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Modern agriculture is the basis of human existence, a blessing, but also a curse. It provides nourishment and well-being to the ever-growing human population, yet destroys biodiversity-mediated processes that underpin productivity: ecosystem services such as water filtration, pollination and biological pest control. Ecological intensification is a promising alternative to conventional farming, and aims to sustain yield and ecosystem health by actively managing biodiversity and essential ecosystem services. Here, I investigate opportunities and obstacles for ecological intensification. My research focuses on 1) the relative importance of soil, management and landscape variables for biodiversity and wheat yield (Chapter II); 2) the influence of multi-scale landscape-level crop diversity on biological pest control in wheat (Chapter III) and 3) on overall and functional bird diversity (Chapter IV). I conclude 4) by introducing a guide that helps scientists to increase research impact by acknowledging the role of stakeholder engagement for the successful implementation of ecological intensification (Chapter V).
Ecological intensification relies on the identification of natural pathways that are able to sustain current yields. Here, we crossed an observational field study of arthropod pests and natural enemies in 28 real-life wheat systems with an orthogonal on-field insecticide-fertilizer experiment. Using path analysis, we quantified the effect of 34 factors (soil characteristics, recent and historic crop management, landscape heterogeneity) that directly or indirectly (via predator-prey interactions) contribute to winter wheat yield. Reduced soil preparation and high crop rotation diversity enhanced crop productivity independent of external agrochemical inputs. Concurrently, biological control by arthropod natural enemies could be restored by decreasing average field sizes on the landscape scale, extending crop rotations and reducing soil disturbance. Furthermore, reductions in agrochemical inputs decreased pest abundances, thereby facilitating yield quality.
Landscape-level crop diversity is a promising tool for ecological intensification. However, biodiversity enhancement via diversification measures does not always translate into agricultural benefits due to antagonistic species interactions (intraguild predation). Additionally, positive effects of crop diversity on biological control may be masked by inappropriate study scales or correlations with other landscape variables (e.g. seminatural habitat). Therefore, the multiscale and context-dependent impact of crop diversity on biodiversity and ecosystem services is ambiguous. In 18 winter wheat fields along a crop diversity gradient, insect- and bird-mediated pest control was assessed using a natural enemy exclusion experiment with cereal grain aphids. Although birds did not influence the strength of insect-mediated pest control, crop diversity (rather than seminatural habitat cover) enhanced aphid regulation by up to 33%, particularly on small spatial scales. Crop diversification, an important Greening measure in the European Common Agricultural Policy, can improve biological control, and could lower dependence on insecticides, if the functional identity of crops is taken into account. Simple measures such as ‘effective number of crop types’ help in science communication.
Although avian pest control did not respond to landscape-level crop diversity, birds may still benefit from increased crop resources in the landscape, depending on their functional grouping (feeding guild, conservation status, habitat preference, nesting behaviour). Observational studies of bird functional diversity on 14 wheat study fields showed that non-crop landscape heterogeneity rather than crop diversity played a key role in determining the richness of all birds. Insect-feeding, non-farmland and non-threatened birds increased across multiple spatial scales (up to 3000 m). Only crop-nesting farmland birds declined in heterogeneous landscapes. Thus, crop diversification may be less suitable for conserving avian diversity, but abundant species benefit from overall habitat heterogeneity. Specialist farmland birds may require more targeted management approaches.
Identifying ecological pathways that favour biodiversity and ecosystem services provides opportunities for ecological intensification that increase the likelihood of balancing conservation and productivity goals. However, change towards a more sustainable agriculture will be slow to come if research findings are not implemented on a global scale. During dissemination activities within the EU project Liberation, I gathered information on the advantages and shortcomings of ecological intensification and its implementation. Here, I introduce a guide (‘TREE’) aimed at scientists that want to increase the impact of their research. TREE emphasizes the need to engage with stakeholders throughout the planning and research process, and actively seek and promote science dissemination and knowledge implementation. This idea requires scientists to leave their comfort zone and consider socioeconomic, practical and legal aspects often ignored in classical research.
Ecological intensification is a valuable instrument for sustainable agriculture. Here, I identified new pathways that facilitate ecological intensification. Soil quality, disturbance levels and spatial or temporal crop diversification showed strong positive correlations with natural enemies, biological pest control and yield, thereby lowering the dependence on agrochemical inputs. Differences between functional groups caused opposing, scale-specific responses to landscape variables. Opposed to our predictions, birds did not disturb insect-mediated pest control in our study system, nor did avian richness relate to landscape-level crop diversity. However, dominant functional bird groups increased with non-crop landscape heterogeneity. These findings highlight the value of combining different on-field and landscape approaches to ecological intensification. Concurrently, the success of ecological intensification can be increased by involving stakeholders throughout the research process. This increases the quality of science and reduces the chance of experiencing unscalable obstacles to implementation.
