Mesozoic–Cenozoic multistage tectonic evolution of the Pamir: Detrital fission-track constraints from the Tajik Basin

Knowledge of the tectonic history of the Pamir contributes to our understanding of both the evolution of collisional orogenic belts as well as factors controlling Central Asian aridification. It is, however, not easy to decipher the Mesozoic–Cenozoic tectonics of the Pamir due to extensive Neogene deformation in an orogen that remains largely understudied. This study reports detrital apatite and zircon fission-track (FT) ages from both the eastern Tajik Basin sedimentary rocks and Pamir modern river sands. These FT data, supported by vitrinite reflectance and zircon and apatite U–Pb double dating, suggest that the majority of the FT ages are unreset and record exhumation stages of the Pamir, which has served as the source terrane of the Tajik Basin since the Cretaceous. Furthermore, we combine the new data with a compilation of published detrital apatite and zircon FT data from both the Tajik Basin sedimentary rocks and Pamir modern river sands, to explore the Mesozoic–Cenozoic tectonic history of Pamir. Deconvolved FT Peak Ages document two major Mesozoic exhumation events associated with the Late Triassic–Early Jurassic Cimmerian orogeny that reflects accretion of the Pamir terranes, as well as the Early–early Late Cretaceous deformation associated with the northward subduction of the Neo-Tethys Ocean beneath Pamir. The compiled data also show significant Late Eocene–Neogene exhumation associated with the ongoing formation of the Pamir, which peaks at ca. 36, 25, 14 and 7 Ma.     

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results.     

Biomass and carbon storage of Gracilariopsis lemaneiformis （Rhodophyta） in Zhanshan Bay,Qingdao, China

Marine macroalgae can absorb carbon and play an important role in carbon sequestration. As an important economic macroalga, Gracilariopsis lemaneiformis has the potential to significantly affect carbon absorption and storage in wave-sheltered intertidal reef systems. However, detailed knowledge on seasonal biomass changes and carbon storage of G. lemaneiformis is lacking, especially in many small and scattered ecosystems. Considering the influence of human activities on wild distribution of G. lemaneiformis, the understanding of seasonal dynamics of an economically important species in nature is necessary. In this study, we first investigated seasonal variations in biomass, coverage area, and carbon storage during low tide from August 2011 to July 2012 in Zhanshan Bay, Qingdao, China. Furthermore, we estimated the carbon storage potential of wild G. lemaneiformis using light use efficiency(LUE). The results show that the standing biomass and coverage area changed significantly with season. However, seasonal variations in carbon content and water content were not obvious, with an average content of 35.1% and 83.64%, respectively. Moreover, carbon storage in individual months varied between 0.67 and 47.03 g C/m 2, and the value of carbon storage was the highest in August and June and the lowest in February. In Zhanshan Bay, LUE of G. lemaneiformis was only 0.23%. If it is increased to the theoretical maximum(5%–6%), the carbon storage will have an increase of at least 21 times compared with the current, which suggested that carbon storage of wild G. lemaneiformis had a high enhancement potential. The study will help to assess a potential role of G. lemaneiformis in reducing atmospheric CO2.     

地学大数据技术研究实验平台GeoBDA

信息化时代不可避免地来临,随着地质数据的数据量的飞速增长,地质数据也正式归类到了大数据中。应势,国土资源部地质信息技术重点实验室建设了地学大数据技术研究实验平台GeoBDA,用以解决地质大数据的存储和管理等问题。     

Using a spatial overlap approach to estimate the risk of collisions between deep diving seabirds and tidal stream turbines: A review of potential methods and approaches

It is likely that there will be a substantial increase in the number of tidal stream turbines within the UK over the next decade. However, the ecological impacts upon marine top-predators, including seabirds, remain largely unknown. Although tidal stream turbines could have many direct and indirect impacts upon seabird populations, it is the risk of direct collisions between individuals and moving components that currently causes the most concern. Species such as Auks Alcidae sp., Cormorants Phalacrocorax sp. and Divers Gavia sp. almost certainly face higher risks than others. However, it is likely that they are not equally vulnerable. Part of predicting which are most vulnerable involves the estimation of spatial overlap between their foraging distributions and the location of tidal stream turbines. This paper reviews potential methods and approaches that should help to predict whether a population would: (1) exploit areas suitable for tidal stream turbines, (2) dive near tidal stream turbines within these areas, or (3) dive to depths where moving components are found? Answering these questions in a hierarchical manner (from 1 to 3) could help to predict the extent of spatial overlap for vulnerable populations. These approaches require a fundamental understanding of the mechanistic links between physical conditions, prey characteristics and foraging opportunities. Therefore, multi-disciplinary approaches incorporating methods usually associated with oceanographic and fisheries studies are needed to document physical conditions and prey characteristics over large and small spatial scales. Answering these questions also requires collaborative efforts and a strategic governance approach to collating the wide range of distributional, prey and physical datasets currently being collected.     

