Building use-inspired species distribution models: Using multiple data types to examine and improve model performance.

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery dependent (conventional mark-recapture tags, fisheries observer records) and two fishery independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage the strengths of individual data types while statistically accounting for limitations, such as sampling biases.

Selection of planning unit size in dynamic management strategies to reduce human-wildlife conflict.

Conservation planning traditionally relies upon static reserves; however, there is increasing emphasis on dynamic management (DM) strategies that are flexible in space and time. Due to its novelty, DM lacks best practices to guide design and implementation. We assessed the effect of planning unit size in a DM tool designed to reduce entanglement of protected whales in vertical ropes of surface buoys attached to crab traps in the lucrative U.S. Dungeness crab (Metacarcinus magister) fishery. We conducted a retrospective analysis from 2009 to 2019 with modeled distributions of blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales and observed fisheries effort and revenue to evaluate the effect of 7 planning unit sizes on DM tool performance. We measured performance as avoided whale entanglement risk and protected fisheries revenue. Small planning units avoided up to $47 million of revenue loss and reduced entanglement risk by up to 25% compared to the large planning units currently in use by avoiding the incidental closure of areas with low biodiversity value and high fisheries revenue. However, large planning units were less affected by an unprecedented marine heat wave in 2014-2016 and by delays in information on the distributions of whales and the fishery. Our findings suggest that the choice of planning unit size will require decision-makers to navigate multiple socioecological considerations-rather than a one-size-fits-all approach-to separate wildlife from threats under a changing climate.

Selección del tamaño de la unidad de planeación en las estrategias dinámicas de manejo para reducir el conflicto humano-fauna Resumen La planeación de la conservación depende por tradición de las reservas estáticas; sin embargo, cada vez hay más énfasis en estrategias de manejo dinámico (MD) que son flexibles con el tiempo y el espacio. Ya que es novedoso, el MD carece de buenas prácticas que guíen el diseño y la implementación. Analizamos el efecto del tamaño de la unidad de planeación en una herramienta de MD diseñada para reducir el número de ballenas que se enredan en las cuerdas verticales de las boyas amarradas a las trampas para cangrejos de la pesquería lucrativa del cangrejo Dungeness (Metacarcinus magister) en los Estados Unidos. Realizamos un análisis retrospectivo de 2009 a 2019 con modelos de distribución de la ballena azul (Balaenoptera musculus) y la ballena jorobada (Megaptera novaeangliae) y observamos los esfuerzos y ganancias de la pesquería para evaluar el efecto del tamaño de siete unidades de planeación sobre el desempeño de una herramienta de MD. Medimos el desempeño como el riesgo de enredamiento evitado y los ingresos protegidos de la pesquería. Las unidades pequeñas de planeación evitaron hasta $47 millones de ingresos perdidos y redujeron el riesgo de enredamiento hasta en 25% en comparación con las unidades grandes que se usan actualmente al evitar el cierre indirecto de áreas con un valor bajo de biodiversidad e ingresos elevados para la pesquería. Sin embargo, las unidades grandes de planeación estuvieron menos afectadas por una ola de calor marino sin precedentes entre 2014 y 2016 y por los retrasos en la información sobre la distribución de las ballenas y la pesquería. Nuestros hallazgos sugieren que la selección del tamaño de la unidad de planeación requerirá que el órgano decisorio navegue múltiples consideraciones socio-ecológicas-en lugar de un enfoque de un-tamaño-para-todos-para separar a la fauna de las amenazas bajo el clima cambiante.

A satellite-based mobile warning system to reduce interactions with an endangered species.

