This dataset contains the municipalities (surface objects), concerned by the industrial and territorial ecology (EIT) procedures of New Aquitaine.

PLEASE NOTE: this dataset is not exhaustive on the perimeter of New Aquitaine, it concerns the perimeters of the former regions Limousin and Poitou-Charentes.

Based on a systemic approach, industrial and territorial ecology (EIT) is an operational approach that draws on natural ecosystems to strive for optimal material and energy management: the industrial system can be considered as a particular form of ecosystem.

Thus, like the functioning of food chains in the natural environment, waste and co-products of one activity can become a resource for another activity. Companies can reuse their production residues (vapours, co-products, exhaust gas, effluents, waste, etc.) between themselves, or with local authorities, and thus limit pollution, the collection of resources, the production of waste and energy consumption.

Le réseau écologique régional a été réalisé par un bureau d'études au cours de l'année 2009 pour la région Centre-Val de Loire avec l'appui d'un groupe de pilotage élargi (Etat, experts naturalistes, associations, ...). L'analyse a été réalisée à travers une analyse SIG menée à partir de la base de données Corine Land Cover 2006. Les restitutions ont un niveau de précision d'environ 1/100 000. Ce jeu de données contient les écopaysages qui ont été définis lors de cette étude. Fiche de métadonnées

Data tables for Birds Collisions of the knowledge update related to the offshore wind ecological programme.

Data (and versioning) could also be accessed via the dedicated data repository of this project at WOZEP.

This dataset is about politicians and is filtered where the political party is Europe Ecologie Les Verts (France), featuring 10 columns including birth date, country, death date, gender, and Instagram followers. The preview is ordered by birth date (descending).

A vector GIS dataset of candidate areas for terrestrial ecological restoration based on landscape context. The dataset was created using NLCD 2011 (www.mrlc.gov) and morphological spatial pattern analysis (MSPA) (http://forest.jrc.ec.europa.eu/download/software/guidos/mspa/). There are 13 attributes for the polygons in the dataset, including presence and length of roads, candidate area size, size of surround contiguous natural areas, soil productivity, presence and length of road, areas suitable for wetland restoration, and others. This dataset is associated with the following publication: Wickham, J., K. Riiters, P. Vogt, J. Costanza, and A. Neale. An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context. RESTORATION ECOLOGY. Blackwell Publishing, Malden, MA, USA, 25(6): 894-902, (2017).

Revision Note: Please note that this dataset has been revised and is available from the Land Information Ontario (LIO) Warehouse.

Eco Regions are areas of land within which the response of vegetation to the features of landform follows a consistent pattern. An ecoregion (ecological region) is an ecologically and geographically defined area that is smaller than a bioregion, which in turn is smaller than an ecozone.

Various systems exist to delineate natural regions based on ecological factors. MNR defines ecological units on the basis of bedrock, climate, physiography and corresponding vegetation, creating an Ecological Land Classification (ELC) system.

The ELC of Ontario was revised by the ELC Working Group in 2000 to better reflect the ELC system originally developed by Angus Hills (1959 and later revisions). This dataset was revised to take account new information and new technology, while maintaining Hills's original concepts. For further information on the rationale for the revisions, refer to Ecoregions of Ontario Modifications to Angus Hills Site Regions and Districts, Revisions and Rationale, Crins and Uhlig 2000 . In 2002, the spatial data was updated using NRVIS drainage polygon data including islands from Great Lakes, St. Lawrence, and Ottawa River, and more detailed shoreline data. NTS mapping was also used to delineate the northern, eastern (Quebec border), and western (Manitoba border) boundaries of the province. In 2006, the shorelins of the Great Lakes, St. Lawrence, and Ottawa River were removed and the effected polygon boundaries were extended out over the water bodies to the extent of the provincial boundary. This modification was undertaken to provide a more generic data layer which is intended to be used as a selection tool, and as a backdrop upon which evolving and multi scalar hydorology layers may be overlain or intersected.

