Citizen Science Data Collection for Integrated Wildlife Population Analyses

Citizen science, or community science, has emerged as a cost-efficient method to collect data for wildlife monitoring. To inform research and conservation, citizen science sampling designs should collect data that match the robust statistical analyses needed to quantify species and population patterns. Further increasing the contributions of citizen science, integrating citizen science data with other datasets and datatypes can improve population estimates and expand the spatiotemporal extent of inference. We demonstrate these points with a citizen science program called iSeeMammals developed in New York state in 2017 to supplement costly systematic spatial capture-recapture sampling by collecting opportunistic data from one-off observations, hikes, and camera traps. iSeeMammals has initially focused on the growing population of American black bear (Ursus americanus), with integrated analysis of iSeeMammals camera trap data with systematic data for a region with a growing bear population. The triumvirate of increased spatial and temporal coverage by at least twofold compared to systematic sampling, an 83% reduction in annual sampling costs, and improved density estimates when integrated with systematic data highlight the benefits of collecting presence-absence data in citizen science programs for estimating population patterns. Additional opportunities will come from applying presence-only data, which are oftentimes more prevalent than presence-absence data, to integrated models. Patterns in data submission and filtering also emphasize the importance of iteratively evaluating patterns in engagement, usability, and accessibility, especially focusing on younger adult and teenage demographics, to improve data quality and quantity. We explore how the development and use of integrated models may be paired with citizen science project design in order to facilitate repeated use of datasets in standalone and integrated analyses for supporting wildlife monitoring and informing conservation.

Anticipation of common buzzard population patterns in the changing UK landscape

Harmonious coexistence between humans, other animals and ecosystem services they support is a complex issue, typically impacted by landscape change, which affects animal distribution and abundance. In the last 30 years, afforestation on grasslands across Great Britain has been increasing, motivated by socio-economic reasons and climate change mitigation. Beyond expected benefits, an obvious question is what are the consequences for wider biodiversity of this scale of landscape change. Here, we explore the impact of such change on the expanding population of common buzzards Buteo buteo , a raptor with a history of human-induced setbacks. Using Resource-Area-Dependence Analysis (RADA), with which we estimated individuals' resource needs using 10-day radio-tracking sessions and the 1990s Land Cover Map of GB, and agent-based modelling, we predict that buzzards in our study area in lowland UK had fully recovered (to 2.2 ind km −2 ) by 1995. We also anticipate that the conversion of 30%, 60% and 90% of economically viable meadow into woodland would reduce buzzard abundance nonlinearly by 15%, 38% and 74%, respectively. The same approach used here could allow for cost-effective anticipation of other animals' population patterns in changing landscapes, thus helping to harmonize economy, landscape change and biodiversity.

Archaeology, demography and life history theory together can help us explain past and present population patterns

Population matters. Demographic patterns are both a cause and a consequence of human behaviour in other important domains, such as subsistence, cooperation, politics and culture. Demographers interested in contemporary and recent historical populations have rich data at their fingertips; the importance of demography means many interested parties have gathered demographic data, much of which is now readily available for all to explore. Those interested in the demography of the distant past are not so fortunate, given the lack of written records. Nevertheless, the emergence in recent years of a new interest in the demography of ancient populations has seen the development of a range of new methods for piecing together archaeological, skeletal and DNA evidence to reconstruct past population patterns. These efforts have found evidence in support of the view that the relatively low long-term population growth rates of prehistoric human populations, albeit ultimately conditioned by carrying capacities, may have been owing to ‘boom–bust’ cycles at the regional level; rapid population growth, followed by population decline. In fact, this archaeological research may have come to the same conclusion as some contemporary demographers: that demography can be remarkably hard to predict, at least in the short term. It also fits with evidence from biology that primates, and particularly humans, may be adapted to environmental variability, leading to associated demographic stochasticity. This evidence of the fluctuating nature of human demographic patterns may be of considerable significance in understanding our species' evolution, and of understanding what our species future demographic trajectories might be. This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’.