R code as used for the publication "Combined species occurrence and density predictions to improve marine spatial management" in Ocean and Coastal Management (2021). Code was used to create a species distribution model to predict probability of occurrence and density for two bivalve species in New Zealand estuaries . Code uses boosted regression trees in the dismo package, combined with a bootstrap approach (code provided by FS, Stephenson et al. 2020). This code combines the probability of occurrence and abundance BRT's and spatial predictions. 3rd party data is not made publicly available yet, so randomly generated data is used as an example. See data availability statement in publication for access to original data
We used a species distribution modelling approach called random forest (RF) to predict the probabili...
Boosted Regression Trees. Excellent for data-poor spatial management but hard to use Marine resource...
Species distribution models (SDMs) are tools that combine species observations of occurrence, abunda...
R code as used for the publication "Combined species occurrence and density predictions to improve m...
Species distribution models (SDMs) are becoming an important tool for marine conservation and manage...
Contains R code to fit all spatial distribution models for Oystercatchers based on generalised funct...
Species Distribution Models (SDMs) are useful tools to project potential future species distribution...
These files are the data and code needed to reproduce the analysis of the manuscript "Estimating den...
This folder contains the code, functions, workflow, data and figures for the manuscript "Improving t...
The data files are output from a model to predict the benthic cover of Pocillopora meandrina in the ...
The data files are output from a model to predict the benthic cover of Montipora capitata in the Haw...
The r-code and raw data were used to clarify principles of habitat design for enhancing species dive...
The data files are output from a model to predict the benthic cover of Montipora patula in the Hawai...
The data files are output from a model to predict the benthic cover of Montipora flabellata in the H...
The data files are output from a model to predict the benthic cover of Porites compressa in the Hawa...
We used a species distribution modelling approach called random forest (RF) to predict the probabili...
Boosted Regression Trees. Excellent for data-poor spatial management but hard to use Marine resource...
Species distribution models (SDMs) are tools that combine species observations of occurrence, abunda...
R code as used for the publication "Combined species occurrence and density predictions to improve m...
Species distribution models (SDMs) are becoming an important tool for marine conservation and manage...
Contains R code to fit all spatial distribution models for Oystercatchers based on generalised funct...
Species Distribution Models (SDMs) are useful tools to project potential future species distribution...
These files are the data and code needed to reproduce the analysis of the manuscript "Estimating den...
This folder contains the code, functions, workflow, data and figures for the manuscript "Improving t...
The data files are output from a model to predict the benthic cover of Pocillopora meandrina in the ...
The data files are output from a model to predict the benthic cover of Montipora capitata in the Haw...
The r-code and raw data were used to clarify principles of habitat design for enhancing species dive...
The data files are output from a model to predict the benthic cover of Montipora patula in the Hawai...
The data files are output from a model to predict the benthic cover of Montipora flabellata in the H...
The data files are output from a model to predict the benthic cover of Porites compressa in the Hawa...
We used a species distribution modelling approach called random forest (RF) to predict the probabili...
Boosted Regression Trees. Excellent for data-poor spatial management but hard to use Marine resource...
Species distribution models (SDMs) are tools that combine species observations of occurrence, abunda...