Distribution Of Vegetation Types Research Articles

Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI

The purpose of this paper is to develop Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modelling and Mapping Studies (GIMMS) Normalised Difference Vegetation Index (NDVI; AVHRR GIMMS NDVI for short) based fraction of absorbed photosynthetically active radiation (FPAR) from 1982 to 2006 and focus on their seasonal and spatial patterns analysis. The available relationship between FPAR and NDVI was used to calculate FPAR values from 1982 to 2006 and validated by Moderate-resolution Imaging Spectroradiometer (MODIS) FPAR product. Then, the seasonal dynamic patterns were analysed, as well as the driving force of climatic factors. Results showed that there was an agreement between FPAR values from this study and those of the MODIS product in seasonal dynamic, and the spatial patterns of FPAR vary with vegetation type distribution and seasonal cycles. The time series of average FPAR revealed a strong seasonal variation, regular periodic variations from January 1982 to December 2006, and opposite patterns between the Northern and Southern Hemispheres. Evergreen vegetation FPAR values were close to 0.7. A clear single-peak curve was observed between 30°N and 80°N – an area covered by deciduous vegetation. In the Southern Hemisphere, the time series fluctuations of FPAR averaged by 0.7° latitude zones were not clear compared to those in the Northern Hemisphere. A significant positive correlation (P<0.01) was observed between the seasonal variation of temperature and precipitation and FPAR over most other global meteorological sites.

Forest structure and aboveground biomass in the southwestern United States from MODIS and MISR

Red band bidirectional reflectance factor data from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) acquired over the southwestern United States were interpreted through a simple geometric–optical (GO) canopy reflectance model to provide maps of fractional crown cover (dimensionless), mean canopy height (m), and aboveground woody biomass (Mg ha − 1 ) on a 250 m grid. Model adjustment was performed after dynamic injection of a background contribution predicted via the kernel weights of a bidirectional reflectance distribution function (BRDF) model. Accuracy was assessed with respect to similar maps obtained with data from the NASA Multiangle Imaging Spectroradiometer (MISR) and to contemporaneous US Forest Service (USFS) maps based partly on Forest Inventory and Analysis (FIA) data. MODIS and MISR retrievals of forest fractional cover and mean height both showed compatibility with the USFS maps, with MODIS mean absolute errors (MAE) of 0.09 and 8.4 m respectively, compared with MISR MAE of 0.10 and 2.2 m, respectively. The respective MAE for aboveground woody biomass was ~ 10 Mg ha − 1 , the same as that from MISR, although the MODIS retrievals showed a much weaker correlation, noting that these statistics do not represent evaluation with respect to ground survey data. Good height retrieval accuracies with respect to averages from high resolution discrete return lidar data and matches between mean crown aspect ratio and mean crown radius maps and known vegetation type distributions both support the contention that the GO model results are not spurious when adjusted against MISR bidirectional reflectance factor data. These results highlight an alternative to empirical methods for the exploitation of moderate resolution remote sensing data in the mapping of woody plant canopies and assessment of woody biomass loss and recovery from disturbance in the southwestern United States and in parts of the world where similar environmental conditions prevail.

Flood mapping with remote sensing and hydrochemistry: A new method to distinguish the origin of flood water during floods

River flooding is important for the ecological functioning of river floodplains. It is implicitly assumed that in many river floodplains during floods, river water is spreading all over the floodplain. We hypothesize that during flood events a spatial distribution of water types exists, which is correlated to different water sources (river water, atmospheric water and groundwater) and to the spatial distribution of vegetation types. The objective of this paper is to assess a new methodology to determine the extent of flooding and the spatial distribution of different water sources during the flood, using GPS, multispectral remote sensing and hydrochemical analyses. This methodology is applied to the Biebrza River Lower Basin, which has little human impact. Remote sensing resulted in a map distinguishing inundated areas from dry areas, which showed 85% agreement with GPS field measurements. Principal Component Analyses and Cluster Analyses on the measured water chemistry identified different water sources during the flood (river water, groundwater, rainwater) and showed the effects of human impact on water quality. River flood water dominated the entire inundation zone in the northern Lower Basin, which is narrower and steeper than the southern Lower Basin where groundwater and rainwater were significant contributors to the major part of the inundated area. Vegetation in the river flood zone is distinctly different from the rest of the floodplain. Due to mixing of ground- and rainwater, correlation analyses between vegetation and water type were not possible outside the river flood zone. The new methodology is effective in distinguishing inundated areas from dry regions and in separating river flood water from other water sources during a flood.

