View records for development projects currently under review or previously reviewed by the MEPA office. Look up projects by name, municipality, and location.

IntroductionBuilt environment attributes have been linked to cardiovascular disease (CVD) risk. Therefore, identifying built environment attributes that are associated with CVD risk is relevant for facilitating effective public health interventions.ObjectiveTo conduct a systematic review of literature to examine the influence of built environmental attributes on CVD risks.Data SourceMultiple database searches including Science direct, CINAHL, Masterfile Premier, EBSCO and manual scan of reference lists were conducted.Inclusion CriteriaStudies published in English between 2005 and April 2015 were included if they assessed one or more of the neighborhood environmental attributes in relation with any major CVD outcomes and selected risk factors among adults.Data ExtractionAuthor(s), country/city, sex, age, sample size, study design, tool used to measure neighborhood environment, exposure and outcome assessments and associations were extracted from eligible studies.ResultsEighteen studies met the inclusion criteria. Most studies used both cross-sectional design and Geographic Information System (GIS) to assess the neighborhood environmental attributes. Neighborhood environmental attributes were significantly associated with CVD risk and CVD outcomes in the expected direction. Residential density, safety from traffic, recreation facilities, street connectivity and high walkable environment were associated with physical activity. High walkable environment, fast food restaurants, supermarket/grocery stores were associated with blood pressure, body mass index, diabetes mellitus and metabolic syndrome. High density traffic, road proximity and fast food restaurants were associated with CVDs outcomes.ConclusionThis study confirms the relationship between neighborhood environment attributes and CVDs and risk factors. Prevention programs should account for neighborhood environmental attributes in the communities where people live.

Journal of environmental biology - ResearchHelpDesk - Journal of Environmental Biology (JEB) is one of the oldest peer-reviewed research journals published in India since 1980. In the year 1978, an International Conference was organized at Muzaffarnagar, India. Participating delegates of the conference realized the need of an international research Journal to cater to the needs of Environmental Biologists and Toxicologists, and the organizer of the conference Dr. R. C. Dalela, was entrusted the responsibility to take the necessary steps. After several meetings, the Journal of Environmental Biology was launched on 7th October 1980 with Dr. Dalela as Editor-in-chief and was registered with the Government of India (GOI). In 1996, the editorial office of the Journal shifted to Lucknow and the registration was revised by GOI, accordingly. Website (www.jeb.co.in) of the journal was launched in 2006 with Open Access facility free-of-charge. Aims and Scope: Journal of Environmental Biology is a broad-based, peer-reviewed International Journal that publishes in English Language original research papers and research reviews (with prior permission) from all areas of Environmental Biology such as : Environmental Science Biological Science Environment Engineering Environmental Health Biotechnology Microbiology Biochemistry Toxicology Ecology Agricultural Sciences including Forestry and Fish & Fisheries Abstracting & Indexing Journal of Environmental Biology is covered by the following Abstracting and Indexing Services Medline® Scopus® Embase® Geo Abstracts Paryavaran Abstracts Toxicology Abstracts Zoological Record® Biological Abstracts® Chemical AbstractsTM Indian Science Abstracts ESCI PubMed® Aqualine Science Direct Web of Science Global Health EBSCO Discovery Service Essential Science Indicators BIOSIS Previews Pollution Abstracts Excerpta Medica Environment Complete™ Environmental Abstracts Cambridge Scientific Abstracts Veterinary Science Database Environmental Science Database Elsevier Bibliographic Databases Forest Science Database (CABI) Aquatic Sciences and Fisheries Abstracts (ASFA) Current Contents® (Agriculture, Biology and Environ. Sci.)

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This Central West (CEN) dataset contains v2.2 of the Asset database (CEN_asset_database_20160216.mdb), a Geodatabase version for GIS mapping purposes (CEN_asset_database_GISOnly_20160216.gdb), the draft Water Dependent Asset Register spreadsheet (BA-NIC-CEN-130-WaterDependentAssetRegister-AssetList-v20160216.xlsx), a data dictionary (CEN_asset_database_doc_20160216.doc), a folder (Indigenous_doc) containing documentation associated with Indigenous water asset project, a folder (NRM_DOC) and a folder (NRM_DOC) containing documentation associated with the Water Asset Information Tool (WAIT) process as outlined below.

The Asset database supersedes the previous version of Asset database for the Central West subregion on 21 August 2015 (GUID: 5e90d2ee-a551-48c5-ba48-83e3a907fcf9). Updates to this database compared to the previous database include:

V2.2

(1) Total number of registered water assets was increased by 6 due to:

(a) The 2 assets changed M2 test to "Yes" from the review done by Ecologist group.

(b) 4 indigenous water assets from OWS were added.

V2.1

(2) Change "PAE_Region" to "Central West BA subregion boundary" for 149 NSW TS assets in field PAE_Region of table assetlist

The Asset database is registered to the BA repository as an ESRI personal goedatabase (.mdb - doubling as a MS Access database) that can store, query, and manage non-spatial data while the spatial data is in a separated file geodatabase joined by AID/Element ID/BARID. Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. All reports received associated with the WAIT process for Central Westare included in the zip file as part of this dataset. Elements are initially included in the preliminary assets database if they are partly or wholly within the subregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list.Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of " CEN_asset_database_doc_20160216.doc ", located in the zip file as part of this dataset. The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset. Detailed information describing the database structure and content can be found in the document " CEN_asset_database_doc_20160216.doc" located in the zip file. Some of the source data used in the compilation of this dataset is restricted.

The public version of this asset database can be accessed via the following dataset: Asset database for the Central West subregion on 16 February 2016 Public (https://data.gov.au/data/dataset/546107ad-27b0-4432-b17e-8876e7c9769d)

Dataset History

VersionID Date Notes

1.0 29/04/2015 Initial database

2.0 21/08/2015 v2 - additions as follows:

(1) At the request of NSW OEH, data identifying species and ecological communities listed under NSW legislation has been included in two additional attribute tables "NSW_TS" and "NSW_TEC" (a total of 149 new elements and assets, AIDs 70001-70149). However, given the extremely course catchment-scale resolution of the data as compared to the relatively fine-scale of the PAE, it is essentially a non-spatial list of species and communities which may or may not occur within the PAE. As the data was unable to be meaningfully used as a spatial dataset it was subsequently "turned off" at decision M0 (not fit for purpose), with the decision reflected in the "Assetlist"and "AssetDecisions" tables.

(2) The database has been updated to include M2 (water dependency) test results from the CEN project team, and a draft "Water-dependent asset register and asset list" spreadsheet (BA-NIC-CEN-130-WaterDependentAssetRegister-AssetList-V20150814.xlsx) has been created and is included in this dataset.

(3) Four queries have been added to the non-spatial database (mdb) (Find_All_Used_Assets, Find_All_WD_Assets, Find_Amount_Asset_in_Class and Find_Amount_Elements_in_Class) to assist project teams to identify and calculate figures to be published.

2.1 29/09/2015 "Change ""PAE_Region"" to ""Central West BA subregion boundary"" for 149 NSW TS assets in field

                           PAE_Region of table assetlist"

2.2 16/02/2016 "Total number of registered water assets was increased by 6 due to:

                             (a) The 2 assets changed M2 test to "Yes" from the review done by Ecologist group. 

                             (b) 4 indigenous water assets from OWS were added."

Dataset Citation

Bioregional Assessment Programme (2013) Asset database for the Central West subregion on 16 February 2016. Bioregional Assessment Derived Dataset. Viewed 08 February 2017, http://data.bioregionalassessments.gov.au/dataset/8ac1d434-7697-4a8f-9908-814e8daf4604.

