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Ruiz-Gutierrez, V.

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

3 recordsLinked to original sources

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

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

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