Earth-observing satellites are a major research tool for spatially explicit ecosystem nowcasting and forecasting. However, there are practical challenges when integrating satellite data into usable real-time products for stakeholders. The need of forecast immediacy and accuracy means that forecast systems must account for missing data and data latency while delivering a timely, accurate, and actionable product to stakeholders. This is especially true for species that have legal protection. Acipenser oxyrinchus oxyrinchus (Atlantic sturgeon) were listed under the United States Endangered Species Act in 2012, which triggered immediate management action to foster population recovery and increase conservation measures. Building upon an existing research occurrence model, we developed an Atlantic sturgeon forecast system in the Delaware Bay, USA. To overcome missing satellite data due to clouds and produce a 3-d forecast of ocean conditions, we implemented data interpolating empirical orthogonal functions (DINEOF) on daily observed satellite data. We applied the Atlantic sturgeon research model to the DINEOF output and found that it correctly predicted Atlantic sturgeon telemetry occurrences over 90% of the time within a 3-d forecast. A similar framework has been utilized to forecast harmful algal blooms, but to our knowledge, this is the first time a species distribution model has been applied to DINEOF gap-filled data to produce a forecast product for fishes. To implement this product into an applied management setting, we worked with state and federal organizations to develop real-time and forecasted risk maps in the Delaware River Estuary for both state-level managers and commercial fishers. An automated system creates and distributes these risk maps to subscribers' mobile devices, highlighting areas that should be avoided to reduce interactions. Additionally, an interactive web interface allows users to plot historic, current, future, and climatological risk maps as well as the underlying model output of Atlantic sturgeon occurrence. The mobile system and web tool provide both stakeholders and managers real-time access to estimated occurrences of Atlantic sturgeon, enabling conservation planning and informing fisher behavior to reduce interactions with this endangered species while minimizing impacts to fisheries and other projects.

Decision-support tools for dynamic management.

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers. Article impact statement: Marxan can function as a decision-support tool for dynamic management scenarios in which boundaries are flexible in space and time.

Herramientas de Apoyo para la Toma de Decisiones en el Manejo Dinámico Resumen El manejo espacial es una estrategia valiosa para llevar hacia adelante los objetivos regionales para la conservación de la naturaleza, el desarrollo económico y la salud humana. Uno de los retos del manejo espacial es la navegación a través de la priorización de múltiples caracteres. Este reto se vuelve más pronunciado dentro de los escenarios de manejo dinámico, en los cuales los límites son flexibles en el tiempo y en el espacio como respuesta a las cambiantes condiciones biológicas, ambientales o socioeconómicas. Para implementar el manejo dinámico, se necesitan herramientas de apoyo para la toma de decisiones para guiar a la priorización espacial conforme la distribución de los caracteres se modifica bajo condiciones cambiantes. Marxan es una herramienta de apoyo para la toma de decisiones utilizada ampliamente y diseñada para escenarios de manejo estático, pero su utilidad para el manejo dinámico no ha sido evaluada. EcoCast es una nueva herramienta de apoyo para la toma de decisiones desarrollada explícitamente para el manejo dinámico de múltiples caracteres, pero carece de algunas funcionalidades que tiene Marxan. Usamos un análisis de información retrospectiva para comparar la capacidad de estas dos herramientas para priorizar a cuatro especies marinas en un escenario de manejo dinámico con respecto a la sustentabilidad de las pesquerías. Configuramos exitosamente la herramienta Marxan para que operara dinámicamente con respecto a una escala diaria de tiempo y así se asemejara a EcoCast. La relación entre las soluciones de EcoCast y las distribuciones subyacentes de las especies fue más lineal y menos ruidosa, mientras que las soluciones de Marxan tuvieron un mayor contraste entre las aguas que eran buenas y aquellas que eran pobres para los peces. Ninguna de las dos herramientas de apoyo para la toma de decisiones tuvo un mejor desempeño que la otra; la pertinencia de cada una depende del propósito del manejo, la preferencia del administrador de los recursos y la capacidad tecnológica de quienes desarrollan la herramienta.

Projecting marine species range shifts from only temperature can mask climate vulnerability.

