Institut für Pflanzenproduktion und Agrarökologie in den Tropen und Subtropen

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/15

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Ecophysiological and agronomic response of Abaca (Musa textilis) to different resource conditions in Leyte Island, Philippines
(2012) Bande, Marlito M.; Sauerborn, Joachim
Abaca (Musa textilis Née) is closely related to edible bananas (Musa acuminata Colla and M. balbisiana Colla). Abaca usually thrives in the shade beneath tall trees, especially important for protecting the young plants from the sun and the older, taller plants from wind breakage. However, there is still disagreement on the need for shade trees in abaca cultivation. Hence, this study was conducted to ascertain the ecophysiological and agronomic response of abaca grown in different shade conditions, water and nutrient management systems in Leyte Island, Philippines. The objectives of the study were to: (a) explore the influence of shade and irrigation-fertilization on the morphological and physiological performance of abaca; (b) investigate the effect of reducing light intensities by 30%, 40% and 50% of full sunlight on fiber yield and fiber quality; (c) determine the optimum light requirement of abaca plants to attain the optimum yield without affecting the quality of the fiber for industrial use; (d) examine the effect of shade and irrigation-fertilization on biomass production and allocation as well as on NPK absorption and distribution among abaca organs; and (e) find out if irrigation and fertilization could offset the effect of shade on biomass production, NPK absorption and fiber yield of abaca. Field trials were established where light infiltration was reduced by 30%, 40%, and 50% of full sunlight using polypropylene shade nets. Irrigation was applied at a rate of 5 liters plant-1 application-1 day-1. The frequency of irrigation was applied two times per day at seedling stage (1-3 months after planting), three times at the early vegetative stage (4-6 MAP), four times at the late vegetative stage (7-9 MAP), and five times at flagleaf stage (10-12 MAP). On the other hand, placement application of N, P2O5, K2O using complete fertilizer was done at 14 g plant-1 in every three months for the first six months and was increased to 40 g plant-1 in every three months for the next six months after planting. The results of this study showed that plant height, cumulative leaf area, pseudostem length and base girth of abaca significantly improved when the light was further reduced to 50%. The application of NPK fertilizer and combination of irrigation-fertilization further enhanced the growth performance of abaca. Statistical analysis showed that shade, NPK fertilization and combination of irrigation-fertilization positively affected dry matter production, crop growth rate, leaf area ratio and net assimilation rate from seedling to flagleaf stage. Furthermore, biomass allocation and NPK distribution among abaca organs was significantly affected by high radiation and/or temperature at seedling and early vegetative stages, and differential leaf senescence at flagleaf stage where shade plays a considerable function. The amount of NPK absorbed by each organ was influenced by the growth made during the different stages of crop development. Meanwhile, irrigation and fertilizer application further improved biomass allocation that considerably increased NPK absorption and distribution among plant parts. With regards to agronomic response, the abaca planted under different light regimes showed that 50% shade had significantly higher fiber yield compared to those that were under other light treatments since the plants pseudostem under such treatment were longer, bigger and heavier. The combination of irrigation and fertilization could further enhance fiber yield to as much as 141% (compared to the control) but this was not enough to offset the effects of shade on the physiological performance of the plant which significantly increased fiber yield to as much as 265% (compared to the control). Statistical analysis showed that shade and irrigation-fertilizer application had no significant effect on fiber fineness and tensile strength. The superior productivity of abaca in response to shade was due to the avoidance of photoinhibition and photooxidative damage that negatively affected the abaca grown under full sunlight at seedling and early vegetative stage. Likewise, the detrimental effect of photoinhibition on the photosynthetic capacity of abaca grown in full sunlight significantly decreased biomass production and allocation among abaca organs. The amount of NPK absorbed by each organ was influenced by high radiation causing photooxidative damage at seedling stage and differential leaf senescence at flagleaf stage. This significantly affected the pattern of biomass allocation and NPK distribution among abaca plant organs. On the other hand, the application of fertilizer considerably enhanced biomass production but did not change the usual pattern of biomass and NPK distribution. The results showed that irrigation and fertilizer application cannot offset or equalize the positive effect of shade on the vegetative growth, physiological performance, and NPK absorption among plant organs.
Salience, credibility and legitimacy in land use change modeling : model validation as product or process?
(2015) Lusiana, Betha; Cadisch, Georg
