Browsing by Subject "Bodenfruchtbarkeit"

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    Fertility and microbial functioning of soils of smallholder farming systems under contrasting tropical agro-ecologies
    (2021) Balume, Isaac; Rasche, Frank
    Soil fertility in tropical agroecosystems is often subjected to degradation that leads to nutrient depletion with negative effects on land productivity and food security. This challenge is aggravated by the complexity of socio-economic (market distance, farm typology) and biophysical (agro-ecology, site) conditions causing soil fertility variability. Consequently, blanket fertilizer recommendations cannot be applied in areas of high fertility variability. In this PhD study, methods were harmonized to assess drivers of soil fertility status across regions. Despite being pointed as factors contributing to soil fertility variability, market access, farm typology (resource endowment) and agro-ecology have not been subjected to soil fertility assessment. This PhD study aimed mainly at verifying that these factors have to integrated rather than considered in isolation to enable accurate assessments of soil fertility across spatial scales and socio-economic gradients. It was hypothesized that market distance and farm typology is a determinant of agricultural development in Democratic Republic of Congo (DRC). As market distance is increasing, the soil fertility status of smallholder farming systems decreases despite farmers’ wealth. In a parallel study conducted in Ethiopia, it was complementarily hypothesized that the soil fertility status is also influenced by inter-related effects of agro-ecology and farm typology. As nitrogen (N) is known to be limiting in smallholder farms, conservation and sustainable provision of this nutrient will be essential to achieve niche-based integrated soil fertility management (ISFM) strategies. Therefore, understanding of the ecological processes (proteolysis, nitrification) that control soil N availability through organic residue management in varying soil fertility variability conditions will be essential. Low concentrations of lignin (L) and polyphenols (PP) relative to N have been acknowledged to facilitate decomposition, hence, stimulate the abundance of proteolytic and nitrifying soil microbial communities. Therefore, it was hypothesized that high quality (low (L+PP)/N)) residue applied to high pH soils have a positive relationship between the functional potential of proteolytic enzymatic activities and abundance of nitrifying communities. The survey studies in DRC and Ethiopia were guided by the following objectives; 1) To determine the inter-related influence of market distance and farm typology on soil fertility status of smallholder farming systems of South-Kivu, Eastern DRC. 2) To assess the inter-related effects of agro-ecology and farm typology on soil fertility status across crop-livestock systems in Western and Central Ethiopia. Moreover, to better understand the ecological processes (proteolysis, nitrification) that control N through organic residue management in varying soil fertility variability conditions, an incubation study was performed to meet objective 3) To verify that potential proteolytic enzyme activities modulate archaeal and bacterial nitrifier abundance in soils with differing acidity and organic residue treatment. Results from the soil survey study in DRC revealed a decreasing soil fertility with increasing market distance across all farm typologies. A significant influence of farm typology was found for exchangeable calcium and magnesium, while factor site resulted in a significant difference of plant available phosphorus. Furthermore, factor “site” interacted with market distance for soil organic carbon (SOC) quality indexes. In addition, the interaction of market distance and typology became obvious in the medium wealthy and poor farms. Market distance effects were associated with walking distance, while site effects were attributed to factors such as soil type and climatic conditions. In Ethiopia, inter-related effect of agro-ecology and farm typology was found. Higher total carbon and total nitrogen was found in wealthy farmers’ field compared to poor farmers’ field in the highlands. As an indication of soil quality, lowest SOC stability indexes were revealed in soils of wealthy compared to that from poor farm typology. These differences in soil fertility were attributed to farm management practices among typology classes and agro-ecological zone distinctions. The result from the incubation study revealed a significant relationship of proteolytic enzyme activities with the abundance of ammonia oxidizing bacteria and archaea, even though the extent of this relationship was more dependent on soil pH and incubation time, but not residue quality. This suggests that the effect of soil pH is stronger than that of residue quality on enzyme activity and nitrifiers community, reflecting the importance of soil physico-chemical conditions rather than management practices. The incubation study further showed that nitrifying prokaryotes benefitted from the release of N spurred by proteolysis, and indicated a niche specialization between ammonia oxidizing bacteria and archaea depending on soil acidity and resource availability. Overall, this PhD study showed that market access, typology and agro-ecology were important drivers of soil fertility variability in the study regions of DRC and Ethiopia. However, factor site played a significant role in shaping soil fertility variability, implying that site-specific recommendations could be a way forward for designing soil fertility management in smallholder farmers. It was inferred that prospective niche-based ISFM strategies must consider such contrasting but interrelated factors including, but not limited to agro-ecology, farm typology and market access. This would reduce the effect of soil fertility variability across regions. This PhD study only considered land size (DRC, Ethiopia), livestock and mineral fertilizers (Ethiopia) as key features to define the wealth status of targeted farms; future studies should consider a wider range of socio-economic and biophysical factors including labor availability, off-farm household income and soil management history for more accuracy of soil fertility variability. This will strengthen the accuracy of prospective soil fertility assessments across socio-economic gradients and spatial scales. Finally, it is suggested to extend the results from the incubation study to field conditions considering soils with a broader soil acidity range and organic residues with more distinct biochemical quality. This will verify the given assumptions about the functional relationships between proteolytic and nitrifying soil communities. Overall, the presented PhD study has contributed to ongoing research on best-fit soil fertility recommendations and knowledge gaps about soil ecological functioning, by providing an advanced understanding of driving factors of soil fertility variability and soil microbial functioning in smallholder farms in tropical environments.
