scholarly journals Comparing floral resource maps and land cover maps to predict predators and aphid suppression on field bean

2021 ◽  
Author(s):  
Lolita Ammann ◽  
Aliette Bosem-Baillod ◽  
Philipp W. Eckerter ◽  
Martin H. Entling ◽  
Matthias Albrecht ◽  
...  
Keyword(s):  
Land Cover ◽  
Faba Bean ◽  
Floral Resources ◽  
Aphid Infestation ◽  
Positive Effects ◽  
Aphid Control ◽  
Aphid Predators ◽  
Predator Abundance ◽  
Floral Resource ◽  
Land Cover Maps

Abstract Context Predatory insects contribute to the natural control of agricultural pests, but also use plant pollen or nectar as supplementary food resources. Resource maps have been proposed as an alternative to land cover maps for prediction of beneficial insects. Objectives We aimed at predicting the abundance of crop pest predating insects and the pest control service they provide with both, detailed flower resource maps and land cover maps. Methods We selected 19 landscapes of 500 m radius and mapped them with both approaches. In the centres of the landscapes, aphid predators – hoverflies (Diptera: Syrphidae), ladybeetles (Coleoptera: Coccinellidae) and lacewings (Neuroptera: Chrysopidae) – were surveyed in experimentally established faba bean phytometers (Vicia faba L. Var. Sutton Dwarf) and their control of introduced black bean aphids (Aphis fabae Scop.) was recorded. Results Landscapes with higher proportions of forest edge as derived from land cover maps supported higher abundance of aphid predators, and high densities of aphid predators reduced aphid infestation on faba bean. Floral resource maps did not significantly predict predator abundance or aphid control services. Conclusions Land cover maps allowed to relate landscape composition with predator abundance, showing positive effects of forest edges. Floral resource maps may have failed to better predict predators because other resources such as overwintering sites or alternative prey potentially play a more important role than floral resources. More research is needed to further improve our understanding of resource requirements beyond floral resource estimations and our understanding of their role for aphid predators at the landscape scale.

scholarly journals Identity of mass-flowering crops moderates functional trait composition of pollinator communities

2021 ◽  
Author(s):  
Nicole Beyer ◽  
Felix Kirsch ◽  
Doreen Gabriel ◽  
Catrin Westphal
Keyword(s):  
Faba Bean ◽  
Management Practices ◽  
Functional Trait ◽  
Flower Morphology ◽  
Landscape Diversity ◽  
Floral Resources ◽  
Wild Bees ◽  
Natural Habitats ◽  
Mass Flowering ◽  
Wild Bee

Abstract Context Pollinator declines and functional homogenization of farmland insect communities have been reported. Mass-flowering crops (MFC) can support pollinators by providing floral resources. Knowledge about how MFC with dissimilar flower morphology affect functional groups and functional trait compositions of wild bee communities is scarce. Objective We investigated how two morphologically different MFC, land cover and local flower cover of semi-natural habitats (SNH) and landscape diversity affect wild bees and their functional traits (body size, tongue length, sociality, foraging preferences). Methods We conducted landscape-level wild bee surveys in SNH of 30 paired study landscapes covering an oilseed rape (OSR) (Brassica napus L.) gradient. In 15 study landscapes faba beans (Vicia faba L.) were grown, paired with respective control landscapes without grain legumes. Results Faba bean cultivation promoted bumblebees (Bombus spp. Latreille), whereas non-Bombus densities were only driven by the local flower cover of SNH. High landscape diversity enhanced wild bee species richness. Faba bean cultivation enhanced the proportions of social wild bees, bees foraging on Fabaceae and slightly of long-tongued bumblebees. Solitary bee proportions increased with high covers of OSR. High local SNH flower covers mitigated changes of mean bee sizes caused by faba bean cultivation. Conclusions Our results show that MFC support specific functional bee groups adapted to their flower morphology and can alter pollinators` functional trait composition. We conclude that management practices need to target the cultivation of functionally diverse crops, combined with high local flower covers of diverse SNH to create heterogeneous landscapes, which sustain diverse pollinator communities.

Incorporating the uncertainty of linguistic-scale reference data to assess accuracy of land-cover maps using fuzzy intervals

2013 ◽  
Vol 34 (11) ◽  
pp. 4008-4024 ◽  
Author(s):  
Pedro Sarmento ◽  
Cidália C. Fonte ◽  
Mário Caetano ◽  
Stephen V. Stehman
Keyword(s):  
Land Cover ◽  
Reference Data ◽  
Land Cover Maps

scholarly journals Key Challenges for Land Use Planning and Its Environmental Assessments in the Abuja City-Region, Nigeria

