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12 results for “Ecosystem classification”
Landscape Ecosystem Classification Soils and Vegetation Plots Data at the University of Michigan Biological Station, Pellston, Michigan from 1987 to 2015 remeasurements
Landscape ecosystems are a means of understanding the spatial patterns of and the functional interrelationships in forest ecosystems. Landscape ecosystem research is a multifactor, holistic approach to identifying, classifying, describing, and mapping terrain ecosystems. Abiotic and biotic factors are integrated in the field to distinguish repeating units similar in ecological structure and function. Landscape ecosystems are identified by simultaneous integration of physiographic, soil, and vegetation information. The more stable components--physiography and soil--largely determine local climate, and water and nutrient relations, and thus the interrelationships of physiography and soil form the foundation of a landscape ecosystem classification. Vegetation is seen as a phytometer that integrates the many abiotic factors and their interactions, and therefore reflects differences in ecosystem structure and function. When the three main ecosystem factors are analyzed simultaneously, one can perceive interrelationships that result in ecologically meaningful differences among segments of the ecosphere. Landscape ecosystems are spatial; they are volumetric, multi-dimensional segments of earth, whose components include soil, water, atmosphere, solar radiation, and biota. These segments can be identified, classified, described, and mapped at various scales. From the years of 1988 to 2001, various graduate students of Burton V. Barnes completed their masters thesis and dissertations in this pursuit. The attached data set is a culmination of these individual work. Each plot has measurements at various scales within the 10 by 30 meet plot. A stratified random design was used to locate plot locations. The random design was stratified by major and minor landforms in the region. All trees within the plot where identified and dbh was measured. All individual shrubs where identified and abundance was counted within the entire plot. Soils pits locations for each plot where selected
Taxonomy, distribution and classification of ecosystem-types, integrating the recent IUCN function-based typology and local conceptualizations
<p>1. Introduction:</p> <p>This dataset is a work in progress. It compiles data gathered on ecosystem-types and their distribution based on a series of field studies led by the author, in Seychelles and West and Central Africa (Senterre 2014, Senterre & Wagner 2014, Senterre 2016, Senterre et al. 2017, 2019, 2020, 2021a, 2022). The aims of this dataset are:</p> <p>a. To share in an explicit and transparent way data on proposed taxonomies of ecosystems, i.e. conceptualizations of ecosystem-types, including explicit ecosystem names and management of synonymies.</p> <p>b. To develop ecosystem red listing based on transparent and falsifiable distribution raw data, combining distribution modeling (maps) and in situ observation of individual stand occurrences.</p> <p>c. To illustrate in detail how to deal with ecosystem data following the approach described in Senterre et al. (2021b) (i.e. "ecosystemology" approach).</p> <p>d. To integrate the above approach with the newly developed function-based typology of ecosystems (Keith et al. 2022), therefore contributing to bridging the persistent gap between the global and the local scales in ecosystem descriptions and classifications.</p> <p> </p> <p>2. Context and versions:</p> <p>This dataset was initially planned for publication on GBIF (Global Biodiversity Information Facility), as part of a project developed for the review of Key Biodiversity Areas in Seychelles: "Mainstreaming recent species and ecosystem distribution data into Key Biodiversity Areas assessments in Seychelles" (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>).</p> <p>In the first version of the GBIF dataset (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>), we proposed an analysis of the potential 'core' and 'extension' files available in GBIF for a publication of ecosystem-type names (and synonymies) and their corresponding occurrences recorded from field observations. This is an original analysis of taxonomic principles managed entirely at the scale of local observable objects, and their history of identifications or interpretations.