Dataset Ancestors

• Derived From Macquarie Marshes Vegetation 1991-2008 VIS_ID 3920

• Derived From NSW Office of Water GW licence extract linked to spatial locations NIC v2 (28 February 2014)

• Derived From NSW Office of Water Surface Water Entitlements Locations v1_Oct2013

• Derived From Travelling Stock Route Conservation Values

• Derived From NSW Wetlands

• Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only

• Derived From Asset database for the Central West subregion on 29 April 2015

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas

• Derived From Birds Australia - Important Bird Areas (IBA) 2009

• Derived From Spatial Threatened Species and Communities (TESC) NSW 20131129

• Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only)

• Derived From NSW Office of Water Surface Water Offtakes - NIC v1 20131024

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA)

• Derived From Environmental Asset Database - Commonwealth Environmental Water Office

• Derived From Asset database for the Central West subregion on 21 August 2015

• Derived From Ramsar Wetlands of Australia

• Derived From Native Vegetation Management (NVM) - Manage Benefits

• Derived From Key Environmental Assets - KEA - of the Murray Darling Basin

• Derived From National Heritage List Spatial Database (NHL) (v2.1)

• Derived From Climate Change Corridors (Dry Habitat) for North East NSW

• Derived From Great Artesian Basin and Laura Basin groundwater recharge areas

• Derived From NSW Office of Water combined geodatabase of regulated rivers and water sharing plan regions

• Derived From New South Wales NSW Regional CMA Water Asset Information WAIT tool databases, RESTRICTED Includes ALL Reports

• Derived From New South Wales NSW - Regional - CMA - Water Asset Information Tool - WAIT - databases

• Derived From NSW Office of Water Groundwater licences extract linked to spatial locations NIC v3 (13 March 2014)

• Derived From [Australia - Species of National Environmental Significance

This dataset represents Rock Outcrop Critical Environmental Features (CEFs) identified during the development review process since 1995. Prior to 1995, data is either unavailable or lost. Rock Outcrop CEFs were digitized from construction plans, environmental assessments, and City of Austin staff field observations into a versioned SDE database using ArcMap.

Database of literature reviewed in the publication "What influences the implementation of natural climate solutions? A systematic map and review of the evidence" (Schulte et al., 2021).

This project will conduct a meta-review of case studies on water-related adaptation responses and evaluate the effectiveness of these responses in reducing water insecurity risks. This will provide the basis for a more robust framework to support the design of future adaptation responses than is available now. Studies (n=359) which met the inclusion criteria and were coded across 100 plus variables. These were included because they provided metrics of benefits of adaptation (Sheet 1). Studies (n-1460) which did not meet the inclusion criteria and were coded for a limited number of variables (Sheet 2). Coding manual that explains the codes (Sheet 3).

Introduction

Payments for ecosystem services (PES) are a leading conservation finance tool to encourage land-users to deliver ecosystem services in exchange for financial incentives (Blundo-Canto et al., 2018; Kaiser et al., 2021; Salzman et al., 2018; Schomers and Matzdorf, 2013). They have generated considerable interest over the past two decades, following the publication of the UN’s Millennium Ecosystem Assessment (MEA, 2005). Yet, there has been a dearth of analysis that reveals the outcomes and evolution of the PES research body itself, with most studies having a very specific or limited focus on the theoretical and empirical development of these PES programmes. The ePEStemology database assembles a systematic literature review into a meta-analysis aimed at understanding knowledge generation in PES research. The database allows for an analysis of key trends in how the body of literature on PES has informed scholars and practitioners since the emergence of this conservation tool.

Research questions and main objectives:

The ePEStemology database is the largest review of PES scientific research to date and addresses the following research questions:

• In the history of 15 years of PES research, what are the dominant criteria used to define and assess success of PES in practice? Are there geographical patterns in defining those criteria? Where does research take place? And by whom?
• What does 15 years of PES research illustrate in terms of the social and political consequences that arise in the implementation of PES? To what extent does literature engage with territorial dynamics and conflicting frameworks around nature’s values?
• How has PES research evolved? Do research recommendations feed into future research objectives over time?
• How does the epistemological position, including methods used, geographic location and disciplinary focus of authors among other variables, influence PES research outcomes?

A core objective of the database is to ensure it remains a living compendium of PES research. While the database does not account for every peer-reviewed published article on PES, it facilitates the possibility of iteratively adding new publications or retroactively adding in missing articles as well as those that use cognate terms to define PES (e.g. as rewards or compensation for ecosystem services). The database also aims to serve as an important basis for future research questions on overall or regional trends emerging from PES research.

Search strategy

Using these key objectives and questions, we defined a set of variables (see attached) and search strategy to construct the ‘ePEStemology’ database. The database is populated by International Scientific Indexed (ISI) peer-reviewed journal articles. It includes Anglophone articles in Scopus and Web of Science (WoS), using all of the search terms “PES”, “Payments for Ecosystem Services,” “Payment for Ecosystem Services,” “Payment for Environmental Service,” or Payments for Environmental Services” either in the title, abstract, or keywords of queried articles.

Articles were excluded if they were produced in a language other than English or if they were book chapters, books, conference papers, reviews, or webpages. While recognizing the caveats of excluding research articles in other languages as well as in other media (e.g. as books or conference papers), we justify our approach in order to ensure consistency and comparability of the body of research literature.

Following the different steps prescribed by the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol (Moher et al., 2009), we identified a total of 1,067 published articles between 2005 and 2019. We took the year 2005 as the starting point for published research on PES, following the Millennium Ecosystem Assessment (Millennium Ecosystem Assessment, 2005) of the same year as well as an initial seminal publication on the subject (Wunder, 2005). Initial screening of articles began in September, 2018 with a total of 1,215 ISI-peer reviewed research articles on PES identified between both the Scopus and WoS queries. Additional articles were included to account for the year 2019 in October, 2020 to total 1,439 articles.

It is also worth noting that Scopus providing the greatest coverage of published articles on PES, accounting for 78% of the total identified. WoS accounted for 66% of the total, but also included 305 articles that did not fall within the Scopus search.

The screening procedure for selecting articles was contingent on the time in which the search in SCOPUS and WoS were conducted. It should be noted that this systematic review does not account for every ISI-research article published on PES during the time period considered. Since the database search tools are continuously updated retroactively, the query date may alter the number of articles retrieved in the search, increasing them over time despite being limited to specific dates. However, even if the database gets adapted over time, we can safely assume that the corpus represents a representative account of peer-reviewed published research on PES. In addition to the language exclusions made (i.e. our database only includes Anglophone publications), there are various permutations on the PES terminology, including “payments for hydrological services,” “payments for watershed services”, “conservation payments,” “rewards for ecosystem services,” or “agro-ecological incentives,” and many others that make it challenging to fully account for every relevant article. However, the protocol does not include all these possible variations, but can easily allow these variations to be included and brought into the analysis at a later stage.

Coding strategy

For the initial database (2005-2019) four independent reviewers to review each abstract and full text of each article were selected (BT, CJ, GVH, VK). Each reviewer had experience in (empirical) PES research and have published peer-reviewed research on PES or other market-like transactions for ecosystem services (e.g. Tabaichount et al., 2019; Jacob et al., 2016; Van Hecken et al., 2015; Kolinjivadi and Sunderland, 2012). Broad variables of interest that guide our analysis (e.g. research objectives, disciplines, methods, author affiliations and positionality, geographical base, research outcomes, and others) served as the basis for coding. However, in order to establish a foundation of codes for each of these categories of interest and further refine each of those broader categories, the research team randomly selected 100 articles of the final 1,067 articles identified and applied a grounded theory open-coding process (e.g. Strauss and Corbin, 1990; Thornberg and Charmaz, 2014). The latter implies a process in which any preconceived identification for each category of interest was open to be further adapted prior to the final coding process. The iterative process of initial coding determined the most relevant sets of codes for each identified variable of interest, as well as possible values for each of them. Additional codes were added to the list as more articles were reviewed and until saturation was reached.

After discussing and deciding on the final categories/variables with the whole group, all remaining articles in the corpus were evenly and randomly divided among all reviewers. On average, each of the four reviewers coded between 500 and 600 articles.

Subsequently, and for over a period of 15 months, the coding team revised and coded all articles based on the abstracts and a review of the full text in case the abstract did not allow to accurately code some of the variables. Each article was independently (blindly) coded by two different reviewers. To ensure robustness of coding, pairs of reviewers for each set compared results of the coding process for each article through a triangulation process and resolved discrepancies through collective deliberation and cross-checked consensus.

