Human-Wildlife Conflict Mitigation Based on Damage, Distribution, and Activity: A Case Study of Wild Boar in Zhejiang, Eastern China

Human-wildlife conflicts are becoming increasingly common worldwide and are a challenge to biodiversity management. Compared with compensatory management, which often focuses on solving emergency conflicts, mitigation management allows decision-makers to better understand where the damage is distributed, how the species are distributed and when the species conduct their activity. Here, we integrated data collected from 90 districts/counties' damage surveys and 1271 camera traps to understand the damage status, abundance, density and activity rhythms of wild boar (Sus scrofa) in Zhejiang, Eastern China, from January 2019 to August 2023. We found that (1) wild boar-human conflicts were mainly distributed in the northwest and southwest mountainous regions of Zhejiang Province; (2) the total abundance of wild boar was 115,156 ± 24,072 individuals, indicating a growing trend over the past decade and a higher density in the western and southern regions; (3) wild boar exhibited different activity patterns across different damage regions, and the periods around 7:00, 11:00 and 16:00 represented activity peaks for wild boar in seriously damaged regions. The damage distribution, density, distribution and activity rhythms provide specific priority regions and activity intensity peaks for conflict mitigation. We believe that these findings based on the damage, distribution and activity could provide a scientific basis for mitigation management at the county level and enrich the framework of human-wildlife conflict mitigation.

AbundanceR: A Novel Method for Estimating Wildlife Abundance Based on Distance Sampling and Species Distribution Models

Appropriate field survey methods and robust modeling approaches play an important role in wildlife protection and habitat management because reliable information on wildlife distribution and abundance is important for conservation planning and actions. However, accurately estimating animal abundance is challenging in most species, as usually only a small proportion of the population can be detected during surveys. Species distribution models can predict the habitat suitability index, which differs from species abundance. We designed a method to adjust the results from species distribution models to achieve better accuracy for abundance estimation. This method comprises four steps: (1) conducting distance sampling, recording species occurrences, and surveying routes; (2) performing species distribution modeling using occurrence records and predicting animal abundance in each quadrat in the study area; (3) comparing the difference between field survey results and predicted abundance in quadrats along survey routes, adjusting model prediction, and summing up to obtain total abundance in the study area; (4) calculating uncertainty from three sources, i.e., distance sampling (using detection rate), species distribution models (using R squared), and differences between the field survey and model prediction [using the standard deviation of the ratio (observation/prediction) at different zones]. We developed an R package called abundanceR to estimate wildlife abundance and provided data for the Tibetan wild ass (Equus kiang) based on field surveys at the Three-River-Source National Park, as well as 29 layers of environmental variables covering the terrestrial areas of the planet. Our method can provide accurate estimation of abundance for animals inhabiting open areas that can be easily observed during distance sampling, and whose spatial heterogeneity of animal density within the study area can be accurately predicted using species distribution models.

Crested porcupine (Hystrix cristata) abundance estimation using Bayesian methods: first data from a highly agricultural environment in central Italy

Wildlife abundance estimation is one of the key components in conservation biology. Bayesian frameworks are widely used to adjust the potential biases derived by data collected in the field, as they can increase the precision of model parameter as a consequence of the combination of previous pieces of knowledge (priors) combined with data collected in the field to produce an a-posteriori distribution. Capture-recapture is one of the most common techniques used to assess animal abundance. However, the implementation with camera traps requires that animals present unique phenotypic traits for individual-based recognition. The crested porcupine Hystrix cristata is a semi-fossorial rodent with a continuous, but patchily distribution across Italy. Despite the species does not present evident individual-specific phenotypic traits, the information gathered using presence-only data obtained from camera traps, opportunistic observations, and road-killing events could be used to provide a rough estimate of the species abundance within an area. The main purpose of the present research was hence to provide the first preliminary estimate of the abundance of the crested porcupine in central Italy using presence-only data obtained from the above different monitoring methods. The results obtained estimated an average minimum number of 1803 individuals (SD = 26.89, CI 95% = 1750–1855) within an area covering about 17,111 km2. Since the porcupine is considered as “potentially problematic” because of damages to croplands and riverbanks, assessing its abundance is even more important to delineate adequate conservation and management actions to limit the potential trade-off effects over human activities.

Variability in deer diet and plant vulnerability to browsing among forests with different establishment years of sika deer

Increased ungulate browsing alters the composition of plant communities and modifies forest ecosystems worldwide. Ungulates alter their diet following changes in availability of plant species; however, we know little about how browse selection and plant community composition change with different stages of deer establishment. Here, we provide insight into this area of study by combining multiple approaches: comparison of the understory plant community, analysis of records of browsing damage, and DNA barcoding of sika deer feces at 22 sites in forests in northern Japan varying in when deer were first established. The coverage of vegetation and number of plant species were only lower at sites where deer were present for more than 20 years, while the difference in plant coverage among deer establishment years varied among plant species. Deer diet differed across establishment years, but was more affected by the site, thereby indicating that food selection by deer could change over several years after deer establishment. Plant life form and plant architecture explained the difference in plant coverage across establishment years, but large variability was observed in deer diet within the two categories. Integrating these results, we categorized 98 plant taxa into six groups that differed in vulnerability to deer browsing (degree of damage and coverage). The different responses to browsing among plant species inferred from this study could be a first step in predicting the short- and long-term responses of forest plant communities to deer browsing.