Climate change is causing range shifts in many marine species, with implications for biodiversity and fisheries. Previous research has mainly focused on how species' ranges will respond to changing ocean temperatures, without accounting for other environmental covariates that could affect future distribution patterns. Here, we integrate habitat suitability modeling approaches, a high-resolution global climate model projection, and detailed fishery-independent and -dependent faunal datasets from one of the most extensively monitored marine ecosystems-the U.S. Northeast Shelf. We project the responses of 125 species in this region to climate-driven changes in multiple oceanographic factors (e.g., ocean temperature, salinity, sea surface height) and seabed characteristics (i.e., rugosity and depth). Comparing model outputs based on ocean temperature and seabed characteristics to those that also incorporated salinity and sea surface height (proxies for primary productivity and ocean circulation features), we explored how an emphasis on ocean temperature in projecting species' range shifts can impact assessments of species' climate vulnerability. We found that multifactor habitat suitability models performed better in explaining and predicting species historical distribution patterns than temperature-based models. We also found that multifactor models provided more concerning assessments of species' future distribution patterns than temperature-based models, projecting that species' ranges will largely shift northward and become more contracted and fragmented over time. Our results suggest that using ocean temperature as a primary determinant of range shifts can significantly alter projections, masking species' climate vulnerability, and potentially forestalling proactive management.

Self-Directed Walk With Ease Workplace Wellness Program - Montana, 2015-2017.

Arthritis occurs in 27% of adults in Montana, among whom 50% have activity limitations, 16% have social participation restrictions, and 23% have severe joint pain attributable to arthritis (1). Physical activity is beneficial in managing arthritis symptoms and in preventing other chronic diseases (2). Walk With Ease is a 6-week evidence-based physical activity program recommended by CDC to increase physical activity and help improve arthritis symptoms (3). In 2015, Walk With Ease was added to an ongoing workplace wellness program for Montana state employees; the results for five outcomes (minutes spent walking, engaging in other physical activity [including swimming, bicycling, other aerobic equipment use, and other aerobic exercise], stretching, pain, and fatigue) were analyzed by the Montana Department of Public Health and Human Services and CDC. Outcomes at baseline (pretest), 6 weeks after the program (posttest), and 6 months later (follow-up) were analyzed by self-reported arthritis status at the time the participant enrolled in the program. Significant increases (p<0.05) in the mean number of minutes spent per week walking and engaging in other physical activity were observed among participants with and without arthritis at the 6-week posttest. Time spent stretching did not change significantly at posttest for either group. Mean pain levels among participants without arthritis increased significantly both at the 6-week posttest and 6-month follow-up; however, pain and fatigue decreased significantly at posttest and follow-up for participants with or without arthritis who began the program with moderate or severe pain and fatigue levels. The data from these analyses suggest that, as a component of a workplace wellness program, self-directed Walk With Ease might be effective in increasing physical activity not only among adults with arthritis, but also among persons without arthritis.

Unseen overlap between fishing vessels and top predators in the northeast Pacific.

Accurate assessments of human-wildlife risk associated with industrial fishing are critical for the conservation of marine top predators. Automatic Identification System (AIS) data provide a means of mapping fishing and estimating human-wildlife risk; however, risk can be obscured by gaps in the AIS record due to technical issues and intentional disabling. We assessed the extent to which unseen fishing vessel activity due to AIS gaps obscured estimates of overlap between fishing vessel activity and 14 marine predators including sharks, tunas, mammals, seabirds, and critically endangered leatherback turtles. Among vessels equipped with AIS in the northeast Pacific, up to 24% of total predator overlap with fishing vessel activity was unseen, and up to 36% was unseen for some individual species. Waters near 10°N had high unseen overlap with sharks yet low reported shark catch, revealing potential discrepancies in self-reported datasets. Accounting for unseen fishing vessel activity illuminates hidden human-wildlife risk, demonstrating challenges and solutions for transparent and sustainable marine fisheries.

Budget impact of the Walk With Ease program for knee osteoarthritis.

