Resource Policy Analysis Research Articles

Climate Smart Agriculture - A Comprehensive Scoping and Assessment Study with Particular Reference to Uganda

** The paper is based on the study carried out by the author for FAO (Food and Agriculture Organization) and FANRPAN (Food, Agriculture and Natural Resources Policy Analysis Network) as a consultant.
 Based on the projection on population growth and food consumption pattern in developing countries, there is likely to be a deficit in the food production by the year
 2050. Africa’s population has just passed 1 billion and it is expected to double by the year 2050 (FAO 2012) According to FAO, Sub Saharan Africa, Uganda inclusive, is the region that has the highest proportion of poor and undernourished people in Africa (FAO,2011a). Agricultural production will, therefore have to increase by at least 70% in order to ensure that the food demands are met.
 Meeting the food demands of a growing population is already a formidable task for agricultural sector of many developing nations like Uganda but this will be further exacerbated by climate change. Largely due to climate change, agricultural productivity is likely to decrease. Similarly, the stability of production and incomes are likely to change. This trend may be even worse in countries which are already experiencing food insecurity (FAO 2012)
 The important implication of this is that for Uganda, policy makers will be faced with an even greater challenge to ensure that agriculture contributes more in addressing food security issues, development and climate change (adaptation and mitigation). In other words, agriculture in Uganda must undergo major and significant transformation in order to address the challenges likely to be faced in achieving food security and responding to climate change. Put in another way, in order to stabilize output and income, production systems must become more resilient or more capable of performing well in the face of disruptive events. This requires transformation in the management of natural resources and higher efficiency in the use of these resources and inputs for production. 
 According to FAO, approaches that seek to maximize the benefits and minimize the trade-offs across the multiple objectives, often associated with agricultural sector, require more integrated and coordinated planning, policies and institutional arrangements as well as financing and investments. Such approaches and related enabling requirements are referred to by FAO as climate smart agriculture. Climate Smart Agriculture (CSA) is thus a way to ensure the achievements of future food security under climate change. CSA encompasses sustainable agriculture and it includes the need for adaptation and the potential for mitigation with associated technical, policy and financing implications.
 This scoping study attempts to review and examine the current production practices as it relates to CSA in Uganda. The study also seeks to conduct comprehensive reviews of the existing policies, analyze gaps and identify relevant policy recommendations.

Bali Cattle Business Competitiveness According to the Moyo Watershed (DAS) in Sumbawa Regency, West Nusa Tenggara

The research objectives were: (1) to analyze the cost of domestic resources for Bali cattle according to the business typology and (2) to analyze the efficiency of the Bali cattle business according to the business typology. The research location was the central area of the Moyo Watershed, Sumbawa Regency, with 50 random respondents and key figures: village heads, heads of livestock groups, intermediary traders, inter-island wholesalers, traders of agricultural tools, materials and medicines as well as the livestock and animal health services of Sumbawa Regency. Methods of taking respondents randomly based on business typology with survey methods and analyzed by (1) domestic resource cost analysis (BSD) and (2) Policy Analysis Matrix (PAM) analysis. From the results of the study, information was obtained that bali cattle breeders in the central area of the Moyo Watershed, Sumbawa Regency, West Nusa Tenggara used 3 (three) business typologies, namely: (1) breeding business typology, (2) savings business typology and (3) combination business typology (1+2). Comparative competitiveness of Bali cattle according to business typology as shown by the respective DRCR values, namely breeding typology 0.54; savings typology 0.49 and combination typology 0.32. The competitive competitiveness shown by the PCR value is the breeding typology of 0.49; savings typology 0.59 and combination typology 0.35.

Network Analysis of Price Comovements Among Corn Futures and Cash Prices

Abstract Due to significant implications for resource and food sectors that directly influence social well-being, commodity price comovements represent an important issue in agricultural economics. In this study, we approach this issue by concentrating on daily prices of the corn futures market and 496 cash markets from 16 states in the United States for the period of July 2006 – February 2011 through correlation based hierarchical analysis and synchronization analysis, which allow for determining interactions and interdependence among these prices, heterogeneities in price synchronization, and their changing patterns over time. As the first study of the issue focusing on prices of the futures and hundreds of spatially dispersed cash markets for a commodity of indubitable economic significance, empirical findings show that the degree of comovements is generally higher after March 2008 but no persistent increase is observed. Different groups of cash markets are identified, each of which has its members exhibit relatively stable price synchronization over time that is generally at a higher level than the synchronization among the futures and all of the 496 cash markets. The futures is not found to show stable price synchronization with any cash market. Certain cash markets have potential of serving as cash price leaders. Results here benefit resource and food policy analysis and design for economic welfare. The empirical framework has potential of being adapted to network analysis of prices of different commodities.

