library(mapview)
library(aqm)
## 
## Attaching package: 'aqm'
## The following object is masked from 'package:stats':
## 
##     dt
library(sf)
## Warning: package 'sf' was built under R version 4.0.5
## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1

Introduction

In 2017, 2018 and 2019 students on this unit conducted field work at Arne in order to collect some original data for analysis.

From the perspective of the ILOs of the unit the objective of the study was to put into practice some of the techniques for analysing data using both spatially explicit and no spatial techniques.

The questions being addressed by the exercise revolved around the management of lowland heathland, but also has some broader ecological relevance.

Scots pine (Pinus sylvestris) is native to the UK. There is evidence that the species was once quite widely distributed Southern England and may have been a common species in the neolithic landscape [@whitehouse2010] Habitats in the UK have been influenced by human activity throughout the holocene, in a wide range of different ways. Scots pine appears to have been extirpated from most England by human over exploitation and clearance for agriculture by around 6500 years before present leading to the widespread development of open heathland by around 3000 years before present[@groves2012]. The precise cause and date of the loss is not entirely clear. Pines were reintroduced for timber in the 17th century and those found at Arne probably have an originally central European provenance. They are therefore often regarded as an introduced species. The pine forests in Dorset are the result of deliberate management for timber. Lowland heath is a priority habitat for conservation and management at Arne is focussed on the restoration of open heathland, with some scattered trees. A challenge for management arises as a result of natural regeneration of pines in the open heath and difficulties in retaining previously forested areas as heathland after felling.

Pines establishing on heathland may show less vigorous growth than those establishing after felling. A possible explanation for this may be the presence of mycorrhizal fungi that mediate invasion [@collier2009].

In 2019 the students looked at the differences between the growth of young pines in two areas at Arne. The aim was to quantify any detectable difference using a study that could be designed to be conducted in less than two hours. As it was raining heavily the study was restricted to two small areas. It is worth pointing out that this causes some difficulties for formal inference due to spatial autocorrelation. You can ignore this for the purposes of the exercise.

The diameter of young regenerating pines 3cm above the ground was measured together with their height. An estimate of age was also made by counting the number of whorls. GPS way points were recorded and matched to the data.

Un the following code to load the data.

data(arne_pine_hts)
pine_hts$Site<-as.factor(pine_hts$Site)
 pine_hts %>% st_drop_geometry() -> d ## Take out geometry and make a simple data fram called d
 # Convert the numerical value of the site to a factor
mapview(pine_hts,z="Site") 
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()

Pines growing at site 2 had regenerated following clearance. The clearance of the pines even shows up on a global classification of Landsat derived satellite imagery [@hansen2013]

mapview(pine_hts,z="Site") %>% giscourse::hansen_wms()
## Loading required package: leaflet.extras
## Loading required package: leaflet
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()