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    Impact of environmental and socio-economic factors on soil fertility variability and microbial carbon use efficiency in tropical smallholder farming systems
    (2022) Agumas Endalew, Birhanu; Rasche, Frank
    Die Hauptfaktoren für die Variabilität der Bodenfruchtbarkeit in Subsahara-Afrika (SAA) müssen verstanden werden, um maßgeschneiderte Strategien für ein integriertes Bodenfruchtbarkeitsmanagement (ISFM) zu entwickeln, die die agro-ökologischen Zonen, die Ressourcenausstattung der Kleinbauern und ihr indigenes Wissen über die Bodenfruchtbarkeit berücksichtigen. Darüber hinaus mangelt es den meisten Bodenfruchtbarkeitsindikatoren, einschließlich, aber nicht beschränkt auf den Gesamtgehalt an organischem Kohlenstoff (SOC) im Boden, an Empfindlichkeit und Genauigkeit. Die Unempfindlichkeit und Ungenauigkeit dieser Indikatoren erschwert ihre Anwendung für die Erfassung der Bodenfruchtbarkeit in kleinbäuerlichen Systemen auf größeren räumlichen Skalen. Daher ist die Überprüfung neuartiger Bodenfruchtbarkeitsindikatoren, wie z.B. funktionelle SOC-Gruppen und mikrobielle Kohlenstoffnutzungseffizienz (CUE), die von Umweltfaktoren (z.B. pH-Wert des Bodens, Qualität des organischen Inputs) beeinflusst werden, von größter Bedeutung, um diese Einschränkung zu überwinden. Die Umsetzung einer solchen methodischen Innovation würde helfen, das Ausmaß der regionalen Bodenfruchtbarkeitsvariabilität besser zu verstehen und anschließend nischenbasierte ISFM-Strategien für kleinbäuerliche Anbausysteme in SSA zu entwickeln. Daher war das erste Ziel dieser Studie, die wechselseitigen Auswirkungen biophysikalischer und sozioökonomischer Faktoren auf die Variabilität der Bodenfruchtbarkeit zu untersuchen, wie sie sich in den Nährstoffgehalten des Bodens sowie im SOC-Gehalt und den Qualitätsparametern (d.h. den SOC-Funktionsgruppen) widerspiegelt. Das zweite Ziel war die Bewertung des CUE als zusätzlicher Proxy zur Beurteilung der Bodenfruchtbarkeit unter Berücksichtigung des Einflusses von Umwelt- und methodischen Variationen auf die CUE-Berechnung. Die spezifischen Ziele dieser PhD-Studie waren,: - zu verifizieren, dass die Variabilität der Bodenfruchtbarkeit in zwei Modellregionen in Zentral- und West-Äthiopien mit vier unterschiedlichen agro-ökologischen Zonen durch die miteinander verbundenen Effekte der Agrarökologie und der Ressourcenausstattung der Landwirte ("reiche" versus "arme" Landwirte) bestimmt werden kann. - diesen Ansatz der lokalen Bewertung der Bodenfruchtbarkeit in Äthiopien zu bestätigen, indem die "Marktdistanz" als zusätzlicher Faktor für die Variabilität der Bodenfruchtbarkeit einbezogen wird, wie es in der Demokratischen Republik Kongo (DRC) vorgemacht wurde. - zu testen, ob das indigene Wissen der Landwirte über den Zustand der Bodenfruchtbarkeit durch interdependente Effekte der Agrarökologie, der Marktdistanz und der Betriebstypologie bestimmt wird, unter Berücksichtigung des kontinuierlichen Wissenstransfers zwischen den Landwirten innerhalb und zwischen den agro-ökologischen Zonen. - das Potenzial der funktionellen SOC-Gruppen und des mikrobiellen CUE im Boden als vielversprechende Indikatoren für den Zustand der Bodenfruchtbarkeit zu bewerten, die von den physikalisch-chemischen Bodeneigenschaften und dem Management organischer Inputs beeinflusst werden. - die bestehende Single-C-Cycling-Enzym-Stöchiometrie (SCE-STM) zu modifizieren, indem neuartige "Multi"-C-Cycling-Enzym-Stöchiometrie (MCE-STM) Methoden zur CUE-Abschätzung vorgeschlagen werden. Um die Ziele 1-3 der vorgestellten PhD-Studie anzugehen, wurden zwei lokale feldbasierte Bodenfruchtbarkeitsuntersuchungen in Äthiopien und der DRC durchgeführt. Für die Ziele 4 und 5 wurde eine laborbasierte Inkubationsstudie durchgeführt. Für die Erhebungen der Bodenfruchtbarkeit wurden die Mid-Infrarot-Spektroskopie