Network analysis of corn cash price comovements

Commodity price comovements are an important issue in economics given their significant implications for food and resource sectors that directly influence social well-being. This study approaches this issue by focusing on daily cash prices of 182 corn markets from the seven largest harvest states in the United States for 2006–2011 by using correlation based hierarchical analysis and synchronization analysis, through which we can determine interactions and interdependence among these prices, heterogeneities in price synchronization, and their changing patterns over time. As the first study of the issue concentrating on prices of hundreds of spatially dispersed markets for a commodity of indubitable economic significance, empirical findings show that the degree of comovements is generally higher after November 2006 but no persistent increase is observed. Different groups of markets are identified, each of which has its members exhibit similar price dynamics. Certain markets show potential of serving as price leaders. Results here benefit food and resource policy analysis and design for economic welfare. The empirical framework has potential of being adapted to network analysis of prices of different commodities.

Water Resource Policy Analysis and Stakeholder Involvement in Water Security

In accordance with the ratification of the Water Resource Law, which was established after Law Number 7 of 2004 is canceled by the Constitutional Court in 2015, water has now becoming fully controlled by the state through the Law no. 17/2019 concerning Water Resource Law. The identification of emerging interests on who would advantage from the use of water are not only coming from the communities but also from the various stakeholders. The method used in this journal is theoretical qualitative as basis for discussion and analysis. The purpose of this journal is to examine thoroughly the part of the policy which addressing water compliance, water security with an increasing threat on water crimes and water conflicts and involving stakeholders in enforcing the sustainability of water management upon the enactment of the latest Water Resource law.

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Marine Food Security Challenges

External interaction:The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency's new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

A bibliometric analysis of comparative research on the evolution of international and Chinese ecological footprint research hotspots and frontiers since 2000

The ecological footprint (EF) methodology, which is a tool for evaluating the natural resource use level and regional carrying capacity, has been extensively used to measure the capacity to reach both an ecological supply and demand balance and a level of sustainable development. In this study, to systematically sort and analyse the distribution of EF research, its hot areas and the evolution of its fronts, papers with “ecological footprint” as the subject term in the Web of Science Core Collection Database and the China Knowledge Resource Integrated Database Core Journals since 2000 are visually analysed using CiteSpace. The characteristics of these papers, including the quantity trend, quality, author group, affiliated institution type and journal type, are summarized, and keyword co-appearance and paper co-citation knowledge maps are produced. The results show the following: (1) Chinese researchers have been closely following international research fronts and steadily improving their research results. (2) Hotspots such as carbon dioxide emissions, the carbon footprint (CF), water footprint (WF) and sustainable use have been receiving attention both in China and internationally. International researchers focus on hot topics such as public satisfaction, land and resource use, spatial equity and policy analysis. In comparison, Chinese researchers prefer to modify and improve relevant methods, such as the three-dimensional EF (3D EF) and footprint family methods. (3) The research frontier of EF is based on improving the EF accounting method, which is aimed at assessing and monitoring the relationship between ecology and the economic society on a multi-scale basis, establishing an index system that can evaluate the demand for natural resources and environmental pressure, and explore the issues of mechanisms of regional ecology resource allocation fairness, and market-led and government-led ecological governance efficiency.

Dr. Ari M. Michelsen: Life Dedicated to Advances in Water Resources Development

Dr. Ari M. Michelsen: Life Dedicated to Advances in Water Resources Development

Integrating natural capital into system of national accounts for policy analysis: An application of a computable general equilibrium model

Natural capital is an asset that provides natural resource inputs and environmental services for economic production. Regional patterns of production and consumption have direct and indirect effects on sustainability of its natural capital. Traditional gross domestic product (GDP) estimates fail to explicitly and fully account for natural capital in system of national accounts (SNA). To address this gap, this study builds on United Nation's System of Environmental-Economic Accounting (SEEA) and provides a methodological framework to integrate natural capital into system of national accounts, in input-output table. It further illustrates how natural capital-integrated system of national accounts in input-output table can be used as an effective tool for natural resource management and policy analysis in computable general equilibrium (CGE) modeling framework. Results indicate that, without natural capital accounting and integration into system of national accounts, GDP estimates may give misleading signals as a measure of a region's economic performance, where economic growth could be at the expense of natural capital depletion.

