Distribution Of Marine Species Research Articles

Nonlinearity and Spatial Autocorrelation in Species Distribution Modeling: An Example Based on Weakfish (Cynoscion regalis) in the Mid-Atlantic Bight

Nonlinearity and spatial autocorrelation are common features observed in marine fish datasets but are often ignored or not considered simultaneously in modeling. Both features are often present within ecological data obtained across extensive spatial and temporal domains. A case study and a simulation were conducted to evaluate the necessity of considering both characteristics in marine species distribution modeling. We examined seven years of weakfish (Cynoscion regalis) survey catch rates along the Atlantic coast, and five types of statistical models were formulated using a delta model approach because of the high percentage of zero catches in the dataset. The delta spatial generalized additive model (GAM) confirmed the presence of nonlinear relationships with explanatory variables, and results from 3-fold cross-validation indicated that the delta spatial GAM yielded the smallest training and testing errors. Spatial maps of residuals also showed that the delta spatial GAM decreased the spatial autocorrelation in the data. The simulation study found that the spatial GAM over competes other models based on the mean squared error in all scenarios. That indicates that the recommended model not just works well for the NEAMAP survey but also for other cases as in the simulated scenarios.

Artificial intelligence convolutional neural networks map giant kelp forests from satellite imagery

Climate change is producing shifts in the distribution and abundance of marine species. Such is the case of kelp forests, important marine ecosystem-structuring species whose distributional range limits have been shifting worldwide. Synthesizing long-term time series of kelp forest observations is therefore vital for understanding the drivers shaping ecosystem dynamics and for predicting responses to ongoing and future climate changes. Traditional methods of mapping kelp from satellite imagery are time-consuming and expensive, as they require high amount of human effort for image processing and algorithm optimization. Here we propose the use of mask region-based convolutional neural networks (Mask R-CNN) to automatically assimilate data from open-source satellite imagery (Landsat Thematic Mapper) and detect kelp forest canopy cover. The analyses focused on the giant kelp Macrocystis pyrifera along the shorelines of southern California and Baja California in the northeastern Pacific. Model hyper-parameterization was tuned through cross-validation procedures testing the effect of data augmentation, and different learning rates and anchor sizes. The optimal model detected kelp forests with high performance and low levels of overprediction (Jaccard’s index: 0.87 ± 0.07; Dice index: 0.93 ± 0.04; over prediction: 0.06) and allowed reconstructing a time series of 32 years in Baja California (Mexico), a region known for its high variability in kelp owing to El Niño events. The proposed framework based on Mask R-CNN now joins the list of cost-efficient tools for long-term marine ecological monitoring, facilitating well-informed biodiversity conservation, management and decision making.

Unifying approaches to Functional Marine Connectivity for improved marine resource management: the European SEA-UNICORN COST Action

Truly sustainable development in a human-altered, fragmented marine environment subject to unprecedented climate change, demands informed planning strategies in order to be successful. Beyond a simple understanding of the distribution of marine species, data describing how variations in spatio-temporal dynamics impact ecosystem functioning and the evolution of species are required. Marine Functional Connectivity (MFC) characterizes the flows of matter, genes and energy produced by organism movements and migrations across the seascape. As such, MFC determines the ecological and evolutionary interdependency of populations, and ultimately the fate of species and ecosystems. Gathering effective MFC knowledge can therefore improve predictions of the impacts of environmental change and help to refine management and conservation strategies for the seas and oceans. Gathering these data are challenging however, as access to, and survey of marine ecosystems still presents significant challenge. Over 50 European institutions currently investigate aspects of MFC using complementary methods across multiple research fields, to understand the ecology and evolution of marine species. The aim of SEA-UNICORN, a COST Action supported by COST (European Cooperation in Science and Technology), is to bring together this research effort, unite the multiple approaches to MFC, and to integrate these under a common conceptual and analytical framework. The consortium brings together a diverse group of scientists to collate existing MFC data, to identify knowledge gaps, to enhance complementarity among disciplines, and to devise common approaches to MFC. SEA-UNICORN will promote co-working between connectivity practitioners and ecosystem modelers to facilitate the incorporation of MFC data into the predictive models used to identify marine conservation priorities. Ultimately, SEA-UNICORN will forge strong forward-working links between scientists, policy-makers and stakeholders to facilitate the integration of MFC knowledge into decision support tools for marine management and environmental policies.

