Ex Ante Impact Assessment of Policies Affecting Land Use, Part B: Application of the Analytical Framework

The use of science-based tools for impact assessment has increasingly gained focus in addressing the complexity of interactions between environment, society, and economy. For integrated assessment of policies affecting land use, an analytical framework was developed. The aim of our work was to apply the analytical framework for specific scenario cases and in combination with quantitative and qualitative application methods. The analytical framework was tested for two cases involving the ex ante impact assessment of: (1) a European Common Agricultural Policy (CAP) financial reform scenario employing a modeling approach and combined with a comprehensive indicator analysis and valuation; and (2) a regional bioenergy policy scenario, employing a fully participatory approach. The results showed that European land use in general is less sensitive to changes in the Common Agricultural Policy, but in the context of regions there can be significant impacts on the functions of land use. In general, the implementation of the analytical framework for impact assessment proved to be doable with both methods, i.e., with the quantitative modeling and with the qualitative participatory approach. A key advantage of using the system of linked quantitative models is that it makes possible the simultaneous consideration of all relevant sectors of the economy without abstaining from a great level of detail for sectors of particular interest. Other advantages lie in the incontestable character of the results. Based on neutral, existing data with a fixed set of settings and regions, an absolute comparability and reproducibility throughout Europe can be maintained. Analyzing the pros and cons of both approaches showed that they could be used complementarily rather than be seen as competing alternatives

Integrated Assessment Modelling of Complexity in the New Zealand Farming Industry

As New Zealand farming industry pursues more productivity this has implication for environment and makes land use and agricultural policy decision processes more complex for which integrated assessment modeling (IAM) can support. The purpose of this review paper is to propose means through which IAM can be improved specifically to minimize uncertainties and increase relevance, reliability, and utility of outputs of different models. Literature suggests that the general motivation for land use change is that farmers do consider the environment, but need to maintain profitability. There are handful decision support tools for land use and land policy decisions but one common feature of most of the models is that each seems suitable for only a part of the complexity. An appropriate framework for linking different models in an integrated assessment is still needed. As integrated assessment often goes beyond an individual researcher‘s role, research institutions need to align their research portfolio across the dimensions of the complexity by creating an appropriate mechanism to integrate individual research into integrated assessments while individual researchers need to present modelling results in a compatible format for integration into another model‘s application.integrated assessment, modeling, complexity, farming industry, New Zealand, Agribusiness, Land Economics/Use,

Development of scenarios for land cover, population density, impervious cover, and conservation in New Hampshire, 2010–2100

Future changes in ecosystem services will depend heavily on changes in land cover and land use, which, in turn, are shaped by human activities. Given the challenges of predicting long-term changes in human behaviors and activities, scenarios provide a framework for simulating the long-term consequences of land-cover change on ecosystem function. As input for process-based models of terrestrial and aquatic ecosystem function, we developed scenarios for land cover, population density, and impervious cover for the state of New Hampshire for 2020–2100. Key drivers of change were identified through information gathered from six sources: historical trends, existing plans relating to New Hampshire’s land-cover future, surveys, existing population scenarios, key informant interviews with diverse stakeholders, and input from subject-matter experts. Scenarios were developed in parallel with information gathering, with details added iteratively as new questions emerged. The final scenarios span a continuum from spatially dispersed development with a low value placed on ecosystem services (Backyard Amenities) to concentrated development with a high value placed on ecosystem services (the Community Amenities family). The Community family includes two population scenarios (Large Community and Small Community), to be combined with two scenarios for land cover (Protection of Wildlands and Promotion of Local Food), producing combinations that bring the total number of scenarios to six. Between Backyard Amenities and Community Amenities is a scenario based on linear extrapolations of current trends (Linear Trends). Custom models were used to simulate decadal change in land cover, population density, and impervious cover. We present raster maps and proportion of impervious cover for HUC10 watersheds under each scenario and discuss the trade-offs of our translation and modeling approach within the context of contemporary scenario projects

