Adaptive environmental governance of changing social-ecological systems: Empirical insights from the Okavango Delta,Botswana

Adaptive management and related fields have theorized new governance strategies that embrace complexity and are able to respond effectively to changing and unpredictable biophysical dynamics. However, this body of work pays inadequate attention to important on-the-ground realities, including feasibility of implementation and the power dynamics embedded in multi-scalar systems of environmental governance. This paper presents findings from a research project on challenges to adaptive management in the variable wetland ecosystem of the Okavango Delta, Botswana. Many residents of this rural region rely on transitional agricultural practices, shifting between dryland and floodplain farming in response to dynamic precipitation and flooding patterns. Higher than average floods in 2009–2011 inundated many floodplain fields past the point of production, causing farmers to shift to the dryland for multiplem seasons. At the same time, the highly centralized Government of Botswana began to implement stricter regulations over floodplain resources, which stemmed in part from a new adaptive management plan developed for the region. As a result, many farmers felt pressured by the government to abandon transitional livelihood practices and to shift permanently to dryland agriculture even though many preferred to continue floodplain farming. This loss of a responsive livelihood strategy will likely result in decreased long-term adaptive capacity for many residents. Drawing on these findings, this paper advances the argument that if adaptive management is to become a viable option for communities in changing environments, more attention must be given to the role of unequal power relations in multi-scalar systems of environmental governance.     

Agricultural adaptation to drought in the Sri Lankan dry zone

Droughts affect more people than any other natural disaster. Drought severity is not merely a function of precipitation; it emerges from a web of interrelations between human and natural systems. The impacts of drought are equally complex, shifting across temporal scales, economic sectors, and regions. Even in regions with similar hydroclimatic characteristics, there is tremendous variation in the effects of drought. This study combines satellite imagery, geospatial data, and qualitative data to identify the multi-scalar factors that drive variations in agricultural responses to drought. We analyzed eleven years of remotely sensed imagery to identify agricultural areas in which cultivation occurred during an extreme drought in Sri Lanka. We visited a subset of these communities and conducted interviews with officials and farmers to identify the factors that influenced agricultural adaptation. Results suggest that though structural factors such as infrastructural capacity and physical environment significantly affect agricultural adaptation, dynamic factors such as local control of water supply, perceived risk, community cohesion, and farmer experience explain significant variation in the adaptive capacity of agricultural systems.     

Adapting water management to climate change: Institutional involvement,inter-institutional networks and barriers in India

The capacity of a nation to address the hydrological impacts of climate change depends on the institutions through which water is governed. Inter-institutional networks that enable institutions to adapt and the factors that hinder smooth coordination are poorly understood. Using water governance in India as an example of a complex top-down bureaucratic system that requires effective networks between all key institutions, this research unravels the barriers to adaptation by combining quantitative internet data mining and qualitative analysis of interviews with representatives from twenty-six key institutions operating at the national level.Institutions' online presence shows a disconnect in the institutional discourse between climate change and water with institutions such as the Ministries of Water Resources, Earth Sciences and Agriculture, indicating a lesser involvement compared to institutions such as the Ministries of Finance, External Affairs, Planning Commission. The online documents also indicate a more centralised inter-institutional network, emanating from or pointing to a few key institutions including the Planning Commission and Ministry of Environment and Forests. However, the interviews suggest more complex relational dynamics between institutions and also demonstrate a gap between the aspirational ideals of the National Water Mission under the National Action Plan on Climate Change and the realities of climate change adaptation. This arises from institutional barriers, including lengthy bureaucratic processes and systemic failures, that hinder effective inter-institutional networks to facilitate adaptation. The study provides new understanding of the involvement and barriers of complex multi-layered institutions in climate change adaptation.     

Harnessing scientific and local knowledge to face climate change in small-scale fisheries