Variable list

The variable list and description of variables and their corresponding values can be found in the attached Word-document

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The …Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This Gloucester dataset contains v8.2 of the Asset database (GLO_asset_database_20160212.mdb), a Geodatabase version for GIS mapping purposes (GLO_asset_database_20160212_GISOnly.gdb), the draft Water Dependent Asset Register spreadsheet (BA-NSB-GLO-130-WaterDependentAssetRegister-AssetList-v20160212.xlsx), a data dictionary (GLO_asset_database_doc_20160212.doc), a folder (Indigenous_doc) containing documentation associated with Indigenous water asset project, a folder (NRM_DOC) and a folder (NRM_DOC) containing documentation associated with the Water Asset Information Tool (WAIT) process as outlined below. The Gloucester Asset database v8.2 supersedes the previous version of the GLO Asset database in asset relevant tables/ feature class only (i.e. AssetDecisions, AssetList, Element_to_Asset, ElementList, tbl_Indigenous_water_asset, tbl_GAL_Species_TEC_decisions_review_23112015 in GLO_asset_database_20160212.mdb and GM_GLO_AssetList_pt, GM_GLO_ElementList_pt in GLO_asset_database_20160212_GISOnly.gdb). This version of GLO asset database has been updated to: (1) Total number of registered water assets was increased by 18 due to: (a) The 3 assets changed M2 test to "Yes" from the review done by Ecologist group. (b) 15 indigenous water assets from OWS were added. The Asset database is registered to the BA repository as an ESRI personal goedatabase (.mdb - doubling as a MS Access database) that can store, query, and manage non-spatial data while the spatial data is in a separated file geodatabase joined by AID/Element ID/BARID. Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. All reports received associated with the WAIT process for Gloucester are included in the zip file as part of this dataset. Elements are initially included in the preliminary assets database if they are partly or wholly within the subregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list. Descriptions of the assets identified in the Gloucester subregion are found in the "AssetList" table of the database. In this version of the database only M1 has been assessed. Assets are the spatial features used by project teams to model scenarios under the BA program. Detailed attribution does not exist at the asset level. Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of "GLO_asset_database_doc_20160212.doc", located in the zip file as part of this dataset. The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset. Detailed information describing the database structure and content can be found in the document "GLO_asset_database_doc_20160212.doc" located in the zip file. The public version of this asset database can be accessed via the following dataset: Asset database for the Gloucester subregion on 12 February 2016 Public v02 (https://data.gov.au/data/dataset/5def411c-dbc4-4b75-b509-4230964ce0fa). Purpose Used for Gloucester subregion for bioregional assessments The public version of this asset database can be accessed via the following dataset: Asset database for the Gloucester subregion on 12 February 2016 Public v02 (https://data.gov.au/data/dataset/5def411c-dbc4-4b75-b509-4230964ce0fa). Dataset History VersionID Date Notes 1.0 17/03/2014 Initial database 1.01 19/03/2014 Update classification using latest one 2.0 23/05/2014 Update asset area for some assets 3.0 9/07/2014 updated to include new assets and elements identified by community. 4.0 29/08/2014 updated assets and elements from WSP 5.0 4/09/2014 Table AssetDecisions is added to record decision making process and decisions about M2 are also added in table asset list 6.0 8/04/2015 195/9 Groundwater economic point elements/assets were added in while 81/7 Groundwater economic point elements/assets were turned off 7.0 27/05/2015 The receptor data ( tables: ReceptorList, tbl_Receptors_GDE, tbl_Receptors_GW, tbl_Receptors_SW and tbl_Receptors_SW_Catchment_Ref_Only; and spatial data: GM_GLO_ReceptorList_pt) is added 7.1 21/08/2015 "(1) Delete (a) line 26 from tab "Description" and (b) column E from tab "Receptor register" about "Depth" parameters in BA-NSB-GLO-140-ReceptorRegister-v20150821.xlsx (2) Delete field of "Depth" from table "ReceptorList" in GLO_asset_database_20150821.mdb (3) Add two fields of "InRegister" and "Registered Date" to table "ReceptorList" in GLO_asset_database_20150821.mdb for the consistency with other subregions in the future" 8 16/09/2015 "(1) (a) Update Latitude, Longitude, LandscapeClass using the latest data from GLO project team and update the values for RegisteredDate, and Group using "GDE", "SW" and "GW" in table ReceptorList in GLO_asset_database_20150916.mdb; (b) Create draft BA-NSB-GLO-140-ReceptorRegister-v20150916.xlsx (2) Update tbl_Receptors_GDE, tbl_Receptors_GW and tbl_Receptors_SW in GLO_asset_database_20150916.mdb, using the latest data from GLO project team. (3) Update GM_GLO_ReceptorList_pt in GLO_asset_database_20150916_GISOnly.gdb, using the latest data from GLO project team" 8.1 29/10/2015 (a) Update LandscapeClass field in table ReceptorList for all 222 economic Receptors to match the latest decision about this parameter (b) Create draft BA-NSB-GLO-140-ReceptorRegister-v20151029.xlsx 8.2 12/02/2016 "(1) Total number of registered water assets was increased by 18 due to: (a) The 3 assets changed M2 test to "Yes" from the review done by Ecologist group. The original data is included the database as the table tbl_GLO_Species_TEC_decisions_review_23112015 (b) 15 indigenous water assets from OWS were added. The data and documents from OWS are included in subdirectory Indigenous_doc (c)The draft new Water Dependent Asset Register file (BA-NSB-GLO-130-WaterDependentAssetRegister-AssetList- v20160212.xlsx) was created" The source metadata was updated to meet the purpose of the Bioregional Assessment Programme Dataset Citation Bioregional Assessment Programme (2014) Asset database for the Gloucester subregion on 12 February 2016. Bioregional Assessment Derived Dataset. Viewed 18 July 2018, http://data.bioregionalassessments.gov.au/dataset/72a47bec-1393-49d6-b379-0e48551d26a9. Dataset Ancestors Derived From Standard Instrument Local Environmental Plan (LEP) - Heritage (HER) (NSW) Derived From NSW Office of Water GW licence extract linked to spatial locations - GLO v5 UID elements 27032014 Derived From Asset database for the Gloucester subregion on 21 August 2015 Derived From Gloucester digitised coal mine boundaries Derived From Groundwater Dependent Ecosystems supplied by the NSW Office of Water on 13/05/2014 Derived From NSW Office of Water GW licence extract linked to spatial locations GLOv4 UID 14032014 Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only Derived From National Groundwater Dependent Ecosystems (GDE) Atlas Derived From Asset database for the Gloucester subregion on 16 September 2015 Derived From GEODATA 9 second DEM and D8: Digital Elevation Model Version 3 and Flow Direction Grid 2008 Derived From National Groundwater Information System (NGIS) v1.1 Derived From Groundwater Entitlement Data GLO NSW Office of Water 20150320 PersRemoved Derived From Asset database for the Gloucester subregion on 29 October 2015 Derived From Geofabric Surface Cartography - V2.1 Derived From Groundwater Entitlement Data Gloucester - NSW Office of Water 20150320 Derived From Collaborative Australian Protected Areas Database (CAPAD) 2010 - External Restricted Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA) Derived From EIS Gloucester Coal 2010 Derived From Report for Director Generals Requirement Rocky Hill Project 2012 Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only) Derived From Asset database for the Gloucester subregion on 28 May 2015 Derived From NSW Office of Water GW licence extract linked to spatial locations GLOv3 12032014 Derived From EIS for Rocky Hill Coal Project 2013 Derived From National Heritage List Spatial Database (NHL) (v2.1) Derived From NSW Office of Water Groundwater Entitlements Spatial Locations Derived From Gloucester - Additional assets from local councils Derived From NSW Office of Water combined geodatabase of regulated rivers and water sharing plan regions Derived From Asset database for the Gloucester subregion on 29 August 2014 Derived From New South Wales NSW Regional CMA Water Asset Information WAIT tool databases, RESTRICTED Includes ALL Reports Derived From Groundwater Modelling Report for Stratford Coal Mine Derived From Groundwater Economic Assets GLO 20150326 Derived From NSW Office of Water Groundwater Licence Extract Gloucester - Oct

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

The asset database for Pedirka subregion (v4) supersedes previous versions of the Arckaringa Asset database (Asset database for the Pedirka subregion on 27 August 2015, GUID: 62dc178f-65ae-4e6a-b5d4-12895b37d04c). Total number of registered water assets in this V4 database was increased by 2 because two assets changed M2 test from "No" to "Yes" from M2 test review done by Ecologist group.

This dataset contains v4 of the Asset database (PED_asset_database_20160308.mdb), a Geodatabase version for GIS mapping purposes (PED_asset_database_20160308_GISOnly.gdb), an updated draft Water Dependent Asset Register spreadsheet (BA-LEB-PED-130-WaterDependentAssetRegister-AssetList-v20160308.xlsx), a data dictionary (PED_asset_database_doc_20160308.doc), and a folder (NRM_DOC) containing documentation associated with the Water Asset Information Tool (WAIT) process.

