Effect of Lure on Detecting Mammals with Camera Traps

Integrated species distribution models reveal spatiotemporal patterns of human-wildlife conflict

To mitigate human-wildlife conflict it is imperative to know where and when conflict occurs. However, standard methods used to predict the occurrence of human-wildlife conflict often fail to recognize how a species distribution likely limits where and when conflict may happen. As such, methods that predict human-wildlife conflict could be improved if they could identify where conflict will occur relative to species' underlying distribution. To this end, we used an integrated species distribution model that combined presence-only wildlife complaints with data from a systematic camera trapping survey throughout Chicago, Illinois. This model draws upon both data sources to estimate a latent distribution of species; in addition, the model can estimate where conflict is most likely to occur within that distribution. We modeled the occupancy and conflict potential of coyote (Canis latrans), Virginia opossum (Didelphis virginiana), and raccoon (Procyon lotor) as a function of urban intensity, per capita income, and home vacancy rates throughout Chicago. Overall, the distribution of each species constrained the spatiotemporal patterns of conflict throughout the city of Chicago. Within each species distribution, we found that human-wildlife conflict was most likely to occur where humans and wildlife habitat overlap (e.g., featuring higher-than-average canopy cover and housing density). Furthermore, human-wildlife conflict was most likely to occur in high-income neighborhoods for Virginia opossum and raccoon, despite the fact that those two species have higher occupancy in low-income neighborhoods. As such, knowing where species are distributed can inform guidelines on where wildlife management should be focused, especially if it overlaps with human habitats. Finally, because this integrated model can incorporate data that have already been collected by wildlife managers or city officials, this approach could be used to develop stronger collaborations with wildlife management agencies and conduct applied research that will inform landscape-scale wildlife management.

Effectiveness of a commercial lure to attract red fox

In camera trap studies, attractants may be used to increase detection probabilities of wildlife, which may help to improve estimates of abundance and occupancy. Using a semi-experimental approach, we investigated if a commercial, strawberry scented lure increased detection probability and visiting time duration in red fox Vulpes vulpes, and the potential reasons for variation in these parameters. In September 2020, within the Stelvio National Park, central Italian Alps, 32 camera sites were randomly assigned to 4 different treatments: 8 to commercial lure, the target of our investigation; 8 to orange aroma, to test for the “curiosity” effect; 8 to cat kibble, to test for the “likability” effect; 8 to camera trap only, the control test. Detection probability and duration of visiting time were estimated using hurdle negative binomial regression models. Daily detection probability was significantly higher with lure (0.078), orange aroma (0.086), kibble (0.075) than with camera trap only (0.031); in the first day after treatment, the time an animal spent in front of the cameras significantly increased with orange aroma (16.61 s) and kibble (33.78 s) compared to lure (9.97 s) and camera trap only (0.38 s). Our results support the use of lures to improve detection probability and visit duration in red fox, but we could not disentangle the drivers of increased parameter estimates. When consumable costs are considered, the use of the commercial strawberry scented lure does not appear justified for both detection probability and visit duration, and cheaper alternatives may be preferable.

Mammals adjust diel activity across gradients of urbanization

Time is a fundamental component of ecological processes. How animal behavior changes over time has been explored through well-known ecological theories like niche partitioning and predator-prey dynamics. Yet, changes in animal behavior within the shorter 24-hour light-dark cycle have largely gone unstudied. Understanding if an animal can adjust their temporal activity to mitigate or adapt to environmental change has become a recent topic of discussion and is important for effective wildlife management and conservation. While spatial habitat is a fundamental consideration in wildlife management and conservation, temporal habitat is often ignored. We formulated a temporal resource selection model to quantify the diel behavior of eight mammal species across ten U.S. cities. We found high variability in diel activity patterns within and among species and species-specific correlations between diel activity and human population density, impervious land cover, available greenspace, vegetation cover, and mean daily temperature. We also found that some species may modulate temporal behaviors to manage both natural and anthropogenic risks. Our results highlight the complexity with which temporal activity patterns interact with local environmental characteristics, and suggest that urban mammals may use time along the 24-hour cycle to reduce risk, adapt, and therefore persist, and in some cases thrive, in human-dominated ecosystems.

