Slopes of Avian Species-Area Relationships, Human Population Density, and Environmental Factors

There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species–area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species–area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km × 10 km) and regional (290 km × 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.

Linking Canadian Harvested Juvenile American Black Ducks to Their Natal Areas Using Stable Isotope (δD, δ13C, and δ15N) Methods

Understanding source-sink dynamics of game birds is essential to harvest and habitat management but acquiring this information is often logistically and financially challenging using traditional methods of population surveys and banding studies. This is especially true for species such as the American Black Duck (Anas rubripes), which have low breeding densities and extensive breeding ranges that necessitate extensive surveys and banding programs across eastern North America. Despite this effort, the contribution of birds fledged from various landscapes and habitat types within specific breeding ranges to regional harvest is largely unknown but remains an important consideration in adaptive harvest management and targeted habitat conservation strategies. We investigated if stable isotope (δD, δ13C, δ15N) could augment our present understanding of connectivity between breeding and harvest areas and so provide information relevant to the two main management strategies for black ducks, harvest and habitat management. We obtained specimens from 200 hatch-year Black Duck wings submitted to the Canadian Wildlife Service Species Composition Survey. Samples were obtained from birds harvested in Western, Central, and Eastern breeding/harvest subregions to provide a sample representative of the range and harvest rate of birds harvested in Canada. We sampled only hatch-year birds to provide an unambiguous and direct link between production and harvest areas. Marine origins were assigned to 12%, 7%, and 5% of birds harvested in the Eastern, Central, and Western subregions, respectively. In contrast, 32%, 9%, and 5% of birds were assigned, respectively, to agricultural origins. All remaining birds were assigned to nonagricultural origins. We portrayed probability of origin using a combination of Bayesian statistical and GIS methods. Placement of most eastern birds was western Nova Scotia, eastern New Brunswick, Prince Edward Island, and southern Newfoundland. Agricultural birds from the Central region were consistent with the Saguenay region of Québec and the eastern claybelt with nonagricultural birds originating in the boreal. Western nonagricultural birds were associated with broad boreal origins from southern James Bay to Lake of the Woods and east to Cochrane, Ontario. Our work shows that the geographic origins, landscape, and habitat associations of hatch-year Black Ducks can be inferred using this technique and we recommend that a broad-scale isotopic study using a large sample of Canadian and US harvested birds be implemented to provide a continental perspective of source-sink population dynamics.

Identification of Putative Wintering Areas and Ecological Determinants of Population Dynamics of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) Breeding in Northern Italy

To identify the causes of population decline in migratory birds, researchers must determine the relative influence of environmental changes on population dynamics while the birds are on breeding grounds, wintering grounds, and en route between the two. This is problematic when the wintering areas of specific populations are unknown. Here, we first identified the putative wintering areas of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) populations breeding in northern Italy as those areas, within the wintering ranges of these species, where the winter Normalized Difference Vegetation Index (NDVI), which may affect winter survival, best predicted annual variation in population indices observed in the breeding grounds in 1992–2009. In these analyses, we controlled for the potentially confounding effects of rainfall in the breeding grounds during the previous year, which may affect reproductive success; the North Atlantic Oscillation Index (NAO), which may account for climatic conditions faced by birds during migration; and the linear and squared term of year, which account for nonlinear population trends. The areas thus identified ranged from Guinea to Nigeria for the Common House-Martin, and were located in southern Ghana for the Common Swift. We then regressed annual population indices on mean NDVI values in the putative wintering areas and on the other variables, and used Bayesian model averaging (BMA) and hierarchical partitioning (HP) of variance to assess their relative contribution to population dynamics. We re-ran all the analyses using NDVI values at different spatial scales, and consistently found that our population of Common House-Martin was primarily affected by spring rainfall (43%–47.7% explained variance) and NDVI (24%–26.9%), while the Common Swift population was primarily affected by the NDVI (22.7%–34.8%). Although these results must be further validated, currently they are the only hypotheses about the wintering grounds of the Italian populations of these species, as no Common House-Martin and Common Swift ringed in Italy have been recovered in their wintering ranges.