Do flying beetles respond to human-dominated landscapes as complex mosaics or binary patterns

Abstract

Understanding and measuring functional connectivity for animals with habitats that have been fragmented by human activity requires that the biology and movement of the species be considered. We used least cost paths in GIS to test hypotheses regarding how different species of longhorned beetles likely connect habitats with dispersal. We predicted that there would be differences in the functional connectivity of landscapes depending on species larval niche breadth, adult feeding habits, and the potential for use of non-forest habitats. For the species with very specialized larvae, we developed a classification tree to determine areas likely to contain the appropriate species of host tree. Connectivity calculated using least cost paths did not out-perform Euclidean distances for three generalist beetles. This was also the case for the specialist beetle species when all forest was considered habitat. However, when we delineated habitat based on areas likely to support the host tree the functional connectivity incorporating least cost paths was a much better predictor than that using Euclidean distances. Generalists may respond to fragmented habitat in a binary habitat-matrix way while more specialized species may respond to a mosaic. These trends are obscured if habitat is defined by human perceptions rather than species biology.

How do field margins contribute to the functional connectivity of insect-pollinated plants?

“…(ii) C. sancta occurs in unploughed fields, which may lead pollinators to make intermediate stops between our sampling points. Additionally, it is pollinated by a generalist insect, Apis mellifera that may be attracted to a broader range of floral resources and thus be less affected by the apparent landscape heterogeneity, consistently with the findings of Foley and Holland (2010) on generalist flying beetles, known to travel straight between resources. (iii) Finally, the subtle contrasts pointed out between the alternative models integrating the heterogeneity of the matrix, and the reference models may proceed from the difficulty that we encountered in inferring the resistance values for each landscape feature.…”

Fifteen years of Landscape Online: Looking back at the development of an e-journal

“…From 2007 until 2012, the topics were often related to geographical landscape research, topological ecological approaches and natural sciences. Articles addressed factors that affect ecosystems and species, e.g., change of treelines (Holtmeier, 2012;Holtmeier and Broll, 2007;Kullman, 2010;Öberg and Kullman, 2012;Szerencsits, 2012), diversity and compositions of vegetation (Mehmeti et al, 2009;Richter et al, 2009) abundance and distribution of avifauna (Riffell et al, 2012(Riffell et al, , 2008, and insects (Foley and Holland, 2010). Articles also focused on landscape metrics analysis (Bianchin et al, 2011;Herbst et al, 2009;Hoechstetter et al, 2008), including multiple dimensions and 3D-metrics (Drǎguţ et al, 2010;Stupariu et al, 2010), as well as further geostatistical approaches for landscape classifications (Schröder et al, 2007).…”

Graph and circuit theory connectivity models of conservation biological control agents

“…To take into account these effects, a few studies have measured least-cost path distance and counted successful dispersal events (Bunn et al 2000, Lookingbill et al 2010. A least-cost path is calculated by an algorithm to find the optimal, least costly, single path for an animal movement on a map representing resistance to movement (e.g., Foley and Holland 2010). However, it is often indicated that a least-cost path is not necessarily the path used and does not allow for more realistic movement along many alternative paths simultaneously (Fahrig 2007, Pinto andKeitt 2009).…”