Documenting lemming population change in the Arctic: Can we detect trends?

Lemmings are a key component of tundra food webs and changes in their dynamics can affect the whole ecosystem. We present a comprehensive overview of lemming monitoring and research activities, and assess recent trends in lemming abundance across the circumpolar Arctic. Since 2000, lemmings have been monitored at 49 sites of which 38 are still active. The sites were not evenly distributed with notably Russia and high Arctic Canada underrepresented. Abundance was monitored at all sites, but methods and levels of precision varied greatly. Other important attributes such as health, genetic diversity and potential drivers of population change, were often not monitored. There was no evidence that lemming populations were decreasing in general, although a negative trend was detected for low arctic populations sympatric with voles. To keep the pace of arctic change, we recommend maintaining long-term programmes while harmonizing methods, improving spatial coverage and integrating an ecosystem perspective.     

Assessing aboveground tropical forest biomass using Google Earth canopy images

Reducing Emissions from Deforestation and Forest Degradation (REDD) in efforts to combat climate change requires participating countries to periodically assess their forest resources on a national scale. Such a process is particularly challenging in the tropics because of technical difficulties related to large aboveground forest biomass stocks, restricted availability of affordable, appropriate remote-sensing images, and a lack of accurate forest inventory data. In this paper, we apply the Fourier-based FOTO method of canopy texture analysis to Google Earth's very-high-resolution images of the wet evergreen forests in the Western Ghats of India in order to (1) assess the predictive power of the method on aboveground biomass of tropical forests, (2) test the merits of free Google Earth images relative to their native commercial IKONOS counterparts and (3) highlight further research needs for affordable, accurate regional aboveground biomass estimations. We used the FOTO method to ordinate Fourier spectra of 1436 square canopy images (125 x 125 m) with respect to a canopy grain texture gradient (i.e., a combination of size distribution and spatial pattern of tree crowns), benchmarked against virtual canopy scenes simulated from a set of known forest structure parameters and a 3-D light interception model. We then used 15 1-ha ground plots to demonstrate that both texture gradients provided by Google Earth and IKONOS images strongly correlated with field-observed stand structure parameters such as the density of large trees, total basal area, and aboveground biomass estimated from a regional allometric model. Our results highlight the great potential of the FOTO method applied to Google Earth data for biomass retrieval because the texture-biomass relationship is only subject to 15% relative error, on average, and does not show obvious saturation trends at large biomass values. We also provide the first reliable map of tropical forest aboveground biomass predicted from free Google Earth images.     

Incompletely resolved phylogenetic trees inflate estimates of phylogenetic conservatism

The tendency for more closely related species to share similar traits and ecological strategies can be explained by their longer shared evolutionary histories and represents phylogenetic conservatism. How strongly species traits co-vary with phylogeny can significantly impact how we analyze cross-species data and can influence our interpretation of assembly rules in the rapidly expanding field of community phylogenetics. Phylogenetic conservatism is typically quantified by analyzing the distribution of species values on the phylogenetic tree that connects them. Many phylogenetic approaches, however, assume a completely sampled phylogeny: while we have good estimates of deeper phylogenetic relationships for many species-rich groups, such as birds and flowering plants, we often lack information on more recent interspecific relationships (i.e., within a genus). A common solution has been to represent these relationships as polytomies on trees using taxonomy as a guide. Here we show that such trees can dramatically inflate estimates of phylogenetic conservatism quantified using S. P. Blomberg et al.'s K statistic. Using simulations, we show that even randomly generated traits can appear to be phylogenetically conserved on poorly resolved trees. We provide a simple rarefaction-based solution that can reliably retrieve unbiased estimates of K, and we illustrate our method using data on first flowering times from Thoreau's woods (Concord, Massachusetts, USA).     

Nesting habits shape feeding preferences and predatory behavior in an ant genus

We tested if nesting habits influence ant feeding preferences and predatory behavior in the monophyletic genus Pseudomyrmex (Pseudomyrmecinae) which comprises terrestrial and arboreal species, and, among the latter, plant-ants which are obligate inhabitants of myrmecophytes (i.e., plants sheltering so-called plant-ants in hollow structures). A cafeteria experiment revealed that the diet of ground-nesting Pseudomyrmex consists mostly of prey and that of arboreal species consists mostly of sugary substances, whereas the plant-ants discarded all the food we provided. Workers forage solitarily, detecting prey from a distance thanks to their hypertrophied eyes. Approach is followed by antennal contact, seizure, and the manipulation of the prey to sting it under its thorax (next to the ventral nerve cord). Arboreal species were not more efficient at capturing prey than were ground-nesting species. A large worker size favors prey capture. Workers from ground- and arboreal-nesting species show several uncommon behavioral traits, each known in different ant genera from different subfamilies: leaping abilities, the use of surface tension strengths to transport liquids, short-range recruitment followed by conflicts between nestmates, the consumption of the prey’s hemolymph, and the retrieval of entire prey or pieces of prey after having cut it up. Yet, we never noted group ambushing. We also confirmed that Pseudomyrmex plant-ants live in a kind of food autarky as they feed only on rewards produced by their host myrmecophyte, or on honeydew produced by the hemipterans they attend and possibly on the fungi they cultivate.     

Negative relationship between dispersal distance and demography in butterfly metapopulations

Little is known about the connection between demography and dispersal in metapopulations. The meta-analysis of the population time series of five butterfly species indicated that (meta)population dynamics are driven by density-dependent factors. Inter-specific comparison reveals a significant inverse relationship between population growth rate and the magnitude of dispersal distance. As the range of dispersal distances is constrained by the patch system, dispersing individuals moving too far away would (probably) get lost. This generates selective pressures on individuals with a high dispersal propensity, but favors individuals investing more in reproduction and results in a higher (meta)population growth rate. From a conservation perspective, individuals from (meta)populations and species sacrificing dispersal for the sake of reproductive performances are most vulnerable because of their higher sensitivity to stochastic events: the temporal variation of growth rate was much higher in the two metapopulations where dispersal was limited.     

An acanthocephalan parasite increases the salinity tolerance of the freshwater amphipod <Emphasis Type="Italic">Gammarus roeseli</Emphasis> (Crustacea: Gammaridae)

Studies of the influence of parasites on host fitness generally conclude that parasites have a strong negative effect on their hosts. In this study, we have investigated experimentally the role of Polymorphus minutus, an acanthocephalan parasite, on the salinity tolerance of the freshwater amphipod Gammarus roeseli, one of its intermediate hosts. Unexpectedly, P. minutus-infected gammarids were more tolerant to salinity stress than uninfected ones. The mean lethal salt concentrations for 50% mortality of hosts tested were 17.3 (infected) and 9.7 g/L (uninfected). The parasitic load (one or two parasites per host) did not affect the result. The size of hosts had no significant influence on the salinity tolerance of either infected or uninfected gammarids. The mobility of all types of gammarid decreased when the salinity exceeded 9.0 g/L, but there was no significant difference between infected and uninfected gammarids. We discuss the higher salinity tolerance of infected amphipods in relation to O₂ consumption and osmoregulation. Finally, we demonstrate that the salinity tolerance is enhanced in the parasitized amphipod but without a significant change in behavior or an osmoregulatory adjustment.     

Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

Immunocompetence analysis of the aquatic snail Lymnaea stagnalis exposed to urban wastewaters

Environmental Science and Pollution Research - Wastewater treatment plant effluents from urban area are a well-known source of chronic multiple micropollution to the downstream living organisms. In...