gekoppelt mit der Partial Least Squares Regression (midDRIFTS-PLSR) und Nasslaboranalysen verwendet, um die Bodenfruchtbarkeit (d.h. pH-Wert des Bodens, Gesamtkohlenstoff (TC), Gesamtstickstoff (TN), pflanzenverfügbarer Phosphor (Pav) und Kalium (Kav), austauschbares Kalzium (Caex) und Magnesium (Mgex)) in vier agro-ökologischen Zonen in Äthiopien zu bewerten. Die MidDRIFTS-Peakflächenanalyse der Spektralfrequenzen (2930 (aliphatische C-H), 1620 (aromatische C=C), 1159 (C-O polyalkoholische und Ether-Gruppen) cm-1) wurde zur Charakterisierung der SOC-Qualität und zur Berechnung des SOC-Stabilitätsindex angewendet. In der DRC wurden beide Techniken eingesetzt, um die Bodenfruchtbarkeit über Marktentfernungen (definiert als Gehzeit) in verschiedenen Regionen zu bewerten. Für die laborbasierte Inkubationsstudie (60 Tage) wurden zwei Böden, die sich hauptsächlich im Säuregrad unterscheiden, mit zwei Proben von Pflanzenresten gemischt, die sich im Lignin- (L) und Polyphenolgehalt (PP) unterscheiden. Zur Abschätzung der mikrobiellen CUE im Boden während des Abbaus von Pflanzenresten in den verschiedenen Böden wurden die Methoden der Single-C-Cycling-Enzym-Stöchiometrie (SCE-STM) und der neu vorgeschlagenen "Multi"-C-Cycling-Enzym-Stöchiometrie (MCE-STM) gegenüber der herkömmlichen C-Bilanz-Methode validiert. Die Ergebnisse der MidDRIFTS-PLSR- und Peak-Flächen-Analyse der äthiopischen Fallstudie zeigten, dass die miteinander verbundenen Effekte der Agrarökologie und der Ressourcenausstattung der Landwirte die beobachtete Variabilität der Bodenfruchtbarkeit in vier agroökologischen Zonen bestimmten. Von der Ressourcenausstattung abhängige Optionen des Bodenfruchtbarkeitsmanagements zeigten eine höhere TZ in der hochgelegenen agroökologischen Zone, während in den niedrigeren agroökologischen Zonen auf den Feldern der wohlhabenden Landwirte eine höhere TN und Kav gefunden wurde. In ähnlicher Weise wurde eine höhere SOC-Qualität in den Böden von wohlhabenden als von armen Betrieben in den höher gelegenen Zonen gefunden. Somit trugen agro-ökologische Zonenunterschiede zu diesen Unterschieden in der Variabilität der Bodenfruchtbarkeit bei. Es wurde abgeleitet, dass dieser Unterschied im Bodenfruchtbarkeitsstatus zwischen den Feldern wohlhabender und armer Landwirte in den verschiedenen agro-ökologischen Zonen auf die hohe Variabilität in der Pro-Kopf-Größe des Landbesitzes, des Viehbestandes und der Menge des pro Flächeneinheit verwendeten Düngers zurückzuführen ist. So legen wohlhabende Landwirte im Tiefland ihr Land brach und bringen organische Reststoffe aus, während die Landwirte im Hochland den Einsatz von chemischen Düngemitteln und Hofdünger in größerem Umfang in Betracht ziehen. Ergänzend zeigten die Ergebnisse der DRC-Fallstudie, dass die "Marktdistanz" und die "Betriebstypologie" wichtige Determinanten für die Variabilität der Bodenfruchtbarkeit sind, beide mit gegensätzlichen Trends in den Untersuchungsgebieten. Ein abnehmender Bodenfruchtbarkeitsstatus wurde bei allen Betriebstypologien mit zunehmender Marktentfernung festgestellt. Ein signifikanter Einfluss der "Betriebstypologie" wurde für Caex und Mgex gefunden, während der Faktor "Standort" zu einem signifikanten Unterschied von Pav führte. Für die SOC-Qualitätsindizes (d.h. das Verhältnis 1530:2930) war der Faktor "Standort" entscheidend, was sich in seiner Interaktion mit der "Marktdistanz" widerspiegelte. Der Effekt der Marktdistanz wurde jedoch auf den Feldern der mittelreichen und armen Landwirte deutlich, wo ein steigender SOC-Qualitätsindex von 1530:2930 mit zunehmender Marktdistanz eine geringere SOC-Qualität in den abgelegenen Betrieben implizierte. Bodentiefe und Bodenfarbe waren die von den Landwirten am häufigsten verwendeten Indikatoren für die Bodenfruchtbarkeit, unabhängig von der Agrarökologie, der Marktentfernung und der Betriebstypologie. Was das indigene Wissen der