Assessing nutrient stores in avian species is important for understanding the extent to which body condition influences success or failure in life-history events. We evaluated predictive models using morphometric characteristics to estimate total body lipids (TBL) and total body protein (TBP), based on traditional proximate analyses, in spring migrating lesser snow geese (Anser caerulescens caerulescens) and Ross's geese (A. rossii). We also compared performance of our lipid model with a previously derived predictive equation for TBL developed for nesting lesser snow geese. We used external and internal measurements on 612 lesser snow and 125 Ross's geese collected during spring migration in 2015 and 2016 within the Central and Mississippi flyways to derive and evaluate predictive models. Using a validation data set, our best performing lipid model for snow geese better predicted TBL (root mean square error [RMSE] of 23.56) compared with a model derived from nesting individuals (RMSE ¼ 48.60), suggesting the importance of season-specific models for accurate lipid estimation. Models that included body mass and abdominal fat deposit best predicted TBL determined by proximate analysis in both species (lesser snow goose, R 2 ¼ 0.87, RMSE ¼ 23.56: Ross's geese, R 2 ¼ 0.89, RMSE ¼ 13.75). Models incorporating a combination of external structural measurements in addition to internal muscle and body mass best predicted protein values (R 2 ¼ 0.85, RMSE ¼ 19.39 and R 2 ¼ 0.85, RMSE ¼ 7.65, lesser snow and Ross's geese, respectively), but protein models including only body mass and body size were also competitive and provided extended utility to our equations for field applications. Therefore, our models indicated the importance of specimen dissection and measurement of the abdominal fat pad to provide the most accurate lipid estimates and provide alternative dissection-free methods for estimating protein. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Evidence that decoy harvest techniques primarily remove individuals of poorer body condition is well established in short‐lived duck species; however, there is limited support for condition bias in longer‐lived waterfowl species, such as geese, where decoy harvest is considered primarily additive because of their high natural survival rates. We evaluated support for the harvest condition bias hypothesis of 2 long‐lived waterfowl species, the lesser snow goose (Anser caerulescens caerulescens) and Ross's goose (Anser rossii). We used proximate analysis to quantify lipid and protein content of lesser snow and Ross's geese collected during the Light Goose Conservation Order (LGCO) in 2015 and 2016 during spring migration in Arkansas, Missouri, Nebraska, and South Dakota, USA. In each state, LGCO participants collected birds using traditional decoy techniques and we collected birds from the general population using jump‐shooting tactics. Total body lipid content in both lesser snow and Ross's geese varied with age, region of harvest, and harvest type (decoy or jump‐shooting). On average, adult lesser snow and Ross's geese harvested over decoys had 60 g and 41 g, respectively, fewer lipids than conspecifics collected using jump‐shooting. We observed lower lipid reserves in decoy‐shot geese in all 4 states sampled despite general gains in lipid reserves as migration chronology progressed. Our data support that the harvest condition bias extends to longer‐lived waterfowl species and during a life‐history event (spring migration) in which harvest is not normally observed. In the case of overabundant light geese, the disproportionate harvest of poorer‐conditioned lesser snow and Ross's geese may serve as an additional challenge against any realized effects of harvest to reduce the population, in addition to extremely low harvest rates. © 2019 The Wildlife Society.
Context The North American Waterfowl Management Plan and the Upper Mississippi River/Great Lakes Joint Venture waterfowl habitat conservation strategy provide continental and regional guidance, respectively, for waterfowl habitat conservation planning. They were not designed to guide watershed- scale waterfowl habitat delivery. Objective Our goal was to develop a waterfowl habitat decision support framework for the state of Wisconsin using biological and social criteria to guide state and local-scale practitioners with an explicit link to larger scale objectives. Methods We engaged a core group of wetland and waterfowl experts to decide upon decision support layers relevant to biological and social objectives, evaluate variables, establish weights, and review model outputs for reasonableness and accuracy. We used spatial analyst tools, kernel density estimators, and weighted sums to create spatially explicit models to identify landscapes and watersheds important for waterfowl. We identified habitat resources that exist currently (Conservation Capital) and considered potential resources (Conservation Opportunities) which could enhance wetland restoration efforts. Results We developed a transparent framework to identify and prioritize landscapes for conserving waterfowl habitat at the Hydrologic Unit Code 12 watershed scale in Wisconsin, by maintaining continental and regional priorities, and including local landscape characteristics, biological criteria, and researcher, manager, and biologist expertise. Conclusions Local detail is critical for implementing waterfowl habitat delivery and making efficient use of limited funds for conservation but can be more abstract in larger regional or continental conservation planning. Our models are science-based, transparent, defensible, and can be modified as social, political, biological, and environmental forces change.
Agriculture and moist-soil management are important management techniques used on wildlife refuges to provide adequate energy for migrant waterbirds. In semi-arid systems, the accumulation of soluble salts throughout the soil profile can limit total production of wetland plants and agronomic crops and thus jeopardize meeting waterbird energy needs. This study evaluates the effect of distinct hydrologic regimes associated with moist-soil management and agricultural production on salt accumulation in a semi-arid floodplain. We hypothesized that the frequency of flooding and quantity of floodwater in a moist-soil management hydroperiod results in a less saline soil profile compared to profiles under traditional agricultural management. Findings showed that agricultural croplands differed (p-value<0.001, df=9) in quantities of total soluble salts (TSS) compared to moist-soil impoundments and contained greater concentrations (TSS range = 1,160-1,750 (mg kg-1)) at depth greater than 55 cm below the surface of the profile, while moist-soil impoundments contained lower concentrations (TSS range = 307-531 (mg kg-1)) at the same depths. Increased salts in agricultural may be attributed to the lack of leaching afforded by smaller summer irrigations while larger periodic flooding events in winter and summer flood irrigations in moist-soil impoundments may serve as leaching events.
Expanding populations of North American midcontinent lesser snow geese (Anser caerulescens caerulescens) have potential to alter ecosystems throughout the Arctic and subarctic where they breed. Efforts to understand origins of harvested lesser snow geese to better inform management decisions have traditionally required mark-recapture approaches, while aerial photographic surveys have typically been used to identify breeding distributions. As a potential alternative, isotopic patterns that are metabolically fixed within newly grown flight feathers following summer molting could provide inferences regarding geographic breeding origin of individuals, without the need for prior capture. Our objective was to assess potential to use four stable isotopes (δ13C, δ15N, δ34S, δ2H) from feather material to determine breeding origins. We obtained newly grown flight feathers from individuals during summer banding at three Arctic and two subarctic breeding colonies in 2014 (n = 56) and 2016 (n = 45). We used linear discriminant analyses to predict breeding origins from models using combinations of stable isotopes as predictors and evaluated model accuracy when predicting colony, subregion, or subpopulation levels. We found a strong inverse relationship between δ2H values and increasing latitude (R2 = 0.83), resulting in differences (F4, 51 = 90.41, P < 0.0001) among sampled colonies. No differences in δ13C or δ15N were detected among colonies, although δ34S in Akimiski Island, Baffin Island, and Karrak Lake were more enriched (F4, 51 = 11.25, P < 0.0001). Using δ2H values as a predictor, discriminant analyses improved accuracy in classification level as precision decreased [model accuracy = 67% (colony), 88% (subregion), 94% (subpopulation)]. Application of the isotopic methods we describe could be used to provide an alternative monitoring method of population metrics, such as overall breeding population distribution, region-specific productivity and migratory connectivity that are informative to management decision makers and provide insight into cross-seasonal effects that may influence migratory behavior.
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