borealbirds Goto Github PK
Name: Boreal Avian Modelling Project
Type: Organization
Name: Boreal Avian Modelling Project
Type: Organization
Stores the model coefficients and the bird species indicators based on those coefficients, run in ALCES Online land use scenarios
Species Results API
Boreal Avian Modeling Project
The BAM guide to the analysis of messy bird data
Public facing website
Canada Warbler Zonation results for BCR 14
Critical Habitat ID work for Wood Thrush and Canada Warbler
Scripts that are used across projects (e.g., data pre-processing, lookup tables, etc)
A mini website describing the cross border birds and forestry project
noun: a mass of small bubbles
Generalized National Models
Phylogeny and species trait effects on detectability
Bird density models for Moose Cree FN
Nicole's work to evaluate the mig birds ranking matrix
A starting point for templating mini websites using R and Jekyll
Example point count data set with paired human and ARU data
Uses the cure4insect package to predict bird species abundance in two Patchworks harvest scenarios and in a NRV scenario simulating an absence of human footprint
Post-hoc binning provides a method of rapidly producing and assessing categorical models of bird density for a given study area using existing rasters of predicted bird density.
Calibrating indices of avian density from non-standardized survey data
A user-friendly way to calculate QPAD offsets
Point Count Data Analysis
Removal and distance sampling to populate the QPAD package
Fing of Fire project website
Tutorials describing BAM's analytical workflow (!= SOP)
This repo aims to keep everything that is needed to translate source data to expected WildTrax upload format
This repo has a step by step guide on how to run a prioritization in Zonation 5 along with the relevant information on the EHJV prioritization
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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An Open Source Machine Learning Framework for Everyone
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Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.