Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning.

Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigated at state scales, but a regional model to predict locations of new infections can guide increasingly efficient surveillance efforts. We predicted CWD incidence by county using CWD surveillance data depicting white-tailed deer (Odocoileus virginianus) in 16 eastern and midwestern US states. We predicted the binary outcome of CWD-status using four machine learning models, utilized five-fold cross-validation and grid search to pinpoint the best model, then compared model predictions against the subsequent year of surveillance data. Cross validation revealed that the Light Boosting Gradient model was the most reliable predictor given the regional data. The predictive model could be helpful for surveillance planning. Predictions of false positives emphasize areas that warrant targeted CWD surveillance because of similar conditions with counties known to harbor CWD. However, disagreements in positives and negatives between the CWD Prediction Web App predictions and the on-the-ground surveillance data one year later underscore the need for state wildlife agency professionals to use a layered modeling approach to ensure robust surveillance planning. The CWD Prediction Web App is at https://cwd-predict.streamlit.app/ .

Between conflict and reciprocal habituation: Human-wild boar coexistence in urban areas.

Urbanization is an ongoing global environmental change. Wildlife may respond using anthropized environments and resources, which is known as synurbization, creating human-wildlife interactions. Wild boar (Sus scrofa) populations have become common in urban areas, including the metropolitan area of Barcelona. Humans respond to wild boars in urban environments either habituating, with lower conflict perception and higher wild boar acceptance, or sensitizing, with reduced tolerance towards wild boars. Since citizen response influences conflict management, this study analysed the drivers of human responses, which should allow adopting socially-accepted measures to manage synurbic wild boar populations. Interviews to 1956 Barcelona citizens were performed, grouping the response variables to score citizen and urban characteristics, as well as citizen lay-knowledge, emotions, experiences, and perception of wild boar. Five citizen clusters were identified: cluster 1 (3.3 %), highly habituated and active wild boar feeder; cluster 2 (11.3 %), habituated to wild boars with positive feelings; cluster 3 (19.8 %), not habituated nor sensitized, willing to maintain urban wild boar populations; cluster 4 (29.1 %), sensitized and concerned, defending to reduce wild boar; and cluster 5 (40.1 %), highly sensitized and proposing to reduce or even eliminate wild boar. Positive attitudes associated wild boar to aesthetic value, closeness to nature and sympathy, and were more frequent in young citizens with urban background and high education, animal lovers habituated to wild boar through contact without negative experiences. Conversely, negative attitudes were concerned about city fouling, safety or health, accepted lethal management measures, and were more frequent in older citizens with rural background, lower education, low contact with wild boar or sensitized through negative experiences. We document for the first time the sensitization and reciprocal habituation of humans to wild boar in urban areas. The identification of the drivers of citizen attitudes towards urban wildlife should be useful to design socially-accepted management measures.

Infection prediction in swine populations with machine learning.

The pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model's ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of [Formula: see text] on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms.

Assessing mammal trapping standards in wild boar drop-net capture.

Applying contemporary trapping standards when managing wildlife should no longer be an option, but a duty. Increasing wild boar populations originate a growing number of conflicts and hunting is the only cost-effective management option in most cases. However, new scenarios where hunting is unfeasible emerge and trapping necessities cope with lacking regulatory frameworks and technical guidelines. In this research, we evaluated drop nets, a capture method not considered by the international trapping standards, to capture Eurasian wild boar (Sus scrofa), a wildlife species not included in the list of mammal species under the scope of the Agreement on International Humane Trapping Standards (AIHTS). Less than 20% of the captured wild boars presented moderate or severe injuries attributable to the capture method, hence fulfilling the acceptance thresholds of the outdated AIHTS. Based on the new standards thresholds of acceptance, the humaneness of drop-nets in our study ranged 66-78%, under the 85% required. The capture success and selectivity were 100%, as ensured by operator-driven triggering, which should be considered the main strengths of this method, together with the minimization of animal suffering owing the short duration of the stressful situation. Additionally, in spite of the socially adverse environment, with people contrary to wild boar removal, no disturbances against the capture system or operations occurred. This is the first assessment of a drop-net capture method according to internationally accepted mammal trapping standards, with unconclusive results. However, there is a need for adapted procedures and thresholds of acceptance aimed at not-mechanical traps in general, and specifically at drop-nets. Compared to other live-capture methods, drop-nets minimize the duration of the stressful situation -at the expense of a strong adrenergic acute response-, maximize the probabilities of capturing entire sounders of prosocial species, which may be also considered as more humane, and has the ability to coordinate higher values of capture success, absolute selectivity and adaptability to difficult environments.

Environmental predictors of filarial infection in Amazonian primates: Ecological factors and primate filarial infection.

