CityScapeLab Berlin: A Research Platform for Untangling Urbanization Effects on Biodiversity

Urban biodiversity conservation requires an understanding of how urbanization modulates biodiversity patterns and the associated ecosystem services. While important advances have been made in the conceptual development of urban biodiversity research over the last decades, challenges remain in understanding the interactions between different groups of taxa and the spatiotemporal complexity of urbanization processes. The CityScapeLab Berlin is a novel experimental research platform that allows the testing of theories on how urbanization affects biodiversity patterns and biotic interactions in general and the responses of species of conservation interest in particular. We chose dry grassland patches as the backbone of the research platform because dry grasslands are common in many urban regions, extend over a wide urbanization gradient, and usually harbor diverse and self-assembled communities. Focusing on a standardized type of model ecosystem allowed the urbanization effects on biodiversity to be unraveled from effects that would otherwise be masked by habitat- and land-use effects. The CityScapeLab combines different types of spatiotemporal data on (i) various groups of taxa from different trophic levels, (ii) environmental parameters on different spatial scales, and (iii) on land-use history. This allows for the unraveling of the effects of current and historical urban conditions on urban biodiversity patterns and the related ecological functions.BMBF, 01LC1501, BIBS-Verbund: Bridging in Biodiversity Science (BIBS

Active Amplification of the Terrestrial Albedo to Mitigate Climate Change: An Exploratory Study

This study explores the potential to enhance the reflectance of solar insolation by the human settlement and grassland components of the Earth's terrestrial surface as a climate change mitigation measure. Preliminary estimates derived using a static radiative transfer model indicate that such efforts could amplify the planetary albedo enough to offset the current global annual average level of radiative forcing caused by anthropogenic greenhouse gases by as much as 30 percent or 0.76 W/m2. Terrestrial albedo amplification may thus extend, by about 25 years, the time available to advance the development and use of low-emission energy conversion technologies which ultimately remain essential to mitigate long-term climate change. However, additional study is needed to confirm the estimates reported here and to assess the economic and environmental impacts of active land-surface albedo amplification as a climate change mitigation measure.Comment: 21 pages, 3 figures. In press with Mitigation and Adaptation Strategies for Global Change, Springer, N

Land cover maps for environmental modeling at multiple scales

As described in the ECOCHANGE proposal, Task01.02.02 “Map production and aggregation”, two major products are generated within this WP. Firstly, land cover maps at high spatial resolutions will be produced for the European Union and for the reference years of 1960, 1990 and 2000. Secondly, thematic and spatial aggregated products will be derived at coarser spatial resolutions in order to synthesize the fragmentation and variability within coarser cells for biodiversity assessment and modelling. The name of the official deliverable is D01.02.01 “Land cover maps for environmental modelling at multiple scales” and includes this report, the digital land cover products and an interactive website to view the data at all thematic and spatial scales

Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products

In this study, using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC (vegetation, wetlands and others only), we studied spatial and areal inconsistencies in the three most recent multi-resource land cover products in a complex mountain-oasis-desert system and quantitatively discussed the uncertainties in classification system conversion. This is the first study to compare these products based on terrain and to quantitatively study the uncertainties in classification system conversion. The inconsistencies and uncertainties decreased from high to low levels of aggregation (IGBP-17 to TC) and from mountain to desert areas, indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. The overall areal inconsistency in the comparison of the FROM-GLC and GlobCover 2009 datasets is the smallest among the three pairs, but the smallest overall spatial inconsistency was observed between the FROM-GLC and MODISLC. The GlobCover 2009 had the largest conversion uncertainties due to mosaic land cover definition, with values up to 23.9%, 9.68% and 0.11% in mountainous, oasis and desert areas, respectively. The FROM-GLC had the smallest inconsistency, with values less than 4.58%, 1.89% and 1.2% in corresponding areas. Because the FROM-GLC dataset uses a hierarchical classification scheme with explicit attribution from the second level to the first, this system is suggested for producers of map land cover products in the future

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

Linking remote-sensing estimates of land cover and census statistics on land use to produce maps of land use of the conterminous United States

Human use of the land has a large effect on the structure of terrestrial ecosystems and the dynamics of biogeochemical cycles. For this reason, terrestrial ecosystem and biogeochemistry models require moderate resolution (e.g., ≤0.5°) information on land use in order to make realistic predictions. Few such data sets currently exist. To create a land use data set of sufficient resolution, we developed models relating land cover data derived from optical remote sensing and a census database on land use for the conterminous United States. The land cover product used was from the International Geosphere-Biosphere Programme DISCover global product, derived from 1 km advanced very high resolution radiometer imagery, with 16 land cover classes. Land use data at state-level resolution came from the U.S. Department of Agriculture\u27s Major Land Uses database, aggregated into four general land use categories: Cropland, Pasture/Range, Forest, and Other. We developed and applied models relating these data sets to generate maps of land use in 1992 for the conterminous United States at 0.5° spatial resolution

Artificial Light Increases Local Predator Abundance, Predation Rates, and Herbivory.

Human activity is rapidly increasing the radiance and geographic extent of artificial light at night (ALAN) leading to alterations in the development, behavior, and physiological state of many organisms. A limited number of community-scale studies investigating the effects of ALAN have allowed for spatial aggregation through positive phototaxis, the commonly observed phenomenon of arthropod movement toward light. We performed an open field study (without restricted arthropod access) to determine the effects of ALAN on local arthropod community composition, plant traits, and local herbivory and predation rates. We found strong positive phototaxis in 10 orders of arthropods, with increased (159% higher) overall arthropod abundance under ALAN compared to unlit controls. The arthropod community under ALAN was more diverse and contained a higher proportion of predaceous arthropods (15% vs 8%). Predation of immobilized flies occurred 3.6 times faster under ALAN; this effect was not observed during the day. Contrary to expectations, we also observed a 6% increase in herbivory under ALAN. Our results highlight the importance of open experimental field studies in determining community-level effects of ALAN