What I'm going to do now is try and give an overview of some of the model based processes that go into these
calculations of emissions hopefully it will give a bit of a background to those of you who don't do this kind of
bioter physical, biochemical, even by modeling @unoise@ % um for those of you who do % um. It might be a bit going
over old ground, but we will see @unoise@ so. Just to put this plot here up again that you have seen before. I'm not
going to go through it because Joe went quite nicely through most of the sinks and sources that really matter here. The
one thing, one of the things I will highlight is that the Gp, the total uptake of carbon by the terrestrial biosphere
is, we reckon it is about one hundred and twenty pedagograms of carbon per year. And when you compare this to the amount
of carbon in the atmosphere. That implies that every seven years, the carbon in the atmosphere is being pulled through
the biosphere. And it doesn't mean it is being removed by the biosphere. Much of it goes straight back out into the
atmosphere for respiration, but it it gives you an kind of idea of just how much of an effect and how closely linked
these different parts of the carbon cycle are this. Is again, the equation that basically that Joe showed you
earlier. So we, we do these carbon budget calculations, and we can say that the change of the Co2 in the atmosphere is
simply a function of the emissions from fossil fuels and land use change. We put in with the ocean, the land sink taken
away from that. And course, what we are interested in here is the land sink and the land used change emissions
however. I, Mean these are really quite artificially separated. When we think about this, when we actually think about
the processes involved. They are really closely linked, and it is very difficult to separate the land juice change
emission from this residual sink And as June Mentioned there is parts of this that we know really quite well. And
the bit that we are interested in. We really don't have a good handle on at the moment. So just start by doing
fooder the basic elements to address your account cycle. A couple of definitions, which are easy to get confused. So
obviously we have the uptake of Co2 by the plants. This is photosynthesis and then some of this Co2 is quite
rapidly returned to the atmosphere for the plant respiration then these plants so when we turn it we turned
out to first emphasize prime before activity. So one of the definitions and the net of the plant respiration and
the photosynthesis, we turn the net primary productivity which are two terms you will hear a lot and talking about
the biosphere. Then, of course, these plants, they die, or they turn over their leaves and they create litter. And this
litter was broken down, and it responded. And this is soil respiration flux and so when we look at the difference
between these fluxes that gives us our net ecosystem exchange, or the net exchange of carbon between this small part of
the ecosystem and the atmosphere. And this is typically what we measure with a flux tower, for instance, but. Of
course there is other processes that happen on a much longer timescale. So fires return Co2 to the atmosphere and fires
don't generally happen every year in most ecosystems so. In order to take the full carbon accounting of an
ecosystem. We have to take into account these things that happen a bit less regularly, or interventions by humans in the
system, for instance, who harvest and we turn the sum of all of these different fluxes in and out of the the
terrestrial carbon system, the net productivity this. Is a net amount of carbon taken up by the whole biosphere
and you will see both of these terms in the literature, and sometimes you see them confused, that it actually
makes quite a difference in the Netflix that you are looking at, whether or not you include fire. The Fireflx is a maybe
a couple of pedagograms a year. And when the Netflix is two paragraphs a year. You see, it is important to be clear on
the definition so. How do we go about understanding this? well, we have several different sources of measurements
that we can use to try and understand the carbon cycle. We have flux towers, where you can make direct measurements of
the fluxes in and out of the ecosystem, particularly we can make direct measurements of Gp and N E. We can also make
measurements of the total respiration. But here we start having to make some assumptions flux towers have a
limitation that they are only limited to a spatial coverage. It is essentially the footprint of the tower, maybe a few
hundred meters in each direction, depending on how hydrogen is. But they have a very high frequency, which can tell us
quite a lot about aspects of system and how it works. By a complete difference go. We have satellite measurements
so we have, for instance, in normalized Differential Vegetation Index. It is a sensing index of greenness we
also have now light our measurements of canopy height, which we can use to drive biomass, and we can also to some extent
drive Gp. But this is generally derived as a secondary product from other measurements. So, but the trouble with
satellites is we are generally measuring something that is a change in radiation so we can get a a column, a
column, measurement of how much of a gas we have in the atmosphere, we can get a change in the surface energy balance in
various different wavelengths. But in order to turn those into the the flexes that we are really interested in and bias
here we often have to make a level of assumptions or use models or calibrate them against service measurements. And so
they are a less direct way of extending the knowledge that we already have of the surface, maybe. And of course, these
have a much lower frequency than flux towers. And then we have another class of measurements, which is inventor. So we
go out and take," Well, I don't go out, but some people go out and take measurements of the biomassin forests. They are
how fast the trees grow. The different the different allocations of carbon to different parts where it is
the roots to trees and the trunks, etc. And he is having generally an even lower frequency, because it takes echo a long
time to go out of forest and Sampl order trees in it but basically this isn't an exhaustive view of all the
measurements we have, but it is kind of to point out that we don't have any nice global scale. Overview of the key
flexes that we are really interested in in trying to understand the global carbon cycle from the terrestrial point of
