Understanding Demographic and Behavioral Mechanisms that Guide Responses of Neotropical Migratory Birds to Urbanization: a Simulation Approach

Although studies often report that densities of many forest birds are negatively related to urbanization, the mechanisms guiding this pattern are poorly understood. Our objective was to use a population simulation to examine the relative influence of six demographic and behavioral processes on patterns of avian abundance in urbanizing landscapes. We constructed an individual-based population simulation model representing the annual cycle of a Neotropical migratory songbird. Each simulation was performed under two landscape scenarios. The first scenario had similar proportions of high- and low-quality habitat across the urban to rural gradient. Under the first scenario, avian density was negatively related to urbanization only when rural habitats were perceived to be of higher quality than they actually were. The second landscape scenario had declining proportions of high-quality habitat as urbanization increased. Under the second scenario, each mechanism generated a negative relationship between density and urbanization. The strongest effect on density resulted when birds preferentially selected habitats in landscapes from which they fledged or were constrained from dispersing. The next strongest patterns occurred when birds directly evaluated habitat quality and accurately selected the highest-quality available territories. When birds selected habitats based on the presence of conspecifics, the density–urbanization relationship was only one-third the strength of other habitat selection mechanisms and only occurred under certain levels of population survival. Although differences in adult or nest survival in the face of random habitat selection still elicited reduced densities in urban landscapes, the relationships between urbanization and density were weaker than those produced by the conspecific attraction mechanism. Results from our study identify key predictions and areas for future research, including assessing habitat quality in urban and rural areas in order to determine if habitats in urban areas are underutilized.

Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives

Two types of ecological thresholds are now being widely used to develop conservation targets: breakpoint-based thresholds represent tipping points where system properties change dramatically, whereas classification thresholds identify groups of data points with contrasting properties. Both breakpoint-based and classification thresholds are useful tools in evidence-based conservation. However, it is critical that the type of threshold to be estimated corresponds with the question of interest and that appropriate statistical procedures are used to determine its location. On the basis of their statistical properties, we recommend using piecewise regression methods to identify breakpoint-based thresholds and discriminant analysis or classification and regression trees to identify classification thresholds.