</p> <p>Toward the end of the above-mentioned GBIF project, considering the limitations and gaps currently present in GBIF, it was decided to restrict the GBIF dataset to a simple 'metadata' entry and to publish the complete version of this dataset in Zenodo. This allows to include all tables needed, as well as all required fields without having to accommodate them within the limited GBIF structure (see metadata description on GBIF for more details). The fields of the tables published here are described in the GBIF metadata entry and in the ecosystemology paper (Senterre et al. 2021b).</p> <p> </p> <p>3. New development on typology aspects:</p> <p>In addition, considering that the new IUCN global typology of ecosystems is now published (Keith et al. 2022), we have reviewed in detail the possibility of integration of ecosystems conceptualized using our ecosystemology approach within the new IUCN typology. The result of this analysis is being considered for a publication, and this Zenodo dataset would then be published in full (i.e. including all typology aspects) as supplementary materials. In the meantime, I would be happy to discuss any of these aspects with whoever is interested.</p> <p> </p> <p>4. Access to ecosystem data for conservation actors:</p> <p>Finally, the actual data (published here) on ecosystem-types, their names, synonymies, classification, distribution, and red list status are compiled into a format that we designed to be useful to conservation actors in the form of interactive webpages (produced with R as shiny apps). This development is based on very limited resources, and the author is still quite new to R, so any help or feedback on ways to improve the scripts would be very much welcomed.</p> <p>The interactive page is available here (currently filtered to Seychelles' data only, although the dataset contains data beyond the Seychelles): https://shiny.bio.gov.sc/bioeco/</p> <p>The R scripts are available on Github: https://github.com/bsenterre/ecosystemology</p> <p> </p> <p>5. Tables contained in this dataset:</p> <p>a. Ecosystem taxonomy tables:</p> <p>ecoSpecies: Contains the list of all ecosystem-type names with their unique identifier.</p> <p>ecoOccurrences: Contains the list of individual stand occurrences, including ecosystem characters as standardized in Senterre et al. (2021b; i.e. virtual ecosystem specimen).</p> <p>ecoSpeciesProfiles: Contains basic metadata on ecosystem-types, such as their Red List evaluations.</p> <p>ecoIdentifications: Contains all the different interpretations/identifications (referring to the table ecoSpecies or to higher levels of classification, see below) made on the stands observed in the ecoOccurrences table.</p> <p> </p> <p>b. Ecosystem typology tables (TO BE ADDED LATER):</p> <p>IUCNL3: This is just a transcription, as is, of the IUCN global typology version 2.1.</p> <p>IUCNL3BIOCrossover: This table defines and comments correspondences between BIOL2 (the level 2 of the typology used by us) and the IUCN typology L3 (level 3).</p> <p>BIOL2: This is a variation based on the IUCN typology, here our level 2.</p> <p>BIOL3: This is a variation based on the IUCN typology, here our level 3.</p> <p>BIOL4: This is a variation based on the IUCN typology, here our level 4.</p> <p>ecoGenus: This is a general type of stand (thus excluding any regional ecosystem connotation), defined at a local scale and never combined with any geographic connotation (see ecosystemology paper: Senterre et al. 2021b).</p> <p>ecoFamily: This is a generalized version of the ecoGenus (i.e. still excluding any regional, sub-regional or geographic aspect).</p> <p>ecoOrder: This is a further generalized version of the ecoGenus (see also Senterre et al. 2020).</p> <p>lifeZone: This is a basic and incomplete list of life zones as defined following the Holdridge (1967) approach, with some additional elements proposed in Senterre et al. (2021b).</p> <p> </p> <p>6. Literature cited:</p> <p>Holdridge, L. R. 1967. Life zone ecology. Tropical Science Center, San Jose, Costa Rica.</p> <p>Keith, D. A., J. R. Ferrer-Paris, E. Nicholson, M. J. Bishop, B. A. Polidoro, E. Ramirez-Llodra, M. G. Tozer, J. L. Nel, R. Mac Nally, E. J. Gregr, K. E. Watermeyer, F. Essl, D. Faber-Langendoen, J. Franklin, C. E. R. Lehmann, A. Etter, D. J. Roux, J. S. Stark, J. A. Rowland, N. A. Brummitt, U. C. Fernandez-Arcaya, I. M. Suthers, S. K. Wiser, I. Donohue, L. J. Jackson, R. T. Pennington, T. M. Iliffe, V. Gerovasileiou, P. Giller, B. J. Robson, N. Pettorelli, A. Andrade, A. Lindgaard, T. Tahvanainen, A. Terauds, M. A. Chadwick, N. J. Murray, J. Moat, P. Pliscoff, I. Zager, and R. T. Kingsford. 2022. A function-based typology for Earth’s ecosystems. . Nature 610:513–518. doi:10.1038/s41586-022-05318-4.</p> <p>Senterre, B. 2014. Mapping habitat-types within the Hummingbird site at Dugbe (Liberia, West Africa). Consultancy Report, Missouri Botanical Garden. P. 56. https://doi.org/10.13140/RG.2.2.32628.48003.