Presentation made by Wendy Gram et al. as part of the "Bringing Research Data to the Ecology Classroom: Opportunities, Barriers, and Next Steps” Session at the Ecological Society of America annual meeting, August 8th, 2017, Portland Oregon

Marine organisms show population structure at a relatively fine spatial scale, even in open habitats. The tools commonly used to assess subtle patterns of connectivity have diverse levels of resolution. We have assessed the discriminatory power of genetic markers and otolith shape to reveal the population structure of the common sole (Solea solea), living in the Eastern English Channel stock off France and the UK. The aims were to (i) inform the short and long-term population structure by comparing genetic and otolith shape approaches, and (ii) combine the tracers in a single analysis to assess the interest of a combined approach. First, we applied Single Nucleotide Polymorphisms to assess population structure at an evolutionary scale. Then, we tested for spatial segregation of the subpopulations using otolith shape as an integrative tracer of life history. Finally, we combined the genotypes and otolith phenotypes in a supervised machine learning framework to probabilistically assign adults to subpopulations. Genetic assignments and otolith shape analyses provided congruent results suggestive of a metapopulation structure for the common sole of the Eastern English Channel. Despite congruent results from genetics and otolith shape, the combined analysis did not provide realistic reallocation probabilities. Our findings support the idea that independent analyses of tracers provide fruitful insights and that a combined approach should be preferred when a large and balanced number of fish is available for each tracer analyzed.

Ecology

## Overview

Ecology is a dataset for object detection tasks - it contains Containers annotations for 355 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Download: Density of indicative threatened ecological community distributions (arcgis.com)Web service: species/ec_density (ImageServer)The density of indicative threatened ecological community distributions is derived from the Department's ecological communities of national environmental significance data. Threatened Ecological Communities (TEC) distributions contain three categories to indicate where their habitat is known, likely or may occur across Australia. The spatial input data was filtered using the following criteria: 1. Distributions for EPBC Act (1999) listed TECs that are Matters of National Environmental Significance (critically endangered or endangered).2. Contains ‘known’ and/or ‘likely to occur’ habitat categories. 3. Marine TECs are includedThe number of overlaps for each distribution in the selected feature set were counted and gridded to a 0.01 decimal degree (~1km) cell size. Note projecting the data will alter the cell size. The source distribution for each TEC is determined independently of others and is indicative in nature. As such, a count higher than one may indicate:• TECs have been mapped in the same habitat or • TECs are mapped adjacent within the same 1km grid cell or • TECs distributions have been mapped at different scales or levels of detail Given the indicative nature of the source data which includes data of a range of quality and currency, this output should be used as a guide to the location of TECs across the country.The selection of TEC distributions for inclusion in the count is based on the EPBC Act list of TECs and spatial data in the Department enterprise GIS as at the revision date in the metadata. Current EPBC Act listed TECs are described in the Species Profiles and Threats application (SPRAT: https://www.environment.gov.au/cgi-bin/sprat/public/sprat.pl).

In response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterized in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs.

R files are included to describe data processing and analyses conducted within Wormley, A. S., Kwon, J. Y., Barlev, M., & Varnum, M. E. W. How much cultural variation is explained by ecology?

From 1986 to 2000, a major ecological inventory program was carried out in the forests of southern Quebec in order to describe the diversity of forest ecosystems. In total, 28,425 ecological observation points (POE) were established on a territory covering 760,000 km2, located between 45° and 53° N latitude and 57° and 80° W longitude. The POE is a circular sampling unit that covers an area of 400 m². It collects data on the characteristics of forest stand (composition, structure), soil (texture, deposit, drainage), and topography, as well as location information. The coverage of each plant species in the plot is estimated visually. A detailed description of a soil profile is available in approximately 35% of POEs. The ecological classification elements of POEs (groups of indicator species, forest types, potential vegetation, ecological types, etc.) are determined using computerized identification keys using data on vegetation and the physical environment. The criteria used for this ecological classification are those presented in the guides for the recognition of ecological types. The levels of the ecological classification system of the territory are also determined for each POE.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Part of the course "Applications of stable isotopes in marine ecosystems", taught by Gilles Lepoint & Loïc Michel at University of Liège (Belgium).

