Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence

Arctic puzzle: Pioneering a northern shrimp (Pandalus borealis) habitat model in Disko Bay, West Greenland

Recent advancements in spatial modelling leverage remote sensing data and statistical species-environment relationships to forecast the distribution of a specific species. Our study focuses on Disko Bay in West Greenland, recognized as a significant marine biodiversity hotspot in the region. We conducted comprehensive analyses using multiple datasets spanning from 2010 to 2019, incorporating shrimp and fish surveys, commercial shrimp fishery catches, high-resolution (25 × 25 m) multibeam bathymetry and backscatter data along with a medium-resolution (200 × 200 m) bathymetric model, measured and modelled oceanographic data, and satellite chlorophyll data. Through multivariate regression analysis, we tested the significance of various physical factors (seafloor depth, sediment class, bottom water temperature, bottom water salinity, bottom current velocity, space, and time), biological factors (chlorophyll a, Greenland halibut (Reinhardtius hippoglossoides)), and anthropogenic impact (shrimp fishery; standardized catch per unit effort) on the density of northern shrimp in the area. Our results indicate a significant association between northern shrimp density, seafloor depth, and sediment class, explaining 36 % of the variation in shrimp density. Subsequently, we developed a high-resolution (optimized) spatial linear mixed-effect model to map the distribution of northern shrimp across Disko Bay, representing the first model of its kind developed for an Arctic area. The optimal habitat for northern shrimp is characterized by medium-deep waters (approximately 150-350 m), turbulent conditions, and mixed sediments, predominantly located in the northern and southern regions of Disko Bay. Notably, the northern region hosts a relatively diverse benthic community, with northern shrimp and sponges as the primary contributors of epibenthic biomass. This novel high-resolution model significantly enhances our understanding of the physical drivers and detailed spatial patterns influencing the distribution of northern shrimp in the Arctic.

Spatial distribution of the range-expanding species Seriola fasciata (Bloch, 1793) in Mediterranean Sea: From past to future

The Mediterranean Sea is a highly susceptible area to climate change, that facilitates the introduction of warm-affinity exotic species, contributing to the expansion of their biogeographical range. One such thermophilic species is the Atlantic fish Seriola fasciata, which has colonised this area over the past three decades. The present study analyzed its spatial distribution in the Mediterranean Sea to identify aggregation areas and dynamics over time, and the environmental predictors influencing its presence. The utilized statistical tools and the Species Distribution Model proved effective in identifying specific spatial and temporal distribution patterns, as well as discerning some environmental variables influencing the species presence, with distinctions recorded between juveniles and adults. S. fasciata was observed to be established in the central Mediterranean, with Fishing Aggregating Devices potentially influencing its presence, particularly of juveniles. Sea floor temperature and habitats emerged as the primary factors driving species distribution. An aggregation area in the Levant Sea, conducive mainly for the adults, was identified and is expected to intensify over time. These findings contribute valuable insights into a relatively understudied species and its presence in the Mediterranean Sea, where climate change is affecting marine biodiversity.

Distribution models of baleen whale species in the Irish Exclusive Economic Zone to inform management and conservation

Irish waters are under increasing pressure from anthropogenic sources including the development of offshore renewable energy, vessel traffic and fishing activity. Spatial planning requires robust datasets on species distribution and the identification of important habitats to inform the planning process. Despite limited survey effort, long-term citizen science data on whale presence are available and provide an opportunity to fill information gaps. Using presence-only data as well as a variety of environmental variables, we constructed seasonal ensemble species distribution models based on five different algorithms for minke whales, fin whales, humpback whales, sei whales, and blue whales. The models predicted that the coastal waters off the south and west of Ireland are particularly suitable for minke, fin and humpback whales. Offshore waters in the Porcupine Seabight area were identified as a relevant habitat for fin whales, sei whales and blue whales. We combined model outputs with data on maritime traffic, fishing activity and offshore wind farms to measure the exposure of all the species to these pressures, identifying areas of concern. This study serves as a baseline for the species presence in Irish waters over the last two decades to help develop appropriate marine spatial plans in the future.

Unveiling the resistance of native weed communities: insights for managing invasive weed species in disturbed environments

Weed communities influence the dynamics of ecosystems, particularly in disturbed environments where anthropogenic activities often result in higher pollution. Understanding the dynamics existing between native weed communities and invasive species in disturbed environments is crucial for effective management and normal ecosystem functioning. Recognising the potential resistance of native weed communities to invasion in disturbed environments can help identify suitable native plants for restoration operations. This review aims to investigate the adaptations exhibited by native and non-native weeds that may affect invasions within disturbed environments. Factors such as ecological characteristics, altered soil conditions, and adaptations of native weed communities that potentially confer a competitive advantage relative to non-native or invasive weeds in disturbed environments are analysed. Moreover, the roles of biotic interactions such as competition, mutualistic relationships, and allelopathy in shaping the invasion resistance of native weed communities are described. Emphasis is given to the consideration of the resistance of native weeds as a key factor in invasion dynamics that provides insights for conservation and restoration efforts in disturbed environments. Additionally, this review underscores the need for further research to unravel the underlying mechanisms and to devise targeted management strategies. These strategies aim to promote the resistance of native weed communities and mitigate the negative effects of invasive weed species in disturbed environments. By delving deeper into these insights, we can gain an understanding of the ecological dynamics within disturbed ecosystems and develop valuable insights for the management of invasive species, and to restore long-term ecosystem sustainability.

