Asim Zia

Acknowledging Conservation Trade‐Offs and Embracing Complexity

There is a growing recognition that conservation often entails trade-offs. A focus on trade-offs can open the way to more complete consideration of the variety of positive and negative effects associated with conservation initiatives. In analyzing and working through conservation trade-offs, however, it is important to embrace the complexities inherent in the social context of conservation. In particular, it is important to recognize that the consequences of conservation activities are experienced, perceived, and understood differently from different perspectives, and that these perspectives are embedded in social systems and preexisting power relations. We illustrate the role of trade-offs in conservation and the complexities involved in understanding them with recent debates surrounding REDD (Reducing Emissions from Deforestation and Degradation), a global conservation policy designed to create incentives to reduce tropical deforestation. Often portrayed in terms of the multiple benefits it may provide: poverty alleviation, biodiversity conservation, and climate-change mitigation; REDD may involve substantial trade-offs. The gains of REDD may be associated with a reduction in incentives for industrialized countries to decrease carbon emissions; relocation of deforestation to places unaffected by REDD; increased inequality in places where people who make their livelihood from forests have insecure land tenure; loss of biological and cultural diversity that does not directly align with REDD measurement schemes; and erosion of community-based means of protecting forests. We believe it is important to acknowledge the potential trade-offs involved in conservation initiatives such as REDD and to examine these trade-offs in an open and integrative way that includes a variety of tools, methods, and points of view.

Evaluating the effects of ideology on public understanding of climate change science: How to improve communication across ideological divides?

While ideology can have a strong effect on citizen understanding of science, it is unclear how ideology interacts with other complicating factors, such as college education, which influence citizens’ comprehension of information. We focus on public understanding of climate change science and test the hypotheses: [H 1] as citizens’ ideology shifts from liberal to conservative, concern for global warming decreases; [H2] citizens with college education and higher general science literacy tend to have higher concern for global warming; and [H3] college education does not increase global warming concern for conservative ideologues. We implemented a survey instrument in California’s San Francisco Bay Area, and employed regression models to test the effects of ideology and other socio-demographic variables on citizen concern about global warming, terrorism, the economy, health care and poverty. We are able to confirm H1 and H3, but reject H2. Various strategies are discussed to improve the communication of climate change science across ideological divides.

Cross-Scale Value Trade-Offs in Managing Social-Ecological Systems: The Politics of Scale in Ruaha National Park, Tanzania

Management of social-ecological systems takes place amidst complex governance processes and cross-scale institutional arrangements that are mediated through politics of scale. Each management scenario generates distinct cross-scale trade-offs in the distribution of pluralistic values. This study explores the hypothesis that conservation-oriented management scenarios generate higher value for international and national scale social organizations, whereas mixed or more balanced management scenarios generate higher value for local scale social organizations. This hypothesis is explored in the management context of Ruaha National Park (RNP), Tanzania, especially the 2006 expansion of RNP that led to the eviction of many pastoralists and farmers. Five management scenarios for RNP, i.e., national park, game reserve, game control area, multiple use area, and open area, are evaluated in a multicriteria decision analytical framework on six valuation criteria: economic welfare; good governance; socio-cultural values; social equity; ecosystem services; and biodiversity protection; and at three spatial scales: local, national, and international. Based upon this evaluation, we discuss the politics of scale that ensue from the implementation of management alternatives with different mixes of conservation and development goals in social-ecological systems.

Accountable Climate Governance: Dilemmas of Performance Management across Complex Governance Networks

Abstract How can accountability be institutionalized across complex governance networks that are dealing with the transboundary pollution problem of mitigating greenhouse gas emissions at multiple spatial, temporal and social scales? To address this question, we propose an accountability framework that enables comparison of the democratic, market and administrative anchorage of actor accountability within and across governance networks. A comparative analysis of performance measures in a sample of climate governance networks is undertaken. This comparative analysis identifies four critical performance management dilemmas in the areas of strategy, uncertain science, integration of multiple scales, and monitoring and verification of performance measures.

Linking models of human behaviour and climate alters projected climate change

Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.Human behaviour is an important driver of emissions. A system-dynamics model that couples a psychological model of behaviour with a model of emissions and climate change shows that behaviour can influence global temperature in the year 2100 by up to 1.5 °C.

