Adaptive Management of Urban Ecosystem Restoration: Learning From Restoration Managers in Rhode Island,USA

Urban aquatic restoration can be difficult to accomplish because of complications like industrial pollutants, population density, infrastructure, and expense; however, unique opportunities in urban settings, including the potential to provide benefits to many diverse people, can make urban restoration especially rewarding. The success of urban restoration projects—even those focused primarily on ecological targets—depends on community involvement and managers considering community needs. However, research on the social barriers to urban restoration and strategies managers use to overcome them is relatively rare. This work attempts to fill that gap by presenting barriers for aquatic restoration projects in urban settings and strategies to overcome them. Building from interviews with restoration managers involved in urban aquatic restoration projects in Rhode Island, we contribute through an adaptive management approach: identifying and synthesizing the lessons learned from managers’ work in urban settings. Ultimately, we suggest potential for double- and triple-loop learning by disentangling and critiquing the frames and policy/power structures that influence decision making in urban aquatic restoration.     

A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data

Kernel density estimation (KDE) is a classic approach for spatial point pattern analysis. In many applications, KDE with spatially adaptive bandwidths (adaptive KDE) is preferred over KDE with an invariant bandwidth (fixed KDE). However, bandwidths determination for adaptive KDE is extremely computationally intensive, particularly for point pattern analysis tasks of large problem sizes. This computational challenge impedes the application of adaptive KDE to analyze large point data sets, which are common in this big data era. This article presents a graphics processing units (GPUs)-accelerated adaptive KDE algorithm for efficient spatial point pattern analysis on spatial big data. First, optimizations were designed to reduce the algorithmic complexity of the bandwidth determination algorithm for adaptive KDE. The massively parallel computing resources on GPU were then exploited to further speed up the optimized algorithm. Experimental results demonstrated that the proposed optimizations effectively improved the performance by a factor of tens. Compared to the sequential algorithm and an Open Multiprocessing (OpenMP)-based algorithm leveraging multiple central processing unit cores for adaptive KDE, the GPU-enabled algorithm accelerated point pattern analysis tasks by a factor of hundreds and tens, respectively. Additionally, the GPU-accelerated adaptive KDE algorithm scales reasonably well while increasing the size of data sets. Given the significant acceleration brought by the GPU-enabled adaptive KDE algorithm, point pattern analysis with the adaptive KDE approach on large point data sets can be performed efficiently. Point pattern analysis on spatial big data, computationally prohibitive with the sequential algorithm, can be conducted routinely with the GPU-accelerated algorithm. The GPU-accelerated adaptive KDE approach contributes to the geospatial computational toolbox that facilitates geographic knowledge discovery from spatial big data.     

Adaptive and risk-based approaches to climate change and the management of uncertainty and institutional risk: The case of future flooding in England

This paper focuses on how scientific uncertainties about future peak flood flows and sea level rises are accounted for in long term strategic planning processes to adapt inland and coastal flood risk management in England to climate change. Combining key informant interviews (n = 18) with documentary analysis, it explores the institutional tensions between adaptive management approaches emphasising openness to uncertainty and to alternative policy options on the one hand and risk-based ones that close them down by transforming uncertainties into calculable risks whose management can be rationalized through cost-benefit analysis and nationally consistent, risk-based priority setting on the other hand. These alternative approaches to managing uncertainty about the first-order risks to society from future flooding are shaped by institutional concerns with managing the second-order, ‘institutional’ risks of criticism and blame arising from accountability for discharging those first-order risk management responsibilities. In the case of river flooding the poorly understood impacts of future climate change were represented with a simplistic adjustment to peak flow estimates, which proved robust in overcoming institutional resistance to making precautionary allowances for climate change in risk-based flood management, at least in part because its scientific limitations were acknowledged only partially. By contrast in the case of coastal flood risk management, greater scientific confidence led to successively more elaborate guidance on how to represent the science, which in turn led to inconsistency in implementation and increased the institutional risks involved in taking the uncertain effects of future sea level rise into account in adaptation planning and flood risk management. Comparative analysis of these two cases then informs some wider reflections about the tensions between adaptive and risk-based approaches, the role of institutional risk in climate change adaptation, and the importance of such institutional dynamics in shaping the framing uncertainties and policy responses to scientific knowledge about them.     