view and so what we have to do is is fill in the gaps with process based models, or we have to fill in the gaps of
models. And we tend to use process based ones so. The models that we use today have evolved from a variety of
different backgrounds. It is just on the left side. Here I go through some of them. So we have the the Gcm land surface
models which have been put together to to give the boundary between the atmosphere and the land surface for global
circulations, simulations and this is really focusing on the surface energy balance and the surface roughness
then we have the terrestrial bio chemistry models really looking at the the exchanges of the trace gases,
particularly Co2, with the surface in the atmosphere. Another class going back in time is plant geography models. So
what kind of plants grow? where are there limits that say particular plants grow in these regions, for instance,
and then we have vegetation dynamics. So how does different types of vegetation direct with each other. What are
the the mortality processes and how do they affect the kinds of vegetation we have? how do it established and so
over the last twenty or thirty years, these different fields that were one separate, and now started to merge quite a
lot, as we have got a appreciation of how the Earth system, everything is connected and interacts with each other
and so I've tried to group together that the models that we generally use today into three different types we have
the the land surface model again. But this time as part of an Earth system model so this is incorporating both
energy balance and and and the basic version of that uses a static vegetation. And this is commonly what is used
in five models that we are using. The last assessment report coming from the other direction we have the the
dynamic global vegetation models. And these are focusing on being able to simulate the type of vegetation that we would
have in a particular place under a particular set of environmental conditions and then the exchanges of the
various gases that go along with that. And the increasing trend is to start incorporating into land surface
models. So we have this combined class, which includes both of them @unoise@ @unoise@ one of the the real problems with
modeling the terrestrial bias is the range of scales we have to cover. So we have a huge range of spatial scales. We
have to go from the molecule in terms of photos and photosynthesis to scaling this up to a leaf, and then the leaf is
obviously just one part of a tree, and the tree is part of an ecosystem. It may have a whole range of different trees
and grasses and completely different to just multiplying one tree after another and then within a the grid cell
that we typically model out, which is anything from half a degree to two degrees across, then we might not just have a
forest. We have all different types of land cover. So we have an increase in heterogeneity. And of course, this happens
again at the globe. So as the scale increases, the level of heterogeneity that we have to incorporate increases. And it
is not just a simple case of saying, okay, at the globe, we have twelve billion leaves. So if we model twelve billion
leaves, we will get the right answer for Gdp. That is, there is so many nonlinearities in there. Don't it just doesn't
work that way and we have to use differences in scales. We also get differences in time scale. So we have
processes that we really need to model at very high time frequency. So the biology of physics in terms of minutes, or
maybe half an hour, depending on the model we are using and its interactions with the atmosphere needs to be a very high
frequency, similar emissions of some compounds, such as volatile organics, need to be a relatively high frequency, at
least an hour or so, then we have things like phonology, so that the turnover of leaves here we are talking days to
weeks is probably sufficient to capture a seasonal cycle in in leaves, and then as other processes that we can really
just treat annually. So vegetation dynamics and soil. By geo chemistry, you can often get away with making
simplications. So we only have to run those parts of these models down nearly @unoise@ and in D G, M's we actually
tend to do these processes, daily revolutions of daily, just to make them a bit lighter and easier to run @unoise@ so.
Really the, point of this talk is to to go through some of the massive number of assumptions and uncertainties that we
have in putting these processes together. And really, there is enough here to fill an entire summer scorn. And there are
whole training stores just dedicated to this subject. So I'm really going to skip over lots of things and miss many
things out. But if you have questions, and I'll try and answer so I'm going to go through these aspects of the
system.
I won't read them out to you. You can read them, and we will get to them in a few @unoise@ @unoise@ so first. Off we
have to run our models with something, and generally we run these models with boundary conditions that are mostly
atmospheric. So all models were looking at the Chester bias. So we have to provide them a short wave radiation. We also
need to provide precipitation measurements. And the atmospheric Co2 mixing ratio is also very important and then
depending on the model type, we even need the incoming long wave radiation so that we can make a calculation of surface
energy balance, or we need the surface temperature directly, which we can take from a different model. And then,
depending on the different model types. Some also need humidity. Wind speed deposition of different components
aside. From this there, is also non parameters relating to the soils in particular but if you have
static vegetation, you might need a vegetation type map if you are studying to consider land cover, then you need
land cover fractions or different management variables, how much nitrogen you are using to fertilize Copplants, for
instance, might become relevant @unoise@ and generally we ever get these some historical reconstructions where they are
available. We have historical analysis for climate that we can use, or we take them from global climate models. If we
running offline, or we give assumed mission trajectories based on the scenarios that that mark was describing yesterday
and put these into other system models @unoise@ so. Going through the processes I'll start with photosynthesis I
think you all know that photosynthesis is a combination of Co2 and water to make some sugars and give gives out oxygen.