A data mining approach to predictive vegetation mapping using probabilistic graphical models

This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.

Evaluation of Geostatistical Techniques for Mapping Spatial Distribution of Soil PH, Salinity and Plant Cover Affected by Environmental Factors in Southern Iran

The study presented in this paper attempts to evaluate some interpolation techniques for mapping spatial distribution of soil pH, salinity and plant cover in Hormozgan province, Iran. The relationships among environmental factors and distribution of vegetation types were also investigated. Plot sampling was applied in the study area. Landform parameters of each plot were recorded and canopy cover percentages of each species were measured while stoniness and browsing damage were estimated. Results indicated that there was a significant difference in vegetation cover for high and low slope steepness. Also, vegetation cover was greater than other cases in the mountains with calcareous lithology. In general, there were no significant relationships among vegetation cover and soil properties such as pH, EC, and texture. Other soil properties, such as soil depth and gravel percentage were significantly affected by vegetation cover. Moreover, the geostatistical results showed that kriging and cokriging methods were better than inverse distance weighting (IDW) method for prediction of the spatial distribution of soil properties. Also, the results indicated that all the concerned soil and plant parameters were better determined by means of a cokriging method. Land elevation, which was highly correlated with studied parameters, was used as an auxiliary parameter.

Evaluating the dependence of vegetation on climate in an improved dynamic global vegetation model

The capability of an improved Dynamic Global Vegetation Model (DGVM) in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land Model-DGVM (CLM3.0-DGVM) with a submodel for temperate and boreal shrubs, as well as other revisions such as the “two-leaf” scheme for photosynthesis and the definition of fractional coverage of plant functional types (PFTs). Results show that the revised model may correctly reproduce the global distribution of temperate and boreal shrubs, and improves the model performance with more realistic distribution of different vegetation types. The revised model also correctly reproduces the zonal distributions of vegetation types. In reproducing the dependence of the vegetation distribution on climate conditions, the model shows that the dominant regions for trees, grasses, shrubs, and bare soil are clearly separated by a climate index derived from mean annual precipitation and temperature, in good agreement with the CLM4 surface data. The dominant plant functional type mapping to a two dimensional parameter space of mean annual temperature and precipitation also qualitatively agrees with the results from observations and theoretical ecology studies.

Spatial and temporal variability in soil CO 2–C emissions and relation to soil temperature at King George Island, maritime Antarctica

Few studies have examined the effects of temperature on spatial and temporal trends in soil CO 2–C emissions in Antarctica. In this work, we present in situ measurements of CO 2–C emissions and assess their relation with soil temperature, using dynamic chambers. We found an exponential relation between CO 2 emissions and soil temperature, with the value of Q 10 being close to 2.1. Mean emission rates were as low as 0.026 and 0.072 g of CO 2–C m −2 h −1 for bare soil and soil covered with moss, respectively, and as high as 0.162 g of CO 2–C m −2 h −1 for soil covered with grass, Deschampsia antarctica Desv. (Poaceae). A spatial variability analysis conducted using a 60-point grid, for an area with mosses ( Sannionia uncianata) and D. antarctica, yielded a spherical semivariogram model for CO 2–C emissions with a range of 1 m. The results suggest that soil temperature is a controlling factor on temporal variations in soil CO 2–C emissions, although spatial variations appear to be more strongly related to the distribution of vegetation types.