Is robustness really robust? How different definitions of robustness impact decision-making under climate change

Robust decision-making is being increasingly used to support environmental resources decisions and policy analysis under changing climate and society. In this context, a robust decision is a decision that is as much as possible insensitive to a large degree of uncertainty and ensures certain performance across multiple plausible futures. Yet, the concept of robustness is neither unique nor static. Multiple robustness metrics, such as maximin, optimism-pessimism, max regret, have been proposed in the literature, reflecting diverse optimistic/pessimistic attitudes by the decision maker. Further, these attitudes can evolve in time as a response to sequences of favorable (or adverse) events, inducing possible dynamic changes in the robustness metrics. In this paper, we explore the impact of alternative definitions of robustness and their evolution in time for a case of water resources system management under changing climate. We study the decisions of the Lake Como operator, who is called to regulate the lake by balancing irrigation supply and flood control, under an ensemble of climate change scenarios. Results show a considerable variability in the system performance across multiple robustness metrics. In fact, the mis-definition of the actual decision maker’s attitude biases the simulation of its future decisions and produces a general underestimation of the system performance. The analysis of the dynamic evolution of the decision maker’s preferences further confirms the potentially strong impact of changing robustness definition on the decision-making outcomes. Climate change impact assessment studies should therefore include the definition of robustness among the uncertain parameters of the problem in order to analyze future human decisions under uncertainty.

Determinants of Vulnerability to Livelihood Insecurity at Household Level: Evidence from Maphutseng, Lesotho

This study investigated the major factors that influence the vulnerability of a household to food insecurity in the context of a rural community in Mohale’s Hoek. The study also traced the changes in the level of vulnerability of households to poverty between 2009 and 2013. Primary data was collected through the Household Vulnerability Index (HVI) survey of 2581 households in 2009 and 325 randomly sampled households in 2013. The Household Vulnerability Index developed by the Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) was used to quantify the household vulnerability of household based on the capital assets of the Sustainable Livelihood Framework: social assets, physical assets, financial assets, natural assets and human assets. An ordinal regression was estimated for the categories of vulnerability based on the HVI score: Low vulnerability, Moderate vulnerability and High Vulnerability. The results indicate that the proportion of households with a high vulnerability have increased by 7.8 percent between 2009 and 2013. Parameter estimates of the ordinal regression model identify highly vulnerable households as household as predominantly comprising of; (i) female headed households where the household head is of an elderly age, (ii) where the household has at most two meals a day which will be mainly wild fruits and inter-family food transfers, and (iii) those with limited land for cropping of staple foods. There is an urgent need to develop policies that are aimed at directly improve the livelihood of households in poverty stricken districts such Maphutesng as well as make the households more resilient to shocks.

A framework to bridge science and policy in complex decision making arenas

We argue that science concerned with natural resource policy analysis is entering a new phase. In response to policy demands for triple-bottom-line assessments, developing transdisciplinary endeavours has been a primary focus, catalysing methodological innovations. However, the period of innovation has increased the divergence between a science domain characterised by increasing complexity of communicated analytical outputs and a policy domain that generally remains impelled towards single metric outcomes. We argue that this new phase will see the focus shift from method innovation towards the design of research processes to correct the discrepancy. This paper describes the Challenge-and-Reconstruct Learning framework (ChaRL) for designing sustainability-focused research processes to better align science contributions and policy aspirations in complex decision making arenas. This paper provides evidence for how the ChaRL framework can (1) establish and maintain an effective science–policy interface despite high levels of complexity and high levels of contested values and (2) challenge and reconstruct existing knowledge, providing a robust foundation to evidence-based decision making. Critical for these achievements is that the design of the engagement process starts with the cognitive elements critical to the decision making processes, that is individuals’ causal beliefs and values.