In most of these models, we use a very standard way now of of calculating photosynthesis, which is known as the
model, which comes from the early 1980s. It is a very neat process base approach of trying to capture the main
aspects of photosynthesis from our point of view, and nearly order the major models that we are looking at nowadays even
use this model, or derivative thereof. And essentially, this model comes down to a minimum of two different rates, which
limit the rate of carbon assimilation. One is the regenerate regeneration of by phosphate which you can
essentially consider as the rate of energy supply from light into the system. And another is the capacity, which
is the rate at which the enzyme can take Co2 and stick it into a larger organic molecule @unoise@ and. So we
simply take the minimum of this as our these two rates within this equation as our assimilation rate. So this
assimilation obviously depends on the amount of light we have. You can see in this light response curve down here. That
is the the vote on flux density increases, and our assimilation rate also increases until a point where it out so
at low light levels, you get a strong increase. And as light increases relatively high levels, you don't get any more
effect that the leaf simply can't deal with anymore. Intake of it can't handle any more. Light can make use of it
as well as the light level. Temperature is also important so. This this particular curve is this is for one
species. So don't take too much note of where the temperature maximum is. But we have an increase of the assimilation
rate at low temperatures, reaching some maximum, which is species and environment dependent, and then a tailing off due
to mainly the the activity of the enzymes involved. So as as Rubisco gets warmer, it gets less effective at fixing Co2.
It starts to get it confused with oxygen and trying to stick oxygen into the into their carbon molecule that is
energetically not very good, and it costs a plant carbon to to deal with that. So we get to drop off in the Inn.
Assimilation rate @unoise@ now obviously, because, the plant is fixing Co2 to the amount of the substrate it has to work
with is is also important so. For a vast majority of plants globally. So all trees and temperate grasses, we see a
very strong response of the simulation rate to the amount of Co2 that we have in the atmosphere. And this is the Co2
fertilization effect. So as you increase the Co2 concentration, you get a very strong increase in assimilation. The
exception to this is plants that go under C four photosynthesis, which is tropical grasses, basically. And they Plato
out in terms of their seat to Co2 concentration at a very low level, which is far below what we have in the atmosphere
today @unoise@ @unoise@ but that is not the whole story. Of course, we know that plants are also limited by nutrients
and nitrogen is one nutrients, gives a particular fundamental control on photosynthesis. So this plot here shows
the the change in the net photosynthesis. As you change the leaf nitrogen content. And you can see that there is
differences between broadly for needle leaf, which I won't go into now would, as you increase the amount of nitrogen.
The plant has more capacity to to photosynthesize, because it can make the proteins that it requires. Rubisco needs a
lot of nitrogen in order to be made @unoise@ so. The amount of Co2 matters and the amount of year two in the atmosphere
matters. But what really matters is the amount of Co2 to get into the leaf so it is the Co2 inside the leaf that
actually controls the rate of photosynthesis. And the plants take in the Co2 food a small paws on the
underside of the leaves. And this is essentially a trade off, because as you open these pores to take in Co2, you also
give out moisture, and plants have to reach some kind of optimum or happy medium state where they are not losing too
much water, but they are getting in enough Co2 @unoise@ and this could be quite a difficult process to model. If
we think about order, the biochemical things that are biophysical processes that are going on inside the leaf. But what
we tend to do here when we are modeling. It is what we do with many environmental problems. We simplify them by saying
that the plant does what is optimal, and therefore we can bring it down to a very simple equation. Plants don't always
do what is optimal, or they probably do do what is optimal, but they are taking into account many other things which
make these these assumptions a little bit uncertain in many cases. But the way we typically model this exchange of of
Co2 and and moisture is to say that the plants optimize the Sl model conductions so that they get the maximum Co2 intake
versus an acceptable amount of water loss so. In the model we stayed at smarter conductions. It is a
function of a minimum to which we add a function according to the net assimilation rate, the amount of Co2 in the
atmosphere, and then a function which is controlled by how stressed the plant is in terms of the amount of water that it
has. And so you can also see here, because the the atmosphere of two concentration is included that you have not only a
direct fertilization of photosynthesis for you to Co2 acting on the photosynthetic process. But you also have a
change in the water, use efficiency through the automobile conductants. And both these processes are important at the
global scale. So what does this look like? if we look at Gp globally. This is some output from Lp. J guess it is
just indicative. We have a lot of strong uptake of of Co2 in the tropic tropical rainforests. We also have a strong
uptake across the the northern mid latitudes, but less sue. Because here we have to take into account seasonal effects
in the tropics. There we have high temperature. We have a lot of water availability that plants can be productive all
year round. Just to ground the model here with some measurements, we can compare it to chlorophyll fluorescence