The origin and temporal development of an ancient cultural landscape

AbstractAim To reconstruct the Late Glacial and Holocene vegetation history of western Tasmania and to test the long‐held notion of a replacement of forest by moorland during the mid to late Holocene in western Tasmania, Australia.Location Western Tasmania, Australia.Methods Fossil pollen data were screened with a modern pollen dataset using detrended correspondence analysis and charcoal data were analysed using significance tests.Results At the landscape scale, the distribution of vegetation types in western Tasmania has remained remarkably stable through the post‐glacial period. Open moorland has dominated the landscape since the Late Glacial, while rain forest expanded at that time in to areas which it occupies today. Vegetation development in the Holocene is markedly different and charcoal values are significantly higher when compared with those in previous interglacial periods.Main conclusions The dominant paradigm of a replacement of rain forest by moorland across western Tasmania during the mid to late Holocene is not supported by this regional analysis. The arrival of humans in Tasmania during the Last Glacial Stage provided an ignition source that was independent of climate, and burning by humans through the Late Glacial period deflected vegetation development and facilitated the establishment of open moorland in regions occupied by rain forest during previous interglacial periods. It is concluded that the present dominance of the landscape of western Tasmania by open moorland is the direct result of human activity during the Late Glacial and that this region represents an ancient cultural landscape.

Plant geography upon the basis of functional traits: an example from eastern North American trees

Plant geographers have sought for decades to describe and predict the geographic distribution of vegetation types on the basis of plant function and its relationship with the abiotic environment. Traditionally this has been accomplished using categorical representations such as plant functional types. Increasingly, plant functional ecologists have sought to refine categorical functional types via quantitative functional traits in order to understand the ecological implications of trade-offs in plant form and function. Fewer works have focused upon testing whether commonly measured functional traits enhance our understanding of plant biogeography broadly and the geographic distribution of vegetation types in particular. Here we combine a continental-scale forest inventory data set containing 18 111 plots with a plant functional trait data set to ask: (1) Is there a strong relationship between the abiotic environment and the distribution of functional trait values in forest inventory plots? And (2) can different Holdridge life zones be distinguished upon the basis of their functional trait distributions? The results show geographic patterns of functional trait distributions that are often strongly correlated with climate and also show that the Holdridge life zones in the study area can be differentiated using a combination of functional traits.

Study of effective ecological factors on distribution of vegetation types (Case study: Southern margin of Haj Aligholi Kavir, Damghan)

Abstract The objective of current research is to investigate distribution patterns of vegetation types and its relation with environmental factors in southern margin of Haj Aligholi Kavir of Damghan. Three vegetation types including Halecnemum strobilaceum, Sedlitzia rosmarinus and Artemisia sieberi were studied in marginal arid regions and uplands of the study area. Firstly, geographic location of vegetation types was determined using GPS. Then the boundary of the region was delineated on the topographic map in scale 1:50000. Elevation, slope and aspect of vegetation types were determined as well. Ten plots were established in the field based on randomized – systematic approach. The area of each plot was determined according to the kind of plant species and distribution of plants. Floristic list, canopy cover and average percent of species canopy cover were determined in each plot. Finally, five soil samples were taken in each vegetation type. The characteristics of soil samples including texture, EC, pH, %CaCO3, %CaSO4, %OM, SAR and ESP were measured too. ANOVA and Duncan's test were used to analyze the collected data. The result of analysis of variance showed that F test of all studied characteristics except %CaCO3, %CaSO4, %OM and elevation is significant in %1. The results of Duncan's test showed that soil texture, EC, SAR, ESP and pH of Halecnemum strobilaceum type is significantly different from two other types. Also, SAR, ESP and slope in habitat of Artemisia sieberi and Sedlitzia rosmarinus types were significantly different

Changes in predictor influence with time and with vegetation type identity in a post-abandonment situation