Global habitat suitability modeling reveals insufficient habitat protection for mangrove crabs

Mangrove crabs are important components of mangrove forests however their large scale habitat suitability and conservation received little attention. The Metopograpsus thukuhar/cannicci species complex is a mangrove dwelling species occurs in the Indo-Pacific mangrove forests. Since identifying the complex suitable habitat is critical for its conservation, we modeled global habitat suitability of the complex within marine biogeographic realms and estimated representation of the complex suitable habitats within marine protected areas. We found that the complex’ largest and smallest suitable ranges are located in Central Indo-Pacific and Temperate Southern Africa realms, respectively. Only 12.5% of the complex suitable habitat is protected. The highest proportion of the complex’ protected suitable habitat (22.9%) is located in Western Indo-Pacific realm while the lowest proportion of the complex’ protected suitable habitat (1.38%) is located in Central Indo-Pacific realm. Suitable unprotected habitats of the complex identified in this study have high priority for conservation and should be included in marine protected areas to ensure species conservation. Our results show that species distribution models are practical tools to study marine species distribution across large spatial scales and help marine conservation planning.

Climate, currents and species traits contribute to early stages of marine species redistribution

Anthropogenic climate change is causing a rapid redistribution of life on Earth, particularly in the ocean, with profound implications for humans. Yet warming-driven range shifts are known to be influenced by a variety of factors whose combined effects are still little understood. Here, we use scientist-verified out-of-range observations from a national citizen-science initiative to assess the combined effect of long-term warming, climate extremes (i.e., heatwaves and cold spells), ocean currents, and species traits on early stages of marine range extensions in two warming ‘hotspot’ regions of southern Australia. We find effects of warming to be contingent upon complex interactions with the strength of ocean currents and their mutual directional agreement, as well as species traits. Our study represents the most comprehensive account to date of factors driving early stages of marine species redistributions, providing important evidence for the assessment of the vulnerability of marine species distributions to climate change.

Filling ecological gaps in Chilean Central Patagonia: Patterns of biodiversity and distribution of sublittoral benthic invertebrates from the Katalalixar National Reserve waters (~48°S)

Knowledge about the composition, diversity, and geographic distribution of marine species is important for successful conservation planning in the future. The ecological and zoogeographic patterns of benthic communities in Central Patagonia have been scarcely studied, due to the remoteness of the area combined with harsh weather conditions. During the past years, five scientific expeditions were executed in order to study the biodiversity, ecological, and biogeographical patterns of benthic invertebrates in the Katalalixar National Reserve (KNR) waters, Central Patagonia (~48°S). Our analyses comprised images from 26 video transects using a remotely operated vehicle, completed with biological sampling at four stations by means of SCUBA diving, covering a bathymetric range from 10 to 220 m depth. Stations covered the entire longitudinal range of the KNR, from inner channels to the Pacific Ocean. A total of 187 benthic invertebrate taxa were identified as OTUs (operational taxonomic units), with mollusks being the most conspicuous taxonomic group (18.7%), followed by sponges, echinoderms (16.6% each), and arthropods (14.4%). A higher OTU richness (42 to 51 OTUs) was observed in the central and western parts of the KNR waters. Analyses of the β-diversity indicated a similar level of species turnover between shallow, intermediate, and deep strata, as well as an important turnover between different locations. Dissimilitudes in the assemblage structure of invertebrates were explained mainly by changes in substrate types and longitude. Most of the species (49%) found in the KNR waters showed a wide latitudinal distribution range along the Eastern South Pacific Ocean (ESP) and the Chilean Patagonia of fjords and channels (CPFC) (~18°S and ~56°S), whereas 9.4% of the species have a wide distribution range between the CPFC and south of the Antarctic polar front (SAPF) (~42°S and ~65°S). Since only 16.7% of the species identified in the KNR are distributed exclusively in CPFC waters, it may be considered a transition area for marine invertebrates. It is distributed between northern ESP and SAPF. Knowledge of species composition and distribution patterns along spatial and environmental gradients is essential for any sustainable management, monitoring, and future conservation plans to protect the fragile and diverse marine ecosystems of Chilean Patagonia.