measurements. This is is quite a new set of measurements just become available when chlorophyll takes up light,
shortwave radiation. It also a bit in a slightly different wavelength. And now we are able to separate this wave
length of light, which is fluoresced and it gives an indicator for Gp. And you can see that this indicator here
has a very similar spatial layout to the model, with the exception of this little bidden in North East America
which I'll come back to you later so that is production what about respiration respiration? we usually do
much more simply than we do production we basically divide plant respiration into growth and maintenance
respiration, because they have different intrinsic rates growth. Respiration is generally at a higher rate than
maintenance. Respiration and we modeledly simply in, at least in an L, P, J guest. But this is kind of generally,
once again, representative. It is a function of the the species, the amount of carbon in the leaf, or the amount of
carbon in tissue more to the point and the carbon to nitrogen ratio into particular tissue. So we have different rates
of respiration in leaves versus in wood versus in roots, depending on the amount of nitrogen, magnificent carbon we have
there. And then we modified us by a function that is dependent on temperature this is the temperature function in
the Lp J models, at least the ones that I've been working with. And you see it at the temperature. The function
increases very strongly with temperature. In reality, there is some kind of maximum, but many models don't take this
into account. So as as the temperature increases with climate change. For instance, we get a strong increase in
respiration in these models growth we, do actually much more simply. In our case, we just say it is a a fraction
of the leftover carbon goes into growth, respiration and completely gloss over order processes to go into that @unoise@
@unoise@ so this. Is how we generally do it. And it is a huge simplification of the underlying processes. And if you are
interested, particularly in how modeled you can look at this paper here Which, goes through some of the
different decisions you can make in in modeling respiration, which we typically don't do at the global scale. At the
moment, we are trying to get better at that. There is also things such as . So there is quite a lot of evidence. If
you take a particular plant from one climate, and you stick it in another climate. It doesn't just move up this curve,
but it actually to that new environment and kind of resett its base rate of respiration. We don't generally take
account of that. And simply, we don't account for how models respond and how plants respond. And our models in terms of
stress. So there is a lot of evidence that we get respiration going in completely the wrong direction in drought
conditions. For instance, @unoise@ soy respiration very similar we take simple lifetime functions, so we generally split
the poet soil into pools of different carbon, depending on how quickly that carbon breaks down. And we characterize each
pool by a lifetime. And then we modified our lifetime according to the temperature and the moisture so. Here we
have exactly the same temperature function that we are using the plant, a natural fact and then as the amount of
moisture increases, we say that the respiration rate increases, which is generally true up until a point when the soil
becomes water locked actually, we don't account for that here and again, this is. This is a huge simplification.
And when you consider it a lot of the response of our our bike models in terms of carbon going to the future is an
increase in respiration in soils. This is something that we really need to look at more closely, and is now being looked
at more closely in the in the modeling community. And there is a whole range of different factors that go into this. And
some models now coming out that actually look at how we can model the processes of the actual bacteria and the soil are
doing when they break these. These carbon molecules down @unoise@ so. This is just a genetic nephew system flux balance.
It looks very similar in terms of the spatial breakdown to the Gdp. So we have generally a high uptake in the tropics,
and also some uptake in the north and mid latitudes, but smaller. But this is basically to break the spatial breakdown
of that net terrestrial sink that Joe pointed out earlier the other interesting aspect I think here is is the
seasonal aspect you see there is. There is much more land in the northern hemisphere, in the southern hemisphere. And so
the the vegetation cycles in the northern hemisphere tend to dominate the seasonal cycle of Co2. And you can see this
both at measurements and flux sites here, from a a paper user to evaluate L, P, J. We have a um net out out flux
of carbon in winter months, and an uptake in the summer and you can actually see this in the seasonal variation of
Co2. You can see the seasonal cycling of vegetation. The main thing that controls the seasonal variation is the
biosphere, as opposed to emissions which controlled a @unoise@ the overall trend @unoise@ so that is a really
brief run food at the main flexes that we try and simulate. How do we put these all together? We do this using
concept of pools, as I mentioned, for soil. So there is a pool of carbon in the atmosphere. We take this up with
photosynthesis, and it goes into a pool of carbon into vegetation, and the vegetation is dies, or it turns over, and it
goes into a a set of soil carbon pools, which vary in their lifetime, as I mentioned, and a vegetation pool.
We have different ways of representing this and linking it with the actual vegetation we see outside. So it it might be
that we represent our vegetation through a single, average individual, which has characteristic features, or a whole
range of different individuals. And this depends on the module, on the model we are using um @unoise@ but.