To help increase understanding of synthetic aperture radar (SAR) and promote its use as a powerful tool for terrestrial ecologists, ASF offers examples of data that can be used for a variety of purposes. The data are subsets for selected field sites — such as flux tower locations — from the PALSAR (Phased Array L-band Synthetic Aperture Radar) sensor flown on the Advanced Land Observing Satellite (ALOS). This dataset provides SAR images for 42 selected sites from various terrestrial-ecology and meteorological-monitoring networks, including FLUXNET, AmeriFlux, Long Term Ecological Research (LTER), and the Greenland Climate Network (GC-Net).Click to view Figure 1: SAR images for (a) Walker Branch Watershed, Tennessee, and (b) Niwot Ridge, Colorado, sites. In SAR visualizations for land use, green usually represents tree canopy, pink is crop or barren soil, black is water, and grays are low vegetation. The star icon indicates the location of the field site. Terrestrial Ecology OverviewThe Terrestrial Ecology products were created using ALOS PALSAR data. To make the SAR scenes more user friendly, the polarization data was classified as reds, greens, and blues in the image. The ranging data are terrain-corrected by a process that assigns the ranging values to geographic coordinates by utilizing a digital surface model (DSM). High-resolution DSM data are not available for the entire planet and existing data at high latitudes is problematic, especially in areas of very little terrain relief, such as sheet glaciers. To use a consistent DSM for this project and all of the sites being investigated, the DSM data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imaging instrument was used for the terrain correction.The Terrestrial Ecology products are offered in a GeoTIFF format in Universal Transverse Mercator (UTM) projection and 15-meter resolution. Each scene is available in GeoTIFF format with an XML file containing metadata. A PDF document file is also available for each site and contains image-specific metadata, image analysis notes about channel assignments and colors, and a thumbnail of the SAR image. For sites with multiple images, only one thumbnail is included as images are quite similar in appearance. Collection Boundaries(All latitude and longitude given in decimal degrees)Westernmost LongitudeEasternmost LongitudeNorthernmost LatitudeSouthernmost Latitude-156.665-29.999778.5266-10.7618 Temporal CoverageSAR subsets were extracted for the dates shown in the table below. The exact time of the image is included in the documentation. The selected sites, the name of their respective compressed image files, the date(s), and projections of the SAR subset image(s) are provided. Site NameSite NumberImage Date(s)Image ProjectionArctic LTER (ARC1)7897/11/2010WGS84, UTM, Zone 6NBaltimore Ecosystem Study (BES1)9457/28/2009WGS84, UTM, Zone 18NBartlett Experimental Forest8232007/07/20, 2007/09/04, 2007/10/20, 2008/06/06, 2009/07/25, 2009/10/25, 2010/07/28, 2010/09/12, 2010/10/28WGS84, UTM, Zone 19NBOREAS NSA — Old Black Spruce2349/24/2010WGS84, UTM, Zone 14NBOREAS SSA — Young Aspen2857/19/2010WGS84, UTM, Zone 13NBritish Columbia — Campbell River — Clearcut Site1216/5/2010WGS84, UTM, Zone 10NBritish Columbia — Campbell River — Mature Forest Site1206/5/2010WGS84, UTM, Zone 10NBuffalo13 ESE — SDSU Antelope Research Station (Calving Pasture Site)106010/2/2010WGS84, UTM, Zone 13NCascades/H.J. Andrews LTER — Oregon80910/25/2008WGS84, UTM, Zone 10NChamela Biological Station64410/10/2010WGS84, UTM, Zone 13NCP1272311/10/2009WGS84, UTM, Zone 23NDuke Forest Hardwoods8689/25/2010WGS84, UTM, Zone 17NHarvard Forest EMS Tower (HFR1)8862007/08/23, 2010/08/31, 2010/10/16WGS84, UTM, Zone 18NHJ Andrews Aeronet Sunphotometer (AND1)103310/25/2010WGS84, UTM, Zone 10NHowland Forest (Main Tower)89010/18/2010WGS84, UTM, Zone 19NHumboldt Gl.27316/29/2010WGS84, UTM, Zone 21NJuniper Woodland Site10507/20/2010WGS84, UTM, Zone 12NKULU27382008/05/21, 2008/07/06, 2008/08/21WGS84, UTM, Zone 24NLost Creek93110/8/2010WGS84, UTM, Zone 15NLuquillo LTER (LUQ1)68110/11/2010WGS84, UTM, Zone 20NMetolius Eyerly Burn9546/29/2010WGS84, UTM, Zone 10NMetolius Intermediate Pine9556/29/2010WGS84, UTM, Zone 10NMissouri Ozark Site9678/4/2010WGS84, UTM, Zone 15NNASA-E272712/23/2009WGS84, UTM, Zone 25NNGRIP27296/29/2010WGS84, UTM, Zone 23NNiwot Ridge (LTER NWT1)9972007/06/05, 2007/07/21, 2007/10/21, 2008/06/07, 2009/07/26, 2010/06/13, 2010/07/29, 2010/10/29, 2010/12/14WGS84, UTM, Zone 13NPark Falls103610/8/2010WGS84, UTM, Zone 15NPhillips Creek Marsh (PHCK)109110/31/2010WGS84, UTM, Zone 18NRond. — Faz. Nossa Senhora-Ji Parana — Pasture7110/21/2010WGS84, UTM, Zone 20SRond. — Rebio Jaru Ji Parana — Tower B737/17/2010WGS84, UTM, Zone 20SSantarem — Km77 Pasture842007/06/12, 2008/05/30, 2009/06/18, 2009/08/03, 2010/06/21, 2010/07/21, 2010/08/06, 2010/11/06WGS84, UTM, Zone 21SSask — SSA Old Aspen25811/5/2010WGS84, UTM, Zone 13NSask — SSA Old Jack Pine26010/31/2010WGS84, UTM, Zone 13NSioux Falls Portable27552010/03/20, 2010/06/29, 2010/07/16, 2010/08/31, 2010/10/16, 2010/12/01WGS84, UTM, Zone 14NSky Oaks106711/18/2009WGS84, UTM, Zone 11NSummit27411/23/2010WGS84, UTM, Zone 24NSwiss Camp27421/5/2010WGS84, UTM, Zone 22NTablelands Juniper Savanna27129/18/2010WGS84, UTM, Zone 13NTonzi Ranch10789/17/2010WGS84, UTM, Zone 10NValles Caldera Mixed Conifer271510/5/2010WGS84, UTM, Zone 13NWalker Branch Watershed109610/27/2010WGS84, UTM, Zone 16NWestern Peatland — LaBiche-Black Spruce/Larch Fen2929/23/2010WGS84, UTM, Zone 12NTerrestrial Ecology Products Data UsesThe data can be used for a number of purposes (1) to validate the SAR measurements using flux tower site characterization data; (2) to examine the impacts of vegetation dynamics on climate; (3) to understand human impacts on vegetation at a local scale; (3) to detect deforestation and forest degradation; (4) to map and differentiate growth stages and change; (5) to retrieve woody biomass and structural attributes; and (6) to characterize, map, and monitor ecoregions such as mangroves and wetlands. More About Data SourceThe SAR images are subset scenes of approximately 60 km x 70 km that include an established site in one of the monitoring networks. The spatial resolution of all scenes is 15 meters. These scenes are distributed as GeoTIFF files, with appropriate projection information defined within the file. The acquisition mode for all data is the Fine Beam Dual Polarization or FBD with the HH/HV polarization. The HH and HV channels are distributed as 3 channels to allow for an intuitive image display. The HH band is displayed in the red and blue channels, and the HV band is displayed in the green channel. The resulting images show vegetation in shades of green and barren land in shades of pink or purple. For some images only single polarization is available; these images are distributed as grayscale images. Support AcknowledgmentThe National Aeronautics and Space Administration (NASA) funded this EOSDIS Tech Infusion project as a collaboration between the ASF DAAC, the National Snow and Ice Data Center (NSIDC), and the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) in 2010.

