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This analysis was prepared by the Fynbos Node of the South African Environmental Observation Network (SAEON).
Here we present the record of stream flow rates for the Langrivier catchment and rainfall from the Dwarsberg weather station in the Jonkershoek Valley for the period January 1961 to the end of June 2019. The Dwarsberg weather station is at 1214 metres above sea level on the boundary of the catchments of the Eerste, Berg and Sonderend rivers and is a good indicator of rainfall feeding the Berg and Theewaterskloof dams.
The City of Cape Town’s Draft Water Strategy is out for comment until the 15th March. This post provides a quick and opinionated précis of what it contains and the comments I’ve sent to the City. Even if you don’t agree with me, I encourage you to write to the City and have your say.
The Strategy in brief The document is structured around 5 “Commitments”, which are defined as “A willingness to give our time and energy to something that we believe in, a promise, a firm decision to do something”
The Basics Interlude Doing GIS from R Since I first started maintaining blog posts on handling spatial data in R perhaps the most common question I’ve received is “How do I handle big spatial data in R?”. I thought its finally time to provide a blog post to deal with this particular topic. The answer of course is that there are many, many ways.
Now I know those of you who have asked me in person are thinking “That’s not what he said when I asked?
A quick note on the structure of this tutorial Data Description Housekeeping Getting and cleaning the data, but first and foremost, projection!!! Let’s start with point data Raster data (mostly functions from library(raster)) Polygons! Going parallel!!! Animation! Some other data visualization and analysis But what about our poor cedars? Options for writing out spatial data This post follows on from Handling Spatial Data in R - #1. Getting started, which gives the basics on installing R and RStudio, CRAN Spatial Task Views and useful DIY resources.
Installing R (and RStudio) CRAN Spatial Task Views!!! Useful DIY resources Points, lines, polygons and rasters - R can handle them all. My aim for this post is to give you the basics required to teach yourself spatial data analysis in R - following 3 major sections listed above.
In the next post I provide a practical example working with point, line, polygon and raster data. If you’re already familiar with R then you can skip straight there, but you may be interested to check out the useful DIY resources before you go.
The current drought experienced by Cape Town and surrounds has brought the issue of climate change to the fore in public discourse (if it wasn’t already). It’s discussed extensively in the media and plays a prominent role in the City’s Water Outlook 2018 Report (Version 25 - updated 20 May 2018) as motivation for the need for long term bulk water augmentation schemes.
This is an updated quick and dirty analysis of the CapeNature fire database (spanning 1927 to 2017) to see if the major drought that is currently being experienced in the Cape Floristic Region has had any impact on the occurrence or extent of wildfires. I first ran this analysis exactly a year ago and I think you’ll find the new year’s worth of data quite interesting.
Wildfires are an essential component of fynbos, but components of the fire regime such as return interval need to be within certain bounds of variability to maintain healthy ecosystems.
This post provides an interactive visualization of the results of Le Maitre et al. 2016. Estimates of the impacts of invasive alien plants on water flows in South Africa. Water SA Vol. 42 No. 4. It aims to highlight how much water could be reclaimed by clearing alien species from our catchments.
The extreme drought that is gripping Cape Town and surrounds has municipalities desperately seeking options to augment bulk water supply.
Update! We submitted this project for the UN Global Pulse Data for Climate Action competition and won the Thematic Award for Climate Mitigation at COP23 in Bonn, Germany! :)
Recent advances have seen the development of near-real time monitoring tools that report on the state and changes in vegetation based on satellite observations, e.g. globalforestwatch.org. These tools are hugely valuable for managing ecosystems and for developing the long term records required to understand ecosystem dynamics and trajectories of change.
This is just a very quick post to point out a Smartphone App I’ve been working on that allows citizen scientists, field rangers and landowners to map threats to and impacts on biodiversity. These include a range of impacts from invasive alien plants, plant mortality, landslides or illegal vegetation clearing, etc.
NOTE: Unfortunately, release of the app has been released due to location accuracy issues with the app development platform I’ve been using see this post for details.