Energetic Carrying Capacity of Actively and Passively Managed Wetlands for Migrating Ducks in Ohio

Abstract

Habitat conservation strategies of the North American Waterfowl Management Plan (NAWMP) are guided by current understanding of factors that limit growth of waterfowl populations. The 1998 implementation plan of the Upper Mississippi River and Great Lakes Region Joint Venture (UMR and GLRJV) assumed that availability of foraging resources during autumn in wetlands actively managed for waterfowl was the primary limiting factor for duck populations during the nonbreeding season. We used multistage sampling during autumn and spring 2001–2004 to estimate energetic carrying capacity (ECC) of actively and passively managed wetlands in Ohio, USA, and examine this assumption. Energetic carrying capacity during autumn was similar between actively and passively managed wetlands each year. Averaged across years, energetic carrying capacity was 3,446 and 2,047 duck energy‐days (DED)/ha for actively and passively managed wetlands, respectively. These estimates exceeded the UMR and GLRJV assumption that 1,236 DED/ha were provided by managed wetland habitats. Energetic carrying capacity declined each year by >80% between autumn and spring migration. Consequently, ECC of actively and passively managed wetlands was low during spring ( = 66–242 DED/ha). These results suggested that duck foraging resources in actively and passively managed wetland habitats are abundant during autumn, but overwinter declines may create food‐limiting environments during spring.

Estimation and correction of seed recovery bias from moist‐soil cores

“…Wetlands in the MAV had been dewatered in summer and received soil disturbance within 2 yr of core sampling promoting annual, large‐seeded species (e.g., Echinochloa spp., P. pensylvanicum , Rhynchospora spp., S. herbacea ) commonly occurring in actively managed moist‐soil wetlands (Brasher et al 2007, Nelms 2007, Kross et al 2008, Strickland et al 2009). Wetlands sampled in the Midwest had more variable water and disturbance regimes than MAV wetlands resulting in production of small‐ and medium‐seeded plants (e.g., Amaranthus spp., Eleocharis spp., P. hydropiperoides ) that may occur in greater proportion in more passively or unmanaged moist‐soil wetlands (Brasher et al 2007, Kross et al 2008, Pankau 2008). Size‐specific correction factors produced more accurate mass estimates than constant correction factors and were similar to taxon‐specific correction factors in both regions.…”

“…Several Joint Ventures implementing NAWMP in nonbreeding regions have set habitat objectives based on an operational assumption that food may be limiting for migrating and wintering waterfowl (Reinecke et al 1989, Loesch et al 1994, Abraham et al 2007). Consequently, since the 1980s, conservation planners have estimated food resources in and evaluated management strategies for waterfowl foraging habitats (Miller 1987, Stafford et al 2006, Brasher et al 2007, Kross et al 2008).…”

Trophic Niche and Feeding Strategy of the White Stork (Ciconia ciconia) during different Phases of the Breeding Season

“…Ecologists investigate the trophic niches of animal species to determine precisely their actual place in food webs and understand diet specialisation and population dynamics (Svanbäck and Persson, 2004;Nielsen et al, 2010). In fact, countless levels of perception, such as food quantity, food availability, biomass and calorific intake and diet variations in time and space, have been used to study trophic niches (Brasher et al, 2007;Nielsen et al, 2010;Crampton et al, 2011).…”

Agricultural practices and residual corn during spring crane and waterfowl migration in Nebraska

“…Thus, we used analysis of variance (ANOVA) in an experimental framework to quantify effects of post‐harvest treatments and depletion by migratory birds on residual corn density. We used stratified random sampling that allowed us to apply a multi‐stage sampling (MSS) design (Stafford et al 2006 a , b ; Brasher et al 2007; Kross et al 2008 b ) to estimate density of residual corn in each post‐harvest field treatment and for the CPRV as a whole. The nonweighted ANOVA analysis is an experimental evaluation of post‐harvest management effects on residual corn density, which provided information about the processes that may reduce residual corn density and could have application to areas outside the CPRV.…”

“…Because our interest in these objectives was in experimental effects, we used unweighted observations, and we present back‐transformed geometric means for objective 1 that are appropriate for comparison between levels of effects. We met objective 3 using PROC SURVEYMEANS to estimate mean and 95% confidence limits of residual corn density for the CPRV under the MSS design (SAS Institute 2002; Stafford et al 2006 a , b ; Brasher et al 2007; Kross et al 2008 b ). Because our interest in this objective was in corn density for the CPRV as a whole, we weighted our observations and computed arithmetic means.…”