Setting conservation priorities in Fiji: Decision science versus additive scoring systems

There is a well-established scientific field – decision science – that can be used to rigorously set conservation priorities. Despite well-documented shortcomings, additive scoring approaches to conservation prioritization are still prevalent. This paper discusses the shortcomings and advantages of both approaches applied in Fiji to identify priorities for terrestrial protected areas. The two main shortcomings of using a scoring approach (discussed in Keppel (2014) [1]) that are resolved with decision science approaches (presented in Klein et al. (2014) [2]) in Fiji were (1) priorities did not achieve one of the most important stated conservation goals of representing ~40% of Fiji׳s major vegetation types and (2) the weighting of different selection criteria used was arbitrary. Both approaches considered expert knowledge and land–sea connections important to decision makers in Fiji, but only decision science can logically integrate both, in addition to other important considerations. Thus, decision makers are urged to use decision science and avoid additive scoring systems when prioritizing places for conservation. Fiji has the opportunity to be a global leader in using decision science to support integrated land–sea planning decisions.     

Planning for offshore CO2 storage: Law and policy in the United Kingdom

‘Offshore CO₂ storage’ refers to the injection of liquefied CO₂ into deep geological formations beneath the seabed (e.g. depleted oil and gas reservoirs, and saline aquifers) for the purpose of storing it there on a permanent basis. The storage in this manner of captured CO₂ emissions from industrial installations and power plants has attracted considerable scientific and technical interest as a potential mitigation response to climate change. A key issue facing policymakers in several countries is how to reconcile policy commitments to develop offshore CO₂ storage with other competing – and potentially conflicting – uses of the marine environment. With a view to informing policy responses to this issue, this paper presents a case study of legal and policy frameworks concerning offshore CO₂ storage in United Kingdom. The paper maps key design features of the United Kingdom׳s framework for marine permitting and planning, appraising the extent to which they enable orderly development of offshore CO₂ storage in a manner consistent with relevant high-level policy objectives.     

International trade buffers the impact of future irrigation shortfalls

There is increasing interest in the water–food nexus, especially the restrictive effect of water on food production in hot spots where irrigation stress is growing. However, little is known about the larger-scale implications of future irrigation shortfalls for global trade and economic welfare, as well as of the potential buffering impacts of international trade on the local impacts of irrigation shortage. In this paper, we utilize a recently developed model, GTAP-BIO-W, to study the economic effects of changes in irrigation outlook for 126 river basins, globally by 2030. Projected irrigation availability is obtained from the IMPACT-WATER model, and imposed upon the present-day economy. Irrigation availability in 2030 is expected to drop by 30–60% in several key rivers basins, including: Hai He, Indus, Luni, and the Eastern Mediterranean basin, leading to significant output declines in China, South Asia, and the Middle East. We find that the regional production impacts of future irrigation water shortages are quite heterogeneous, depending on the size of the shortfall, the irrigation intensity of crop production, the possibility of expanding rainfed areas, as well as the crop mix. These changes in regional output significantly alter the geography of international trade. To compensate for the loss of productivity caused by the irrigation constraint, an estimated 7.6 million hectares of cropland expansion is needed to meet the demand for food. In spite of the remarkable reduction of irrigation in some basins, the resulting welfare impact is relatively modest as a result of the buffering capacity of global markets. The global welfare loss amounts to $3.7 billion (2001 prices) and results from a combination of the reduction in irrigation availability as well as the interplay with agricultural support policies.     

商河县耕层土壤有机碳密度及储量研究

采用商河县2010年耕地地力评价有机质采样点的数据,运用GIS和地统计学相结合的方法,研究了商河县土壤有机质的密度及储量,并按照土类统计分析了不同土壤类型间的有机碳密度及储量差异。研究表明,商河县土壤有机碳密度范围为1.69~5.17kg/m2,平均3.44kg/m2;有机碳储量为0.26×1010kg。按乡镇统计,有机碳密度最大值为玉皇庙镇3.65kg/m2,最小值为郑陆镇3.15kg/m2,有机碳储量最大值玉皇庙镇3.47×108 kg,最小值张坊乡0.92×108 kg;按土壤类型统计,有机碳密度最大的为湿潮土3.46kg/m2,最小为风沙土3.29kg/m2,有机碳储量最大为潮土10.38×108 kg,最小为褐土化潮土1.34×108 kg。     

Research Approaches for Understanding,Enhancing, and Monitoring Community Resilience

The growing interest in the understanding of community resilience suggests a need for improving research approaches. This article reviews methods used to date, and suggests opportunities for expanding the range and efficacy of approaches used to understand, improve, and monitor the coupled social and ecological aspects of community resilience. We explore three potential foci: research approaches that enhance understanding of community resilience; those that help to improve community resilience through the research process; and the further development of methods to guide monitoring. Most studies have relied on mixed and multistaged methods, including in-depth interviews and case studies. We comment on the wide range of approaches used, and suggest others that could be valuable. There is particular scope for greater use of cumulative studies, historical or retrospective studies, participatory methods, and systems approaches, and a need for more methods that explore the coupling of social and ecological dimensions.