The tabular attribute data can be joined in a GIS to the "Assetlist" table in the mdb database using the "AID" field to view asset attributes (BA attribution). To view the more detailed attribution at the element-level, the intermediate table "Element_to_asset" can be joined to the assets spatial datasets using AID, and then joining the individual attribute tables from the Access database using the common "ElementID" fields. Alternatively, the spatial feature layers representing elements can be linked directly to the individual attribute tables in the Access database using "ElementID", but this arrangement will not provide the asset-level groupings.

Further information is provided in the accompanying document, "PED_asset_database_doc_20160308.doc" located within this dataset.

The public version of this asset database can be accessed via the following dataset: Asset database for the Pedirka subregion on 08 March 2016 Public (https://data.gov.au/data/dataset/c104deb9-5969-4427-977a-12f284564c93).

Dataset History

VersionID Date Notes

1.0 13/03/2015 Initial database

1.1 19/03/2015 Add SA point Eco data (2 assets and 28 Elements) and fixed Note field value in table AssetDecisions

2 7/08/2015 "(1) Updated the database for M2 test results provided from PED assessment team and created the draft BA-LEB-PED-130-WaterDependentAssetRegister-AssetList-V20150807.xlsx

(2) Updated the group, subgroup, class and depth for (up to) 67 NRM WAIT assets to cooperate the feedback to OWS from relevant SA NRM office (whose staff missed the asset workshop). The AIDs and names of those assets are listed in table LUT_changed_asset_class_20150807 in PED_asset_database_20150807.mdb

(3) Appendix C in PED_asset_database_doc_201500807.doc is about total elements/assets in current Group and subgroup

(4) Four SQL queries (Find_All_Used_Assets, Find_All_WD_Assets, Find_Amount_Asset_in_Class and Find_Amount_Elements_in_Class) in PED_asset_database_20150807.mdb can be used for total assets and total numbers

(5)There are 1 asset (in PED subregion), which is same as 1 asset in MBC subregion. Its AID, Asset Name, Group, SubGroup, Depth, Source and ListDate is using values from MBC asset. This asset is listed in table LUT_DUP_PED_MBC in PED_asset_database_20150807.mdb

(6)The databases, especially spatial database (PED_asset_database_20150807Only.gdb), were changed such as duplicated attribute fields in spatial data were removed and only ID field is kept. The user needs to join the Table Assetlist or Elementlist to the relevant spatial data."

3 27/08/2015 M2_Reason in the Assetlist table and DecisionBrief in the AssetDecisions table have been updated with short descriptions (<255 characters) provided by project team 21/8, and the draft "water-dependent asset register and asset list" (BA-LEB-PED-130-WaterDependentAssetRegister-AssetList-V20150827) also updated accordingly. No changes to asset numbers.

4 8/03/2016 "(1) Total number of registered water assets was increased by 2 due to: Two assets changed M2 test from "No" to "Yes" from M2 test review done by Ecologist group.

              (2) The draft new Water Dependent Asset Register file (BA-LEB-PED-130-WaterDependentAssetRegister-AssetList-V20160308.xlsx) was created"

Dataset Citation

Bioregional Assessment Programme (2014) Asset database for the Pedirka subregion on 08 March 2016. Bioregional Assessment Derived Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/336879f0-470f-4f9d-826c-e6c8653657eb.

Dataset Ancestors

• Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements 20131204

• Derived From Queensland QLD - Regional - NRM - Water Asset Information Tool - WAIT - databases

• Derived From Northern Territory Groundwater Elements v120141202

• Derived From Matters of State environmental significance (version 4.1), Queensland

• Derived From Geofabric Surface Network - V2.1

• Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only

• Derived From South Australia SA - Regional - NRM Board - Water Asset Information Tool - WAIT - databases

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas

• Derived From PED AssetList V1 20150313

• Derived From National Groundwater Information System (NGIS) v1.1

• Derived From Birds Australia - Important Bird Areas (IBA) 2009

• Derived From Queensland QLD Regional CMA Water Asset Information WAIT tool databases RESTRICTED Includes ALL Reports

• Derived From Queensland wetland data version 3 - wetland areas.

• Derived From Asset database for the Pedirka subregion on 07 August 2015

• Derived From SA Department of Environment, Water and Natural Resources (DEWNR) Water Management Areas 141007

• Derived From South Australian Wetlands - Groundwater Dependent Ecosystems (GDE) Classification

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA)

• Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements linked to bores v3 03122014

• Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only)

• Derived From Asset database for the Pedirka subregion on 27 August 2015

• Derived From Permanent and Semi-Permanent Waterbodies of the Lake Eyre Basin (Queensland and South Australia) (DRAFT)

• Derived From Queensland wetland data version 3 - wetland lines.

• Derived From SA EconomicElements v1 20141201

• Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements linked to bores and NGIS v4 28072014

• Derived From National Heritage List Spatial Database (NHL) (v2.1)

• Derived From Great Artesian Basin and Laura Basin groundwater recharge areas

• Derived From Northern Territory Groundwater Management Units 20140630

• Derived From Northern Territory - Lake Eyre Basin - Wetlands Mapping - METADATA ONLY

• Derived From SA Department of Environment, Water and Natural Resources (DEWNR) Groundwater Licences 141007

• Derived From Northern Territory Groundwater Licence Extract 20140130

• Derived From Lake Eyre Basin (LEB) Aquatic Ecosystems Mapping and Classification

