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The oceanographic conditions of the Southern California Bight (SCB) dictate the distribution and abundance of prey resources and therefore the presence of mobile predators, such as goose‐beaked whales (Ziphius cavirostris). Goose‐beaked whales are deep‐diving odontocetes that spend a majority of their time foraging at depth. Due to their cryptic behavior, little is known about how they respond to seasonal and interannual changes in their environment. This study utilizes passive acoustic data recorded from two sites within the SCB to explore the oceanographic conditions that goose‐beaked whales appear to favor. Utilizing optimum multiparameter analysis, modeled temperature and salinity data are used to identify and quantify these source waters: Pacific Subarctic Upper Water (PSUW), Pacific Equatorial Water (PEW), and Eastern North Pacific Central Water (ENPCW). The interannual and seasonal variability in goose‐beaked whale presence was related to the variability in El Niño Southern Oscillation events and the fraction and vertical distribution of the three source waters. Goose‐beaked whale acoustic presence was highest during the winter and spring and decreased during the late summer and early fall. These seasonal increases occurred at times of increased fractions of PEW in the California Undercurrent and decreased fractions of ENPCW in surface waters. Interannual increases in goose‐beaked whale presence occurred during El Niño events. These results establish a baseline understanding of the oceanographic characteristics that correlate with goose‐beaked whale presence in the SCB. Furthering our knowledge of this elusive species is key to understanding how anthropogenic activities impact goose‐beaked whales. [ABSTRACT FROM AUTHOR]

Abstract The oceanographic conditions of the Southern California Bight (SCB) dictate the distribution and abundance of prey resources and therefore the presence of mobile predators, such as goose‐beaked whales (Ziphius cavirostris). Goose‐beaked whales are deep‐diving odontocetes that spend a majority of their time foraging at depth. Due to their cryptic behavior, little is known about how they respond to seasonal and interannual changes in their environment. This study utilizes passive acoustic data recorded from two sites within the SCB to explore the oceanographic conditions that goose‐beaked whales appear to favor. Utilizing optimum multiparameter analysis, modeled temperature and salinity data are used to identify and quantify these source waters: Pacific Subarctic Upper Water (PSUW), Pacific Equatorial Water (PEW), and Eastern North Pacific Central Water (ENPCW). The interannual and seasonal variability in goose‐beaked whale presence was related to the variability in El Niño Southern Oscillation events and the fraction and vertical distribution of the three source waters. Goose‐beaked whale acoustic presence was highest during the winter and spring and decreased during the late summer and early fall. These seasonal increases occurred at times of increased fractions of PEW in the California Undercurrent and decreased fractions of ENPCW in surface waters. Interannual increases in goose‐beaked whale presence occurred during El Niño events. These results establish a baseline understanding of the oceanographic characteristics that correlate with goose‐beaked whale presence in the SCB. Furthering our knowledge of this elusive species is key to understanding how anthropogenic activities impact goose‐beaked whales.

Nesting events of loggerhead sea turtles (Caretta caretta) are on the rise in the Western Mediterranean Sea, far from their usual nesting areas in the Mediterranean and Atlantic basins. The study of dispersal behavior toward potential developmental areas of loggerhead post-hatchlings from this new nesting area is crucial to comprehend this colonization process and determining grounded conservation strategies. To fill this gap, we investigated, for the first time in the Mediterranean Sea, the dispersal strategies and habitat use based on data from 19 head-started loggerhead post-hatchlings released from the Spanish Mediterranean coast and satellite-tracked between 2016 and 2018. Turtles dispersed over large areas and showed active swimming phases, as they frequently dispersed against sea currents. Dispersal routes varied for each individual, although they consistently dispersed south-eastwards, especially during the coldest periods. Several post-hatchlings traveled through the Sicilian Channel to reach deep and warmer areas in the eastern Mediterranean basin. The most year-round suitable areas corresponded to the Ionian and Levantine Seas, which correspond with those found in their traditional nesting areas. Therefore, conservation measures focused on this stage should be taken in the path toward and these developmental areas. [ABSTRACT FROM AUTHOR]

Since the late 1970s the international ICES mackerel egg survey takes place in the Northeast Atlantic to obtain an estimate of total annual egg production (TAEP), to assess the spawning stock biomass and to support the sustainable management of the mackerel stock. However, its standard calculation of TAEP has some shortcomings: egg production is estimated from arithmetic averages of individual observations regardless whether they are extreme, rarely observed values, and has shown difficulties coping with the spatial expansion of mackerel spawning observed since 2007 (increasing the number of interpolated estimates). Various previous modeling efforts attempted to map the habitat of spawning mackerel to obtain more accurate egg production estimates by using generalized additive models (GAMs). In this study, we review and improve these models by introducing new features: We model both the western and southern components of the mackerel stock with a Tweedie distribution and test more than 400 model forms, including new predictors (like population size) and complex covariate interactions. We select the best model with various metrics, including the score of a tenfold cross validation. Our results show that environmental variables should be included in the model as simple functional, unimodal terms. This leads to a model that is more similar to a generalized linear mixed model than the typical GAM with smoothers. Models including only smoothers performed worse as they have a poor skill to extrapolate beyond the sampled region. Additionally, accounting for the effect of population size on the spatial distribution of eggs was shown to be fundamental to better model performance. [ABSTRACT FROM AUTHOR]

An ecohydraulic model system was developed to evaluate the effects of the Da‐Wei dam construction and possible fish restoration strategies. The ecohydraulic model system consists of a hydrodynamic model, a hydromorphology model, a habitat model, and the logistic and matrix population models. The effects of dam construction and fish stocking strategy on fish habitat and population status were studied in the Jiao‐Mu River, providing the modeled ecological status of Schizothorax prenanti and Schizothorax plagiostomus heckel populations within the river segment. The two fish species richness, fish age structures, and fish density distributions were predicted. Based on the fish number prediction, the optimal number of fish to stock was evaluated with the population models, and an optimal fish stocking proposition was worked out. The results indicated that the two fish species habitat quality and fish richness would decrease due to the hydropower dam construction, and the fish stocking strategy could make up the fish species ecological status. The findings could facilitate the quantity and quality assessment of a dam development plan and increase the success rate of fish restoration. [ABSTRACT FROM AUTHOR]

Context. Nursery areas provide refuge from predators, rich foraging grounds, and physical conditions conducive to growth and development of juvenile inhabitants. Specifically, the Mississippi Sound in the northern Gulf of Mexico is likely a nursery ground for multiple large and small coastal sharks. Aims and methods. Using over a decade of shark survey catch data, we employed habitat modelling approaches to identify preferred environmental conditions and spatial distribution, and quantify core habitat overlap within the Mississippi Sound for young-of-year (YOY), juvenile and adult life stages of four coastal shark species. Results. YOY Atlantic sharpnose (Rhizoprionodon terraenovae), blacktip (Carcharhinus limbatus) and finetooth (Carcharhinus isodon) sharks showed a preference for a combination of shallow, warm, low salinity, low dissolved oxygen and turbid waters. Corresponding to shared environmental preferences, spatial distributions of YOY sharks showed a high degree of overlap, particularly in the northern portion of the Mississippi Sound where few adult sharks were observed, suggesting that these life stages partition themselves to avoid predation. Conclusion and implications. With a continued rise in US coastal shark populations, we hope this study can help further refine essential fish habitat for these coastal species and provide a framework analysis that can be used to understand habitat partitioning in other regions. [ABSTRACT FROM AUTHOR]

