tmr_partition_annual

<p>Annual variant of <code>tmr_partition</code>. Built from points rarefied with
<code>time_cols = "year"</code> only (one point per pixel per year) and
extracted against annual predictors. Predictors attached to each point
are <code>forest_cover</code>, <code>pr_ann</code> (annual precipitation), and
<code>elevation</code>, all z-scored. Uses
<code>n_spatial_folds = 2</code> and <code>n_temporal_folds = 2</code> for four
folds. Loaded with <code>data(tmr_partition_annual)</code>.</p>

datasets

Increases the ease of implementing a temporally-explicit modeling
methodology when building ecological niche and species distribution models.
Provides functions to assist with three major steps of temporally-explicit
models: (i) preprocessing species and environmental data and generating
suitable background or pseudoabsence data, (ii) building a niche model and
generating temporally-explicit predictions from that model, and (iii) model
postprocessing to explore spatiotemporal trends in model predictions.
Methodological and theoretical foundations are described in Ingenloff and
Peterson (2021) <doi:10.1111/2041-210X.13564>, Franklin (2010, ISBN:9780521700023),
Peterson et al. (2011, ISBN:9780691136882), Blonder (2018) <doi:10.1111/ecog.03187>,
Senay et al. (2013) <doi:10.1371/journal.pone.0071218>, and Li and Zhang (2024) <doi:10.48550/arXiv.2404.05933>.

Connor Hughes

TemporalModelR

Temporally Explicit Species Distribution Modelling

Mariana Castaneda-Guzman

Luis E. Escobar

tmr_partition_annual function

<p>A list as returned by <code>spatiotemporal_partition</code>.</p>

tmr_partition_annual: Pre-built spatiotemporal partition (annual workflow)

Description

Usage

Arguments

Format