Landwirte in den Untersuchungsregionen in Äthiopien und der Demokratischen Republik Kongo betrifft, wurden fruchtbare und weniger fruchtbare Felder visuell durch die Bodenfarbe unterschieden. In den meisten agro-ökologischen Zonen der äthiopischen Fallstudie wurden höhere pH-Werte und Pav-Werte in fruchtbaren (braun/schwarz) als in weniger fruchtbaren (rot) Böden gefunden. Außerdem wurden höhere Peakflächen von 1159 cm-1 und SOC-Stabilitätsindizes in weniger fruchtbaren im Vergleich zu fruchtbaren Böden in Äthiopien beobachtet. In enger Übereinstimmung mit dem einheimischen Wissen der Landwirte in der DRC-Studienregion war die Bodenfruchtbarkeit in tiefen Böden höher als in flachen Böden, was sich in höheren Nährstoffvorräten in tiefen Böden widerspiegelte, die organische Ergänzungen erhielten. Dementsprechend sind standortspezifische Bodenbewirtschaftungsstrategien mit der Integration des indigenen Wissens der Landwirte eine machbare Option, um die geringe Akzeptanz von ISFM zu überwinden. Diese PhD-Studie schlug vor, empfindlichere Indikatoren, wie z.B. den mikrobiellen CUE-Wert des Bodens, zu verwenden, um den Zustand der Bodenfruchtbarkeit genau zu beurteilen und Entscheidungen für ein nischenbasiertes Bodenfruchtbarkeitsmanagement zu treffen. Darüber hinaus zeigte die PhD-Studie, dass in fruchtbareren und weniger sauren (pH 5,1) Böden, die mit Rückständen höherer Qualität ergänzt wurden, ein höherer CUE-Wert gemessen wurde als in den anderen drei Kombinationen. Daraus wurde gefolgert, dass die Mikroorganismen mehr Energie zur Unterstützung des Wachstums in saureren (pH 4,3) Böden investierten, um die Bodensäure zu tolerieren, was wiederum die N-akquirierenden enzymatischen Aktivitäten unterdrückte und den CUE weiter reduzierte. Niedrigere CUE-Werte wurden von der Multi-C-Cycling-Enzym-Stöchiometrie-Modellierung (MCE-STM) im Vergleich zu den CUE-Werten aufgezeichnet, die von den C-Balance- und Single-C-Cycling-Enzym-Stöchiometrie-Modellierungsmethoden (SCE-STM) erhalten wurden. Die in dieser Dissertationsarbeit vorgeschlagene Modifikation der MCE-STM-Methode zur CUE-Bestimmung war in der Lage, den kombinierten Effekt von Boden-pH und Pflanzenrückstandsqualität auf die Effizienz des mikrobiellen Stoffwechsels zu quantifizieren. Dadurch verbesserte sie den ursprünglichen stöchiometrischen Modellierungsansatz (SCE-STM), der sich nur auf das Konzept der Nährstoffverfügbarkeit stützte. Zusammenfassend lässt sich sagen, dass sich die midDRIFTS-PLSR-Vorhersagen zusammen mit den midDRIFTS-Peaks, die die funktionalen SOC-Gruppen repräsentieren, für die regionale Bewertung der Bodenfruchtbarkeit als sensibler sowie effizienter und robuster Ansatz erwiesen haben, verglichen mit den bestehenden Ansätzen, die sich auf klassische Bodeneigenschaften (z. B. den SOC-Gehalt) stützen, die durch Nasslaboranalysen ermittelt werden. Basierend auf den mit midDRIFTS generierten Daten wurden die Haupttreiber für die Variabilität der Bodenfruchtbarkeit aufgedeckt, wobei insbesondere die zusammenhängenden Effekte von Agrarökologie, Ressourcenausstattung, Marktdistanz und indigenem Wissen der Landwirte berücksichtigt wurden. Darüber hinaus liefert die Integration der mikrobiellen CUE (z.B. MCE-STM) in die Bewertung der Bodenfruchtbarkeit nicht nur ein klareres Bild des Zustands der Bodenfruchtbarkeit. Sie dient auch dem besseren Verständnis ökologischer Prozesse in Böden im Allgemeinen. Damit förderte diese Doktorandenstudie das Wissen über Bodenfruchtbarkeitstreiber über räumliche Skalen hinweg und legte die wissenschaftliche Basis für die Förderung neuartiger Bodenfruchtbarkeitsindikatoren, die auf mikrobiellen CUE im Boden basieren. Dieses Ergebnis wird der Entwicklung von Nischen-basierten Bodenfruchtbarkeits-Management-Strategien zugute kommen, die von größter Bedeutung für die Sicherung der Lebensgrundlage von kleinbäuerlichen Systemen in SSA sind.
