R

Wildlife management decisions are rarely settled by ecological data alone. They live or die in the messy human world of competing values. Understanding what people think and why is as much a scientific skill as counting animals in a field. This tutorial walks you through quantitative analysis of a real attitude survey, using R. Background and Learning Objectives The ecological context The Irish hare (Lepus timidus hibernicus) is a subspecies endemic to Ireland — found nowhere else on Earth. It has been present since before the last Ice Age, making it one of the island’s oldest residents and a genuine conservation priority. ...

Generate Random Sampling Points by Minimum Distance Anthony Caravaggi 2026-03-25 Overview This document demonstrates how to generate random sampling points within a polygon while enforcing a minimum distance between points using a Simple Sequential Inhibition (SSI) process. Libraries library(sf) library(spatstat.geom) library(spatstat.random) library(dplyr) library(ggplot2) library(maptiles) library(ggspatial) library(units) We load: sf for modern spatial data handling spatstat modules for generating spatial point patterns ggplot2 for plotting maptiles and ggspatial for modern basemaps and map annotations units to safely handle distance units (e.g. metres) First, create a bounding polygon using longitude and latitude coordinates in the WGS84 coordinate system. While this format is convenient for defining locations, it is not suitable for measuring distances because the units are in degrees rather than metres. To address this, the polygon is reprojected into the British National Grid coordinate system (EPSG:27700), which uses metres as its unit. This transformation is essential for ensuring that the minimum distance constraint applied later is accurate and interpretable. You can of course use our own shapefile if you don’t want to manually create a bounding polygon. ...