The Impact of Spatial Variation in Land Use Patterns and Aquifer Characteristics on the Agricultural Cost of Groundwater Conservation for the Southern Ogallala Aquifer

Land Economics/Use,

The Impact of Spatial Heterogeneity in Land Use Practices and Aquifer Characteristics on Groundwater Conservation Policy Cost

Estimation of agricultural policy cost for a given level of groundwater conservation requires the establishment of an accurate baseline condition. This is especially critical when the benefits and cost of any conservation program are generally estimated relative to the status quo policy or baseline situation. An inaccurate baseline estimate will lead to poor estimates of potential water conservation savings and agricultural policy cost. Over a 60-year planning horizon per acre net present value is as much as 29.8% higher for a study area when aquifer characteristics are assumed to be homogenous and set to their average area value than when the heterogeneity in aquifer characteristics is explicitly modeled.Aquifer Modeling, Economics, Resource /Energy Economics and Policy,

Integrating forest structural diversity measurement into ecological research

The measurement of forest structure has evolved steadily due to advances in technology, methodology, and theory. Such advances have greatly increased our capacity to describe key forest structural elements and resulted in a range of measurement approaches from traditional analog tools such as measurement tapes to highly derived and computationally intensive methods such as advanced remote sensing tools (e.g., lidar, radar). This assortment of measurement approaches results in structural metrics unique to each method, with the caveat that metrics may be biased or constrained by the measurement approach taken. While forest structural diversity (FSD) metrics foster novel research opportunities, understanding how they are measured or derived, limitations of the measurement approach taken, as well as their biological interpretation is crucial for proper application. We review the measurement of forest structure and structural diversity—an umbrella term that includes quantification of the distribution of functional and biotic components of forests. We consider how and where these approaches can be used, the role of technology in measuring structure, how measurement impacts extend beyond research, and current limitations and potential opportunities for future research

SOX7 Target Genes and Their Contribution to Its Tumor Suppressive Function

SOX7 is a transcription factor and acts as a tumor suppressor, but its target genes in cancers are poorly explored. We revealed SOX7-mediated gene expression profile in breast cancer cells using microarray chips and discovered multiple altered signaling pathways. When combinatorially analyzing the microarray data with a gene array dataset from 759 breast cancer patients, we identified four genes as potential targets of SOX7 and validated them by quantitative PCR and chromatin immunoprecipitation assays. Among these four genes, we determined that SOX7-activated SPRY1 and SLIT2, and SOX7-repressed TRIB3 and MTHFD2 could all differentially contribute to SOX7-mediated tumor suppression. Overall, we identified multiple cancer-related pathways mediated by SOX7 and for the first time revealed SOX7-regulated target genes in a cancer-relevant context

Projecting the Economic Impact and Level of Groundwater Use in the Southern High Plains under Alternative Climate Change Forecasts Using a Coupled Economic and Hydrologic Model

This research estimates the impact that eight alternative climate change scenarios are likely to have on agricultural returns and the useful life of the Ogallala aquifer in the Southern High Plains (SHP) over a 90-year planning horizon, relative to the situation where climate conditions are maintained at the historical average condition for 1960 to 2009. The empirical analysis is accomplished with the aid of an integrated water policy model that couples a dynamic economic optimization model to a detailed aquifer model of the Southern Ogallala Aquifer. The integrated model controls for the effects of spatial heterogeneity in land use practices and aquifer characteristics. For each climate scenario, changes in annual economic returns, irrigated acres, water use, and aquifer storage levels are measured relative to respective estimates derived from the historic no change climate scenario. The annual 90-year time path of economic returns, water use, and cropping patterns under the eight climate change scenarios significantly varies from the baseline forecast. Moreover, relative to a baseline condition that estimates significant annual decreases in economic returns due to continued groundwater mining, the climate change scenarios generally suggest climate change will mitigate the cost of increasing groundwater scarcity due to a complimentary effect between crop yields and the various climate change scenarios

The Impact of Spatial Heterogeneity in Land Use Practices and Aquifer Characteristics on Groundwater Conservation Policy Cost

Estimation of agricultural policy cost for a given level of groundwater conservation requires the establishment of an accurate baseline condition. This is especially critical when the benefits and cost of any conservation program are generally estimated relative to the status quo policy or baseline situation. An inaccurate baseline estimate will lead to poor estimates of potential water conservation savings and agricultural policy cost. Over a 60-year planning horizon per acre net present value is as much as 29.8% higher for a study area when aquifer characteristics are assumed to be homogenous and set to their average area value than when the heterogeneity in aquifer characteristics is explicitly modeled

Scale dependency of lidar‐derived forest structural diversity

Abstract Lidar‐derived forest structural diversity (FSD) metrics—including measures of forest canopy height, vegetation arrangement, canopy cover (CC), structural complexity and leaf area and density—are increasingly used to describe forest structural characteristics and can be used to infer many ecosystem functions. Despite broad adoption, the importance of spatial resolution (grain and extent) over which these structural metrics are calculated remains largely unconsidered. Often researchers will quantify FSD at the spatial grain size of the process of interest without considering the scale dependency or statistical behaviour of the FSD metric employed. We investigated the appropriate scale of inference for eight lidar‐derived spatial metrics—CC, canopy relief ratio, foliar height diversity, leaf area index, mean and median canopy height, mean outer canopy height, and rugosity (RT)‐‐representing five FSD categories—canopy arrangement, CC, canopy height, leaf area and density, and canopy complexity. Optimal scale was determined using the representative elementary area (REA) concept whereby the REA is the smallest grain size representative of the extent. Structural metrics were calculated at increasing canopy spatial grain (from 5 to 1000 m) from aerial lidar data collected at nine different forested ecosystems including sub‐boreal, broadleaf temperate, needleleaf temperate, dry tropical, woodland and savanna systems, all sites are part of the National Ecological Observatory Network within the conterminous United States. To identify the REA of each FSD metric, we used changepoint analysis via segmented or piecewise regression which identifies significant changepoints for both the magnitude and variance of each metric. We find that using a spatial grain size between 25 and 75 m sufficiently captures the REA of CC, canopy arrangement, canopy leaf area and canopy complexity metrics across multiple forest types and a grain size of 30–150 m captures the REA of canopy height metrics. However, differences were evident among forest types with higher REA necessary to characterize CC in evergreen needleleaf forests, and canopy height in deciduous broadleaved forests. These findings indicate the appropriate range of spatial grain sizes from which inferences can be drawn from this set of FSD metrics, informing the use of lidar‐derived structural metrics for research and management applications