Implications of habitat‐driven survival and dispersal on recruitment in a spatially structured piping plover population

Abstract

Natal survival and dispersal have important consequences for populations through the movement of genes and individuals. Metapopulation theory predicts either balanced natal dispersal among regions or source-sink dynamics, which can dramatically change population structure. For species reliant on dynamic, early-successional habitats, availability and location of habitat will shift from year to year, requiring primiparous individuals to locate an appropriate breeding habitat. We estimated hatch-year survival to adulthood and natal dispersal rates between two breeding groups of Northern Great Plains piping plovers (Charadrius melodus) from four cohorts (n = 2669 total individuals; 2014-2017). Hatch-year survival to adulthood was slightly higher for individuals hatched on the Missouri River than on the US Alkali Wetlands but declined over time. Individuals hatched on the US Alkali Wetlands were more likely to disperse to breed on the Missouri River (0.33 [0.20, 0.48]) than vice versa (0.17 [0.11, 0.24]). When more habitat was available at the natal site than in the prior year, natal dispersal rates increased. However, despite higher recruitment rates as a result of higher natal fidelity, the Missouri River showed lower total recruitment with a declining trend in the number of recruits, largely due to differences in abundance between breeding groups. Overall, unbalanced, high natal dispersal rates within the Northern Great Plains indicate high connectivity among distinct regions with different water regimes on the Missouri River and on the US Alkali Wetlands driven by fluctuating availability of habitat. Our results suggest that plovers in the Northern Great Plains take advantage of dynamic habitats where they are available in a broad geographic area, which is consistent with a spatially structured panmictic population rather than a true metapopulation, but further research on adult breeding dispersal is needed to clarify population structure.

Conspecific density and habitat quality affect breeding habitat selection: Support for the social attraction hypothesis

“…The Garrison Reach had high connectivity and a disproportionate effect on network connectivity during habitat loss simulations. Plovers may perceive sandbars on the Garrison Reach as high‐quality habitats, which has been suggested previously due to high nest and chick survival (Anteau et al, 2019; Shaffer et al, 2013; Swift, Anteau, Ellis, Ring, Sherfy, Toy, & Koons, 2021; Swift, Anteau, Ring, et al, 2020; Swift, Anteau, Roche, et al, 2020), high renest probability and success (Swift, Anteau, Ring, et al, 2020), high natal fidelity (Swift et al, 2022), and shorter dispersal distances (Swift, Anteau, Ellis, Ring, Sherfy, & Toy, 2021). High connectivity in the network graph also indicates that current management practices to provide an abundance of habitat on the riverine stretches of the Missouri River may be especially important (USFWS, 2018).…”

“…Adults were captured at the nest site with either a remote‐controlled walk‐in trap or bow net and banded with a U.S. Geological Survey (USGS) aluminum band, a unique combination of color bands, and a unique alpha‐numeric engraved flag. Individuals could have been previously marked prior to 2014 for other studies (Anteau et al, 2019; Shaffer et al, 2013) or marked as chicks and recruited into the breeding population (Swift et al, 2022). Adults were attributed to a nest by capturing individuals at the nest, observing known individuals return to incubate, or using video cameras briefly set up near the nest (Toy et al, 2017).…”

“…We identify important breeding locations within the network for plovers, and we examine the effect of habitat loss on network connectivity. Habitat availability, density dependence, and public information (i.e., inadvertent conspecific social cues; Danchin et al, 2004) have all been previously documented to influence piping plover dispersal decisions (Catlin et al, 2016; Davis et al, 2017; Rioux et al, 2011; Roche et al, 2012; Swift et al, 2022; Swift, Anteau, Ellis, Ring, Sherfy, & Toy, 2021; Swift, Anteau, Ellis, Ring, Sherfy, Toy, & Koons, 2021). However, little is known about how habitat selection may differ between returning adults and those that must immigrate to a new breeding location due to a previous decision to disperse.…”

Estimating population viability of the northern Great Plains piping plover population considering updated population structure, climate change, and intensive management

“…In a post-hoc scenario where connectivity rates were increased to 0.13, extinction risk for the entire NGP population increased to 0.083above the proposed delisting criteria (McGowan et al, 2014;USFWS, 2016). A recent largescale empirical study resighting marked individuals found that dispersal between two spatially distinct breeding groups in the NGP was much higher than those initially simulated connectivity rates and was also unbalanced for both adult (U.S. Alkali Wetlands to Northern Rivers: 0.04, Northern Rivers to U.S. Alkali Wetlands: 0.17) and hatch-year (U.S. Alkali Wetlands to Northern Rivers: 0.33, Northern Rivers to U.S. Alkali Wetlands: 0.17) plovers (Swift et al, 2021a;Swift et al, 2022). This suggests that extinction risk for NGP plovers under high, unbalanced dispersal conditions may not meet the draft recovery criteria (USFWS, 2016) and needs to be reevaluated.…”

Assessing trade‐offs in developing a landscape‐scale nest monitoring programme for a threatened shorebird

“…Piping plover habitats are widely distributed in the PPR, but nests are often concentrated within ‘hotspots’ (Ellis, Anteau, MacDonald, Swift, Ring, Toy, Sherfy, et al., 2023). This type of aggregation of nests across space is common for species that use patches of habitat distributed across large areas, for species exhibiting colonial or semi‐colonial nesting behaviours (Dardenne et al., 2013; Gibbs, 1991; Patrick, 2013), and where social cues or community interactions contribute to the spatial pattern of nests, in addition to habitat conditions (Cunningham et al., 2016; Samplonius & Both, 2017; Swift et al., 2017, 2023). Therefore, precision and bias will likely differ with varying aggregation and spatiotemporal autocorrelation of nest patterns and available habitats (Blanchard et al., 2008).…”