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    Land use change and its impact on soil properties using remote sensing, farmer decision rules and modelling in rural regions of Northern Vietnam
    (2017) Nguyen, Thanh Thi; Cadisch, Georg
    After the Indo China war in 1954, a dramatic rise in population in Northwest Vietnam led to an increased demand of agricultural land for food security requirements. Slash and burn systems which existed for many hundreds of years were replaced by intense cash crop systems, particularly maize production. Maize cropping was further expanded to steeper sloping areas, resulting in a risk of soil degradation. Therefore, investigating Land Use Change (LUC) and its impact on soil properties were considered in this study. The study aimed to identify LUC in 1954, 1973, the 1990s and 2007 in Chieng Khoi commune, Yen Chau district, Son La province, Vietnam using available remote sensing data. Furthermore, a detailed land use map classification method was developed using farmers’ decision rules. Based on farmers’ crop decision rules and, food requirement and population information, a simple LUC model was developed to simulate LUC annually from 1954 to 2007. Moreover, total soil nitrogen and carbon were determined under a chronosequence of intense cultivation. Thus, developing a modelling tool had the aim to assess the impacts of LUC on soil fertility at watershed level. The first case study (Chapter 3) presented the LUC assessment, using available remote sensing data combined with farmer information. Forest areas decreased from 1954 to 2007, except in the 1990s because of policies that aimed to encourage and support afforestation programmes to increase forest land. However, planted forest has since decreased again since 1999 whereas agricultural land has increased dramatically. Agricultural land expanded to both natural forest and planted forest areas until 2007 legally (with encouragement of agroforestry) and illegally thereafter (at the border between cultivated land and forest). The establishment of an artificial lake in Chieng Khoi commune opened the accessibility to forest land surrounding the lake, with a forest area of 929 ha remaining in 2007 compare to more than 2,500 ha in 1954. Paddy rice areas did not change because of their specific location (lower and flat lands), but production increased and was intensified by two cropping seasons per year due to irrigation improvements and a continuous water supply from the artificial lake. The second case study (Chapter 4) presented the development of a LUC model, using the outputs from the first case study comprising farmers’ decision rules and food requirements for an increased population. For later periods, the influence of market orientation factor was considered. The model successfully simulated the expansion of cultivation areas and replacement of forest land by agricultural land. Simulations were at accepted level of accuracy comparing actual and simulated LUC (Goodness-of-fit – GOF values greater than 0.7 and Figure of merit - FOM values greater than 50%). The third case study (Chapter 5) demonstrated an investigation of the soil fertility dynamic under intense cultivation and the development of a simple dynamic and spatially-explicit modelling tool to assess the changes in soil fertility. The Dynamic of total Carbon and Nitrogen distribution (DyCNDis) model was constructed using field data combined with literature information. The field data showed that, under a decade of maize mono cultivation in slope areas, both nitrogen and carbon were largely depleted. Furthermore, the DyCNDis model showed an acceptable level of validation (modelling efficiency – EF of 0.71 and root mean square error - RMSE of 0.42) to simulate nitrogen and carbon under intense maize cultivation at watershed level. Additionally, the model identified hotspot areas of 134 ha (18.9% of total upland cultivation areas) that are threatened by soil degradation through intense cultivation over a long-term period. In conclusion, the combination of qualitative and quantitative approaches allowed assessing impacts of LUC on environmental services such as soil fertility through the developed DyCNDis modeling tool. The combination of improved LUC analysis with a simple spatial dynamic soil fertility modeling tool may assist policy makers in developing alternative implementation strategies for local stakeholders in regions which face data limitations. The modelling tools developed in this study were able to successfully simulate LUC and to identify locations where soil conservation methods at watershed level need most urgently to be applied to avoid soil degradation. The model tools were able to simulate the trends rather than values of agricultural area expansion and reduction of soil nitrogen and carbon. The developed approaches could be linked and coupled to other modelling tools to economically consider benefits or ecological concerns toward sustainable crop production in remote and rural regions.
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    Nutrient management and spatial variability of soils across scales and settlement schemes in Zimbabwe
    (2010) Cobo Borrero, Juan Guillermo; Cadisch, Georg
    Decline in soil fertility in Africa is one of the most limiting biophysical factors to agricultural productivity, as nutrient mining and low yields are strongly related. However, the high heterogeneity in management together with different biophysical, socio-economical and political conditions across each African agro-ecosystem make blanket recommendations difficult. Thus, acknowledging heterogeneity, and moreover quantifying it at different spatial scales, are the first steps to make adequate recommendations for the different actors. The goal of this thesis was to develop new methodological approaches to better understand nutrient management and spatial variability of soils across different scales in African agro-ecosystems, having various small-holder settlement schemes in Zimbabwe as a case study. Firstly, the thesis includes a literature review on nutrient balances in Africa, which was carried out to illustrate main approaches, challenges, and progress made, with emphasis on issues of scale. The review revealed that nutrient balances are widely used across the continent. The collected dataset from 57 peer-reviewed studies indicated, however, that most of the balances were calculated at plot and farm scale, and generated in East Africa. Data confirmed the expected trend of negative balances for N and K (>75% of studies had mean values below zero), while for P only 56% of studies showed negative mean balances. Several cases with positive nutrient balances indicated that soil nutrient mining cannot be generalized across the African continent. Land use systems of wealthier farmers and plots located close to homesteads mostly presented higher N and P balances than systems of poorer farmers (p<0.001) and plots located relatively farther away (p<0.05). Partial nutrient balances were significantly higher (p<0.001) than full balances calculated for the same systems, but the latter carried more uncertainties. The change in magnitude of nutrient balances from plot to continental level did not show any noticeable trend, which challenges prevailing assumptions that a trend exists. However, methodological differences made a proper inter-scale comparison of results difficult. Actually, the review illustrated the high diversity of methods used to calculate nutrient balances and highlighted the main pitfalls, especially when nutrient flows and balances were scaled-up. In