Rotational grazing of beef cattle to support Bobolink breeding success

Conservation actions for the federally and provincially threatened Bobolink (Dolichonyx oryzivorus) in Ontario, Canada are ongoing in agricultural landscapes, including pastures. However, conditions conducive to Bobolink fledging young from breeding territories in rotationally grazed beef cattle (Bos taurus) pastures are not well understood. We tested two management strategies designed to provide habitat where Bobolink could fledge young in rotationally grazed pastures. We conducted (1) a refuge paddock experiment using a crossover design, comparing fledging success when paddocks were ungrazed in one year to when they were grazed in another year; and (2) a light spring grazing experiment. Additionally, we explored associations between fledging of young from territories with cattle stocking rate and date that cattle first entered paddocks. We used spot mapping and nest monitoring to determine if young fledged in 83 Bobolink territories in 2016 and 72 territories in 2017 on six farms in the Ottawa Valley, Ontario. In the refuge paddock experiment, 54% (N = 28) of Bobolink territories fledged young in eight ungrazed paddocks compared to 16% (N = 25) when these paddocks were grazed in another breeding season. In the light spring grazing experiment, 67% (N = 12) of territories fledged young from four paddocks that were grazed with a low stocking rate between 21 May and 03 June 2017 and not again until after 02 July. Additionally, predictions from a logistic regression model indicated that the probability of young fledging from a territory (N = 118) decreased from 0.53 to 0.04 when mid-season stocking rates increased from 0 to 174 cattle-days/ha. Our results illustrate that paddocks on rotationally grazed beef cattle farms that are ungrazed until the Bobolink breeding season is finished or grazed lightly for a brief duration soon after territories are established can provide areas that enable Bobolink to fledge young

Supplement 1. R package (Windows and cross-platform) including all data and analysis.

<h2>File List</h2><div> <p><a href="foRthood.zip">foRthood.zip</a> (MD5: 52fd9a6dc2b8f59901a40e602de70668)</p> <p><a href="foRthood.tar.gz">foRthood.tar.gz</a> (MD5: da915abaed3c94d3d04bd1f08eeccc65)</p> </div><h2>Description</h2><div> <p>foRthood.zip – Windows binary package and documentation for the R package containing all data and analysis</p> <p>foRthood.tar.gz – Cross-platform source code and documentation for the R package containing all data and analysis</p> </div

Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients

Species distribution models (SDM) link species occurrence with a suite of environmental predictors and provide an estimate of habitat quality when the variable set captures the biological requirements of the species. SDMs are inherently more complex when they include components of a species' ecology such as conspecific attraction and behavioral flexibility to exploit resources that vary across time and space. Wading birds are highly mobile, demonstrate flexible habitat selection, and respond quickly to changes in habitat quality; thus serving as important indicator species for wetland systems. We developed a spatio-temporal, multi-SDM framework using Great Egret (Ardea alba), White Ibis (Eudocimus albus), and Wood Stork (Mycteria Americana) distributions over a decadal gradient of environmental conditions to predict species-specific abundance across space and locations used on the landscape over time. In models of temporal dynamics, species demonstrated conditional preferences for resources based on resource levels linked to differing temporal scales. Wading bird abundance was highest when prey production from optimal periods of inundation was concentrated in shallow depths. Similar responses were observed in models predicting locations used over time, accounting for spatial autocorrelation. Species clustered in response to differing habitat conditions, indicating that social attraction can co-vary with foraging strategy, water-level changes, and habitat quality. This modeling framework can be applied to evaluate the multi-annual resource pulses occurring in real-time, climate change scenarios, or restorative hydrological regimes by tracking changing seasonal and annual distribution and abundance of high quality foraging patches