Occurrence and Abundance of an Apex Predator and a Sympatric Mesopredator in Rural Areas of the Coastal Range of Southern Chile

The two mammalian carnivores, puma (Puma concolor) and South American grey fox (Lycalopex griseus) were studied, in a remote area located in the humid temperate forest of the coastal range of southern Chile. A total of six locations were selected in three landscapes: pre-mountain range, mountain range, and coast. The chosen study locations are relevant because they correspond to threatened areas with different levels of human intervention., so they offer the ideal setting for studying how different species of carnivores respond to both human presence and activities. A dataset was collected for 24 months during 2016–2018 through photo-trapping (13 camera traps placed along 50 photo-trap stations). Wes estimated the apparent occurrence and relative abundance index (RAI) of the fauna registered, by means of generalized linear models to contrast those of an apex predator, such as the puma and a sympatric mesopredator, the South American grey fox, across the three landscapes. The ecological variables assessed were the RAI of the other carnivore considered, exotic carnivores such as dogs and cats, human intervention, farmland effect, prey availability, and habitat quality. The primary hypothesis was that the apparent occurrence and RAI of puma and fox would be positively associated with the RAI of prey and livestock and negatively with human intervention. On the other hand, the secondary hypothesis dealt with the interactions between puma and fox faced with different degrees of human intervention. The results showed that the apparent occurrence of the puma was statistically explained by location only, and it was highest at the mountain range. The apparent occurrence of foxes was explained by both puma apparent occurrence and relative integrated anthropization index (INRA), being highest in the pre-mountain range. Concerning the RAI of pumas, high values were yielded by location and fox RAI. For the RAI of foxes, they were location, puma RAI, and INRA. It can be suggested that eucalyptus plantations from the pre-mountain range could offer an adequate habitat for the puma and the fox, but not the coastal range, as the mountain range could be acting as a biological barrier. Due to the nature of the data, it was not possible to detect any relevant effect between the two carnivores’ considered, between their respective preys, or the very abundant presence of dogs.

A multi-state occupancy model to non-invasively monitor visible signs of wildlife health with camera traps that accounts for image quality

Camera traps are an increasingly popular tool to monitor wildlife distributions. However, traditional analytical approaches to camera trap data are difficult to apply to visible wildlife characteristics in single images, such as infection status. Several parasites produce visible signs of infection that could be sampled via camera traps. Sarcoptic mange Sarcoptes scabiei is an ideal disease to study using cameras because it results in visible hair loss and affects a broad host range. Here, we developed a multi-state occupancy model to estimate the occurrence of mange in coyotes Canis latrans across an urban gradient. This model incorporates a secondary detection function for apparent by-image infection status to provide detection-corrected estimates of mange occurrence. We analysed a multi-year camera trap dataset in Chicago, Illinois, United States, to test whether the apparent occurrence of sarcoptic mange in coyotes Canis latrans increases with urbanization or varies through time. We documented visible signs consistent with current or recovering mange infection and variables we hypothesized would improve mange detection: The proportion of the coyote in frame, image blur and whether the image was in colour. We were more likely to detect coyotes with mange in images that were less blurry, in colour, and if a greater proportion of the coyote was visible. Mangy coyote occupancy was significantly higher in urban developed areas with low housing density and higher canopy cover whereas coyote occupancy, mangy or otherwise, decreased with urbanization. By incorporating image quality into our by-image detection function, we provide a robust method to non-invasively survey visible aspects of wildlife health with camera traps. Apparently mangy coyotes were associated with low-density forested neighbourhoods, which may offer vegetated areas while containing sources of anthropogenic resources. This association may contribute to human-wildlife conflict and reinforces posited relationships between infection risk and habitat use. More generally, our model could provide detection-corrected occupancy estimates of visible characteristics that vary by image such as body condition or injuries.