A Bayesian state-space model using age-at-harvest data for estimating the population of black bears (Ursus americanus) in Wisconsin

Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management

Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.

Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management

Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.

Population reduction by hunting helps control human-wildlife conflicts for a species that is a conservation success story

Among the world's large Carnivores, American black bears (Ursus americanus) are the foremost conservation success story. Populations have been expanding across North America because the species is adaptable and tolerant of living near people, and because management agencies in the U.S. and Canada controlled hunting and other human-sources of mortality. As a result, human-black bear conflicts (damage to property, general nuisance, threat to human safety) have dramatically increased in some areas, making it urgently important to develop and deploy a variety of mitigation tools. Previous studies claimed that legal hunting did not directly reduce conflicts, but they did not evaluate whether hunting controlled conflicts via management of population size. Here, we compared temporal patterns of phoned-in complaints about black bears (total ~63,500) in Minnesota, USA, over 4 decades to corresponding bear population estimates: both doubled during the first decade. We also quantified natural bear foods, and found that large year-to-year fluctuations affected numbers of complaints; however, since this variation is due largely to weather, this factor cannot be managed. Complaints fell sharply when the management agency (1) shifted more responsibility for preventing and mitigating conflicts to the public; and (2) increased hunting pressure to reduce the bear population. This population reduction was more extreme than intended, however, and after hunting pressure was curtailed, population regrowth was slower than anticipated; consequently both population size and complaints remained at relatively low levels statewide for 2 decades (although with local hotspots). These long-term data indicated that conflicts can be kept in tolerable bounds by managing population size through hunting; but due to the bluntness of this instrument and deficiencies and uncertainties in monitoring and manipulating populations, it is wiser to maintain a population at a level where conflicts are socially-acceptable than try to reduce it once it is well beyond that point.

Relationships of catch-per-unit-effort metrics with abundance vary depending on sampling method and population trajectory

Catch-per-unit-effort (CPUE) is often used to monitor wildlife populations and to develop statistical population models. Animals caught and released are often not included in CPUE metrics and their inclusion may create more accurate indices of abundance. We used 21 years of detailed harvest records for bobcat (Lynx rufus) in Wisconsin, U.S.A., to calculate CPUE and ‘actual CPUE’ (ACPUE; including animals caught and released) from bobcat hunters and trappers. We calibrated these metrics to an independent estimate of bobcat abundance and attempted to create simple but effective models to estimate CPUE and ACPUE using harvest success data (i.e., bobcats harvested/available permits). CPUE showed virtually no relationship with bobcat abundance across all years, but both CPUE and ACPUE had stronger, non-linear, and negative relationships with abundance during the periods when the population was decreasing. Annual harvest success strongly predicted composite ACPUE and CPUE from hunters and trappers and hunter ACPUE and CPUE but was a poorer predictor of trapper ACPUE and CPUE. The non-linear, and sometimes weak, relationships with bobcat abundance likely reflect the increasing selectivity of bobcat hunters for trophy animals. Studies calibrating per-unit-effort metrics against abundance should account for population trajectories and different harvest methods (e.g., hunting and trapping). Our results also highlight the potential for estimating per-unit-effort metrics from relatively simple and inexpensive data sources and we encourage additional research into the use of per-unit-effort metrics for population estimation.

Black bear translocations in response to nuisance behaviour indicate increased effectiveness by translocation distance and landscape context

Abstract ContextTranslocation is a widely used non-lethal tool to mitigate human–wildlife conflicts, particularly for carnivores. Multiple intrinsic and extrinsic factors may influence translocation success, yet the influence of release-site landscape context on the success of translocations of wildlife involved in nuisance behaviour is poorly understood. Moreover, few studies of translocated wildlife involved in nuisance behaviour have provided estimates of translocation success under different scenarios. AimsWe evaluated the role of intrinsic (age, sex) and extrinsic (translocation distance, landscape composition) features on translocation success of American black bears (Ursus americanus) involved in nuisance behaviour and provide spatially explicit predictions of success under different scenarios. MethodsWe analysed data from 1462 translocations of 1293 bears in Wisconsin, USA, from 1979 to 2016 and evaluated two measures of translocation success: repeated nuisance behaviour and probability of returning to a previous capture location. Key resultsTranslocation distances ranged from 2 to 235km (mean=57km). Repeated nuisance behaviour was recorded following 13.2% of translocation events (192 of 1457) and was not significantly affected by translocation distance. Bears repeated nuisance behaviour and were recaptured at their previous captures site (i.e. returned) after 64% of translocation events (114 of 178). Return probability decreased with an increasing translocation distance, and yearling bears were less likely to return than were adults. The proportions of agriculture and forest within 75km and 100km respectively, of the release site had positive and negative effects on return probability. ConclusionsMangers can use bear characteristics and landscape context to improve translocation success. For example, achieving a 10% predicted probability of return would require translocation distances of 49–60km for yearlings in low-agriculture and high-forest landscapes. In contrast, estimated return probability for adults was ≥38% across all translocation distances (0–124km) and almost all landscape contexts. ImplicationsOur results emphasise the importance of considering the effects of landscape conditions for developing spatially explicit guidelines for maximising translocation success.