Projected habitat preferences of commercial fish under different scenarios of climate change

The challenges of commercial species with the threats of climate change make it necessary to predict the changes in the distributional shifts and habitat preferences of the species under possible future scenarios. We aim to demonstrate how future climatic changes will affect the habitat suitability of three species of commercial fish using the predictive technique MaxEnt. The dataset used to extract geographical records included OBIS (54%), GBIF (1%), and literature (45%). The output of the model indicated accurate projections of MaxEnt (AUC above 0.9). Temperature was the main descriptor responsible for the main effects on the distribution of commercial fish. With increasing RCP from 2.5 to 8.5, the species would prefer saltier, higher temperatures and deeper waters in the future. We observed different percentages of suitable habitats between species during RCPs showing distinct sensitivity of each fish in facing climate changes. Negative effects from climate change on the distribution patterns of commercial fish were predicted to lead to varying degrees of reduction and changes of suitable habitats and movement of species towards higher latitudes. The finding emphasizes to implement adaptive management measures to preserve the stocks of these commercial fish considering that the intensification of the effects of climate change on subtropical areas and overexploited species is predicted.

Evolution of the ecological niche behind the largest disjunct freshwater fish distribution in the world

Ecological processes that are behind distributions of species that inhabit isolated localities, complex disjunct distributions, remain poorly understood. Traditionally, vicariance and dispersion have been proposed as explanatory mechanisms that drive such distributions. However, to date, our understanding of the ecological processes driving evolution of ecological niches associated with disjunct distributions remains rudimentary. Here, we propose a framework to deconstruct drivers of such distribution using World's most widespread freshwater fish Galaxias maculatus as a model and integrating marine and freshwater environments where its life cycle may occur. Specifically, we assessed ecological and historical factors (Gondwanan vicariance, marine dispersion) and potential dispersion (niche-tracking) that explain its distribution in the Southern Hemisphere. Estimated distribution was consistent with previously reported distribution and mainly driven by temperature and topography in freshwater environments and by primary productivity and nitrate in marine environments. Niche dynamics of G. maculatus provided evidence of synergy between vicariance and marine dispersion as explanatory mechanisms of its disjunct distribution, suggesting that its ecological niche was conserved since approximately 30 Ma ago. This integrated assessment of ecological niche in marine and freshwater environments serves as a generic framework that may be applied to understand processes underpinning complex distributions of diadromous species.

A species distribution model of the giant kelp Macrocystis pyrifera: Worldwide changes and a focus on the Southeast Pacific

Worldwide climate-driven shifts in the distribution of species is of special concern when it involves habitat-forming species. In the coastal environment, large Laminarian algae-kelps-form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat-forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios with a focus on the Southeast Pacific shores. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the single most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the Southeast Pacific, we observed an upper range contraction of -17.08° S of latitude for 2090-2100 under the RCP8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to -27.83° S in Chile. Along the area of Northern Chile where a complete habitat loss is predicted by our model, natural stands are under heavy exploitation. The loss of habitat suitability will take place worldwide: Significant impacts on marine biodiversity and ecosystem functioning are likely. Furthermore, changes in habitat suitability are a harbinger of massive impacts in the socio-ecological systems of the Southeast Pacific.

Incorporating adaptive genomic variation into predictive models for invasion risk assessment

Global climate change is expected to accelerate biological invasions, necessitating accurate risk forecasting and management strategies. However, current invasion risk assessments often overlook adaptive genomic variation, which plays a significant role in the persistence and expansion of invasive populations. Here we used Molgula manhattensis, a highly invasive ascidian, as a model to assess its invasion risks along Chinese coasts under climate change. Through population genomics analyses, we identified two genetic clusters, the north and south clusters, based on geographic distributions. To predict invasion risks, we employed the gradient forest and species distribution models to calculate genomic offset and species habitat suitability, respectively. These approaches yielded distinct predictions: the gradient forest model suggested a greater genomic offset to future climatic conditions for the north cluster (i.e., lower invasion risks), while the species distribution model indicated higher future habitat suitability for the same cluster (i.e, higher invasion risks). By integrating these models, we found that the south cluster exhibited minor genome-niche disruptions in the future, indicating higher invasion risks. Our study highlights the complementary roles of genomic offset and habitat suitability in assessing invasion risks under climate change. Moreover, incorporating adaptive genomic variation into predictive models can significantly enhance future invasion risk predictions and enable effective management strategies for biological invasions in the future.

Spatial and temporal patterns of phytoplankton community succession and characteristics of realized niches in Lake Taihu, China

Understanding the dynamics and succession of phytoplankton in large lakes can help inform future lake management. The study analyzed phytoplankton community variations in Lake Taihu over a 21-year period, focusing on realized niches and their impact on succession. The study developed a niche periodic table with 32 niches, revealing responses to environmental factors and the optimal number of niches. Results showed that the phytoplankton in Lake Taihu showed significant spatial and temporal heterogeneity, with biomass decreasing as one moved from the northwest to the southeast and expanding towards central lake area, and towards autumn and winter. Different phytoplankton groups in Lake Taihu occupied realized niches shaped by temperature, nitrate, and phosphate. To predict the response of eutrophic freshwater lake ecosystems to human activities and climate change, it is critical to interpret the law of phytoplankton bloom and niche succession.

Environmental DNA and remote sensing datasets reveal the spatial distribution of aquatic insects in a disturbed subtropical river system

Biodiversity datasets with high spatial resolution are critical prerequisites for river protection and management decision-making. However, traditional morphological biomonitoring is inefficient and only provides several site estimates, and there is an urgent need for new approaches to predict biodiversity on fine spatial scales throughout the entire river systems. Here, we combined the environmental DNA (eDNA) and remote sensing (RS) technologies to develop a novel approach for predicting the spatial distribution of aquatic insects with high spatial resolution in a disturbed subtropical Dongjiang River system of southeast China. First, we screened thirteen RS-based vegetation indices that significantly correlated with the eDNA-inferred richness of aquatic insects. In particular, the green normalized difference vegetation index (GNDVI) and normalized difference red-edge2 (NDRE2) were closely related to eDNA-inferred richness. Second, using the gradient boosting decision tree, our data showed that the spatial pattern of eDNA-inferred richness could achieve a high spatial resolution to 500 m reach and accurate prediction of more than 80%, and the prediction efficiency of the headwater streams (Strahler stream order = 1) was slightly higher than the downstream (Strahler stream order >1). Third, using the random forest algorithm, the spatial distribution of aquatic insects could reach a prediction rate of over 70% for the presence or absence of specific genera. Overall, this study provides a new approach to achieving high spatial resolution prediction of the distribution of aquatic insects, which supports decision-making on river diversity protection under climate changes and human impacts.

