MULTIFILE
While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few ‘hyperdominant’species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing morecarbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing andproducing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carboncycling, and whether dominant species are characterized by specific functional traits.
MULTIFILE
Ghanaian farmers suffer from a decline in cocoa production partly due to damages and diseases from insect pests. To increase predation by bats on insects on the cocoa plantations we installed two different types of bat boxes on 15 plantations around the village of Buoyem. Bat activity, bat species composition (numbers of insectivorous and frugivorous bats) and insect abundance were measured before and after bat box installation. Insectivorous bats were present on all ofthe sampled plantations, namelyleaf-nosed bats (Hipposideros sp.), slit-faced bats (Nycteridae sp.), horseshoe bats (Rhinolophus sp.) and vesper bats (Vespertilionidae sp.). Furthermore, no correlation between insect abundance and bat activity could be detected. The bat boxes were not occupied yet during the research period since rainy season started in the second half of the measurements and bat activity decreases with increasing precipitation which is supported by our Un dings. Additionally, the available time period between in stallation and measuring of the effects of the boxes was very short when compared to similar researches. Bats alsohave different preferences per species for size and shape of bat boxes and the number of naturally available roosting sites also influences bat box occupancy. Our results suggest that bats are abundant above cocoa plantations in Buoyem and therefore bat boxes have the potential to be ahelpful tool in insect pest control.
MULTIFILE
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
