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Abstract Past water resource developments in dryland regions rarely estimated the full suite of environmental and social impacts arising from damming and diverting water for food production. Nowadays there is a greater focus on sustainable resource development which considers the economic, social and environmental costs and benefits. A challenge is to apply tools and methods which can capture the often disparate knowledge and data describing many costs and benefits. This paper describes a proof of concept application of a large Bayesian Decision Net to estimate the total utility of water resource development according to criteria of social, economic and environmental sustainability. We focus on two water-scarce catchments in remote northern Australia which are under investigation for development. The study catchments contain a diverse set of ecosystem services and socio-cultural values, including important Indigenous values and high value freshwater ecosystems. The Bayesian Decision Net was shown to have many properties that made it useful for performing a social, economic and environmental sustainability assessment, in particular its ease of construction; its ability to handle quantitative and qualitative data types; its preservation of system knowledge and; its ease of use in aiding decision making. From the perspective of the sustainability assessment in our case study, the total utility of water resource development for new irrigation is negative in both the studied catchments. The overall utility of water resource development could be positive if irrigation development is highly sensitive to the environment and there are very low environmental impacts, and much higher net economic returns to irrigators eventuate, possibly through higher commodity prices, lower capital costs of irrigation development or some combination of both. Highlights • Development of water resources involves trade-offs between economy and environment. • Integrated social-environment-economy sustainability (SEES) assessments support trade-offs analyses. • Bayesian Decision Networks (BDNs) support SEES assessments with diverse data types. • BDN applied to irrigation development scenarios of two remote catchments in north Australia. • The economic and ecosystem service benefits of the case study irrigation developments are questionable. [ABSTRACT FROM AUTHOR]

Abstract: In many parts of the world the boundaries between grassland and shrubland biomes have changed substantially over the course of the last century. Many are projected to shift further from being grass-dominated to shrub-dominated by 2050 under global climate change and land use change projections. This paper used long-term surveys and repeat photography to assess vegetation change at the shrubland-grassland ecotone in semi-arid, South Africa. Changes in several climate variables as well as in the cover of grasses and dwarf shrubs over three time periods (1962, 1989 and 2009) were investigated at eight localities within a broad 500 km ecotone between the Grassland and Nama-karoo biomes. Results showed that for most sites grass cover has increased and that dwarf shrub cover has decreased over time. This contradicts earlier views which warned against the expansion of dwarf shrublands in response to over-grazing as well as more recent views which suggest that more mesic biomes in the Karoo Midlands will contract in response to climate-induced aridification. The decline in stocking densities and more conservation-friendly land management practices together with an increase in large wet events in the Nama-karoo biome may have contributed to the increase in grass cover. [Copyright &y& Elsevier]

Abstract: Degradation in arid rangelands is an on-going concern, as they appear to be trapped in a vicious circle of desertification–marginalization–impoverishment. Recent theoretical developments in dryland research strive to provide keys to understanding linked social-ecological systems and land management. One approach, the desert-syndrome, depicts the socio-ecological evolution of drylands as being determined mainly by ecological factors. A second approach, the adaptive management paradigm, acknowledges the existence of socio-ecological systems in drylands which are considered to have adapted to a given political–economic context and a given range of economic and ecological variability. This paper proposes a conceptual framework integrating both approaches in order to point out supplementary important drivers of the socio-ecological evolution of drylands systems, especially rangelands at the global economic and political scale. The analysis is broadly conducted from a political ecology and co-evolutionary perspectives and discusses three main factors: (1) world-wide application of western-based paradigms in resource management and their effect on rangelands, (2) the fossil-fuel based Green Revolution, and (3) capitalist institutions used to regulate agricultural trade and the corresponding tools and policies. The marginalization of arid rangelands is avoidable, but requires real changes in the current general political and economic rationale under which resources are allocated. [Copyright &y& Elsevier]

Abstract: Science is frequently touted as the solution to dryland management problems, yet most management decisions are, by necessity, based primarily on expert knowledge and experience. This paper describes an integrated framework for organizing, synthesizing, and applying our growing understanding of aridland ecosystems using a flexible, multi-objective assessment, monitoring, and management approach. The framework is dual-purpose: (1) to coordinate the use of existing tools, resources, and diffuse knowledge, and (2) to facilitate the integration and application of new knowledge as it is developed. In particular, this framework must facilitate the integration of new knowledge about linkages among landscape units across scales. The framework includes five elements: (1) an ecological site-based approach for categorizing land based on soils and climate, (2) a repository for organizing existing data and knowledge about each ecological site, (3) conceptual models that organize information on the impacts of management and climate variability, and protocols for (4) assessing and (5) monitoring key ecosystem attributes fundamental to a variety of management objectives. Within this framework, basic and applied research are explicitly linked to management of arid and semi-arid ecosystems to more effectively articulate research questions and set research priorities. [Copyright &y& Elsevier]

In arid and semi-arid regions, unregulated land use changes as a result of poor planning, and the expansion of agricultural and livestock activities increase the risk of desertification and other potentially severe environmental impacts. Several consequences of improper land management practices are soil deterioration and erosion, which may be intensified by meteorological events. This paper presents a historical evaluation of the temporal and spatial evolution of soil deterioration in the southern Chihuahuan Desert in Mexico. A multi-temporal analysis of the study area during the 1995–2016 period was carried out using satellite data (Landsat series). Two seasons were analyzed to determine the influence of external events such as rainfall and wind: dry and rainy. The identification of soil conditions was based on the Brightness Index (BI) considering the complete satellite data set. The soil conditions were classified into five categories according to their reflectance values: highly deteriorated, deteriorated, in the process of being deteriorated, in good condition and other (clouds, water, non-soil). The change detection maps clearly show a growing trend wherein areas of deteriorated and eroded soil increase over time. Agriculture and strong winds are the two main factors involved in the soil deterioration process of the study region. • Deficient agricultural practices and strong winds precursors to desertification. • Spatial-temporal identification of deteriorated soil in arid/semi-arid zones. • Spectral analysis based method for categorization of soil conditions. • Comparative analysis of sensitivity in rainy and dry seasons. [ABSTRACT FROM AUTHOR]