Potential geographical distribution of harmful algal blooms caused by the toxic dinoflagellate Karenia mikimotoi in the China Sea

The fish-killing dinoflagellate Karenia mikimotoi frequently blooms in China and poses a threat to food safety and human health. To better understand harmful algal blooms (HABs) caused by K. mikimotoi and predict the risk of HABs under climate change, the combined effect of nitrate and norfloxacin (NOR) on the growth of K. mikimotoi was tested. A growth model was used to test the effects of nutrients and pollutants on the carrying capacity of the unicellular algae. The carrying capacity increased with increasing concentrations of nitrate and NOR, reaching a maximum at 62.2 μmol L-1 of nitrate and 9.03 mg L-1 of NOR. The calculated carrying capacity of K. mikimotoi in the China Sea showed a declining trend from nearshore to offshore, with a value >30 × 106 cells L-1 in the estuary of the Changjiang River and Hangzhou Bay. The HAB index proposed in this study as a measurement of HAB risk was constructed using the carrying capacity and relative abundance from the MaxEnt (maximum entropy) model. The index showed that HABs caused by K. mikimotoi consecutively occurred in Zhejiang and Fujian coastal waters and predicted that they will continue until 2100, regardless of the greenhouse gas emission scenario. The center of the integrated area moved northward, with a range of 120-900 km. The HAB index integrates the characteristics of the carrying capacity and suitability of habitats, and expresses the information contained in the intensive and extensive variables that affect HAB occurrence. This index is a promising predictor of HAB risk in coastal waters.

Niche differentiation, reproductive interference, and range expansion

Understanding species distributions and predicting future range shifts requires considering all relevant abiotic factors and biotic interactions. Resource competition has received the most attention, but reproductive interference is another widespread biotic interaction that could influence species ranges. Rubyspot damselflies (Hetaerina spp.) exhibit a biogeographic pattern consistent with the hypothesis that reproductive interference has limited range expansion. Here, we use ecological niche models to evaluate whether this pattern could have instead been caused by niche differentiation. We found evidence for climatic niche differentiation, but the species that encounters the least reproductive interference has one of the narrowest and most peripheral niches. These findings strengthen the case that reproductive interference has limited range expansion and also provide a counterexample to the idea that release from negative species interactions triggers niche expansion. We propose that release from reproductive interference enables species to expand in range while specializing on the habitats most suitable for breeding.

Environmental factors influencing the diversity and distribution of dictyostelid cellular slime molds in forest and farmland soils of western China

IMPORTANCE

Soil protists are an essential yet seriously understudied component of the soil microbiome. In this study, 11 new records of dictyostelids belonging to 2 orders, 3 families, and 4 genera were identified from 99 soil samples collected from different elevations and habitats in central Gansu and the southeastern and southcentral portions of Guizhou Province, China. We found that dictyostelid communities were significantly different between Gansu and Guizhou Provinces, apparently in response to different environmental factors. Moreover, dictyostelids were found to have the highest species diversity in mixed forests. Soil pH, temperature, and elevation were determined to be the primary factors that affect the distribution and occurrence of dictyostelids in Guizhou and Gansu Provinces. This work supplements the survey data available for dictyostelids elsewhere in China. These new findings have significant implications for our understanding of the diversity of soil microorganisms.

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Distribution and co-occurrence patterns of charophytes and angiosperms in the northern Baltic Sea

The distribution data of 11 soft substrate charophyte and angiosperm species were analyzed. Our study aimed to elucidate the co-occurrence patterns among these sympatric macrophyte species and quantify their distribution areas. The central hypothesis of this study proposed that the observed co-occurrence patterns among the studied species deviate from what would be expected by random chance. Macrophyte occurrence data was derived from an extensive field sampling database. Environmental variables available as georeferenced raster layers including topographical, hydrodynamic, geological, physical, chemical, and biological variables were used as predictor variables in the random forest models to predict the spatial distribution of the species. Permutation tests revealed statistically significant deviations from random co-occurrence patterns. The analysis demonstrated that species tended to co-occur more frequently within their taxonomic groups (i.e., within charophytes and within angiosperms) than between these groups. The most extensive distribution overlap was observed between Chara aspera Willd. and Chara canescens Loisel., while Zostera marina L. exhibited the least overlap with the other species. The mean number of co-occurring species was the highest in Chara baltica (Hartman) Bruzelius while Z. marina had the largest share of single-species occurrences. Based on the distribution models, Stuckenia pectinata (L.) Börner had the largest distribution area.

Opening the floodgates for invasion-modelling the distribution dynamics of invasive alien fishes in India

Invasive alien species have become the second major threat to biodiversity affecting all three major ecosystems (terrestrial, marine, and freshwater). Increasing drivers such as habitat destruction, expanding horticulture and aquaculture industries, and global pet and food trade have created pathways for exotic species to be introduced leading to severe impacts on recipient ecosystems. Although relatively less studied than terrestrial ecosystems, freshwater ecosystems are highly susceptible to biological invasions. In India, there has been a noticeable increase in the introduction of alien fish species in freshwater environments. In the current study, we aimed to understand how climate change can affect the dynamics of the biological invasion of invasive alien fishes in India. We also evaluated the river-linking project's impact on the homogenization of biota in Indian freshwater bodies. We used species occurrence records with selected environmental variables to assess vulnerable locations for current and future biological invasion using species distribution models. Our study has identified and mapped the vulnerable regions to invasion in India. Our research indicates that the interlinking of rivers connects susceptible regions housing endangered fish species with invasive hotspots. Invasive alien fishes from the source basin may invade vulnerable basins and compete with the native species. Based on the results, we discuss some of the key areas for the management of these invasive alien species in the freshwater ecosystems.

