@article{DhillonDahmsKuebertFlocketal.2022,
  author    = {Dhillon, Maninder Singh and Dahms, Thorsten and K{\"u}bert-Flock, Carina and Steffan-Dewenter, Ingolf and Zhang, Jie and Ullmann, Tobias},
  title     = {Spatiotemporal Fusion Modelling Using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {3},
  issn      = {2072-4292},
  doi       = {10.3390/rs14030677},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323471},
  year      = {2022},
  abstract  = {The increasing availability and variety of global satellite products provide a new level of data with different spatial, temporal, and spectral resolutions; however, identifying the most suited resolution for a specific application consumes increasingly more time and computation effort. The region's cloud coverage additionally influences the choice of the best trade-off between spatial and temporal resolution, and different pixel sizes of remote sensing (RS) data may hinder the accurate monitoring of different land cover (LC) classes such as agriculture, forest, grassland, water, urban, and natural-seminatural. To investigate the importance of RS data for these LC classes, the present study fuses NDVIs of two high spatial resolution data (high pair) (Landsat (30 m, 16 days; L) and Sentinel-2 (10 m, 5-6 days; S), with four low spatial resolution data (low pair) (MOD13Q1 (250 m, 16 days), MCD43A4 (500 m, one day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, eight day)) using the spatial and temporal adaptive reflectance fusion model (STARFM), which fills regions' cloud or shadow gaps without losing spatial information. These eight synthetic NDVI STARFM products (2: high pair multiply 4: low pair) offer a spatial resolution of 10 or 30 m and temporal resolution of 1, 8, or 16 days for the entire state of Bavaria (Germany) in 2019. Due to their higher revisit frequency and more cloud and shadow-free scenes (S = 13, L = 9), Sentinel-2 (overall R\(^2\) = 0.71, and RMSE = 0.11) synthetic NDVI products provide more accurate results than Landsat (overall R\(^2\) = 0.61, and RMSE = 0.13). Likewise, for the agriculture class, synthetic products obtained using Sentinel-2 resulted in higher accuracy than Landsat except for L-MOD13Q1 (R\(^2\) = 0.62, RMSE = 0.11), resulting in similar accuracy preciseness as S-MOD13Q1 (R\(^2\) = 0.68, RMSE = 0.13). Similarly, comparing L-MOD13Q1 (R\(^2\) = 0.60, RMSE = 0.05) and S-MOD13Q1 (R\(^2\) = 0.52, RMSE = 0.09) for the forest class, the former resulted in higher accuracy and precision than the latter. Conclusively, both L-MOD13Q1 and S-MOD13Q1 are suitable for agricultural and forest monitoring; however, the spatial resolution of 30 m and low storage capacity makes L-MOD13Q1 more prominent and faster than that of S-MOD13Q1 with the 10-m spatial resolution.},
  language  = {en}
}
@article{LaswayKinaboMremietal.2021,
  author    = {Lasway, Julius V. and Kinabo, Neema R. and Mremi, Rudolf F. and Martin, Emanuel H. and Nyakunga, Oliver C. and Sanya, John J. and Rwegasira, Gration M. and Lesio, Nicephor and Gideon, Hulda and Pauly, Alain and Eardley, Connal and Peters, Marcell K. and Peterson, Andrew T. and Steffan-Dewenter, Ingolf and Njovu, Henry K.},
  title     = {A synopsis of the Bee occurrence data of northern Tanzania},
  series = {Biodiversity Data Journal},
  volume    = {9},
  journal   = {Biodiversity Data Journal},
  doi       = {10.3897/BDJ.9.e68190},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265018},
  year      = {2021},
  abstract  = {Background Bees (Hymenoptera: Apoidea: Anthophila) are the most important group of pollinators with about 20,507 known species worldwide. Despite the critical role of bees in providing pollination services, studies aiming at understanding which species are present across disturbance gradients are scarce. Limited taxononomic information for the existing and unidentified bee species in Tanzania make their conservation haphazard. Here, we present a dataset of bee species records obtained from a survey in nothern Tanzania i.e. Kilimanjaro, Arusha and Manyara regions. Our findings serve as baseline data necessary for understanding the diversity and distribution of bees in the northern parts of the country, which is a critical step in devising robust conservation and monitoring strategies for their populations. New information In this paper, we present information on 45 bee species belonging to 20 genera and four families sampled using a combination of sweep-netting and pan trap methods. Most species (27, ~ 60\%) belong to the family Halictidae followed by 16 species (35.5\%) from the family Apidae. Megachilidae and Andrenidae were the least represented, each with only one species (2.2\%). Additional species of Apidae and Megachilidae sampled during this survey are not yet published on Global Biodiversity Information Facility (GBIF), once they will be available on GBIF, they will be published in a subsequent paper. From a total of 953 occurrences, highest numbers were recorded in Kilimanjaro Region (n = 511), followed by Arusha (n = 410) and Manyara (n = 32), but this pattern reflects the sampling efforts of the research project rather than real bias in the distributions of bee species in northern Tanzania.},
  language  = {en}
}
@phdthesis{Redlich2020,
  author    = {Redlich, Sarah},
  title     = {Opportunities and obstacles of ecological intensification: Biological pest control in arable cropping systems},
  doi       = {10.25972/OPUS-17122},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-171228},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}