Context. The construction of dams on the Chin-sha River will affect fish spawning sites, leading to a decline in fish species. Aims. This paper presents a model to evaluate the ecological status of restoration strategies aimed at fish species living at a spawning site. Methods. The model comprises hydro-morphodynamic and habitat modules. The modelling approach was applied with two restoration strategies (side-channel addition and riverbank reconstruction) and their corresponding post-restoration effects. Key results. Three indicators were utilised to assess the ecological status of the spawning site. Modelling results showed poor ecological status under current hydrological conditions, with weighted usable area and overall suitability index values of 1.07 x 106 m² and 0.41. Without implementing a restoration strategy, the ecological status would continue to fragment and deteriorate. Conclusions. Theweighted usable area can be recovered to 2.86 x 10[sup 6] and 1.67 x 106 m² in scenarios of side-channel and bank construction respectively. The overall suitability index values increase to 0.67 and 0.63 respectively. Implications. It is also noted that the ecological restoration strategy (side-channel addition) can considerably enhance the freshwater Reeves shad's habitat status. Additionally, the restoration strategy illustrated the feasibility of the side-channel addition restoration strategy. [ABSTRACT FROM AUTHOR]

Beaver management requires understanding beaver habitat preferences. Despite the American beaver (Castor canadensis Kuhl, 1820) being relatively common in the upper Midwest region of the United States, there are no beaver habitat relationship models based on this area. We used 1735 colonization events from long-term monitoring data generated by the Chequamegon-Nicolet National Forest in northern Wisconsin, USA, to determine what geomorphological and biological factors were selected by beavers colonizing new sites. We developed and evaluated prediction performance for three colonization models: geomorphology factors only, geomorphology and vegetation factors, and a full colonization model based on geomorphology, vegetation, and availability of dispersing beavers. Overall, the geomorphology–vegetation–colonizer model was the best model, predicting actual colony locations better than the other two models. Spatially, the landscape open to beaver colonization was a mosaic of streams with suitable and unsuitable habitat. These models improve our understanding of how beaver site selection factors in the upper Midwest region differ from factors identified in the literature for the western and eastern United States. This information may be useful for land managers in this region seeking to spatially target resources for restoring northern forest landscapes such as the Chequamegon-Nicolet National Forest. [ABSTRACT FROM AUTHOR]

Global change has altered the nature of disturbance regimes, and megafire events are increasingly common. Megafires result in immediate changes to habitat available to terrestrial wildlife over broad landscapes, yet we know surprisingly little about how such changes shape space use of sensitive species in habitat that remains. Functional responses provide a framework for understanding and predicting changes in space use following habitat alteration, but no previous studies have assessed functional responses as a consequence of megafire. We studied space use and tested for functional responses in habitat use by breeding greater sage‐grouse (Centrocercus urophasianus) before and after landscape‐level changes induced by a >40,000 ha, high‐intensity megafire that burned sagebrush steppe in eastern Idaho, USA. We also incorporated functional responses into predictive resource selection functions (RSFs) to map breeding habitat before and after the fire. Megafire had strong effects on the distribution of available resources and resulted in context‐dependent habitat use that was heterogeneous across different components of habitat. We observed functional responses in the use and selection of a variety of resources (shrubs and herbaceous vegetation) for both nesting and brood rearing. Functional responses in the use of nesting habitat were influenced by the overarching effect of megafire on vegetation, whereas responses during brood rearing appeared to be driven by individual variation in available resources that were conditional on nest locations. Importantly, RSFs built using data collected prior to the burn also had poor transferability for predicting space use in a post‐megafire landscape. These results have strong implications for understanding and predicting how animals respond to a rapidly changing environment, given that increased severity, frequency, and extent of wildfire are consequences of global change with the capacity to reshape ecosystems. We therefore demonstrate a conceptual framework to better understand space use and aid habitat conservation for wildlife in a rapidly changing world. [ABSTRACT FROM AUTHOR]

Understanding species' associations with physical habitat conditions is a fundamental goal of ecology. For organisms that occupy lotic ecosystems, relationships to streamflow are of particular importance, but these associations are unstudied for most species. We tested the predictability of fish–microhabitat relationships in river shoals (shallow, rocky areas with relatively swift water flow) using a large data set from the Conasauga River in Georgia, USA. Our objective was to assess the consistency of species‐specific relationships with flow‐dependent variables (depth, velocity, Reynolds number and Froude number) while accounting for other microhabitat variables (e.g. vegetation). We used data from 8285 seine‐sets collected during late summer or autumn at 26 sites over 12 years to relate occurrence and counts of 22 fish species to habitat variables using generalised linear multiple regression models. Results showed that microhabitat models explained a substantial amount of the variation in counts for some species, although other species were poorly predicted. We classified 16 species as velocity specialists and nine species as depth specialists, with six species specialised for depth and velocity and three species classified as depth and velocity generalists. The variability in habitat associations that we observed suggests that species will be unevenly affected by anthropogenic activities that alter flows. [ABSTRACT FROM AUTHOR]

Long‐term browning has resulted in increases in dissolved organic carbon and reduced water clarity that have altered the vertical physical structure of many lake ecosystems. The primary responses include reduced ultraviolet (UV) penetration, warming surface waters, and decreased deepwater dissolved oxygen concentrations that interactively alter vertical habitat suitability for zooplankton.Over 3 decades, Daphnia populations have decreased in abundance and shallowed in their vertical distribution in temperate Lake Giles (Pennsylvania, USA). Using 3 decades of corresponding long‐term vertical profile data of UV radiation, water temperature, and dissolved oxygen, we modelled both the suitable vertical habitat and thermally optimal habitat for Daphnia to understand the potential role of habitat availability for their population dynamics.The vertical extent of suitable habitat increased over time primarily due to strong decreases in UV penetration. In contrast, thermally optimal habitat decreased due to strong increases in vertical thermal gradients that were especially strong in late summer.The vertical distribution of Daphnia became shallower over this time period and may be a response to lower UV exposure near the surface, but continued warming of surface waters and decreasing deepwater dissolved oxygen concentrations are likely to lead to a vertical habitat squeeze.The biological implications of long‐term browning require more attention due to the complex and important implications for population dynamics, species interactions, and food web structure in lakes. [ABSTRACT FROM AUTHOR]

The operation of a reservoir may change natural hydrological processes, thus affecting the habitat of aquatic organisms. However, the risks posed by reservoirs on aquatic organisms remain to be fully evaluated. In this study, a risk assessment model was established to assess the ecological risk of reservoir flow regulation based on the consequences of deviating from the environmental flow range of an aquatic habitat. We applied this model to the Three Gorges Reservoir by obtaining the risk time series of different aquatic habitats in the Yangtze River before and after the construction of the reservoir. The risk analysis results showed that when habitat discharge is above or below the appropriate range of environmental flows, the ecological risk increases. The Chinese sturgeon, four major Chinese carp species, and finless porpoise habitats were identified to be at low-flow risk, low-flow risk, and high-flow risk, respectively. We suggest that the habitat flows of Chinese sturgeon, four major Chinese carp species, and finless porpoise during the spawning period should not be less than 6,850, 7,000, and 13,500 m3/s, respectively. The results of this study could help river managers optimize reservoir operations to minimize risks and maximize ecological benefits. [ABSTRACT FROM AUTHOR]

Abstract Seafloor characteristics can help in the prediction of fish distribution, which is required for fisheries and conservation management. Despite this, only 5%–10% of the world's seafloor has been mapped at high resolution, as it is a time‐consuming and expensive process. Multibeam echo‐sounders (MBES) can produce high‐resolution bathymetry and a broad swath coverage of the seafloor, but require greater financial and technical resources for operation and data analysis than singlebeam echo‐sounders (SBES). In contrast, SBES provide comparatively limited spatial coverage, as only a single measurement is made from directly under the vessel. Thus, producing a continuous map requires interpolation to fill gaps between transects. This study assesses the performance of demersal fish species distribution models by comparing those derived from interpolated SBES data with full‐coverage MBES distribution models. A Random Forest classifier was used to model the distribution of Abalistes stellatus, Gymnocranius grandoculis, Lagocephalus sceleratus, Loxodon macrorhinus, Pristipomoides multidens, and Pristipomoides typus, with depth and depth derivatives (slope, aspect, standard deviation of depth, terrain ruggedness index, mean curvature, and topographic position index) as explanatory variables. The results indicated that distribution models for A. stellatus, G. grandoculis, L. sceleratus, and L. macrorhinus performed poorly for MBES and SBES data with area under the receiver operator curves (AUC) below 0.7. Consequently, the distribution of these species could not be predicted by seafloor characteristics produced from either echo‐sounder type. Distribution models for P. multidens and P. typus performed well for MBES and the SBES data with an AUC above 0.8. Depth was the most important variable explaining the distribution of P. multidens and P. typus in both MBES and SBES models. While further research is needed, this study shows that in resource‐limited scenarios, SBES can produce comparable results to MBES for use in demersal fish management and conservation.

