Assessing the Effectiveness of Tradable Landuse Rights for Biodiversity Conservation: An Application to Canada's Boreal Mixedwood Forest

Ecological reserve networks are an important strategy for conserving biodiversity. One approach to selecting reserves is to use optimization algorithms that maximize an ecological objective function subject to a total reserve area constraint. Under this approach, economic factors such as potential land values and tenure arrangements are often ignored. Tradable landuse rights are proposed as an alternative economic mechanism for selecting reserves. Under this approach economic considerations determine the spatial distribution of development and reserves are allocated to sites with the lowest development value, minimizing the cost of the reserve network. The configuration of the reserve network as well as the biodiversity outcome is determined as a residual. However cost savings can be used to increase the total amount of area in reserve and improve biodiversity outcomes. The appropriateness of this approach for regional planning is discussed in light of key uncertainties associated with biodiversity protection. A comparison of biodiversity outcomes and costs under ecological versus economic approaches is undertaken for the Boreal Forest Natural Region of Alberta, Canada. We find a significant increase in total area protected and an increase in species representation under the TLR approach.Biodiversity conservation, Reserve design, Tradable landuse rights

Using Participatory Research Methods in Economic Research

Research Methods/ Statistical Methods,

Results from the Farm Behaviour Component of the Integrated Economic-Hydrologic Model for the Watershed Evaluation of Beneficial Management Practices Program

This report summarizes preliminary results from the Farm Behavior component of the South Tobacco Creek Integrated Modeling Project (STC Project) which is being undertaken as part of the Watershed Evaluation of BMPs (WEBs) Program. WEBS is a partnership between Agriculture and Agri-Food Canada (AAFC) and Ducks Unlimited Canada (DUC) established to evaluate the economic and environmental performance of BMPs for water quality at the watershed scale. Water draining from South Tobacco Creek eventually enters to Lake Winnipeg which is degraded from the cumulative effects of nutrient loading, particularly phosphorous. Many jurisdictions across the world, including Canada, use payments programs to encourage land owners to change land management practices in order to reduce non-point source pollution. BMP incentive programs in Canada, such as Greencover, rely on fixed payment schemes which pay producers a set amount for BMPs, regardless of costs or benefits. In order to improve the performance of payment programs many jurisdictions have instituted auction type mechanisms. The purpose of the Farm Behavior component of the STC project is to examine the performance of various types of payment programs for BMPs relative to reducing phosphorous loads from STC. Theoretical and empirical evidence from conservation auctions suggest that the performance of auctions depends on several factors which affect the bidding behavior of producers during the auction, and therefore the cost-effectiveness of auctions over other types of payment programs. In particular, some producers actually benefit from BMPs, however under certain auction rules these producers would be paid the same amount as high cost producers; alternatively, producers with low costs of adopting BMPs may not always provide the greatest benefits in terms of pollution abatement depending on their location in the watershed, and physical features of their land. We assessed the relative performance of different payment programs by developing producer response functions for adoption of Beneficial Management Practices (BMPs). Producer adoption responses under different incentive schemes were tested using experiments with student subjects and limited trials with producers. We examined four BMPs: construction of holding ponds, riparian management, forage conversion, and conservation till. The results of the adoption response experiments conducted under WEBS were used to draw preliminary observations on BMP policy design and form the basis for recommendations for further research. The farm behavior project focuses on addressing the following two questions: 1. Does BMP adoption at a given farm make the individual farm household better or worse off from an economic perspective? 2. How much will it cost the government to get farms to adopt BMPs under different payment programs? Since producer heterogeneity is key to understanding the performance of conservation auctions, we examined the costs and benefits of BMPs at the individual farm level and developed on-farm costs for each BMP for each producer in the watershed. The basic components of the model are described below, however the details including underlying assumptions regarding baseline farm behavior, are outlined within the body of the report. We used the on-farm cost model to generate aggregate cost functions for BMPs for the watershed and to parameterize the policy experiments related to conservation auctions. Preliminary estimates of environmental benefits of individual BMP adoption were provided by Dr. Wanhong Yang using results from a SWAT model developed under a separate component of the South Tobacco Creek WEBS project. Based on this information, we were able to evaluate the performance of various auction formats in terms of cost effectiveness, distribution of payments amongst producers, and environmental benefit. The results from the Farm behavior component of the South Tobacco Creek project are preliminary, and are currently being refined. Therefore it is difficult to draw generalized conclusions at this point. Further experiments are being conducted to complete the data collection during FY 08-09 through Interim WEBS funding. Nonetheless main findings to date are summarized below: 1. The four BMPs assessed differ in terms of their cost as well as their ability to deliver environmental benefits. Unfortunately, there is no BMP that dominates across farms at all abatement levels. Farms have heterogeneous costs in terms of BMPs, and some farms are cost effective at supplying abatement using one BMP, but not another. 2. This suggests that if water quality benefits (e.g. phosphorous reduction) can be quantified through modeling by BMP and by farm, then water quality should be the contracting unit for the auction rather than the BMP. This would allow producers to select the most cost effective BMP for supplying water quality benefits, and then decision makers could allocate contracts based on ranking the costs of abatement. 3. At the next stage of the research we will test for synergies between farms – ie., whether the joint production function for water quality between farms differs from the sum of individual production functions. This will have implications for how the payment scheme should be designed. 4. Incorporating „fairness‟ types of allocation rules for conservation dollars, such as maximum participation in conservation programs is inefficient in terms of cost and environmental benefits. If fairness, or using conservation payments as a form of extension to learn about on farm costs of BMPs is the goal of the auction, then fixed payment programs which are open to everyone may be more desirable. 5. The performance of the auction depends on the shape of the cost function for BMPs and/or pollution abatement, as well as whether uniform (pay everyone the highest bid) or discriminatory pricing (pay everyone their own bid) rules are applied. In future research we will be investigating to what extent we can generalize results about the performance of uniform versus discriminatory pricing rules in this context. In conclusion, this research has allowed us to investigate individually the performance of incentive payments for individual BMPs. The results of the analysis provide us with a baseline of information by which we can begin to assess more complex conservation program issues, such as how to optimally select multiple BMPs within the watershed, and whether/how to spatially target BMPs.watersheds, South Tobacco Creek, water quality, Environmental Economics and Policy, Land Economics/Use, Resource /Energy Economics and Policy, Q12,Q52,D44,

