ecological preferences are often poorly understood. Species distribution modelling (SDM) could improve our knowledge and inform marine ecosystem management and conservation. Although marine environmental data are available from various sources, there are currently no user‐friendly, high‐resolution global datasets designed for SDM applications. This study aims to fill this gap by assembling a comprehensive, uniform, high‐resolution and readily usable package of global environmental rasters.Location Global, marine.Methods We compiled global coverage data, e.g. satellite‐based and in situ measured data, representing various aspects of the marine environment relevant for species distributions. Rasters were assembled at a resolution of 5 arcmin (c. 9.2 km) and a uniform landmask was applied. The utility of the dataset was evaluated by maximum entropy SDM of the invasive seaweed Codium fragile ssp. fragile.Results We present Bio‐ORACLE (ocean rasters for analysis of climate and environment), a global dataset consisting of 23 geophysical, biotic and climate rasters. This user‐friendly data package for marine species distribution modelling is available for download at http://www.bio‐oracle.ugent.be. The high predictive power of the distribution model of C. fragile ssp. fragile clearly illustrates the potential of the data package for SDM of shallow‐water marine organisms.Main conclusions The availability of this global environmental data package has the potential to stimulate marine SDM. The high predictive success of the presence‐only model of a notorious invasive seaweed shows that the information contained in Bio‐ORACLE can be informative about marine distributions and permits building highly accurate species distribution models.

Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities

Aim Species distribution models (SDMs) have been used to address a wide range of theoretical and applied questions in the terrestrial realm, but marine-based applications remain relatively scarce. In this review, we consider how conceptual and practical issues associated with terrestrial SDMs apply to a range of marine organisms and highlight the challenges relevant to improving marine SDMs. Location We include studies from both marine and terrestrial systems that encompass many geographic locations around the globe. Methods We first performed a literature search and analysis of marine and terrestrial SDMs in ISI Web of Science to assess trends and applications. Using knowledge from terrestrial applications, we critically evaluate the application of SDMs in marine systems in the context of ecological factors (dispersal, species interactions, aggregation and ontogenetic shifts) and practical considerations (data quality, alternative modelling approaches and model validation) that facilitate or create difficulties for model application. Results The relative importance of ecological factors to be considered when applying SDMs varies among terrestrial and marine organisms. Correctly incorporating dispersal is frequently considered an important issue for terrestrial models, but because there is greater potential for dispersal in the ocean, it is often less of a concern in marine SDMs. By contrast, ontogenetic shifts and feeding have received little attention in terrestrial SDM applications, but these factors are important to many marine SDMs. Opportunities also exist for applying more advanced SDM approaches in the marine realm, including mechanistic ecophysiological models, where water balance and heat transfer equations are simpler for some marine organisms relative to their terrestrial counterparts. Main conclusions SDMs have generally been under-utilized in the marine realm relative to terrestrial applications. Correlative SDM methods should be tested on a range of marine organisms, and we suggest further development of methods that address ontogenetic shifts and feeding interactions. We anticipate developments in, and cross-fertilization between, coupled correlative and process-based SDMs, mechanistic eco-physiological SDMs, and spatial population dynamic models for climate change and species invasion applications in particular. Comparisons of the outputs of different model types will provide insight that is useful for improved spatial management of marine species.

Applications and future challenges in marine species distribution modeling

Abstract Anthropogenic climate change affects both phenology and distribution patterns of the world's biota including marine species. During the last decade, species distribution models have been more frequently used to assess the potential distributions of species and possible effects of climate change. However, unlike for terrestrial species, there have been few investigations assessing climate change effects on distribution patterns of marine organisms. An overview of marine species distribution modelling is given. Possibilities of how to characterize and project the environmental niches of species onto climatic change scenarios are highlighted and novel techniques for addressing specific needs in a 3‐D context are proposed. A detailed introduction into different modelling tools and databases for environmental parameters given provides a starting point for the application of these models. Application of a species distribution model and its projections onto a glacial and future scenario on a global scale are presented for the great white shark (Carcharodon carcharias) for illustrative purposes. An approach for addressing marine migratory species with seasonal distribution patterns is presented. Copyright © 2010 John Wiley & Sons, Ltd.

Adaptive Phenotypic Plasticity: Target or By-Product of Selection in a Variable Environment?

Adaptive Phenotypic Plasticity: Target or By-Product of Selection in a Variable Environment?