Filarial nematode infections are common in primates, but have received little attention in the Neotropics. Epidemiological data on filarial infections in primates are still too sparse to fully understand the complex of this parasitism, especially because of the difficulty in studying the ecology and epidemiology of wild primates.. We describe natural infections by Dipetalonema parasitizing 211 primates belonging to eight free-living primate genera in Amazonia, and assess the relationships between parasitic indicators and climatic (rainfall and river level), ecological (fruiting periods of plants) and biological (sex, species' body mass, group size and density) factors. The overall prevalence was 64.4% (95% CI: 64.0 - 64.9); parasitic mean abundance (N filariae per individual) and parasitic mean intensity (N filariae per infected host) of infection were 11.9 (95% CI: 8.3 - 15.6) and 18.4 (95% CI: 13.4 - 23.4) filariae/individual, respectively. Although we observed differences in parasitic parameters among primate genera, there was no correlation between parasitic parameters with density, body mass or group size. Sapajus, Cebus and Lagothrix had the highest prevalence and parasitic mean intensity. Using Lagothrix lagotricha poeppigii, the most sampled species (n = 92), as a model, we found that the number of filariae per infected host was associated with fruit production in swamp forests during the dry season, the time of food scarcity. The long periods of food shortage may cause environmental stress on primates, impairing their immune defenses and leading to increased parasite load but not affecting infection prevalence. However, the lack of information on vector ecology, key to understand risk factors associated to infection rate, prevents confirming the existence of an infection pattern dependent on food availability.

Use of Fertility Control (Nicarbazin) in Barcelona: An Effective yet Respectful Method towards Animal Welfare for the Management of Conflictive Feral Pigeon Colonies.

This study describes a three-year evaluation (2017-2019) of a fertility control protocol using nicarbazin (Ovistop®) to reduce the abundance of the most conflictive colonies of feral pigeon, Columba livia var. domestica, in Barcelona, Spain, as a long-term strategy based on animal welfare. The treatment was supplied to 34 pigeon colonies by automatic hopper feeders installed in public areas. A superiority study and a population monitoring study were carried out to evaluate differences in the abundance of the colonies, as well as the proportion of juveniles, the possible intake of nicarbazin by non-target species and the movement of individuals among colonies. The results showed statistical differences in the population trends between the test (-22.03%) and control (+12.86%) groups, and a significant steady decreasing trend in the pigeon abundance (-55.26%) was registered until the end of 2019. The proportion of juveniles was significatively lower in the test colonies, and a non-target species (Eurasian collared doves, Streptopelia decaocto) was observed consuming in a residual form. The protocol using nicarbazin is able to both control the abundance of pigeons, with no impact over non-target species, and respond to the public interest about animal welfare by providing an ethical method to manage overabundant and/or conflictive populations.

Wild boar in the city: Phenotypic responses to urbanisation.

Urbanisation is a global human-induced environmental change and one of the most important threats to biodiversity. To survive in human-modified environments, wildlife must adjust to the challenging selection pressures of urban areas through behaviour, morphology, physiology and/or genetic changes. Here we explore the effect of urbanisation in a large, highly adaptable and generalist urban adapter species, the wild boar (Sus scrofa, Linnaeus 1758). From 2005 to 2018, we gathered wild boar data and samples from three areas in NE Spain: one urban (Barcelona municipality, n = 445), and two non-urban (Serra de Collserola Natural Park, n = 183, and Sant Llorenç del Munt i Serra de l'Obac Natural Park, n = 54). We investigated whether urbanisation influenced wild boar body size, body mass, body condition, and the concentration of serum metabolites, considering also the effect of age, sex and use of anthropogenic food resources. Wild boars from the urban area had larger body size, higher body mass, better body condition, and a higher triglyceride and lower creatinine serum concentrations than non-urban wild boars. In addition, urban wild boars consumed food from anthropogenic origin more frequently, which suggests that differences in their diet probably induced the biometric and the metabolic changes observed. These responses are probably adaptive and suggest that wild boars are thriving in the urban environment. Our results show that urbanisation can change the morphological and physiological traits of a large mammal urban adapter, which may have consequences in the ecology and response to urban selection pressures by the species. The phenotypic plasticity shown by wild boars provides both further and new evidence on the mechanisms that allow urban adapter species of greater size to respond to urbanisation, which is expected to continue growing globally over the coming decades.

Assessing methods to live-capture wild boars (Sus scrofa) in urban and peri-urban environments.