Arc River: Geo-Referenced Representation of River Hydrodymnamics

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Data-Driven Copy-Paste Imputation for Energy Time Series

A cornerstone of the worldwide transition to smart grids are smart meters. Smart meters typically collect and provide energy time series that are vital for various applications, such as grid simulations, fault-detection, load forecasting, load analysis, and load management. Unfortunately, these time series are often characterized by missing values that must be handled before the data can be used. A common approach to handle missing values in time series is imputation. However, existing imputation methods are designed for power time series and do not take into account the total energy of gaps, resulting in jumps or constant shifts when imputing energy time series. In order to overcome these issues, the present paper introduces the new Copy-Paste Imputation (CPI) method for energy time series. The CPI method copies data blocks with similar properties and pastes them into gaps of the time series while preserving the total energy of each gap. The new method is evaluated on a real-world dataset that contains six shares of artificially inserted missing values between 1 and 30%. It outperforms by far the three benchmark imputation methods selected for comparison. The comparison furthermore shows that the CPI method uses matching patterns and preserves the total energy of each gap while requiring only a moderate run-time.Comment: 8 pages, 7 figures, submitted to IEEE Transactions on Smart Grid, the first two authors equally contributed to this wor

Data-Driven Copy-Paste Imputation for Energy Time Series

A cornerstone of the worldwide transition to smart grids are smart meters. Smart meters typically collect and provide energy time series that are vital for various applications, such as grid simulations, fault-detection, load forecasting, load analysis, and load management. Unfortunately, these time series are often characterized by missing values that must be handled before the data can be used. A common approach to handle missing values in time series is imputation. However, existing imputation methods are designed for power time series and do not take into account the total energy of gaps, resulting in jumps or constant shifts when imputing energy time series. In order to overcome these issues, the present paper introduces the new Copy-Paste Imputation (CPI) method for energy time series. The CPI method copies data blocks with similar characteristics and pastes them into gaps of the time series while preserving the total energy of each gap. The new method is evaluated on a real-world dataset that contains six shares of artificially inserted missing values between 1 and 30%. It outperforms the three benchmark imputation methods selected for comparison. The comparison furthermore shows that the CPI method uses matching patterns and preserves the total energy of each gap while requiring only a moderate run-time