Species distribution modelling and imperfect detection: comparing occupancy versus consensus methods

Geographic patterns of distribution and ecological niche of the snake-necked turtle genus Hydromedusa

Biotic and abiotic factors play a crucial role in determining the distribution of species. These factors dictate the conditions that must be met for a species to thrive in a particular area. Sister species that present some degree of niche overlap can shed light on how they are distributed and coexist in their environment. This study aims to investigate the geographical distribution and ecological niche of the sister species of snake-necked turtles Hydromedusa maximiliani and H. tectifera. By analyzing their niche overlap, we aim to obtain a better understanding of how these two species coexist and which variables are determining their occurences. We applied species distribution modeling and compared the niches using the niche equivalence and similarity tests. Our findings show that the distribution of H. maximiliani is most influenced by temperature seasonality and isothermality, while H. tectifera is most affected by the temperature seasonality, precipitation of warmest quarter and mean diurnal range. In addition, our results suggest that the niche expressed by H. maximiliani retained ecological characteristics that can accurately predict the H. tectifera distribution, but the inverse is not true. In this sense, differences are not solely due to the geographic availability of environmental conditions but can reflect niche restrictions, such as competition.

Distribution update of water deer (Hydropotes inermis) and prediction of their potential distribution in Northeast China

Human interventions have a great potential of spatially cornering and limiting species, therefore investigating the species distribution is one of the most crucial issues for managing wildlife populations and suggesting robust conservation strategies. Water deer (Hydropotes inermis) are widespread in China throughout history and are endemic to East Asia. However, they disappeared from Northeast China for years. We rediscovered the water deer in a previous study in Jilin Province, China. Then, we conducted further research in Northeast China to determine their distribution status, supplying fundamental data for the recovery and expansion of their population. An interview survey, line transect survey and infrared camera monitoring were carried out in some counties/cities in Northeast China from June to December 2021. The results showed that the water deer were distributed in Wuchang city of Heilongjiang Province, Changbai Korean Autonomous County, Baishan Municipal District, Ji'an city, Hunchun city, Huadian city, Antu County and Helong County of Jilin Province, Benxi Manchu Autonomous County, Huanren Manchu Autonomous County, Kuandian Manchu Autonomous County, Fengcheng city and Donggang city of Liaoning Province. The ensemble species distribution model constructed by sdm within the TSS of various models that were set as weight revealed that the potential distribution area of the water deer in the study area was 8764.66 km² (28.77% of the study area). Combining recent studies concerning the distribution of water deer and the current study, we updated the distribution of wild water deer in Northeast China, which is vital for their conservation worldwide.

Occupancy winners in tropical protected forests: a pantropical analysis

The structure of forest mammal communities appears surprisingly consistent across the continental tropics, presumably due to convergent evolution in similar environments. Whether such consistency extends to mammal occupancy, despite variation in species characteristics and context, remains unclear. Here we ask whether we can predict occupancy patterns and, if so, whether these relationships are consistent across biogeographic regions. Specifically, we assessed how mammal feeding guild, body mass and ecological specialization relate to occupancy in protected forests across the tropics. We used standardized camera-trap data (1002 camera-trap locations and 2-10 years of data) and a hierarchical Bayesian occupancy model. We found that occupancy varied by regions, and certain species characteristics explained much of this variation. Herbivores consistently had the highest occupancy. However, only in the Neotropics did we detect a significant effect of body mass on occupancy: large mammals had lowest occupancy. Importantly, habitat specialists generally had higher occupancy than generalists, though this was reversed in the Indo-Malayan sites. We conclude that habitat specialization is key for understanding variation in mammal occupancy across regions, and that habitat specialists often benefit more from protected areas, than do generalists. The contrasting examples seen in the Indo-Malayan region probably reflect distinct anthropogenic pressures.

Climate change negative effects on the Neotropical fishery resources may be exacerbated by hydroelectric dams

Climate change is now recognized as a reality and along with human pressures such as river fragmentation by dams, amplifies the threats to freshwater ecosystems and their biodiversity. In the Brazilian portion of the Upper Paraguay River Basin (UPRB) that encompasses the Pantanal, one of the largest tropical wetlands in the world, in addition to the high biodiversity found there, fisheries are an important ecosystem service mostly supported by migratory fishes. We estimated the current range of migratory fish of commercial interest, also assessing the climate change effects predicted on the distribution patterns. Then, we assessed the effects of future climate on fish richness, and combining species ranges with routes blocked by artificial dams investigated possible impacts on fishery and food security in the UPRB. Climate change will induce range contraction between 47% and 100% for the species analyzed, and only four migratory fish may have suitable habitat until the end-of-century. The local richness will reduce about 85% in the basin. River fragmentation by dams acting together with climate change will prevent upstream shifts for most fish species. About 4% of present range and up to 45% of future range of migratory fish should be blocked by dams in UPRB. Consequently, this will also negatively affect fishery yield and food security in the future.