BACKGROUND: Wild boar (Sus scrofa) populations are increasing worldwide and invading urban areas. Live-capture can improve the management of this challenge, maximising efficiency, allowing scientific studies and potentially improving animal welfare. This study assesses teleanaesthesia, drop-net, corral trap and cage trap to live-capture wild boar in urban and peri-urban areas, evaluating efficiency and animal stress through haematology and serum biochemistry. METHODS: From 2012 to 2018, 655 wild boars were captured in 279 operations (drop-net=17, teleanaesthesia=186, cage trap=66 and corral trap=10) in the urban and peri-urban areas of Barcelona (Spain). Haematological and serum biochemical variables were determined in 145 wild boars (42 drop-netted, 41 teleanaesthetised, 38 cage-trapped and 24 corral-trapped). RESULTS: Performance (wild boars captured per operation) was highest for drop-net, followed by corral and cage traps, and finally teleanaesthesia. The three physical capture methods were more stressful than teleanaesthesia, causing a more intense physiological reaction, muscular damage, renal function impairment and homeostasis adaption. Stress response was predominantly adrenergic for drop-net and cortisol-induced for cage and corral traps. CONCLUSION: Teleanaesthesia is the choice in reactive urban situations thanks to its adaptability; drop-net effectively targets wild boars in peri-urban environments; cage and corral traps are useful as long-term methods in specific areas.

Stochastic assessment of management strategies for a Mediterranean peri-urban wild boar population.

Wild boar (Sus scrofa) population spread into urban and periurban areas has exacerbated conflicts with humans. There is a need for planned wild boar management strategies, and Population viability analysis (PVA) combined with perturbation analyses allow the assessment of the management effort of control methods. Our study aims to develop stochastic predictive models of the increasing wild boar population of the 80 km2 peri-urban Mediterranean area of Collserola Natural Park (CNP), located near Barcelona, Spain, as well as assessing specific management measures (including reduced food availability, selective harvest, and reduction in fertility). Population parameters were estimated from previously published census and hunting data provided by the CNP and the local hunting administration. The results revealed that under the current conditions the CNP wild boar population will continue to increase. The most efficient strategy to reduce wild boar abundance was a combination of reducing supplementary anthropogenic food resources and selective removal of juvenile (<1 year) and yearling (1-2 years) wild boar. These strategies will probably be also the most efficient ones in other oversupplemented increasing wild boar populations in similar situations, although specific studies will be needed to fine-tune the best management option for each context. PVA allows the prediction of future population trends and the assessment of the efficacy and efficiency of potential management strategies before implementing management measures.

Urban wild boars prefer fragmented areas with food resources near natural corridors.

Wild boar populations are expanding throughout the world and intruding into periurban and urban areas. In the last years, wild boar has colonized several European cities, including our study area, the city of Barcelona. It is required to identify the main factors driving wild boar into urban areas prior to establish management measures. We built Boosted Regression Trees (BRT) using 3148 wild boar presences registered in the urban area of Barcelona from 2010 to 2014 to identify the variables correlated with these presences. The variables analysed included proxies for distance to source population, urban food resources, climate and urban habitat structure. Wild boars enter the urban area from close natural habitat using corridors such as streams, preferably in fragmented urban environment, looking for food such as urban green areas or dry pet food from cat colonies. Wild boar presence is higher in spring possibly due to the births of piglets and the dispersion of yearlings during that season, and also when natural resources in the Mediterranean habitat fail to satisfy the nutritional requirements of the wild boar population during the summer season. Management measures derived from this study are currently being applied in the city of Barcelona, including vegetation clearings in the wild boar entrance areas and an awareness campaign aimed at reducing the anthropogenic food availability for wild boars. The methodology used can be applied to other cities with wild boar or even other wildlife species issues. The comparison between the factors attracting wild boars into different urban areas would be helpful to understand the global phenomenon.

Water contamination from oil extraction activities in Northern Peruvian Amazonian rivers.

Oil extraction activities in the Northern Peruvian Amazon have generated a long-standing socio-environmental conflict between oil companies, governmental authorities and indigenous communities, partly derived from the discharge of produced waters containing high amounts of heavy metals and hydrocarbons. To assess the impact of produced waters discharges we conducted a meta-analysis of 2951 river water and 652 produced water chemical analyses from governmental institutions and oil companies reports, collected in four Amazonian river basins (Marañon, Tigre, Corrientes and Pastaza) and their tributaries. Produced water discharges had much higher concentrations of chloride, barium, cadmium and lead than are typically found in fresh waters, resulting in the widespread contamination of the natural water courses. A significant number of water samples had levels of cadmium, barium, hexavalent chromium and lead that did not meet Peruvian and international water standards. Our study shows that spillage of produced water in Peruvian Amazon rivers placed at risk indigenous population and wildlife during several decades. Furthermore, the impact of such activities in the headwaters of the Amazon extended well beyond the boundaries of oil concessions and national borders, which should be taken into consideration when evaluating large scale anthropogenic impacts in the Amazon.