Model‐based inference for estimating shifts in species distribution, area occupied and centre of gravity

Biological and environmental covariates of juvenile sockeye salmon distribution and abundance in the southeastern Bering Sea, 2002-2018

Climate change is altering the distribution and abundance of marine species, especially in Arctic and sub-Arctic regions. In the eastern Bering Sea, home of the world's largest run of sockeye salmon (Oncorhynchus nerka), juvenile sockeye salmon abundance has increased and their migration path shifted north with warming, 2002-2018. The reasons for these changes are poorly understood. For these sockeye salmon, we quantify environmental and biological covariate effects within spatio-temporal species distribution models. Spatio-temporally, with respect to juvenile sockeye salmon densities: (1) sea surface temperature had a nonlinear effect, (2) large copepod, Calanus, a minor prey item, had no effect, (3) age-0 pollock (Gadus chalcogrammus), a major prey item during warm years, had a positive linear effect, and (4) juvenile pink salmon (O. gorbuscha) had a positive linear effect. Temporally, annual biomass of juvenile sockeye salmon was nonlinearly related to sea temperature and positively related to age-0 pollock and juvenile pink salmon abundance. Results indicate that sockeye salmon distributed with and increased in abundance with increases in prey, and reached a threshold for optimal temperatures in the eastern Bering Sea. Changes in population dynamics and distribution of sockeye salmon in response to environmental variability have potential implications for projecting specific future food securities and management of fisheries in Arctic waters.

Decadal changes in biomass and distribution of key fisheries species on Newfoundland's Grand Banks

Canadian fisheries management has embraced the precautionary approach and the incorporation of ecosystem information into decision-making processes. Accurate estimation of fish stock biomass is crucial for ensuring sustainable exploitation of marine resources. Spatio-temporal models can provide improved indices of biomass as they capture spatial and temporal correlations in data and can account for environmental factors influencing biomass distributions. In this study, we developed a spatio-temporal generalized additive model (st-GAM) to investigate the relationships between bottom temperature, depth, and the biomass of three key fished species on The Grand Banks: snow crab (Chionoecetes opilio), yellowtail flounder (Limanda ferruginea), and Atlantic cod (Gadus morhua). Our findings revealed changes in the centre of gravity of Atlantic cod that could be related to a northern shift of the species within the Grand Banks or to a faster recovery of the 2J3KL stock. Atlantic cod also displayed hyperaggregation behaviour with the species showing a continuous distribution over the Grand Banks when biomass is high. These findings suggest a joint stock assessment between the 2J3KL and 3NO stocks would be advisable. However, barriers may need to be addressed to achieve collaboration between the two distinct regulatory bodies (i.e., DFO and NAFO) in charge of managing the stocks. Snow crab and yellowtail flounder centres of gravity have remained relatively constant over time. We also estimated novel indices of biomass, informed by environmental factors. Our study represents a step towards ecosystem-based fisheries management for the highly dynamic Grand Banks.

Interspecific behavioural interference and range dynamics: current insights and future directions

Novel biotic interactions in shifting communities play a key role in determining the ability of species' ranges to track suitable habitat. To date, the impact of biotic interactions on range dynamics have predominantly been studied in the context of interactions between different trophic levels or, to a lesser extent, exploitative competition between species of the same trophic level. Yet, both theory and a growing number of empirical studies show that interspecific behavioural interference, such as interspecific territorial and mating interactions, can slow down range expansions, preclude coexistence, or drive local extinction, even in the absence of resource competition. We conducted a systematic review of the current empirical research into the consequences of interspecific behavioural interference on range dynamics. Our findings demonstrate there is abundant evidence that behavioural interference by one species can impact the spatial distribution of another. Furthermore, we identify several gaps where more empirical work is needed to test predictions from theory robustly. Finally, we outline several avenues for future research, providing suggestions for how interspecific behavioural interference could be incorporated into existing scientific frameworks for understanding how biotic interactions influence range expansions, such as species distribution models, to build a stronger understanding of the potential consequences of behavioural interference on the outcome of future range dynamics.

