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A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence–absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size ( n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) faces multiple problems. The main one is improving the lives of the 30% of its population that suffers from extreme poverty and food insecurity. As more than 70% of the population lives off farming and related activities, agricultural development will have to play a major role in improving this situation. Fortunately, Africa has an abundant supply of natural resources that can support a huge expansion in food, specifically rice production. Because of strong demand, rice area expansion in SSA is larger than for any other crop. Total milled rice production increased from 2.2 million Mg in 1961 to 9.1 million Mg in 2004. Rice imports into SSA also increased from 0.5 million Mg of milled rice in 1961 to 6.0 million Mg in 2003 and SSA currently accounts for 25% of global rice imports, at a cost of more than US$1.5 billion per year. Therefore, many African governments accord high priority to developing their local rice sector as an important component of national food security, economic growth, and poverty alleviation. The abundant supply of agroclimatically suitable wetlands (∼239 million ha) and water resources can support a large expansion in rice area and productivity. Currently, less than 5% of the potentially suitable wetlands are planted with rice because of various constraints. Expansion and intensification of rice cultivation in SSA will not compete with other crops in terms of land and water resources because, during the rainy season, only rice can be grown on low-lying wetlands, including inland valleys. In addition, the labor-intensive nature of rice cultivation will provide additional sources of work and income to the rural poor, especially women. Should labor shortages become acute, however, appropriate mechanization can be considered. Small farmers want to earn money from rice farming, but lack modern inputs and capital to fully exploit their rice lands as these items are limited or not available. This is where an innovative public-private partnership is desirable to support the intensification of rice farming. Rice is cultivated in four ecosystems of SSA: dryland (38% of the cultivated rice area), rainfed wetland (33%), deepwater and mangrove swamps (9%), and irrigated wetland (20%). Many abiotic stresses (drought, flood, and variable rainfall; extreme temperatures; salinity; acidity/alkalinity and poor soils, soil erosion, and high P fixation) and biotic constraints [weeds, blast, Rice yellow mottle virus (RYMV), and African rice gall midge (AfRGM)] limit rice production on the continent. The changing climate is expected to further aggravate the abiotic constraints and reduce rice yields in all ecosystems. Rice production is also restricted by many technical, management, socioeconomic, health, and policy constraints. The constraints to irrigated wetland rice in the Sahel of SSA are similar to those faced by Asian farmers in the 1960s; therefore, well-tested irrigated rice technologies from Asia and elsewhere are being introduced and adapted to local conditions to obtain fast returns on investment. For rice in irrigated wetlands in the humid and moist savanna zones, rainfed wetlands, and drylands, locally developed NERICA (new rice for Africa) varieties and production technologies are being tested in target environments. The progenies of Oryza glaberrima and O. sativa subspecies indica are better adapted to rainfed and irrigated wetlands, while those of O. glaberrima and O. sativa subspecies japonica are more suited to rainfed drylands. In addition, research is ongoing to tackle SSA-specific problems such as RYMV and AfRGM and to develop efficient crop management technologies.… [ABSTRACT FROM AUTHOR]

The unpredictability of drought patterns and the inherent complexity of the physiological responses involved have made it difficult to characterize component traits required for improved performance, thus limiting crop improvement efforts to enhance drought resistance in rice. The various stress-response mechanisms and options to enhance plant survival under severe stress do not usually translate into yield stability under water deficit. Increased crop yield and water productivity require the optimization of the physiological processes involved in the critical stages of plant response to soil drying, water-use efficiency, and dehydrationavoidance mechanisms. New high-throughput phenotyping methodologies have been developed to allow fast and detailed evaluation of potential drought-resistant donors and the large number of lines identified by drought-breeding programs. Similarly, large collections of rice germplasm, including minicore sets, wild relatives, and mutant lines have been screened for drought-resistance traits. Genetic sources of drought resistance have now been identified for all major rice agroecosystems and some of the associated traits have been characterized. The identification and genetic mapping of major QTLs for performance under drought stress across environments are currently a major focus. This approach provides a powerful tool to dissect the genetic basis of drought resistance. If validated with accurate phenotyping and properly integrated in marker-assisted breeding programs, these approaches will accelerate the development of drought-resistant genotypes. This chapter reviews the recent progress and achievements in dissecting drought resistance in rice and presents future perspectives for the genetic enhancement of drought adaptation. [ABSTRACT FROM AUTHOR]

The geographic distribution of wild potatoes (Solanaceae sect. Petota) was analyzed using a database of 6073 georeferenced observations. Wild potatoes occur in 16 countries, but 88% of the observations are from Argentina, Bolivia, Mexico, and Peru. Most species are rare and narrowly endemic: for 77 species the largest distance between two observations of the same species is <100 km. Peru has the highest number of species (93), followed by Bolivia (39). A grid of 50 × 50 km cells and a circular neighborhood with a radius of 50 km to assign points to grid cells was used to map species richness. High species richness occurs in northern Argentina, central Bolivia, central Ecuador, central Mexico, and south and north-central Peru. The highest number of species in a grid cell (22) occurs in southern Peru. To include all species at least once, 59 grid cells need to be selected (out of 1317 cells with observations). Wild potatoes occur between 38° N and 41° S, with more species in the southern hemisphere. Species richness is highest between 8° and 20° S and around 20° N. Wild potatoes typically occur between 2000 and 4000 m altitude.