Temporal trajectories of phosphorus and pedo-patterns mapped in Water Conservation Area 2, Everglades, Florida, USA

Grunwald, Sabine; Osborne, Todd Z.; Reddy, K. R.

doi:10.1016/j.geoderma.2008.03.023

Cited by 20 publications

(16 citation statements)

References 39 publications

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“…This soil phosphorus gradient has been widely documented and studied (DeBusk et al 1994;Grunwald et al 2004Grunwald et al , 2008Rivero et al 2007a,b;Grunwald 2010). Given the unavailability of spatial soil phosphorus data beyond map classifications (Grunwald 2010), soil phosphorus input maps were created by overlaying the WCA2A mesh on the existing maps obtained from Grunwald et al (2004Grunwald et al ( , 2008. The soil phosphorus map of 1990 was used for the model training period of 1991-1995, while the soil phosphorus map of 2003 was used for both the testing 1 (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003) and testing 2 (1995-2003) simulation periods.…”

Section: Soil Phosphorusmentioning

confidence: 94%

A spatially distributed, deterministic approach to modeling Typha domingensis (cattail) in an Everglades wetland

et al. 2012

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Introduction: The emergent wetland species Typha domingensis (cattail) is a native Florida Everglades monocotyledonous macrophyte. It has become invasive due to anthropogenic disturbances and is out-competing other vegetation in the region, especially in areas historically dominated by Cladium jamaicense (sawgrass). There is a need for a quantitative, deterministic model in order to accurately simulate the regional-scale cattail dynamics in the Everglades. Methods: The Regional Simulation Model (RSM), combined with the Transport and Reaction Simulation Engine (TARSE), was adapted to simulate ecology. This provides a framework for user-defineable equations and relationships and enables multiple theories with different levels of complexity to be tested simultaneously. Five models, or levels, of increasing complexity were used to simulate cattail dynamics across Water Conservation Area 2A (WCA2A), which is located just south of Lake Okeechobee, in Florida, USA. These levels of complexity were formulated to correspond with five hypotheses regarding the growth and spread of cattail. The first level of complexity assumed a logistic growth pattern to test whether cattail growth is density dependent. The second level of complexity built on the first and included a Habitat Suitability Index (HSI) factor influenced by water depth to test whether this might be an important factor for cattail expansion. The third level of complexity built on the second and included an HSI factor influenced by soil phosphorus concentration to test whether this is a contributing factor for cattail expansion. The fourth level of complexity built on the third and included an HSI factor influenced by (a level 1-simulated) sawgrass density to determine whether sawgrass density impacted the rate of cattail expansion. The fifth level of complexity built on the fourth and included a feedback mechanism whereby the cattail densities influenced the sawgrass densities to determine the impact of inter-species interactions on the cattail dynamics. Results: All the simulation results from the different levels of complexity were compared to observed data for the years 1995 and 2003. Their performance was analyzed using a number of different statistics that each represent a different perspective on the ecological dynamics of the system. These statistics include box-plots, abundance-area curves, Moran's I, and classified difference. The statistics were summarized using the Nash-Sutcliffe coefficient. The results from all of these comparisons indicate that the more complex level 4 and level 5 models were able to simulate the observed data with a reasonable degree of accuracy.

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Section: Soil Phosphorusmentioning

confidence: 94%

A spatially distributed, deterministic approach to modeling Typha domingensis (cattail) in an Everglades wetland

et al. 2012

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“…When water quality is restored, soils may continue to be a source of nutrients for some time. This legacy effect is of great concern as it may confound assessment of ongoing restoration activities (Reddy, et al, 2005;Grunwald et al, 2008;Marchant et al, 2009). Ecological stressors, such as hydrologic alteration, soil loss, and water/soil quality, are interrelated and thus efforts to assess and manage these stressors must likewise be integrated (Scheidt and Kalla, 2007;Osborne et al 2011a;Osborne et al 2013b).…”

Section: Introductionmentioning

confidence: 99%

Soil Nutrient Assessment and Characterization in a Degraded Central Florida Swamp