Sustainable resource management requires balancing trade-offs between land productivity and environmental integrity while maintaining equality in resource access. Scenario analysis based on a credible simulation model can help to efficiently assess the dynamic and complex interactions in between components and their trade-offs. However, despite the potential of simulation models as decision support tools, acceptance and use by decision makers and natural resource managers are still major challenges, particularly in developing countries. This study was carried out to address issues related to validation of simulation models that includes users’ perspectives on validity of simulation models, scenario-based trade-offs analysis and uncertainty assessment for designing management intervention. Firstly, the current study analyzed users’ perspectives on validity of a simulation model for natural resource management based on two activities. The first activity is based on surveys in four countries (Indonesia, Kenya, Philippines and Vietnam). It explored the perceptions and expectations of potential model users (researchers, lecturers, natural resource managers, policy makers, communicators) on a hypothetical model. The second activity was a participatory model evaluation in Aceh, Indonesia involving use of the spatially explicit FALLOW model and evaluation of its outputs. When assessing a hypothetical model, potential model users’ considered salience (relevance) as the most important attribute in a simulation model followed by credibility. Once a model was used, the ability of the model results to depict reality on the ground (credibility) became a critical and most important aspect for users. Nevertheless, even in cases where model performance was poor, users considered the scenario approach in evaluating their landscape a novelty. Potential model users’ profession, prior exposure to a simulation model and interest in using models did not significantly influence respondents’ ranking of model attributes (salience, credibility, legitimacy). In the second study, to improve salience of a FALLOW model application, a livestock module was developed and tested for a peri-urban situation in the Upper Konto catchment, East Java, Indonesia. This study aimed to explore the impact of land use zoning strategies on farmers’ welfare, fodder availability and landscape carbon stocks. Scenario analysis revealed that the current land zoning policy of establishing protected areas and allowing farmers’ access to fodder extraction in part of the protected areas is the most promising strategy in balancing the trade-offs of production (farmers’ welfare) and environment (represented by above-ground carbon sequestration). Compared to the scenario reflecting current policy, the ‘open-access’ scenario that allows opening land in protected areas, was simulated to increase farmers’ welfare by 13% at the expense of losing 23% of landscape carbon. The extended FALLOW model with its livestock module proved an effective tool to examine the interactions between livestock, cropping systems, household decision and natural resources in data poor environments. The FALLOW model was able to simulate the land cover spatial pattern in the catchment (2002-2005) with a goodness of fit of 81% while the ability of predicting land change was 34.5% at a pixel resolution of 1 ha. In the third study, to understand the effect of uncertainty in input parameters influencing model outcome, an uncertainty analysis of landscape C stock and emissions was carried out using several approaches that can cater for different situations of data availability (plot level carbon stocks and land cover maps). The analysis used data collected during a study assessing opportunities for REDD+ (Reducing Emission from Deforestation and Degradation) in a forest frontier region in Jambi, Indonesia, during 2000-2009. In a minimum data set situation (only single plot carbon estimates and a single land cover map available) the average landscape C stock estimates were 114.5 Mg.ha-1 and 81.0 Mg.ha-1 for 2000 and 2009, respectively. Based on an ‘expected-carbon-deviance’ curve, the confidence levels that the landscape C estimates were correct were 70% and 63% for 2000 and 2009, respectively. For other cases of enhanced data availability, Monte Carlo simulations were carried out to evaluate the propagation of land use classification errors and plot-level carbon stocks variation, jointly influencing landscape C stock and emission estimates. Results showed that excluding errors in land use classification resulted in biased estimates of landscape C stock and emissions. However, the bias over the whole area was estimated to be less than 7.5% (or 2.8 Mg.ha-1) with a coefficient variation of less than 0.2%. In the last study, we combined spatial aggregation analysis on the error-perturbed C emission maps (resulting from Monte Carlo analysis in the third study) with local stakeholders’ perspectives to develop an effective REDD+ scheme at the district level. The uncertainty analysis formed the basis for determining an appropriate scale for monitoring carbon emission estimates as performance measures of a REDD+ scheme. Changes in spatial resolution of C emission maps influenced the magnitude of potential area eligible for carbon payment and the uncertainty in carbon emission estimates. At 100 m resolution, 34.8% of the area would be eligible for REDD+ with an uncertainty of 82% , while at 5000 m resolution only 6.5% of the area would be eligible with a 1% error. At 1 km2 pixel size (1000 m resolution), the errors dropped below 5%, retaining most of the coarser spatial variation in the district. Hence, feasible measures for emission reduction in the district, derived from a participatory planning process, are compatible with the 1000 m spatial resolution of the C emission map. Overall, the research elucidates the importance of involving model users in evaluating a simulation model, including scenario development and subsequent results analysis and interpretation. The study also indicates the importance of making efforts to improve model output accuracy to gain users’ acceptance as users consider spatial accuracy is an important aspect of landscape-based models. In data-scarce situations, model users considered model ‘robustness’ in responding to new situations to be more important than ‘precision’. Scenario analysis proved to be an effective tool to examine interactions in a complex landscape, including their consequences for trade-offs (e.g. farmer’s welfare versus landscape carbon stocks) and synergies (e.g. fodder availability and farmers’ welfare). Analysis of uncertainty of landscape C emission during land use changes can provide guidance in developing appropriate natural resource management interventions. Although model users may perceive model validation as a product, it is in fact a process.

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