Temperature and Prey Species Richness Drive the Broad-Scale Distribution of a Generalist Predator

The ongoing climate change and the unprecedented rate of biodiversity loss render the need to accurately project future species distributional patterns more critical than ever. Mounting evidence suggests that not only abiotic factors, but also biotic interactions drive broad-scale distributional patterns. Here, we explored the effect of predator-prey interaction on the predator distribution, using as target species the widespread and generalist grass snake (Natrix natrix). We used ensemble Species Distribution Modeling (SDM) to build a model only with abiotic variables (abiotic model) and a biotic one including prey species richness. Then we projected the future grass snake distribution using a modest emission scenario assuming an unhindered and no dispersal scenario. The two models performed equally well, with temperature and prey species richness emerging as the top drivers of species distribution in the abiotic and biotic models, respectively. In the future, a severe range contraction is anticipated in the case of no dispersal, a likely possibility as reptiles are poor dispersers. If the species can disperse freely, an improbable scenario due to habitat loss and fragmentation, it will lose part of its contemporary distribution, but it will expand northwards.

Improving the reliability of eDNA data interpretation

Global declines in biodiversity highlight the need to effectively monitor the density and distribution of threatened species. In recent years, molecular survey methods detecting DNA released by target-species into their environment (eDNA) have been rapidly on the rise. Despite providing new, cost-effective tools for conservation, eDNA-based methods are prone to errors. Best field and laboratory practices can mitigate some, but the risks of errors cannot be eliminated and need to be accounted for. Here, we synthesize recent advances in data processing tools that increase the reliability of interpretations drawn from eDNA data. We review advances in occupancy models to consider spatial data-structures and simultaneously assess rates of false positive and negative results. Further, we introduce process-based models and the integration of metabarcoding data as complementing approaches to increase the reliability of target-species assessments. These tools will be most effective when capitalizing on multi-source data sets collating eDNA with classical survey and citizen-science approaches, paving the way for more robust decision-making processes in conservation planning.

Assessment of Long-Term Trends in Fish Distributions at Multiple Scales Decreases Uncertainty Associated with Historical Datasets

Monitoring long-term changes in aquatic biodiversity requires the effective use of historical data that were collected with different methods and varying levels of effort. Aggregating data into different spatial scales can control for such differences and provide a robust framework for monitoring distribution trends. We used a quantitative, multi-scale assessment to evaluate the potential drivers of distribution change for 60 fish species at three spatial scales, using 503 unique sampling events conducted between 1931 and 2019 in a stream biodiversity hotspot (French Creek, Pennsylvania, U.S.A). Trends delineated at multiple scales demonstrated that only one cyprinid species consistently declined through time. In contrast, several species, particularly centrarchids (bass and sunfish), appeared to increase with time. However, evidence for species' increases varied among the different spatial scales, and our observations suggest that differences in effort and detection across time periods may contribute to patterns of species increases. There was agreement among scales that agricultural land use, non-native brown trout (Salmo trutta), and anthropogenic barriers did not explain patterns in biodiversity change from the distribution trends in this study. The lack of species declines is likely due to the limited levels of historical impacts in the watershed compared with other locations in the region that experienced more acute pollution bottlenecks. Species increases were most prevalent for sportfish and baitfish species, suggesting that distribution increases were human mediated. Similar multi-scale assessments should provide more robust insight into patterns of biodiversity loss and distribution changes by maximizing the use of historical data.

Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA

Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms.