Environmental interlinked problems such as human-induced land cover change, water scarcity, loss in soil fertility, and anthropogenic climate change are expected to affect the viability of agriculture and increase food insecurity in many developing countries. Climate change is certainly the most serious of these challenges for the twenty-first century. The poorest regions of the world – tropical West Africa included – are the most vulnerable due to their high dependence on climate and weather sensitive activities such as agriculture, and the widespread poverty that limits the institutional and economic capacities to adapt to the new stresses brought about by climate change. Climate change is already acting negatively on the poor smallholders of tropical West Africa whose livelihoods dependent mainly on rain-fed agriculture that remains the cornerstone of the economy in the region. Adaptation of the agricultural systems to climate change effects is, therefore, crucial to secure the livelihoods of these rural communities. Since information is a key for decision-making, it is important to provide well-founded information on the magnitude of the impacts in order to design appropriate and sustainable adaptation strategies.
Considering the case of agricultural production in the Republic of Benin, this study aims at using large-scale climatic predictors to assess the potential impacts of past and future climate change on agricultural productivity at a country scale in West Africa. Climate signals from large-scale circulation were used because state-of-the art regional climate models (RCM) still do not perfectly resolve synoptic and mesoscale convective processes. It was hypothesised that in rain-fed systems with low investments in agricultural inputs, yield variations are widely governed by climatic factors. Starting with pineapple, a perennial fruit crops, the study further considered some annual crops such as cotton in the group of fibre crops, maize, sorghum and rice in the group of cereals, cowpeas and groundnuts belonging to the legume crops, and cassava and yams which are root and tuber crops. Thus the selected crops represented the three known groups of photosynthetic pathways (i.e. CAM, C3, and C4 plants).
In the study, use was made of the historical agricultural yield statistics for the Republic of Benin, observed precipitation and mean near-surface air temperature data from the Climatic Research Unit (CRU TS 3.1) and the corresponding variables simulated by the regional climate model (RCM) REMO. REMO RCM was driven at its boundaries by the global climate model ECHAM 5. Simulations with different greenhouse gas concentrations (SRES-A1B and B1 emission scenarios) and transient land cover change scenarios for present-day and future conditions were considered. The CRU data were submitted to empirical orthogonal functions analysis over the north hemispheric part of Africa to obtain large-scale observed climate predictors and associated consistent variability modes. REMO RCM data for the same region were projected on the derived climate patterns to get simulated climate predictors. By means of cross-validated Model Output Statistics (MOS) approach combined with Bayesian model averaging (BMA) techniques, the observed climate predictors and the crop predictand were further on used to derive robust statistical relationships. The robust statistical crop models perform well with high goodness-of-fit coefficients (e.g. for all combined crop models: 0.49 ≤ R2 ≤ 0.99; 0.28 ≤ Brier-Skill-Score ≤ 0.90).
Provided that REMO RCM captures the main features of the real African climate system and thus is able to reproduce its inter-annual variability, the time-independent statistical transfer functions were then used to translate future climate change signal from the simulated climate predictors into attainable crop yields/crop yield changes. The results confirm that precipitation and air temperature governed agricultural production in Benin in general, and particularly, pineapple yield variations are mainly influenced by temperature. Furthermore, the projected yield changes under future anthropogenic climate change during the first-half of the 21st century amount up to -12.5% for both maize and groundnuts, and -11%, -29%, -33% for pineapple, cassava, and cowpeas respectively. Meanwhile yield gain of up to +10% for sorghum and yams, +24% for cotton, and +39% for rice are expected. Over the time period 2001 – 2050, on average the future yield changes range between -3% and -13% under REMO SRES–B1 (GHG)+LCC, -2% and -11% under REMO SRES–A1B (GHG only),and -3% and -14% under REMO SRES–A1B (GHG)+LCC for pineapple, maize, sorghum, groundnuts, cowpeas and cassava. In the meantime for yams, cotton and rice, the average yield gains lie in interval of about +2% to +7% under REMO SRES–B1 (GHG)+LCC, +0.1% and +12% under REMO SRES–A1B (GHG only), and +3% and +10% under REMO SRES–A1B (GHG)+LCC. For sorghum, although the long-term average future yield depicts a reduction there are tendencies towards increasing yields in the future. The results also reveal that the increases in mean air temperature more than the changes in precipitation patterns are responsible for the projected yield changes. As well the results suggest that the reductions in pineapple yields cannot be attributed to the land cover/land use changes across sub-Saharan Africa. The production of groundnuts and in particular yams and cotton will profit from the on-going land use/land cover changes while the other crops will face detrimental effects.
Henceforth, policymakers should take effective measures to limit the on-going land degradation processes and all other anthropogenic actions responsible for temperature increase. Biotechnological improvement of the cultivated crop varieties towards development of set of seed varieties adapted to hotter and dry conditions should be included in the breeding pipeline programs. Amongst other solutions, application of appropriate climate-smart agricultural practices and conservation agriculture are also required to offset the negative impacts of climate change in agriculture.