Key Words ecological boundary, ecotone, edge effect, effective area model, core area model, habitat fragmentation ■ Abstract Edge effects have been studied for decades because they are a key component to understanding how landscape structure influences habitat quality. However, making sense of the diverse patterns and extensive variability reported in the literature has been difficult because there has been no unifying conceptual framework to guide research. In this review, we identify four fundamental mechanisms that cause edge responses: ecological flows, access to spatially separated resources, resource mapping, and species interactions. We present a conceptual framework that identifies the pathways through which these four mechanisms can influence distributions, ultimately leading to new ecological communities near habitat edges. Next, we examine a predictive model of edge responses and show how it can explain much of the variation reported in the literature. Using this model, we show that, when observed, edge responses are largely predictable and consistent. When edge responses are variable for the same species at the same edge type, observed responses are rarely in opposite directions. We then show how remaining variability may be understood within our conceptual frameworks. Finally, we suggest that, despite all the research in this area, the development of tools to extrapolate edge responses to landscapes has been slow, restricting our ability to use this information for conservation and management.

Habitat loss is a primary threat to biodiversity across the planet, yet contentious debate has ensued on the importance of habitat fragmentation 'per se' (i.e., altered spatial configuration of habitat for a given amount of habitat loss). Based on a review of landscape-scale investigations, Fahrig (2017; Ecological responses to habitat fragmentation per se. Annual Review of Ecology, Evolution, and Systematics 48:1-23) reports that biodiversity responses to habitat fragmentation Highlights  Habitat loss and fragmentation have long been considered to have negative effects on biodiversity, yet recent review by Fahrig (2017) argues that in fact habitat fragmentation has largely positive effects on biodiversity.  We highlight several key shortcomings to the approach taken in Fahrig (2017) that limits conclusions regarding habitat fragmentation effects.  Several sources of counter evidence not considered in Fahrig (2017) illustrate that negative effects of habitat fragmentation are common and that positive effects can be misleading or not of conservation importance.  We provide six key reasons why the conclusions in Fahrig (2017) should not be used in conservation decision-making.

Edge effects are among the most extensively studied ecological phenomena, yet we lack a general, predictive framework to understand the patterns and variability observed. We present a conceptual model, based on resource distribution, that predicts whether organismal abundances near edges are expected to increase, decrease, or remain unchanged for any species at any edge type. Predictions are based on whether resources are found predominantly in one habitat (decreased abundance in preferred habitat, increase in non‐preferred), divided between habitats (predicts an increase near both edges), spread equally among habitats (predicts a neutral edge response), or concentrated along the edge (increase). There are several implications of this model that can explain much of the variability reported in the edge literature. For instance, our model predicts that a species may show positive, negative, and neutral responses, depending on the edge type encountered, which explains some intraspecific variability observed in the literature. In addition, any predictable change in resource use (for example, by region or season) may explain temporal or spatial variability in responses even for the same species at the same edge type. We offer a preliminary test of our model by making predictions for 52 bird species from three published studies of abundance responses near forest edges. Predictions are based solely on general information about each species' habitat associations and resource use. Our model correctly predicted the direction of 25 out of 29 observed edge responses, although it tended to under‐predict increases and over‐predict decreases. This model is important because it helps make sense of a largely descriptive literature and allows future studies to be carried out under a predictive framework.

Summary1. The behaviour of two butterfly species, a habitat specialist ( Speyeria idalia ) and a habitat generalist ( Danaus plexippus ), was tracked at four prairie edges to determine the extent to which edges act as a barrier to emigration. The four edge types studied were crop, road, field and treeline. The edges differed in structure ranging from highcontrast (treeline) to low-contrast (field). 2. S. idalia , the habitat specialist, responded strongly to all edges, even those with low structural contrast. However, S. idalia 's response was strongly affected by conspecific density at crop and field edges; individuals were less likely to exit from high density plots. S. idalia responded to edges both by turning to avoid crossing them, and returning to the plot if they had crossed. 3. D. plexippus responded strongly only to treeline edges. Wind direction and time of year were important factors influencing behaviour at edges for this species. Conspecific density was not a significant factor affecting their behaviour. D. plexippus responded to edges by not crossing them, but rarely returned once they had crossed. 4. In highly fragmented landscapes, such as the one in which this study occurred, butterflies which show little or no response to edges may exhibit high emigration rates because of the high probability of encountering an edge in small habitat patches. Butterflies may respond strongly to even subtle habitat boundaries, but those responses may be modified by the edge structure, local environment or other conditions. Therefore, modifying edge structure may be a way to influence emigration rates, making it a useful tool for conservation.

Understanding the impacts of climate on migratory species is complicated by the fact that these species travel through several climates that may be changing in diverse ways throughout their complete migratory cycle. Most studies are not designed to tease out the direct and indirect effects of climate at various stages along the migration route. We assess the impacts of spring and summer climate conditions on breeding monarch butterflies, a species that completes its annual migration cycle over several generations. No single, broad-scale climate metric can explain summer breeding phenology or the substantial year-to-year fluctuations observed in population abundances. As such, we built a Poisson regression model to help explain annual arrival times and abundances in the Midwestern United States. We incorporated the climate conditions experienced both during a spring migration/breeding phase in Texas as well as during subsequent arrival and breeding during the main recruitment period in Ohio. Using data from a state-wide butterfly monitoring network in Ohio, our results suggest that climate acts in conflicting ways during the spring and summer seasons. High spring precipitation in Texas is associated with the largest annual population growth in Ohio and the earliest arrival to the summer breeding ground, as are intermediate spring temperatures in Texas. On the other hand, the timing of monarch arrivals to the summer breeding grounds is not affected by climate conditions within Ohio. Once in Ohio for summer breeding, precipitation has minimal impacts on overall abundances, whereas warmer summer temperatures are generally associated with the highest expected abundances, yet this effect is mitigated by the average seasonal temperature of each location in that the warmest sites receive no benefit of above average summer temperatures. Our results highlight the complex relationship between climate and performance for a migrating species and suggest that attempts to understand how monarchs will be affected by future climate conditions will be challenging.