Invasive Plant Species Establishment and Range Dynamics in Sri Lanka under Climate Change

Plant invasion has been widely recognized as an agent of global change that has the potential to have severe impacts under climate change. The challenges posed by invasive alien plant species (IAPS) on biodiversity and ecosystem stability is growing and not adequately studied, especially in developing countries. Defining climate suitability for multiple invasive plants establishment is important for early and strategic interventions to control and manage plant invasions. We modeled priority IAPS in Sri Lanka to identify the areas of greatest climatic suitability for their establishment and observed how these areas could be altered under projected climate change. We used Maximum Entropy method to model 14 nationally significant IAPS under representative concentration pathways 4.5 and 8.5 for 2050 and 2070. The combined climate suitability map produced by summing up climatic suitability of 14 IAPS was further classified into five classes in ArcMap as very high, high, moderate, low, and very low. South and west parts of Sri Lanka are projected to have potentially higher climatic suitability for a larger number of IAPS. We observed suitable area changes (gains and losses) in all five classes of which two were significant enough to make an overall negative impact i.e., (i) contraction of the very low class and (ii) expansion of the moderate class. Both these changes trigger the potential risk from IAPS in Sri Lanka in the future.

Heterospecific social attraction in migrant birds: habitat niche overlap between two threatened shrikes

Context Effective biodiversity conservation requires information about a species’ ecology and its relationship with the geographical context. To achieve this efficiently, species distribution models can be developed, also taking into account species associations. Aims I aimed to illustrate the habitat requirements of two threatened passerines of semi-open landscapes, i.e. the lesser grey shrike, Lanius minor, and the woodchat shrike, Lanius senator, in southern Italy. Further, I assessed whether there is heterospecific social attraction between them, by assessing how their habitat niches overlap. Methods Data were collected by territory mapping during the 2009–13 breeding seasons. The habitat requirements of the species were investigated with the help of ecological niche factor analysis (ENFA). In addition, the areas of sympatry between the two species were defined by indicator kriging and the habitat niche overlap was analysed using the generalised linear model (GLM). Key results The results showed that these two species inhabit open areas, with scattered vegetation such as shrubs and trees, while avoiding intensively cultivated permanent crops, such as vineyards and olive groves. Moreover, a little difference was observed in the percentage cover of shrublands, which were higher in the woodchat shrike territories than in the lesser grey ones. The strong overlap in their habitat niches suggests heterospecific social attraction between them, especially because of the species rarity. Conclusions The lesser grey and the woodchat shrike were found to occur in very similar environments, by evidencing the overlap of their macrohabitat niches. This suggests the presence of heterospecific social attraction, corroborating the understudied hypothesis that this phenomenon is valid for migrant birds as well. The lesser grey shrike, in particular, may use occurrences of the woodchat shrike as a cue for assessing habitat quality and, thus, to establish its territory. Implications Considering the high habitat niche overlap, habitat changes occurring in the landscape might affect them equally. Furthermore, the use of heterospecific social information in habitat selection potentially has many important conservation implications. Indeed, by reproducing the appropriate information, birds could be attracted to specific sites known to be high-quality habitat.

Temperature and hydrologic alteration predict the spread of invasive Largemouth Bass (Micropterus salmoides)

The successful establishment of an aquatic invasive alien species can be mediated by a suite of environmental factors, including climate and anthropogenic disturbance. Dams and reservoirs are thought to promote freshwater fish invasion success through hydrological alterations but the evidence for their role in the global invasion of Largemouth Bass (Micropterus salmoides) on a landscape scale is limited. Here, we examine the distribution of Largemouth Bass, one of the most widely introduced fish in the world, from the Iberian Peninsula using species distribution models (SDMs), including an ensemble forecast. We used these models to test the role of twelve environmental predictors expected to influence the distribution of Largemouth Bass, including the reservoir storage capacity at local and upstream reaches. We found that the predictive accuracy, based on AUC criteria, of the ensemble model was higher than any of the six individual SDMs for Largemouth Bass. The most influential predictor of bass distribution included in our model of the Iberian Peninsula was temperature, where warmer temperatures were generally associated with bass presence, and cooler temperatures with absence. In addition to warmer temperatures, increasing storage of local and upstream reservoirs increased predicted presence, suggesting an important role of reservoirs in mediating the invasive success of this fish. Our results indicate that although natural climatic factors may be crucial in the successful invasion of Largemouth Bass, hydrological alteration (e.g., regulated flow regimes and lentic habitats associated with dams and reservoirs) may be important. Understanding the drivers promoting the establishment of this global invader will be important in identifying areas at risk and in developing future efforts to control its spread, especially when those drivers are ongoing anthropogenic disturbances such as the construction and operation of dams and reservoirs.