• Derived From [Australia - Species of National Environmental Significance

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The …Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This Gwydir (DWY) dataset contains v23 of the Asset database (GWY_asset_database_20160311.mdb), a Geodatabase version for GIS mapping purposes (GWY_asset_database_GISOnly_21060311.gdb), the draft Water Dependent Asset Register spreadsheet (BA-NIC-GWY-130-WaterDependentAssetRegister-AssetList-v20160311.xlsx), a data dictionary (GWY_asset_database_doc_20160311.docx), a folder (NRM_DOC) and a folder (NRM_DOC) containing documentation associated with the Water Asset Information Tool (WAIT) process. This Asset database supersedes the previous version of Asset database for the Gwydir subregion on 24 August 2015 (GUID: 7350df87-5103-40f5-b82c-42b0fc59a6a5). Updating in this v3 GWY database includes total number of GWY registered water assets was increased by 1 (= +2-1) because two assets changed M2 test from "No" to "Yes", but one asset changed M2 test from "Yes" to "No" from M2 test decision review done by Ecologist group. The tabular attribute data can be joined in a GIS to the "Assetlist" table in the mdb database using the "AID" field to view asset attributes (BA attribution). To view the more detailed attribution at the element-level, the intermediate table "Element_to_asset" can be joined to the assets spatial datasets using AID, and then joining the individual attribute tables from the Access database using the common "ElementID" fields. Alternatively, the spatial feature layers representing elements can be linked directly to the individual attribute tables in the Access database using "ElementID", but this arrangement will not provide the asset-level groupings. Further information is provided in the accompanying document, "GWY_asset_database_doc_20160311.docx" located within this dataset. The public version of this asset database can be accessed via the following dataset: Asset database for the Gwydir subregion on 11 March 2016 Public (https://data.gov.au/data/dataset/cce59770-99b8-46d1-87c6-582920e0687a) Purpose This Asset database is developed for BA The public version of this asset database can be accessed via the following dataset: Asset database for the Gwydir subregion on 11 March 2016 Public (https://data.gov.au/data/dataset/cce59770-99b8-46d1-87c6-582920e0687a) Dataset History VersionID Date Notes 1.0 8/05/2015 Initial database 2.0 24/08/2015 v2 - additions as follows: (1) At the request of NSW OEH, data identifying species and ecological communities listed under NSW legislation has been included in two additional attribute tables "NSW_TS" and "NSW_TEC" (a total of 110 elements and assets, AIDs 70150-70259). However, given the extremely course catchment-scale resolution of the data as compared to the relatively fine-scale of the PAE, it is essentially a non-spatial list of species and communities which may or may not occur within the PAE. As the data was unable to be meaningfully used as a spatial dataset it was subsequently "turned off" at decision M0 (not fit for purpose), with the decision reflected in the "Assetlist"and "AssetDecisions" tables. Although they are included in the asset database, these new assets are not included in the asset count for GWY. (2) The database has been updated to include M2 (water dependency) test results from the GWY project team, and a draft "Water-dependent asset register and asset list" spreadsheet (BA-NIC-GWY-130-WaterDependentAssetRegister-AssetList-V20150824.xlsx) has been created and is included in this dataset. (3) Four queries have been added to the non-spatial database (mdb) (Find_All_Used_Assets, Find_All_WD_Assets, Find_Amount_Asset_in_Class and Find_Amount_Elements_in_Class) to assist project teams to identify and calculate figures to be published. 3 11/03/2016 "(1) Total number of registered water assets was increased by 1 (+2-1) due to: Two assets changed M2 test from "No" to "Yes" and one asset changed M2 test from "Yes" to "No" from M2 test review done by Ecologist group. (2) The draft new Water Dependent Asset Register file (BA-LEB-PED-130-WaterDependentAssetRegister-AssetList-V20160308.xlsx) was created" Further information is contained in the associate document GWY_asset_database_doc_20160311.docx". Dataset Citation Bioregional Assessment Programme (2013) Asset database for the Gwydir subregion on 11 March 2016. Bioregional Assessment Derived Dataset. Viewed 08 February 2017, http://data.bioregionalassessments.gov.au/dataset/089f3ab8-74cf-41b8-9597-c6e55b0adcef. Dataset Ancestors Derived From NSW Office of Water GW licence extract linked to spatial locations NIC v2 (28 February 2014) Derived From NSW Office of Water Surface Water Entitlements Locations v1_Oct2013 Derived From Travelling Stock Route Conservation Values Derived From NSW Wetlands Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only Derived From Climate Change Corridors for Nandewar and New England Tablelands Derived From NSW Office of Water Surface Water Licences in NIC linked to locations v1 (22 April 2014) Derived From Birds Australia - Important Bird Areas (IBA) 2009 Derived From Spatial Threatened Species and Communities (TESC) NSW 20131129 Derived From Environmental Asset Database - Commonwealth Environmental Water Office Derived From Ecological assets of the Gwydir wetlands and floodplain 2008 VIS_ID 3923 Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA) Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only) Derived From Ramsar Wetlands of Australia Derived From Native Vegetation Management (NVM) - Manage Benefits Derived From Asset database for the Gwydir subregion on 24 August 2015 Derived From Key Environmental Assets - KEA - of the Murray Darling Basin Derived From Asset database for the Gwydir subregion on 8 May 2015 Derived From National Heritage List Spatial Database (NHL) (v2.1) Derived From Great Artesian Basin and Laura Basin groundwater recharge areas Derived From NSW Office of Water combined geodatabase of regulated rivers and water sharing plan regions Derived From New South Wales NSW Regional CMA Water Asset Information WAIT tool databases, RESTRICTED Includes ALL Reports Derived From New South Wales NSW - Regional - CMA - Water Asset Information Tool - WAIT - databases Derived From Collaborative Australian Protected Areas Database (CAPAD) 2010 (Not current release) Derived From Australia - Species of National Environmental Significance Database Derived From NSW Office of Water Surface Water Offtakes - NIC v1 20131024 Derived From NSW Office of Water Groundwater Licence Extract NIC- Oct 2013 Derived From Australia, Register of the National Estate (RNE) - Spatial Database (RNESDB) Internal Derived From NSW Office of Water Groundwater Entitlements Spatial Locations Derived From National Groundwater Dependent Ecosystems (GDE) Atlas Derived From Directory of Important Wetlands in Australia (DIWA) Spatial Database (Public) Derived From NSW Office of Water Groundwater licences extract linked to spatial locations NIC v3 (13 March 2014)

Systematic review of 434 references dealing with up-to-date contributions describing the links between Biodiversity (BD)- Ecosystem Functions (EF)- Ecosystem Services (ES) - Human Well Being (HWB). Details on the methodology for data collection are explained at Pascual et al., 2016. (Ecosystem Services, Volume 17, Pages 112–122).Paper source must be cited if the entire or part of the data contained here is to be used for future publications (Cite: Pascual, M., Pérez Miñana, E., Giacomello, E. (2016). Integrating knowledge on biodiversity and ecosystem services: Mind-mapping and Bayesian Network modelling. Ecosystem Services 16: 112-122. doi:10.1016/j.ecoser.2015.12.004

This database compiles systematic reviews (SRs) of animal studies (i.e., reviews that focused exclusively on non-human animal research, or reviews that included animal studies along with human studies). This database was developed using a rigorous, systematic approach and it covers a broad range of research fields: preclinical research, toxicology, environmental health, and veterinary medicine. The goals of this database are to: (1) provide a comprehensive collection of animal study SRs to advance systematic review methods development; (2) enable researchers to avoid duplication of effort and, thus, reduce research waste by identifying published SRs of animal studies that may already address a research question; and (3) aid in the creation of evidence maps, usually designed as interactive figures of study characteristics.

The SRs included in the database were identified using a comprehensive search strategy (see data) in MEDLINE (via PubMed), Embase (via Ovid), and Web of Science. The records included in the animal studies SR database meet the following eligibility criteria: 1. The reference aims to systematically review the literature. The title or abstract states this aim using terminology such as “literature review,” “literature overview,” “systematic review,” “systematic survey,” or “meta-analysis.” 2. The reference summarizes the results of studies in laboratory or experimental animals to investigate human or animal health. 3. The reference reports the eligibility criteria for the primary studies, specifies search terms, and the search is performed in at least one specified database/electronic source (e.g., PubMed). 4. A full text version of the reference is publicly available.

There were no restrictions in language or publication date.

Version 1.0 covers data through 13 February 2018 Version 1.1 covers data through 18 June 2019

See full Resource Data Guide here.Abstract: The Natural Diversity Database Areas is a 1:24,000-scale, polygon feature-based layer that represents general locations of endangered, threatened and special concern species. The layer is based on information collected by DEEP biologists, cooperating scientists, conservation groups and landowners. In some cases an occurrence represents a location derived from literature, museum records and specimens. These data are compiled and maintained by the DEEP Bureau of Natural Resources, Natural Diversity Database Program. The layer is updated every six months and reflects information that has been submitted and accepted up to that point. The layer includes state and federally listed species. It does not include Critical Habitats, Natural Area Preserves, designated wetland areas or wildlife concentration areas. These general locations were created by randomly shifting the true locations of terrestrial species and then adding a 0.25 mile buffer distance to each point, and by mapping linear segments with a 300 foot buffer associated with aquatic, riparian and coastal species. The exact location of the species observation falls somewhere within the polygon area and not necessarily in the center. Attribute information includes the date when these data were last updated. Species names are withheld to protect sensitive species from collection and disturbance. Data is compiled at 1:24,000 scale. These data are updated every six months, approximately in June and December. It is important to use the most current data available.Purpose: This dataset was developed to help state agencies and landowners comply with the State Endangered Species Act. Under the Act, state agencies are required to ensure that any activity authorized, funded or performed by the state does not threatened the continued existence of endangered or threatened species or their essential habitat. Applicants for certain state and local permits may be required to consult with the Department of Energy and Environmental Protections's Natural Diversity Data Base (NDDB) as part of the permit process. Follow instructions provided in the appropriate permit guidance. If you require a federal endangered species review, work with your federal regulatory agency and review the US Fish & Wildlife IPaC tool. Natural Diversity Data Base Areas are intended to be used as a pre-screening tool to identify potential impacts to known locations of state listed species. To use this data for site-based endangered species review, locate the project boundaries and any additionally affected areas on the map. If any part of the project is within a NDDB Area then the project may have a conflict with listed species. In the case of a potential conflict, an Environmental Review Request (https://portal.ct.gov/deep-nddbrequest) should be made to the Natural Diversity Data Base for further review. The DEEP will provide recommendations for avoiding impacts to state listed species. Additional onsite surveys may be requested of the applicant depending on the nature and scope of a project. For this reason, applicants should apply early in the planning stages of a project. Not all land use choices will impact the particular species that is present. Often minor modifications to the proposed plan can alleviate conflicts with state listed species.Other uses of the data include targeting areas for conservation or site management to enhance and protect rare species habitats.Supplemental information: For additional information, refer to the Department of Energy and Environmental Protection Endangered Species web page at https://portal.ct.gov/DEEP/Endangered-Species/Connecticuts-Endangered-Threatened-and-Special-Concern-Species

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

The asset database for Arckaringa subregion (v5) supersedes previous versions of the Arckaringa Asset database (Asset database for the Arckaringa subregion on 27 August 2015, GUID: 7680ecd5-8942-44a2-80a4-d510eee1871d). Total number of registered water assets in this V5 was increased by 2 because two assets changed M2 test from "No" to "Yes" from M2 test review done by Ecologist group.

