Colonization history of the Swiss Rhine basin by the bullhead (Cottus gobio): inference under a Bayesian spatially explicit framework

The present distribution of freshwater fish in the Alpine region has been strongly affected by colonization events occurring after the last glacial maximum (LGM), some 20,000 years ago. We use here a spatially explicit simulation framework to model and better understand their colonization dynamics in the Swiss Rhine basin. This approach is applied to the European bullhead (Cottus gobio), which is an ideal model organism to study fish past demographic processes since it has not been managed by humans. The molecular diversity of eight sampled populations is simulated and compared to observed data at six microsatellite loci under an approximate Bayesian computation framework to estimate the parameters of the colonization process. Our demographic estimates fit well with current knowledge about the biology of this species, but they suggest that the Swiss Rhine basin was colonized very recently, after the Younger Dryas some 6600 years ago. We discuss the implication of this result, as well as the strengths and limits of the spatially explicit approach coupled to the approximate Bayesian computation framework.

A Method for Detecting Population Genetic Structure in Diverse, High Gene-Flow Species

Detecting small amounts of genetic subdivision across geographic space remains a persistent challenge. Often a failure to detect genetic structure is mistaken for evidence of panmixia, when more powerful statistical tests may uncover evidence for subtle geographic differentiation. Such slight subdivision can be demographically and evolutionarily important as well as being critical for management decisions. We introduce here a method, called spatial analysis of shared alleles (SAShA), that detects geographically restricted alleles by comparing the spatial arrangement of allelic co-occurrences with the expectation under panmixia. The approach is allele-based and spatially explicit, eliminating the loss of statistical power that can occur with user-defined populations and statistical averaging within populations. Using simulated data sets generated under a stepping-stone model of gene flow, we show that this method outperforms spatial autocorrelation (SA) and UST under common real-world conditions: at relatively high migration rates when diversity is moderate or high, especially when sampling is poor. We then use this method to show clear differences in the genetic patterns of 2 nearshore Pacific mollusks, Tegula funebralis (5 Chlorostoma funebralis) and Katharina tunicata, whose overall patterns of within-species differentiation are similar according to traditional population genetics analyses. SAShA meaningfully complements UST/FST, SA, and other existing geographic genetic analyses and is especially appropriate for evaluating species with high gene flow and subtle genetic differentiation.

Geographic information system-based decision support for soil conservation planning in Tajikistan

Soil erosion on sloping agricultural land poses a serious problem for the environment, as well as for production. In areas with highly erodible soils, such as those in loess zones, application of soil and water conservation measures is crucial to sustain agricultural yields and to prevent or reduce land degradation. The present study, carried out in Faizabad, Tajikistan, was designed to evaluate the potential of local conservation measures on cropland using a spatial modelling approach to provide decision-making support for the planning of spatially explicit sustainable land use. A sampling design to support comparative analysis between well-conserved units and other field units was established in order to estimate factors that determine water erosion, according to the Revised Universal Soil Loss Equation (RUSLE). Such factor-based approaches allow ready application using a geographic information system (GIS) and facilitate straightforward scenario modelling in areas with limited data resources. The study showed first that assessment of erosion and conservation in an area with inhomogeneous vegetation cover requires the integration of plot-based cover. Plot-based vegetation cover can be effectively derived from high-resolution satellite imagery, providing a useful basis for plot-wise conservation planning. Furthermore, thorough field assessments showed that 25.7% of current total cropland is covered by conservation measures (terracing, agroforestry and perennial herbaceous fodder). Assessment of the effectiveness of these local measures, combined with the RUSLE calculations, revealed that current average soil loss could be reduced through low-cost measures such as contouring (by 11%), fodder plants (by 16%), and drainage ditches (by 53%). More expensive measures such as terracing and agroforestry can reduce erosion by as much as 63% (for agroforestry) and 93% (for agroforestry combined with terracing). Indeed, scenario runs for different levels of tolerable erosion rates showed that more cost-intensive and technologically advanced measures would lead to greater reduction of soil loss. However, given economic conditions in Tajikistan, it seems advisable to support the spread of low-cost and labourextensive measures.

Potential drought stress in a Swiss mountain catchment-Ensemble forecasting of high mountain soil moisture reveals a drastic decrease, despite major uncertainties