Predatory walls may impair climate warming-associated population expansion

Climate change has a profound impact on species distribution and abundance globally, as well as local diversity, which affects ecosystem functioning. In particular, changes in population distribution and abundance may lead to changes in trophic interactions. Although species can often shift their spatial distribution when suitable habitats are available, it has been suggested that predator presence can be a constraint on climate-related distribution shifts. We test this using two well-studied and data-rich marine environments. Focusing on a pair of sympatric fishes, Atlantic haddock Melanogrammus aeglefinus and cod Gadus morhua, we study the effect of the presence and abundance of the latter on the former distribution. We found that the distribution of cod and increased abundance may limit the expansion of haddock to new areas and could consequently buffer ecosystem changes due to climate change. Though marine species may track the rate and direction of climate shifts, our results demonstrate that the presence of predators may limit their expansion to thermally suitable habitats. By integrating climatic and ecological data at scales that can resolve predator-prey relationships, this analysis demonstrates the usefulness of considering trophic interactions to gain a more comprehensive understanding and to mitigate the effects of climate change on species distributions.

The shadow model: how and why small choices in spatially explicit species distribution models affect predictions

The use of species distribution models (SDMs) has rapidly increased over the last decade, driven largely by increasing observational evidence of distributional shifts of terrestrial and aquatic populations. These models permit, for example, the quantification of range shifts, the estimation of species co-occurrence, and the association of habitat to species distribution and abundance. The increasing complexity of contemporary SDMs presents new challenges-as the choices among modeling options increase, it is essential to understand how these choices affect model outcomes. Using a combination of original analysis and literature review, we synthesize the effects of three common model choices in semi-parametric predictive process species distribution modeling: model structure, spatial extent of the data, and spatial scale of predictions. To illustrate the effects of these choices, we develop a case study centered around sablefish (Anoplopoma fimbria) distribution on the west coast of the USA. The three modeling choices represent decisions necessary in virtually all ecological applications of these methods, and are important because the consequences of these choices impact derived quantities of interest (e.g., estimates of population size and their management implications). Truncating the spatial extent of data near the observed range edge, or using a model that is misspecified in terms of covariates and spatial and spatiotemporal fields, led to bias in population biomass trends and mean distribution compared to estimates from models using the full dataset and appropriate model structure. In some cases, these suboptimal modeling decisions may be unavoidable, but understanding the tradeoffs of these choices and impacts on predictions is critical. We illustrate how seemingly small model choices, often made out of necessity or simplicity, can affect scientific advice informing management decisions-potentially leading to erroneous conclusions about changes in abundance or distribution and the precision of such estimates. For example, we show how incorrect decisions could cause overestimation of abundance, which could result in management advice resulting in overfishing. Based on these findings and literature gaps, we outline important frontiers in SDM development.

Spatiotemporal evolution law and driving force of mining city patterns

Urban transformation is an inevitable trend for mining cities to achieve sustainable development. Analyzing the spatiotemporal evolution laws and driving mechanisms of mining cities is necessary for providing a scientific basis for their transformation. In this study, Jixi was taken as an example, which is a typical mining city in China. Based on geographic information system, various mathematical statistical analysis methods were used to quantitatively analyze the evolution pattern of mining cities. In addition, the driving mechanisms of land expansion in mining cities were examined further. The results showed that (1) the urban land in the mining city is mainly distributed in low-lying areas, and land expansion mainly occurred in flat areas. (2) Based on the distribution of mineral resources, the land use pattern of mining cities was scattered; with steady economic development, the urban spatial pattern tends to be compact. (3) The spatial pattern of mining cities is affected by natural, economic, and policy factors. The results reveal the spatiotemporal evolution law and driving mechanism of the patterns in mining cities, thereby providing a scientific basis for the sustainable development planning and land management of mining cities.