The distribution of wide-ranging cetacean species often cross national or jurisdictional boundaries, which creates challenges for monitoring populations and managing anthropogenic impacts, especially if data are only available for a portion of the species’ range. Many species found off the U.S. West Coast are known to have continuous distributions into Mexican waters, with highly variable abundance within the U.S. portion of their range. This has contributed to annual variability in design-based abundance estimates from systematic shipboard surveys off the U.S. West Coast, particularly for the abundance of warm temperate species such as striped dolphin, Stenella coeruleoalba, which increases off California during warm-water conditions and decreases during cool-water conditions. Species distribution models (SDMs) can accurately describe shifts in cetacean distribution caused by changing environmental conditions, and are increasingly used for marine species management. However, until recently, data from waters off the Baja California peninsula, México, have not been available for modeling species ranges that span from Baja California to the U.S. West Coast. In this study, we combined data from 1992–2018 shipboard surveys to develop SDMs off the Pacific Coast of Baja California for ten taxonomically diverse cetaceans. We used a Generalized Additive Modeling framework to develop SDMs based on line-transect surveys and dynamic habitat variables from the Hybrid Coordinate Ocean Model (HYCOM). Models were developed for ten species: long- and short-beaked common dolphins (Delphinus delphis delphis and D. d. bairdii), Risso’s dolphin (Grampus griseus), Pacific white-sided dolphin (Lagenorhynchus obliquidens), striped dolphin, common bottlenose dolphin (Tursiops truncatus), sperm whale (Physeter macrocephalus), blue whale (Balaenoptera musculus), fin whale (B. physalus), and humpback whale (Megaptera novaeangliae). The SDMs provide the first fine-scale (approximately 9 x 9 km grid) estimates of average species density and abundance, including spatially-explicit measures of uncertainty, for waters off the Baja California peninsula. Results provide novel insights into cetacean ecology in this region as well as quantitative spatial data for the assessment and mitigation of anthropogenic impacts.

Worldwide, many productive rivers are dam‐regulated and rely on flow management strategies that must balance support of ecological processes with human water use. One component of evaluating this balance is to understand ecological consequences of alternative flow management strategies, which has often been accomplished by coupling population dynamics models with models that relate streamflow to habitat availability and quality. Numerous methods assign habitat availability to locations within a river basin: These include fine‐scale field‐measured values that are extrapolated to other locations within the basin having similar physical characteristics or equation‐driven values created by functions of model‐predicted values of physical characteristics. The array of options for creating habitat models is evolving rapidly as high‐resolution remote‐sensing data becomes more accessible and computational capacity improves. Our objective was to identify trade‐offs among approaches that assign habitat relationships to large rivers and to create a decision support tool to supplement choices of extent and granularity. Using a selection of case studies that represent a breadth of scales and diverse trade‐offs, we demonstrate the need for a transparent process of data evaluation and assessment to determine the appropriate fit for model scope or context that best supports management needs and recognize sources of uncertainty. The structured approach proposed here aims at improving future model development and refine population dynamics models that inform the management of rivers. [ABSTRACT FROM AUTHOR]

Seafloor characteristics can help in the prediction of fish distribution, which is required for fisheries and conservation management. Despite this, only 5%–10% of the world's seafloor has been mapped at high resolution, as it is a time‐consuming and expensive process. Multibeam echo‐sounders (MBES) can produce high‐resolution bathymetry and a broad swath coverage of the seafloor, but require greater financial and technical resources for operation and data analysis than singlebeam echo‐sounders (SBES). In contrast, SBES provide comparatively limited spatial coverage, as only a single measurement is made from directly under the vessel. Thus, producing a continuous map requires interpolation to fill gaps between transects. This study assesses the performance of demersal fish species distribution models by comparing those derived from interpolated SBES data with full‐coverage MBES distribution models. A Random Forest classifier was used to model the distribution of Abalistes stellatus, Gymnocranius grandoculis, Lagocephalus sceleratus, Loxodon macrorhinus, Pristipomoides multidens, and Pristipomoides typus, with depth and depth derivatives (slope, aspect, standard deviation of depth, terrain ruggedness index, mean curvature, and topographic position index) as explanatory variables. The results indicated that distribution models for A. stellatus, G. grandoculis, L. sceleratus, and L. macrorhinus performed poorly for MBES and SBES data with area under the receiver operator curves (AUC) below 0.7. Consequently, the distribution of these species could not be predicted by seafloor characteristics produced from either echo‐sounder type. Distribution models for P. multidens and P. typus performed well for MBES and the SBES data with an AUC above 0.8. Depth was the most important variable explaining the distribution of P. multidens and P. typus in both MBES and SBES models. While further research is needed, this study shows that in resource‐limited scenarios, SBES can produce comparable results to MBES for use in demersal fish management and conservation. [ABSTRACT FROM AUTHOR]

Understanding habitat use and reproductive biology of invasive species is essential to predicting invasions, designing early detection programs, and developing management plans. The rudd (Scardinius erythrophthalmus; Linnaeus, 1758) is an omnivorous fish native to Europe and western Asia that has been translocated to several countries in western Europe, New Zealand, North America, and Africa. However, little is known about early life history of rudd, particularly in invaded ecosystems, limiting our ability to predict invasions and create early detection and control programs. The upper Niagara River has the most abundant population of rudd in North America and has been the focus of several ecological investigations. Our study identified critical nursery habitats by determining which nearshore habitat factors were most strongly associated with presence of age-0 rudd. We found that emergent vegetation was the most important habitat characteristic associated with the presence of age-0 rudd. When emergent vegetation was not present, rudd were more likely to be present at sites with abundant submerged aquatic vegetation. Additionally, the odds of rudd presence decreased as distance to the nearest wetland increased. These findings can be used to create habitat-driven predictive models of rudd invasion and guide early detection programs for rudd outside their native range. [ABSTRACT FROM AUTHOR]

Understanding habitat use by remnant populations of imperiled species can inform conservation efforts. Arctic ground squirrels (AGS; Urocitellus parryii) occupy alpine and boreal forest habitats in southwestern Yukon, Canada, where populations have been monitored since the 1970s. While alpine populations have remained stable, those in the boreal forest collapsed in the late 1990s and have not recovered. Propelled by the region-wide decline of AGS at low-elevation sites, our purpose was to document site occupancy by remnant populations and to identify habitats that are a high priority for monitoring and have potential for conservation. Using walking transects, we surveyed 155 sites in eight study areas for presence of AGS. Model-averaged occupancy probability was 0.643 (SE = 0.066), and the associated detection probability was 0.835 (SE = 0.075). AGS occurrence was strongly related to increasing habitat openness and also positively influenced by anthropogenic habitat and neighborhood occupancy. The availability of open habitat patches and connectivity among colonies within the boreal forest are consequential for the persistence of low-elevation populations of AGS. These factors may be linked to predator avoidance. Shrubification in the boreal forest as a result of climate warming may reduce AGS ability to detect and avoid predators. Recognizing anthropogenic habitats in land-use planning, and managing potential conflicts with landowners, may be important for the persistence and recovery of AGS at the southern edge of their range. [ABSTRACT FROM AUTHOR]

Abstract 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.