Scientific knowledge and scientific uncertainty in bushfire and flood risk mitigation: literature review

EXECUTIVE SUMMARY The Scientific Diversity, Scientific Uncertainty and Risk Mitigation Policy and Planning (RMPP) project aims to investigate the diversity and uncertainty of bushfire and flood science, and its contribution to risk mitigation policy and planning. The project investigates how policy makers, practitioners, courts, inquiries and the community differentiate, understand and use scientific knowledge in relation to bushfire and flood risk. It uses qualitative social science methods and case studies to analyse how diverse types of knowledge are ordered and judged as salient, credible and authoritative, and the pragmatic meaning this holds for emergency management across the PPRR spectrum. This research report is the second literature review of the RMPP project and was written before any of the case studies had been completed. It synthesises approximately 250 academic sources on bushfire and flood risk science, including research on hazard modelling, prescribed burning, hydrological engineering, development planning, meteorology, climatology and evacuation planning. The report also incorporates theoretical insights from the fields of risk studies and science and technology studies (STS), as well as indicative research regarding the public understandings of science, risk communication and deliberative planning. This report outlines the key scientific practices (methods and knowledge) and scientific uncertainties in bushfire and flood risk mitigation in Australia. Scientific uncertainties are those ‘known unknowns’ and ‘unknown unknowns’ that emerge from the development and utilisation of scientific knowledge. Risk mitigation involves those processes through which agencies attempt to limit the vulnerability of assets and values to a given hazard. The focus of this report is the uncertainties encountered and managed by risk mitigation professionals in regards to these two hazards, though literature regarding natural sciences and the scientific method more generally are also included where appropriate. It is important to note that while this report excludes professional experience and local knowledge from its consideration of uncertainties and knowledge, these are also very important aspects of risk mitigation which will be addressed in the RMPP project’s case studies. Key findings of this report include: Risk and scientific knowledge are both constructed categories, indicating that attempts to understand any individual instance of risk or scientific knowledge should be understood in light of the social, political, economic, and ecological context in which they emerge. Uncertainty is a necessary element of scientific methods, and as such risk mitigation practitioners and researchers alike should seek to ‘embrace uncertainty’ (Moore et al., 2005) as part of navigating bushfire and flood risk mitigation

The ecomics of ecosystems and biodiversity: scoping the scale

The G8 decided in March 2007 to initiate a “Review on the economics of biodiversity loss”, in the so called Potsdam Initiative: 'In a global study we will initiate the process of analysing the global economic benefit of biological diversity, the costs of the loss of biodiversity and the failure to take protective measures versus the costs of effective conservation. The study is being supported by the European Commission (together with the European Environmental Agency and in cooperation with the German Government. “The objective of the current study is to provide a coherent overview of existing scientific knowledge upon which to base the economics of the Review, and to propose a coherent global programme of scientific work, both for Phase 2 (consolidation) and to enable more robust future iterations of the Review beyond 2010.

Synergies for Improving Oil Palm Production and Forest Conservation in Floodplain Landscapes

Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world’s tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates ($413/ha?yr–$637/ha?yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of $-299/ha?yr-$-65/ha?yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes

Mapping and explaining the productivity of Pinus radiata in New Zealand

Mapping Pinus radiata productivity for New Zealand not only provides useful information for forest owners, industry stakeholders and policy managers, but also enables current and future plantations to be visualised, quantified, and planned. Using an extensive set of permanent sample plots, split into fitting (n = 1,146) and validation (n = 618) datasets, models of P. radiata 300 Index (an index of volume mean annual increment) and Site Index (an index of height growth) were developed using a regression kriging technique. Spatial predictions were accurate and accounted for 61% and 70% of the variance for 300 Index and Site Index, respectively. Productivity predicted from these surfaces for the entire plantation estate averaged 27.4 m³ ha⁻¹ yr⁻¹ for the 300 Index and 30.4 m for Site Index. Surfaces showed wide regional variation in this productivity, which was attributable mainly to variation in air temperature and root-zone water storage from site to site