Abstract Variation in the explanatory potential of separate variable groups describing past vegetation patterns and/or abiotic environment were investigated using data from two points in time for three vegetation types, which are variants of the steppe grassland component of the forest steppe biome. First, we compared the predictive power of environmental variables assessed by the performance of generalised linear models (GLMs) explaining the distribution of three vegetation types in 1988 and 2002. Second, we fitted models based on conceptual hypotheses to explain vegetation distribution in 2002. Specifically, we wanted to examine, whether (i) current abiotic topo-environment, (ii) past neighbourhood configuration, or (iii) historical vegetation patterns or a combination of these determine best the current distribution of vegetation types. We developed basic predictor sets for each hypothesis, and using GLMs we tested to what degree these predictor sets were capable of explaining the currently observed patterns of individual vegetation types. We compared model accuracy by AUC and TSS values. Predictive performance of models changed both with time and with vegetation type. The analyses of changes over time showed that two of the three vegetation types had come closer to an equilibrium with abiotic conditions, while the third had moved farther away from equilibrium. Knowledge of past conditions was sufficient to predict the distribution of one of the three investigated vegetation types alone, thus no topo-environmental predictors were needed to successfully predict this type. The other two vegetation types were best explained by current topo-environmental predictors. We conclude that historical conditions clearly improve predictive models, though there may be variation in their contribution to models of different vegetation types and this may depend on how far vegetation types are from an equilibrium state.

The relationship between temporal patterns of wildfires and phytoclimatic regions in Sardinia (Italy)

As a precursor to land management and biodiversity conservation, hierarchical landscape classification and mapping has recently received renewed attention. Since climate is the main factor affecting the coarse‐scale spatial distribution of vegetation types, the first step to deal with for developing a hierarchical landscape classification is to categorize the landscape based on the climatic variables that influence the biological systems. Climate also plays an important role in characterizing wildfire regimes. Through its influence on biomass production, climate controls fuel availability. At the same time, climate affects fuel moisture, which is the main determinant for fire ignition and propagation. The influence of climate on coarse‐scale landscape classification and fire regimes invites a comparison of phytoclimatic maps to wildfire data. The main objectives of this paper are: (1) to evaluate the phenological uniqueness of the main phytoclimatic regions of Sardinia (Italy) based on five‐year data (2000–04) of SPOT‐Vegetation NDVI profiles, and (2) to evaluate to what extent the wildfire time series associated to the phytoclimatic regions of Sardinia differ in their temporal properties over the same time span.

Spatial Variability of Landscape Pattern Change Following a Ponderosa Pine Wildfire in Northeastern New Mexico, USA

Forest fires have profound impacts on the spatial distribution of vegetation type and density. This research analyzes the impacts of the 2002 Ponil Fire in New Mexico on landscape patterns using a moving-window analysis of landscape metrics. Categorically derived landscape metrics and a measure of fire severity—the Normalized Burn Ratio—are used to produce a quantitative, spatial distribution of landscape change. While gross land-cover change summaries and landscape-metric changes indicate a more heterogeneous landscape following the fire, the moving-window approach demonstrates the oversimplification of landscape-scale metrics and summaries. The moving-window approach indicates that the majority of areas in the landscape were unchanged in mean patch size, whereas mean (and median) patch size increased according to landscape-level measures. Contrary to expectations, average patch density and richness were also nearly unchanged. The moving-window approach is particularly helpful in analyzing large fires with considerable variability in severity, allowing greater insight into the relationship between fire severity and landscape composition and structure in post-fire landscapes. The moving-window approach also can guide researchers and managers to specific areas of a landscape where large changes have occurred and where evidence for understanding the process driving that change is most likely to be found.

Impacts of land-use change on hydrologic responses in the Great Lakes region

Summary Human activities have historically affected hydrology in the upper Midwestern United States, specifically through the conversion of forests and prairie grasslands to agricultural uses. The hydrologic impacts of land-use change due to settlement on the water balance of three Great Lakes states: Minnesota, Wisconsin, and Michigan were analyzed using the Variable Infiltration Capacity (VIC) large-scale hydrology model, and changes in the spatial distribution of vegetation types were studied. Point model simulations demonstrated that the VIC model simulated changes in average annual and monthly evapotranspiration (ET) and total runoff response were in the same direction and had similar magnitudes to values from other published land-use change studies. At regional scales, simulated changes resulting from land-use modifications varied spatially and seasonally, but were strongly correlated to the type of vegetation conversion and the geographic location of the land-use type centroid. Deforestation was most dramatic in the central part of the study domain where five million hectares of deciduous forest have been converted to wooded grasslands and row crop agriculture, which resulted in a 5–15% decrease in ET and a 10–30% increase in total runoff. Northern areas, where land-use change was primarily from majority evergreen to majority deciduous forest, experienced decreases of 5–10% in ET and increases of 20–40% in total runoff. The southern and western parts of the study domain were dominated by a conversion from prairie grasslands to row agriculture crop, resulting in a 10–15% increase in ET and a 20–30% decrease in total runoff.

