We examined survival of ring-necked pheasants (Phasianus colchicus) occupying fragmented landscapes within the Prairie Pothole Region in South Dakota, USA, where severe winter weather events historically limited pheasant population growth through increased mortality. Recent landscape transformations could further affect overwinter adult female survival by reducing critical winter resources. Assessing the influence of time-dependent landscape features on survival at small focal scales may reveal spatially important relationships. We captured and monitored 321 adult female pheasants from 2017-2019 and recorded 110 pheasant winter mortalities.Female pheasant winter survival was 0.66 (85% CI = 0.62-0.70) and was inversely correlated to snow depth. We generated Cox proportional hazard models to determine risk of mortality associated with landscape features. Pheasants using landscapes other than perennial cover (i.e., emergent wetland, tall vegetation, woody, food plots) experienced a 2.22 times greater risk of raptor predation than pheasants using perennial cover. Additionally, pheasants experienced a 58% reduced risk of weather mortality when using emergent wetlands. We analyzed resource selection ratios to understand how perceived landscape risks at the population level scaled down to land use selection at the individual level. Female pheasants selected for emergent wetlands, showed no selection for woody features, and avoided tall vegetation (non-aquatic herbaceous vegetation >75 cm) during severe winters. Pheasants would greatly benefit from conservation of emergent
Habitat loss and fragmentation are two important drivers of biodiversity decline. Understanding how species respond to landscape composition and configuration in dynamic landscapes is of great importance for informing the conservation and management of grassland species. With limited conservation resources, prescribed management targeted at the appropriate landscape process is necessary for the effective management of species. We used pheasants (Phasianus colchicus) across South Dakota, USA as a model species to identify environmental factors driving spatiotemporal variation in population productivity. Using an emerging Hotspot analysis, we analyzed annual count data from 105 fixed pheasant brood routes over a 24-year period to identify high (HotSpot) and low (ColdSpot) pheasant population productivity areas. We then applied classification and regression tree modeling to evaluate landscape attributes associated with pheasant productivity among spatial scales (500 m and 1000 m). We found that the amount of grassland at a local spatial scale was the primary factor influencing an area being a HotSpot. Our results also demonstrated non-significant or weak effects of fragmentation per se on pheasant populations. These findings are in accordance with the habitat amount hypothesis highlighting the importance of habitat amount in the landscape for maintaining and increasing the pheasant population. We, therefore, recommend that managers should focus on increasing the total habitat area in the landscape and restoring degraded habitats. Our method of identifying areas of high productivity across the landscape can be applied to other species with count data.
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