Biology subjects

Ruiz-Gutierrez, V.

Publications and source records attributed to Ruiz-Gutierrez, V..

7 recordsLinked to original sources

bioRxiv2025

Differential Avian Responses to Coffee Farming Lead to Community Homogenization in a Working Landscape in Jardin, Colombia.

In Colombia, coffee production has an ingrained cultural and economic importance. Coffee is cultivated in biodiverse areas using a variety of practices ranging from sun-exposed monocultures to mixed and shaded plantations. Management practices on this working landscape alter the composition of bird communities. We hypothesize that coffee agroecosystems homogenize bird communities by favoring the occupancy of non-forest dependent bird species and deterring forest dependent birds. We evaluate the effects of coffee plantations and associated metrics of vegetation structure on a subset of bird species in an agroforestry landscape in the Western Andes in Colombia and evaluate the hypothesis of community homogenization. We collected data in two consecutive years in 153 sites in coffee plantations and other habitats in Jardin, Colombia. In order to evaluate birds response to changes in the working landscape we made single-season occupancy models and used five covariates: coffee (binary covariate), foliage height diversity (FHD) and canopy height (CH) as proxies for coffee management practices, human footprint (LHFI), and elevation. Finally, we used generalized dissimilarity models (GDM) with the same covariates and geographical distance to evaluate the homogenization hypothesis among coffee sites. We identified 193 species (six endangered and five endemics) and modeled occupancy of 74 species. Coffee plantations significantly decreased the occupancy of 14 species while 13 were favored. In general, non-forest dependent species preferred lower FHD and lower CH values, and occurred at lower elevations with high LHFI. On the contrary, forest dependent species preferred higher FHD and CH, and were found at higher elevations. The GDM with best fit supported the hypothesis that coffee sites tend to be more similar than no-coffee sites, and that elevation and FHD explained most of the variation in dissimilarity. The working landscape in Jardin holds an important community of birds but coffee plantations are driving its homogenization. We anticipate that non-forest dependent birds will continue to colonize working landscapes, unless structural vegetation changes are promoted. Increasing FHD and CH is a potential strategy to improve forest dependent bird occupancy and reduce homogenization in Jardin.

ecology↗

bioRxiv2024

Integrated Movement Models for Individual Tracking and Species Distribution Data

O_LIWhile the quantity, quality, and variety of movement data has increased, methods that jointly allow for population- and species-level movement parameters to be estimated are still needed. We present a formal data integration approach to combine individual-level movement and population-level distribution data. We show how formal data integration can be used to improve precision of individual and population level movement parameters and allow additional population level metrics (e.g., connectivity) to be formally quantified. C_LIO_LIWe describe three components needed for an Integrated Movement Model (IMM): a model for individual movement, a model for among-individual heterogeneity, and a model to quantify changes in species distribution. We outline a general IMM framework and develop and apply a specific stochastic differential equation model to a case study of telemetry and species distribution data for golden eagles in western North American during spring migration. C_LIO_LIWe estimate eagle movements during spring migration from data collected between 2011 and 2019. Individual heterogeneity in migration behavior was modeled for two sub-populations, individuals that make significant northward migrations and those that remained in the southern Rocky Mountain region through the summer. As is the case with most tracking studies, the sample population of individual telemetered birds is not representative of the population, and underrepresents the proportion of long-distance migrants in. The IMM was able to provide a more biological accurate subpopulation structure by jointly estimating the structure using the species distribution data. In addition, the integrated approach a) improves accuracy of other estimated movement parameters, b) allows us to estimate the proportion of migratory and non-migratory birds in a given location and time, and c) estimate future spatio-temporal distributions of birds given a wintering location, which provide estimates of seasonal connectivity and migratory routes. C_LIO_LIWe demonstrate how IMMs can be successfully used to address the challenge of estimating accurate population level movement parameters. Our approach can be generalized to a broad range of available movement models and data types, allowing us to significantly improve our knowledge of migration ecology across taxonomic groups, and address population and continental level information needs for conservation and management. C_LI

ecology↗

bioRxiv2020

Integrating tracking and resight data from breeding Painted Bunting populations enables unbiased inferences about migratory connectivity and winter range survival

Archival geolocators have transformed the study of small, migratory organisms but analysis of data from these devices requires bias correction because tags are only recovered from individuals that survive and are re-captured at their tagging location. We show that integrating geolocator recovery data and mark-resight data enables unbiased estimates of both migratory connectivity between breeding and non-breeding populations and region-specific survival probabilities for wintering locations. Using simulations, we first demonstrate that an integrated Bayesian model returns unbiased estimates of transition probabilities between seasonal ranges and to determine how different sampling designs influence estimability of transition probabilities. We then parameterize the model with tracking data and mark-resight data from declining Painted Bunting (Passerina ciris) populations breeding in the eastern United States, hypothesized to be threatened by the illegal pet trade in parts of their Caribbean, non-breeding range. Consistent with this hypothesis, we found that male buntings wintering in Cuba were 20% less likely to return to the breeding grounds than birds wintering elsewhere in their range. Improving inferences from archival tags through proper data collection and further development of integrated models will advance our understanding of full annual cycle ecology of migratory species.

