Anthropogenic land use is one of the dominant drivers of ongoing biodiversity loss on a global scale and it has often been asked how much biodiversity loss is “too much” for sustaining ecosystem function. Our new paper in the journal Science came out last week and attempts to quantify for the first time the global biodiversity intactness within the planetary boundary framework. I am absolutely delighted to have contributed to this study and it received quite a bit of media attention so far ( https://www.altmetric.com/details/9708902 ) with a number of nice articles in the BBC and the Guardian.
In our study we calculated the Biodiversity intactness index (BII) first proposed by Scholes and Biggs (2005) for the entire world using the local biodiversity estimates from the PREDICTS project and combined them with the best available down-scaled land-use information to date. We find that many terrestrial biomes are already well beyond the proposed biodiversity planetary boundary (previously defined and set as a precautionary 10% reduction of biodiversity intactness). Unless these ongoing trends are decelerated and stopped in the near future it is likely that biodiversity loss might corroborate national and international biodiversity conservation targets, ecosystem functioning and long-term sustainable development.
- Newbold, Tim, et al. “Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment.” Science 353.6296 (2016): 288-291. DOI: 10.1126/science.aaf2201
Scholes, R. J., and R. Biggs. “A biodiversity intactness index.” Nature 434.7029 (2005): 45-49. DOI: 10.1038/nature03289
A quick post to highlight a new publication in this weeks issue of Current Biology. Edwards et al. went for another piece on the land-sharing/land-sparing debate and presented a very nice case study. Land-sharing is often defined as combining “sustainable” agricultural production with higher biodiversity outcomes often at the tradeoff of harvesting less and loss of natural habitats. Land-sparing on the other hand attempts to prevent remaining natural habitat from being used by humans, but instead intensify production and increase yield from other areas, thus reducing their potential for wildlife-friendly farming. They combined field work from the Choco-andres region (Taxonomic focus: Birds) with simulation models to investigate which strategy might benefit biodiversity the most. Contrary to many other previous publications they focused on phylogenetic richness (PD) rather than “species richness”. Based on landscape simulation models they could show that PD decreases steadily with greater distance to forests, which is interesting because it demonstrates that land-sharing strategies might only be successful, if sufficient amounts of natural habitat are in close proximity, that can act as source habitat for dispersing species.
According to their analysis some species seem to benefit more from land-sparing strategies than others. Specific evolutionary traits thus might be ether beneficial or detrimental for surviving in intensive human land use such as agriculture. They conclude that land-sharing might be of limited benefit without the simultaneous protection of nearby blocks of natural habitat, which can only be achieved with a co-occurring land-sharing strategy.
Since quite some time ecological models have tried to incorporate both continuous and discrete characteristics of species into their models. Newbold et al. (2013) demonstrated that functional traits affect the response of tropical bird species towards land-use intensity. Tropical forest specialist birds seem to decrease globally in probability of presence and abundance in more intensively used forests. This patterns extends to many taxonomic groups and the worldwide decline of “specialist species” has been noted before by Clavel et al. (2011).
But how to acquire such data on habitat specialization? Ether you assemble your own exhaustive trait database or you query information from some of the openly available data sources. One could for instance be the IUCN redlist, which not only has expert-validated data on a species current threat status, but also on population size and also on a species habitat preference. Here IUCN follows its own habitat classification scheme ( http://www.iucnredlist.org/technical-documents/classification-schemes/habitats-classification-scheme-ver3 ). The curious ecologist and conservationist should keep in mind however, that not all species are currently assessed by IUCN.
There are already a lot of scripts available on the net from which you can get inspiration on how to query the IUCN redlist (Kay Cichini from the biobucket explored this already in 2012 ). Even better: Someone actually compiled a whole r-package called letsR full of web-scraping functions to access the IUCN redlist. Here is some example code for Perrin’s Bushshrike, a tropical bird quite common in central Africa
# Install package install.packages(letsR) library(letsR) # Perrin's or Four-colored Bushshrike latin name name <- 'Telophorus viridis' # Query IUCN status lets.iucn(name) #>Species Family Status Criteria Population Description_Year #>Telophorus viridis MALACONOTIDAE LC Stable 1817 #>Country #>Angola, Congo, The Democratic Republic of the Congo, Gabon, Zambia # Or you can query habitat information lets.iucn.ha(name) #>Species Forest Savanna Shrubland Grassland Wetlands Rocky areas Caves and Subterranean Habitats #>Telophorus viridis 1 1 1 0 0 0 0 #> Desert Marine Neritic Marine Oceanic Marine Deep Ocean Floor Marine Intertidal Marine Coastal/Supratidal #> 0 0 0 0 0 0 #> Artificial/Terrestrial Artificial/Aquatic Introduced Vegetation Other Unknown #> 1 0 0 0 0
letsR also has other methods to work with the spatial data that IUCN provides ( http://www.iucnredlist.org/technical-documents/spatial-data ), so definitely take a look. It works by querying the IUCN redlist api for the species id (http://api.iucnredlist.org/go/Telophorus-viridis). Sadly the habitat function does only return the information if a species is known to occur in a given habitat, but not if it is of major importance for a particular species (so if for instance a Species is known to be a “forest-specialist” ). Telophorus viridis for instance also occurs in savannah and occasionally artificial habitats like gardens ( http://www.iucnredlist.org/details/classify/22707695/0 ).