Abstract Background Forest management affects the viability of forest grouse populations, causing alterations to habitat quality. At the regional level, common targets for wood harvesting and safeguarding of specific habitats are negotiated between various stakeholders. Analysing potential trade-offs between forest grouse habitats and wood production in the region could support resource-smart decision making. Methods In this paper, we compiled trade-off curves represented as production possibility frontiers demonstrating the relationship between forest grouse habitat area and wood removal, using a Finnish forestry dynamics model and the Finnish Multi-Source National Forest Inventory. For the modelling of forest grouse habitats, a landscape-level occurrence model based on nationwide wildlife triangle census data was used. Five alternative forest scenarios in terms of wood removal were compiled for two study areas in Finland representing two different landscape structures. Results and conclusions Results showed that impacts on forest grouse habitats were case-specific. In the southern study area, increasing the roundwood harvesting rate affected grouse habitats more strongly as forests were already fragmented for other land uses and became more spruce-dominated over time. If the maximum sustainable removal rate was implemented, predicted grouse habitat area was 55% less than in a no-removal scenario. In the eastern study area, a more heavily forested region, the decrease was far lower at 22%. Scenario results were also compared to levels of recorded (business as usual) wood removal and that envisaged by valid regional forestry programmes, and their sustainability in terms of grouse habitat area was discussed. The production possibility frontiers calculated in this study support the evaluation of the loss of suitable habitat caused by different wood harvesting rates, or vice versa, the economic cost of increasing habitat areas.

Germany is an EU member state and is thus obliged to monitor and protect its marine and coastal areas in the context of international treaties (e.g. EU Marine Strategy Framework Directive, EU Natura2000 directives, Trilateral Monitoring and Assessment Programme, OSPAR) to achieve the good environmental status (GES). Suitable indicators thus need to be developed to assess the status of relevant ecosystems. Intertidal bivalve beds belong to the most productive habitats in the shallow coastal waters of the Wadden Sea but are highly dynamic and difficult to monitor. Extensive benthos and sediment sampling are required to study their development and distribution. We therefore evaluated the suitability of herring gulls (Larus argentatus) as a bioindicator species for monitoring these habitats. As flexible and opportunistic top-predators, herring gulls prefer to forage on intertidal flats and feed on bivalves (Cerastoderma edule, Mytilus edulis, Ensis leei) and crustaceans, with intertidal habitats near the breeding colony preferred during the incubation period. We used state of the art tracking devices to analyse habitat selection by herring gulls, and assessed how this was driven by biotic and abiotic factors. We then designed a habitat model to predict the occurrence of intertidal bivalve beds for directed monitoring, based on GPS logger data from herring gulls and hydrodynamic data. Both methods showed high correlations of herring gull foraging patterns with bivalve biomass and inundation time, depending on the distance from the breeding colony. The movement patterns of herring gulls clearly mirrored intertidal bivalve distributions. These results showed that combining GPS-logger data for top-predators, such as birds, with environmental data has great potential for monitoring and assessing the GES. We propose that herring gulls may be used as an indicator to locate bivalve beds in the Wadden Sea and to detect changes in the food web.

Using the gridded fishery data to estimate the habitat preferences of bigeye tuna (Thunnusobesus) in the Indian Ocean is challenging, as it is still not clear what type of model is appropriate to make reliable habitat predictions. In this study, we tested two classes of habitat models: Generalized Additive Models (including Gaussian distribution GAM, Poisson distribution GAM, Negative Binomial distribution GAM, Tweedie class distribution GAM, and Zero‐inflated distribution GAM) and Maximum Entropy Model (MaxEnt) for forecasting the habitat of bigeye tuna in the Indian Ocean, using the 5°×5° monthly gridded fishery data from 2008 to 2015 provided by Indian Ocean Tuna Commission (IOTC) and the environmental factors (i.e., the vertical temperature, salinity, dissolved oxygen concentration, thermocline depth, vertical shear of ocean current, concentration of sea surface chlorophyll‐a (chl‐a), and the eddy kinetic energy (EKE)). We compared the models' fitting ability, predictive performance, predicted results, and the ecological interpretation within the models. The results showed (1) GAMs provided better model fit and predictive performance than MaxEnt; (2) GA‐GAM showed the best model fit performance by using the log transformation of the standardized CPUE as response variable; (3) TW‐GAM was suitable for predicting the habitat of adult bigeye tuna with the over‐dispersed fishery datasets. (4) Results suggested that the vertical temperature, dissolved oxygen concentration, and thermocline depth could be used as reliable predictors in forecasting the spatial‐temporal distribution of the adult bigeye tuna in the Indian Ocean. [ABSTRACT FROM AUTHOR]

Although it is still common in undisturbed tropical habitats, populations of yellow-throated marten (Martes flavigula) have continuously declined throughout their range, particularly in South Korea where the population has been designated as an endangered species. Despite their threatened status, the northeastern population of yellow-throated marten and their habitats are poorly studied, and limited information exists to aid recovery and conservation of this mesocarnivore. In this study, presence data of martens were analyzed using 23 raster datasets for MaxEnt and Biomapper modeling. We assessed resulting habitat models for yellow-throated marten in 773 of 10 × 10 km survey grids in South Korea using field sign and trail cameras in 2018 and 2019. With 2667 confirmed sightings of this species, we created the first distribution map of yellow-throated martens in South Korea. We then analyzed 13 environmental features related to marten occurrence using linear mixed-effects models. Our top models indicated that altitude, precipitation, seasonality, land cover, land price, rail, roads, tourism attractions, and traffic volume explained marten occurrence. Direct human activities were the most reliable indicators of disturbance rather than stationary features such as roads and buildings. Our results also suggest that yellow-throated martens can exist in areas of high human population density. The new ecological information we provide on the distribution and habitat relationships of yellow-throated martens in South Korea will be beneficial for management and conservation of this species in Southeast Asia. [ABSTRACT FROM AUTHOR]

Documenting the spatial distribution of high-quality habitat patches, the distributions of threats and protected areas, and the vulnerability of habitat patches to changes in environmental conditions is vital for conservation of rare species. Range-wide species distribution models were developed for Black Rails (Laterallus jamaicensis) to predict the distribution of high-quality habitat patches for breeding Eastern Black Rails (L. j. jamaicensis). Overlay analyses were conducted to quantify the distribution of habitat relative to human development and existing protected areas, as well as the vulnerability of the best habitat to future sea level rise. The amount of high-quality habitat varied among states (0.4-7.6% of area) and was relatively rare throughout the subspecies' range (3.3% of area). Human development was common but the amount varied spatially among states (2.2-15.3% of area). Higher-quality breeding habitat was more common on federal lands (9.4% of area) and protected areas (6.4% of area), yet 33-42% of the highest-quality habitat patches were vulnerable to sea level rise of 0.61-1.83 m. Our results imply that even though many of the highest-quality habitat patches may be less likely sites for development they are often vulnerable to rising seas, and thus maintenance of existing high-quality habitat patches may be difficult without management that takes into account the likelihood of future inundation. [ABSTRACT FROM AUTHOR]