Isotopic niche overlap among foraging marine turtle species in the Gulf of Mexico

Sympatric species may overlap in their use of habitat and dietary resources, which can increase competition. Comparing the ecological niches and quantifying the degree of niche overlap among these species can provide insights into the extent of resource overlap. This information can be used to guide multispecies management approaches tailored to protect priority habitats that offer the most resources for multiple species. Stable isotope analysis is a valuable tool used to investigate spatial and trophic niches, though few studies have employed this method for comparisons among sympatric marine turtle species. For this study, stable carbon, nitrogen, and sulfur isotope values from epidermis tissue were used to quantify isotopic overlap and compare isotopic niche size in loggerhead (Caretta caretta), green (Chelonia mydas), and Kemp's ridley (Lepidochelys kempii) turtles sampled from a shared foraging area located offshore of Crystal River, Florida, USA. Overall, the results revealed high degrees of isotopic overlap (>68%) among species, particularly between loggerhead and Kemp's ridley turtles (85 to 91%), which indicates there may be interspecific competition for resources. Samples from green turtles had the widest range of isotopic values, indicating they exhibit higher variability in diet and habitat type. Samples from loggerhead turtles had the most enriched mean δ34S, suggesting they may forage in slightly different micro-environments compared with the other species. Finally, samples from Kemp's ridley turtles exhibited the smallest niche size, which is indicative of a narrower use of resources. This is one of the first studies to investigate resource use in a multispecies foraging aggregation of marine turtles using three isotopic tracers. These findings provide a foundation for future research into the foraging ecology of sympatric marine turtle species and can be used to inform effective multispecies management efforts.

Impacts of climate change on the distribution of venomous Conus (Gastropoda: Conidae) species in the Indo-Pacific region

Climate change is affecting the distribution of marine organisms worldwide, including venomous marine gastropods that offer risks to human health, but also potential pharmacological resources, such as Conus sp. Species Distribution Models (SDMs) are valuable tools for predicting species distribution under climate change. The objective of our study was to evaluate the potential distribution of Conus geographus and C. textile in the Indo-Pacific region under different climate change scenarios for 2050 and 2090. We constructed SDMs with MaxEnt for each species, using bioclimatic variables from Bio-ORACLE and NOAA, and occurrence data from GBIF. We projected the best-fit model for the present and different future climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). We obtained high accuracy SDMs for C. geographus and C. textile, with Temperature and Primary Productivity as the main explanatory variables. Our future projections reveal that both species may react differently to climate change. Southeast Asia and Micronesia will continue to provide a climatically appropriate environment for both species; however, they may become more suitable for C. geographus and less suitable for C. textile. This may lead to a higher risk of human envenomation by C. geographus, but a lower risk by C. textile. A decreased suitability for C. textile may also lead to the loss of potential pharmacological resources among its range. Our study emphasizes how SDMs can be used to assess the future distribution of species with human health implications, which can aid in the monitoring of venomous marine species.

Three-dimensional species distribution modelling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs

The three-dimensional structure of habitats is a critical component of species' niches driving coexistence in species-rich ecosystems. However, its influence on structuring and partitioning recruitment niches has not been widely addressed. We developed a new method to combine species distribution modelling and structure from motion, and characterized three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and gorgonians. Fine-scale roughness was the most important predictor of suitable habitat for both taxa, and their niches largely overlapped, primarily due to scleractinians' broader niche breadth. Crevices and holes at mm scales on calcareous rock with low coral cover were more suitable for octocorals than for scleractinian recruits, suggesting that the decline in scleractinian corals is facilitating the recruitment of octocorals on contemporary Caribbean reefs. However, the relative abundances of the taxa were independent of the amount of suitable habitat on the reef, emphasizing that niche processes alone do not predict recruitment rates.

Forecasting Brassica napus production under climate change with a mechanistic species distribution model

Brassica napus, a versatile crop with significant socioeconomic importance, serves as a valuable source of nutrition for humans and animals while also being utilized in biodiesel production. The expansion potential of B. napus is profoundly influenced by climatic variations, yet there remains a scarcity of studies investigating the correlation between climatic factors and its distribution. This research employs CLIMEX to identify the current and future ecological niches of B. napus under the RCP 8.5 emission scenario, utilizing the Access 1.0 and CNRM-CM5 models for the time frame of 2040-2059. Additionally, a sensitivity analysis of parameters was conducted to determine the primary climatic factors affecting B. napus distribution and model responsiveness. The simulated outcomes demonstrate a satisfactory alignment with the known current distribution of B. napus, with 98% of occurrence records classified as having medium to high climatic suitability. However, the species displays high sensitivity to thermal parameters, thereby suggesting that temperature increases could trigger shifts in suitable and unsuitable areas for B. napus, impacting regions such as Canada, China, Brazil, and the United States.

Responses of population structure and genomic diversity to climate change and fishing pressure in a pelagic fish

The responses of marine species to environmental changes and anthropogenic pressures (e.g., fishing) interact with ecological and evolutionary processes that are not well understood. Knowledge of changes in the distribution range and genetic diversity of species and their populations into the future is essential for the conservation and sustainable management of resources. Almaco jack (Seriola rivoliana) is a pelagic fish with high importance to fisheries and aquaculture in the Pacific Ocean. In this study, we assessed contemporary genomic diversity and structure in loci that are putatively under selection (outlier loci) and determined their potential functions. Using a combination of genotype-environment association, spatial distribution models, and demogenetic simulations, we modeled the effects of climate change (under three different RCP scenarios) and fishing pressure on the species' geographic distribution and genomic diversity and structure to 2050 and 2100. Our results show that most of the outlier loci identified were related to biological and metabolic processes that may be associated with temperature and salinity. The contemporary genomic structure showed three populations-two in the Eastern Pacific (Cabo San Lucas and Eastern Pacific) and one in the Central Pacific (Hawaii). Future projections suggest a loss of suitable habitat and potential range contractions for most scenarios, while fishing pressure decreased population connectivity. Our results suggest that future climate change scenarios and fishing pressure will affect the genomic structure and genotypic composition of S. rivoliana and lead to loss of genomic diversity in populations distributed in the eastern-central Pacific Ocean, which could have profound effects on fisheries that depend on this resource.

