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Friday, September 14, 2007


Cheryl A Palm, Pedro Sanchez, Sonya Ahmed and Alex Awiti

In general the increased provisioning of food, fuel and fiber realized over the last four decades [3] has resulted in the degradation of soils and several supporting and regulatory services provided by soils [3]. This decline in soil properties and regulating ecosystem services will ultimately impact the ecosystem provisioning services. Understanding the factors that affect the stability and resilience of soils upon disturbance is one of the frontiers of soil science [77].

Soil degradation can be defined as the adverse changes in soil properties and processes leading to a reduction in ecosystem services. Through such changes in soil properties and processes, soil degradation undermines the sustainability of many of the ecosystem services. There are innumerable studies on soil degradation, such as loss of soil organic matter, increased erosion, and nutrient depletion [78] but there are relatively few studies that have quantified the linkages and thresholds between the change in soil properties and the associated change in soil processes. In other words, how much change in soil aggregation is required before there is a change in soil porosity and water infiltration? What level of soil organic matter, relative to the initial condition, is needed to maintain soil aggregation at sufficient levels? The studies rarely provide quantitative assessments on the impacts of soil degradation on the provisioning ecosystem services of soils. The connection to and impacts of soil degradation on the regulating services of soil have only recently begun to be considered [3, 39]. Until such quantitative links are made between the magnitude of changes in soil properties, to the magnitude of change in soil processes, and ultimately integrated to ecosystem processes it will be difficult to assess or redress soil degradation in a meaningful way.

Types and process of soil degradation

Globally, the five principal anthropogenic causes of soil degradation in order of magnitude are considered to be overgrazing, deforestation, poor land management, harvest of fuelwood, and urbanization [79]. Soil degradation almost invariably begins with the removal of the natural vegetative cover through deforestation, biomass burning, nutrient depletion and overgrazing. The soil surface is exposed to impacts of rainfall that disrupts soil aggregates, and higher temperatures that increase SOM decomposition rates; in addition, litterfall and roots, the major sources of organic inputs that maintain SOM are removed or diminished considerably. Subsequent rates and types of soil degradation are determined by the type and intensity of land use. Soil degradation can occur quickly depending on the combination and feedbacks between management practices, initial soil conditions, vegetation, and environmental factors such as climate [80-82] Soil degradation is usually categorized by physical, chemical and biological processes; the division provides a means of establishing links between land management, degradation processes, and soil processes (Table 6).

Soil physical degradation

Physical degradation involves the structural breakdown of the soil through aggregate disruption, surface sealing, and compaction – these degradation processes result in reduced infiltration and increased water runoff and soil erosion.

The impact of raindrops leads to surface sealing and compaction. The formation of a structural seal results from two complementary mechanisms: (i) physical disintegration of surface aggregates caused by wetting raindrop impact energy; and (ii) physicochemical dispersion of clay particles which migrate into soil with infiltrating water, and clog the pore immediately beneath the surface forming a zone of decreased porosity [83]. Soils with intermediate (loamy) clay content (200 g kg-1) are the most susceptible to seal formation because the amount of clay is too low to stabilize aggregates but sufficient to clog pores at the surface. Cultivation further affects soil structure by destroying soil aggregates that result in loss of SOM [28, 84].

Soil erosion is often highlighted as the major type of soil degradation, it is also the most visible. The impacts of soil erosion ramify throughout the soil processes and ecosystem services by the loss of soil depth, soil nutrients, biota, organic matter, and water resources; these integrated changes translate into reduced primary productivity potential of ecosystems. The extent of soil erosion are usually estimated from experimental Wischmeier erosion plots [85]; this methodology overestimates erosion losses due to the small size of these plots and do not account for redistribution of soil in the same field, which result in no net losses at the field scale [86]. These point measurements have been extrapolated to different soils, climates, and landscapes to give estimates of global soil erosion. Erosion risk does not automatically imply productivity losses or land degradation, something that is often assumed. There are however landscape level models that estimate erosion in an integrated manner taking into account climate, soil properties, and topography and are being used to look at impacts on other ecosystem services [87].

Physical degradation processes other than erosion were found to be more common in temperate region agriculture because of more intensive use of heavy machinery [88]. Unfortunately none of these estimates were related to changes in agroecosystem productivity.

Soil chemical degradation

Soil chemical degradation processes are associated with soil chemical imbalances due to chemical reaction or pH, declines in availability of plant nutrients (nutrient depletion) and excessive build up of nutrients (eutrophication), salts (salinization in the root zone and beyond), or toxic materials.

