Integrating citizen science and remotely sensed data to help inform time-sensitive policy decisions for species of conservation concern. (September 2019)

• Record Type: Journal Article
• Authors: Long, Ashley M.; Pierce, Brian L.; Anderson, Amanda D.; Skow, Kevin L.; Smith, Addie; Lopez, Roel R.
• Is Part Of: Biological conservation. Volume 237(2019)
• Page Start: 463
• Page End: 469
• Publication Date: 2019-09
• Subjects: Anthus spragueii -- Citizen science -- Endangered Species Act -- Species distribution models -- Species Status Assessment -- Sprague's pipit; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2019.07.025
• Languages: English
• ISSNs: 0006-3207

Abstract

Abstract: The United States Fish and Wildlife Service (USFWS) uses a Species Status Assessment (SSA) framework to inform Endangered Species Act (ESA) policy decisions. A major challenge for development of SSAs includes inconsistent or incomplete monitoring throughout a species' range, which can result from inadequate time and funding for data collection prior to final rulings. In 2014, the USFWS initiated an SSA for the Sprague's pipit ( Anthus spragueii ; hereafter pipit), a migratory songbird scheduled for consideration as Threatened or Endangered in fall 2015. At the time, researchers had no field data to identify the spatial distribution of habitat across the geographic extent of the pipit's wintering grounds or to forecast the species' response to probable future scenarios of environmental conditions or conservation efforts during winter. In addition, the timing of the ESA decision precluded range-wide surveys on the pipit's wintering grounds. We present an SSA case study to demonstrate how citizen science and remotely sensed data could be integrated to help inform time-sensitive policy decisions for species of conservation concern. We developed three independent estimates of potential pipit habitat, and we assumed that spatial congruence among models provided increased evidence of habitat likely to support our focal species. We do not suggest that our approach replace more robust analyses, but rather illustrate an alternative strategy to obtain baseline information for SSAs and other policy decisions when data and time are lacking.