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ahmnimble

aphalara

butterfly_trends

Analysis of population trends of butterflies monitored in Ohio since 1995.

carbon_trends

chap1-bfly-landuse-climate

Species' responses to climate variability

collisions

Visualization of bicycle collisions in Montreal

common_garden

counting-butterflies

Correct citizen science counts for abundance estimates

ddrp-cohorts-v1

The objective of the Degree-Day, establishment Risk, and Pest event mapping system (DDRP) is to predict phenology and climate suitability of invasive, biocontrol, and IPM species for the conterminous United States. DDRP is written entirely in the R statistical programming language (R Development Core Team 2019), making it flexible and extensible, and has a simple command-line interface that has already been adapted for online use. The platform can use a variety of gridded weather and climate data types for any historical (post-hoc), real-time, or future (downscaled GCM) time period. Model products include gridded (raster) and graphical outputs of number of completed generations, phenological/pest events, and climate suitability (i.e., establishment risk maps).

ddrp_v2

A final production version of the DDRP platform that includes cohorts, parallel processing, and improving mapping routines. The objective of the Degree-Day, establishment Risk, and Pest event mapping system (DDRP) is to predict phenology and climate suitability of invasive, biocontrol, and IPM species for the conterminous United States. DDRP is written entirely in the R statistical programming language (R Development Core Team 2019), making it flexible and extensible, and has a simple command-line interface that has already been adapted for online use. The platform can use a variety of gridded weather and climate data types for any historical (post-hoc), real-time, or future (downscaled GCM) time period. Model products include gridded (raster) and graphical outputs of number of completed generations, phenological/pest events, and climate suitability (i.e., establishment risk maps).

dynamic_shift_detector

A new tool for detecting changes in dynamic rules in population time series data

electability

fire_tradeoffs

gaura_pva

Population viability of Oenothera neomexicana

grevstad_etal_2021

Code and data to reproduce manuscript analysis and figures

ibutton-vs-weatherstation

Measure temperature at monitoring sites across Ohio

kruschke-doing_bayesian_data_analysis

John K. Kruschke's Doing Bayesian Data Analysis: A Tutorial with R and BUGS

movement-butterflies

Analyzing behavioral observations of butterfly flight using biangulation

multivoltine

Testing the lost generation hypothesis

ohbutterfly

ohio_bfly_predictions

ohiogdd

phen_mismatch

phenology-butterflies

Species' physiological traits and springtime emergence

photovoltinism

rankr

rent4ever

rmark

R package for interface to MARK for mark-recapture data analysis

shiny-examples

shiny-server