Bukata¹,

Osborne

Szafraniec

2015

Water Air Soil Pollut

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Flatford Swamp, a 2800-acre forested wetland in east Manatee County, Florida, serves as the headwaters of the Myakka River. Over the last two decades, Flatford swamp has experienced significant tree mortality. The cause of this mortality, as well as dramatic encroachment of several invasive herbaceous and shrub species, is thought to be linked to hydrologic alterations that resulted in increased inundation during the wet and dry seasons. A biogeochemical characterization of wetland soils was conducted to (1) establish a baseline spatial distribution of soil P and N in Flatford Swamp, (2) determine if soil biogeochemistry could be related to tree mortality, and (3) determine if soil biogeochemical conditions may affect future restoration efforts. Mean total nitrogen and total carbon in sampled soils ranged from 13.8 to 24.9 mg kg −1 and 211 to 468 mg kg −1 , respectively, indicating that soils are predominantly organic. Environmental conditions suggest that the nitrate-reduction process occurs readily in Flatford Swamp, and thus N abatement will continue naturally during restoration. Soil total phosphorus content is significantly higher than expected and is likely one of several contributing factors that led to observed changes in vegetation community structure. Levels of total sulfur, total calcium, and conductivity, indicative of agricultural use of groundwater for irrigation, suggest sulfide toxicity as a plausible contributing mechanism in the observed dieback of Nyssa sylvatica var. biflora.

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“…Various prediction or interpolation methods have been applied in the digital mapping of soil properties, especially statistical methods such as multiple linear regression (Hengl et al, 2007;Mabit et al, 2008;Ciampalini et al, 2012), geostatistical approaches such as ordinary kriging (Bishop & McBratney, 2001;Grunwald et al, 2008) and co-kriging (Ersahin, 2003;Rivero et al, 2007), and hybrid techniques such as regression-kriging (Bishop & McBratney, 2001;Sun et al, 2012). …”

Section: Introductionmentioning

confidence: 99%

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Carvalho

Chagas

Lagacherie

et al. 2014

Rev. Bras. Ciênc. Solo

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SUMMARYSoil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.Index terms: multiple linear regression, kriging, Co-Kriging.(1) Received for publicationon July 9, 2013 andapprovedonFebruary 27, 2014. RESUMO: AVALIAÇÃO DE MODELOS ESTATÍSTICOS E GEOESTATÍSTICOS NO MAPEAMENTO DIGITAL DE PROPRIEDADES DOS SOLOS, EM REGIÕES TROPICAIS MONTANHOSASAs propriedades dos solos têm grande impacto sobre aspectos econômicos e ambientais da produção agropecuária. As relações quantitativas entre as propriedades dos solos e os fatores que condicionam sua variabilidade são a base do mapeamento digital de solos. Os modelos preditivos de propriedades dos solos avaliados neste trabalho são os estatísticos (Regressão Linear Múltipla-RLM) e geoestatísticos (krigagem ordinária e cokrigagem). Este estudo foi desenvolvido para o município de Bom Jardim, RJ, e usou um banco de dados de solos com 208 pontos amostrais. Foram avaliados modelos preditivos para as frações areia, silte e argila, pH em água e carbono orgânico para seis profundidades, de acordo com as especificações do consórcio de mapeamento digital de solos em nível global (GlobalSoilMap). Utilizaram-se covariáveis preditoras contínuas e categóricas, estas últimas para avaliar suas contribuições ao modelo. Apenas as covariáveis ambientais elevação, aspecto, índice de potência de fluxo (SPI), índice de umidade (SWI), índice de vegetação por diferença normalizada (NDVI) e relação entre bandas b3/b2 apresentaram correlação significativa com as propriedades d...

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Temporal trajectories of phosphorus and pedo-patterns mapped in Water Conservation Area 2, Everglades, Florida, USA

Cited by 20 publications

References 39 publications

A spatially distributed, deterministic approach to modeling Typha domingensis (cattail) in an Everglades wetland

A spatially distributed, deterministic approach to modeling Typha domingensis (cattail) in an Everglades wetland

Soil Nutrient Assessment and Characterization in a Degraded Central Florida Swamp

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

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