Skip to content

Ecology and Evolution Publishes Issue 3.6

June 17, 2013

ECE 3 6The latest issue of Ecology and Evolution is now live! Over 30 excellent articles free to read, download and share. The cover image is taken from ‘Ejaculate investment and attractiveness in the stalk-eyed fly, Diasemopsis meigenii by Elisabeth Harley et al. Below are some highlights from this issue:

purple_lock_open Belowground interactions shift the relative importance of direct and indirect genetic effects by Mark A. Genung, Joseph K. Bailey and Jennifer A. Schweitzer
Summary: Intraspecific genetic variation can affect decomposition, nutrient cycling, and interactions between plants and their associated belowground communities. However, the effects of genetic variation on ecosystems can also be indirect, meaning that genes in a focal plant may affect ecosystems by altering the phenotype of interacting (i.e., neighboring) individuals. We manipulated genotype identity, species identity, and the possibility of belowground interactions between neighboring Solidago plants. We hypothesized that, because our plants were nitrogen (N) limited, the most important interactions between focal and neighbor plants would occur belowground. More specifically, we hypothesized that the genotypic identity of a plant’s neighbor would have a larger effect on belowground biomass than on aboveground biomass, but only when neighboring plants were allowed to interact belowground.

purple_lock_open Reevaluation of a classic phylogeographic barrier: new techniques reveal the influence of microgeographic climate variation on population divergence by J. Angel Soto-Centeno, Lisa N. Barrow, Julie M. Allen and David L. Reed
Summary: We evaluated the mtDNA divergence and relationships within Geomys pinetis to assess the status of formerly recognized Geomys taxa. Additionally, we integrated new hypothesis-based tests in ecological niche models (ENM) to provide greater insight into causes for divergence and potential barriers to gene flow in Southeastern United States (Alabama, Florida, and Georgia). Our DNA sequence dataset confirmed and strongly supported two distinct lineages within G. pinetis occurring east and west of the ARD. Divergence date estimates showed that eastern and western lineages diverged about 1.37 Ma (1.9 Ma–830 ka). Predicted distributions from ENMs were consistent with molecular data and defined each population east and west of the ARD with little overlap. Niche identity and background similarity tests were statistically significant suggesting that ENMs from eastern and western lineages are not identical or more similar than expected based on random localities drawn from the environmental background.

purple_lock_open Patterns of ecological specialization among microbial populations in the Red Sea and diverse oligotrophic marine environments by Luke R. Thompson, Chris Field, Tamara Romanuk, David Kamanda Ngugi, Rania Siam, Hamza El Dorry and Ulrich Sting
Summary: Large swaths of the nutrient-poor surface ocean are dominated numerically by cyanobacteria (Prochlorococcus), cyanobacterial viruses (cyanophage), and alphaproteobacteria (SAR11). How these groups thrive in the diverse physicochemical environments of different oceanic regions remains poorly understood. Comparative metagenomics can reveal adaptive responses linked to ecosystem-specific selective pressures. The Red Sea is well-suited for studying adaptation of pelagic-microbes, with salinities, temperatures, and light levels at the extreme end for the surface ocean, and low nutrient concentrations, yet no metagenomic studies have been done there. The Red Sea (high salinity, high light, low N and P) compares favorably with the Mediterranean Sea (high salinity, low P), Sargasso Sea (low P), and North Pacific Subtropical Gyre (high light, low N). We quantified the relative abundance of genetic functions among Prochlorococcus, cyanophage, and SAR11 from these four regions. Gene frequencies indicate selection for phosphorus acquisition (Mediterranean/Sargasso), DNA repair and high-light responses (Red Sea/Pacific Prochlorococcus), and osmolyte C1 oxidation (Red Sea/Mediterranean SAR11). The unexpected connection between salinity-dependent osmolyte production and SAR11 C1 metabolism represents a potentially major coevolutionary adaptation and biogeochemical flux.

purple_lock_open Forecasting deforestation and carbon emissions in tropical developing countries facing demographic expansion: a case study in Madagascar by Ghislain Vieilledent, Clovis Grinand and Romuald Vaudry
Summary: Anthropogenic deforestation in tropical countries is responsible for a significant part of global carbon dioxide emissions in the atmosphere. To plan efficient climate change mitigation programs (such as REDD+, Reducing Emissions from Deforestation and forest Degradation), reliable forecasts of deforestation and carbon dioxide emissions are necessary. Although population density has been recognized as a key factor in tropical deforestation, current methods of prediction do not allow the population explosion that is occurring in many tropical developing countries to be taken into account. Here, we propose an innovative approach using novel computational and statistical tools, including R/GRASS scripts and the new phcfM R package, to model the intensity and location of deforestation including the effect of population density. We used the model to forecast anthropogenic deforestation and carbon dioxide emissions in five large study areas in the humid and spiny-dry forests of Madagascar. Using our approach, we were able to demonstrate that the current rapid population growth in Madagascar (+3.39% per year) will significantly increase the intensity of deforestation by 2030 (up to +1.17% per year in densely populated areas).

Read other top articles in this issue >

Submit your paper to Ecology and Evolution here >

Sign up for e-toc alerts here >

Advertisements
No comments yet

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: