Abstract
The data envelopment analysis (DEA) is useful for the measuring of efficiencies of functions in various research fields. In previous studies the soil carbon sequestration (SCseq) efficiency index (SCI) was assessed at regional scale; however, the effects of various calculation factors—including returns-to-scales (RTSs), selection of orientation (input or output), and global (or meta-)/local (or group) frontiers—on the SCI scores are still unclear. Thus, in this paper, the sensitivity of DEA frontier models with various types of RTSs and orientations was investigated. The models examined the SCseq rates as target outputs in three land use/land cover (LULC) types (pinelands, improved pastures, and wetlands). The rates were calculated based on lab-measured soil organic carbon concentration collected from the topsoil (~20 cm depth) between 1965 and 2009 in Florida, United States. Pedogenic, hydrologic, and environmental variables relevant to the carbon sequestration function were chosen as inputs, including soil available water capacity, sand concentration, pH, soil total nitrogen and phosphorus, Enhanced Vegetation Index, and Normalized Difference Vegetation Index. The input and output variables for the three LULC types informed multivariate normal distributions that served to simulate the local frontiers. Results show that the SCseq rates in wetland soils were statistically lowest (p<0.05), while the SCI scores were highest. This suggests that the efficiency of the soil carbon sequestration function was distinctively different from the SCseq rates. The SCI scores also demonstrated to identify internal causes (i.e., local management practices) for inefficiency in the SCseq in pasture soils and suitability of the function among the LULC types. A higher ability in output orientation to discern efficient from inefficient sites for the SCseq function was also observed than the input orientation. The preferred choice of RTSs in either conservative or progressive approaches to SCseq efficiency management was also identified in the study. Sensitive scores reflected regions that are in need for efficient soil management (such as no-tillage) to improve the performance of individual soils in terms of SCseq efficiency. SCseq efficiency scores enable land resource managers to refine their approaches to optimize soil carbon and possibly other soil and ecological functions. Further research is invited to identify potential cause(s) that determine(s) the local/global frontiers.
| Original language | English |
|---|---|
| Article number | 107602 |
| Journal | Ecological Indicators |
| Volume | 125 |
| DOIs | |
| State | Published - Jun 2021 |
Bibliographical note
Publisher Copyright:© 2021 The Authors
Funding
We are grateful to our statistics consultant, James Colee, for his practical responses to our questions regarding statistics in general. Funding support came from the Japan Student Services Organization and the University of Florida Soil and Water Sciences Department for general work, and from the USDA-CSREES-NRI-funded project 2007-35107-18368, “Rapid Assessment and Trajectory Modeling of Changes in Soil Carbon across a Southeastern Landscape” (National Institute of Food and Agriculture–Agriculture and Food Research Initiative) for soil data. The Pedometrics, Landscape Analysis, and GIS Laboratory of Dr. Grunwald provided computational resources and geospatial environmental data. This project is a Core Project of the North American Carbon Program. Historical soil data were retrieved from the Florida Soil Characterization dataset compiled by Dr. Grunwald and Dr. Harris. We are grateful to our statistics consultant, James Colee, for his practical responses to our questions regarding statistics in general. Funding support came from the Japan Student Services Organization and the University of Florida Soil and Water Sciences Department for general work, and from the USDA-CSREES-NRI-funded project 2007-35107-18368, ?Rapid Assessment and Trajectory Modeling of Changes in Soil Carbon across a Southeastern Landscape? (National Institute of Food and Agriculture?Agriculture and Food Research Initiative) for soil data. The Pedometrics, Landscape Analysis, and GIS Laboratory of Dr. Grunwald provided computational resources and geospatial environmental data. This project is a Core Project of the North American Carbon Program. Historical soil data were retrieved from the Florida Soil Characterization dataset compiled by Dr. Grunwald and Dr. Harris.
| Funders | Funder number |
|---|---|
| US Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative | |
| North American Carbon Program | |
| USDA-CSREES-NRI-funded | 2007-35107-18368 |
| University of Florida Soil and Water Sciences Department | |
| US Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative | |
| Japan Student Services Organization |
Keywords
- Data envelopment analysis
- Efficiency benchmarking
- Metafrontier models
- Multivariate normal distribution
- Sensitivity analysis
- Soil carbon sequestration
ASJC Scopus subject areas
- General Decision Sciences
- Ecology, Evolution, Behavior and Systematics
- Ecology