All of the nearly all of the models that we use at the global scale have some cut set of alometric rules that decide if
that carbon is coming into vegetation, to which part of the vegetation does it go? does it go to the to the roots? does
it go to the wood? does it go to the leaves. And this has often huge implications for the carbon, because it, it changes
the lifetime, the typical lifetime of that carbon within the system, the lifetime of carbon and leaves is much short on
the lifetime of carbon in wood and then the typical way to Scode is up to the grid cell is to have fractional
coverages, a tiling of different plant functional types. So you might say that one third of the grid cell is this plant
functional type one and another. Twenty percent is this type, and another twenty five percent is this type so. In
that way we can represent different plants in the grid cell. But I mean, you can't look outside the window, because we
have closed the blinds. But if you could look outside the window and looked at the forest, then you would see that the
forest doesn't separate species into little blocks. You know, everything is mixed in with each other. And this has quite
fundamental implications for how the ecosystem functions. So if you, if you consider a forest, a real forest. You have
different species, and you have different ages of species, and some plants are taller than others, and overshadow
others, and therefore have a competitive advantage for light others have larger root networks, and that gives them
a competitive advantage in terms of gaining nutrients. When you drink some short supply. So some models, the Lp J guests
being one of them. And I'm unassumably going to show you lots of things from Lp. J guess because it is the model I work
with use an approach where you also break down. There is plant functional types into different age groups, and you
mix them together in the grid cell so. Do you try an account for some of this different, this heterogeneity that
have natural systems. And if anybody is more interested in how we do that, then I can go into a bit more detail later on
offline. @unoise@ plants also die of course it is not just a case of taking in carbon and respiring it, but
eventually they die in that carbon's return to the soil. And eventually, in most case, it is the atmosphere and
there is a variety of different ways that we represent these deaf mechanisms in models so we might use Biomatic
limits. We say that this particular plant type can only survive between a temperature of ten and thirty degrees. And if
not, then it dies. If the temperature strays outside that for a long period of time, or if the plant can't maintain a
positive net primary production for a set period of time, and it dies. Similarly, growth efficiency this is a
minimum amount of biomass increase per unit leaf area and then as the simpler things, such as a maximum age that a
plant can live to a set background rate, after which plants die long way. So the thing about these is that all
these mechanisms, they are kind of logical, and it makes sense. But they are not really very well tested. And in
particular, they don't really explicitly represent the mechanisms that that lead to how plants die. So plants die
because they don't have the necessary stores. And an intake of carbon in order to be able to fulfill their basic
functions, or they die because they have a hydraulic failure. They don't have enough water within their tissues in order
to be able to maintain their basic functions, either they fall over or they their. They can't % um run their metabolism
properly. So there is quite a disconnect in the way that we represent processes at the global scale and how they
actually happen in reality and as well as these kind of processes that come from within the plant. There is a lot
of processes that come from without that can cause plants to die in ecosystem disturbances. So fire wind fro
insect attack such as we see in a lot of the the Boi or forests? why not a boiled at the forest around here
you see a lot of deaths due to bark beetle attack and this is really quite a big issue at the moment. And this is
this comes from a. This plot comes from a paper which was published last year in Nature, Climate change. It is the
increase in the amount of wood in terms of forest biomass that is been affected by disturbance in Europe over the last
forty. Forty years and you can see it as a huge increase in the amount of disturbed biomass and in an increase in
all types. So in wind disturbance, in in beetle disturbance and in forest fires. So there is now some evidence that
these disturbance rates are not just important for turnover, but they are also increasing with climate change. And this
is a major uncertainty that we don't really have a proper handle on in the system yet just to give an idea of the
possible magnitude of that. This is some simulations we did with Lp. J guess it is a change in vegetation, carbon
storage, as you change the rate of disturbance in the system, basically. So moving to the left on this axis is more
disturbance and this this line here shows a tropical forest, the mid latitudes and the boreal regions. And you see
that if you between doubled the rate of disturbance everywhere, like we see in Europe, then you would have a drop in the
vegetation, carbon storage of a couple of hundred petagrams so this is something that is comparable to all the
emissions we have put into the atmosphere of over the last one hundred and fifty years. This is a really large amount of
carbon that is sensitive to changes and disturbances. @unoise@ % um touched a little bit earlier on on plant functional
types there is a huge range of species out there in reality and we don't have the computational capacity, or
indeed the data to our models in order to be able to represent all these species. If we are looking at just
regional scales, for instance, Europe, we can get most of the major species, but but globally, we can't even come close
thousands of species out there, just in terms of trees so. We we break these down into groups that we call
plant functional types. And we differentiate these by different traits so by the type of photosynthesis by whether
it is ever green or deciduous. Whether it is woody or herbaceous plant, or the limits are typical, but there
is all sorts of different ways we can do it. And so we, we break these down into different classes. And typically in
global models, we have maybe five to fifteen different classes of plant functional types, which had tried to capture
order variation in global vegetation. And you can immediately see that there is a huge simplification there, and we can
actually, we can broadly get the the general distribution of these plant types, but it raises questions of resilience.
