Remotely sensed albedo allows the identification of two ecosystem states along aridity gradients in Africa

Empirical verification of multiple states in drylands is scarce, impeding the design of indicators to anticipate the onset of desertification. Remote sensing‐derived indicators of ecosystem states are gaining new ground due to the possibilities they bring to be applied inexpensively over large areas. Remotely sensed albedo has been often used to monitor drylands due to its close relationship with ecosystem status and climate. Here, we used a space‐for‐time‐substitution approach to evaluate whether albedo (averaged from 2000 to 2016) can identify multiple ecosystem states in African drylands spanning from the Saharan desert to tropical Africa. By using latent class analysis, we found that albedo showed two states (low and high; the cut‐off level was 0.22 at the shortwave band). Potential analysis revealed that albedo exhibited an abrupt and discontinuous increase with increased aridity (1 − [precipitation/potential evapotranspiration]). The two albedo states co‐occurred along aridity values ranging from 0.72 to 0.78, during which vegetation cover exhibited a rapid, continuous decrease from ~90% to ~50%. At aridity values of 0.75, the low albedo state started to exhibit less attraction than the high albedo state. Low albedo areas beyond this aridity value were considered as vulnerable regions where abrupt shifts in albedo may occur if aridity increases, as forecasted by current climate change models. Our findings indicate that remotely sensed albedo can identify two ecosystem states in African drylands. They support the suitability of albedo indices to inform us about discontinuous responses to aridity experienced by drylands, which can be linked to the onset of land degradation.This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDA19030500), the National Key Research and Development Program of China (Grant 2016YFC0503302), the European Research Council (BIODESERT project, ERC Grant Agreement 647038), the Joint PhD, Training Program of the University of Chinese Academy of Sciences, and the Research Foundation of Henan University of Technology (Grant 31401178)

MODIS time series contribution for the estimation of nutritional properties of alpine grassland

This is an Accepted Manuscript of an article published by Taylor & Francis in European Journal of Remote Sensing on 17th February 2017, available online: https://doi.org/10.5721/EuJRS20164936Despite the Normalised Difference Vegetation Index (NDVI) has been used to make predictions on forage quality, its relationship with bromatological field data has not been widely tested. This relationship was investigated in alpine grasslands of the Gran Paradiso National Park (Italian Alps). Predictive models were built using remotely sensed derived variables (NDVI and phenological information computed from MODIS) in combination with geo-morphometric data as predictors of measured biomass, crude protein, fibre and fibre digestibility, obtained from 142 grass samples collected within 19 experimental plots every two weeks during the whole 2012 growing season. The models were both cross-validated and validated on an independent dataset (112 samples collected during 2013). A good predictability ability was found for the estimation of most of the bromatological measures, with a considerable relative importance of remotely sensed derived predictors; instead, a direct use of NDVI values as a proxy of bromatological variables appeared not to be supported

Comparison of methods for estimation of absolute vegetation and soil fractional cover using MODIS normalized BRDF-adjusted reflectance data

Green vegetation (GV), nonphotosynthetic vegetation (NPV), and soil are important ground cover components in terrestrial ecosystems worldwide. There are many good methods for observing the dynamics of GV with optical remote sensing, but there are fewer good methods for observing the dynamics of NPV and soil. Given the difficulty of remotely deriving information on NPV and soil, the purpose of this study is to evaluate several methods for the retrieval of information on fractional cover of GV, NPV, and soil using 500-m MODIS nadir BRDF-adjusted reflectance (NBAR) data. In particular, three spectral mixture analysis (SMA) techniques are evaluated: simple SMA, multiple-endmember SMA (MESMA), and relative SMA (RSMA). In situ cover data from agricultural fields in Southern Australia are used as the basis for comparison. RSMA provides an index of fractional cover of GV, NPV, and soil, so a method for converting these to absolute fractional cover estimates is also described and evaluated. All methods displayed statistically significant correlations with in situ data. All methods proved equally capable at predicting the dynamics of GV. MESMA predicted NPV dynamics best. RSMA predicted dynamics of soil best. The method for converting RSMA indices to fractional cover estimates provided estimates that were comparable to those provided by SMA and MESMA. Although it does not always provide the best estimates of ground component dynamics, this study shows that RSMA indices are useful indicators of GV, NPV, and soil cover. However, our results indicate that the choice of unmixing technique and its implementation ought to be application-specific, with particular emphasis on which ground cover retrieval requires the greatest accuracy and how much ancillary data is available to support the analysis.Gregory S. Okin, Kenneth D. Clarke, Megan M. Lewi

A Genomewide Screen for Suppressors of Alu-Mediated Rearrangements Reveals a Role for PIF1

Alu-mediated rearrangement of tumor suppressor genes occurs frequently during carcinogenesis. In breast cancer, this mechanism contributes to loss of the wild-type BRCA1 allele in inherited disease and to loss of heterozygosity in sporadic cancer. To identify genes required for suppression of Alu-mediated recombination we performed a genomewide screen of a collection of 4672 yeast gene deletion mutants using a direct repeat recombination assay. The primary screen and subsequent analysis identified 12 candidate genes including TSA, ELG1, and RRM3, which are known to play a significant role in maintaining genomic stability. Genetic analysis of the corresponding human homologs was performed in sporadic breast tumors and in inherited BRCA1-associated carcinomas. Sequencing of these genes in high risk breast cancer families revealed a potential role for the helicase PIF1 in cancer predisposition. PIF1 variant L319P was identified in three breast cancer families; importantly, this variant, which is predicted to be functionally damaging, was not identified in a large series of controls nor has it been reported in either dbSNP or the 1000 Genomes Project. In Schizosaccharomyces pombe, Pfh1 is required to maintain both mitochondrial and nuclear genomic integrity. Functional studies in yeast of human PIF1 L319P revealed that this variant cannot complement the essential functions of Pfh1 in either the nucleus or mitochondria. Our results provide a global view of nonessential genes involved in suppressing Alu-mediated recombination and implicate variation in PIF1 in breast cancer predisposition

Woodland Caribou Habitat Selection Patterns in Relation to Predation Risk and Forage Abundance Depend on Reproductive State

The ideal free distribution assumes that animals select habitats that are beneficial to their fitness. When the needs of dependent offspring differ from those of the parent, ideal habitat selection patterns could vary with the presence or absence of offspring. We test whether habitat selection depends on reproductive state due to top‐down or bottom‐up influences on the fitness of woodland caribou (Rangifer tarandus caribou), a threatened, wide‐ranging herbivore. We combined established methods of fitting resource and step selection functions derived from locations of collared animals in Ontario with newer techniques, including identifying calf status from video collar footage and seasonal habitat selection analysis through latent selection difference functions. We found that females with calves avoided predation risk and proximity to roads more strongly than females without calves within their seasonal ranges. At the local scale, females with calves avoided predation more strongly than females without calves. Females with calves increased predation avoidance but not selection for food availability upon calving, whereas females without calves increased selection for food availability across the same season. These behavioral responses suggest that habitat selection by woodland caribou is influenced by reproductive state, such that females with calves at heel use habitat selection to offset the increased vulnerability of their offspring to predation risk