Data as input for the KEC 5.0 calculations (RWS-WVL)

This dataset provides a presentation that highlights the role NASA research and researchers played in developing a wide range of significant, quantitative ecological applications of satellite data. The presentation by Dr Diane E. Wickland, former NASA Terrestrial Ecology Program Manager and Lead for NASA Carbon Cycle and Ecosystems Focus Area, provides a top-level overview from her perspective of the development and evolution of the program. Dr Wickland joined NASA in 1985 to manage a newly formed Terrestrial Ecosystems Program. Along with other NASA program managers, she was charged with reorienting the program to be less empirical and have a greater focus on first principles, and to prepare for a next generation of earth-observing satellites. As an ecologist, she thought that focusing on important ecological questions and recruiting practicing ecologists to the program would facilitate such a change in directions. The presentation emphasizes the early years of U.S. satellite remote sensing and covers a few highlights after 2005.

The inventory of Natural Environments of Ecological Interest (MNIE) was launched under the impetus of the elected representatives of the District of Rennes since the 1990s. This voluntary approach of elected officials to improve the consideration of biodiversity at the level of their territory has made it possible to significantly enrich the knowledge and distribution of the natural environments of the territory. The elected representatives of the SCoT decided to extend this inventory to the whole territory of the Pays de Rennes. The SCoT has established strict protection of these environments. Since its approval in December 2007, they have become regulatoryly inconstructible. A single document “Atlas des MNIE du Pays de Rennes” locates all the sites identified in the territory of the Pays de Rennes. The SCoT Joint Union is now the structure that drives the MNIE file.

This atlas refers, among other things: - Large natural ensembles (GEN), spaces without regulatory scope; - Natural environments of ecological interest (MNIE), areas strictly protected by the SCOT, which gives them a regulatory scope.

As part of the inventory of natural areas of wildlife interest, this layer localises species of heritage and regional interest.

The acronym MNIE is referred to as “Natural Ecological Interest”. These are sites consisting of one or more natural habitats and of significant interest in fauna and/or flora. A MNIE is smaller than a GEN, in which it is very often included. Note, however, that some MNIEs can be isolated in a trivialised space outside a GEN. These MNIEs are spaces strictly protected by the ScoT, which gives them a regulatory scope.

2015_VCA_3:If Ecologie Conseil