And there is a lot of evidence that if you have many different strategies and an ecosystem, many different species
following different roots, and that ecosystem is more resilient than if you have one type as we do in these models
so this is just showing a potential natural vegetation map from Lp J guests. So it a vegetation. It would be there if
there was no human influence at all. According to our model processes. And this is an attempt at reconstructing what the
potential natural vegetation should be based on observations. Obviously, there is no observation of real potential,
natural vegetation. You should be saw earlier in the earlier talks, just how much of the land service is strongly
affected by by human management and land use change. But you can see that the broad features agree. So the tropical
forests are quite similar in in their extent. And also the regions. We even get the the Siberian large forest out
here, more or less these models are a reasonable job of getting the biosphere, at least as it is now going into
the future. That is a completely different question @unoise@ @unoise@ but of course we, know that the biosphere isn't
potential natural vegetation. That is why we are here. There is a huge amount of management that goes on. But until
recently, until their fifth assessment report in Earth system models and generally trust your biosphere modeling. We
only concentrated on potential natural vegetation. And we didn't take into account the huge modifications that humans
have made to this system. But you know, these managed systems differ fundamentally in many of these aspects. So in a in
a , we might represent establishment and mortality. Processors will represent maybe some fire and competition with
you. Different plant types but you think of a cropand what you have is you have a prescribed species, and that
species may be fertilized to irrigate it, to increase its productivity. You don't have to worry about
establishment, because it is so on a specific date, and mortality is less relevant, although not obviously completely
irrelevant, because you harvest at the end of the year. So the process is involved really completely different. And so
this would suggest that the exchange of trace gases would also be completely different and of course that is what
we see. So this plot here is, once again, these chlorophyll measurements of Gdp. And you saw earlier this large increase
at this high amount of Gdp in the northeastern Usa Which, the the Lpg guess didn't capture in its potential
natural vegetation. And the reason is that this particular bit of land is dominated by cropland. And this particular
cropland very heavily intensively managed, so that you have very high productivity there. And what this paper, which
came out last year, showed is that this very high productivity in many of the global cropins, particularly in North
America and in India isn't captured in the trespasser of biosphere models that we that we are using to model Gp. This is
an example of a difference plot here between the data and and a couple of different types of models @unoise@ and
also this is a very active bit of research actually does. A couple of papers that came out in nature just at the end of
last year that showed the effect that this that the Copland productivity has on the inter annual cycle of Co2, not the
interior of the seasonal cycle of Co2. And they showed that there is been an increase in the amplitude of the seasonal
cycle over the last decades, and at a very large proportion of this increase can actually be attributed to the increased
productivity in in the northern hemisphere so these managed agricultural lands are really modifying the
exchange of gases. Do you have a question @unoise@ @unoise@ no what they measured here was an early agricultural
intensification, and they, they um @unoise@ they. Calibrated their model to the increase in yields that had been seen
@unoise@ and then ran that for the chemical consequences @unoise@ it. Is not just productivity to changes though.
It also, we see large changes in the soil, carbon stocks so. This plot here this is some output from Lp J guest
once again what I've done here has run natural vegetation and then completely changed it over into different
land use types. So and then looked at the change in soil carbon. After ten years after fifty years, and after a hundred
years. And if we change natural vegetation into grassland, then as a global mean value. This is just a typical
indication for the global average response, you actually get an increase in slow carbon. And this is due to some
changes, mainly in in how the allocation and turnover happens within the system. But once you start grazing that
grassland, then you will probably come out with some kind of more equal response. There is a slow carbon response as an
average isn't particularly different, although there is a huge spatial variability. Some places show us an increase from
places, show a loss and of course, it depends on the intensity of degrading. And if we move to Cropand, you see a very
strong loss in soil carbon. And this is partially due to the harvest, which takes out a lot of carbon from the system,
partly due to processes such as tillage, which increase the the restoration rates of of the soil carbon. And these these
model results just to show are broadly consistent with metro analysis of of force to quantify the capacity conversions
that we we see from observations @unoise@ all. Right so, that is my with quick run through of some of the key processes
I want to just try and bring that all together and talk a little bit about what the projections of the global
carbon cycle actually look like. So as always, I'll start with Lp J guests, but I will mention a couple of other models
just to be a little bit more even handed this plot on the left shows the the threshold carbon accumulation from
one thousand, eight hundred and fifty to two thousand, one hundred following a strong climate change. Eight point five
scenario from two thousand and six onwards. And if you concentrate here first on on the blue lines, the blue dash line
shows the uptake of carbon. You get just due due to Co2 fertilization alone so Co2 fertilization has a potentially
a huge uptake of carbon effect in these models. If you look at the dash dot line. This is the effect of climate. And you
see a strong decrease in carbon in the ecosystem, in the global ecosystem. And this is primarily due to the effects of
temperature and respiration. So at the higher temperatures, we are getting much higher respiration in soil is
particularly in lower soil lower soil carbon stocks. And when you do both, you get this. This blue line, which is
partially covered here Which, is much smaller than the Co2 effects alone. But you can see it is positive and quite
large, at least an hour model. So we noted that more is important than just the carbon. So nutrient limitations are also
important. And the red lines here showed us the same set of simulations, but with nitrogen limitation or nitrogen
