|VASQUES, GUSTAVO - Embrapa National Research Center|
|GRUNWALD, SABINE - University Of Florida|
Submitted to: Landscape Ecology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/14/2011
Publication Date: 1/3/2012
Citation: Vasques, G.M., Grunwald, S., Myers, D.B. 2012. Associations between soil carbon and ecological landscape drivers at escalating spatial scales in Florida, USA. Landscape Ecology. 27:355-367.
Interpretive Summary: The soil carbon pool is a large reservoir of carbon that actively exchanges carbon dioxide with the atmosphere. This exchange might be managed to store carbon into the soil, but the factors driving this exchange are dependent on highly variable soil and ecosystem properties. This variation produces spatial patterns in soil carbon distribution which can be examined to understand what soil and ecosystem properties are controlling the soil-atmosphere exchange of carbon. This study was designed to characterize linkages between hydrologic, biotic and soil carbon patterns across a large mixed-use landscape in Florida, USA, a humid subtropical region. Numerical and statistical techniques can be used to compare spatial patterns. We used these techniques to test a suite of soil, hydrologic, topographic, and remotely sensed land-surface properties to see if their spatial patterns matched that of soil carbon. Our results indicate that the spatial patterns of soil carbon in Florida are closely associated with the spatial patterns of soil available water capacity, suggesting that soil carbon patterns are linked to hydrologic patterns. In turn, hydrologic patterns correspond to water-related soil forming processes, in this case mostly related to organic matter decomposition, transformation, and accumulation in the soil. These findings suggest a hydrologic (process) – soil carbon (pattern) relationship. Secondary drivers of soil carbon variation were found to include soil saturated hydraulic conductivity, vegetation density, soil pH, land use, and soil drainage. This study enhanced our knowledge of pattern-process relationships between soil carbon and key hydrologic and ecological processes across a large subtropical landscape. Our results will inform land managers and policy makers implementing best management practices to retain soil carbon or reduce atmospheric carbon, and provide guidance to those wanting to understand the patterns of soil carbon distribution in other landscapes.
Technical Abstract: The spatial distribution of soil carbon (C) is controlled by ecological landscape processes that evolve over a range of spatial scales. Soil C patterns derive from a number of interacting ecological processes, some of which more dominant than others, depending on the landscape conditions. The spatial behavior of soil C and landscape patterns generated by complex hydrologic and biotic processes at different nested spatial scales is still poorly understood. Our objectives were to (i) identify the appropriate spatial scale to observe soil total C (TC) in a subtropical landscape with pronounced hydrologic and biotic variation, and (ii) investigate the spatial behavior and cross-relationships of TC and ecological landscape properties which aggregate various hydrologic and biotic processes. We aimed to identify possible ecological drivers (processes) to generate/explain TC’s patterns. The study was conducted in Florida, USA, characterized by extreme hydrologic (poorly to excessively drained soils) and vegetation/land use gradients ranging from natural (wetlands), urban, to intensively managed agro-forest systems. We compared the spatial dependence structure (through the semivariogram and landscape indices) of TC to that of 19 ecological landscape properties, identifying similarities and establishing pattern-process relationships between them. Key ecological variables, which mirrored the spatial behavior of TC at fine (< 6 km) and coarse (< 300 km) spatial scales, included a suite of soil, hydrologic and biotic properties. This study provides further guidance to identify the appropriate scale to measure those properties and processes which control C dynamics.