Range edges of North American marine species are tracking temperature over decades

Understanding the dynamics of species range edges in the modern era is key to addressing fundamental biogeographic questions about abiotic and biotic drivers of species distributions. Range edges are where colonization and extirpation processes unfold, and so these dynamics are also important to understand for effective natural resource management and conservation. However, few studies to date have analyzed time series of range edge positions in the context of climate change, in part because range edges are difficult to detect. We first quantified positions for 165 range edges of marine fishes and invertebrates from three U.S. continental shelf regions using up to five decades of survey data and a spatiotemporal model to account for sampling and measurement variability. We then analyzed whether those range edges maintained their edge thermal niche-the temperatures found at the range edge position-over time. A large majority of range edges (88%) maintained either summer or winter temperature extremes at the range edge over the study period, and most maintained both (76%), although not all of those range edges shifted in space. However, we also found numerous range edges-particularly poleward edges and edges in the region that experienced the most warming-that did not shift at all, shifted further than predicted by temperature alone, or shifted opposite the direction expected, underscoring the multiplicity of factors that drive changes in range edge positions. This study suggests that range edges of temperate marine species have largely maintained the same edge thermal niche during periods of rapid change and provides a blueprint for testing whether and to what degree species range edges track temperature in general.

Thorson J. Are we ready to track climate-driven shifts in marine species across international boundaries? - A global survey of scientific bottom trawl data

Marine biota are redistributing at a rapid pace in response to climate change and shifting seascapes. While changes in fish populations and community structure threaten the sustainability of fisheries, our capacity to adapt by tracking and projecting marine species remains a challenge due to data discontinuities in biological observations, lack of data availability, and mismatch between data and real species distributions. To assess the extent of this challenge, we review the global status and accessibility of ongoing scientific bottom trawl surveys. In total, we gathered metadata for 283,925 samples from 95 surveys conducted regularly from 2001 to 2019. We identified that 59% of the metadata collected are not publicly available, highlighting that the availability of data is the most important challenge to assess species redistributions under global climate change. Given that the primary purpose of surveys is to provide independent data to inform stock assessment of commercially important populations, we further highlight that single surveys do not cover the full range of the main commercial demersal fish species. An average of 18 surveys is needed to cover at least 50% of species ranges, demonstrating the importance of combining multiple surveys to evaluate species range shifts. We assess the potential for combining surveys to track transboundary species redistributions and show that differences in sampling schemes and inconsistency in sampling can be overcome with spatio-temporal modeling to follow species density redistributions. In light of our global assessment, we establish a framework for improving the management and conservation of transboundary and migrating marine demersal species. We provide directions to improve data availability and encourage countries to share survey data, to assess species vulnerabilities, and to support management adaptation in a time of climate-driven ocean changes.

Spatio-temporal patterns in juvenile habitat for 13 groundfishes in the California Current Ecosystem

Identifying juvenile habitats is critical for understanding a species' ecology and for focusing spatial fishery management by defining references like essential fish habitat (EFH). Here, we used vector autoregressive spatio-temporal models (VAST) to delineate spatial and temporal patterns in juvenile density for 13 commercially important species of groundfishes off the US west coast. In particular, we identified hotspots with high juvenile density. Three qualitative patterns of distribution and abundance emerged. First, Dover sole Microstomus pacificus, Pacific grenadier Coryphaenoides acrolepis, shortspine thornyhead Sebastolobus alascanus, and splitnose rockfish Sebastes diploproa had distinct, spatially-limited hotspots that were spatially consistent through time. Next, Pacific hake Merluccius productus and darkblotched rockfish Sebastes crameri had distinct, spatially limited hotspots, but the location of these hotspots varied through time. Finally, arrowtooth flounder Atheresthes stomias, English sole Parophrys vetulus, sablefish Anoplopoma fimbria, Pacific grenadier Coryphaenoides acrolepis, lingcod Ophiodon elongatus, longspine thornyhead Sebastolobus altivelis, petrale sole Eopsetta jordani, and Pacific sanddab Citharichthys sordidus had large hotspots that spanned a broad latitudinal range. These habitats represent potential, if not likely, nursery areas, the location of which will inform spatial management.

