Part 1: Food or Carbon? What to Choose?

It has been far too long since my last full post! I can only apologise and offer meager excuses of tackling difficult data coursework and busy times at work! Should be seeing some more regular posts so please check back soon =) But let us not digress any further! 

SO with a rainy Saturday ahead, let's look at how we can tackle the whole 'how can countries increase their agricultural land without dramatically reducing carbon storage?' Obviously an ideal situation would be to stop agricultural expansion, however, this is unfeasible when intensification methods can only take us so far (and also impact upon our environment - to be explored in later posts!) and there is a demand for food and income. With environmental problems everywhere we turn; we have to find a solution that works in order to avoid land clearances like those happening in Indonesia.

This is where modelling can help us! One example that I wanted to share was the work done by Chaplin-Kramer et al., (2015): these guys modelled the impact on carbon storage of different agricultural expansion scenarios: 

1.  Edge: expansion from forest edge towards the core

2.  Core: expansion from the center of forest patches out towards the edges

3.  Fragmentation: expansion converts the forest pixel furthest from the forest edge in each time step

4. Current cropland: agriculture expands outwards into whatever is surrounding it. 

As we can see the scenarios are quite simplistic; in reality cropland expansion is not clearly subdivided into these categories and the authors make clear that their fragmentation scenario is extreme (fragmentation usually follows road expansion). But, as with all things you have to start somewhere, so with modelling we have to simplify the scenarios to a certain extent in order to quantify their individual impact. The scenarios the authors have chosen allow them to test the sensitivity to different spatial methods of expansion of a theoretical homogeneous, continuous patch of forest to see how their model is working and then assess the scenarios on study forests in Mato Grosso and Mato Grosso do Sul.

What did they deduce?  

If you have a single patch of continuous forest and we convert 30% of it, we can see that carbon stocks are highest for edge expansion, then core expansion, then dramatically lower for fragmentation; from these findings we can see that carbon stocks are more sensitive to fragmentation. 

Does this fit in with our wider knowledge? The answer to this is yes; it makes sense to see less carbon lost when deforesting from the edge of a forest due to there being less carbon there initially. We find less carbon there because of the environmental conditions at the edge of a forest; temperature, light, wind, and moisture are all different compared to the forest interior resulting in different species composition and smaller trees at the edges. Much research has been done concerning 'edge effects' and studies have found that when edges are created many trees die as the new conditions are beyond their physiological tolerances. 

BUT when interpreting Chaplin-Kramer et al. (2015) fragmentation results we must remember that the fragmentation scenario employed is not a realistic simulation, and instead is modelled to simulate the greatest amount of damage that can be done.

Now let’s see what happens to carbon stocks of Mato Grosso and Mato Grosso do Sul when these scenarios are modelled..... 

For Mato Grosso interestingly we can see that fragmentation and core expansion are pretty similar, though edge expansion is still better. BUT even better than that is expansion out from regions that are already used for agriculture into surrounding land: 

For Mato Grosso do Sul expansion from current cropland is again the better method, and intriguingly core expansions appears to be slightly worse than the fragmentation scenario:

Hmmmm intriguing results… the reason why we might be seeing core expansion having a greater impact than fragmentation in Mato Grosso do Sul, as well as core and fragmentation being almost the same for Mato Grosso is due to the already fragmented nature of the forests. This is corroborated by looking at the results when applied to the ‘continuous forest’: the fragmentation scenario has the greatest impact initially before levelling off. So the already fragmented nature of the forests perhaps negates the effect of the fragmentation simulation.... 

What are the limitations of this study? Two I have already mentioned and they are the categories of agricultural expansions and how fragmentation is simulated. Another is that the effects of land clearance on the remaining forest is not taken into account; edge effects penetrate into the forest. Additionally soil carbon is not considered; soil carbon is a major carbon store and disturbances caused by land clearance will impact upon this. 

Even with these limitations considered, what I think we can draw from this study is that by gradually spreading outwards from existing agricultural lands and minimizing the number of edges we create we can reduce carbon losses. Yes the more we expand the more carbon we lose, but if we combine gradual expansion outward from existing agricultural land combined with sensible agricultural intensification methods then we could protect our forests of carbon.

But the next hurdle - though we can identify the best expansion methods, how do we actually put this into practice and persuade farmers to follow certain expansion policies?  More on this in the next post!