This dataset contains v3 of the Asset database (ARC_asset_database_20160304.mdb), a Geodatabase version for GIS mapping purposes (ARC_asset_database_GISOnly_20160304.gdb), an updated draft Water Dependent Asset Register spreadsheet (BA-LEB-ARC-130-WaterDependentAssetRegister-AssetList-v20160304.xlsx), a data dictionary (ARC_asset_database_doc_20160304.doc), and a folder (NRM_DOC) containing documentation associated with the Water Asset Information Tool (WAIT) process.

This dataset contains a combination of spatial and non-spatial (attribute) components of the Arckaringa subregion Asset List - an mdb file (readable as an MS Access database or as an ESRI personal geodatabase) holds the non-spatial tabular attribute data, and an ESRI file geodatabase contains the spatial data layers, which are attributed only with unique identifiers ("AID" for assets, and "ElementID" for elements).

The tabular attribute data can be joined in a GIS to the "Assetlist" table in the mdb database using the "AID" field to view asset attributes (BA attribution). To view the more detailed attribution at the element-level, the intermediate table "Element_to_asset" can be joined to the assets spatial datasets using AID, and then joining the individual attribute tables from the Access database using the common "ElementID" fields. Alternatively, the spatial feature layers representing elements can be linked directly to the individual attribute tables in the Access database using "ElementID", but this arrangement will not provide the asset-level groupings.

Further information is provided in the accompanying document, "ARC_asset_database_doc_20160304.doc" located within this dataset.

The public version of this asset database can be accessed via the following dataset: Asset database for the Arckaringa subregion on 04 March 2016 Public (https://data.gov.au/data/dataset/f64b6216-7b7a-4a7e-9420-d1a801d59d5d)

Dataset History

VersionID Date Notes

1.0 17/03/2015 Initial database

1.1 19/03/2015 Add SA point Eco data ( 2 assets and 67 Elements) and fix some AIDs in table AssetDecisions

2 16/04/2015 remove 6 elements ('NGIS_Bore_HydroID_30020907','NGIS_Bore_HydroID_30020908','NGIS_Bore_HydroID_30020921','Unit No 633800074_South Australian Arid Lands_56231','Unit No 633800075_South Australian Arid Lands_56239','Unit No 633900013_South Australian Arid Lands_56243') from relevant tables and reprocess two assets with AIDs 17632 and 17648 without above 3 elements for each, base on SA state information after asset community workshop

3 7/08/2015 (1) Updated the database for M2 test results provided from ARC assessment team and created the draft BA-LEB-ARC-130-WaterDependentAssetRegister-AssetList-V20150807.xlsx

(2) updated the group, subgroup, class and depth for (up to) 141 NRM WAIT assets to cooperate the feedback to OWS from relevant SA NRM regional office (whose staff missed the asset workshop). The AIDs and names of those assets are listed in table LUT_changed_asset_class_20150807 in ARC_asset_database_20150807.mdb

(3) As a result of (2), added three new assets separated from three exiting assets. Those assets and their parents are listed in table LUT_ADD_3_asstes_20150807 in ARC_asset_database_20150807.mdb. The M2 and M3 test results for those 3 assets are inherited from their parents in this version

(4) Four assets' names from RNE data source were changed for confidential reason and they are listed in table LUT_changed_RNE_20150807 in ARC_asset_database_20150807.mdb

(5) Added Appendix C in ARC_asset_database_doc_201500807.doc is about total elements/assets in current Group and subgroup

(6)Added Four SQL queries (Find_All_Used_Assets, Find_All_WD_Assets, Find_Amount_Asset_in_Class and Find_Amount_Elements_in_Class) in ARC_asset_database_20150807.mdb for total assets and total numbers

(7)The databases, especially spatial database (ARC_asset_database_20150807Only.gdb), were changed such as duplicated attribute fields in spatial data were removed and only ID field is kept. The user needs to join the Table Assetlist or Elementlist to the relevant spatial data.

('NGIS_Bore_HydroID_30020907','NGIS_Bore_HydroID_30020908','NGIS_Bore_HydroID_30020921','Unit No 633800074_South Australian Arid Lands_56231','Unit No 633800075_South Australian Arid Lands_56239','Unit No 633900013_South Australian Arid Lands_56243') from relevant tables and reprocess two assets with AIDs 17632 and 17648 without above 3 elements for each, base on SA state information after asset community workshop.

1. 27/08/2015 M2_Reason in the Assetlist table and DecisionBrief in the AssetDecisions table have been updated with short descriptions (<255 characters) provided by project team 21/8, and the draft "water-dependent asset register and asset list" (BA-LEB-ARC-130-WaterDependentAssetRegister-AssetList-V20150827) also updated accordingly. No changes to asset numbers.

5 4/03/2016 "(1) Total number of registered water assets was increased by 2 because two assets changed M2 test from "No" to "Yes" from M2 test review done by Ecologist group.

(2) The draft new Water Dependent Asset Register was created"

Dataset Citation

Bioregional Assessment Programme (2014) Asset database for the Arckaringa subregion on 04 March 2016. Bioregional Assessment Derived Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/c6fa12de-6b4b-47b9-8b8e-5ad9a4ccc4c0.

Dataset Ancestors

• Derived From Asset database for the Arckaringa subregion on 16 April 2015

• Derived From Geofabric Surface Network - V2.1

• Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only

• Derived From South Australia SA - Regional - NRM Board - Water Asset Information Tool - WAIT - databases

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas

• Derived From National Groundwater Information System (NGIS) v1.1

• Derived From Birds Australia - Important Bird Areas (IBA) 2009

• Derived From Asset database for the Arckaringa subregion on 18 March 2015

• Derived From SA Department of Environment, Water and Natural Resources (DEWNR) Water Management Areas 141007

• Derived From South Australian Wetlands - Groundwater Dependent Ecosystems (GDE) Classification

• Derived From Asset database for the Arckaringa subregion on 27 August 2015

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA)

• Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only)

• Derived From Asset database for the Arckaringa subregion on 19 March 2015

• Derived From Permanent and Semi-Permanent Waterbodies of the Lake Eyre Basin (Queensland and South Australia) (DRAFT)

• Derived From SA EconomicElements v1 20141201

• Derived From National Heritage List Spatial Database (NHL) (v2.1)

• Derived From Great Artesian Basin and Laura Basin groundwater recharge areas

• Derived From Northern Territory Groundwater Management Units 20140630

• Derived From Northern Territory - Lake Eyre Basin - Wetlands Mapping - METADATA ONLY

• Derived From Asset database for the Arckaringa subregion on 07 August 2015

• Derived From SA Department of Environment, Water and Natural Resources (DEWNR) Groundwater Licences 141007

• Derived From Lake Eyre Basin (LEB) Aquatic Ecosystems Mapping and Classification

• Derived From [Australia -

Species introductions of anthropogenic origins are a major aspect of rapid ecological change globally. Research on biological invasions has generated literature on many different aspects of this phenomenon. This literature is enormous and has grown rapidly since the mid‐twentieth century. Therefore, we created this dataset in order to describe and categorize some aspects of this literature, to better understand what has been studied and what we know, mapping well‐studied areas and important gaps. To do so, we employed the techniques of systematic reviewing widely adopted in other scientific disciplines. We identified 2398 relevant studies in a field synopsis of the biological invasions literature. The purpose of the field synopsis was to map and categorize the scope of available information (and what is not known) from the literature addressing a fundamental understanding of biological invasions. We then examined 1537 papers in greater detail in a systematic review. The systematic review addressed the state of our knowledge about the mechanisms that permit species to invade novel environments. We carried this out by attempting to identify and characterize the literature, including what hypotheses have been tested, and what organisms and systems have been studied. A secondary goal of our work was to create a publicly accessible database of this literature for future research.