Nutrient depletion, or soil fertility decline, is the predominant form of chemical degradation in much of the tropics, particularly Africa, where nutrient losses through crop residue removal and harvested products, erosion and leaching are not replaced with sufficient external inputs [89]. Nutrient depletion results in lower productivity of crops and biomass in general that lead to further declines of soil organic matter. Soils with low initial nutrient capital, low cation exchange, capacity, low activity variable charge clays, and low soil organic matter become depleted more quickly than soils without these properties and include Ultisols, Oxisols, and sandy Inceptisols. There is a growing body of literature that will be useful in making the links between nutrient depletion and reduction in plant productivity as has been done for soil erosion and declines in productivity [90]. Soil eutrophication on the other hand is a degradation process that is found primarily in developed countries in temperate regions where excessive amounts of fertilizer, manures,(and pesticides) are applied in large scale agriculture [91].

Soil biological degradation

Many key soil functions are underpinned by soil organic matter and soil biota so biological degradation is often synonymous with decline in soil organic matter and loss of soil biota. The depletion of soil organic matter when natural systems are converted to agriculture and the intensification of agriculture with tillage is the most comprehensively studied form of biological degradation [8, 26, 32, 92-99].

Rates of changes in soil organic matter content and the level of change depends in part on the soil type (slower in clayey soils), land use type, and climate (slower in colder or drier climates and water logged condtions) among other factors. The body of literature on soil carbon changes when natural systems are converted to annual croplands is extensive and sufficient to provide the pedotransfer functions needed for relating loss of soil properties to many ecosystem processes [22, 97]. Information on changes following other land use transitions, including natural systems to pastures or tree plantations or annual cropping systems to pastures or tree based systems, or even changes in management of annual cropping systems is more recent. A meta analysis of soil carbon changes with land use change in both temperate and tropical soils shows decline of soil carbon by 50% in the top 30 cm when forests were converted to cropland; a decline of 15% when forests were converted to coniferous plantations, no decline when forest were converted to broadleaf plantations; and an overall increase of about 10% when forests were converted to pastures [99].

Assessment of soil degradation

There are three significant assessments of the global extent of land degradation: the Global Assessment of Human Induced Soil Degradation (GLASOD) map of 1991, research work [100], and more recent assessments [101]. GLASOD is the most comprehensive and widely quoted assessment. Though the initial framework set up for GLASOD was sound and based on scientific information, due to time and resource constraints, the final methodology and assessment was based on expert opinion from 250 soil and environmental scientists. The quality of the GLASOD data is extremely uneven [102] and the estimates indicative at best [103]. Furthermore, dating from 1991, the estimate of total land area affected by soil degradation at 2 billion hectares is now out of date. This dataset should no longer be used for quantifying the extent of soil degradation and just like the FAO-Unesco soil map of the world there is a need for up-to-date and accurate information on soil degradation and global soil information.

One assessment was based on anecdotal accounts, research reports, travelers’ descriptions, personal opinions, and local experience [100]. The most recent assessment [101] has the benefit of combining multiple sources of information including regional data sets derived from literature review, erosion models, field assessments, and remote sensing. However, it did not have complete spatial coverage and was limited to 62% of drylands, with some areas relying on a single data set.

These assessments of land degradation all have major weaknesses. Literature on soil degradation assessments are replete with gross extrapolations based on limited data, often outside the regions from which the data were obtained [86]. These data cannot be used for baseline development, assessment and monitoring of soil degradation, and are unsuitable for land use planning and identification of conservation/restoration policies [102]. A major indictment of the GLASOD land degradation assessment was delivered by its exclusion from the Pilot 2006 Environmental Performance Index for the reasons that the data are outdated and not comparable enough to permit cross-country performance assessments [104].

Conventional methods of soil assessment rely on direct laboratory measurements that are time consuming and costly. Temporal and spatial variability in soil attributes presents formidable challenges for soil survey design. There is a global surge towards developing time-and cost-efficient techniques for soil evaluation [105, 106]. This demand is driven by the need for large amounts of good quality, inexpensive soil data for use in monitoring, modeling, precision agriculture and risk assessment [107, 108].