Small-scale fisheries in developing regions are particularly vulnerable to climate change, but the assessment of climate-induced changes and impacts are often hampered by the data poor-situation of these social-ecological systems. Based on 40 years of scientific and local ecological knowledge, we provide a coherent narrative about the effects of a marine hotspot of climate change on a small-scale fishery across different geographical and temporal scales. We applied a mixed-methods approach to assess biophysical changes, social-ecological impacts, and the incremental spectrum of actions implemented at multiple levels to increase the adaptive capacity of a small-scale clam fishery. The warming hotspot here analyzed was the fastest-warming region in the South Atlantic Ocean. Long-term changes in wind intensity and direction were also noticeable at a regional scale. Both sea surface temperature and winds showed a clear shifting pattern in the late 1990 s. These climate-related stressors determined ecosystem and targeted population changes (e.g. clam mass mortalities, slow stock recovery rates after ecological shocks, habitat narrowing), and favored harmful algal bloom-forming organisms. Climate-induced drivers also affected the human component of the social-ecological system, preventing fishers from securing a fulltime livelihood and limiting the fishery economic potential. Adaptive responses at multiple levels provided some capacity to address climate change effects, and transformative pathways are being taken to adapt to climate-induced changes over the long-term. Transformative changes were fostered by the local perception of environmental change, shared narratives, sustained scientific monitoring programs, and the interaction between knowledge systems, facilitated by a bridging organization within a broader process of governance transformation. The combination of autonomous adaptations (based on linking social capital and fishery leaders agency) and government-led adaptations were essential to face the challenges imposed by climate change. Our results serve as a learning platform to anticipate threats and envision solutions to a wide range of small-scale fisheries in fast-warming regions worldwide.     

In two waters: contemporary evolution of lagoonal and marine white seabream (Diplodus sargus) populations

Brackish water ecosystems are often exposed to wide variations in environmental variables, including temperature and salinity, which may cause strong selective pressures on organisms modifying the genetic patterns of species. The aim of this work was to test whether there is a ‘divergence-with-gene flow’ in coastal lagoon populations of white seabream (Diplodus sargus) (Ria Formosa, S Portugal and Mar Menor, SE Spain) respect to four marine populations, by using partial sequences of cyt b mitochondrial gene and information from nine microsatellite loci. Genetic diversity was highest in both coastal lagoons (Mar Menor and Ria Formosa) considering mitochondrial and nuclear markers. Although some of F_ST population pairwise comparisons were not significant, analyses of molecular variance (AMOVAs) detected differences between groups (coastal lagoon and marine) close to significance. Also, only two haplotypes (Cytb-17 and Cytb-18) were detected in both coastal lagoon sampling sites and these localities (Mar Menor and Ria Formosa) showed the highest number of singletons, some of them with a high number of mutations, as has been already described for other Mar Menor populations (Pomatochistus marmoratus and Holothuria polii). Also, several tests detected significant positive and balancing selection considering mtDNA and microsatellite data. These data support the hypothesis of selection as one of the drivers of the genetic differences found between coastal lagoon and marine populations. The life strategy adopted by Diplodus sargus in coastal lagoons allows it to decrease its mortality rate and improve the heritability of its genes. Also, the increase time spent in coastal lagoons with different temperatures and salinities favours the fitness selection and the maintenance of exclusive haplotypes and genotypes in coastal lagoon inhabitants favouring the ‘divergence-with-gene-flow’.     

Social cohesion and passive adaptation in relation to climate change and disease

Climate change affects biophysical processes related to the transmission of many infectious diseases, with potentially adverse consequences for the health of communities. While our knowledge of biophysical associations between meteorological factors and disease is steadily improving, our understanding of the social processes that shape adaptation to environmental perturbations lags behind. Using computational modeling methods, we explore the ways in which social cohesion can affect adaptation of disease prevention strategies when communities are exposed to different environmental scenarios that influence transmission pathways for diseases such as diarrhea. We developed an agent-based model in which household agents can choose between two behavioral strategies that offer different levels of protection against environmentally mediated disease transmission. One behavioral strategy is initially set as more protective, leading households to adopt it widely, but its efficacy is sensitive to variable weather conditions and stressors such as floods or droughts that modify the disease transmission system. The efficacy of the second strategy is initially moderate relative to the first and is insensitive to environmental changes. We examined how social cohesion (defined as average number of household social network connections) influences health outcomes when households attempt to identify an optimal strategy by copying the behaviors of socially connected neighbors who seem to have adapted successfully in the past. Our simulation experiments suggest that high-cohesion communities are able to rapidly disseminate the initially optimal behavioral strategy compared to low-cohesion communities. This rapid and pervasive change, however, decreases behavioral diversity; i.e., once a high cohesion community settles on a strategy, most or all households adopt that behavior. Following environmental changes that reduce the efficacy of the initially optimal strategy, rendering it suboptimal relative to the alternative strategy, high-cohesion communities can fail to adapt. As a result, despite faring better early in the course of computational experiments, high-cohesion communities may ultimately experience worse outcomes. In the face of uncertainty in predicting future environmental stressors due to climate change, strategies to improve effective adaptation to optimal disease prevention strategies should balance between intervention efforts that promote protective behaviors based on current scientific understanding and the need to guard against the crystallization of inflexible norms. Developing generalizable models allows us to integrate a wide range of theories and multiple datasets pertaining to the relationship between social mechanisms and adaptation, which can provide further understanding of future climate change impacts. Models such as the one we present can generate hypotheses about the mechanisms that underlie the dynamics of adaptation events and suggest specific points of measurement to assess the impact of these mechanisms. They can be incorporated as modules within predictive simulations for specific socio-ecological contexts.     