A novel expert-driven methodology to develop thermal response curves and project habitat thermal suitability for cetaceans under a changing climate

Over the last decades, global warming has contributed to changes in marine species composition, abundance and distribution, in response to changes in oceanographic conditions such as temperature, acidification, and deoxygenation. Experimentally derived thermal limits, which are known to be related to observed latitudinal ranges, have been used to assess variations in species distribution patterns. However, such experiments cannot be undertaken on free-swimming large marine predators with wide-range distribution, like cetaceans. An alternative approach is to elicit expert's knowledge to derive species' thermal suitability and assess their thermal responses, something that has never been tested in these taxa. We developed and applied a methodology based on expert-derived thermal suitability curves and projected future responses for several species under different climate scenarios. We tested this approach with ten cetacean species currently present in the biogeographic area of Macaronesia (North Atlantic) under Representative Concentration Pathways 2.6, 4.5 and 8.5, until 2050. Overall, increases in annual thermal suitability were found for Balaenoptera edeni, Globicephala macrorhynchus, Mesoplodon densirostris, Physeter macrocephalus, Stenella frontalis, Tursiops truncatus and Ziphius cavirostris. Conversely, our results indicated a decline in thermal suitability for B. physalus, Delphinus delphis, and Grampus griseus. Our study reveals potential responses in cetaceans' thermal suitability, and potentially in other highly mobile and large predators, and it tests this method's applicability, which is a novel application for this purpose and group of species. It aims to be a cost-efficient tool to support conservation managers and practitioners.

Predicting non-native seaweeds global distributions: The importance of tuning individual algorithms in ensembles to obtain biologically meaningful results

Modelling non-native marine species distributions is still a challenging activity. This study aims to predict the global distribution of five widespread introduced seaweed species by focusing on two mains aspects of the ensemble modeling process: (1) Does the enforcement of less complex models (in terms of number of predictors) help in obtaining better predictions? (2) What are the implications of tuning the configuration of individual algorithms in terms of ecological realism? Regarding the first aspect, two datasets with different number of predictors were created. Regarding the second aspect, four algorithms and three configurations were tested. Models were evaluated using common evaluation metrics (AUC, TSS, Boyce index and TSS-derived sensitivity) and ecological realism. Finally, a stepwise procedure for model selection was applied to build the ensembles. Models trained with the large predictor dataset generally performed better than models trained with the reduced dataset, but with some exceptions. Regarding algorithms and configurations, Random Forest (RF) and Generalized Boosting Models (GBM) scored the highest metric values in average, even though, RF response curves were the most unrealistic and non-smooth and GBM showed overfitting for some species. Generalized Linear Models (GLM) and MAXENT, despite their lower scores, fitted smoother curves (especially at intermediate complexity levels). Reliable and biologically meaningful predictions were achieved. Inspecting the number of predictors to include in final ensembles and the selection of algorithms and its complexity have been demonstrated to be crucial for this purpose. Additionally, we highlight the importance of combining quantitative (based on multiple evaluation metrics) and qualitative (based on ecological realism) methods for selecting optimal configurations.

Combining electronic tag data and fish harvesters’ knowledge to identify ocean management concerns

Understanding the distribution and reproductive behavior of marine species can inform ocean spatial management to address conservation needs and reduce risks of conflicts among various marine and coastal industries. Combining spatial data on species behavior with fish harvesters’ knowledge can be particularly effective for identifying spatiotemporal overlaps between human activities and critical events at various life stages of marine species. In the present study, the migratory behavior of Atlantic halibut (Hippoglossus hippoglossus), a flatfish of great economic importance in the Gulf of St. Lawrence, was characterized using electronic tags, and potential ocean industry impacts to the halibut population were identified using fish harvesters’ knowledge reported at public meetings and during semi-structured interviews. Results from electronic tagging analyses, including potential seasonal migration paths and presumed spawning locations, were presented to halibut harvesters who responded by identifying industries that could impact the halibut population. Harvesters identified the potential for halibut bycatch in the developing redfish trawl fishery as the main risk to the current high halibut abundance levels, which they attributed to the reduction of Gulf trawling and halibut bycatch since the 1990s. Other potential impacts to halibut identified by harvesters included offshore oil and gas drilling, and effluent discharge from a paper mill transformation project. The present study demonstrates that utilizing complementary data from both fish tracking devices and fish harvesters’ knowledge can help identify and anticipate potential conflicts between fisheries and other ocean industries, and ultimately inform the ecosystem-based marine spatial management of large marine ecosystems.

Population structure and demographic history of the gastropod Thaisella chocolata (Duclos, 1832) from the Southeast Pacific inferred from mitochondrial DNA analyses.

The present‐day population structure of a species reflects the combination of oceanographic currents, life‐history traits, and historical events. However, little is known about the mechanisms that have shaped the gene lineage distribution of marine species inhabiting the Southeast Pacific. Here, we provide a comprehensive phylogeographical study of a species distributed along the Southeast Pacific coastal region by analyzing the endemic gastropod Thaisella chocolata (Duclos, 1832). Sequencing of mitochondrial cytochrome c oxidase subunit 1 (CO1) and 16S rRNA revealed strikingly high haplotypic nucleotide and genetic diversity but a lack of significant population differentiation within the survey area. In addition, a star‐shaped phylogeny and significantly negative Tajima's D and Fu's Fs tests of neutrality suggested historical occurrence of rapid demographic expansion. Mismatch distributions and Bayesian inference analyses also confirmed T. chocolata to have undergone two ancestral demographic expansions. Calculations suggested that these expansions began in the lower and middle Pleistocene epoch, likely due to continental shelf development and climatic conditions. These findings could help establish a genetic baseline for T. chocolata as the first step toward sustainable spatial management of this species, as well as understand this species’ response to future climate change.

First in situ observations of the benthic-demersal fauna on the upper continental slope off Punta Pichalo (19°36'S), northern Chile

An autonomous lander equipped with a video camera (dropcam) was used for in situ observations of the bento-demersal macrofauna on the upper continental slope off Punta Pichalo in northern Chile, an area of permanent coastal upwelling processes, located ~70 km north of Iquique. The lander was deployed at nine stations and between 227 and 798 m of depth. According to morphological characteristics, 34 operational taxonomic units (OTUs) were identified to the lowest taxonomic level; 24 belonged to macroinvertebrates and 10 to fishes. Macroinvertebrates comprised 9 OTUs of crustaceans, seven cnidarians, and six echinoderms. Fishes included 3 OTUs of the order Chondrichthyes, 3 belonging to macrourid. Perciformes, Anguilliformes, and Alepocephaliformes were represented by one OTU each. Also, we observed one species of lanternfish (Myctophidae). Apart from the brachyuran decapod Lophorochinia parabranchia Garth, 1969 and euphausiids, all species were observed at depths greater than 560 m. The presence of one individual identified as the granulate dogfish Centroscyllium granulatum Günther, 1887 extended the known distribution range of this species about 1000 km to the north. Images taken at 795 m showed Bathyraja peruana McEachran & Miyake, 1984. Our study suggests that the upper continental slope of northern Chile harbors nearly undiscovered biodiversity, worth to be studied more intensively to complete the comparable sparse knowledge about marine biodiversity and species distribution at the continental margin in front of Chile.

Modeling the Probability of Overlap Between Marine Fish Distributions and Marine Renewable Energy Infrastructure Using Acoustic Telemetry Data