Objective: Walk With Ease (WWE) is an effective low-cost walking program. We estimated the budget impact of implementing WWE in persons with knee osteoarthritis (OA) as a measure of affordability that can inform payers' funding decisions. Methods: We estimated changes in two-year healthcare costs with and without WWE. We used the Osteoarthritis Policy (OAPol) Model to estimate per-person medical expenditures. We estimated total and per-member-per-month (PMPM) costs of funding WWE for a hypothetical insurance plan with 75,000 members under two conditions: 1) all individuals aged 45+ with knee OA eligible for WWE, and 2) inactive and insufficiently active individuals aged 45+ with knee OA eligible. In sensitivity analyses, we varied WWE cost and efficacy and considered productivity costs. Results: With eligibility unrestricted by activity level, implementing WWE results in an additional $1,002,408 to the insurance plan over two years ($0.56 PMPM). With eligibility restricted to inactive and insufficiently active individuals, funding WWE results in an additional $571,931 over two years ($0.32 PMPM). In sensitivity analyses, when per-person costs of $10 to $1000 were added with 10-50% decreases in failure rate (enhanced sustainability of WWE benefits), two-year budget impact varied from $242,684 to $6,985,674 with unrestricted eligibility and from -$43,194 (cost-saving) to $4,484,122 with restricted eligibility. Conclusion: Along with the cost-effectiveness of WWE at widely accepted willingness-to-pay thresholds, these results can inform payers in deciding to fund WWE. In the absence of accepted thresholds to define affordability, these results can assist in comparing the affordability of WWE with other behavioral interventions.

Ecological forecasts for marine resource management during climate extremes.

Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members. Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally.

Widespread habitat loss and redistribution of marine top predators in a changing ocean.

The Northwest Atlantic Ocean and Gulf of Mexico are among the fastest warming ocean regions, a trend that is expected to continue through this century with far-reaching implications for marine ecosystems. We examine the distribution of 12 highly migratory top predator species using predictive models and project expected habitat changes using downscaled climate models. Our models predict widespread losses of suitable habitat for most species, concurrent with substantial northward displacement of core habitats >500 km. These changes include up to >70% loss of suitable habitat area for some commercially and ecologically important species. We also identify predicted hot spots of multi-species habitat loss focused offshore of the U.S. Southeast and Mid-Atlantic coasts. For several species, the predicted changes are already underway, which are likely to have substantial impacts on the efficacy of static regulatory frameworks used to manage highly migratory species. The ongoing and projected effects of climate change highlight the urgent need to adaptively and proactively manage dynamic marine ecosystems.

Walk with ease for knee osteoarthritis: A cost-effectiveness analysis.

Objective: The Walk With Ease (WWE) program was developed by the Arthritis Foundation to help people with arthritis learn to exercise safely and improve arthritis symptoms. We sought to establish the value of the WWE program. Methods: We used the Osteoarthritis Policy (OAPol) Model, a widely published and validated computer simulation of knee osteoarthritis (OA), to assess the cost-effectiveness of WWE in knee OA. We derived model inputs using data from a workplace wellness initiative in Montana that offered WWE to state employees. Our primary outcomes were quality-adjusted life years (QALYs) and costs over a 2-year period, which we used to calculate the incremental cost-effectiveness ratio (ICER). The base case analysis was restricted to subjects who were inactive or insufficiently active (<180 â€‹min/week of PA) at baseline. We performed scenario and probabilistic sensitivity analyses to determine the impact of uncertainty in model parameters on our results. Results: In the base case analysis, adding WWE to usual care resulted in an ICER of $47,900/QALY. When the program was offered without preselection by baseline activity level, the ICER for WWE â€‹+ â€‹usual care was estimated at $83,400/QALY. Results of the probabilistic sensitivity analysis indicated that WWE offered to inactive or insufficiently active individuals has a 52% chance of having an ICER <$50,000/QALY. Conclusion: The WWE program offers good value for inactive/insufficiently active individuals. Payers may consider including such a program to increase physical activity in individuals with knee OA.

Impacts of marine heatwaves on top predator distributions are variable but predictable.