The inherent methodological weaknesses can only be removed using a combination of in situ data on soil parameters at the “pedon” or “soilscape” and satellite information at multiple resolutions [76, 109, 110]. Current advances in pedotransfer functions (PTF), reflectance spectroscopy, statistical inference, and remote sensing can overcome the great limitations of conventional methods of soil analysis. PTF research has focused on the development of functions for predicting soil physical and chemical properties for different geographical areas or soil types. Soil inference systems (SINFERS) have been developed [76] where pedotransfer functions are the knowledge rules for inference engines. A soil inference system takes measurements that are more-or-less known with a given level of (un)certainty, and infers data that is unknown with minimal inaccuracy, by means of properly and logically linked pedotransfer functions [111, 112]. Near infrared spectroscopy is rapid, inexpensive and single spectrum permits simultaneous characterization of various chemical, physical and biological properties [113-119]. In addition the repeatability over time and reproducibility among different laboratories of this technique far exceeds the performance of conventional soil analysis. Soil properties predicted from spectra may be used in an inference system to predict other important and functional soil properties using PTFs].

Research has demonstrated that regional patterns of soil degradation can be reliably mapped using automated or supervised digital information extraction, based on spectral and/or structural pattern recognition techniques. Extrapolation of this approach to other regions where soil degradation features are correlated with spectrally distinguishable surface characteristics is feasible. For instance, the state of land degradation in a small Mediterranean watershed was characterized using (Advanced Spaceborne Thermal Emission and Reflection radiometer) ASTER data and ground-based spectral reflectance measurements [120].

A combination of pedotransfer functions, reflectance spectroscopy, statistical inference, and remote sensing offer the best opportunity for developing dynamic digital soil maps that would include the types and extent of soil degradation, transforming the way soil information is obtained and produced.

The challenges of halting and reversing the degradation of the provisioning, regulating, and supporting ecosystems services on which will all depend are daunting. The challenge must be met if we are to attain the Millennium Development Goals and particularly to provide an environment that can continue providing these services into the future. Many of these ecosystem services are dependent of soils and therefore the reversal of ecosystem degradation starts with the rehabilitation of soils. Our understanding of the links between specific soil properties, soil processes, and ecosystem services is incomplete to meet this challenge. Renewed and directed efforts and partnerships among reductionist soil science that links soil properties to processes; ecosystem ecologists that link soil processes to ecosystem services; and landscape ecologists and agronomists that put these processes into a broader and relevant context for planning and management decisions are the way forward.

Soil Condition Classification using Infrared Spectroscopy: A Proposition for Assessment of Soil Condition along a Tropical Forest-Cropland Chronosequence

Alex O. Awiti, Markus G. Walsh, Keith D. Shepherd and Jensio Kinyamario


Soil fertility depletion in smallholder agricultural systems in sub-Saharan Africa presents a formidable challenge both for food production and environmental sustainability. A critical constraint to managing soils in sub-Saharan Africa is poor targeting of soil management interventions. This is partly due to lack of diagnostic tools for screening soil condition that would lead to a robust and repeatable spatially explicit case definition of poor soil condition. The objectives of this study were to: (i) evaluate the ability of near infrared spectroscopy to detect changes in soil properties across a forest-cropland chronosequence; and (ii) develop a heuristic scheme for the application of infrared spectroscopy as a tool for case definition and diagnostic screening of soil condition for agricultural and environmental management. Soil reflectance was measured for 582 topsoil samples collected from forest-cropland chronosequence age classes namely; forest, recently converted, RC (17 years) and historically converted, HC (ca.70 years). 130 randomly selected samples were used to calibrate soil properties to soil reflectance using partial least-squares regression (PLSR). 64 randomly selected samples were withheld for validation. A proportional odds logistic model was applied to chronosequence age classes and 10 principal components of spectral reflectance to determine three soil condition classes namely; “good”, “average” and “poor” for 194 samples. Discriminant analysis was applied to classify the remaining 388 “unknown” samples into soil condition classes using the 194 samples as a training set. Validation r2 values were: total C, 0.91; total N, 0.90; effective cation exchange capacity (ECEC), 0.90; exchangeable Ca, 0.85; clay content, 0.77; silt content, 0.77 exchangeable Mg, 0.76; soil pH, 0.72; and K, 0.64. A spectral based definition of “good”, “average” and “poor” soil condition classes provided a basis for an explicitly quantitative case definition of poor or degraded soils. Estimates of probabilities of membership of a sample in a spectral soil condition class presents an approach for probabilistic risk-based assessments of soil condition over large spatial scales. The study concludes that reflectance spectroscopy is rapid and offers the possibility for major efficiency and cost saving, permitting spectral case definition to define poor or degraded soils, leading to better targeting of management interventions.

Keywords: Infrared spectroscopy; Tropical rainforest; Chronosequence; Soil condition class; Case definition; Probabilistic risk-based assessment


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