Biology subjects

Bozzuto, C.

Publications and source records attributed to Bozzuto, C..

3 recordsLinked to original sources

bioRxiv2025

The forecasted mean of 80 percent of wild populations and communities shows no change, and why

Many retrospective analyses of biodiversity trends reveal a complex picture, including significant declines but also increases. However, prospective analyses (i.e. what near-term trends to expect) remain comparatively rare. Here, we generate and assess forecasts for approximately 43,000 population-level and 10,000 community-level time series from localities across the globe and covering taxa across the Tree of Life. Using unobserved components models and model selection, we found that only 23.5% of wild populations exhibit forecasted time trends (with increasing and decreasing trends roughly equal), while 76.5% show a forecasted constant mean. For communities (temporal - and {beta}-diversity), this figure rises to 84.0%. We identified high variation in the rate of change, var(RoC), as the most important predictor of a forecasted constant mean, and it scaled more strongly with intrinsic ecological dynamics than observation noise. Furthermore, biological structure (taxonomy, life-history traits, and locality) contributed to the identification of trends, highlighting that biological factors underlie, in part, predictions of trends. In summary, despite time trends being identifiable in ecological time-series data, parsimonious statistical models will very often forecast no change. Our results suggest that the absence of directional change may be the norm rather than the exception across the Tree of Life.

ecology↗

bioRxiv2024

Towards an eco-epidemiological framework for managing freshwater crayfish communities confronted with crayfish plague

Wildlife diseases figure prominently among the main causes of biodiversity loss worldwide. Especially fungal and fungus-like pathogens are on the rise, wreaking havoc across the tree of life by threatening species persistence and destabilizing ecosystems. A worrisome example are freshwater crayfish species in Eurasia and Oceania, facing the dual challenge of introduced competitive crayfish species and an introduced water mold (Aphanomyces astaci) causing crayfish plague. A. astaci locally extinguishes susceptible native crayfish populations, while non-native individuals (mostly from North America) remain largely unaffected. Despite its significant impact and its [~]150 years of presence in Europe, studies and disease management recommendations for crayfish plague that are firmly rooted in epidemiological theory are scarce. Here, we present a practical eco-epidemiological framework to understand how multi-species crayfish communities react to crayfish plague introductions. The framework is based on the observation that the dynamics of crayfish communities are mainly determined by life-history characteristics, within- and among-species competition, effects of generalist predators (including fishing), and host-pathogen interactions. From this ecological and epidemiological context, we derive fundamental epidemiological metrics, single-host species and community-level basic reproduction numbers (R0). We investigate how host species densities affect the likelihood of a disease outbreak in a crayfish community, and we demonstrate that a communitys R0 value is simply the sum of the communitys single-host species R0 values, adjusted for competition and predation. We further demonstrate how R0 can be used to guide preventative and mitigation actions for crayfish communities. For example, we show how R0 expressions - even without a detailed parametrization - can be used to construct regional risk rankings for different crayfish communities, for an effective allocation of resources to local conservation plans. Our eco-epidemiological framework will also be of interest to the management of other aquatic host-pathogen systems with water-borne pathogen transmission as the main route of pathogen spread.

ecology↗

bioRxiv2023

Predictability of ecological and evolutionary dynamics in a changing world

Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures menacing life on Earth. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations about the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (that is, the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes, and mammals (i) 50% of the populations are predictable at most one year in advance, and (ii) the median one-year-ahead predictive power corresponds to a sobering prediction R2 of approximately 20%. Nonetheless, predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, considering multivariate time series, incorporating explanatory variables or accounting for time trends (environmental forcing) can enhance predictability. To effectively address the urgent challenge of biodiversity loss, researchers and practitioners must be aware of the predictive information within the available data and explore efficient ways to leverage this information for environmental stewardship.

ecology↗