So I just programmed my own function to assess if forest habitat is of major importance to a given species. It takes a IUCN species id as input and returns ether “Forest-specialist”, if forest habitat is of major importance to a species, “Forest-associated” if a species is just known to occur in forest or “Other Habitats” if a species does not occur in forests at all. The function works be cleverly querying the IUCN redlist and breaking up the HTML structure at given intervals that indicate a new habitat type.
Find the function on gist.github (Strangely WordPress doesn’t include them as they promised)
How does it work? You first enter the species IUCN redlist id. It is in the url after you have queried a given species name. Alternatively you could also download the whole IUCN classification table and match your species name against it 😉 Find it here. Then simply execute the function with the code.
name = 'Telophorus viridis' data <- read.csv('all.csv') # This returns the species id data$Red.List.Species.ID[which(data$Scientific.Name==name)] #> 22707695 # Then simply run my function isForestSpecialist(22707695) #> 'Forest-specialist'
And here are some news from my current field work that is part of my Thesis. After spending some quiet, but exiting days in Nairobi (maybe later more about that) I finally arrived in Wundanyi, Taita Hills, where a substantial part of my work will be conducted along the CHIESA transect. Suited in the coastel area in proximity to Mombasa the Taita Hills are renown for their extraordinary bird diversity and endemic species and as such are considered to be part of the Eastern Arc Mountains Diversity hotspot. The Taita hills encompass a variety of different land-use forms, but the majority of them surely are tropical homegardens as most of the “Taita” people are subsistence farmers growing crops in the highly fertile soil of the mountain slopes. Besides homegardens there are riverine forests in the valleys, shrubland vegetation in the lower altitudes, exotic tree plantations and of course the remaining indigenous forests remaining on the Taita hills mountain tops. Every last forest part is known well and was traditionally protected by the locals as part of their culture. However in the later centuries the remaining forest area became more and more scarcer and even during my visits in some of the forest fragments with the highest biodiversity value (Chawia, Ngangao) I saw frequent signs of fuelwood and timber extraction. Clearly a lack of funding for biodiversity protection seems to be the problem, but also an economic perspective and opportunities such as ecotourism might enhance locals perception if and how these last forest parts should be protected.
My work in the Taita hills is all about birds. Specifically I am conducting avian diversity and abundance assessments along an altitudinal transect encompassing a variety of different land-use systems. Although avian assessments have been conducted in Taita many times before, they were often restricted to the forest fragments and for instance didn’t look at the bird diversity in homegardens in different altitudes. The resulting data will just be used for my thesis as validation dataset, but I am hoping that it has maybe some value on its own as well. Initial results show that especially the homegarden in Taita support quite a high diversity of birds, which is even similar to levels in the remaining forest fragments (although the community is somewhat different and biotic homogenization is likely on-going).
It can be quite challenging to conduct avian research in tropical human-dominated landscapes. Not only do you have to arrange for transport to the specific transect areas and lodging (in my case provided by the University of Helsinki Research station in Wundanyi), but also account for the frequent interruption by children and farmers asking what you are doing. Furthermore it is not an easy task to count birds in for instance a maize or sugarcane plantation due to the limited accessibility and my intention not to damage the farmers crops. Most of the farmers however happily provide access to their land and are very interested in what kind of research this “Mzungu” is doing on their farm. From my own experience here I can tell that the Taita people are very kind and it is a pleasure to work with them on their land. They are very respectful and even walking around late at night or very early in the morning seems to be no problem here (in contrast to for instance Nairobi or Mombasa).
In the end my sampling goes on quite well and much better than I expected. Although it is technically raining season and long heavy rains can be expected every day, the mornings were exceptionally dry and weather was mostly favourable for ornithological research. Generally this time of the year in East Africa is especially interesting for bird assessments as many local bird species are in their breeding plumage and nesting, but also because European migrants are often still around or on their way back to Europe (for instance I saw and heard an European Willow Warbler some days ago). Lets see what else the next weeks will have for be in terms of avian diversity.
Scott Chamberlain posted new interesting examples what you can do with the “rgbif” package in the ropensci suite. See over to his page at github for some excellent demonstrations what is possible with just a few lines of r-code and the vastlast amounts of GBIF data.
GBIF certainly becomes one of the best and easiest to use data sources in many fields of ecology. Although the data coverage for many countries is still underreported, other countries made quite the process for free and easy access to biodiversity information (For instance the majority of the volunteer raised vegetation data provided by the German FloraWeb server is already available in GBIF).