description: This is one of several important historical documents associated with remediation activities at the Rocky Flats National Wildlife Refuge. The Rocky Flats National Wildlife Refuge was once of 13 nuclear weapons production facilities in the United States during the Cold War and was managed by the Department of Energy (DOE). The plant operated from 1952 to 1994 with manufacturing activities taking place in the center portion of the site with a large buffer zone around the area. In 1989, nuclear production work stopped to address environmental and safety concerns. Although work resumed in 1990, the mission was terminated when President George H. W. Bush canceled the W-88 Trident Warhead program in 1992. Nuclear and nonnuclear production stopped in 1993, and in 1994 the last shipment of defense-related materials was sent off-site.When the facilitys mission changed from production to cleanup and closure, it was renamed the Rocky Flats Environmental Technology Site (RFETS). The site was added to the Environmental Protection Agencys National Priorities List (Superfund List) in 1989. With oversight from the EPA and Colorado Department of Public Health and the Environment (CDPHE), the DOE completed the $7 billion dollar cleanup in 2005. The Rocky Flats National Wildlife Refuge Act of 2001 (Pub.L. 107-107, 115 Stat. 1379, enacted December 8, 2001), mandated that once remediation was complete the site would become a national wildlife refuge.U.S. Fish and Wildlife Service (Service) policy requires a Level III Preacquisition Survey when it is determined, on the basis of the Level I or II Survey, that there is a reasonable basis to assume that hazardous substances were present on the real property or that there were effects of such hazardous substances present at the site, and extensive work (e.g. "significant" sampling and original research) is required to determine the extent of any hazardous substance, obtain an estimate of the remediation or other cleanup costs, and determine whether reprogramming is required. Although no formal Level I or II Surveys were conducted at the RFETS, the history of the site, coupled with evidence of contamination revealed during extensive DOE and contractor sampling, before and during the Remedial Investigation/Feasibility Study (RI/FS), provided reasonable basis to conduct a Modified Level III Survey.This report concludes that the review of the data collected by DOE and their contractors and stored in the RI-ready database showed that the database used for the Remedial Investigation was of adequate quality to make determinations on the clean up process and the comprehensive risk assessment. The Service was included in the comprehensive risk assessment workgroup and was presented the opportunity, along with the EPA and CDPHE to comment on the development and assumptions used in the risk assessment. The comprehensive risk assessment was conservative enough in its assumptions that clean up work that was completed by DOE and its contractor, for all receptors at the Rocky Flats National Wildlife Refuge, are protective of human health and the environment in the Peripheral OU. Supplementary/confirmatory sampling done by Service personnel supported the database used by DOE and its contractor and the comprehensive risk assessment. Service sampling results were, although not always at or below background levels, well within the range of results that DOE presented in their RI-ready database.The refuge was officially established in 2007.; abstract: This is one of several important historical documents associated with remediation activities at the Rocky Flats National Wildlife Refuge. The Rocky Flats National Wildlife Refuge was once of 13 nuclear weapons production facilities in the United States during the Cold War and was managed by the Department of Energy (DOE). The plant operated from 1952 to 1994 with manufacturing activities taking place in the center portion of the site with a large buffer zone around the area. In 1989, nuclear production work stopped to address environmental and safety concerns. Although work resumed in 1990, the mission was terminated when President George H. W. Bush canceled the W-88 Trident Warhead program in 1992. Nuclear and nonnuclear production stopped in 1993, and in 1994 the last shipment of defense-related materials was sent off-site.When the facilitys mission changed from production to cleanup and closure, it was renamed the Rocky Flats Environmental Technology Site (RFETS). The site was added to the Environmental Protection Agencys National Priorities List (Superfund List) in 1989. With oversight from the EPA and Colorado Department of Public Health and the Environment (CDPHE), the DOE completed the $7 billion dollar cleanup in 2005. The Rocky Flats National Wildlife Refuge Act of 2001 (Pub.L. 107-107, 115 Stat. 1379, enacted December 8, 2001), mandated that once remediation was complete the site would become a national wildlife refuge.U.S. Fish and Wildlife Service (Service) policy requires a Level III Preacquisition Survey when it is determined, on the basis of the Level I or II Survey, that there is a reasonable basis to assume that hazardous substances were present on the real property or that there were effects of such hazardous substances present at the site, and extensive work (e.g. "significant" sampling and original research) is required to determine the extent of any hazardous substance, obtain an estimate of the remediation or other cleanup costs, and determine whether reprogramming is required. Although no formal Level I or II Surveys were conducted at the RFETS, the history of the site, coupled with evidence of contamination revealed during extensive DOE and contractor sampling, before and during the Remedial Investigation/Feasibility Study (RI/FS), provided reasonable basis to conduct a Modified Level III Survey.This report concludes that the review of the data collected by DOE and their contractors and stored in the RI-ready database showed that the database used for the Remedial Investigation was of adequate quality to make determinations on the clean up process and the comprehensive risk assessment. The Service was included in the comprehensive risk assessment workgroup and was presented the opportunity, along with the EPA and CDPHE to comment on the development and assumptions used in the risk assessment. The comprehensive risk assessment was conservative enough in its assumptions that clean up work that was completed by DOE and its contractor, for all receptors at the Rocky Flats National Wildlife Refuge, are protective of human health and the environment in the Peripheral OU. Supplementary/confirmatory sampling done by Service personnel supported the database used by DOE and its contractor and the comprehensive risk assessment. Service sampling results were, although not always at or below background levels, well within the range of results that DOE presented in their RI-ready database.The refuge was officially established in 2007.

The Priority Habitats of Rare Species datalayer contains polygons representing the geographic extent of Habitat of state-listed rare species in Massachusetts based on observations documented within the last 25 years in the database of the Natural Heritage & Endangered Species Program (NHESP). Priority Habitat polygons are the filing trigger for project proponents, municipalities, and all others for determining whether or not a proposed project or activity must be reviewed by the NHESP for compliance with the Massachusetts Endangered Species Act (MESA) and its implementing regulations. Areas delineated as Priority Habitats can include wetlands, uplands, and marine habitats-in fact, over half of the total acreage of Priority Habitat is mapped for marine habitats of state-listed rare species. The Priority Habitats presented here are those published in the 13th Edition of the Massachusetts Natural Heritage Atlas, and are effective beginning October 1, 2008. If your project or activity falls within Priority Habitat and does not meet a MESA filing exemption (321 CMR 10.14), then you must file directly with the NHESP pursuant to MESA. For more information, please see the Regulatory Review section of the NHESP website. The Priority Habitats of Rare Species datalayer is stored in ArcSDE as PRIHAB_POLY. Occurrence records are continually being added, updated, deleted or otherwise modified in the NHESP database. These changes are incorporated into revisions to the Priority Habitats of Rare Species datalayer every two years and are displayed in the latest Natural Heritage Atlas. Questions about the creation of this datalayer should be directed to NHESP at 508-389-6375. For questions relating to the use of this datalayer in Environmental Review, please call 508-389-6380.

ObjectsHealth Behaviours in School-aged Children (HBSC) is an international survey programme aiming to investigate adolescents’ health behaviours, subjective perception of health status, wellbeing, and the related contextual information. Our scoping review aimed to synthesise the evidence from HBSC about the relationship between family environmental contributors and adolescents’ health-related outcomes.MethodsWe searched previous studies from six electronic databases. Two researchers identified the qualified publications independently by abstract and full-text screening with the assistance of an NLP-based AI instrument, ASReview. Publications were included if they were based on HBSC data and investigated the effects of family environment on adolescents’ health outcomes. Researches addressed family-related factors as mediators or moderators were also included.ResultsA total of 241 articles were included. Family environmental contributors could be mapped into six categories: (1) Demographic backgrounds (N = 177); (2) General family’s psycho-socio functions (N = 44); (3) Parenting behaviours (N = 100); (4) Parental health behaviours (N = 7); (5) Family activities (N = 24); and (6) Siblings (N = 7). Except for 75 papers that assessed family variables as moderators (N = 70) and mediators (N = 7), the others suggested family environment was an independent variable. Only five studies employed the data-driven approach.ConclusionOur results suggest most research studies focussed on the influences of family demographic backgrounds on adolescents’ health. The researches related to parental health behaviours and siblings are most inadequate. Besides, we recommend further research studies to focus on the mediator/moderator roles of the family, for exploring the deep mechanism of the family’s impacts. Also, it would be valuable to consider data-driven analysis more in the future, as HBSC has mass variables and data.