Eurasian lynx (Lynx lynx) once inhabited almost the whole of the European continent. After facing nearly complete extinction about a century ago, they now form a more or less connected metapopulation with eleven broadscale populations and numerous isolated habitat patches throughout Europe. Increasing public interest and a favourable legislative status by the EU give rise to hope for the return of the felide to parts of Central and Western Europe, where it is currently absent. In this context, a solid understanding of the overall suitability of the European landscape for a well-connected lynx population is crucial. Therefore, this work is looking into the current situation as well as potential habitats, ease of movement between those habitats, and potential future distribution, with the main focus on broad-scale spatial patterns. In addition to existing populations, eight habitat clusters were identified across Europe, using a modelling approach, rooted in a rule-based assessment accompanied by least-cost path identification, generating possible movement corridors. Key findings include large areas of potential habitat, yet overall low connectivity, with lynx movement restricted by a lack of forest cover as well as human land use, including mainly linear barriers like highways and dense road networks. This situation provides a number of challenges and opportunities for national and international conservation: The results clearly indicate that for a recolonisation of many parts of the European landscape reintroduction measures are indispensable in many parts of Europe. They also offer a first step towards a general understanding of how large carnivores like the Eurasian lynx might exist within a landscape increasingly shaped by anthropogenic actions and land use. [ABSTRACT FROM AUTHOR]

Small petrels are the most abundant seabirds in the Southern Ocean. However, because they breed in burrows on remote and often densely vegetated islands, their colony sizes and conservation status remain poorly known. To estimate the abundance of these species on Bird Island in the Falkland archipelago, we systematically surveyed their breeding burrow density and occupancy across this near-pristine tussac (Poa flabellata)-covered island. By modelling burrow density as functions of topography and Sentinel 2 satellite-derived Normalised Difference Vegetation Index data, we inferred habitat associations and predicted burrow abundance of the commonest species—Thin-billed Prions (Pachyptila belcheri) and Wilson's Storm-petrels (Oceanites oceanicus). We estimate that there are 631,000 Thin-billed Prion burrows on the island (95% CI 496,000–904,000 burrows). Assuming that burrow occupancy lies between 12 and 97%, this equates to around 76,000–612,000 breeding pairs, making Bird Island the second or third largest P. belcheri colony in the world, holding approximately 3–27% of the species' breeding population. We estimate that 8200–9800 (95% CI 5,200–18,300 pairs) pairs of Wilson's Storm-petrels also breed on the island. Notably, the latter burrowed predominantly under and within tussac pedestals, whereas they are usually assumed to breed in rock cavities. Thin-billed Prions are declining in the Kerguelen archipelago, but their population trends in the Falklands are unknown. Given the wide confidence intervals around our own and other population estimates for these cryptic species, we recommend that their populations should be monitored regularly, at multiple sites. [ABSTRACT FROM AUTHOR]

Identification of species' Biologically Important Areas (BIAs) is fundamental to conservation planning and species distribution models (SDMs) are a powerful tool commonly used to do this. Presence‐only data are increasingly being used to develop SDMs to aid the conservation decision‐making process. The application of presence‐only SDMs for marine species' is particularly attractive due to often logistical and economic costs of obtaining systematic species' distribution data. However, robust model validation is important for conservation management applications that require accurate and reliable species' occurrence data (e.g., spatially explicit risk assessments). This is commonly done using a random subset of the data and less commonly with fully independent test data. Here, we apply a spatial block cross‐validation (CV) approach to validate a MaxEnt presence‐only model using independent presence/absence survey data for a highly mobile, marine species (humpback whale, Megaptera novaengliae) in the Great Barrier Reef (GBR). A MaxEnt model was developed using opportunistic whale sightings (2003–2007) and then used to identify areas differing in habitat suitability (low, medium, high) to conduct a systematic, line‐transect, aerial survey (2012) and derive a density surface model. A spatial block CV buffering strategy was used to validate the MaxEnt model, using the opportunistic sightings as training data and independent aerial survey sightings data as test data. Moderate performance measures indicate MaxEnt was reliable in identifying the distribution patterns of a mobile whale species on their breeding ground, indicated by areas of high density aligned to areas of high habitat suitability. Furthermore, we demonstrate that MaxEnt models can be useful and cost‐effective for designing a sampling scheme to undertake systematic surveys that significantly reduces sampling effort. In this study, higher quality information on whale reproductive class (calf vs. non‐calf groups) was obtained that the presence‐only data lacked, while sampling only 18% of the GBR World Heritage Area. The validation approach using fully independent data provides greater confidence in the MaxEnt model, which indicates significant overlap with the main breeding ground of humpback whales and the inner shipping route. This is important when evaluating presence‐only models within certain conservation management applications, such as spatial risk assessments. [ABSTRACT FROM AUTHOR]

Both trophic structure and biomass flow within marine food webs are influenced by the abiotic environment and anthropogenic stressors such as fishing. The abiotic environment has a large effect on species spatial distribution patterns and productivity and, consequently, spatial co-occurrence between predators and prey, while fishing alters species abundances and food-web structure. In order to disentangle the impacts of the abiotic environment and fishing in the Celtic Sea ecosystem, we developed a spatio-temporal trophic model, specifically an Ecopath with Ecosim with Ecospace model, for the period 1985–2016. In this model, particular attention was paid to the parameterization of the responses of all trophic levels to abiotic environmental changes. Satellite remote sensing data were employed to determine the spatial distribution and annual fluctuations of primary production (PP). Spatial and temporal changes in the habitat favorable for zooplankton were predicted with a novel ecological-niche approach using daily detection of productivity fronts from satellite ocean color. Finally, functional responses characterizing the effect of several abiotic environmental variables (including, among others, temperature, salinity and dissolved oxygen concentration, both at the surface and at the bottom) on fish species groups’ habitat suitability were produced from the predictions of statistical habitat models fitted to presence-absence data collected by multiple fisheries-independent surveys. The dynamic component of our model (Ecosim) was driven by time-series of fishing effort, PP, zooplankton habitat suitability and abiotic environmental variables, and was fitted to abundance and fisheries catch data. The spatial component of our model (Ecospace) was constructed, for specific years of the period 1985–2016 with contrasted abiotic environmental conditions, to predict the variable distribution of the biomass of all functional groups. We found that fishing was the main driver of observed ecosystem changes in the Celtic Sea over the period 1985–2016. However, the integration of the environmental variability into the model and the subsequent improvement of the fit of the dynamic Ecosim component highlighted (i) the control of the overall pelagic production by PP and (ii) the influence of temperature on the productivity of several trophic levels in the Celtic Sea, especially on trophic groups with warm and cold water affinities. In addition, Ecospace predictions indicated that the spatial distributions of commercial fish species may have substantially changed over the studied period. These spatial changes mainly appeared to be driven by temperature and may, therefore, largely impact future fisheries given the continuity of climatic changes.

Habitat modeling is one of the most common practices in ecology today, aimed at understanding complex associations between species and an array of environmental, bioclimatic, and anthropogenic factors. This review of studies of seven species of terrestrial bears (Ursidae) occupying four continents examines how habitat models have been employed, and the functionality of their predictions for management and conservation. Bear occurrence data have been obtained at the population level, as presence points (e.g., sign surveys or camera trapping), or as locations of individual radio-collared animals. Radio-collars provide greater insights into how bears interact with their environment and variability within populations; they are more commonly used in North America and Europe than in South America and Asia. Salient problematic issues apparent from this review included: biases in presence data; predictor variables being poor surrogates of actual behavioral drivers; predictor variables applied at a biologically inappropriate scale; and over-use of data repositories that tend to detach investigators from the species. In several cases, multiple models in the same area yielded different predictions; new presence data occurred outside the range of predicted suitable habitat; and future range projections, based on where bears presently exist, underestimated their adaptability. Findings here are likely relevant to other taxa.