</p> <p>Senterre, B. 2016. Habitat-type ground-truthing and assessment of ecosystem conservation value in the Bel Air Alufer mining site (Guinea, West Africa), with recommendations for improving the draft map of land cover types. Consultancy Report, Missouri Botanical Garden, A study conducted for Alufer Mining Limited. P. 54.</p> <p>Senterre, B., E. Bidault, and T. Stévart. 2019. Identification et évaluation des écosystèmes menacés du Mont Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 106. https://doi.org/10.13140/RG.2.2.13242.93129.</p> <p>Senterre, B., E. Bidault, T. Stévart, and P. P. Lowry II. 2020. Assessment of Key Biodiversity Areas in the Lofa-Gola-Mano & Nimba complexes (West Africa) using ecosystem criteria. Final Report, Missouri Botanical Garden. P. 146. 10.13140/RG.2.2.17934.89924.</p> <p>Senterre, B., E. Bidault, T. Stévart, M. Wagner, and P. Lowry. 2017. Mapping habitat-types in south-east Kouilou (Republic of Congo). Consultancy Report, Missouri Botanical Garden (MBG), Africa and Madagascar Department, St. Louis, Missouri, USA. P. 163.</p> <p>Senterre, B., R. M. Bristol, G. Gendron, and E. Henriette. 2021a. Fine-tuning conservation priorities in Seychelles at the landscape scale, using global KBA guidelines with both species and ecosystem criteria. Consultancy Report, United Nations Development Programme, GOS/UNDP/GEF Programme Coordination Unit, Victoria, Seychelles.</p> <p>Senterre, B., P. P. Lowry II, E. Bidault, and T. Stévart. 2021b. Ecosystemology: a new approach toward a taxonomy of ecosystems. . Ecological Complexity 47:100945. doi:https://doi.org/10.1016/j.ecocom.2021.100945.</p> <p>Senterre, B., A.-H. Paradis, E. Bidault, T. Stévart, and P. P. Lowry II. 2022. Qualité et distribution des savanes montagnardes du Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 73. http://dx.doi.org/10.13140/RG.2.2.13433.34401.</p> <p>Senterre, B., and M. Wagner. 2014. Mapping Seychelles habitat-types on Mahé, Praslin, Silhouette, La Digue and Curieuse. Consultancy Report, Government of Seychelles, United Nations Development Programme, Victoria, Seychelles. P. 119. https://doi.org/10.13140/RG.2.1.4558.6009.</p>
Digital Ecosystem Service Classification
<p>Application of digital ecosystem criteria on digital ecosystem service candidates, to classify these candidates as digital ecosystem services or non digital ecosystem services.</p> <p> </p> <p>Note: In case one criterium for a digital ecosystem service candidate is not fulfilled, the remaining ones have not been checked, indicated through "n/a".</p>
Assessing the peatland hummock-hollow classification framework using high-resolution elevation models: Implications for appropriate complexity ecosystem modelling
<p>The hummock-hollow classification framework used to categorize peatland ecosystem microtopography is pervasive throughout peatland experimental designs and current peatland ecosystem modelling approaches. However, identifying what constitutes a representative hummock-hollow pair within a site and characterizing hummock-hollow variability within or between peatlands remains largely unassessed. Using structure-from-motion (SfM), high resolution digital elevation models (DEM) of hummock-hollow microtopography were used to: 1) examine how much area needs to be sampled to characterize site-level microtopographic variation; and 2) examine the potential role of microtopographic shape/structure on biogeochemical fluxes using data from 9 northern peatlands. This data set is comprised of plot DEMs, supporting data, and the script used to analyze data and produce figures presented in the manuscript submitted to Biogeosciences Discussion "ASSESSING THE PEATLAND HUMMOCK-HOLLOW CLASSIFICATION FRAMEWORK USING HIGH-RESOLUTION ELEVATION MODELS: IMPLICATIONS FOR APPROPRIATE COMPLEXITY ECOSYSTEM MODELLING".</p>
Classification of pictures taken from Flickr and iNaturalist for cultural ecosystem services in Minho Region Portugal
<p>This is classification dataset of photographs from Flirck and iNaturalist applied to buffer 500 meters of main cours rivers Minho, Lima and Cávado in Minho Region (NW Portugal), in between the years 2018- 2019 for cultural ecosystem services studies. Four categories assigned as follows: i) landscape; ii) historical heritage; iii) recreation and river beaches; iv) biodiversity.</p>
Supplementary material 3 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
The area and share of main ecosystem types and sub ecosystem types (ETs, see Tab. 1)) in the German land cover model (LBM-DE) for the time periods 2012, 2015 and 2018. Linear elements such as small scale structures and infrastructures from the topographic-cartographic Information system (ATKIS) were added to the land cover model.