Abstract The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this …Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived. Asset database for the Hunter subregion on 24 February 2016 (V2.5) supersedes the previous version of the HUN Asset database V2.4 (Asset database for the Hunter subregion on 20 November 2015, GUID: 0bbcd7f6-2d09-418c-9549-8cbd9520ce18). It contains the Asset database (HUN_asset_database_20160224.mdb), a Geodatabase version for GIS mapping purposes (HUN_asset_database_20160224_GISOnly.gdb), the draft Water Dependent Asset Register spreadsheet (BA-NSB-HUN-130-WaterDependentAssetRegister-AssetList-V20160224.xlsx), a data dictionary (HUN_asset_database_doc_20160224.doc), and a folder (NRM_DOC) containing documentation associated with the Water Asset Information Tool (WAIT) process as outlined below. This version should be used for Materiality Test (M2) test. The Asset database is registered to the BA repository as an ESRI personal goedatabase (.mdb - doubling as a MS Access database) that can store, query, and manage non-spatial data while the spatial data is in a separate file geodatabase joined by AID/ElementID. Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. A report on the WAIT process for the Hunter is included in the zip file as part of this dataset. Elements are initially included in the preliminary assets database if they are partly or wholly within the subregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list. Descriptions of the assets identified in the Hunter subregion are found in the "AssetList" table of the database. Assets are the spatial features used by project teams to model scenarios under the BA program. Detailed attribution does not exist at the asset level. Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of "HUN_asset_database_doc_20160224.doc ", located in this filet. The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset. Detailed information describing the database structure and content can be found in the document "HUN_asset_database_doc_20160224.doc" located in this file. Some of the source data used in the compilation of this dataset is restricted. The public version of this asset database can be accessed via the following dataset: Asset database for the Hunter subregion on 24 February 2016 Public 20170112 v02 (https://data.gov.au/data/dataset/9d16592c-543b-42d9-a1f4-0f6d70b9ffe7) Dataset History OBJECTID VersionID Notes Date_ 1 1 Initial database. 29/08/2014 3 1.1 Update the classification for seven identical assets from Gloucester subregion 16/09/2014 4 1.2 Added in NSW GDEs from Hunter - Central Rivers GDE mapping from NSW DPI (50 635 polygons). 28/01/2015 5 1.3 New AIDs assiged to NSW GDE assets (Existing AID + 20000) to avoid duplication of AIDs assigned in other databases. 12/02/2015 6 1.4 "(1) Add 20 additional datasets required by HUN assessment project team after HUN community workshop (2) Turn off previous GW point assets (AIDs from 7717-7810 inclusive) (3) Turn off new GW point asset (AID: 0) (4) Assets (AIDs: 8023-8026) are duplicated to 4 assets (AID: 4747,4745,4744,4743 respectively) in NAM subregion . Their AID, Asset Name, Group, SubGroup, Depth, Source, ListDate and Geometry are using values from that NAM assets. (5) Asset (AID 8595) is duplicated to 1 asset ( AID 57) in GLO subregion . Its AID, Asset Name, Group, SubGroup, Depth, Source, ListDate and Geometry are using values from that GLO assets. (6) 39 assets (AID from 2969 to 5040) are from NAM Asset database and their attributes were updated to use the latest attributes from NAM asset database (7)The databases, especially spatial database, were changed such as duplicated attributes fields in spatial data were removed and only ID field is kept. The user needs to join the Table Assetlist or Elementlist to the spatial data" 16/06/2015 7 2 "(1) Updated 131 new GW point assets with previous AID and some of them may include different element number due to the change of 77 FTypes requested by Hunter assessment project team (2) Added 104 EPBC assets, which were assessed and excluded by ERIN (3) Merged 30 Darling Hardyhead assets to one (asset AID 60140) and deleted another 29 (4) Turned off 5 assets from community workshop (60358 - 60362) as they are duplicated to 5 assets from 104 EPBC excluded assets (5) Updated M2 test results (6) Asset Names (AID: 4743 and 4747) were changed as requested by Hunter assessment project team (4 lower cases to 4 upper case only). Those two assets are from Namoi asset database and their asset names may not match with original names in Namoi asset database. (7)One NSW WSP asset (AID: 60814) was added in as requested by Hunter assessment project team. The process method (without considering 1:M relation) for this asset is not robust and is different to other NSW WSP assets. It should NOT use for other subregions. (8) Queries of Find_All_Used_Assets and Find_All_WD_Assets in the asset database can be used to extract all used assts and all water dependant assts" 20/07/2015 8 2.1 "(1) There are following six assets (in Hun subregion), which is same as 6 assets in GIP subregion. Their AID, Asset Name, Group, SubGroup, Depth, Source and ListDate are using values from GIP assets. You will not see AIDs from AID_from_HUN in whole HUN asset datable and spreadsheet anymore and you only can see AIDs from AID_from_GIP ( Actually (a) AID 11636 is GIP got from MBC (B) only AID, Asset Name and ListDate are different and changed) (2) For BA-NSB-HUN-130-WaterDependentAssetRegister-AssetList-V20150827.xlsx, (a) Extracted long ( >255 characters) WD rationale for 19 assets (AIDs: 8682,9065,9073,9087,9088,9100,9102,9103,60000,60001,60792,60793,60801,60713,60739,60751,60764,60774,60812 ) in tab "Water-dependent asset register" and 37 assets (AIDs: 5040,8651,8677,8682,8650,8686,8687,8718,8762,9094,9065,9067,9073,9077,9081,9086,9087,9088,9100,9102,9103,60000,60001,60739,60742,60751,60713,60764,60771, 60774,60792,60793,60798,60801,60809,60811,60812) in tab "Asset list" in 1.30 Excel file (b) recreated draft BA-NSB-HUN-130-WaterDependentAssetRegister-AssetList-V20150827.xlsx (3) Modified queries (Find_All_Asset_List and Find_Waterdependent_asset_register) for (2)(a)" 27/08/2015 9 2.2 "(1) Updated M2 results from the internal review for 386 Sociocultural assets (2)Updated the class to Ecological/Vegetation/Habitat (potential species distribution) for assets/elements from sources of WAIT_ALA_ERIN, NSW_TSEC, NSW_DPI_Fisheries_DarlingHardyhead" 8/09/2015 10 2.3 "(1) Updated M2 results from the internal review * Changed "Assessment team do not say No" to "All economic assets are by definition water dependent" * Changed "Assessment team say No" : to "These are water dependent, but excluded by the project team based on intersection with the PAE is negligible" * Changed "Rivertyles" to "RiverStyles"" 22/09/2015 11 2.4 "(1) Updated M2 test results for 86 assets from the external review (2) Updated asset names for two assets (AID: 8642 and 8643) required from the external review (3) Created Draft Water Dependent Asset Register file using the template V5" 20/11/2015 12 2.5 "Total number of registered water assets was increased by 1 (= +2-1) due to: Two assets changed M2 test from "No" to "Yes" , but one asset assets changed M2 test from "Yes" to "No" from the review done by Ecologist group." 24/02/2016 Dataset Citation Bioregional Assessment Programme (2015) Asset database for the Hunter subregion on 24 February 2016. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/a39290ac-3925-4abc-9ecb-b91e911f008f. Dataset Ancestors Derived From GW Element Bores with Unknown FTYPE Hunter NSW Office of Water 20150514 Derived From Travelling Stock Route Conservation Values Derived From Spatial Threatened Species and Communities (TESC) NSW 20131129 Derived From NSW Wetlands Derived From Climate Change Corridors Coastal North East NSW Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only Derived From Climate Change Corridors for Nandewar and New England Tablelands Derived From National Groundwater Dependent Ecosystems (GDE) Atlas Derived From Asset database for the Hunter subregion on 27 August 2015 Derived From Birds Australia - Important Bird Areas (IBA) 2009 Derived From Estuarine Macrophytes of Hunter Subregion NSW DPI Hunter 2004 Derived From Hunter CMA GDEs (DRAFT DPI pre-release) Derived From Camerons Gorge Grassy White Box Endangered Ecological Community (EEC) 2008 Derived From NSW Office of Water Surface Water Licences Processed for Hunter v1 20140516 Derived From Fauna Corridors for North East NSW Derived From Asset database for the Hunter subregion on 12 February 2015 Derived From New South Wales NSW Regional CMA Water Asset Information WAIT tool databases,