Panarchy of an indigenous agroecosystem in the globalized market: The quinoa production in the Bolivian Altiplano

Agricultural globalization is blamed for destructive impacts on small farms in developing countries. Yet, many local societies are proactive in the face of these changes and show high adaptive capacity. Investigating their transformations with an integrative perspective and enough hindsight may reveal some of the bases of their resilience and adaptive capacity. Using field data and the panarchy concept of resilience theory, we analyzed the territorial and social dynamics of quinoa growers’ communities in southern Bolivia over the last four decades, a case study of regime shift in a poverty-stricken rural society which deliberately entered the global food market. Linking the dynamics of the household economy to the territorial and social subsystems over several decades, we gained insights into the interactions that shaped the rise of quinoa production in the region. We found that a vivid tradition of mobility allowing for pluriactivity on- and off-farm, combined with community self-governance, explains how local populations succeeded in articulating individual agency with collective control over their commons of land, seed resources, and social rules. Our vulnerability analysis points to landscape homogenization, social inequity, and increased dependence on external factors as potential sources of unsustainability. We conclude that, to cope with the changes of unprecedented magnitude they are facing, local producers should retain social cohesion and autonomous governance, without giving up on their heritage of mobility and economic redundancy. As regards theory, we identified cross-scale subsystem configurations critical for regime shifts, and confirm the value of panarchy in capturing complex socioecological dynamics.     

Integrating biophysical and socio-economic evaluations to improve the efficacy of adaptation assessments for agriculture

This paper demonstrates how biophysical and socio-economic assessments of adaptation options can be integrated to test the effectiveness of options and anticipate social risks and potential barriers to adoption. We present the approach by combining a model analysis with a multiple-criteria evaluation of 12 adaptation options by graziers from the Australian rangelands. Our results show that strategies to manage stocking rates and pasture spelling are likely to be effective in improving climate resilience in the rangelands and are easy-to-implement, short-term solutions. Improving land condition is found to have the greatest potential long-term benefits, but was not considered by the graziers to be feasible or effective due to perceived difficulties of implementation. Areas of concordance identified in the assessments may be used to engage with stakeholders and build a foundation for incorporating climate change considerations into management and policy. The approach also highlights discordant views within the assessments that may result from differing management objectives, adaptive capacity and climate-risk perception. These factors are potential impediments to adaptation. The integrated assessment approach enables adaptation strategies and policy recommendations to be developed that have greater relevance to individual stakeholders, and supports capacity building to facilitate the most effective adaptation actions.     

Application of data assimilation with the Root Zone Water Quality Model for soil moisture profile estimation in the upper Cedar Creek,Indiana

Data assimilation techniques have been proven as an effective tool to improve model forecasts by combining information about observed variables in many areas. This article examines the potential of assimilating surface soil moisture observations into a field‐scale hydrological model, the Root Zone Water Quality Model, to improve soil moisture estimation. The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for nonlinear systems, was applied and compared with a simple direct insertion method. In situ soil moisture data at four different depths (5, 20, 40, and 60 cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were used for assimilation and validation purposes. Through daily update, the EnKF improved soil moisture estimation compared with the direct insertion method and model results without assimilation, having more distinct improvement at the 5 and 20 cm depths than for deeper layers (40 and 60 cm). Local vertical soil property heterogeneity in AS1 deteriorated soil moisture estimates with the EnKF. Removal of systematic bias in the forecast model was found to be critical for more successful soil moisture data assimilation studies. This study also demonstrates that a more frequent update generally contributes in enhancing the open loop simulation; however, large forecasting error can prevent more frequent update from providing better results. In addition, results indicate that various ensemble sizes make little difference in the assimilation results. An ensemble of 100 members produced results that were comparable with results obtained from larger ensembles. Copyright © 2011 John Wiley & Sons, Ltd.     