Intense trapping of the critically endangered Yellow-crested Cockatoo (Cacatua sulphurea) for the international pet trade has devastated its populations across Indonesia such that populations of >100 individuals remain at only a handful of sites. We combined distance sampling with density surface modeling (DSM) to predict local densities and estimate total population size for one of these areas, Komodo Island, part of Komodo National Park (KNP) in Indonesia. We modeled local density based on topography (topographic wetness index) and habitat types (percentage of palm savanna and deciduous monsoon forest). Our population estimate of 1,113 (95% CI: 587–2,109) individuals on Komodo Island was considerably larger than previous conservative estimates. Our density surface maps showed cockatoos to be absent over much of the island, but present at high densities in wooded valleys. Coincidence between our DSM and a set of independent cockatoo observations was high (93%). Standardized annual counts by KNP staff in selected areas of the island showed increases in cockatoo records from <400 in 2011 to ∼650 in 2017. Taken together, our results indicate that KNP, alongside and indeed because of preserving its iconic Komodo dragons (Varanus komodoensis), is succeeding in protecting a significant population of Indonesia's rarest cockatoo species. To our knowledge this is the first time DSM has been applied to a critically endangered species. Our findings highlight the potential of DSM for locating abundance hotspots, identifying habitat associations, and estimating global population size in a range of threatened taxa, especially if independent datasets can be used to validate model predictions. LAY SUMMARY Yellow-crested Cockatoos are threatened by extinction due to illegal trapping for the pet trade. Komodo Island in Indonesia supports one of the largest remaining populations. The island is part of Komodo National Park, famous for its Komodo dragons. A 2006 survey indicated cockatoo numbers might have been declining. In contrast to previous surveys we sampled the whole island instead of focusing on coastal valleys, which are known to harbor the highest cockatoo densities. We used distance sampling and density surface modeling, which allowed us to estimate how many cockatoos remained undetected and to produce a map of predicted cockatoo densities. We estimate there are between 600 and 2,100 cockatoos on Komodo, most likely ∼1,100. Komodo National Park authorities also reported an increase in their annual counts of cockatoos from below 400 in 2011 to around 650 in 2017. Thus, the cockatoo population on Komodo Island is large and stable; Komodo National Park is successfully protecting its cockatoos. [ABSTRACT FROM AUTHOR]

The conservation and management of sharks requires appropriate information on their biological and habitat characteristics. Data needed for the conservation and management of two dominant demersal shark species in the East China Sea, the spurdogs (Squalus japonicus and Squalus brevirostris), are inadequate. To remedy this, we analysed biological, catch and abiotic data from bottom trawl surveys conducted in 2000–05 and 2008–14 from within the East China Sea. The precaudal length of male and female S. japonicus at 50% sexual maturity was 396.1 and 459.9 mm respectively, whereas for S. brevirostris it was 289.6 and 354.9 mm respectively. Prey overlap was high between species, with lanternfishes the most important prey. The fractional trophic level was 4.33 for S. japonicus and 4.31 for S. brevirostris. We estimated spurdog habitat using a generalised additive model. Depth affected the presence of both sharks, with latitude also affecting the presence of S. brevirostris. These two spurdog species were spatially segregated over the continental slope, and body-length and sex-ratio distributions suggested that there was a maturity-based segregation within and among species. The results of this study improve our understanding of the population dynamics of these spurdog species, their reproduction and diet, fundamental information required for their conservation and for improved fisheries management. Biological characteristics and habitat use of two data-deficient spurdog shark species, namely Squalus japonicus and Squalus brevirostris , are described from fishery-independent bottom trawl surveys. Prey overlap was high between species and estimated length at sexual maturity suggested that populations of either species have not declined. Body length and sex ratio distributions of these two spurdog species suggest that they segregate over the continental slope and that there was a maturity-based segregation. [ABSTRACT FROM AUTHOR]

The federally-threatened Preble's meadow jumping mouse (Zapus hudsonius preblei) occurs in riparian zones located along the foothills and plains in the Front Range of Colorado and Wyoming. Anthropogenic and natural disturbances have extensively modified Front Range riparian ecosystems affecting the location, quality, and connectivity of Z. h. preblei populations and habitat. Previous studies suggest that specific microhabitat conditions influence Z. h. preblei occurrence but no landscape-scale assessments have been conducted. To support conservation and management, we assessed Z. h. preblei habitat in Boulder County, Colorado by mapping riparian land cover composition, creating species distribution models (SDM), and evaluating connectivity between suitable habitat and known Z. h. preblei populations. The SDM identified 5381 ha of suitable Z. h. preblei habitat, compared with 252 ha of known Z. h. preblei occupied habitat. We found limited connections between Z. h. preblei populations in different watersheds, as urban development and large expanses of agricultural land disrupt connectivity. Our modeling approach yielded outcomes that are broadly relevant to understanding the distribution and management of geographically restricted species impacted by habitat loss and has provided insight into Z. h. preblei habitat and connectivity that cannot be gathered from field work alone. [ABSTRACT FROM AUTHOR]

The Kemp’s ridley sea turtle (Lepidochelys kempii) is the most endangered sea turtle species in the world, largely due to the limited geographic range of its nesting habitat. There has been limited research regarding the connection between beach geomorphology and Kemp’s ridley nesting patterns, but studies concerning other sea turtle species suggest that certain beach geomorphology variables, such as beach slope and width, influence nest site selection. This research attempts to address the literature gap by quantifying the terrestrial habitat variability of the Kemp’s ridley and investigating the connection between beach geomorphology characteristics and Kemp’s ridley nesting preferences on Padre Island, TX, United States. Geomorphology characteristics, such as beach width and slope, were extracted from lidar-derived digital elevation models and associated with Kemp’s nest coordinates and pseudo-absence points randomly created within the study area. Generalized linear models and random forest models were used to assess the significance of variables for nesting preferences. Kemp’s ridley nest presence was successfully modeled using beach geomorphology characteristics, and elevation, distance from shoreline, maximum dune slope, and average beach slope were the most important variables in the models. Kemp’s ridleys exhibit a preference for a limited range of the study area and avoid nesting on beaches with beach characteristics of extreme values. The results of this study include new information regarding Kemp’s ridley terrestrial habitat and nesting preferences that have many applications for species conservation and management.

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. [ABSTRACT FROM AUTHOR]

Background: Forest management affects the viability of forest grouse populations, causing alterations to habitat quality. At the regional level, common targets for wood harvesting and safeguarding of specific habitats are negotiated between various stakeholders. Analysing potential trade-offs between forest grouse habitats and wood production in the region could support resource-smart decision making. Methods: In this paper, we compiled trade-off curves represented as production possibility frontiers demonstrating the relationship between forest grouse habitat area and wood removal, using a Finnish forestry dynamics model and the Finnish Multi-Source National Forest Inventory. For the modelling of forest grouse habitats, a landscape-level occurrence model based on nationwide wildlife triangle census data was used. Five alternative forest scenarios in terms of wood removal were compiled for two study areas in Finland representing two different landscape structures. Results and conclusions: Results showed that impacts on forest grouse habitats were case-specific. In the southern study area, increasing the roundwood harvesting rate affected grouse habitats more strongly as forests were already fragmented for other land uses and became more spruce-dominated over time. If the maximum sustainable removal rate was implemented, predicted grouse habitat area was 55% less than in a no-removal scenario. In the eastern study area, a more heavily forested region, the decrease was far lower at 22%. Scenario results were also compared to levels of recorded (business as usual) wood removal and that envisaged by valid regional forestry programmes, and their sustainability in terms of grouse habitat area was discussed. The production possibility frontiers calculated in this study support the evaluation of the loss of suitable habitat caused by different wood harvesting rates, or vice versa, the economic cost of increasing habitat areas. [ABSTRACT FROM AUTHOR]