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 443
Author(s):  
Evidence Chinedu Enoguanbhor ◽  
Florian Gollnow ◽  
Blake Byron Walker ◽  
Jonas Ostergaard Nielsen ◽  
Tobia Lakes
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Assessment ◽  
Land Use Planning ◽  
Environmental Sustainability ◽  
Sub Saharan Africa ◽  
Environmental Assessments ◽  
City Regions ◽  
Sub Saharan ◽  
Land Cover Maps

Land use planning as strategic instruments to guide urban dynamics faces particular challenges in the Global South, including Sub-Saharan Africa, where urgent interventions are required to improve urban and environmental sustainability. This study investigated and identified key challenges of land use planning and its environmental assessments to improve the urban and environmental sustainability of city-regions. In doing so, we combined expert interviews and questionnaires with spatial analyses of urban and regional land use plans, as well as current and future urban land cover maps derived from Geographic Information Systems and remote sensing. By overlaying and contrasting land use plans and land cover maps, we investigated spatial inconsistencies between urban and regional plans and the associated urban land dynamics and used expert surveys to identify the causes of such inconsistencies. We furthermore identified and interrogated key challenges facing land use planning, including its environmental assessment procedures, and explored means for overcoming these barriers to rapid, yet environmentally sound urban growth. The results illuminated multiple inconsistencies (e.g., spatial conflicts) between urban and regional plans, most prominently stemming from conflicts in administrative boundaries and a lack of interdepartmental coordination. Key findings identified a lack of Strategic Environmental Assessment and inadequate implementation of land use plans caused by e.g., insufficient funding, lack of political will, political interference, corruption as challenges facing land use planning strategies for urban and environmental sustainability. The baseline information provided in this study is crucial to improve strategic planning and urban/environmental sustainability of city-regions in Sub-Saharan Africa and across the Global South, where land use planning faces similar challenges to address haphazard urban expansion patterns.

scholarly journals Continental-Scale Land Cover Mapping at 10 m Resolution Over Europe (ELC10)

2021 ◽  
Vol 13 (12) ◽  
pp. 2301
Author(s):  
Zander Venter ◽  
Markus Sydenham
Keyword(s):  
Land Cover ◽  
Atmospheric Correction ◽  
Google Earth ◽  
Tree Planting ◽  
Training Data ◽  
Classification Model ◽  
Night Time ◽  
Continental Scale ◽  
Land Cover Maps ◽  
Sentinel 2

Land cover maps are important tools for quantifying the human footprint on the environment and facilitate reporting and accounting to international agreements addressing the Sustainable Development Goals. Widely used European land cover maps such as CORINE (Coordination of Information on the Environment) are produced at medium spatial resolutions (100 m) and rely on diverse data with complex workflows requiring significant institutional capacity. We present a 10 m resolution land cover map (ELC10) of Europe based on a satellite-driven machine learning workflow that is annually updatable. A random forest classification model was trained on 70K ground-truth points from the LUCAS (Land Use/Cover Area Frame Survey) dataset. Within the Google Earth Engine cloud computing environment, the ELC10 map can be generated from approx. 700 TB of Sentinel imagery within approx. 4 days from a single research user account. The map achieved an overall accuracy of 90% across eight land cover classes and could account for statistical unit land cover proportions within 3.9% (R2 = 0.83) of the actual value. These accuracies are higher than that of CORINE (100 m) and other 10 m land cover maps including S2GLC and FROM-GLC10. Spectro-temporal metrics that capture the phenology of land cover classes were most important in producing high mapping accuracies. We found that the atmospheric correction of Sentinel-2 and the speckle filtering of Sentinel-1 imagery had a minimal effect on enhancing the classification accuracy (< 1%). However, combining optical and radar imagery increased accuracy by 3% compared to Sentinel-2 alone and by 10% compared to Sentinel-1 alone. The addition of auxiliary data (terrain, climate and night-time lights) increased accuracy by an additional 2%. By using the centroid pixels from the LUCAS Copernicus module polygons we increased accuracy by <1%, revealing that random forests are robust against contaminated training data. Furthermore, the model requires very little training data to achieve moderate accuracies—the difference between 5K and 50K LUCAS points is only 3% (86 vs. 89%). This implies that significantly less resources are necessary for making in situ survey data (such as LUCAS) suitable for satellite-based land cover classification. At 10 m resolution, the ELC10 map can distinguish detailed landscape features like hedgerows and gardens, and therefore holds potential for aerial statistics at the city borough level and monitoring property-level environmental interventions (e.g., tree planting). Due to the reliance on purely satellite-based input data, the ELC10 map can be continuously updated independent of any country-specific geographic datasets.

Changes in Land Use and Land Cover Along an Urban-Rural Gradient Influence Floral Resource Availability

2021 ◽  
Author(s):  
Lauren Lynch ◽  
Madeline Kangas ◽  
Nikolas Ballut ◽  
Alissa Doucet ◽  
Kristine Schoenecker ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Resource Availability ◽  
Urban Rural ◽  
Floral Resource
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