Spatial models to account for variation in observer effort in bird atlases

To assess the importance of variation in observer effort between and within bird atlas projects and demonstrate the use of relatively simple conditional autoregressive (CAR) models for analyzing grid‐based atlas data with varying effort. Pennsylvania and West Virginia, United States of America. We used varying proportions of randomly selected training data to assess whether variations in observer effort can be accounted for using CAR models and whether such models would still be useful for atlases with incomplete data. We then evaluated whether the application of these models influenced our assessment of distribution change between two atlas projects separated by twenty years (Pennsylvania), and tested our modeling methodology on a state bird atlas with incomplete coverage (West Virginia). Conditional Autoregressive models which included observer effort and landscape covariates were able to make robust predictions of species distributions in cases of sparse data coverage. Further, we found that CAR models without landscape covariates performed favorably. These models also account for variation in observer effort between atlas projects and can have a profound effect on the overall assessment of distribution change. Accounting for variation in observer effort in atlas projects is critically important. CAR models provide a useful modeling framework for accounting for variation in observer effort in bird atlas data because they are relatively simple to apply, and quick to run.

Using landscape habitat associations to prioritize areas of conservation action for terrestrial birds

Predicting species distributions has long been a valuable tool to plan and focus efforts for biodiversity conservation, particularly because such an approach allows researchers and managers to evaluate species distribution changes in response to various threats. Utilizing data from a long-term monitoring program and land cover data sets, we modeled the probability of occupancy and colonization for 38 bird Species of Greatest Conservation Need (SGCN) in the robust design occupancy modeling framework, and used results from the best models to predict occupancy and colonization on the Iowa landscape. Bird surveys were conducted at 292 properties from April to October, 2006-2014. We calculated landscape habitat characteristics at multiple spatial scales surrounding each of our surveyed properties to be used in our models and then used kriging in ArcGIS to create predictive maps of species distributions. We validated models with data from 2013 using the area under the receiver operating characteristic curve (AUC). Probability of occupancy ranged from 0.001 (SE < 0.001) to 0.995 (SE = 0.004) for all species and probability of colonization ranged from 0.001 (SE < 0.001) to 0.999 (SE < 0.001) for all species. AUC values for predictive models ranged from 0.525-0.924 for all species, with 17 species having predictive models considered useful (AUC > 0.70). The most important predictor for occupancy of grassland birds was percentage of the landscape in grassland habitat, and the most important predictor for woodland birds was percentage of the landscape in woodland habitat. This emphasizes the need for managers to restore specific habitats on the landscape. In an era during which funding continues to decrease for conservation agencies, our approach aids in determining where to focus limited resources to best conserve bird species of conservation concern.

Differences in microhabitat selection patterns between a remnant and constructed landscape following management intervention

Context Achieving successful conservation outcomes in habitat creation and reintroductions requires an understanding of how species use their habitat and respond to these interventions. However, few initiatives directly compare microhabitat selection between remnant and managed habitats to measure effectiveness and evaluate outcomes. Probability of detection is also rarely included in studies on microhabitat use, which may lead to erroneous conclusions if detectability varies between variables. Methods In this study, we used the endangered green and golden bell frog (Litoria aurea) to compare differences in microhabitat-use patterns in both a remnant and a constructed habitat. A detectability study was also conducted to determine detection probabilities among microhabitats. Key results Aquatic vegetation was used more than expected in both the remnant and constructed habitats, and rock piles were utilised less than expected in the constructed habitat, despite their recommendation in most habitat templates. We found that detection probabilities altered the outcomes of abundance estimates for nearly all the measured microhabitat variables. Conclusions Future management for this species should focus on providing high proportions of aquatic vegetation. Furthermore, although rock piles have been utilised greatly in past L. aurea habitat creation, placing large rocks on a managed site is expensive and time consuming. Future management initiatives may need to focus on providing smaller proportion of rocks, which would be a more appropriate use of resources. Implications With conservation management projects increasing over the next few decades, understanding habitat use before implementing strategies should be a priority as it will provide important insights and inform decision-making for optimum habitat creation and restoration. Furthermore, accounting for detectability in microhabitat use studies is essential to avoid wrong conclusions that may negatively affect the success of ecological management strategies.