cycling effects included. And you see that, once again, the Co2 still has a positive response on the dash line, but it
is much, much smaller than it was when we didn't consider nitrogen. However, in the other direction, the effect of
climate isn't quite so negative, because increased temperatures, they also increase the memorialization of nitrogen in
the soil and so make more nitrogen available for plants to use. So in some areas, they actually the climate
actually releases some of the nitrogen limitation. Yep @unoise@ Yeah. This includes vegetation dynamics and actually
this part of this effect that you see here is that in the in the Lower Borial region, you have a a relaxation of
nitrogen limitation, which leads to trees instead of grasses being able to grow there. And that gives um an increase in
the @unoise@ amount of % um carbon that is uptake by the biosphere. And that is purely a function of vegetation
dynamics. You wouldn't get it if your model had static vegetation. So in the guest model, we get actually a
net carbon uptate that is pretty similar to the carbon only model. But these other symbols here showed a difference for
a range of other models in the literature, which also incorporate nitrogen and every other model. Apart from ,
actually shows a slight decrease, or some of some sort of decrease in the amount of carbon taken up under
climate change. We have no idea, which is right, because they all incorporate different kinds of processes. Some of
those models don't have dynamic vegetation. Some of them do, but do it in a different way. And it is really uncertain
how this is going to happen just to say that this plot on the on the right here. This shows the latitude on breakdown of
these different fluxes and I think I only want to highlight here that we have much more uptake in the tropics. And
the Co2 fertilization effect is much larger in the tropics, and this comes from. It is basically an outcome of of the
Farquire model, which shows that if you have higher temperature, then the Co2 fertilization effect is more effective
@unoise@ @unoise@ % um. So this is in terms of process terms. This makes sense unfortunately. We, don't have
really yet the measurements to actually see if this is really happening in reality, although there, in the process of of
being made at the moment @unoise@ just to go back to the agriculture some simulations we made with a game of
. But looking at the effect of those different agricultural representations I showed you earlier. So this is the
change in the net uptake of carbon the negative values are uptake. The blue line is, if we just have
potential natural vegetation running into the future so this is historic. August is our Cpa point five climate
. If we just have potential natural vegetation. We have a strong uptake of carbon you would expect. I guess once
you include land management, then you, you lose much of this, but how you include that land management is really
important. So if you represent your crops as grasslands, like many of sister models do, then you get in our
representation of that. You get this line here. If you harvest those grasslands, which some models do, then you get this
line here. And if you include our full crop model, then you get an even larger increase in the year, in the emissions
that are given out. So this is something that Almight was referring to earlier did this is a novel one of these
processes, along with consideration of nitrogen that may lead to have to having much higher land use change emissions
than we have previously considered in the past. And of course, because we have this, this budget equation that says we
know roughly. We know exactly how much the Co2 is increasing in the atmosphere. And we know roughly the sources from
fossil fuels and the loss due to ocean sinks. We have a constraint on the total biosphere effects. So if we increase the
land use emissions, then we must also be increasing the size of the biaseric sink. And that means we are missing sink
processes, or we are not capturing them properly so even though Joe show you do that plot where the residual sink
from the budget method. And the actually matched up very closely that could easily be due to, ah, a set of missing
but compensating processes and @unoise@ you can miss processes and and have them compensate now. But in
fifty years on the different environmental conditions that relative balance might completely change and could change the
@unoise@ the direction of our projections. So as I promised, I'd broaden our way a bit from Lp. J guess but this
plot here is Lpg. I guess but run with a lot of different climate, lot of different climate models as input
so. First you can see that with one, trust your biosphere model, but a lot of different climates, depending on the
climate input that you are using, you can even have an uptake of carbon or a loss of carbon between one thousand, eight
hundred and fifty and one hundred, just from the changes in the amount of warming, and where that warming happens, or
and then if you also add into that uncertainty in the model representations, then you can get something like this
lower plot, which is the the carbon up take simulated by seam. At five system models. The grey bars show the range of
the Lpa J guests results in the top plot. And you can see that the range, when you include this extra level of
uncertainty is even larger and also goes in both directions so. When we are considering land use change emissions
going into the future. It is very difficult because we have a moving baseline of what the carbon stored in the
chestrial bias here is. And we don't even have agreement on what direction that baseline's going in. @unoise@ Just want
to touch on that um. Nitrogen isn't the only important nutrient. This is some work done in the M, B, I in Hamburg by
Daniel . The top plot shows nitrogen limitation spatially across the globe. At the end of this century, in a in a
strong climate change scenario. And you see that most of the nitrogen limitation is in the the northern mid, well in the
middle attitudes. And there is not so much in the tropics. However, what Daniel did was then add phosphorus cycling into
the model and looked at the effects of phosphorus limitation. And once again, there is quite some limitation in the mid
latitude regions, or they are actually in different areas. You notice but, there is also quite a lot of limitation
on the uptake of carbon, or the carbon stocks in the tropics. And it is the tropics that are really the driver of most
of the global carbon uptake in these models and yet nearly basically all the models, but this one have neglected
the effect of phosphorus cycling. And and there is a lot of evidence that suggests that phosphorus could be the limiting
neutron in the tropics. And therefore maybe our projections at a tropical forest up take due to C. A two were too
positive. Once again, we, we don't have a good handle on this, just like we don't really have a good handle on anything.