Climate change is expected to profoundly influence the hydrosphere of mountain ecosystems. The focus of current process-based research is centered on the reaction of glaciers and runoff to climate change; spatially explicit impacts on soil moisture remain widely neglected. We spatio-temporally analyzed the impact of the climate on soil moisture in a mesoscale high mountain catchment to facilitate the development of mitigation and adaptation strategies at the level of vegetation patterns. Two regional climate models were downscaled using three different approaches (statistical downscaling, delta change, and direct use) to drive a hydrological model (WaSiM-ETH) for reference and scenario period (1960–1990 and 2070–2100), resulting in an ensemble forecast of six members. For all ensembles members we found large changes in temperature, resulting in decreasing snow and ice storage and earlier runoff, but only small changes in evapotranspiration. The occurrence of downscaled dry spells was found to fluctuate greatly, causing soil moisture depletion and drought stress potential to show high variability in both space and time. In general, the choice of the downscaling approach had a stronger influence on the results than the applied regional climate model. All of the results indicate that summer soil moisture decreases, which leads to more frequent declines below a critical soil moisture level and an advanced evapotranspiration deficit. Forests up to an elevation of 1800 m a.s.l. are likely to be threatened the most, while alpine areas and most pastures remain nearly unaffected. Nevertheless, the ensemble variability was found to be extremely high and should be interpreted as a bandwidth of possible future drought stress situations.

Dynamics of Shifting Cultivation Landscapes in Northern Lao PDR Between 2000 and 2009 Based on an Analysis of MODIS Time Series and Landsat Images

The rotational nature of shifting cultivation poses several challenges to its detection by remote sensing. Consequently, there is a lack of spatial data on the dynamics of shifting cultivation landscapes on a regional, i.e. sub-national, or national level. We present an approach based on a time series of Landsat and MODIS data and landscape metrics to delineate the dynamics of shifting cultivation landscapes. Our results reveal that shifting cultivation is a land use system still widely and dynamically utilized in northern Laos. While there is an overall reduction in the areas dominated by shifting cultivation, some regions also show an expansion. A review of relevant reports and articles indicates that policies tend to lead to a reduction while market forces can result in both expansion and reduction. For a better understanding of the different factors affecting shifting cultivation landscapes in Laos, further research should focus on spatially explicit analyses.

The Importance of Place Names in the Search for Ecosystem-Like Concepts in Indigenous Societies: An Example from the Bolivian Andes

This paper aims to deepen the search for ecosystem-like concepts in indigenous societies by highlighting the importance of place names used by Quechua indigenous farmers from the central Bolivian Andes. Villagers from two communities in the Tunari Mountain Range were asked to list, describe, map and categorize the places they knew on their community’s territory. Results show that place names capture spatially explicit units which integrate biotic and abiotic nature and humans, and that there is an emphasis on topographic terms, highlighting the importance of geodiversity. Farmers’ perspectives differ from the classical view of ecosystems because they ‘humanize’ places, considering them as living beings with agency. Consequently, they do not make a distinction between natural and cultural heritage. Their perspective of the environment is that of a personalized, dynamic relationship with the elements of the natural world that are perceived as living entities. A practical implication of the findings for sustainable development is that since places names make the links between people and the elements of the landscape, toponymy is a tool for ecosystem management rooted in indigenous knowledge. Because place names refer to holistic units linked with people’s experience and spatially explicit, they can be used as an entry point to implement an intercultural dialogue for more sustainable land management.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction

Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes ire fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories. Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of air asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction. Important findings For entirely vegetative or sexual reproduction, predictions. of the gametic SEIB model were close to the ones of spatially explicit CSMs gametic phenotypic models, hut for mixed modes of reproduction they appoximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of trails governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually, miss the optimum and that selection may lead to loci with smaller effects, in derived compared with ancestral lines.

Water quality and health in a Sahelian semi-arid urban context: an integrated geographical approach in Nouakchott, Mauritania

Access to sufficient quantities of safe drinking water is a human right. Moreover, access to clean water is of public health relevance, particularly in semi-arid and Sahelian cities due to the risks of water contamination and transmission of water-borne diseases. We conducted a study in Nouakchott, the capital of Mauritania, to deepen the understanding of diarrhoeal incidence in space and time. We used an integrated geographical approach, combining socio-environmental, microbiological and epidemiological data from various sources, including spatially explicit surveys, laboratory analysis of water samples and reported diarrhoeal episodes. A geospatial technique was applied to determine the environmental and microbiological risk factors that govern diarrhoeal transmission. Statistical and cartographic analyses revealed concentration of unimproved sources of drinking water in the most densely populated areas of the city, coupled with a daily water allocation below the recommended standard of 20 l per person. Bacteriological analysis indicated that 93% of the non-piped water sources supplied at water points were contaminated with 10-80 coliform bacteria per 100 ml. Diarrhoea was the second most important disease reported at health centres, accounting for 12.8% of health care service consultations on average. Diarrhoeal episodes were concentrated in municipalities with the largest number of contaminated water sources. Environmental factors (e.g. lack of improved water sources) and bacteriological aspects (e.g. water contamination with coliform bacteria) are the main drivers explaining the spatio-temporal distribution of diarrhoea. We conclude that integrating environmental, microbiological and epidemiological variables with statistical regression models facilitates risk profiling of diarrhoeal diseases. Modes of water supply and water contamination were the main drivers of diarrhoea in this semi-arid urban context of Nouakchott, and hence require a strategy to improve water quality at the various levels of the supply chain.