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Knowledge about the biogeographic affinities of the world’s tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world’s tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.
Global change effects on biodiversity and human wellbeing call for improved long-term environmental data as a basis for science, policy and decision making, including increased interoperability, multifunctionality, and harmonization. Based on the example of two global initiatives, the International Long-Term Ecological Research (ILTER) network and the Group on Earth Observations Biodiversity Observation Network (GEO BON), we propose merging the frameworks behind these initiatives, namely ecosystem integrity and essential biodiversity variables, to serve as an improved guideline for future site-based long-term research and monitoring in terrestrial, freshwater and coastal ecosystems. We derive a list of specific recommendations of what and how to measure at a monitoring site and call for an integration of sites into co-located site networks across individual monitoring initiatives, and centered on ecosystems. This facilitates the generation of linked comprehensive ecosystem monitoring data, supports synergies in the use of costly infrastructures, fosters cross-initiative research and provides a template for collaboration beyond the ILTER and GEO BON communities.
Since its founding in 1993 the International Long-term Ecological Research Network (ILTER) has gone through pronounced development phases. The current network comprises 44 active member LTER networks representing 700 LTER Sites and ~ 80 LTSER Platforms across all continents, active in the fields of ecosystem, critical zone and socio-ecological research. The critical challenges and most important achievements of the initial phase have now become state-of-the-art in networking for excellent science. At the same time increasing integration, accelerating technology, networking of resources and a strong pull for more socially relevant scientific information have been modifying the mission and goals of ILTER. This article provides a critical review of ILTER's mission, goals, development and impacts. Major characteristics, tools, services, partnerships and selected examples of relative strengths relevant for advancing ILTER are presented. We elaborate on the tradeoffs between the needs of the scientific community and stakeholder expectations. The embedding of ILTER in an increasingly collaborative landscape of global environmental observation and ecological research networks and infrastructures is also reflected by developments of pioneering regional and national LTER networks such as SAEON in South Africa, CERN/CEOBEX in China, TERN in Australia or eLTER RI in Europe. The primary role of ILTER is currently seen as a mechanism to investigate ecosystem structure, function, and services in response to a wide range of environmental forcings using long-term, place-based research. We suggest four main fields of activities and advancements for the next decade through development/delivery of a: (1) Global multi-disciplinary community of researchers and research institutes; (2) Strategic global framework and strong partnerships in ecosystem observation and research; (3) Global Research Infrastructure (GRI); and (4) a scientific knowledge factory for societally relevant information on sustainable use of natural resources.
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.