Socioeconomic development and ecological traits as predictors of human–bird conflicts

Because of the significant impacts on both human interests and bird conservation, it is imperative to identify patterns and anticipate drivers of human–bird conflicts (HBCs) worldwide. Through a global systematic review, following the PRISMA 2020 guidelines, we analyzed the socioeconomic factors and bird ecological traits driving the degree of knowledge and extent of HBCs. We included 166 articles published from 1971 to 2020 in our analyses through which we built a profile of the socioeconomic conditions of 52 countries with reported conflicts and the ecological traits of the 161 bird species involved in HBCs. Although HBC expanded worldwide, it had the greatest impact in less-developed countries (estimate 0. 66 [SE 0.13], p< 0.05), where agriculture is critical for rural livelihoods. Species with a relatively greater conflict extent had a relatively broader diet (estimate 0.80 [SE 0.22], p<0.05) and an increasing population trend (estimate 0.58 [SE 0.15], p<0.05) and affected human interests, such as agriculture and livestock raising. In countries with greater biodiversity, HBCs caused greater socioeconomic impacts than in more developed countries. Our results highlight the importance of understanding and addressing HBCs from multiple perspectives (ecological, sociocultural, and political) to effectively protect both biodiversity and local livelihoods.     

Lessons from other disciplines for setting management thresholds for biodiversity conservation

Successful, state-dependent management, in which the goal of management is to maintain a system in a desired state, involves defining the boundaries between different states. Once these boundaries have been defined, managers require a strategic action plan with thresholds that initiate management interventions to either maintain or return the system to a desired state. This approach to management is widely used across diverse industries from agriculture, to medicine, to information technology, but it has only been adopted in conservation management relatively recently. Conservation practitioners have expressed a willingness to integrate this structured approach in their management systems, but they have also voiced concerns, including lack of a robust process for doing so. Given the widespread use of state-dependent management in other fields, we conducted an extensive review of the literature on threshold-based management to gain insight into how and where it is applied and identify potential lessons for conservation management. We identified 22 industries using 75 different methods for setting management thresholds in 843 studies. Methods spanned six broad approaches, including expert driven, statistical, predictive, optimization, experimental, and artificial intelligence methods. The objectives of each of these studies influenced the approaches used, including the methods for setting thresholds and selecting actions, and the number of thresholds set. The role of value judgments in setting thresholds was clear; studies across all industries frequently involved experts in setting thresholds, often accompanied by computational tools to simulate the consequences of proposed thresholds under different conditions. Of the 30 conservation studies examined, two-thirds used expert-driven methods, consistent with prior evidence that experience-based information often drives conservation management decisions. The methods we identified from other disciplines could help conservation decision makers set thresholds for management interventions in different contexts, linking monitoring to management actions and ensuring that conservation interventions are timely and effective.