Supplementary material 4 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
Tab. D: Detailed matrix of pre- and post-use of settlement and transportation areas in Germany in the period 2013-2018 in hectare per day (ha/d). (Data source: IOER)
Supplementary material 1 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
Proposal of a classification system for ecosystem types (ETs) in Germany, assignment to the European ecosystem types according to EUNIS and to the CLC types of the database LBM-DE
Supplementary material 2 from: Grunewald K, Schweppe-Kraft B, Syrbe R-U, Meier S, Krüger T, Schorcht M, Walz U (2020) Hierarchical classification system of Germany's ecosystems as basis for an ecosystem accounting – methods and first results. One Ecosystem 5: e50648. https://doi.org/10.3897/oneeco.5.e50648
Supplementation of ecosystem types (ETs) by more differentiated spatially and non-spatially explicit data (system of assignment of biotope and habitat types relevant for nature conservation to ETs
Springs ecosystem classification supplementary information
<p>Springs ecosystems are globally abundant, geomorphologically diverse, and bio-culturally productive, but are highly imperiled by anthropogenic activities. More than a century of scientific discussion about the wide array of ecohydrological factors influencing springs has been informative, but has yielded little agreement on their classification. This lack of agreement has contributed to the global neglect and degradation of springs ecosystems by the public, scientific, and management communities. Here we review the historical literature on springs classification variables, concluding that site-specific source geomorphology remains the most diagnostic approach. We present a conceptual springs ecosystem model that clarifies the central role of geomorphology in springs ecosystem development, function, and typology. We present an illustrated dichotomous key to terrestrial (non-marine) springs ecosystem types and subtypes, and describe those types. We identify representative reference sites, although data limitations presently preclude selection of continentally or globally representative reference springs of each type. We tested the classification key using data from 244 randomly selected springs of 13 major types that were inventoried in North America. The dichotomous key correctly identified springs type in 87.5% of the cases, with discrepancies primarily due to differentiation of primary versus secondary typology, and insufficient inventory team training. Using that information, we identified sources of confusion and clarified the key. Among the types that required more detailed explanation were hypocrenes, springs, in which groundwater is expressed through phreatophytic vegetation. Overall, springs biodiversity and ecosystem complexity are due, in part, to the co-occurrence of multiple intra-springs microhabitats. We describe microhabitats that are commonly associated with different springs types, reporting at least 13 microhabitats, each which can support discrete biotic assemblages. Interdisciplinary agreement on basic classification is needed to enhance scientific understanding and stewardship of springs ecosystems, the loss and degradation of which constitute a global conservation crisis.</p> <p>We provide data on springs ecosystem classification using non-sensitive springs data selected in an unbiased fashion from Springs Online (springsdata.org) to test the springs classificaiton dichotomous key and description (attached as separate pages to this dataset). </p>
Raw Data for 'A Systematic Classification and Labelling Approach to Support a Circular Economy Ecosystem for NdFeB-Type Magnet'
<p>Raw Data for the paper "A Systematic Classification and Labelling Approach to Support a Circular Economy Ecosystem for NdFeB-Type Magnet" </p>
Springs ecosystem classification supplementary information
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