Sixty-years of community-science data suggest earlier fall migration and short-stopping of several species of waterfowl in North America

Abstract

Worldwide, migratory phenology and movement of many bird species are shifting in response to anthropogenic climate and habitat changes. However, due to variation among species and a shortage of analyses, changes in waterfowl migration, particularly in the fall, are not well understood. Fall migration phenology and movement patterns dictate waterfowl hunting success and satisfaction, with cascading implications on economies and support for habitat management and securement. Using 60 years of band recovery data for waterfowl banded in the Canadian Prairie Pothole Region (PPR), we evaluated whether fall migration timing and/or distribution changed in Mallard (Anas platyrhynchos), Northern Pintail (A. acuta), and Blue-winged Teal (Spatula discors) between 1960 and 2019. We found that in the Midcontinent Flyways, Mallards and Blue-winged Teal migrated faster in more recent time periods, while Northern Pintail began fall migration earlier. In the Pacific Flyway, Mallards began fall migration earlier. Both Mallards and Northern Pintails showed evidence of short-stopping in the Midcontinent Flyways. Indeed, the Mallard and Northern Pintail distribution of band recovery data shifted 180 km and 226 km north respectively from 1960 to 2019. Conversely, Blue-winged Teal recovery distributions were consistent across years. Mallards and Northern Pintails also exhibited an increased proportion of band recoveries in the Pacific Flyway in recent decades. We provide clear evidence that the timing and routes of fall migration have shifted over the past six decades, but these phenological and spatial shifts differ among species. We suggest that using community-science data collected by hunters themselves to explain one of the group's major concerns (changes in duck abundance at traditional hunting grounds), within the environmental lens of climate change, may help lead to further engagement and two-way dialogue to support effective waterfowl management for these culturally and ecologically important species.All analysis were carried out using the open-access Program R.Funding provided by: Environment and Climate Change CanadaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100008638Award Number:Data Acquisition We requested banding and encounter records from the Bird Banding Office (Bird Banding Biology, CWS, [email protected]) for six waterfowl species banded in Manitoba (MB), Saskatchewan (SK), or Alberta (AB) available as of 3 December 2020, when we downloaded the data. Our initial six focal species all commonly breed in the Canadian prairies: Mallard, Northern Pintail, Blue-winged Teal, American Green-winged Teal (A. carolinensis), Gadwall (Mareca strepera), and American Wigeon (M. americana). Digitization of banding records was incomplete prior to 1960, so we restricted analyses to 1960–2019. To assess spatiotemporal changes in waterfowl fall migration, we restricted encounter records to birds that died during the first hunting season (September - December) after they were banded with coordinate precision for encounter location of at least 10-minutes (approx. 18.5 km). While the hunting season may extend beyond December in some portions of the United States, we excluded records beyond this point in our analysis to avoid geographic bias between areas that still had active hunting seasons later in the winter vs. those where hunting no longer occurred. By the end of December most if not all individuals of our focal species will have reached terminal points. Blue-winged Teals and Northern Pintails are some of the first ducks migrating southward in the fall, with peak migration for both species occurring in September and October (Clark et al. 2020, Rohwer et al. 2020). Mallards migrate later in the season, with migration peaks between late October to mid-December, with some of the most southern migrants overwintering in Mexico beginning to arrive by November (Drilling et al. 2020). We included both direct recoveries (i.e., birds harvested by a hunter) and birds that were found dead, restricted to Canada and the United States. We did not filter by age or sex of the bird or time of banding. Evaluating Spatiotemporal Change in Waterfowl Recovery Distribution To assess spatiotemporal changes in the phenology and distribution of fall migration, we divided the banding and encounter records into three 20-year periods (1960–1979, 1980–1999, and 2000–2019) and eight 2-week intervals from September through December. Smaller time-steps (e.g., 10-year periods) resulted in insufficient and unequal sample sizes, while larger time-steps (e.g., 30-year periods) amalgamated too many years to capture changes. Two-week intervals provided the shortest time interval to capture a 'snapshot' of the distribution of recoveries through time that enabled sufficient sample sizes. The first two weeks of September had far fewer recovery records; Northern Pintail recovery distributions could not be assessed during this interval. We restricted analysis of spatiotemporal trends in fall migration to Mallards, Northern Pintails, and Blue-winged Teals due to sample size limitations for other species (i.e, Gadwalls, American Widgeons, and American Green-winged Teals). Expanding on the approaches taken by Calenge et al. (2010) and Green and Krementz (2008), we conducted KDE using the R package 'adehabitatHR' (Calenge 2007, with an ad hoc smoothing parameter with the default grid value of 60) for each species, time period, and interval. We extracted Utilization Distribution (UD) contours to produce spatial polygons for each of the 50%, 70%, and 90% probability density contours using the function 'getverticeshr'. We assessed spatial relationships between the 50% UD KDE contours for each time interval and period using approaches from STAMP (Spatio-Temporal Analysis of Moving Polygons, R package 'stampr') to generate metrics describing change events on spatial relationships (Long et al. 2018). For each time interval, we describe stepwise change between the 20-year periods in relation to measures of distance and direction between polygons, and changes in polygon shape. We quantified three distinct types of distribution change events between subsequent periods (e.g., comparing 1960–1979 to 1980–1999, comparing 1980–1999 to 2000–2019). To do this we quantified areas of stability (i.e., areas of complete overlap between the time periods), areas of expansion (areas only included in the later time period), and areas of contraction (areas only included in the earlier time period). Then, we quantified the absolute area (km2) and proportional area that was stable, contracting, or expanding for each 2-week interval