No abstract

Private gardens make up large parts of urban green space. In contrast to public green spaces, planning and management is usually uncoordinated and independent of municipal planning and management strategies. Therefore, the potential for private gardens to provide ecosystem services and habitat and to function as corridors for wildlife is not fully utilized. In order to improve public knowledge on gardens, as well as provide individual gardeners with information on what they can contribute to enhance ecosystem services provision, we developed a GIS-based web application for the city of Braunschweig (Germany): the ‘GartenApp’ (garden app). Users of the app have to outline their garden on a web map and provide information on biodiversity related features and management practices. Finally, they are asked about observations of well recognizable species in their gardens. As an output, the gardeners are provided with an estimate of the ecosystem services their garden provides, with an evaluation of the biodiversity friendliness, customized advice on improving ecosystem services provision, and results from connectivity models that show gardeners the role of their garden in the green network of the city. In this paper, we describe the app architecture and show the first results from its application. We finish with a discussion on the potential of GIS-based web applications for urban sustainability, planning and conservation.

The decline of pollinating insects in agricultural landscapes proceeds due to intensive land use and the associated loss of habitat and food sources. The feeding of those insects depends on the spatial and temporal distribution of nectar and pollen as food resource. Hence, to protect insect biodiversity, a spatio-temporal assessment of food quantity of their habitats is necessary. Therefore, sufficient data on traits of floral resources are required. As floral resources’ traits of plants are important to quantify food availability, we present two databases, the FloRes Database (Floral Resources Database) and the raw database, from where FloRes was derived. Both databases contain the plant traits: (1) flowering period, (2) floral-unit density per day, (3) nectar volume per floral unit per day, (4) sugar content per floral unit, (5) sugar concentration in nectar, (6) pollen mass or volume per floral unit and per day, (7) protein content of pollen and (8) corolla depth. All traits were sampled from literature and online databases. The raw database consists of 702 specified plant species, 138 unspecified species 37 species (spec., sp), 22 species pluralis (spp) and, for 79, only the genus was identified) and two species complexes (agg.). Those 842 taxa belong to 488 genera and 102 families. Finally, only 27 taxa have a complete set of traits, too few for a sufficient assessment of spatio-temporal availability of floral food-resources. As information on floral resources is scattered throughout many publications with different units, we also present our multistep workflow implemented in five consecutive R-scripts. The multistep workflow standardises the trait units of the raw database to comparable entities with identical units and aggregates them on a reasonable taxonomic level into the second application database, the FloRes Database. Finally, the FloRes Database contains aggregated information of traits for 42 taxa and, when corolla depth is excluded, for 72 taxa. This is the first attempt to gather these eight traits from different literature sources into one database with a multistep workflow. The publication of the multistep workflow enables the users to extend the FloRes Database on their own demands with other literature data or newly-gathered data to improve quantification of food resources. Especially, the combination of pollen, nectar and the open flowers per square metre is, as far as we know, a novelty. The FloRes Database can be used to evaluate the quantity of food-resource habitats available for pollinators, for example, to compare seed mixtures of agri-environmental measures, such as flower strips, considering flower phenology on a daily basis.