Beaver herbivory of willow under two flow regimes: a comparative study on the Green and Yampa rivers

The effect of flow regulation on plant-herbivore ecology has received very little attention, despite the fact that flow regulation can alter both plant and animal abundance and environmental factors that mediate interactions between them. To determine how regulated flows have impacted beaver ( Castor Canadensis ) and sandbar willow ( Salix exigua ) ecology, we first quantified the abundance and mapped the spatial distribution of sandbar willow on alluvial sections of the flow-regulated Green River and free-flowing Yampa River in northwestern Colorado. We then established 16 and 15 plots (1 m x 2.7 m) in patches of willow on the Green and Yampa Rivers, respectively, to determine whether rates of beaver herbivory of willow differed between rivers (Green versus Yampa River), seasons (fall-winter versus spring-summer), and years (spring 1998-spring 1999 versus spring 1999-spring 2000). Areal extent of willow was similar on each river, but Green River willow patches were smaller and more numerous. Beavers cut more stems during fall and winter than spring and summer and cut over 6 times more stems (percentage basis) on the Green River than on the Yampa River. We attribute the between-river difference in herbivory to higher availability of willow, greater beaver density, and lower availability of young Fremont cottonwood ( Populus deltoids subsp. wislizenii ; an alternative food source) on the Green River. Flow regulation increased willow availability to beaver by promoting the formation of island patches that are continuously adjacent to water and feature a perimeter with a relatively high proportion of willow interfacing with water.     

Solutions for a cultivated planet

Increasing population and consumption are placing unprecedented demands on agriculture and natural resources. Today, approximately a billion people are chronically malnourished while our agricultural systems are concurrently degrading land, water, biodiversity and climate on a global scale. To meet the world's future food security and sustainability needs, food production must grow substantially while, at the same time, agriculture's environmental footprint must shrink dramatically. Here we analyse solutions to this dilemma, showing that tremendous progress could be made by halting agricultural expansion, closing 'yield gaps' on underperforming lands, increasing cropping efficiency, shifting diets and reducing waste. Together, these strategies could double food production while greatly reducing the environmental impacts of agriculture.     

Ancestral polyploidy in seed plants and angiosperms

Whole-genome duplication (WGD), or polyploidy, followed by gene loss and diploidization has long been recognized as an important evolutionary force in animals, fungi and other organisms, especially plants. The success of angiosperms has been attributed, in part, to innovations associated with gene or whole-genome duplications, but evidence for proposed ancient genome duplications pre-dating the divergence of monocots and eudicots remains equivocal in analyses of conserved gene order. Here we use comprehensive phylogenomic analyses of sequenced plant genomes and more than 12.6 million new expressed-sequence-tag sequences from phylogenetically pivotal lineages to elucidate two groups of ancient gene duplications-one in the common ancestor of extant seed plants and the other in the common ancestor of extant angiosperms. Gene duplication events were intensely concentrated around 319 and 192 million years ago, implicating two WGDs in ancestral lineages shortly before the diversification of extant seed plants and extant angiosperms, respectively. Significantly, these ancestral WGDs resulted in the diversification of regulatory genes important to seed and flower development, suggesting that they were involved in major innovations that ultimately contributed to the rise and eventual dominance of seed plants and angiosperms.     

Evaluation of the predictive performance of biased regression estimators

Regression models are widely used in forecasting, either directly as prediction equations, or indirectly as the basis of other procedures. The predictive performance of a regression model can be adversely affected by both multicollinearity and high-leverage data points. Although biased estimation procedures have been proposed as an alternative to least squares, there has been little analysis of the predictive performance of the resulting equations. This paper discusses the predictive performance of various biased estimators, emphasizing the concept that the predictive region, as well as the strength of the multicollinearity, dictates the choice of appropriate coefficient estimators.