Understanding the spatiotemporal distributions of migratory marine species at marine renewable energy sites is a crucial step towards assessing the potential impacts of tidal stream turbines and related infrastructure upon these species. However, the dynamic marine conditions that make tidal channels attractive for marine renewable power development also make it difficult to identify and follow species of marine fishes with existing technologies such as hydroacoustics and optical cameras. Acoustic telemetry can resolve some of these problems. Acoustic tags provide unique individual ID codes at an ultrasonic frequency, which are then detected and recorded by acoustic receivers deployed in the area of interest. By matching detection locations of fish species with environmental conditions at proposed sites for tidal energy infrastructure, species distribution models can be developed to predict the probability of species occurrence at sites of current and planned tidal power development. This information can be used to develop statistically robust encounter rate models to aid in quantifying the risk of tidal power development to migratory fish species. We used this approach to develop a predictive model of striped bass (Morone saxatilis) distribution within Minas Passage in the upper Bay of Fundy, Nova Scotia. Model results suggested increased probability of striped bass presence in Minas Passage during late ebb tide conditions and at relatively high water temperatures. We demonstrate the potential utility of species distribution modeling of acoustic tag detections in predicting interactions with renewable energy infrastructure, and show the importance of physical oceanographic variables influencing species distributions in a highly dynamic marine environment.

Future seasonal changes in habitat for Arctic whales during predicted ocean warming.

Ocean warming is causing shifts in the distributions of marine species, but the location of suitable habitats in the future is unknown, especially in remote regions such as the Arctic. Using satellite tracking data from a 28-year-long period, covering all three endemic Arctic cetaceans (227 individuals) in the Atlantic sector of the Arctic, together with climate models under two emission scenarios, species distributions were projected to assess responses of these whales to climate change by the end of the century. While contrasting responses were observed across species and seasons, long-term predictions suggest northward shifts (243 km in summer versus 121 km in winter) in distribution to cope with climate change. Current summer habitats will decline (mean loss: −25%), while some expansion into new winter areas (mean gain: +3%) is likely. However, comparing gains versus losses raises serious concerns about the ability of these polar species to deal with the disappearance of traditional colder habitats.

Distribution of phycotoxins in Última Esperanza Province during the PROFAN expedition 2019

Harmful Algae Blooms pose an increasing threat to the public health and economic stability of Southern Chile, particularly to the aquaculture industries. This fieldwork performed during the PROFAN expedition from 12th to 22nd November 2019 extends the knowledge on the distribution of marine toxin-producing species in the difficult to access Última Esperanza Province in the Magallanes Region. Paralytic Shellfish Poisoning toxins with high relative abundances of saxitoxin and lipophilic toxins dominated by yessotoxins, pectenotoxins and domoic acid were detected at nearly each sampling station. The respective toxin-producing organisms are mainly from the genus Alexandrium and Dinophysis. Furthermore, the first detection of pinnatoxin-G (PnTx-G) in Chilean waters strongly indicates the presence of the dinoflagellate Vulcanodinium rugosum.

The morphological diversity within a species can obscure the correct identification

Critical points of various diagnostic characters and a paucity of information relating to the geographical distribution of several marine species can hinder real species delimitation, particularly if they are supposed to be cosmopolitan. Such constraints characterize many amphipod species and are mainly due to the variation in morphological characters during growth. Specifically, the benthic filter-feeding corophiid Cheiriphotis mediterraneaMyers, 1983 displays different shapes for the male gnathopod 2 as it grows. This variation has hitherto never been described but an extensive sampling has provided us with the opportunity of studying it in detail. More than six thousand individuals, belonging to C. mediterranea, were collected along the Israeli coast during a five-year soft-bottom monitoring survey, comprising 282 sites at a depth between 4 and 37 m. One of the objectives of this study was to integrate the original description of C. mediterranea with the identification of definite six morphotypes, which alternate during growth. A mtDNA Cytochrome c oxidase subunit I sequence was obtained, representing the first molecular datum for the genus Cheiriphotis. The results offer the possibility of including variable morphological characters and molecular sequences in the identification process. Throughout the survey, C. mediterranea was confirmed to be one of the most abundant five species in the study area, in particular in Haifa Bay, where the environmental conditions are stressful. Barely-known abundance and distribution notes relating to this species are reported in this paper; a putative role of bioindicator is also suggested.

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.

