DOI: 10.5061/dryad.37pvmcvhv
title: Integrating dynamic processes into waterfowl conservation prioritization tools

description: Aim: Traditional approaches for including species’ distributions in
 conservation planning have presented them as long-term averages of
 variation. Like these approaches, the main waterfowl conservation
 targeting tool in the United States Prairie Pothole Region (US PPR) is
 based primarily on long-term averaged distributions of breeding pairs.
 While this tool has supported valuable conservation, it does not
 explicitly consider spatiotemporal changes in spring wetland availability
 and does not assess wetland availability during the brood rearing period.
 We sought to develop a modeling approach and targeting tool that
 incorporated these types of dynamics for breeding waterfowl pairs and
 broods. This goal also presented an opportunity for us to compare
 predictions from a traditional targeting tool based on long-term averages
 to predictions from spatiotemporal models. Such a comparison facilitated
 tests of the underlying assumption that this traditional targeting tool
 could provide an effective surrogate measure for conservation objectives
 such as brood abundance and climate refugia. Location: US PPR Methods: We
 developed spatiotemporal models of waterfowl pair and brood abundance
 within the PPR of the US. We compared the distributions predicted by these
 models and assessed similarity with the averaged pair data that is used to
 develop the current waterfowl targeting tool. Results: Results
 demonstrated low similarity and correlation between the averaged pair data
 and spatiotemporal brood and pair models. The spatiotemporal pair model
 distributions served as better surrogates for brood abundance than the
 averaged pair data. Main conclusions: Our study underscored the
 contributions that the current targeting tool has made to waterfowl
 conservation but also suggested that conservation plans in the region
 would benefit from the consideration of inter- and intra-annual dynamics.
 We suggested that using only the averaged pair data and derived products
 might result in the omission of 46-98% of important pair and brood
 habitat, respectively, from conservation plans.
description: These data were collected through three different
 studies: Carrlson, K. M.,
 Gue, C. T., Loesch, C. R., & Walker, J. A. (2018). Assessment of
 repeat-visit surveys as a viable method for estimating brood abundance at
 the 10.4-km2 scale. <em>Wildlife Society Bulletin</em>,
 <em>42</em>(1), 72–77. Kemink, K. M.,
 Gue, C. T., Loesch, C. R., Cressey, R. L., Sieges, M. L., &
 Szymanski, M. L. (2019). Impacts of oil and gas development on duck brood
 abundance. <em>The Journal of Wildlife Management</em>,
 <em>83</em>(7), 1485–1494. Walker, J.,
 Rotella, J. J., Schmidt, J. H., Loesch, C. R., Reynolds, R. E., Lindberg,
 M. S., Ringelman, J. K., & Stephens, S. E. (2013). Distribution of
 duck broods relative to habitat characteristics in the Prairie Pothole
 Region. <em>The Journal of Wildlife Management</em>,
 <em>77</em>(2), 392–404. Methods for data
 collection is detailed in each of these manuscripts. All data were
 amalgamated and processed in program R.
description: The traindata.csv file was used to run the spatial brood models
 and the testdata.csv file was used to test the model fit. Column names are
 described as follows, each row represents a wetland surveyed in a given
 year: x/y - UTM coordinates: +proj=aea
 +lat_1=40.38611111111111 +lat_2=47.27722222222222 +lat_0=37
 +lon_0=-105.6855555555556 +x_0=0 +y_0=0 +datum=NAD27 +units=m +no_defs
 +ellps=clrk66<br>+nadgrids=@conus,@alaska,@ntv2_0.gsb,@ntv1_can.dat C1/C2 - AM and PM brood counts at wetland scalePE - scaled value of basin level percent emergent cover scale PE2 - scalePE*scalePE LWA - scaled value of log(July basin wet area)  basinWA - scaled value of July basin wet area  scaleJWA - scaled value of the total wet area within the 10.36 sq km plot on which the wetland was located scaleMWC - scaled value of the total number of wet basins counted in May on the 10.36 sq km plot that the wetland was located scalePC - scaled value of the proportion of the 10.36 sq km plot that was covered in perennial vegetation.  Y09 - Y17 - year in which the count took place (Y08 was treated as the intercept) logDate - scaled value of the log(day) within the study each year SEAS/SEMI/TEMP - regime of the basin (Lake was treated as the intercept) WalkIn - represented whether the survey was conducted on foot (0) or from a vehicle (1).