Impacts of Dams and Global Warming on Fish Biodiversity in the Indo-Burma Hotspot

Both hydropower dams and global warming pose threats to freshwater fish diversity. While the extent of global warming may be reduced by a shift towards energy generation by large dams in order to reduce fossil-fuel use, such dams profoundly modify riverine habitats. Furthermore, the threats posed by dams and global warming will interact: for example, dams constrain range adjustments by fishes that might compensate for warming temperatures. Evaluation of their combined or synergistic effects is thus essential for adequate assessment of the consequences of planned water-resource developments. We made projections of the responses of 363 fish species within the Indo-Burma global biodiversity hotspot to the separate and joint impacts of dams and global warming. The hotspot encompasses the Lower Mekong Basin, which is the world’s largest freshwater capture fishery. Projections for 81 dam-building scenarios revealed progressive impacts upon projected species richness, habitable area, and the proportion of threatened species as generating capacity increased. Projections from 126 global-warming scenarios included a rise in species richness, a reduction in habitable area, and an increase in the proportion of threatened species; however, there was substantial variation in the extent of these changes among warming projections. Projections from scenarios that combined the effects of dams and global warming were derived either by simply adding the two threats, or by combining them in a synergistic manner that took account of the likelihood that habitat shifts under global warming would be constrained by river fragmentation. Impacts on fish diversity under the synergistic projections were 10–20% higher than those attributable to additive scenarios, and were exacerbated as generating capacity increased—particularly if CO₂ emissions remained high. The impacts of dams, especially those on river mainstreams, are likely to be greater, more predictable and more immediately pressing for fishes than the consequences of global warming. Limits upon dam construction should therefore be a priority action for conserving fish biodiversity in the Indo-Burma hotspot. This would minimize synergistic impacts attributable to dams plus global warming, and help ensure the continued provision of ecosystem services represented by the Lower Mekong fishery.

Modeling stream fish distributions using interval-censored detection times

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it uses simple data that can be readily collected by field ecologists.

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts.

Accuracy and efficiency of detection dogs: a powerful new tool for koala conservation and management

Accurate data on presence/absence and spatial distribution for fauna species is key to their conservation. Collecting such data, however, can be time consuming, laborious and costly, in particular for fauna species characterised by low densities, large home ranges, cryptic or elusive behaviour. For such species, including koalas (Phascolarctos cinereus), indicators of species presence can be a useful shortcut: faecal pellets (scats), for instance, are widely used. Scat surveys are not without their difficulties and often contain a high false negative rate. We used experimental and field-based trials to investigate the accuracy and efficiency of the first dog specifically trained for koala scats. The detection dog consistently out-performed human-only teams. Off-leash, the dog detection rate was 100%. The dog was also 19 times more efficient than current scat survey methods and 153% more accurate (the dog found koala scats where the human-only team did not). This clearly demonstrates that the use of detection dogs decreases false negatives and survey time, thus allowing for a significant improvement in the quality and quantity of data collection. Given these unequivocal results, we argue that to improve koala conservation, detection dog surveys for koala scats could in the future replace human-only teams.

Predicting the spatial distribution of a seabird community to identify priority conservation areas in the Timor Sea

Understanding spatial and temporal variability in the distribution of species is fundamental to the conservation of marine and terrestrial ecosystems. To support strategic decision making aimed at sustainable management of the oceans, such as the establishment of protected areas for marine wildlife, we identified areas predicted to support multispecies seabird aggregations in the Timor Sea. We developed species distribution models for 21 seabird species based on at-sea survey observations from 2000-2013 and oceanographic variables (e.g., bathymetry). We applied 4 statistical modeling techniques and combined the results into an ensemble model with robust performance. The ensemble model predicted the probability of seabird occurrence in areas where few or no surveys had been conducted and demonstrated 3 areas of high seabird richness that varied little between seasons. These were located within 150 km of Adele Island, Ashmore Reef, and the Lacepede Islands, 3 of the largest aggregations of breeding seabirds in Australia. Although these breeding islands were foci for high species richness, model performance was greatest for 3 nonbreeding migratory species that would have been overlooked had regional monitoring been restricted to islands. Our results indicate many seabird hotspots in the Timor Sea occur outside existing reserves (e.g., Ashmore Reef Marine Reserve), where shipping, fisheries, and offshore development likely pose a threat to resident and migratory populations. Our results highlight the need to expand marine spatial planning efforts to ensure biodiversity assets are appropriately represented in marine reserves. Correspondingly, our results support the designation of at least 4 new important bird areas, for example, surrounding Adele Island and Ashmore Reef.