A framework for understanding ecological traps and an evaluation of existing evidence

When an animal settles preferentially in a habitat within which it does poorly relative to other available habitats, it is said to have been caught in an "ecological trap." Although the theoretical possibility that animals may be so trapped is widely recognized, the absence of a clear mechanistic understanding of what constitutes a trap means that much of the literature cited as support for the idea may be weak, at best. Here, we develop a conceptual model to explain how an ecological trap might work, outline the specific criteria that are necessary for demonstrating the existence of an ecological trap, and provide tools for researchers to use in detecting ecological traps. We then review the existing literature and summarize the state of empirical evidence for the existence of traps. Our conceptual model suggests that there are two basic kinds of ecological traps and three mechanisms by which traps may be created. To this point in time, there are still only a few solid empirical examples of ecological traps in the published literature (although those few examples suggest that both types of traps and all three of the predicted mechanisms do exist in nature). Therefore, ecological traps are either rare in nature, are difficult to detect, or both. An improved library of empirical studies will be essential if we are to develop a more synthetic understanding of the mechanisms that can trigger maladaptive behavior in general and the specific conditions under which ecological traps might occur.     

Predicting species distributions from samples collected along roadsides

Predictive models of species distributions are typically developed with data collected along roads. Roadside sampling may provide a biased (nonrandom) sample; however, it is currently unknown whether roadside sampling limits the accuracy of predictions generated by species distribution models. We tested whether roadside sampling affects the accuracy of predictions generated by species distribution models by using a prospective sampling strategy designed specifically to address this issue. We built models from roadside data and validated model predictions at paired locations on unpaved roads and 200 m away from roads (off road), spatially and temporally independent from the data used for model building. We predicted species distributions of 15 bird species on the basis of point-count data from a landbird monitoring program in Montana and Idaho (U.S.A.). We used hierarchical occupancy models to account for imperfect detection. We expected predictions of species distributions derived from roadside-sampling data would be less accurate when validated with data from off-road sampling than when it was validated with data from roadside sampling and that model accuracy would be differentially affected by whether species were generalists, associated with edges, or associated with interior forest. Model performance measures (kappa, area under the curve of a receiver operating characteristic plot, and true skill statistic) did not differ between model predictions of roadside and off-road distributions of species. Furthermore, performance measures did not differ among edge, generalist, and interior species, despite a difference in vegetation structure along roadsides and off road and that 2 of the 15 species were more likely to occur along roadsides. If the range of environmental gradients is surveyed in roadside-sampling efforts, our results suggest that surveys along unpaved roads can be a valuable, unbiased source of information for species distribution models.     

Is the effect of forest structure on bird diversity modified by forest productivity?

Currently, the most common strategy when managing forests for biodiversity at the landscape scale is to maintain structural complexity within stands and provide a variety of seral stages across landscapes. Advances in ecological theory reveal that biodiversity at continental scales is strongly influenced by available energy (i.e., climate factors relating to heat and light and primary productivity). This paper explores how available energy and forest structural complexity may interact to drive biodiversity at a regional scale. We hypothesized that bird species richness exhibits a hump-shaped relationship with energy at the regional scale of the northwestern United States. As a result, we hypothesized that the relationship between energy and richness within a landscape is positive in energy-limited landscapes and flat or decreasing in energy-rich landscapes. Additionally, we hypothesized that structural complexity explains less of the variation in species richness in energy-limited environments and more in energy-rich environments and that the slope of the relationship between structural complexity and richness is greatest in energy-rich environments. We sampled bird communities and vegetation across seral stages and biophysical settings at each of five landscapes arrayed across a productivity gradient from the Pacific Coast to the Rocky Mountains within the five northwestern states of the contiguous United States. We analyzed the response of richness to structural complexity and energy covariates at each landscape. We found that (1) richness had a hump-shaped relationship with available energy across the northwestern United States, (2) the landscape-scale relationships between energy and richness were positive or hump shaped in energy-limited locations and were flat or negative in energy-rich locations, (3) forest structural complexity explained more of the variation in bird species richness in energy-rich landscapes, and (4) the slope of the relationship between forest structural complexity and richness was steepest in energy-limited locations. In energy-rich locations, forest managers will likely increase landscape-scale bird diversity by providing a range of forest structural complexity across all seral stages. In low-energy environments, bird diversity will likely be maximized by managing local high-energy hotspots judiciously and adjusting harvest intensities in other locations to compensate for slower regeneration rates.     

Temporal patterns of foraging activity in some wood warblers in relation to the availability of insect prey

Summary I monitored the temporal pattern of diurnal feeding activity in several wood warbler (Parulidae) species and concomitantly recorded the numbers of active (flying) insects in 2 willow habitats in the western United States. At one site the temporal relationship between the density of active and inactive (nonflying) insects was investigated. The diurnal patterns of insect and bird activity were inversely related and each pattern was significantly nonuniform throughout the day; the wood warblers were largely inactive during the middle of the day when insects were most active.As foliage-gleaning birds, wood warblers depend primarily on the availability of inactive (nonflying) insects that they pick from the foliage, and they appear to be limited in their foraging activity by the unavailability of such insects during midday. Interestingly, the duration of midday inactivity for a given bird species varied inversely with the proportion of time that species spent flycatching. Thus, food availability may play an important role in determining the temporal patterns of feeding activity in these insectivorous bird species.