Mapping the biodiversity conservation gaps in the East China sea

Being one of the most productive China seas, the East China Sea is facing the challenge of unprecedented biodiversity loss and habitat degradation under the dual pressure of anthropogenic disturbance and climate change. Although marine protected areas (MPAs) are considered an effective conservation tool, it remains unclear whether existing MPAs adequately protect marine biodiversity. To investigate this issue, we first constructed a maximum entropy model to predict the distributions of 359 threatened species and identified its species richness hotspots in the East China Sea. Then we identified priority conservation areas (PCAs¹) under different protection scenarios. Since the actual conservation in the East China Sea is far from the goals proposed by Convention on Biological Diversity, we calculated a more realistic conservation goal by quantifying the relationship between the percentage of protected areas in the East China Sea and the average proportion of habitats covered for all species. Finally, we mapped conservation gaps by comparing the PCAs under the proposed goal and existing MPAs. Our results showed that these threatened species were very heterogeneously distributed, and their abundance was highest at low latitudes and in nearshore areas. The identified PCAs were distributed mainly in nearshore areas, especially in the Yangtze River estuary and along the Taiwan Strait. Based on the current distribution of threatened species, we suggest a minimum conservation goal of 20.4% of the total area of the East China Sea. Only 8.8% of the recommended PCAs are currently within the existing MPAs. We recommend expanding the MPAs in six areas to achieve the minimum conservation target. Our findings provide a solid scientific reference and a reasonable short-term target for China to realize the vision of protecting 30% of its oceans by 2030.

The genetic basis of the leafy seadragon's unique camouflage morphology and avenues for its efficient conservation derived from habitat modeling

The leafy seadragon certainly is among evolution's most "beautiful and wonderful" species aptly named for its extraordinary camouflage mimicking its coastal seaweed habitat. However, limited information is known about the genetic basis of its phenotypes and conspicuous camouflage. Here, we revealed genomic signatures of rapid evolution and positive selection in core genes related to its camouflage, which allowed us to predict population dynamics for this species. Comparative genomic analysis revealed that seadragons have the smallest olfactory repertoires among all ray-finned fishes, suggesting adaptations to the highly specialized habitat. Other positively selected and rapidly evolving genes that serve in bone development and coloration are highly expressed in the leaf-like appendages, supporting a recent adaptive shift in camouflage appendage formation. Knock-out of bmp6 results in dysplastic intermuscular bones with a significantly reduced number in zebrafish, implying its important function in bone formation. Global climate change-induced loss of seagrass beds now severely threatens the continued existence of this enigmatic species. The leafy seadragon has a historically small population size likely due to its specific habitat requirements that further exacerbate its vulnerability to climate change. Therefore, taking climate change-induced range shifts into account while developing future protection strategies.

Leveraging Public Data to Predict Global Niches and Distributions of Rhizostome Jellyfishes

As climate change progresses rapidly, biodiversity declines, and ecosystems shift, it is becoming increasingly difficult to document dynamic populations, track fluctuations, and predict responses to climate change. Concurrently, publicly available databases and tools are improving scientific accessibility, increasing collaboration, and generating more data than ever before. One of the most successful projects is iNaturalist, an AI-driven social network doubling as a public database designed to allow citizen scientists to report personal biodiversity reports with accuracy. iNaturalist is especially useful for the research of rare, dangerous, and charismatic organisms, but requires better integration into the marine system. Despite their abundance and ecological relevance, there are few long-term, high-sample datasets for jellyfish, which makes management difficult. To provide some high-sample datasets and demonstrate the utility of publicly collected data, we synthesized two global datasets for ten genera of jellyfishes in the order Rhizostomeae containing 8412 curated datapoints from both iNaturalist (n = 7807) and the published literature (n = 605). We then used these reports in conjunction with publicly available environmental data to predict global niche partitioning and distributions. Initial niche models inferred that only two of ten genera have distinct niche spaces; however, the application of machine learning-based random forest models suggests genus-specific variation in the relevance of abiotic environmental variables used to predict jellyfish occurrence. Our approach to incorporating reports from the literature with iNaturalist data helped evaluate the quality of the models and, more importantly, the quality of the underlying data. We find that free, accessible online data is valuable, yet subject to biases through limited taxonomic, geographic, and environmental resolution. To improve data resolution, and in turn its informative power, we recommend increasing global participation through collaboration with experts, public figures, and hobbyists in underrepresented regions capable of implementing regionally coordinated projects.

Forecasting distributional shifts of Patella spp. in the Northeast Atlantic Ocean, under climate change

Mapping species' geographical distribution is fundamental for understanding current patterns and forecasting future changes. Living on rocky shores along the intertidal zone, limpets are vulnerable to climate change, as their range limits are controlled by seawater temperature. Many works have been studying limpets' potential responses to climate change at local and regional scales. Focusing on four Patella species living on the rocky shores of the Portuguese continental coast, this study aims to predict climate change impacts on their global distribution, while exploring the role of the Portuguese intertidal as potential climate refugia. Ecological niche models combine occurrences and environmental data to identify the drivers of these species' distributions, define their current range, and project to future climate scenarios. The distribution of these limpets was mostly defined by low bathymetry (intertidal) and the seawater temperature. Independent of the climate scenario, all species will gain suitable conditions at the northern distribution edge while losing in the south, yet only the extent of occurrence of P. rustica is expected to contract. Apart from the southern coast, maintenance of suitable conditions for these limpets' occurrence was predicted for the western coast of Portugal. The predicted northward range shift follows the observed pattern observed for many intertidal species. Given the ecosystem role of this species, attention should be given to their southern range limits. Under the current upwelling effect, the Portuguese western coast might constitute thermal refugia for limpets in the future.