fact, gathered information showed that despite some few initiatives, appropriate scaling-up methods are still incipient. In the next chapter, the nutrient balance approach was applied in NE Zimbabwe. Three smallholder villages located in a typical communal area (colonial settlement from 1948), and in old (1987) and new (2002) resettlement areas (post- land reform settlements), on loamy sand, sandy loam and clay soils, respectively, were selected to explore differences in natural resource management and land productivity. Focus group discussions and surveys were carried out with farmers. Additionally, farmers in three wealth classes per village were chosen for a detailed assessment of their main production systems. Maize grain yields (Mg ha-1) in the communal (1.5-4.0) and new resettlement areas (1.9-4.3) were similar but significantly higher than in the old resettlement area (0.9-2.7), despite lower soil quality in the communal area. Nutrient input use was the main factor controlling maize productivity in the three areas (R2=59-83%), while inherent soil fertility accounted for up to 12%. Partial N balances (kg ha-1 yr-1) were significantly lower in the new resettlement (-9.1 to +14.3) and old resettlement (+7.4 to +9.6) than in the communal area (+2.1 to +59.6) due to lower nutrient applications. P balances were usually negative. Consistently, maize yields, nutrient applications and partial N balances were higher for the high wealth class than in poorer classes. It is argued that effective policies supporting an efficient fertilizer distribution and improved soil management practices, with clearer rights to land, are necessary to avoid future land degradation and to improve food security in Zimbabwe, particularly in the resettlement areas. In the last chapter, the same three villages in NE Zimbabwe were sampled to determine the feasibility of integrating mid-infrared spectroscopy (MIRS) and geostatistics, as a way of facilitating landscape analysis and monitoring. A nested non-aligned design with hierarchical grids of 750, 150 and 30 m resulted in 432 sampling points across all villages. At each point, a composite topsoil sample was taken and analyzed by MIRS. Conventional laboratory analyses on 25-38% of the samples were used for the prediction of concentration values on the remaining samples through the application of MIRS - partial least squares regression models. Models were successful (R2≥0.89) for sand, clay, pH, total C and N, exchangeable Ca, Mg and effective CEC; but not for silt, available P, and exchangeable K and Al (R20.82). Minimum sample sizes required to accurately estimate the mean of each soil property in each village were calculated. With regard to locations, fewer samples were needed in the new resettlement area than in the other two areas; regarding parameters, least samples were needed for estimating pH and sand. Spatial analyses of soil properties in each village were undertaken by constructing standardized isotropic semivariograms, which were usually well described by spherical models. Spatial autocorrelation of most variables was displayed over ranges of 250-695 m. The nugget-to-sill ratios showed that overall spatial dependence of soil properties was: new resettlement > old resettlement > communal area; which was attributed to both intrinsic (e.g. texture) and extrinsic (e.g. management) factors. As a new approach, geostatistical analysis was performed directly using MIRS data, after principal component analyses, where the first three components explained 70% of the overall variability. Semivariograms based on these components showed that spatial dependence per village was similar to overall dependence identified from individual soil properties in each area. The first component (explaining 49% of variation) related well with all soil properties of reference samples (absolute correlation values of 0.55-0.96). This demonstrated that MIRS data could be directly linked to geostatistics for a broad and quick evaluation of soil spatial variability. Integrating MIRS with geostatistical analyses is a cost-effective promising approach, i.e. for soil fertility and carbon sequestration assessments, mapping and monitoring at landscape level.
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    Prediction of soil properties for agricultural and environmental applications from infrared and X-ray soil spectral properties
    (2013) Towett, Erick Kibet; Cadisch, Georg
    Many of today?s most pressing problems facing developing countries, such as food security, climate change, and environmental protection, require large area data on soil functional capacity. Conventional assessments (methods and measurements) of soil capacity to perform specific agricultural and environmental functions are time consuming and expensive. In addition, repeatability, reproducibility and accuracy of conventional soil analytical data are major challenges. New, rapid methods to quantify soil properties are needed, especially in developing countries where reliable data on soil properties is sparse, and to take advantage of new opportunities for digital soil mapping. Mid infrared diffuse reflectance spectroscopy (MIR) has already shown promise as a rapid analytical tool and there are new opportunities to include other high-throughput techniques, such as total X-ray fluorescence (TXRF), and X-ray diffraction (XRD) spectroscopy. In this study TXRF and XRD were tested in conjunction with IR to provide powerful diagnostic capabilities for the direct prediction of key soil properties for agricultural and environmental applications especially for Sub-Saharan Africa (SSA) soils. Optimal combinations of spectral methods for use in pedotransfer functions for low cost, rapid prediction of chemical and physical properties of African soils as well as prediction models for soil organic carbon and soil fertility properties (soil extractable nutrients, pH and exchangeable acidity) were tested in this study. These state-of-the-art methods for large-area soil health measurement and monitoring will aid in accelerating economic development in developing sub-Saharan Africa countries with regards to climate change, increasing water scarcity and impacts on local and global food security as well as sustainable agricultural production and ecosystem resilience in the tropics. This study has developed and tested a method for the use of TXRF for direct quantification of total element concentrations in soils using a TXRF (S2 PICOFOXTM) spectrometer and demonstrated that TXRF could be used as a rapid screening tool for total element concentrations in soils assuming sufficient calibration measures are followed. The results of the current study have shown that TXRF can provide efficient chemical fingerprinting which could be further tested for inferring soil chemical and physical functional properties which is of interest in the African soil context for agricultural and environmental management at large scale. Further, this thesis has helped to improve understanding of the variation and patterns of element concentration data for 1034 soil samples from 34 stratified randomly-located 100-km2 ?sentinel? sites across SSA and explored the link between variability of soil properties and climate, parent material, vegetation types and land use patterns with the help of Random Forests statistics. Our results of total element concentration were within the range reported globally for soil Cr, Mn, Zn, Ni, V, Sr, and Y and in the high range for Al, Cu, Ta, Pb, and Ga. There were significant variations (P < 0.05) in total element composition within and between the sites for all