The Melting Himalayas: Cascading Effects of Climate Change on Water, Biodiversity, and Livelihoods

The Greater Himalayas hold the largest mass of ice outside polar regions and are the source of the 10 largest rivers in Asia. Rapid reduction in the volume of Himalayan glaciers due to climate change is occurring. The cascading effects of rising temperatures and loss of ice and snow in the region are affecting, for example, water availability (amounts, seasonality), biodiversity (endemic species, predator-prey relations), ecosystem boundary shifts (tree-line movements, high-elevation ecosystem changes), and global feedbacks (monsoonal shifts, loss of soil carbon). Climate change will also have environmental and social impacts that will likely increase uncertainty in water supplies and agricultural production for human populations across Asia. A common understanding of climate change needs to be developed through regional and local-scale research so that mitigation and adaptation strategies can be identified and implemented. The challenges brought about by climate change in the Greater Himalayas can only be addressed through increased regional collaboration in scientific research and policy making.

The tree species composition and history of barrens identified by government land surveyors in southwestern Illinois1

Barrens were areas of scrub oak and prairie plants that were noted by Government Land Office (GLO) Surveys in Illinois. Surveyors described four vegetation types: prairie, barrens, scattering timber, and forest. Since settlement, these vegetation types have nearly disappeared. We used GIS and the GLO survey notes for Jersey and Greene Counties in southwestern Illinois to locate and estimate the area of barrens present at the time of the surveys. Using these estimates it was possible to determine that barrens covered about ten percent of each county. The larger barrens areas were surrounded by prairie and located in the more level eastern portions of the counties. Carya spp., Quercus marilandica, and Q. stellata were more abundant in barrens than in other vegetation types. Surveyor-designated prairies were located both on prairie soils (argiudolls) and forest soils (hapludalfs). Barrens, scattering timber, and forest were all found on forest soils and on steeper slopes than prairies. The distribution of vegetation types suggests that barrens represent an expansion of woody vegetation onto especially vulnerable prairie sites during the Little Ice Age (1450 to 1850 AD).

The spatial distribution of vegetation types in the Serengeti ecosystem: the influence of rainfall and topographic relief on vegetation patch characteristics

AbstractAim The aim of this study is to introduce a structural vegetation map of the Serengeti ecosystem and, based on the map, to test the relative influences of landscape factors on the spatial heterogeneity of vegetation in the ecosystem.Location This study was conducted in the Serengeti–Maasai Mara ecosystem in northern Tanzania and southern Kenya, between 34° and 36° E longitude, and 1° and 2° S latitude.Methods The vegetation map was produced from satellite imagery using data from over 800 ground‐truthing points. Spatial characteristics of the vegetation were analysed in the resulting map using the fragstats software package. Average patch area and nearest neighbour distance (NND) were determined for grassland, shrubland and woodland vegetation types. The heterogeneity of vegetation types was estimated with Simpson’s diversity index (D). Structural equation modelling (SEM) was used to explore the relationships between the spatial characteristics of vegetation and three predictor variables: annual rainfall, coefficient of variation (CV) in annual rainfall, and topographic moisture index (TMI).Results A vegetation map is presented along with a detailed summary of the distribution of land‐cover classes and spatial heterogeneity in the ecosystem. Significant relationships were found between vegetation diversity (D) and TMI, and also between D and average rainfall. The average area of grassland patches showed significant relationships with average rainfall, with rainfall CV and with TMI. Grassland NND was positively associated with average rainfall. Woodland patch area showed a unimodal response to average rainfall and a negative linear association with TMI. Woodland NND showed a U‐shaped association with annual rainfall and a weaker positive linear association with TMI. An acceptable model that explained variation in shrubland patch characteristics could not be identified.Main conclusions The vegetation map and analysis thereof resulted in three significant causal explanatory models that demonstrate that both rainfall and topography are important contributors to the distribution of woodlands and grasslands in the Serengeti. These findings further indicate that changes in patch characteristics have a complex interaction with rainfall and with topography. Our results are concordant with recent studies suggesting that percent woody cover in African savannas receiving less than c. 650 mm year−1 is bounded by average annual rainfall.