We investigated the effect of environmental conditions on Atlantic mackerel spawning habitat in the southern Gulf of St. Lawrence (sGSL). Based on generalized additive models, we (i) modelled the optimal spawning habitat of mackerel in the sGSL using daily egg production (DEP) in June, (ii) predicted known and new potential present spawning habitats in the GSL and the north‐west Atlantic, and (iii) assessed how they respond to future climate change. Our findings showed that both mackerel presence–absence and given‐presence DEP were associated with sea surface temperature (10–16.5°C), salinity above 31 and depth < 120 m. Adding zooplankton showed a marked effect on the DEP given‐presence compared to the presence–absence. Predictions of spawning habitats under present (1999–2012) and future scenario (2066–2085) conditions were estimated from the presence–absence model without zooplankton, using physical conditions of the BNAM. Under present conditions, our model predicted well the main spawning habitat in the sGSL and other known secondary spawning habitats in the northern GSL (nGSL), the western and southern Newfoundland, and the north‐west Atlantic coast. Under future conditions, our study suggests that spawning habitats in the sGSL and the nGSL would expand. Our results, therefore, suggest that mackerel could benefit from a warmer GSL, minimizing the potential for a northward migration of the stock due to decreasing suitability of the sGSL as its main spawning ground, and a new but spatially limited potential habitat in Newfoundland coasts. These results can be used to inform stock management and develop adaptive management plans in the context of climate change. [ABSTRACT FROM AUTHOR]

Aim: Predicting distributions is fundamental to ecology, yet hindered by spatially restricted sampling, scale‐dependent relationships and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi‐scale data and used it to develop range‐wide breeding‐season SDMs for 14 marsh bird species of concern. Location: USA. Methods: We built SDMs using data from range‐wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out‐of‐sample prediction, range‐wide sampling over broad conditions, multi‐scale analyses and scale optimization, and species‐specific detectability for a suite of wide‐ranging species. Results: Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban and hydrologic disturbances operating from local scales (100–500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at >1 scale. Five species showed evidence for continental‐scale range contraction during the study. Main conclusions: We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data‐driven, empirical SDMs built at the range‐wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine‐scale wetland vegetation missed important broadscale drivers of occupancy for marsh birds. [ABSTRACT FROM AUTHOR]

Wetlands are an ecologically important yet threatened plant community type in many natural areas. Inventory and monitoring are essential components of protecting, managing, and restoring wetland resources. However, many challenges currently exist for resource managers looking to perform a comprehensive inventory of wetlands throughout expansive, topographically complex, and/or remote natural areas. Here we present ongoing work in Great Smoky Mountains National Park (GRSM) that is addressing these challenges using spatial modeling to inform on-the-ground surveys. Wetland communities occur throughout GRSM at all elevations but tend to be relatively small and patchily distributed. While simple models based on low (<10%) slope are informative to wetland surveys at low elevations (<1067 m), such models become ineffective in steep topography at high elevations. To address this issue, we developed and implemented parkwide maximum entropy (Maxent) wetland habitat suitability models incorporating 24 environmental variables. Using these models to guide wetland survey efforts for three years, we identified and mapped 93 new wetland occurrences and more than doubled our previous high-elevation (≥1067 m) wetland inventory in roughly half the time. Maxent modeling is a relatively easy to use tool that can help resource managers plan, prioritize, and implement field inventories efficiently and effectively. We encourage natural areas managers to adopt similar spatial modeling approaches to guide the detection of unique, patchily distributed plant community types such as glades, barrens, balds, or rock outcrop communities. [ABSTRACT FROM AUTHOR]

Abstract Geographic distributions are a basic component of a species’ ecology, and predicting distributions is a fundamental task of conservation and resource management. Reliable prediction depends on identification of appropriate scales of effect for environmental data, and scale‐optimization techniques are thus desirable to identify optimal scales for predictor variables. Recent statistical developments have also advanced methods of model selection based explicitly on predictive ability, which differ from commonly used methods that regulate model structures via anticipated predictive performance. Such methods are beginning to permeate into species distribution models (SDMs), yet there remains no consensus methodology for developing optimally predictive multi‐scale SDMs when covariate data are collected over a range of scales. Thus, we compared the performance of common approaches for scale optimization and model selection in terms of their ability to produce optimally predictive multi‐scale Bayesian occupancy models for predicting a species distribution, using models of the breeding distribution for King Rails (Rallus elegans) as a case study. Our results demonstrate sizable gains in predictive performance for hierarchical occupancy models selected via their ability to predict out‐of‐sample data using the logarithmic scoring rule, as compared to models selected using information criteria (deviance information criteria [DIC] and Watanabe information criteria [WAIC]). Information criteria commonly selected individual covariates, as well as scales of effect for those covariates, with suboptimal predictive performance. Performance of models selected using the logarithmic scoring rule was also robust across the method of scale optimization, which was not true for models selected using DIC and WAIC. Thus, we demonstrate empirical benefits of study designs and statistical tools that enable covariate and scale selection based explicitly on predictive ability. Our results also imply that more careful consideration of what constitutes an optimal scale is warranted in many ecological applications, as the meaning of optimal is not independent of the technique used for scale selection.

Identifying and quantifying the major ecosystem processes that regulate recruitment strength of commercially and ecologically important fish species is a central goal of fisheries management research. In the Gulf of Alaska (GOA) five groundfish species are of particular interest: sablefish (Anoplopoma fimbria), Pacific cod (Gadus macrocephalus), walleye pollock (Gadus chalcogrammus), arrowtooth flounder (Atheresthes stomias), and Pacific ocean perch (Sebastes alutus). Habitat suitability models (HSM) were developed for the demersal early juvenile stage to inform survival to recruitment for these species, using catch data and seafloor habitat metrics with presence-only models. Regional-scale maps were produced that predict the probability of suitable habitat available in the GOA from settlement through residency in nursery areas. For example, the HSM for sablefish (150–399 mm) described suitable habitat as bathymetrically low-lying areas with low rocky structure within 25–300 m depth. In contrast, the HSM for Pacific ocean perch (50–200 mm) described suitable habitat as bathymetry rises with rocky structure present on north-south facing slopes within 85–270 m depth. These habitat covariates are useful to refine population estimates for North Pacific groundfish species and to inform life stage-specific definitions of Essential Fish Habitat. This application of MaxEnt models should be applicable for species with low occurrence of spatial data in other marine ecosystems globally. [ABSTRACT FROM AUTHOR]

A common approach to studying habitat use in cetaceans is to conduct line-transect surveys, to investigate their distribution. In developing countries, there are limited resources for data collection. One solution is to employ field surveys to collect a wide range of ecological and behavioural data, for which a haphazard sampling schedule is adopted, to optimize the cost–benefit ratio. As with line-transect surveys, the haphazard sampling may lead to spatial autocorrelation (SAC), an overlooked problem in ecology. Here, we investigated common bottlenose dolphins (Tursiops truncatus truncatus) habitat use on an upwelling area and tested an approach that can improve model-based inference on auto-correlated data. We collected data in Cabo Frio, Rio de Janeiro, photo-identified 429 individuals and compared the predictions and model coefficients of standard generalized linear model (GLM) without correcting for spatial autocorrelation with a spatial eigenvector generalized linear model (SEV-GLM) which compensates for SAC. Our best SEV-GLM predicted dolphins are more likely to occur on cold waters with increased chlorophyll concentration, indicating dolphins are influenced by the upwelling. Moreover, by correcting for SAC, our models had a better fit to data, magnified the relevance of significant variables and showed smaller and less clumped residuals than when not correcting. [ABSTRACT FROM AUTHOR]