Understanding opposing predictions of Prochlorococcus in a changing climate

Statistically derived species distribution models (SDMs) are increasingly used to predict ecological changes on a warming planet. For Prochlorococcus, the most abundant phytoplankton, an established statistical prediction conflicts with dynamical models as they predict large, opposite, changes in abundance. We probe the SDM at various spatial-temporal scales, showing that light and temperature fail to explain both temporal fluctuations and sharp spatial transitions. Strong correlations between changes in temperature and population emerge only at very large spatial scales, as transects pass through transitions between regions of high and low abundance. Furthermore, a two-state model based on a temperature threshold matches the original SDM in the surface ocean. We conclude that the original SDM has little power to predict changes when Prochlorococcus is already abundant, which resolves the conflict with dynamical models. Our conclusion suggests that SDMs should prove efficacy across multiple spatial-temporal scales before being trusted in a changing ocean.

The lack of genetic variation underlying thermal transcriptomic plasticity suggests limited adaptability of the Northern shrimp, Pandalus borealis

Introduction

Genetic variation underlies the populations’ potential to adapt to and persist in a changing environment, while phenotypic plasticity can play a key role in buffering the negative impacts of such change at the individual level.

Methods

We investigated the role of genetic variation in the thermal response of the northern shrimp Pandalus borealis, an ectotherm species distributed in the Arctic and North Atlantic Oceans. More specifically, we estimated the proportion transcriptomic responses explained by genetic variance of female shrimp from three origins after 30 days of exposure to three temperature treatments.

Results

We characterized the P. borealis transcriptome (170,377 transcripts, of which 27.48% were functionally annotated) and then detected a total of 1,607 and 907 differentially expressed transcripts between temperatures and origins, respectively. Shrimp from different origins displayed high but similar level of transcriptomic plasticity in response to elevated temperatures. Differences in transcript expression among origins were not correlated to population genetic differentiation or diversity but to environmental conditions at origin during sampling.

Discussion

The lack of genetic variation explaining thermal plasticity suggests limited adaptability in this species’ response to future environmental changes. These results together with higher mortality observed at the highest temperature indicate that the thermal niche of P. borealis will likely be restricted to higher latitudes in the future. This prediction concurs with current decreases in abundance observed at the southern edge of this species geographical distribution, as it is for other cold-adapted crustaceans.

Modeling present and future distribution of plankton populations in a coastal upwelling zone: the copepod Calanus chilensis as a study case

Predicting species distribution in the ocean has become a crucial task to assess marine ecosystem responses to ongoing climate change. In the Humboldt Current System (HCS), the endemic copepod Calanus chilensis is one of the key species bioindicator of productivity and water masses. Here we modeled the geographic distribution of Calanus chilensis for two bathymetric ranges, 0-200 and 200-400 m. For the 0-200 m layer, we used the Bayesian Additive Regression Trees (BART) method, whereas, for the 200-400 m layer, we used the Ensembles of Small Models (ESMs) method and then projected the models into two future scenarios to assess changes in geographic distribution patterns. The models were evaluated using the multi-metric approach. We identified that chlorophyll-a (0.34), Mixed Layer Depth (0.302) and salinity (0.36) explained the distribution of C. chilensis. The geographic prediction of the BART model revealed a continuous distribution from Ecuador to the southernmost area of South America for the 0-200 m depth range, whereas the ESM model indicated a discontinuous distribution with greater suitability for the coast of Chile for the 200-400 m depth range. A reduction of the distribution range of C. chilensis is projected in the future. Our study suggests that the distribution of C. chilensis is conditioned by productivity and mesoscale processes, with both processes closely related to upwelling intensity. These models serve as a tool for proposing indicators of changes in the ocean. We further propose that the species C. chilensis is a high productivity and low salinity indicator at the HCS. We recommend further examining multiple spatial and temporal scales for stronger inference.

MaxEnt modeling to show patterns of coastal habitats of reef-associated fish in the South and East China Seas

Reef-associated fish are a crucial source of protein for coastal residents and play an important role in the economy and ecology of marine ecosystems. However, human activities and climate change have led to the degradation of their habitats in the South China Sea (SCS) and East China Sea (ECS). This study models the potential habitats of reef-associated fish in the SCS and ECS between 1993 and 2019 using high-spatial-resolution environmental factors and fish presence data, estimates the importance of environmental factors on habitat distribution and identifies seasonal variation and distribution shifts over recent decades, the results show moderate and highly suitable areas for reef-associated fish in the region total 360,000 km2. Sea body temperature, chlorophyll-α concentration, and seawater salinity are crucial for determining the distribution of reef-associated fish. Moreover, reef-associated fish are also sensitive to seawater temperature in winter. Suitable areas for reef-associated fish near coastlines have decreased due to environmental changes within the region. The findings of this study offer valuable resource for developing fishery management and conservation strategies for this important functional group.

