The U.S. Endangered Species Act (ESA) allows listing of subspecies and other groupings below the rank of species. This provides the U.S. Fish and Wildlife Service and the National Marine Fisheries Service with a means to target the most critical unit in need of conservation. While roughly one-quarter of listed taxa are subspecies, these management agencies are hindered by uncertainties about taxonomic standards during listing or delisting activities. In a review of taxonomic publications and societies, we found few subspecies lists and none that stated standardized criteria for determining subspecific taxa. Lack of criteria is attributed to a centuries-old debate over species and subspecies concepts. However, the critical need to resolve this debate for ESA listings lead us to propose that minimal biological criteria to define disjunct subspecies (legally or taxonomically) should include the discreteness and significance criteria of Distinct Population Segments (as defined under the ESA). Our subspecies criteria are in stark contrast to that proposed by supporters of the Phylogenetic Species Concept and provide a clear distinction between species and subspecies. Efforts to eliminate or reduce ambiguity associated with subspecies-level classifications will assist with ESA listing decisions. Thus, we urge professional taxonomic societies to publish and periodically update peer-reviewed species and subspecies lists. This effort must be paralleled throughout the world for efficient taxonomic conservation to take place.
The ecological consequences of climate change have been recognized in numerous species, with perhaps phenology being the most well‐documented change. Phenological changes may have negative consequences when organisms within different trophic levels respond to environmental changes at different rates, potentially leading to phenological mismatches between predators and their prey. This may be especially apparent in the Arctic, which has been affected more by climate change than other regions, resulting in earlier, warmer, and longer summers. During a 7‐year study near Utqiaġvik (formerly Barrow), Alaska, we estimated phenological mismatch in relation to food availability and chick growth in a community of Arctic‐breeding shorebirds experiencing advancement of environmental conditions (i.e., snowmelt). Our results indicate that Arctic‐breeding shorebirds have experienced increased phenological mismatch with earlier snowmelt conditions. However, the degree of phenological mismatch was not a good predictor of food availability, as weather conditions after snowmelt made invertebrate availability highly unpredictable. As a result, the food available to shorebird chicks that were 2–10 days old was highly variable among years (ranging from 6.2 to 28.8 mg trap−1 day−1 among years in eight species), and was often inadequate for average growth (only 20%–54% of Dunlin and Pectoral Sandpiper broods on average had adequate food across a 4‐year period). Although weather conditions vary among years, shorebirds that nested earlier in relation to snowmelt generally had more food available during brood rearing, and thus, greater chick growth rates. Despite the strong selective pressure to nest early, advancement of nesting is likely limited by the amount of plasticity in the start and progression of migration. Therefore, long‐term climatic changes resulting in earlier snowmelt have the potential to greatly affect shorebird populations, especially if shorebirds are unable to advance nest initiation sufficiently to keep pace with seasonal advancement of their invertebrate prey.
Movement has important consequences for individual and population-level processes, but methods are only starting to become available for quantifying fine-scale movement paths of smaller animals. New techniques for inferring behavioral states and their relation to social and environmental factors provide a powerful way to test the influence of such factors on individuals. One such technique that has recently gained popularity is the use of hidden Markov models, which link time series of movement variables and the underlying behavioral states of individuals. We used hidden Markov models to evaluate behavioral states and their relation to environmental, seasonal, and social factors in the cooperatively breeding red-cockaded woodpecker (Picoides borealis) while accounting for individual heterogeneity with discrete random effects. We identified 2 distinct behavioral states, resting and foraging, which were related to covariates in our models. Using this approach, we concluded that woodpecker step lengths tended to be longest in winter, larger groups of woodpeckers tended to spend less time foraging and more time resting when compared with smaller groups, and woodpeckers foraged more and rested less when in higher-quality habitat. Our results demonstrate the impact that social and environmental factors can have on movement in a social species and, thus, reinforce the importance of including these factors in animal movement studies. The extensions of basic hidden Markov models considered here may prove valuable in forthcoming studies that involve highresolution tracking to understand behavior of birds and other small animals.
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