Improving prediction of rare species' distribution from community data

Species distribution models (SDMs) have been increasingly used to predict the geographic distribution of a wide range of organisms; however, relatively fewer research efforts have concentrated on rare species despite their critical roles in biological conservation. The present study tested whether community data may improve modelling rare species by sharing information among common and rare ones. We chose six SDMs that treat community data in different ways, including two traditional single-species models (random forest and artificial neural network) and four joint species distribution models that incorporate species associations implicitly (multivariate random forest and multi-response artificial neural network) or explicitly (hierarchical modelling of species communities and generalized joint attribute model). In addition, we evaluated two approaches of data arrangement, species filtering and conditional prediction, to enhance the selected models. The model predictions were tested using cross validation based on empirical data collected from marine fisheries surveys, and the effects of community data were evaluated by comparing models for six selected rare species. The results demonstrated that the community data improved the predictions of rare species' distributions to certain extent but might also be unhelpful in some cases. The rare species could be appropriately predicted in terms of occurrence, whereas their abundance tended to be underestimated by most models. Species filtering and conditional predictions substantially benefited the predictive performances of multiple- and single-species models, respectively. We conclude that both the modelling algorithms and community data need to be carefully selected in order to deliver improvement in modelling rare species. The study highlights the opportunity and challenges to improve prediction of rare species' distribution by making the most of community data.

Climate-Driven Shifts in Marine Species Ranges: Scaling from Organisms to Communities

The geographic distributions of marine species are changing rapidly, with leading range edges following climate poleward, deeper, and in other directions and trailing range edges often contracting in similar directions. These shifts have their roots in fine-scale interactions between organisms and their environment-including mosaics and gradients of temperature and oxygen-mediated by physiology, behavior, evolution, dispersal, and species interactions. These shifts reassemble food webs and can have dramatic consequences. Compared with species on land, marine species are more sensitive to changing climate but have a greater capacity for colonization. These differences suggest that species cope with climate change at different spatial scales in the two realms and that range shifts across wide spatial scales are a key mechanism at sea. Additional research is needed to understand how processes interact to promote or constrain range shifts, how the dominant responses vary among species, and how the emergent communities of the future ocean will function.

Integrating spatial indicators in the surveillance of exploited marine ecosystems

Spatial indicators are used to quantify the state of species and ecosystem status, that is the impacts of climate and anthropogenic changes, as well as to comprehend species ecology. These metrics are thus, determinant to the stakeholder's decisions on the conservation measures to be implemented. A detailed review of the literature (55 papers) showed that 18 spatial indicators were commonly used in marine ecology. Those indicators were than characterized and studied in detail, based on its application to empirical data (a time series of 35 marine species spatial distributions, sampled either with a random stratified survey or a regular transects surveys). The results suggest that the indicators can be grouped into three classes, that summarize the way the individuals occupy space: occupancy (the area occupied by a species), aggregation (spreading or concentration of species biomass) and quantity dependent (indicators correlated with biomass), whether these are spatially explicit (include the geographic coordinates, e.g. center of gravity) or not. Indicator's temporal variability was lower than between species variability and no clear effect was observed in relation to sampling design. Species were then classified accordingly to their indicators. One indicator was selected from each of the three categories of indicators, to represent the main axes of species spatial behavior and to interpret them in terms of occupancy-aggregation-quantity relationships. All species considered were then classified according to their relationships among those three axes, into species that under increasing abundancy, primarily increase occupancy or aggregation or both. We suggest to use these relationships along the three-axes as surveillance diagrams to follow the yearly evolution of species distributional patterns in the future.