Ecological niche models applied to post-megafire vegetation restoration in the context of climate change

Climate change and land-use changes are the main drivers altering fire regimes and leading to the occurrence of megafires. Current management policies mainly focus on short-term restoration without considering how climate change might affect regeneration dynamics. We aimed to test the usefulness of ecological niche models (ENMs) to integrate the effects of climate change on tree species distributions into post-fire restoration planning. We also examined different important conceptual and methodological aspects during this novel process. We constructed ENM at fine spatial resolution (25 m) for the four main tree species (Pinus pinaster, Quercus pyrenaica, Q. faginea and Q. ilex) in an area affected by a megafire in Central Spain at two scales (local and regional), two periods (2 and 14 years after the fire) at the local scale, and under two future climate change scenarios. The usefulness of ENMs as support tools in decision-making for post-fire management was confirmed for the first time. As hypothesized, models developed at both scales are different, since they represent different scale dependent drivers of species distribution patterns. However, both provide objective information to be considered by stakeholders in combination with other sources of information. Local models generated with vegetation data 14 years after the fire provided valuable information about local and current vegetation dynamics (i.e., current microecology spatial niche prediction). Regional models are capable of considering a higher proportion of the climatic niche of species to generate reliable climate change forecasts (i.e., future macroclimate spatial niche forecast). The use of precise ENMs provide both an objective interpretation of potential habitat conditions and the opportunity of examining vegetation patches, that can be very valuable in managing restoration of areas affected by megafires under climate change conditions.

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.

Extensive range contraction predicted under climate warming for two endangered mountaintop frogs from the rainforests of subtropical Australia

Montane ecosystems cover approximately 20% of the Earth's terrestrial surface and are centres of endemism. Globally, anthropogenic climate change is driving population declines and local extinctions across multiple montane taxa, including amphibians. We applied the maximum entropy approach to predict the impacts of climate change on the distribution of two poorly known amphibian species (Philoria kundagungan and Philoria richmondensis) endemic to the subtropical uplands of the Gondwana Rainforests of Australia, World Heritage Area (GRAWHA). Firstly, under current climate conditions and also future (2055) low and high warming scenarios. We validated current distribution models against models developed using presence-absence field data. Our models were highly concordant with known distributions and predicted the current distribution of P. kundagungan to contract by 64% under the low warming scenario and by 91% under the high warming scenario and that P. richmondensis would contract by 50% and 85%, respectively. With large areas of habitat already impacted by wildfires, conservation efforts for both these species need to be initiated urgently. We propose several options, including establishing ex-situ insurance populations increasing the long-term viability of both species in the wild through conservation translocations.

High vulnerability and a big conservation gap: Mapping the vulnerability of coastal scleractinian corals in South China

Scleractinian corals build the most complex and diverse ecosystems in the ocean with various ecosystem services, yet continue to be degraded by natural and anthropogenic stressors. Despite the rapid decline in scleractinian coral habitats in South China, they are among the least concerning in global coral vulnerability maps. This study developed a rapid assessment approach that combines vulnerability components and species distribution models to map coral vulnerability within a large region based on limited data. The approach contained three aspects including, exposure, habitat suitability, and coral-conservation-based adaptive capacity. The exposure assessment was based on seven indicators, and the habitat suitability was mapped using Maximum Entropy and Random Forest models. Vulnerability of scleractinian corals in South China was spatially evaluated using the approach developed here. The results showed that the average exposure of the study region was 0.62, indicating relatively high pressure. The highest exposure occurred from the east coast of the Leizhou Peninsula to the Pearl River Estuary. Aquaculture and shipping were the most common causes of exposure. Highly suitable habitats for scleractinian corals are concentrated between 18°N-22°N. Only 21.6 % of the potential coral habitats are included in marine protected areas, indicating that there may still be large conservation gaps for scleractinian corals in China. In total, 37.7 % of the potential coral habitats were highly vulnerable, with the highest vulnerability appearing in the Guangdong Province. This study presents the first attempt to map the vulnerability of scleractinian corals along the coast of South China. The proposed approach and findings provide an essential tool and information supporting the sustainable management and conservation of coral reef ecosystems, addressing an important gap on the world's coral reef vulnerability map.

Mapping the Distribution and Dispersal Risks of the Alien Invasive Plant Ageratina adenophora in China

Identifying the distribution dynamics of invasive alien species can help in the early detection of and rapid response to these invasive species in newly invaded sites. Ageratina adenophora, a worldwide invasive plant, has spread rapidly since its invasion in China in the 1940s, causing serious damage to the local socioeconomic and ecological environment. To better control the spread of this invasive plant, we used the MaxEnt model and ArcGIS based on field survey data and online databases to simulate and predict the spatial and temporal distribution patterns and risk areas for the spread of this species in China, and thus examined the key factors responsible for this weed’s spread. The results showed that the risk areas for the invasion of A. adenophora in the current period were 18.394° N–33.653° N and 91.099° E–121.756° E, mainly in the tropical and subtropical regions of China, and densely distributed along rivers and well-developed roads. The high-risk areas are mainly located in the basins of the Lancang, Jinsha, Yalong, and Anning Rivers. With global climate change, the trend of continued invasion of A. adenophora is more evident, with further expansion of the dispersal zone towards the northeast and coastal areas in all climatic scenarios, and a slight contraction in the Yunnan–Guizhou plateau. Temperature, precipitation, altitude, and human activity are key factors in shaping the distribution pattern of A. adenophora. This weed prefers to grow in warm and precipitation-rich environments such as plains, hills, and mountains; in addition, increasing human activities provide more opportunities for its invasion, and well-developed water systems and roads can facilitate its spread. Measures should be taken to prevent its spread into these risk areas.

Phenomenology and dynamics of competitive ecosystems beyond the niche-neutral regimes

Structure, composition, and stability of ecological populations are shaped by the inter- and intraspecies interactions within their communities. It remains to be fully understood how the interplay of these interactions with other factors, such as immigration, controls the structure, the diversity, and the long-term stability of ecological systems in the presence of noise and fluctuations. We address this problem using a minimal model of interacting multispecies ecological communities that incorporates competition, immigration, and demographic noise. We find that a complete phase diagram exhibits rich behavior with multiple regimes that go beyond the classical "niche" and "neutral" regimes, extending and modifying the "rare biosphere" or "niche-like" dichotomy. In particular, we observe regimes that cannot be characterized as either niche or neutral where a multimodal species abundance distribution is observed. We characterize the transitions between the different regimes and show how these arise from the underlying kinetics of the species turnover, extinction, and invasion. Our model serves as a minimal null model of noisy competitive ecological systems, against which more complex models that include factors such as mutations and environmental noise can be compared.

