RESUMEN
Increasing costs are challenging the capacity for resource management agencies to keep up with mounting needs for robust data about fish populations and their habitats. Furthermore, trust among scientists, government agencies, and the public is fundamental to effective fisheries management, and relations among these three groups are increasingly strained when decisions about fishing limits are made (or are perceived to be made) on the basis of limited information or analysis. In the South Atlantic region of the United States, the South Atlantic Fishery Management Council has begun building a citizen science program to increase the quantity and quality of data used for fisheries management decisions throughout the region and to build trust and foster mutual understanding among those involved in the process. The goal is to build on existing management infrastructure to address key challenges to managing fisheries for long-term sustainability. In the present article, we examine the collaborative process used to establish the program.
RESUMEN
Biodiversity is being lost at an unprecedented rate, and monitoring is crucial for understanding the causal drivers and assessing solutions. Most biodiversity monitoring data are collected by volunteers through citizen science projects, and often crucial information is lacking to account for the inevitable biases that observers introduce during data collection. We contend that citizen science projects intended to support biodiversity monitoring must gather information about the observation process as well as species occurrence. We illustrate this using eBird, a global citizen science project that collects information on bird occurrences as well as vital contextual information on the observation process while maintaining broad participation. Our fundamental argument is that regardless of what species are being monitored, when citizen science projects collect a small set of basic information about how participants make their observations, the scientific value of the data collected will be dramatically improved.
RESUMEN
Citizen science involves a range of practices involving public participation in scientific knowledge production, but outcomes evaluation is complicated by the diversity of the goals and forms of citizen science. Publications and citations are not adequate metrics to describe citizen-science productivity. We address this gap by contributing a science products inventory (SPI) tool, iteratively developed through an expert panel and case studies, intended to support general-purpose planning and evaluation of citizen-science projects with respect to science productivity. The SPI includes a collection of items for tracking the production of science outputs and data practices, which are described and illustrated with examples. Several opportunities for further development of the initial inventory are highlighted, as well as potential for using the inventory as a tool to guide project management, funding, and research on citizen science.
RESUMEN
Citizen science involves a range of practices involving public participation in scientific knowledge production, but outcomes evaluation is complicated by the diversity of the goals and forms of citizen science. Publications and citations are not adequate metrics to describe citizen-science productivity. We address this gap by contributing a science products inventory (SPI) tool, iteratively developed through an expert panel and case studies, intended to support general-purpose planning and evaluation of citizen-science projects with respect to science productivity. The SPI includes a collection of items for tracking the production of science outputs and data practices, which are described and illustrated with examples. Several opportunities for further development of the initial inventory are highlighted, as well as potential for using the inventory as a tool to guide project management, funding, and research on citizen science.
RESUMEN
Over the past 20 years, thousands of citizen science projects engaging millions of participants in collecting and/or processing data have sprung up around the world. Here we review documented outcomes from four categories of citizen science projects which are defined by the nature of the activities in which their participants engage - Data Collection, Data Processing, Curriculum-based, and Community Science. We find strong evidence that scientific outcomes of citizen science are well documented, particularly for Data Collection and Data Processing projects. We find limited but growing evidence that citizen science projects achieve participant gains in knowledge about science knowledge and process, increase public awareness of the diversity of scientific research, and provide deeper meaning to participants' hobbies. We also find some evidence that citizen science can contribute positively to social well-being by influencing the questions that are being addressed and by giving people a voice in local environmental decision making. While not all citizen science projects are intended to achieve a greater degree of public understanding of science, social change, or improved science -society relationships, those projects that do require effort and resources in four main categories: (1) project design, (2) outcomes measurement, (3) engagement of new audiences, and (4) new directions for research.