the elements analysed. In addition, the greatest proportion of total variance and number of significant variance components occurred at the site (55-88%) followed by the cluster nested within site levels (10-40%). Our results also indicated that the strong observed within site as well as between site variations in many elements can serve to diagnose their soil fertility potential. Explorations of the relationships between element composition data and other site factors using ?randomForest? statistics have demonstrated that all site and soil-forming factors have important influence on total elemental concentrations in the soil with the most important variables explaining the main patterns of variation in total element concentrations being cluster, topography, landuse, precipitation and temperature. However, the importance of cluster can be explained by spatial correlation at distances of <1 km. This study has also analysed the potential of combining analyses undertaken using MIR spectroscopy and TXRF on 700 soil samples from 44 ?sentinel? sites distributed across SSA. MIR prediction models for soil organic carbon, and other soil fertility properties (such as soil extractable nutrients, pH, exchangeable acidity and soil texture) were developed using Random Forests (RF) regression and the current study has added total element concentration data to the residuals of the MIRS predictions to test how they can improve the MIR prediction accuracies. The RF approach out-perfomed the conventional partial least squares regression (PLSR) on simultaneous determination of soil properties; and in addition, RF results were also easily interpretable, computationally much faster and did not rely on data transformations or any other assumptions about data distributions compared to PLSR. With respect to the potential of combining TXRF and MIR spectra, including total element concentration data from TXRF analysis in the RF models significantly reduced root mean square error of prediction by 63% for Ecd, 54% for Mehlich-3 S, and 53% for Mehlich-3 Na. Thus, TXRF spectra were a useful supplement to improve prediction of soil properties not well predicted by MIRS. The prediction improvement from including TXRF was due to detection of a few outliers that did not appear as MIR spectral outliers. MIR showed remarkable ability to capture total elemental composition effects on physico-chemical soil properties but TXRF may have potential for outlier detection in large studies. This study has also helped to develop high-throughput spectral analytical methods and provided recommendations on optimal spectral analytical methods for the Globally Integrated Africa Soil Information Service (AfSIS) Project. Successfully developed methods in this study will become part of the standard AfSIS procedures.
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    Rainforestation farming on Leyte island, Philippines - aspects of soil fertility and carbon sequestration potential
    (2007) Marohn, Carsten; Sauerborn, Joachim
    This study aimed at investigating rainforestation systems in Leyte, Philippines, under different aspects: Characterisation of typical soils in Leyte with respect to physical, chemical and biological parameters relevant for tree growth, possible contributions of rainforestation to restoring soil fertility, performance of a recently planted rainforestation system under different microclimatic and soil conditions, potential of the rainforestation approach for projects under the umbrella of the Clean Development Mechanism (CDM). Soils in Leyte can be grouped into a volcanic and a calcareous category. The latter were formed on coralline limestone and are high in pH and Ca2+ and Mg2+. Contents of organic matter are high while concentrations of plant available PBray are low. Volcanic soils are characterised by low pH and CEC as well as extremely low PBray contents. Organic matter levels are below those of the calcareous soils but still moderate. In any analysed soil, N would not limit tree growth. Pore volume and water infiltration were propitious for all sites, which is relevant in the context of erosion. For calcareous soils, drought and reduced rootability due to clayey subsoil posed the most relevant constraints. The frequently claimed role of rainforestation in the rehabilitation of degraded soils was assessed in a paired plot approach. Chemical and biological soil parameters under 10 year old rainforestation were contrasted with adjacent fallow or Gmelina sp. Clear tendencies across all seven sampled sites were lower available Mg2+ and pH under rainforestation. Other differences were less distinct. Generally, a depletion of soil reserves e.g. in basic cations can be explained by uptake into the plants. A feed-back of these elements to the topsoil via leaf litter, however, could be observed only for available P. In conclusion, plant uptake of single elements can reach orders of magnitudethat reduce soil stocks. At the same time, generally lower pH under rainforestation may have contributed to elevated losses, especially of basic cations. A general improvement of the sampled soils in terms of chemical or biological characteristics through rainforestation could not be observed. To evaluate plant performance six timber and four fruit species, most native, were interplanted on a 1ha plot. Rainforestation, commonly understood as high-density closed canopy system was modified to a less dense 5x5m grid, interplanted with Musa textilis. The plot varied strongly on a small scale due to heterogeneous canopy closure and relief. Methodologically, the entire area was divided into 10 subplots in representative positions to be sampled. Soil physical and chemical properties, microbial activity, PAR and root length density were determined and correlated to plant survival and growth at consecutive inventories. For Musa textilis, the most sensitive species, which was used as an indicator, logistic regressions were calculated to determine the influence of all relevant parameters on survival rates. The most important predictors for survival were organic matter contents, parameters related to biological activity and leaf litter production, which resembled canopy closure and thus indirectly light intensity and soil moisture. To assess growth, multiple regressions were formulated for biomass at five inventories. Corg and NLOM were the most relevant variables determining the regressions used for biomass and growth of abaca. Assessing the potential of rainforestation for Clean Development Mechanism (CDM) measures, amounts of sequestered CO2 during 10 and 20 years, respectively, were estimated under different management options using the WaNuLCAS model. Despite all given uncertainty associated with modelling, one very obvious finding was the dominant role of soil carbon for the plot balance: Appropriate soil management, especially during land preparation (e.g. clearing vs. enrichment planting) is of paramount importance. Looking at the modelled contribution of various tree species to the carbon balance, Musa textilis had a significant influence only during the very first years; later on, the principal share of carbon was bound in the tree component. Here, exotic Gmelina arborea built up biomass more quickly than a rainforestation plot composed of native Shorea contorta and Durio zibethinus, but was then overtaken. In absolute quantities of CO2 sequestration, magnitudes matched inventory and modelled data given in various literature sources for Leyte and the Philippines. Relative to earlier inventory data from two rainforestation sites, modelled values overestimated growth.
