Biology subjects

Saracco, J. F.

Publications and source records attributed to Saracco, J. F..

4 recordsLinked to original sources

bioRxiv2026

An Integrated Population Model to Incorporate Spatio-Temporal Heterogeneity in Demographic Rates

O_LIDemographic processes in populations are inherently heterogeneous across both space and time. Many ecological models explicitly account for temporal heterogeneity in the demographic rates that govern these processes, but assume spatial homogeneity. Ignoring spatial heterogeneity can bias inference, limit predictive performance, and obscure key spatial structure in demographic rates. Integrated population models (IPMs) offer a powerful framework to estimate spatio-temporal demographic rates by combining diverse ecological data sources collected from multiple sampling locations. However, to accomplish this, IPMs face significant statistical and computational hurdles, including misalignment between different data sources and the need to efficiently account for residual spatial autocorrelation. C_LIO_LIWe present a novel Bayesian spatially explicit integrated population model (sIPM) which integrates population count and capture-recapture data from multiple sampling locations to estimate and predict continuous spatio-temporal demographic rates, such as survival, recruitment and population growth rate, across large geographic domains. This framework employs a joint likelihood approach with change of support to flexibly accommodate spatial and spatio-temporal data misalignment, and incorporates a nearest-neighbor Gaussian process to efficiently model residual spatial autocorrelation and generate spatial predictions. C_LIO_LIWe assess the performance of our sIPM through an extensive simulation study. Results show that our approach provides unbiased and precise estimates and predictions of spatio-temporal demographic rates, even in the presence of significant data misalignment and residual spatial autocorrelation. We demonstrate the utility of our method by analyzing data on Gray Catbirds (Dumetella carolinensis) from the North American Breeding Bird Survey and the Monitoring Avian Productivity and Survivorship program across the eastern coast of the United States from 2004-2014. This analysis results in maps of apparent survival, recruitment and population growth rate, thereby revealing important spatio-temporal variations in demographic rates that would have been obscured by traditional, spatially homogeneous IPMs. C_LIO_LIOur sIPM offers a robust and computationally efficient method for studying spatio-temporal variation in demographic processes across large areas, even in the presence of data misalignment and residual spatial autocorrelation. Ultimately, this framework, applicable to many ecological monitoring programs, facilitates the development of spatially targeted strategies necessary for effective conservation and management. C_LI

ecology↗

bioRxiv2023

Fast and flexible Bayesian Jolly Seber models and application to populations with transients

O_LIJolly Seber (JS) models are an appealing class of capture-recapture models for modeling open populations because they allow for inferences about an array of population parameters, including abundance, survival, and recruitment. Multiple formulations of JS models have been developed and include both maximum likelihood and Bayesian approaches. Bayesian approaches offer greater flexibility; however, they are often extremely slow when applied to moderate to large populations because the latent states of all observed individuals, as well as any potential unobserved individuals (parameter-expanded data augmentation), must be simulated at each time step. C_LIO_LIJS model implementations can be sped up dramatically through marginalization, whereby the conditional likelihoods of states are tracked for unique capture histories, rather than the simulated states of all individuals. Here we describe a marginalized implementation of a multistate JS model and compare its performance to that of an implementation using simulated discrete states. We fit models to data generated under two scenarios, one in which no data was missing and another in which 25% of data was randomly removed. To illustrate how marginalization can accommodate more complex models and datasets, we describe a modified version of the model for application to populations with transients and fit the model to simulated data and to data collected on Kentucky Warblers (Geothlypis formosa) as part of the Monitoring Avian Productivity and Survivorship (MAPS) program. C_LIO_LIBoth the discrete latent state and marginalized JS model implementations performed similarly with respect to bias and coverage; however, the marginalized implementation was roughly 1,000 times faster when no data were missing and 100 times faster when 25% of data was missing. The marginalized model accommodating transients also converged quickly and a more complex version of the model applied to the larger multi-site Kentucky Warbler data set yielded useful estimates of most parameters within a reasonable time frame (hours). C_LIO_LIGains in efficiency provided by marginalization shown here should stimulate additional study and development of this useful class of models and provide new opportunities for real-world applications to large complex data sets. C_LI

ecology↗

bioRxiv2022

Abiotic conditions shape spatial and temporal morphological variation in North American birds

Abiotic environmental conditions play a key role in driving the size and shape of organisms. Quantifying environment-morphology relationships is important not only for understanding the fundamental processes driving phenotypic diversity within and among species (1), but also for predicting how species will respond to ongoing global change (2). Despite a clear set of expectations motivated by ecological theory (3), broad evidence in support of generalizable effects of abiotic conditions, such as temperature (4), on spatial and temporal intraspecific morphological variation has been limited. Using standardized data from over 250,000 captures of 105 landbird species, we assessed intraspecific shifts in bird morphology since 1989 while simultaneously measuring spatial morphological gradients across the North American continent. Across bird species, we found strong spatial and temporal trends in body size, with warmer temperatures associated with smaller body sizes both at more equatorial latitudes and in more recent years. The magnitude of these thermal effects varied both across and within species, with results suggesting it is the warmest, rather than the coldest, temperatures driving both spatial and temporal trends. Across elevation, we found that body size declines as relative wing length increases, likely due to the benefits that longer wings confer for flight in thin air environments. Our results provide support for both existing and new large-scale ecomorphological gradients and highlight how the response of functional tradeoffs to abiotic variation drives morphological change. Significance StatementCharacterizing how the size and shape of organisms varies over space and time is key to understanding the processes that create ecological communities and for predicting how species will respond to climate change. Across more than 100 species of North American birds, we show that within species the size and shape of individuals varies substantially across space and time. Warmer temperatures are associated with smaller body sizes, likely due to the importance of body size for thermoregulation. As the climate continues to warm, these species will likely continue to shrink. We also provide the first large-scale evidence of an increase in wing length with elevation, a pattern that could be attributed to thinner air in high elevation environments.

ecology↗

bioRxiv2020

Genetic variation reveals individual-level climate tracking across the full annual cycle of a migratory bird

For migratory species, seasonal movements complicate local climate adaptation, as it is unclear whether individuals track climate niches across the annual cycle. In the migratory songbird yellow warbler (Setophaga petechia), we find a correlation between individual-level wintering and breeding precipitation but not temperature. Birds wintering in the driest regions of the Neotropics breed in the driest regions of North America. Individuals from drier regions also possess distinct morphologies and population responses to varying rainfall. We find a positive association between bill size and breeding season precipitation which, given documented climate-associated genomic variation, might reflect adaptation to local precipitation regimes. Relative abundance in the breeding range is linked to interannual fluctuations in precipitation, but the directionality of this response varies across geography. Together, our results suggest that variation in climate optima may exist across the breeding range of yellow warblers and provide a mechanism for selection across the annual cycle.

evolutionary biology↗