The Rise and Fall of a Second-Generation CBNRM Project in Zambia: Insights from a Project Perspective

Since the advent of community-based natural resource management (CBNRM) in the mid-1980s, scholars and practitioners have sought to explain the uneven performance of CBNRM programs. Most CBNRM assessments examine the underlying principles of community-based conservation, the local social and ecological contexts, and connections with larger political and historical patterns. In this article, I argue that analysis of the potential and pitfalls of CBNRM also requires an understanding of the institutional history and internal dynamics of projects that implement CBNRM reforms. Drawing upon theory and methods from development ethnography and public policy, I examine the rise and fall of CONASA, a second-generation CBNRM project in Zambia that operated from 2001 to 2004. CONASA was constituted from a merger of organizations and discourses to provide continuity with previous projects. Its ambitious suite of activities included support for household livelihoods, community-based resource management, policy analysis, advocacy, and conservation enterprises at local, national, and transboundary levels. While individual activities were largely successful, CONASA's hybrid origins and logframe-centric management created fissures between its holistic design and operational logics, and hindered its ability to develop a broader narrative and maintain key alliances. This case study illustrates the importance of understanding the interplay between project design and operational context to fully appreciate the possibilities and limitations of project-mode conservation.

A system dynamics approach for water resources policy analysis in arid land: a model for Manas River Basin

The Manas River Basin in Xinjiang Uygur autonomous region, similar to other arid regions, is facing water constraints which challenge decision-makers as to how to rationally allocate the available water resources to meet the demands from industries and natural ecosystems. Policies which integrate the supply and demand are needed to address the water stress issues. An object-oriented system dynamics model was developed to capture the interrelationships between water availability and increasing water demands from the growth of industries, agricultural production and the population through modeling the decision-making process of the water exploration explicitly, in which water stress is used as a major indicator. The model is composed of four sectors: 1) natural surface and groundwater resources; 2) water demand; 3) the water exploitation process, including the decision to build reservoirs, canals and pumps; 4) water stress to which political and social systems respond through increasing the supply, limiting the growth or improving the water use efficiency. The model was calibrated using data from 1949 to 2009 for population growth, irrigated land area, industry output, perceived water stress, groundwater resources availability and the drying-out process of Manas River; and simulations were carried out from 2010 to 2050 on an annual time step. The comparison of results from calibration and observation showed that the model corresponds to observed behavior, and the simulated values fit the observed data and trends accurately. Sensitivity analysis showed that the model is robust to changes in model parameters related to population growth, land reclamation, pumping capacity and capital contribution to industry development capacity. Six scenarios were designed to investigate the effectiveness of policy options in the area of reservoir relocation, urban water recycling, water demand control and groundwater pumping control. The simulation runs demonstrated that the technical solutions for improving water availability and water use efficiency are not sustainable. Acknowledging the carrying capacity of water resources and eliminating a growth-orientated value system are crucial for the sustainability of the Manas River Basin.

A Comparision of Two Methods of Linking Spatial and Economic Data from Farm Surveys

Summary Linking scientific and economic data potentially has many benefits for natural resource management and policy analysis. This paper compares a sophisticated method for bringing these data together in farm surveys using detailed farm boundary data collected during an interview, with a less onerous approach requiring only a single point from each surveyed farm. A comparison is made by modelling land values using regression analysis in central New South Wales. It was found that there were only minor additional benefits from using the more sophisticated approach in this case. Additionally, there are significant costs in collecting and processing the detailed georeferencing data that make it considerably less practical than the simpler approach.

Continuous spatial modelling to analyse planning and economic consequences of offshore wind energy

Offshore wind resources appear abundant, but technological, economic and planning issues significantly reduce the theoretical potential. While massive investments are anticipated and planners and developers are scouting for viable locations and consider risk and impact, few studies simultaneously address potentials and costs together with the consequences of proposed planning in an analytical and continuous manner and for larger areas at once. Consequences may be investments short of efficiency and equity, and failed planning routines. A spatial resource economic model for the Danish offshore waters is presented, used to analyse area constraints, technological risks, priorities for development and opportunity costs of maintaining competing area uses. The SCREAM-offshore wind model (Spatially Continuous Resource Economic Analysis Model) uses raster-based geographical information systems (GIS) and considers numerous geographical factors, technology and cost data as well as planning information. Novel elements are weighted visibility analysis and geographically recorded shipping movements as variable constraints. A number of scenarios have been described, which include restrictions of using offshore areas, as well as alternative uses such as conservation and tourism. The results comprise maps, tables and cost-supply curves for further resource economic assessment and policy analysis. A discussion of parameter variations exposes uncertainties of technology development, environmental protection as well as competing area uses and illustrates how such models might assist in ameliorating public planning, while procuring decision bases for the political process. The method can be adapted to different research questions, and is largely applicable in other parts of the world.

