Anti-RAN monoclonal antibody, clone FQS21801(C)

Land-use change has been the strongest driver of vegetation cover change in the world. In the South American Dry Chaco (similar to 1 M km(2); PPT/ET0 < 0.65), native dry forests are experiencing high deforestation rates that tend to continue in the coming years. Here, we used a hydrological model (Hydrus 1-D) to analyze changes in the water balance triggered by the replacement of dry forests by annual rainfed summer crops. We found that transpiration represented the main water vapour flux in both vegetation covers (59 and 48% of annual rainfall in dry forest and cropland, respectively), followed by evaporation (31 and 30%, respectively) and interception (11 and 9%, respectively). Runoff was five times higher in the cropland compared to the dry forest (10 vs. 2%; p < 0.01). Deep drainage was a negligible water flux in dry forests but it represented 4% of annual rainfall in croplands (p < 0.01), reaching values of zero and 130 mm year(-1) for dry and wet years, respectively. Our results highlight the key role of vegetation cover controlling ecosystem water fluxes in the Dry Chaco. More generally, we suggest that the expansion of dryland cultivation can modify the regional water balance and threaten the primary production of ecosystems in the long run.

We begin with a review of combinatorial hives as introduced by Knutson and Tao, and focus on a conjecture by Danilov and Koshevoy for generating hives from Hermitian matrix pairs. We examine a proposal by Appleby and Whitehead in the spirit of this conjecture and analytically elucidate an obstruction in their construction for guaranteeing hive generation, while detailing stronger conditions under which we can produce hives with almost certain probability. We provide the first mapping of this prescription onto a practical algorithmic space that enables affirming computational results and opens a new area of research into the analysis of the random geometries of hive surfaces. The second part of this article concerns methods of estimating Littlewood-Richardson coefficients from hives. We illustrate experimental confirmation and characterize two numerical algorithms: a rounded estimator on the continuous hive polytope following Narayanan, and a novel construction using a coordinate hit-and-run on the hive lattice.