Marine heatwaves cause widespread environmental, biological, and socio-economic impacts, placing them at the forefront of 21st-century management challenges. However, heatwaves vary in intensity and evolution, and a paucity of information on how this variability impacts marine species limits our ability to proactively manage for these extreme events. Here, we model the effects of four recent heatwaves (2014, 2015, 2019, 2020) in the Northeastern Pacific on the distributions of 14 top predator species of ecological, cultural, and commercial importance. Predicted responses were highly variable across species and heatwaves, ranging from near total loss of habitat to a two-fold increase. Heatwaves rapidly altered political bio-geographies, with up to 10% of predicted habitat across all species shifting jurisdictions during individual heatwaves. The variability in predicted responses across species and heatwaves portends the need for novel management solutions that can rapidly respond to extreme climate events. As proof-of-concept, we developed an operational dynamic ocean management tool that predicts predator distributions and responses to extreme conditions in near real-time.

Association of UV Radiation Exposure, Diagnostic Scrutiny, and Melanoma Incidence in US Counties.

Importance: Although UV radiation exposure is the conventionally reported risk factor for cutaneous melanoma, an alternative exposure is diagnostic scrutiny: the more physicians look for and biopsy moles, the more melanoma they find. Objective: To assess the association of proxies for UV radiation exposure and diagnostic scrutiny with geographical patterns of melanoma incidence. Design, Setting, and Participants: This was a cross-sectional ecological analysis of the 727 continental US counties reporting to the Surveillance, Epidemiology, and End Results (SEER) Program (among a total of 3108 counties). Environmental data relevant to UV radiation exposure (from a variety of sources), Health Resources and Services Administration data relevant to diagnostic scrutiny, and SEER data on melanoma incidence among the non-Hispanic White population diagnosed with melanoma from 2012 through 2016 were combined. Data analysis was performed between January 2020 and July 2022. Exposures: Three UV radiation proxies (UV daily dose, cloud variability, and temperature variability) and 3 diagnostic scrutiny proxies (median household income, dermatologists, and primary care physician supply). Main Outcomes and Measures: Melanoma incidence (in situ and invasive cancers). Results: In total, 235 333 melanomas were diagnosed. Proxies for UV radiation exposure changed gradually across geography, while melanoma incidence and proxies for diagnostic scrutiny changed abruptly across contiguous counties. The UV daily dose, a variable the National Cancer Institute specifically developed for melanoma analyses, was uncorrelated with incidence (r = 0.03; P = .42). For context, smoking prevalence was highly correlated with lung cancer incidence in the same counties (r = 0.81; P < .001). Melanoma incidence was correlated with median household income (r = 0.43; P < .001). Counties with no dermatologists and shortages of primary care physicians had the lowest incidence, while counties amply supplied with both had the highest, despite having lower mean UV daily dose. There was little association between melanoma incidence and melanoma mortality (r = 0.09; P = .05), while the analogous association in lung cancer was strong (r = 0.96; P < .001). Conclusions and Relevance: In this cross-sectional ecological study, the current geographical pattern of melanoma incidence across US counties was less associated with proxies for UV radiation exposure and more so with proxies for diagnostic scrutiny. Incidence-the fundamental epidemiologic measure of disease frequency-now had little association with the feared outcome of melanoma: death.

Hot spots of unseen fishing vessels.

Illegal, unreported, and unregulated (IUU) fishing incurs an annual cost of up to US$25 billion in economic losses, results in substantial losses of aquatic life, and has been linked to human rights violations. Vessel tracking data from the automatic identification system (AIS) are powerful tools for combating IUU, yet AIS transponders can be disabled, reducing its efficacy as a surveillance tool. We present a global dataset of AIS disabling in commercial fisheries, which obscures up to 6% (>4.9 M hours) of vessel activity. Disabling hot spots were located near the exclusive economic zones (EEZs) of Argentina and West African nations and in the Northwest Pacific, all regions of IUU concern. Disabling was highest near transshipment hot spots and near EEZ boundaries, particularly contested ones. We also found links between disabling and location hiding from competitors and pirates. These inferences on where and why activities are obscured provide valuable information to improve fisheries management.

