Estimating Waterfowl Carrying Capacity at Local Scales: A Case Study From Edwin B. Forsythe National Wildlife Refuge, New Jersey1

Abstract

Abstract The management of wintering North American waterfowl is based on the premise that the amount of foraging habitat can limit populations. To estimate carrying capacity of winter habitats, managers use bioenergetic models to quantify energy (food) availability and energy demand, and use results as planning tools to meet regional conservation objectives. Regional models provide only coarse estimates of carrying capacity because habitat area, habitat energy values, and temporal trends in population-level demand are difficult to quantify precisely at large scales. We took advantage of detailed data previously collected on wintering waterfowl at Edwin B. Forsythe National Wildlife Refuge and surrounding marsh, New Jersey, and created a well-constrained local model of carrying capacity. We used 1,223 core samples collected between 2006 and 2015 to estimate food availability. We used species-specific 24-h time–activity data collected between 2011 and 2013 to estimate daily energy expenditure, morphometrically corrected for site- and day-specific thermoregulatory costs. To estimate population-level energy demand, we used standardized monthly ground surveys (2005–2014) to create a migration curve, and proportionally scaled that to fit aerial survey data (2005–2014). Crucially, we also explicitly incorporated estimates of variance in all of these parameters and conducted a sensitivity analysis to diagnose the most important sources of variation in the model. Our results from an outlier-removed, a strict depletion model indicated that at estimated mean levels of supply (923 million kcal) and cumulative demand (3.4 billion kcal), refuge food resources were depleted before November. However, a constant-supply model that represented tidal replenishment of resources indicated that just enough energy was present to sustain peak winter populations. Variation in model output appeared to be driven primarily by uncertainty in population abundance during peak periods of use, emphasizing a new management focus on studying migration chronologies of waterfowl. This model allows for relative assessment of biases and uncertainties in carrying-capacity modeling, and serves as a framework identifying critical science needs to improve local and regional waterfowl management planning.