A multidisciplinary framework to assess the sustainability and acceptability of wildlife tourism operations

ABSTRACT Wildlife tourism is growing in popularity, diversity of target species, and type of tours. This presents difficulties for management policy that must balance the complex trade‐offs between conservation, animal welfare, and pragmatic concerns for tourist satisfaction and economic value. Here, we provide a widely applicable, multidisciplinary framework to assess the impacts of wildlife tourism focusing on industry tractability, socioeconomic values, and their effects on conservation, animal welfare, and ecosystem impacts. The framework accommodates and quantifies the complexity of factors influencing wildlife tourism management, including direct and indirect effects on target and nontarget species, and identifies priorities for future biological, socioeconomic, and cultural heritage research. When applied to white shark cage‐diving as a case study, the output demonstrates the utility of the framework for researchers, managers, and policy makers, and highlights the benefits of undertaking the assessment as an inclusive workshop to facilitate a more multidisciplinary assessment of wildlife tourism industries. The use of a universally applicable assessment framework will enable the identification of relevant factors to account for when managing wildlife tourism, provide an inventory of current knowledge, identify research needs, and semiquantitatively compare categories and target and nontarget species, leading to improved conservation outcomes for species and ecosystems

The impact of changing the cut-off threshold of the interferon-gamma (IFN-γ) assay for diagnosing bovine tuberculosis in Ireland

In Ireland, the interferon-gamma (IFN-γ) assay is routinely used as an ancillary test interpreted in parallel with the single intradermal comparative tuberculin test (SICTT) to maximize the detection of bovine tuberculosis (bTB) infected animals. Up until 2018, a positive test result was recorded in the IFN-γ ELISA assay following whole blood stimulation with purified protein derivative (PPD)-bovine (B), PPD-avian (A) and nil sample (N), using the interpretation criteria, B-N > 50 optical density units (OD), B > 100 and B-A > 0. Following a review of available data, the threshold of the B-A component changed to B-A > 80. As predicting the impact of changing the cut-off thresholds for the IFN-γ test de novo is challenging, the aims of this study were to follow animals that initially tested negative using the new IFN-γ assay interpretation criteria and investigate their future risk of disclosure with bTB, with a focus on animals that otherwise would have been removed when using the older interpretation criteria (0 < B-A ≤ 80). Enrolled animals (n = 28,669 cattle from 527 herds) were followed up for two years (2019–2021), or to point of bTB detection or death. At the end of follow-up, 1151 (4.0%) of enrolled animals were bTB cases. The majority of these cases were diagnosed using SICTT (80.5%). The cumulative number of positive animals that would have been removed if the old cut-off (0 < B-A ≤ 80) was used amounted to 1680 cattle (5.9% of the enrolled cohort). Of these, 127 (7.5%) were diagnosed with bTB during follow-up. In contrast, 1024 of the 1151 cattle which subsequently tested positive during the study period following a negative IFN-γ test would not have been identified with the old or new IFN-γ cut-off criteria. Survival analysis showed that animals that would have been removed under the old interpretation criteria were at increased risk of a positive diagnosis with bTB during follow-up compared to other test negative animals. A newly developed risk prediction model (using a Cox proportional hazard model) showed that age, animal number of SICTT tests, number of inconclusive SICTT tests, B-A (IFN-γ assay), B-N (IFN-γ assay), animals from store herds and the percentage of the rest of the herd that were positive during the breakdown were statistically significantly associated with bTB detection. However, inclusion of the IFN-γ OD variables did not show added value in terms of prediction performance of the model.</p