How could climate change influence the distribution of the black soldier fly, Hermetiaillucens (Linnaeus) (Diptera, Stratiomyidae)?

The black soldier fly, Hermetiaillucens (Linnaeus, 1758), is a saprophagous species used to decompose organic matter. This study proposes a distribution model of H.illucens to illustrate its current and future distribution. The methodology includes data collection from the Global Biodiversity Information Facility (GBIF), complemented with iNaturalist, manual expert curation of occurrence records, six species distribution models algorithms and one ensemble model. The average temperature of the driest annual quarter and the precipitation of the coldest annual quarter were the key variables influencing the potential distribution of H.illucens. The distribution range is estimated to decrease progressively and their suitable habitats could change dramatically in the future due to global warming. On the other hand, current optimal habitats would become uninhabitable for the species, mainly at low latitudes. Under this scenario, the species is projected to move to higher latitudes and elevations in the future. The results of this study provide data on the distribution of H.illucens, facilitating its location, management and sustainable use in current and future scenarios.

Assessing the Effectiveness of Correlative Ecological Niche Model Temporal Projection through Floristic Data

Simple Summary

Climate change is the main threat for conservation in the 21st century. Reliable methodologies and tools for the evaluation of its impact are urgently needed. Correlative ecological niche models (ENMs) are effective tools for predicting the future distribution of species under climate change scenarios. Despite this, many alternative different methods have been proposed, and objective reasons for a proper selection are unclear. Therefore, a comparative study to evaluate the consistency of predictions of the main ENM algorithms was performed. To test the effectiveness of correlative ENM temporal projection, we compared predictions generated using historical data and projected to the modern climate with predictions generated using modern distribution and climate data. In total, 600 case studies were generated, by using 25 Italian endemic plant species, 12 algorithms and 2 alternative sets of environmental variables. As a result, we highlighted the similarity of eight algorithms and the poor performance of four.

Abstract

Correlative ecological niche modelling (ENM) is a method widely used to study the geographic distribution of species. In recent decades, it has become a leading approach for evaluating the most likely impacts of changing climate. When used to predict future distributions, ENM applications involve transferring models calibrated with modern environmental data to future conditions, usually derived from Global Climate Models (GCMs). The number of algorithms and software packages available to estimate distributions is quite high. To experimentally assess the effectiveness of correlative ENM temporal projection, we evaluated the transferability of models produced using 12 different algorithms on historical and modern data. In particular, we compared predictions generated using historical data and projected to the modern climate (simulating a “future” condition) with predictions generated using modern distribution and climate data. The models produced with the 12 ENM algorithms were evaluated in geographic (range size and coherence of predictions) and environmental space (Schoener’s D index). None of the algorithms shows an overall superior capability to correctly predict future distributions. On the contrary, a few algorithms revealed an inadequate predictive ability. Finally, we provide hints that can be used as guideline to plan further studies based on the adopted general workflow, useful for all studies involving future projections.

Mediterranean Sea shelters for the gold coral Savalia savaglia (Bertoloni, 1819): An assessment of potential distribution of a rare parasitic species

Savalia savaglia is an ecosystem engineer listed as Near-Threatened by the IUCN, even though effective management and proper monitoring efforts to assess its distribution is still lacking. The record of large, long-established colonies can indicate the occurrence of areas with limited human local pressure. These areas may be considered as proxies for the creation of baselines of reference useful to design restoration strategies. The aim of this work was to update the distribution of S. savaglia Mediterranean populations to develop an Ecological Niche Model, highlighting potential areas for future monitoring programs. Occurrence data were collected and harmonized into a single dataset using the scientific literature and validated observations to feed a presence-only MaxEnt model, obtaining a basin-level potential distribution of the species. The results of our study can support decision-makers in marine spatial planning measures including the preservation of mesophotic environments and prioritizing areas for conservation.

Arctic marine forest distribution models showcase potentially severe habitat losses for cryophilic species under climate change

The Arctic is among the fastest-warming areas of the globe. Understanding the impact of climate change on foundational Arctic marine species is needed to provide insight on ecological resilience at high latitudes. Marine forests, the underwater seascapes formed by seaweeds, are predicted to expand their ranges further north in the Arctic in a warmer climate. Here, we investigated whether northern habitat gains will compensate for losses at the southern range edge by modelling marine forest distributions according to three distribution categories: cryophilic (species restricted to the Arctic environment), cryotolerant (species with broad environmental preferences inclusive but not limited to the Arctic environment), and cryophobic (species restricted to temperate conditions) marine forests. Using stacked MaxEnt models, we predicted the current extent of suitable habitat for contemporary and future marine forests under Representative Concentration Pathway Scenarios of increasing emissions (2.6, 4.5, 6.0, and 8.5). Our analyses indicate that cryophilic marine forests are already ubiquitous in the north, and thus cannot expand their range under climate change, resulting in an overall loss of habitat due to severe southern range contractions. The extent of marine forests within the Arctic basin, however, is predicted to remain largely stable under climate change with notable exceptions in some areas, particularly in the Canadian Archipelago. Succession may occur where cryophilic and cryotolerant species are extirpated at their southern range edge, resulting in ecosystem shifts towards temperate regimes at mid to high latitudes, though many aspects of these shifts, such as total biomass and depth range, remain to be field validated. Our results provide the first global synthesis of predicted changes to pan-Arctic coastal marine forest ecosystems under climate change and suggest ecosystem transitions are unavoidable now for some areas.