加拿大乏燃料处置的研发工作

论述了加拿大从1974年至今的乏燃料地质处置的研发工作,并对2002年以后研发工作中的某些问题进行了较详细的介绍：加拿大核废物管理机构、加拿大第4个乏燃料处置方案——可调整的分期管理（APM）方案的产生、APM方案的特点及其实施的技术路线,以及今后5a（2011-2015年）的战略计划。     

Post-equinox observations of Uranus: Berg’s evolution, vertical structure, and track towards the equator

We present observations of Uranus taken with the near-infrared camera NIRC2 on the 10-m W.M. Keck II telescope, the Wide Field Planetary Camera 2 (WFPC2) and the Wide Field Camera 3 (WFC3) on the Hubble Space Telescope (HST) from July 2007 through November 2009. In this paper we focus on a bright southern feature, referred to as the “Berg.” In Sromovsky et al. (Sromovsky, L.A., Fry, P.M., Hammel, H.B., Ahue, A.W., de Pater, I., Rages, K.A., Showalter, M.R., van Dam, M. [2009]. Icarus 203, 265-286), we reported that this feature, which oscillated between latitudes of −32° and −36° for several decades, suddenly started on a northward track in 2005. In this paper we show the complete record of observations of this feature’s track towards the equator, including its demise. After an initially slow linear drift, the feature’s drift rate accelerated at latitudes ∣θ∣ < 25°. By late 2009 the feature, very faint by then, was spotted at a latitude of −5° before disappearing from view. During its northward track, the feature’s morphology changed dramatically, and several small bright unresolved features were occasionally visible poleward of the main “streak.” These small features were sometimes visible at a wavelength of 2.2 μm, indicative that the clouds reached altitudes of ∼0.6 bar. The main part of the Berg, which is generally a long sometimes multipart streak, is estimated to be much deeper in the atmosphere, near 3.5 bars in 2004, but rising to 1.8-2.5 bars in 2007 after it began its northward drift. Through comparisons with Neptune’s Great Dark Spot and simulations of the latter, we discuss why the Berg may be tied to a vortex, an anticyclone deeper in the atmosphere that is visible only through orographic companion clouds.     

Adaptive governance and the human dimensions of marine mammal management: Implications for policy in a changing North

As climate change has driven dramatic changes in Northern sea ice regimes, marine mammals have gained iconic status around the world reflecting the perils of global warming. There is a tension between policies that have international support like a ban on seal hunting or whaling, and the adoption of adaptive, flexible rules that are likely to work in Northern places. Whereas most wildlife policy focuses on biological information to inform policy strategy, this analysis focuses on the “human dimensions” of Northern marine mammal management. This research examines ways in which human relationships and modes of governance affect conservation success. Standard analyses of risk to animal populations focused on direct sources of take are inadequate to address multi-causal, complex problems such as climate-induced habitat loss or increased industrialization of the Arctic Ocean. Early conservation policy strategies focusing on the moratorium of take have eliminated or reduced such practices as commercialized hunting and high levels of fisheries bycatch, but may be less relevant in an era in which habitats and climate changes are key drivers of population dynamics. This paper argues that effective adaptive policy requires new ways of learning about and governing human interactions with marine mammals. Through an exploration of marine mammal management in three Northern regions (Alaska, Nunavut, and the Finnish Baltic Sea coast), the paper analyzes the extent to which these marine mammal management regimes are practicing adaptive governance, that is, building cross-scale (local to international) understanding while allowing actors at the local scale the flexibility to direct the creation of rules that are ecologically robust and likely to succeed. Lessons are taken from these examples and used to propose selected policy and research recommendations for the marine mammal policy community.     

Nash model parameter uncertainty analysis by AM-MCMC based on BFS and probabilistic flood forecasting

A hydrologic model consists of several parameters which are usually calibrated based on observed hydrologic processes. Due to the uncertainty of the hydrologic processes, model parameters are also uncertain, which further leads to the uncertainty of forecast results of a hydrologic model. Working with the Bayesian Forecasting System (BFS), Markov Chain Monte Carlo simulation based Adaptive Metropolis method (AM-MCMC) was used to study parameter uncertainty of Nash model, while the probabilistic flood forecasting was made with the simulated samples of parameters of Nash model. The results of a case study shows that the AM-MCMC based on BFS proposed in this paper is suitable to obtain the posterior distribution of the parameters of Nash model according to the known information of the parameters. The use of Nash model and AM-MCMC based on BFS was able to make the probabilistic flood forecast as well as to find the mean and variance of flood discharge, which may be useful to estimate the risk of flood control decision.