Regions and the environment: experiences of environmental research networks in southern Africa

This paper analyses how the main environmental research networks in southern Africa have adopted a regional approach to environmental issues. Documented information is used to assess and discuss the experiences of the regional environmental research networks on the basis of four criteria: structure and functionality, productivity, impact and sustainability. It is apparent from the analysis that of the seven main regional environmental research networks studied, only the Food, Agriculture and Natural Resources Policy Analysis Network shows some signs of being on course towards consolidating a regional outlook. The other environmental research networks have structural, operational, funding and capacity constraints that hinder them from making meaningful contribution to environmental issues at a regional level. The paper recommends that an effective regional research network should have a Secretariat, operate as a broker between funding agencies and researchers based in other institutions, be ‘home-grown’ or at least have the support of the majority of local researchers, have a scope that is broader than just academic research and scientific publications and have diversified sources of funding to hedge it against the undue influence, whims and fancies of funding agencies, governments and research trusts.

A Reply to “Stranded Capital in Fisheries: The Pacific Coast Groundfish/Whiting Case” (The Comment)

James E. Wilen is a professor in the Department of Agricultural & Resource Economics and director of the Center for Natural Resources Policy Analysis at the University of California, Davis, CA 95616 USA. He is also a member of the Giannini Foundation (email: wilen@primal.ucdavis.edu). 1 Matulich states, “I begin this comment by anchoring the stranded processing capital issue in the literature Wilen anchors it—in the article by Matulich, Mittelhammer, and Reberte...MMR.” This overstates the connection between my article and MMR. To the extent that my article is “anchored” in any literature, it is in the literature on deregulation in non-fishery settings, notably electricity deregulation, as well as the corresponding literature on policy remedies in those cases. I do acknowledge MMR’s role as the source of the conceptual argument behind the stranded capital claims made by West Coast processors. The main issue I raise is empirical; namely whether the conceptual argument laid out in MMR is relevant to West Coast fisheries. A Reply to Stranded Capital in Fisheries: The Pacific Coast Groundfish/Whiting Case (The Comment)

Agriculture sector resource and environmental policy analysis: an economic and biophysical approach.

Agricultural pollution of the environment is jointly determined by economic decisions driving land use, production practices, and stochastic biophysical processes associated with agricultural production, land and climate characteristics. It follows that environmental and economic statistics, traditionally collected independently of each other, offer little insight into non-point pollutant loadings. We argue that effective policy development would be facilitated by integrating environmental and economic data gathering, combined with simulation modelling linking economic and biophysical components. Integrated data collection links economics, land use, production methods and environmental loadings. An integrated economic/biophysical modelling framework facilitates policy analysis because monetary incentives to reduce pollution can be evaluated in the context of market costs and returns that influence land use and production activity. This allows prediction of environmental and economic outcomes from alternative policies to solve environmental problems. We highlight steps taken to merge economic and biophysical modelling for policy analysis within the Economic Research Service of the United States Department of Agriculture. An example analysis of a policy to reduce agricultural nitrogen pollution is presented, with the economic and environmental results illustrating the value of linked economic and biophysical analysis.

Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A.

Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to each pixel in a digital landscape map. The gradient nearest neighbor method integrates vegetation measurements from regional grids of field plots, mapped environmental data, and Landsat Thematic Mapper (TM) imagery. In the Oregon coastal province, species gradients were most strongly associated with regional climate and geographic location, whereas variation in forest structure was best explained by Landsat TM variables. At the regional level, mapped predictions represented the range of variability in the sample data, and predicted area by vegetation type closely matched sample-based estimates. At the site level, mapped predictions maintained the covariance structure among multiple response variables. Prediction accuracy for tree species occurrence and several measures of vegetation structure and composition was good to moderate. Vegetation maps produced with the gradient nearest neighbor method are appropriately used for regional-level planning, policy analysis, and research, not to guide local management decisions.