Using diatom indices for water quality assessment in a subtropical river, China

Diatoms have been regularly used as bioindicators to assess water quality of surface waters. However, diatom-based indices developed for a specific geographic region may not be appropriate elsewhere. We sampled benthic diatom assemblages in the upper Han River, a subtropical river in China, to evaluate applicability of 14 diatom-based indices used worldwide for water quality assessment. A total of 194 taxa from 31 genera were identified in the dry season and 139 taxa from 23 genera in the wet season. During the dry season, significant relationships were found for all but one of the diatom-based indices (Index Diatom Artois–Picardie) with one or more physical and chemical variables including nutrients and ion concentrations in river waters. The Biological Diatom Index (IBD) and diatom-based eutrophication/pollution index (EPI-D) were strongly related to trophic status and ionic content, while Watanabe’s Index was related to organic pollution and conductivity. Yet, the diatom indices showed weak relationships with physical and chemical variables during the wet season. It suggests that diatom-based indices developed in Europe can be applied with confidence as bioindicators of water quality in subtropical rivers of China, at least during base-flow conditions.     

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L⁻¹), medium dose (amended at 100 μg U L⁻¹), and high dose (500 μg U L⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.     

The challenge of providing environmental flow rules to sustain river ecosystems.

Accounting for natural differences in flow variability among rivers, and understanding the importance of this for the protection of freshwater biodiversity and maintenance of goods and services that rivers provide, is a great challenge for water managers and scientists. Nevertheless, despite considerable progress in understanding how flow variability sustains river ecosystems, there is a growing temptation to ignore natural system complexity in favor of simplistic, static, environmental flow "rules" to resolve pressing river management issues. We argue that such approaches are misguided and will ultimately contribute to further degradation of river ecosystems. In the absence of detailed empirical information of environmental flow requirements for rivers, we propose a generic approach that incorporates essential aspects of natural flow variability shared across particular classes of rivers that can be validated with empirical biological data and other information in a calibration process. We argue that this approach can bridge the gap between simple hydrological "rules of thumb" and more comprehensive environmental flow assessments and experimental flow restoration projects.     

The natives are restless, but not often and mostly when disturbed

The argument that the threat posed by introduced species is overblown is often buttressed by the observation that native species sometimes also become invasive. An examination of the literature on plant invasions in the United States shows that six times more nonnative species have been termed invasive than native species, and that a member of the naturalized nonnative pool is 40 times more likely than a native species to be perceived as invasive. In the great majority of instances in which a native plant species is seen as invasive, the invasion is associated with an anthropogenic disturbance, especially changed fire or hydrological regime, livestock grazing, and changes wrought by an introduced species. These results suggest that natives are significantly less likely than nonnatives to be problematic for local ecosystems.     

Implications of a changing climate on food security and smallholders’ livelihoods in Bogotá, Colombia

Small farmers who supply the city of Bogotá with food are facing many challenges that are jeopardizing their livelihoods and by extension, the food security of Colombia’s capital. We expect future changes in climatic conditions to exacerbate the plight of the small farmers and this is expected to compromise Bogota’s food security even further. This paper specifically seeks to assess the impact of climate change (CC) on the livelihoods of smallholders who supply Bogota with most of its food. In our multidisciplinary methodology, we translated the exposure to CC into direct impact on crops and assessed sensitivity and adaptive capacity using the sustainable rural livelihoods framework. The results show that rainfall (by average of 100 mm) and temperature (by average of 2.1 °C) will increase over the study area, while the future climate suitability of the most important crops such as mango (Mangifera indica), papaya (Carica papaya), corn (Zea mays) and plantain (Musa balbisiana) shows a decrease of 19 % to 47 % climate suitability by the year 2050. The assessment of sensitivity and adaptive capacity demonstrates that farmers participating in a farmers’ market, initiated by several local and international non-governmental organizations (NGOs), are less vulnerable to CC than farmers who sell through intermediaries. Those farmers selling directly to consumers in the farmers’ market have a higher adaptive capacity (3 on a scale of 3) in social and financial capital than those selling to intermediaries with less adaptive capacity (1 on a scale of 3). In light of the reduction in overall climatic suitability of some of the major crops and the change of geographic location of suitability for others, there are likely to be serious threats for Bogotá’s food security, the ecological landscape around the city, and farmers’ livelihoods. We further conclude that unless proper adaptation measures are implemented, the geographical shift in climate suitability may also force farmers to shift their crops to higher elevations including remaining forests and páramos (the Colombian alpine tundra ecosystems), which may be threatened in the near future.     

发展中国家的可持续建筑服务:寻找“最适合“技术的挑战

发展中国家的能源效率智能技术可以根据最适合标准进行评(居住者的有效控制、运行中的最少冲空、内在能源效率以及易于建造、维护和运行).本文提出表面上具有能源效率的方案不会产生预期效果,除非它们适合气候,得到正确的详细解释、定位和使用,并且建筑的管理者和用户能够理解其复杂性.相应的低能耗技术包括灰水理循环系统、被动和主动热蓄热器以及地热泵.广泛、成功地出口这类技将取决于发达国家在本国树立榜样.要让低能耗建筑设计获得持久动力,牌经济分界线两边的商业客户和政府需要宣传对已经证实的--而不是理论上的+能源效率的承诺和建筑.     

From site-level to regional adaptation planning for tropical commodities: cocoa in West Africa

The production of tropical agricultural commodities, such as cocoa (Theobroma cacao) and coffee (Coffea spp.), the countries and communities engaged in it, and the industries dependent on these commodities, are vulnerable to climate change. This is especially so where a large percentage of the global supply is grown in a single geographical region. Fortunately, there is often considerable spatial heterogeneity in the vulnerability to climate change within affected regions, implying that local production losses could be compensated through intensification and expansion of production elsewhere. However, this requires that site-level actions are integrated into a regional approach to climate change adaptation. We discuss here such a regional approach for cocoa in West Africa, where 70 % of global cocoa supply originates. On the basis of a statistical model of relative climatic suitability calibrated on West African cocoa farming areas and average climate projections for the 2030s and 2050s of, respectively, 15 and 19 Global Circulation Models, we divide the region into three adaptation zones: (i) a little affected zone permitting intensification and/or expansion of cocoa farming; (ii) a moderately affected zone requiring diversification and agronomic adjustments of farming practices; and (iii) a severely affected zone with need for progressive crop change. We argue that for tropical agricultural commodities, larger-scale adaptation planning that attempts to balance production trends across countries and regions could help reduce negative impacts of climate change on regional economies and global commodity supplies, despite the institutional challenges that this integration may pose.