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Data · dataset · 2019

Great Bear Rainforest - landscape level planning data

Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp2/gy2qjh

This dataset was developed to analyze various forest management alternatives for the area under the 2016 Great Bear Rainforest order (GBR order).

Description

It was developed for the use with common forest management planning software, such as WOODSTOCK (Remsoft) or Forest Planning Studio Atlas (FPS-Atlas). The area under the GBR order objectives includes 5 timber supply areas (TSA): Kingcome, Mid Coast, North Coast, Strathcona, and small sections of the Pacific.

Geographical data were collected from the BC government's open data program in Canada (DataBC), and the BC government’s website on Strategic Land and Resource Planning for the GBR. The geographical databases accessed from public sources included: (1) administrative boundaries (e.g., GBR boundary, tree farm licenses, Indian reserves, etc.), (2) forest inventory (e.g., BC vegetation resource inventory, depletions to year 2015, environmentally sensitive areas, roads), and (3) management guidance (e.g., reserves, wildlife habitat areas, ungulate winter range, recreation inventory, sensitive watersheds, streams, rivers, lakes, wetlands).

Read the rest (3 more)

Some of the geographical datasets were not publicly available (e.g., logging operability) and are therefore not part of this dataset. The productive forest land base (PFLB) was established after excluding the Provincial and National Parks, reserves, various timber licences (tree farm licences, woodlots, other leases), and non-forested land. Coniferous tree-leading stands dominate the PFLB, with the most common species being western and mountain hemlock (Tsuga heterophylla and Tsuga mertensiana) (46.8%), western redcedar (Thuja plicata) (32.6%) and yellow cedar (Chamaecyparis nootkatensis) (8.9%).

The yield curves associated with each stand type, and spatially with each polygon, were imported from the latest Timber Supply Review (TSR) documents for the Kingcome and Mid Coast TSAs. For the North Coast and Strathcona TSAs, the stand type information in the latest TSR documents was used to develop yield curves using the Variable Density Yield Projection (VDYP) (Forest Analysis and Inventory Branch, 2009) and Table Interpolation Program for Stand Yields (TIPSY) (BC MFLNRO, 2016d) software tools.

The Pacific TSA does not have a published TSR document, yet the small sections of the Pacific TSA that fall under the GBR (0.7%) are spatially adjacent to the Kingcome TSA. It was assumed that Pacific TSA had similar yields and stand types to the Kingcome TSA The dataset represents the status quo at data preparation in the area.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Tabular 65%
Provenance · 2 source records, 25 field assertions
SourceKeyLast seenRaw
Borealisdoi:10.5683/SP2/GY2QJH10 d agoJSON v1
Agri-environmental Research Data Dataversedoi:10.5683/SP2/GY2QJH9 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:field:410204mapping · borealisdata ca dataversevocabulary-mapper@1.0.0keywords['ecosystem services']
concepts[field].anzsrc:field:410204mapping · borealisdata cavocabulary-mapper@1.0.0keywords['ecosystem services']
concepts[field].anzsrc:group:3103mapping · borealisdata cavocabulary-mapper@1.0.0keywords['Ecology']
concepts[field].anzsrc:group:3103mapping · borealisdata ca dataversevocabulary-mapper@1.0.0keywords['Ecology']
concepts[field].dataverse_subject:agricultural-sciencessource · borealisdata caconnector:borealisdata_ca@1.0.0/subjects
concepts[field].dataverse_subject:agricultural-sciencessource · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
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concepts[field].local:field:computer-science-aimapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
concepts[field].local:field:earth-environmentalmapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
concepts[field].local:field:economics-financemapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
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concepts[field].local:field:life-sciencesmapping · borealisdata caconnector:borealisdata_ca@1.0.0/subjects
concepts[field].local:field:life-sciencesmapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
concepts[field].local:field:mathematics-statisticsmapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
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concepts[field].local:field:ocean-atmosphericmapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · borealisdata ca dataverseconnector:borealisdata_ca_dataverse@1.0.0/subjects
concepts[modality].local:modality:tabularenrichment · borealisdata cakeyword-concept-rules@1.0.0title+description (65%)
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