Following on from the release of Ecology and Evolution’s first Impact Factor, the latest issue of Ecology and Evolution is now live! Over 30 excellent articles free to read, download and share. The cover image has been taken from the article Inbreeding reveals mode of past selection on male reproductive characters in Drosophila melanogaster by Outi Ala-Honkola et al. Below are some highlights from this issue:
An age–size reaction norm yields insight into environmental interactions affecting life-history traits: a factorial study of larval development in the malaria mosquitoAnopheles gambiae sensu stricto by Conan Phelan and Bernard D. Rotiberg
Summary: Environmental factors frequently act nonindependently to determine growth and development of insects. Because age and size at maturity strongly influence population dynamics, interaction effects among environmental variables complicate the task of predicting dynamics of insect populations under novel conditions. We reared larvae of the African malaria mosquito Anopheles gambiae sensu stricto (s.s.) under three factors relevant to changes in climate and land use: food level, water depth, and temperature. Each factor was held at two levels in a fully crossed design, for eight experimental treatments. Larval survival, larval development time, and adult size (wing length) were measured to indicate the importance of interaction effects upon population-level processes. For age and size at emergence, but not survival, significant interaction effects were detected for all three factors, in addition to sex. Some of these interaction effects can be understood as consequences of how the different factors influence energy usage in the context of a nonindependent relationship between age and size. Experimentally assessing interaction effects for all potential future sets of conditions is intractable. However, considering how different factors affect energy usage within the context of an insect’s evolved developmental program can provide insight into the causes of complex environmental effects on populations.
Foraging area fidelity for Kemp’s ridleys in the Gulf of Mexico by Donna J. Shaver, Kristen M. Hart, Ikuko Fujisaki, Cynthia Rubio, Autumn R. Sartain, Jaime Peña, Patrick M. Burchfield, Daniel Gomez Gamez and Jaime Ortiz
Summary: For many marine species, locations of key foraging areas are not well defined. We used satellite telemetry and switching state-space modeling (SSM) to identify distinct foraging areas used by Kemp’s ridley turtles (Lepidochelys kempii) tagged after nesting during 1998–2011 at Padre Island National Seashore, Texas, USA (PAIS; N = 22), and Rancho Nuevo, Tamaulipas, Mexico (RN; N = 9). Overall, turtles traveled a mean distance of 793.1 km (±347.8 SD) to foraging sites, where 24 of 31 turtles showed foraging area fidelity (FAF) over time (N = 22 in USA, N = 2 in Mexico). Multiple turtles foraged along their migratory route, prior to arrival at their “final” foraging sites. We identified new foraging “hotspots” where adult female Kemp’s ridley turtles spent 44% of their time during tracking (i.e., 2641/6009 tracking days in foraging mode). Nearshore Gulf of Mexico waters served as foraging habitat for all turtles tracked in this study; final foraging sites were located in water <68 m deep and a mean distance of 33.2 km (±25.3 SD) from the nearest mainland coast. Distance to release site, distance to mainland shore, annual mean sea surface temperature, bathymetry, and net primary production were significant predictors of sites where turtles spent large numbers of days in foraging mode. Spatial similarity of particular foraging sites selected by different turtles over the 13-year tracking period indicates that these areas represent critical foraging habitat, particularly in waters off Louisiana. Furthermore, the wide distribution of foraging sites indicates that a foraging corridor exists for Kemp’s ridleys in the Gulf. Our results highlight the need for further study of environmental and bathymetric components of foraging sites and prey resources contained therein, as well as international cooperation to protect essential at-sea foraging habitats for this imperiled species.
A new method for identifying rapid decline dynamics in wild vertebrate populations by Martina Di Fonzo, Ben Collen and Georgina M. Mace
Summary: Tracking trends in the abundance of wildlife populations is a sensitive method for assessing biodiversity change due to the short time-lag between human pressures and corresponding shifts in population trends. This study tests for proposed associations between different types of human pressures and wildlife population abundance decline-curves and introduces a method to distinguish decline trajectories from natural fluctuations in population time-series. First, we simulated typical mammalian population time-series under different human pressure types and intensities and identified significant distinctions in population dynamics. Based on the concavity of the smoothed population trend and the algebraic function which was the closest fit to the data, we determined those differences in decline dynamics that were consistently attributable to each pressure type. We examined the robustness of the attribution of pressure type to population decline dynamics under more realistic conditions by simulating populations under different levels of environmental stochasticity and time-series data quality. Finally, we applied our newly developed method to 124 wildlife population time-series and investigated how those threat types diagnosed by our method compare to the specific threatening processes reported for those populations. We show how wildlife population decline curves can be used to discern between broad categories of pressure or threat types, but do not work for detailed threat attributions. More usefully, we find that differences in population decline curves can reliably identify populations where pressure is increasing over time, even when data quality is poor, and propose this method as a cost-effective technique for prioritizing conservation actions between populations.
Estimating resource selection with count data by Ryan M. Nielson and Hall Sawyer
Summary: Resource selection functions (RSFs) are typically estimated by comparing covariates at a discrete set of “used” locations to those from an “available” set of locations. This RSF approach treats the response as binary and does not account for intensity of use among habitat units where locations were recorded. Advances in global positioning system (GPS) technology allow animal location data to be collected at fine spatiotemporal scales and have increased the size and correlation of data used in RSF analyses. We suggest that a more contemporary approach to analyzing such data is to model intensity of use, which can be estimated for one or more animals by relating the relative frequency of locations in a set of sampling units to the habitat characteristics of those units with count-based regression and, in particular, negative binomial (NB) regression. We demonstrate this NB RSF approach with location data collected from 10 GPS-collared Rocky Mountain elk (Cervus elaphus) in the Starkey Experimental Forest and Range enclosure. We discuss modeling assumptions and show how RSF estimation with NB regression can easily accommodate contemporary research needs, including: analysis of large GPS data sets, computational ease, accounting for among-animal variation, and interpretation of model covariates. We recommend the NB approach because of its conceptual and computational simplicity, and the fact that estimates of intensity of use are unbiased in the face of temporally correlated animal location data.
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