Environmental DNA reveals fine‐scale habitat associations for sedentary and resident marine species across a coastal mosaic of soft‐ and hard‐bottom habitats

AbstractAccurate knowledge on spatiotemporal distributions of marine species and their association with surrounding habitats is crucial to inform adaptive management actions responding to coastal degradation across the globe. Here, we investigate the potential use of environmental DNA (eDNA) to detect species–habitat associations in a patchy coastal area of the Baltic Sea. We directly compare species‐specific qPCR analysis of eDNA with baited remote underwater video systems (BRUVS), two non‐invasive methods widely used to monitor marine habitats. Four focal species (cod Gadus morhua, flounder Platichthys flesus, plaice Pleuronectes platessa, and goldsinny wrasse Ctenolabrus rupestris) were selected based on contrasting habitat associations (reef‐ vs. sand‐associated species), as well as differential levels of mobility and residency, to investigate whether these factors affected the detection of species–habitat associations from eDNA. To this end, a species‐specific qPCR assay for goldsinny wrasse is developed and made available herein. In addition, potential correlations between eDNA signals and abundance counts (MaxN) from videos were assessed. Results from Bayesian multilevel models revealed strong evidence for a sand association for sedentary flounder (98% posterior probability) and a reef association for highly resident wrasse (99% posterior probability) using eDNA, in agreement with BRUVS. However, contrary to BRUVS, eDNA sampling did not detect habitat associations for cod or plaice. We found a positive correlation between eDNA detection and MaxN for wrasse (posterior probability 95%), but not for the remaining species and explanatory power of all relationships was generally limited. Our results indicate that eDNA sampling can detect species–habitat associations on a fine spatial scale, yet this ability likely depends on the mobility and residency of the target organism, with associations for sedentary or resident species most likely to be detected. Combined sampling with conventional non‐invasive methods is advised to improve detection of habitat associations for mobile and transient species, or for species with low eDNA concentrations.

The salinity effect and sedimentary types for the fauna distribution during the Holocene in Southern Iraq

In the present study, abundance and distribution of fauna in the sub surface sediments of the eight stations, Abo Flos, Ras Al-Besha, Khor Al-Umaya, Khor Shitana, Umm Qaser, Khor Al-Zubair, Kutaiban and Al-Faw were investigated. The stations selected for the present study were located at the southern region of Mesopotamia plain in Iraq. A reconnaissance survey in the study area showed the distribution of many marine species in the coastal areas (Khor Shitana, Umm Qaser, Khor Al-Zubair and Al-Faw). They were affected by the marine water areas with few effects of tidal flat and current waves. The affinities of the studied species are coming from the Indian Ocean towards the Red sea and the Arabian Gulf. The salinity and texture of sediment are the main factors that control the ecology and distribution of recent fauna. The soil texture for eight stations are sandy silt, clayey silt, silt, sandy silt and mud respectively.

Unifying approaches to Functional Marine Connectivity for improved marine resource management: the European SEA-UNICORN COST Action

Truly sustainable development in a human-altered, fragmented marine environment subject to unprecedented climate change, demands informed planning strategies in order to be successful. Beyond a simple understanding of the distribution of marine species, data describing how variations in spatio-temporal dynamics impact ecosystem functioning and the evolution of species are required. Marine Functional Connectivity (MFC) characterizes the flows of matter, genes and energy produced by organism movements and migrations across the seascape. As such, MFC determines the ecological and evolutionary interdependency of populations, and ultimately the fate of species and ecosystems. Gathering effective MFC knowledge can therefore improve predictions of the impacts of environmental change and help to refine management and conservation strategies for the seas and oceans. Gathering these data are challenging however, as access to, and survey of marine ecosystems still presents significant challenge. Over 50 European institutions currently investigate aspects of MFC using complementary methods across multiple research fields, to understand the ecology and evolution of marine species. The aim of SEA-UNICORN, a COST Action within the European Union Horizon 2020 framework programme, is to bring together this research effort, unite the multiple approaches to MFC, and to integrate these under a common conceptual and analytical framework. The consortium brings together a diverse group of scientists to collate existing MFC data, to identify knowledge gaps, to enhance complementarity among disciplines, and to devise common approaches to MFC. SEA-UNICORN will promote co-working between connectivity practitioners and ecosystem modelers to facilitate the incorporation of MFC data into the predictive models used to identify marine conservation priorities. Ultimately, SEA-UNICORN will forge strong forward-working links between scientists, policy-makers and stakeholders to facilitate the integration of MFC knowledge into decision support tools for marine management and environmental policies.

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