Quantifying urban water supply security under global change

Urban water supply security is commonly measured in terms of per capita water availability at the city level. However, the actual services that citizens receive are influenced by several components, including (1) a city's access to water, (2) infrastructure for its treatment, storage and distribution, (3) financial capital for building and maintaining infrastructure, and (4) management efficacy for regulating and operating the water system. These four types of "capital" are required for the provision of public water supply services. A fifth capital “community adaptation” is needed when public services are insufficient. Here, we develop and test an integrated framework for the quantification of urban water supply security based on these five capitals. “Security” involves three dimensions: 1) the level of system function (i.e., supply services); 2) risks to these services; and 3) robustness of system functioning. We apply this Capital Portfolio Approach (CPA) to seven urban case studies selected from a wide range of hydro-climatic and socio-economic regions on four continents. Detailed data on urban water infrastructure and services were collected in two cities, and key stakeholder interviews and household surveys were conducted in one city. Additional cities were assessed based on publicly available utility and globally available datasets. We find that in cities with high levels of public services, adaptive capacity remains inactive, while cities with high levels of water insecurity rely on community adaptation for self-provision of services. Inequality in the capacity to adapt leads to variable levels of urban water security and the vulnerability of the urban poor. Results demonstrate the applicability of the presented framework for the assessment of individual urban water systems, as well as for cross-city comparison of any type of cities. We discuss implications for policy and decision-making.     

气候模式FIO-ESM对2015/16年厄尔尼诺的预测

Recently atmospheric and oceanic observations indicate the tropical Pacific is at the El Ni?o condition. However,it's not clear whether this El Ni?o event of this year is comparable to the very strong one of 1997/98 which brought huge influence on the whole world. In this study, based on the Ensemble Adjusted Kalman Filter(EAKF)assimilation scheme and First Institute of Oceanography-Earth System Model(FIO-ESM), the assimilation system is setup, which can provide reasonable initial conditions for prediction. And the hindcast results suggest the skill of El Ni?o-Southern Oscillation(ENSO) prediction is comparable to other dynamical coupled models. Then the prediction for 2015/16 El Ni?o by using FIO-ESM is started from 1 November 2015. The ensemble results indicate that the 2015/16 El Ni?o will continue to be strong. By the end of 2015, the strongest strength is very like more than 2.0°C and the ensemble mean strength is 2.34°C, which indicates 2015/16 El Ni?o event will be very strong but slightly less than that of 1997/98 El Ni?o event(2.40°C) calculated relative a climatology based on the years1992–2014. The prediction results also suggest 2015/16 El Ni?o event will be a transition to ENSO-neutral level in the early spring(FMA) 2016, and then may transfer to La Ni?a in summer 2016.     

Neural adaptive robust control of underactuated marine surface vehicles with input saturation

This paper proposes a saturated tracking controller for underactuated autonomous marine surface vehicles with limited torque. First, a second-order open-loop error dynamic model is developed in the actuated degrees of freedom to simplify the design procedure. Then, a saturated tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. This, in turn, improves the transient performance of the control system. A multi-layer neural network and adaptive robust control techniques are also employed to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a hovercraft vehicle to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications.     

Palomar and Table Mountain observations of 9P/Tempel 1 during the Deep Impact encounter: First results

We present the first results of the Palomar Adaptive Optics observations taken during the Deep Impact encounter with 9P/Tempel 1 in July 2005. We have combined the Palomar near-IR imaging data with our visual wavelength images obtained simultaneously at JPL's Table Mountain Observatory to cover the total wavelength range from 0.4 to 2.3 μm in the B, V, R, I, J, H, and K filter bands, spanning the dates from 2005 July 03-07. We also include in our overall analysis images taken on the pre-encounter dates of June 1 and June 15, 2005. The broad wavelength range of our observations, along with high temporal resolution, near-IR sensitivity, and spatial resolution of our imaging, have enabled us to place constraints on the temperature of the impact flash and incandescent plume of >700 K, and to provide mean dust velocities of order approximately 1.25 h after impact derived from our 1.64 μm observations. Our ejected dust mass estimates, as derived from our near-IR observations, are an order of magnitude less than those previously reported for visual wavelength observations.