Coupled impacts of climate and land use change across a river–lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000–2040

Global climate change (GCC) is projected to bring higher-intensity precipitation and highervariability temperature regimes to theNortheasternUnited States. The interactive effects of GCCwith anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrientfluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated bywarmerwater temperatures due toGCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCCon the hydrological regime, water temperature, water quality, bloomduration and severity through 2040 in transnational Lake Champlain’sMissisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-basedmodel was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrologicalmodel to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulatedwith a 3Dhydrodynamic-biogeochemicalmodel.We find acceleratedGCC could drastically limit landmanagement options tomaintainwater quality, but the nature and severity of this impact varies dramatically byGCMandGCC scenario.

Risk Zones: Comparative Lesson Drawing and Policy Learning from Flood Insurance Programs

Abstract Risk insurance mechanisms have been proposed as proactive policy options to enhance the resilience of communities for coping with extreme events. Many risk insurance mechanisms require designation of “risk zones” to legalize governmental interventions. After a three-day workshop and ensuing interviews, “wicked” challenges were identified in the designation of risk zones: risk thresholds; land value; damage-reduction; land-use planning; forecast uncertainty; map accuracy; modifiable-areal-unit problem; winners and losers; single versus multiple hazards; and cross-jurisdictional administrative boundaries. A total of 56 peer-reviewed studies are synthesized that evaluate these “wicked” challenges in flood insurance programs and derive deliberative heuristics for designating risk zones in publicly sponsored insurance mechanisms.

The emergence of attractors under multi-level institutional designs: agent-based modeling of intergovernmental decision making for funding transportation projects

Abstract Multi-level institutional designs with distributed power and authority arrangements among federal, state, regional, and local government agencies could lead to the emergence of differential patterns of socioeconomic and infrastructure development pathways in complex social–ecological systems. Both exogenous drivers and endogenous processes in social–ecological systems can lead to changes in the number of “basins of attraction,” changes in the positions of the basins within the state space, and changes in the positions of the thresholds between basins. In an effort to advance the theory and practice of the governance of policy systems, this study addresses a narrower empirical question: how do intergovernmental institutional rules set by federal, state, and regional government agencies generate and sustain basins of attraction in funding infrastructure projects? A pattern-oriented, agent-based model (ABM) of an intergovernmental network has been developed to simulate real-world transportation policy implementation processes across the federal, the state of Vermont, regional, and local governments for prioritizing transportation projects. The ABM simulates baseline and alternative intergovernmental institutional rule structures and assesses their impacts on financial investment flows. The ABM was calibrated with data from multiple focus groups, individual interviews, and analysis of federal, state, and regional scale transportation projects and programs. The results from experimental simulations are presented to test system-wide effects of alternative multi-level institutional designs, in particular different power and authority arrangements between state and regional governments, on the emergence of roadway project prioritization patterns and funding allocations across regions and towns.

The critical role of information sharing to the value proposition of a food systems network

ABSTRACT With goal-directed networks being used so extensively as a strategy to achieve ‘collective impact,’ increased attention is being paid to the investment of participating member organizations’ time, and informational, financial, and human capital in these efforts. Authors draw on the concept of ‘value proposition’ from the business and public administration literature and use extensive network data from a food systems planning network to test hypotheses focusing on the positionality of member organizations within specific operational subnetworks by correlating positionality with multiple assessments of value. Results indicate that embeddedness in the information sharing subnetwork most strongly correlates with member value proposition.

Mining Climate Change Awareness on Twitter: A PageRank Network Analysis Method

Climate change is one of this century’s greatest unbalancing forces that affect our planet. Mining the public awareness is an essential step towards the assessment of current climate policies, dedication of sufficient resources, and construction of new policies for business planning. In this paper, we present an exploratory data mining method that compares two types of networks. The first type is constructed from a set of words collected from a Climate Change corpus, which we consider as ground-truth (i.e., base of comparison). The other type of network is constructed from a reasonably large data set of 72 million tweets; it is used to analyze the public awareness of climate change on Twitter.