Seasonal dynamics of spatial distributions and overlap between Northeast Arctic cod (Gadus morhua) and capelin (Mallotus villosus) in the Barents Sea

The trophic link between cod (Gadus sp.) and capelin (Mallotus sp.) is important in many panarctic ecosystems. Since the early 2000s, the Northeast Arctic cod stock (G. morhua) in the Barents Sea has increased greatly, and the sea has been exceptionally warm. Such changes have potentially large effects on species distributions and overlap, which in turn could affect the strength of species interactions. Due to its high latitude location, the Barents Sea has strong seasonal variation in physical conditions and interactions. To study drivers of variation in cod-capelin overlap, we use data from two annual surveys run in winter and in autumn of 2004–2015. We first model winter and autumn spatial distributions of mature and immature cod and capelin. We then calculate overlap from model predictions on a grid with similar spatial resolution as the survey data. Our approach allowed us to interpret changes in overlap as species-specific effects of stock size and temperature, while accounting for sampling variation due to sampling time and depth. We found that during winter both species expanded their distribution in response to increased stock sizes, but how strongly and where the expansion occurred varied. The effect of temperature on distributions varied in space, and differed for cod and capelin and for different components of the two species. The results for autumn were clearer and more consistent. Both species expanded their distribution areas as their stock sizes increased. A positive effect of temperature was found in the north-eastern Barents Sea, where temperatures were lowest at the start of the study. Overlap increased and shifted north-eastwards during the study period and remained high despite a decline in the capelin stock. The increased overlap during autumn could mainly be attributed to the shift in cod distribution with increased cod stock biomass.

Signals of large scale climate drivers, hatchery enhancement, and marine factors in Yukon River Chinook salmon survival revealed with a Bayesian life history model

Understanding how species might respond to climate change involves disentangling the influence of co-occurring environmental factors on population dynamics, and is especially problematic for migratory species like Pacific salmon that move between ecosystems. To date, debate surrounding the causes of recent declines in Yukon River Chinook salmon (Oncorhynchus tshawytscha) abundance has centered on whether factors in freshwater or marine environments control variation in survival, and how these populations at the northern extremity of the species range will respond to climate change. To estimate the effect of factors in marine and freshwater environments on Chinook salmon survival, we constructed a stage-structured assessment model that incorporates the best available data, estimates incidental marine bycatch mortality in trawl fisheries, and uses Bayesian model selection methods to quantify support for alternative hypotheses. Models fitted to two index populations of Yukon River Chinook salmon indicate that processes in the nearshore and marine environments are the most important determinants of survival. Specifically, survival declines when ice leaves the Yukon River later in the spring, increases with wintertime temperature in the Bering Sea, and declines with the abundance of globally enhanced salmon species consistent with competition at sea. In addition, we found support for density-dependent survival limitations in freshwater but not marine portions of the life cycle, increasing average survival with ocean age, and age-specific selectivity of bycatch mortality in the Bering Sea. This study underscores the utility of flexible estimation models capable of fitting multiple data types and evaluating mortality from both natural and anthropogenic sources in multiple habitats. Overall, these analyses suggest that mortality at sea is the primary driver of population dynamics, yet under warming climate Chinook salmon populations at the northern extent of the species' range may be expected to fare better than southern populations, but are influenced by foreign salmon production.

Relative importance of population size, fishing pressure and temperature on the spatial distribution of nine Northwest Atlantic groundfish stocks