It seems @unoise@ % um @unoise@ that is not really true but there is many things that we don't have a good hands on, as
well as models varying in their their total change as a global average. They also vary a lot spcially. So these are some
results from an into comparison of made by Stephen and colleagues a few years ago. This is the change
between one thousand, eight hundred and sixty in two thousand and nine in the in the tree cover fraction between four
different dynamic vegetation models and you can see that the changes and the direction of changes and the position
of those changes is actually very massively between the models Opaj shows a loss of tree cover in the in the % uh
middle attitudes @unoise@ which, isn't showing it is actually showing an increase in. So when you start to look at
spatial effects. The models are the uncertainty between the models is actually even greater than when you just look at
the global averages and you see the same, the same kind of thing in the in the vegetation, carbon stocks in these
plots here @unoise@ the. Other thing i Just briefly highlighted this issue of Amazon , which resulted from a a
paper in the early two thousand by by Peter Cox and colleagues at the Met office and and the Uk. And they, they ran the
Headley Center coupled climate model and they simulated almost complete loss of the Amazon Rainforest by two
thousand one hundred, which was quite unexpected and made, made quite a shock in the community when it came out. There
is been a lot of work on this, following on to see if this actually happens basically no other model has really
been able to replicate the extent of this. This Amazonian dye back. And indeed, the new version of the Headley Center
model also doesn't replicate it. It looks like it might be a blip but having said that, if you look at the results
in this, this Dgvm comparison. You do see that the model here is the is the dynamic vegetation model in the
Center climate modeling, you see this massive loss basically of of tree cover. The other models, they don't show
the same massive die back, but they do show some tree cover loss said," Eh, there is some kind of agreement, or at least
a strong possibility that while we are unlikely to have complete loss of these forests. Maybe there is some
vulnerability of the forest as we see them now and you see it is also reflected in the carbon stocks, which
sometimes respond much more strongly than the tree cover fractions do @unoise@ on the other side of the story there was
a paper a couple of years ago by Chris Huntingford and also working with the guys at the Met Office. They ran the
Met office dynamic vegetation model, but this time ran it with a whole range of different Dg, different climate inputs
and they found that nearly every single model that they drove it with resulted in an increase in vegetation in the
tropics, apart from their own in house. U k met office model, which showed a decrease and so the outcome of its
paper was they suggested that actually the tropical forests are pretty robust to changes in @unoise@ in % um @unoise@ in
climate however, if I go back to the mortality mechanisms I mentioned earlier. These models aren't necessarily capturing
the real mortality mechanisms there is. There was a paper a couple of years ago that showed that the trees in the in the
Amazon have a very low safety margin for hydraulic conductivity. So basically they live right at the the maximum limits
that the environment allows them to live at, and you only have to push them very slightly before they start getting
hydraulic failure. And so there are questions over wherever we represent these processes related to mortality properly
@unoise@ and. This is my final slide just one thing I think is really important to bring up is that photosynthesis and
respiration. These can the basic rates can respond quite rapidly to changes in climate, but in the vegetation and the
biosphere system. There is a lot of lag. So the vegetation dynamics and the soil, carbon stocks of vegetation, carbon
stocks. These respond on a much longer time scale than the changes in climate. So this is some simulations. We ran where
we ran the model guests with A an S point five climate change up to two thousand one hundred and twenty, one
hundred. We fixed the climate, and we waited to see how long it would take for the biosphere to come back into
equilibrium, and what effect that would have. So you see the time for the biosphere in terms of the the net biosphere
productivity to come back into equilibrium of the climate is is about two hundred years after we fixed forcing
and. This in this time we have a large increase in our vegetation, carbon stock, and quite a substantial decrease in our
soil. Carpent stop so while we can look at changes, we can say we can take two thousand and fifty or two thousand
one hundred and say our model projects that we have this loss of vegetation with this climate at this time. This
isn't necessarily the loss of vegetation that is truly associated with this climate. If you allow the system to come
into equilibrium. And indeed, if you run our models now, um, just fix them at two thousand and five climate, for
instance, and run them into the future. You see, it is a large change just from the the environmental changes we have
had already that is built into the system, even if we could completely stop, or climate change right now, we would still
have large changes in the vegetation @unoise@ @unoise@ so just. Just a summary so we have a lack of appropriate
observations that we have to use models to represent the carbon cycle we try to capture the key processes. But
these are highly, highly simplified ways. We go about doing this. And whilst most models predict a strong uptake of
carbon by the biosphere under environmental change. There is a lot of uncertainty they don't universally agree and
different models represent different processes. And there is some processes to one is completely missing and so as
you are going to see, or as you have seen from from Joe's talk actually now. We swap them round these changes in a
natural vegetation are completely changing. The baseline that we consider when we consider the effects of change,
particularly in terms of that missing sink that Joe was talking about, and I'll leave it at that, flick through some
references, just for the copyright