Effects of deglaciation on circumpolar distribution of arctic vegetation

An understanding of the factors controlling the distribution of arctic vegetation will allow better prediction of the effects of climate change. This study examines the effect of the age of landscapes on the distribution of arctic vegetation. We compared time since deglaciation with the distribution of vegetation types and Advanced Very High Resolution Radiometer (AVHRR) satellite measures of greenness (normalized difference vegetation index, NDVI). Most of the older arctic landscapes occur between the Taimyr Peninsula in Russia and the Mackenzie River in Canada. The vegetation types most commonly associated with the oldest landscapes include tussock-sedge, dwarf-shrub, moss-tundra, and sedge-shrub wetlands. Most of the Arctic, including most bioclimate subzones and most vegetation types, showed increasing NDVI with increasing landscape age. Landscapes showed rapid increases in NDVI during the first several thousand years after deglaciation. Relatively low NDVI values occurred on landscapes 5000 – 15 000 years old, as on the Canadian Shield. Higher NDVI values occurred on landscapes older than 20 000 years. Landscape age accounted for 34% of the variation in NDVI for landscapes younger than 900 000 years. The coldest parts of the Arctic (subzone A) and vegetation types that grow primarily in these areas did not show any trend with landscape age.

Environmental factors controlling the vegetation zonation patterns and distribution of vegetation types in the Olifants Estuary, South Africa

The Olifants Estuary is one of only three permanently open estuaries on the West Coast and is ranked third in terms of conservation importance of all estuaries in South Africa. It has the largest supratidal (143 ha) and floodplain (797.1 ha) salt marshes in the country. Intertidal salt marsh covers 91.94 ha, reeds and sedges 60.05 ha and the submerged macrophyte Zostera capensis 47.72 ha. Correspondence analysis revealed intertidal, supratidal, floodplain and terrestrial plant community types within the studied estuary. The species composition of these communities was the same for the lower, middle and upper reaches of the Olifants Estuary, with the exception of the supratidal community type in the upper reaches that consisted of halophytes with a lower salinity tolerance range rather than the typical dense monospecific stands of Sarcocornia pillansii. The environmental variables that had the greatest influence on the distribution of the dominant salt marsh species, S. pillansii, included soil moisture, distance from the estuary, elevation above mean sea level, and depth to the water table. The most important ecological driver for salt marsh vegetation, especially along the arid West Coast of southern Africa, is moisture. The low rainfall and irregular occurrence of advection sea fog increases the importance of a shallow (< 1.5 m) saline (< 35 psu) water table in the floodplain as a source of moisture during dry periods.

Analysis of soil and vegetation patterns in semi-arid Mediterranean landscapes by way of a conceptual water balance model

Abstract. This paper investigates the impact of various vegetation types on water balance variability in semi-arid Mediterranean landscapes, and the different strategies they may have developed to succeed in such water-limited environments. The existence of preferential associations between soil water holding capacity and vegetation species is assessed through an extensive soil geo-database focused on a study region in Southern Italy. Water balance constraints that dominate the organization of landscapes are investigated by a conceptual bucket approach. The temporal water balance dynamics are modelled, with vegetation water use efficiency being parameterized through the use of empirically obtained crop coefficients as surrogates of vegetation behavior in various developmental stages. Sensitivity analyses with respect to the root zone depth and soil water holding capacity are carried out with the aim of explaining the existence of preferential soil-vegetation associations and, hence, the spatial distribution of vegetation types within the study region. Based on these sensitivity analyses the degrees of suitability and adaptability of each vegetation type to parts of the study region are explored with respect of the soil water holding capacity, and the model results were found consistent with the observed affinity patterns.