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    Reconciling indigenous and scientific ecosystem and soil fertility indicators in swidden systems of Northern Thailand
    (2021) Tongkoom, Krittiya; Cadisch, Georg
    Crop rotations in today’s swidden systems of Northern Thailand typically include five to ten years of fallow. Regarding ecosystem functions, these systems are relatively close to secondary forests when compared to modern agricultural systems; but they are under pressure for intensification, i.e. shortened fallow periods. In general, criteria are needed to decide whether fallow duration can be reduced, safeguarding ecosystem restoration and provision of food and income for farmers. Acknowledging that a comprehensive assessment would cover multiple aspects, our study focuses on the role of fallow duration on tree community succession and use abundances of tree species considered as soil fertility indicators. We studied recovery indicators of tree communities at two potential broad-leaved forest climax sites that differ in soils, forest type and agricultural intensification: An intensive system of one-year upland rice, then one- to two-year maize cultivation with synthetic inputs followed by six years fallow; and an extensive system with one-year upland rice cultivation without agrochemicals and ten years fallow. In a case study village of extensive site, we investigated in how far abundance of indicator tree species corresponded to measured soil fertility parameters and whether an extended list of indicator species could improve prediction of these soil properties. Contrasting systems were chosen to test the applicability of our indicators, not to compare their management practices. From 2010 to 2011, eight variables related to stand structure and tree diversity and four soil properties were either monitored or surveyed in chronosequence plots representing different fallow ages. For each variable, means per fallow year were compared by least squares means (LS-means), and quadratic regressions from mixed models were fitted. Significant differences between LS-means and optima of regressions served to distinguish fallow stages and served as indicators of recovery and system stability. Stepwise multiple regressions confirmed fallow age as main determinant for most variables. Tree species indicator also identify by the component of multiple linear regressions function of each interested soil properties. Numbers of tree species and diversity index recovered to levels of the previous rotation within the respective fallow time, but in both systems were far from climax communities, probably due to seed-bank depletion and shift toward resprouting species. While species dominance changed over time in the extensive system, the intensive system was dominated by a single species. In the extensive system only tree density passed a peak during the fallow period, while biomass-related variables approached plateaus. In combination with the replacement of early fallow species, this points to the onset of competition and transition between successional stages. For the intensive system, no structural variable passed a maximum. With only one of eight indicators on the extensive site fulfilling the statistical criterion of passing a peak during the prevailing fallow time, reducing fallow periods is not recommended for our cases. Generally, combining LS-means and quadratic regression allowed assessing fallow duration based on distinct successional stages at different sites. The approach should include various relevant site-specific indicators, in our case representing biomass and carbon storage, species and structural diversity, considered crucial for both sites. From interview on the extensive site, farmers listed 11 tree species that relate to certain soil quality related properties. They named indicators of good soils for cropping, inappropriate soils for upland rice cropping and hard soils. Botanical tree inventories on 135 plots of one to ten years fallow age were conducted. Abundances of farmers’ indicator on one hand as well as inventory species on the other were introduced into different regression models to predict soil fertility parameters measured on the same plots. Both models were then compared regarding predictive power. Measured fertility parameters such as soil organic matter (SOM), pH, plant available phosphorus (Pav) - related to farmers’ criteria ‘good soil’ or inappropriate for rice cropping’ - as well as bulk density (BD, for ‘hard soil’), changed significantly during the fallow period, initially towards temporary pessima in years 6 to 7 followed by recovery towards year ten. Most indicator species, like Macaranga denticulata for Pav or Dalbergia cultrata for SOM, were clearly related to the soil quality characteristics attributed to them by farmers. Only in one case a species used as farmer indicator for hard soils was selected by multiple regression as predictor for high Pav. Including all tree species found during inventories into multiple regressions significantly improved predictions of measured soil parameters by AIC > |2|. Ten additional species from the survey model had potential to improve the farmer indicator model. Relative density, i.e. abundance of indicator tree species over abundance of all species, did not always match soil properties dynamics, so that the use of the regressions appears more informative for cropping decisions. Our approach to relate indicator species and measured soil parameters is not site-specific, but parameters are. Applicability of the approach could be extended if further farmer criteria such as weed suppression, represented by tree structure parameters as predictors of adequate fallow age, would complement soil fertility indicators. Based on the development of the multiple indicators of recovery of ecosystem services and soil fertility, it is not recommended to reduce fallow age at the two investigated study sites.