Determining the Composition of Resident and Transient Members of the Oyster Microbiome.

To better understand how complex microbial communities become assembled on eukaryotic hosts, it is essential to disentangle the balance between stochastic and deterministic processes that drive their assembly. Deterministic processes can create consistent patterns of microbiome membership that result in persistent resident communities, while stochastic processes can result in random fluctuation of microbiome members that are transient with regard to their association to the host. We sampled oyster reefs from six different populations across the east coast of the United States. At each site we collected gill tissues for microbial community analysis and additionally collected and shipped live oysters to Northeastern University where they were held in a common garden experiment. We then examined the microbiome shifts in gill tissues weekly for 6 weeks using 16S rRNA gene amplicon sequencing. We found a strong population-specific signal in the microbial community composition of field-sampled oysters. Surprisingly, the oysters sampled during the common garden experiment maintained compositionally distinct gill-associated microbial communities that reflected their wild population of origin, even after rearing them in a common garden for several weeks. This indicates that oyster gill-associated microbiota are predominantly composed of resident microbes specific to host population, rather than being a reflection of their immediate biotic and abiotic surroundings. However, certain bacterial taxa tended to appear more frequently on individuals from different populations than on individuals from the same population, indicating that there is a small portion of the gill microbiome that is transient and is readily exchanged with the environmental pool of microbes. Regardless, the majority of gill-associated microbes were resident members that were specific to each oyster population, suggesting that there are strong deterministic factors that govern a large portion of the gill microbiome. A small portion of the microbial communities, however, was transient and moved among oyster populations, indicating that stochastic assembly also contributes to the oyster gill microbiome. Our results are relevant to the oyster aquaculture industry and oyster conservation efforts because resident members of the oyster microbiome may represent microbes that are important to oyster health and some of these key members vary depending on oyster population.

Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models.

BACKGROUND: Habitat suitability models give insight into the ecological drivers of species distributions and are increasingly common in management and conservation planning. Telemetry data can be used in habitat models to describe where animals were present, however this requires the use of presence-only modeling approaches or the generation of 'pseudo-absences' to simulate locations where animals did not go. To highlight considerations for generating pseudo-absences for telemetry-based habitat models, we explored how different methods of pseudo-absence generation affect model performance across species' movement strategies, model types, and environments. METHODS: We built habitat models for marine and terrestrial case studies, Northeast Pacific blue whales (Balaenoptera musculus) and African elephants (Loxodonta africana). We tested four pseudo-absence generation methods commonly used in telemetry-based habitat models: (1) background sampling; (2) sampling within a buffer zone around presence locations; (3) correlated random walks beginning at the tag release location; (4) reverse correlated random walks beginning at the last tag location. Habitat models were built using generalised linear mixed models, generalised additive mixed models, and boosted regression trees. RESULTS: We found that the separation in environmental niche space between presences and pseudo-absences was the single most important driver of model explanatory power and predictive skill. This result was consistent across marine and terrestrial habitats, two species with vastly different movement syndromes, and three different model types. The best-performing pseudo-absence method depended on which created the greatest environmental separation: background sampling for blue whales and reverse correlated random walks for elephants. However, despite the fact that models with greater environmental separation performed better according to traditional predictive skill metrics, they did not always produce biologically realistic spatial predictions relative to known distributions. CONCLUSIONS: Habitat model performance may be positively biased in cases where pseudo-absences are sampled from environments that are dissimilar to presences. This emphasizes the need to carefully consider spatial extent of the sampling domain and environmental heterogeneity of pseudo-absence samples when developing habitat models, and highlights the importance of scrutinizing spatial predictions to ensure that habitat models are biologically realistic and fit for modeling objectives.

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees.

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991-2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.

A dynamic ocean management tool to reduce bycatch and support sustainable fisheries.

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.