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SEOSAW fills a large gap in understanding the vegetation dynamics of tropical regions by creating a network of vegetation plots and encouraging collaboration between researchers working across southern African woodlands. These woodlands cover around 3 million km2, making them the largest savanna in the world and support the livelihoods of more than 160 million people. By monitoring woodland plots over a number of years, questions can be answered regarding woodland responses to climate change, land-atmosphere CO2 interactions, biodiversity impacts of human usage of woodlands etc.
The Earth's vegetation is changing in response to climate change, increased concentrations of CO2 in the atmosphere, and harvesting for fuel, food and building materials. These changes can accelerate or reduce climate change by altering the carbon cycle, and also affect the livelihoods of those who use natural resources in their day-to-day lives. One of the most important ways to understand vegetation change and its impacts, is to make careful measurements of the same patches of vegetation ("plots") repeatedly. Networks of these plots have produced surprising findings, challenging theory and models of vegetation responses to climate change. E.g. in Latin America, a network of these plots has shown that tropical forests are not soaking up as much carbon as predicted. Networks of these on-the-ground plot measurements are the only way to get a detailed view of how vegetation is currently changing. However at the moment, different researchers do not combine their data to understand regional patterns of change. This project will address this by bringing together researchers collecting plot data in southern African woodlands to share data and answer the big questions about what is happening to the vegetation in the region. The southern African woodlands are the largest savanna in the world (3 million km2), and support the livelihoods of 160M people. Many of these people are poor and depend upon the woodlands for 25% of their income and to support their agriculture. Theory and models suggest that these woodlands will be sensitive to increased atmospheric CO2 and other environmental changes underway: this is because, unlike forests, woodlands maintain a balance in the competition between trees and grasses, allowing both types of plant to co-exist. Small changes that benefit trees (such as more CO2 in the atmosphere) might rapidly change woodlands into a tree-dominated system. This would mean that they store more carbon, but might reduce the diversity of plants on the ground. It is also possible that human use of these woodlands, particularly wood harvesting for fuel, is altering their diversity and reducing the "services" that they provide. Currently we have no way to know if these changes are happening - satellite data and models can help, but need to be validated with plot measurements.
Understanding the response of southern African woodlands to global change is the long-term goal of SEOSAW. It will do this by creating a regularly re-measured, systematic plot network. The stepping stones to this network are to: 1) develop an online data-sharing platform to exchange existing plot data so that we can look for signs of widespread change 2) combine NERC-funded data from 486 plots with data from 1,783 plots measured by others, to create a network that covers the whole region 3) use this new data set to better understand the processes that allow trees and grasses to co-exist, to allow modellers to make better predictions of future change 4) encourage researchers to make measurements in similar ways in the future, so that we can more easily detect changes 5) create a plan for future plot measurements that covers the whole region, and makes best use of the available time and money.
SEOSAW will fill a large gap in the network of plots in tropical regions and benefit: - modellers of the Earth's vegetation will be able to test their models against reality in one of the most difficult to model biomes - scientists using satellite data to map vegetation will now be able to calibrate and validate their maps in all types of tropical vegetation - Those modelling the carbon cycle, who need to know how much carbon is being taken up by the woodlands Conservationists will also benefit, as SEOSAW will identify parts of the region that have unique or particularly diverse woodlands, helping to prioritise conservation efforts.
GLP Methods: Consumer Preferences, Decision Making, GIS, Modelling, Past land use/historical land use reconstruction, Qualitative social science methods (interviews, observations, document review, surveys), Remote Sensing, Spatial Analysis, Supply and value chains, Synthesis/meta-analysis/meta-study