The spatial distribution of nine Northwest Atlantic groundfish stocks was documented using spatial indicators based on Northeast Fisheries Science Center spring and fall bottom trawl survey data, 1963–2016. We then evaluated the relative importance of population size, fishing pressure and bottom temperature on spatial distribution with an information theoretic approach. Northward movement in the spring was generally consistent with prior analyses, whereas changes in depth distribution and area occupancy were not. Only two stocks exhibited the same changes in spatiotemporal distribution in the fall as compared with the spring. Fishing pressure was the most important predictor of the center of gravity (i.e., bivariate mean location of the population) for the majority of stocks in the spring, whereas in the fall this was restricted to the east-west component. Fishing pressure was also the most important predictor of the dispersion around the center of gravity in both spring and fall. In contrast, biomass was the most important predictor of area occupancy for the majority of stocks in both seasons. The relative importance of bottom temperature was ranked highest in the fewest number of cases. This study shows that fishing pressure, in addition to the previously established role of climate, influences the spatial distribution of groundfish in the Northwest Atlantic. More broadly, this study is one of a small but growing body of literature to demonstrate that fishing pressure has an effect on the spatial distribution of marine resources. Future work must consider both fishing pressure and climate when examining mechanisms underlying fish distribution shifts.

Risks of ocean acidification in the California Current food web and fisheries: ecosystem model projections

The benefits and ecosystem services that humans derive from the oceans are threatened by numerous global change stressors, one of which is ocean acidification. Here, we describe the effects of ocean acidification on an upwelling system that already experiences inherently low pH conditions, the California Current. We used an end-to-end ecosystem model (Atlantis), forced by downscaled global climate models and informed by a meta-analysis of the pH sensitivities of local taxa, to investigate the direct and indirect effects of future pH on biomass and fisheries revenues. Our model projects a 0.2-unit drop in pH during the summer upwelling season from 2013 to 2063, which results in wide-ranging magnitudes of effects across guilds and functional groups. The most dramatic direct effects of future pH may be expected on epibenthic invertebrates (crabs, shrimps, benthic grazers, benthic detritivores, bivalves), and strong indirect effects expected on some demersal fish, sharks, and epibenthic invertebrates (Dungeness crab) because they consume species known to be sensitive to changing pH. The model's pelagic community, including marine mammals and seabirds, was much less influenced by future pH. Some functional groups were less affected to changing pH in the model than might be expected from experimental studies in the empirical literature due to high population productivity (e.g., copepods, pteropods). Model results suggest strong effects of reduced pH on nearshore state-managed invertebrate fisheries, but modest effects on the groundfish fishery because individual groundfish species exhibited diverse responses to changing pH. Our results provide a set of projections that generally support and build upon previous findings and set the stage for hypotheses to guide future modeling and experimental analysis on the effects of OA on marine ecosystems and fisheries.

Density-dependent changes in effective area occupied for sea-bottom-associated marine fishes

The spatial distribution of marine fishes can change for many reasons, including density-dependent distributional shifts. Previous studies show mixed support for either the proportional-density model (PDM; no relationship between abundance and area occupied, supported by ideal-free distribution theory) or the basin model (BM; positive abundance-area relationship, supported by density-dependent habitat selection theory). The BM implies that fishes move towards preferred habitat as the population declines. We estimate the average relationship using bottom trawl data for 92 fish species from six marine regions, to determine whether the BM or PDM provides a better description for sea-bottom-associated fishes. We fit a spatio-temporal model and estimate changes in effective area occupied and abundance, and combine results to estimate the average abundance-area relationship as well as variability among taxa and regions. The average relationship is weak but significant (0.6% increase in area for a 10% increase in abundance), whereas only a small proportion of species-region combinations show a negative relationship (i.e. shrinking area when abundance increases). Approximately one-third of combinations (34.6%) are predicted to increase in area more than 1% for every 10% increase in abundance. We therefore infer that population density generally changes faster than effective area occupied during abundance changes. Gadiformes have the strongest estimated relationship (average 1.0% area increase for every 10% abundance increase) followed by Pleuronectiformes and Scorpaeniformes, and the Eastern Bering Sea shows a strong relationship between abundance and area occupied relative to other regions. We conclude that the BM explains a small but important portion of spatial dynamics for sea-bottom-associated fishes, and that many individual populations merit cautious management during population declines, because a compressed range may increase the efficiency of harvest.