ecology↗

bioRxiv2019

Integrating citizen science data with expert surveys improves the accuracy and range of inference of species distribution models

Information on species habitat associations and distributions, across a wide range of spatial and temporal scales, are a fundamental source of ecological knowledge. However, collecting biological information at relevant scales if often cost prohibitive, although it is essential for framing the broader context of more focused research and conservation efforts. Citizen-science data has been signaled as an increasingly important source of biological information needed to fill in data gaps needed to make more comprehensive and robust inferences on species distributions. However, there are perceived trade-offs of combining highly structured, scientific survey data with largely unstructured, citizen-science data. As a result, the focus of most methodological advances to combine these sources of information has been on treating these sources as independent. The degree to which each source of information is allowed to directly inform a common underlying process (e.g. species distribution) depends on the perceived quality of the data. In this paper, we explore these trade-offs by applying a simplified approach of filtering citizen-science data to resemble structured survey data, and analyze both sources of data under a common framework. To accomplish this, we explored ways of integrating high-resolution survey data on shorebirds in the northern Central Valley of California with observations in eBird for the entire region that were filtered to improve their quality. The integration of survey data with the filtered citizen-science data in eBird resulted in improved inference and predictive ability, and increased the extent and accuracy of inferences on shorebirds for the Central Valley. The structured surveys were found to improve the overall accuracy of ecological inference based only on citizen-science data, by increasing the representation of data collected from high quality habitats for shorebirds (e.g. rice fields). The practical approach we have shown for data integration can be also be used to improve the efficiency of designing biological surveys in the context of larger, citizen-science monitoring efforts, ultimately reducing the financial and time expenditures typically required of monitoring programs and focused research. The simple processing and filtering method we present can be used to integrate other types of data (e.g. camera traps) with more localized efforts (e.g. research projects), ultimately improving our ecological knowledge on the distribution and habitat associations of species of conservation concern worldwide.

ecology↗

bioRxiv2018

Finding the signal in the noise of Citizen Science Observations

While many observations of species are being collected by citizen science projects worldwide, it can be challenging to identify projects collecting data that effectively monitor biodiversity. Over the past several years the allure of taking a \"Big Data\" approach has provided the opportunity to gather massive quantities of observations via the Internet, too often with insufficient information to describe how the observations were made. Information about species populations -- where and when they occur and how many of them are there -- (i.e., the signal) can be lost because insufficient information is gathered to account for the inherent biases in data collection (i.e., the noise). Here we suggest that citizen science projects that have succeeded in motivating large numbers of participants, must consider factors that influence the ecological process that affect species populations as well as the observation process that determines how observations are made. Those citizen science projects that collect sufficient contextual information describing the observation process can be used to generate increasingly accurate information about the distribution and abundance of organisms. We illustrate this using eBird as a case study, describing how this citizen science platform is able to collect vital contextual information on the observation process while maintaining a broad global constituency of participants. We highlight how eBird provides information with which to generate biodiversity indicators -- specifically distribution, abundance, and habitat associations -- across the entire annual cycle, even for populations of long distance migratory birds, a highly challenging taxon.

ecology↗

bioRxiv2018

Using citizen science data in integrated population models to inform conservation decision-making

Analysis of animal population status and change are core elements of ecological research and critical for prioritizing conservation actions. Traditionally, count-based data from structured surveys have been the main source of information used to estimate trends and changes in populations. In the past decade, advances in integrated population models (IPMs) have allowed these data to be combined with other data sources (e.g., observations of marked individuals). IPMs have allowed researchers to determine the direction and magnitude of a species population trajectory and to test underlying mechanisms. For many species, life-history characteristics (e.g., low site-fidelity), low abundance and/or low detection probability make it difficult to collect sufficient data; thus, IPMs for these species are difficult to employ. We used count data from eBird to estimate population trends for one such species, the tricolored blackbird (Agelaius tricolor). We combined estimates of relative abundance with banding and nesting data. Our joint estimation of demographic rates allowed us to evaluate their individual contributions to the population growth rate. We suggest that investments in increasing reproductive success and recruitment are the most likely conservation strategies to increase the population. The extensive survey efforts of citizen scientists aided the employment of IPMs to inform conservation efforts.\n\nData AccessibilityShould the manuscript be accepted, the data supporting the results will be published along with the manuscript. The eBird data used for analyses in this manuscript may be downloaded from https://ebird.org/data/download.

ecology↗

bioRxiv2018

Modeling Avian Full Annual Cycle Distribution and Population Trends with Citizen Science Data

Information on species distributions and abundances, and how these change over time are central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at relevant scales across range-wide extents for two main reasons. First, local and regional processes that affect populations vary throughout the year and across species ranges, requiring fine-scale, year-round information across broad -- sometimes hemispheric -- spatial extents. Second, while citizen science projects can collect data at these scales, using these data requires appropriate analysis to address known sources of bias. Here we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and relative abundance with enough spatiotemporal resolution to support inference across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intra-annual estimates of the associations between species and the local environment, and inter-annual trends in relative abundance. This is the first example of an analysis to capture intra- and inter-annual distributional dynamics across the entire range of a broadly distributed, highly mobile species.

ecology↗