Aim : Changes in abundance and shifts in distribution as a result of a warming climate have been documented for many marine species, but opportunities to test our ability to forecast such changes have been limited. This study evaluates the ability of habitat‐based density models to accurately forecast cetacean abundance and distribution during a novel year with unprecedented warm ocean temperatures caused by a sustained marine heatwave. Location : California Current Ecosystem, USA. Methods : We constructed generalized additive models based on cetacean sighting and environmental data from 1991 to 2009 for eight species with a diverse range of habitat associations. Models were built with three different sets of predictor variables to compare performance. Models were then used to forecast species abundance and distribution patterns during 2014, a year with anomalously warm ocean temperatures. Cetacean sighting data collected during 2014 were used to assess model forecasts. Results: Ratios of model‐predicted abundance to observed abundance were close to 1:1 for all but one species and accurately captured changes in the number of animals in the study area during the anomalous year. Predicted distribution patterns also showed good concordance with the 2014 survey observations. Our results indicate that habitat relationships were captured sufficiently to predict both changes in abundance and shifts in distribution when conditions warmed, for both cool‐ and warm‐temperate species. Main conclusions: Models built with multidecadal datasets were able to forecast abundance and distribution in a novel warm year for a diverse set of cetacean species. Models with the best explanatory power did not necessarily have the best predictive power. Also, they revealed species‐specific responses to warming ocean waters. Results have implications for modelling effects of climate change on cetaceans and other marine predators. [ABSTRACT FROM AUTHOR]

Flyingfishes are large enough to eat zooplankton, small enough to be consumed by top predators, and therefore form a central mid-trophic component of tropical epipelagic marine food webs. Characterizing patterns of flyingfish abundance, distribution, and habitat preference has important implications for understanding both localized and generalized functions of marine ecosystems. The eastern tropical Pacific Ocean (ETP) supports many flyingfish species and their predators, yet no studies to date have identified oceanographic factors that define flyingfish habitats or estimate species richness and diversity at broad taxonomic and geographic scales. In this study, we analyzed 11,125 flyingfish representing 25 species and all seven named genera, collected from the ETP over a 21-year period. We applied spatially explicit analysis methods (ARCGIS, DIVA-GIS, MAXENT) and compared specimen locality data to remotely sensed oceanographic data and previously described oceanographic partitions. Our results show that Exocoetus is the most abundant genus (49%) and E. monocirrhus the most abundant species (32%) of flyingfishes in the ETP. Mean sea surface temperature was most important for defining flyingfish habitats (19.2-41.7%) and species richness (highest in the North Equatorial Current). Additionally, flyingfish species diversity was found to be highest in coastal regions of the study area (Shannon indices > 1.5). Together, these results provide unprecedented characterizations of a mid-trophic epipelagic community in an economically valuable region during a time when sea surface temperatures are predicted to increase as a result of global climate change. [ABSTRACT FROM AUTHOR]

Understanding the factors that contribute to a population’s habitat use is important for conservation planners and managers to identify reasons behind a population’s distribution. Habitat use often differs between sexes, however few studies on sexually monomorphic species document this difference, resulting in misleading ecological interpretations and non-targeted management actions. The aim of this study was to test for sex-specific differences in the seasonal habitat use of Indo-Pacific bottlenose dolphins (Tursiops aduncus) off Bunbury, Australia. Systematic, boat-based, photographic identification dolphin surveys (n = 587) were conducted across seasons over 6 years during 2007-2013. Generalised additive models explored relationships between the presence-absence of dolphins and sex, water depth and benthic habitat type. Results highlighted that: (i) habitat use differed seasonally for males and females, (ii) depth had a strong influence on habitat use, which differed between sexes for summer, winter and spring, and (iii) there were no sex differences in habitat use in autumn, which coincides with the peak breeding season. In summer and autumn dolphins were concentrated in shallow, near-shore waters predominantly over reef and sand, and in winter and spring dolphins had a broader distribution over reef and mud/silt with the use of deeper, offshore waters. This pattern is consistent with the seasonally-dependent dolphin abundance that has been documented for this population. Identification of sex differences in habitat use provides management agencies with insights to implement informed actions for the conservation of this coastal dolphin population which is forecast to decline by 50% in the next two decades. [ABSTRACT FROM AUTHOR]

Habitat loss and fragmentation induce a decline and endangerment of freshwater organisms such as Aeshna viridis, an endangered dragonfly species characterised by a specific insect-plant association to the macrophyte Stratiotes aloides. In order to implement conservation measures, a good level of knowledge about the occurrence, habitat requirements and quality, as well as patch size of the species is important. We analysed the influence of several habitat parameters on the presence/absence and abundance of A. viridis exuviae using habitat models (generalised linear mixed-effect models). The ditches populated by A. viridis were classified as moderately polluted and meso- to eutrophic with a high cover of emerged S. aloides stands. The main factor contributing to the presence of A. viridis was the coverage of emerged S. aloides combined with the ditch width. The 90% probability of the presence of A. viridis was achieved at a cover of 14% (8.4 m²) and/or 77% (46.2 m²) of emerged S. aloides. The number of A. viridis exuviae was positively affected by the cover of emerged S. aloides and negatively affected by the sediment thickness, water maintenance and water temperature in March and August. The habitat parameters - water temperature and sediment thickness - are associated with S. aloides in the beginning of siltation of ditch succession. If ditch cleaning takes place during larvae development, eggs and larvae are removed by these procedures. In an optimal situation, the S. aloides populations occur in a mosaic of different states of siltation, which is managed by adapted water maintenance. [ABSTRACT FROM AUTHOR]

Anthropogenic activities caused a severe loss of pristine habitats alongside with fragmentation of remaining habitats and the deterioration of habitat quality. The Arabuko Sokoke forest represents the largest remnant of East African coastal forest. Despite conservation efforts to maintain biodiversity in this forest, populations of several species are declining, including flagship species like the endemic Sokoke Scops Owl Otus ireneae. In this study, we assessed the presence of O. ireneae based on playback technique to identify the occurrence of this species across the forest. We then analysed habitat parameters at sites occupied and non-occupied by the owl species. Our data show that O. ireneae occurs restricted to one single forest type, the Cynometra woodland. Results obtained from parametric one-way ANOVA and structural equation modelling reveal that large old Cynometra webberi trees and dead wood are key requirements for the occurrence of this owl species. However, large C. webberi trees are currently illegally logged by the forest adjacent human population to produce timber, carvings, poles. Charcoal and dead wood represents a major energy source for households. Otus ireneae, being the smallest owl of East Africa may serve as a charismatic flag ship species to promote conservation of this endangered coastal forest, and furthermore as umbrella to conserve other forest species with similar habitat requirements. [ABSTRACT FROM AUTHOR]

Coupled three-dimensional circulation and biogeochemical models predict changes in water properties that can be used to define fish habitat, including physiologically important parameters such as temperature, salinity, and dissolved oxygen. However, methods for calculating the volume of habitat defined by the intersection of multiple water properties are not well established for coupled three-dimensional models. The objectives of this research were to examine multiple methods for calculating habitat volume from three-dimensional model predictions, select the most robust approach, and provide an example application of the technique. Three methods were assessed: the “Step,” “Ruled Surface”, and “Pentahedron” methods, the latter of which was developed as part of this research. Results indicate that the analytical Pentahedron method is exact, computationally efficient, and preserves continuity in water properties between adjacent grid cells. As an example application, the Pentahedron method was implemented within the Habitat Volume Model (HabVol) using output from a circulation model with an Arakawa C-grid and physiological tolerances of juvenile striped bass ( Morone saxatilis ). This application demonstrates that the analytical Pentahedron method can be successfully applied to calculate habitat volume using output from coupled three-dimensional circulation and biogeochemical models, and it indicates that the Pentahedron method has wide application to aquatic and marine systems for which these models exist and physiological tolerances of organisms are known. [ABSTRACT FROM AUTHOR]