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| And of course, there are forests, and forests. The top picture is Diana at the base of a giant spruce in Oregon; the bottom one two friends, at a conference, in a plantation in Brazil |
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Forests are diverse and fascinating ecological communities. They
range from the luxuriant rainforests of the tropics, where the warm, wet and
stable conditions encourage enormous plant and insect biodiversity, to the
biologically hardy but impoverished forests of the boreal regions. In between,
there are temperate deciduous and coniferous forests and mixed and broad-leaved
evergreen forests. These include the Eucalyptus forests of Australia. In some
countries they are protected and well managed but in others economic pressures,
and those associated with growing human populations, are bringing about their
destruction.
Forests are important for their aesthetic, ecological and direct
economic values, and because they absorb around 20% of the carbon dioxide that
modern human activities emit into the atmosphere. (The oceans absorb about
30%.) If we are to manage forests, assess their economic value, evaluate
whether the changes taking place in them are sustainable, and improve our
estimates of the amount of carbon dioxide they are likely to absorb or emit, we need to know the mass of material in
them. We also need to know how fast they are growing.
So the business of modelling forests is concerned with determining
the mass of material in them – their biomass – and their growth rates. The
models we use, like all mathematical models, are sets of equations that
describe how we think forests grow. We provide them with input data, press the
buttons on the computers and out come estimates of forest biomass and growth
rates that can be mapped and tabulated and used in decision making.
The question that has to be answered is: how do we develop and test
such models?
Conventional estimates of the amount of wood in a forest, and how
fast it’s growing, are based on laborious, time consuming and expensive
measurements. Standard-sized plots, which are necessarily rather small, are located
across selected areas, taking pains to sample the variations caused by
differences in soil type and topography. The dimensions of all the trees in
those plots are measured. Equations must be developed for each species to
convert the diameters and heights of the trees to wood volume. Biomass and
carbon content are calculated using knowledge of wood density. As you can
imagine, for complex natural forests, with a number of tree species and a range
of unhelpful tree shapes, it can be difficult to get accurate values.
Furthermore, although vast amounts of work have been done all over the world in
forest biometrics, only a tiny fraction of the world’s forests has been
sampled.
However, we can now estimate forest mass and growth rates from
measurements made by some of the wonderful range of earth-observing satellites
carrying all sorts of instruments in various orbits that provide complete
coverage of our earth. These instruments continuously record enormous amounts
of information in digital form.
They include the instrument called lidar — which is the acronym for
light detecting and ranging - from
which laser beams are projected directly downwards. The beams bounce back to
receivers with intensities that vary depending on the amount of foliage they
strike, or on whether they hit gaps in the canopy. The differences between
reflections from the top of the canopy and out of gaps provide estimates of
forest height.
Radar, projected both sideways and downwards, can provide an
accurate picture of the three-dimensional structure of forests. The return
signals from radar of different frequencies reflect differences in the size of
objects in their pathway. Small objects like leaves return higher frequency
waves. Larger objects, such as tree trunks, reflect lower frequencies.
Combining all this with data from lidar, it
becomes possible to estimate the above-ground biomass, and hence the carbon
content, of the forest stands.
To calibrate these satellite-derived estimates of tree heights and
biomass, and test their accuracy, research in various places around the world
is comparing them with conventional, ground-based measurements of the type I
outlined earlier. The areas where measurements have been made on the ground are
identified by what the remote sensing people call georeferencing – made much
easier nowadays with GPS. Agreement between directly measured and
satellite-derived estimates of forest mass is generally excellent.
Therefore, because the forest biomass in small areas can be
accurately estimated from space, we can confidently use satellite measurements
to estimate it for any area of the earth.
The next question is: what about growth rates?
On the basis of what we know about tree physiology and growth from
thousands of measurements by scientists all over the world, over many years, we
can construct models that allow us to calculate how fast forests are growing.
For these we need the right input data, which we can either collect on the
ground or get from satellite measurements.
We know that plants capture carbon dioxide through the process of
photosynthesis, which converts carbon dioxide into carbohydrates.
Photosynthesis is driven by radiant energy from the sun, absorbed by foliage.
Some satellites provide estimates of cloud cover and from these, and the date
and latitude, we can calculate the amount of solar radiation reaching the earth
at any location on any day. Now, if we know how much foliage a forest is
carrying, and something about the photosynthetic characteristics of that
foliage, we can calculate how much solar energy the forest is absorbing and
therefore how fast it is capturing carbon dioxide and how fast it is growing.
Rates of growth are also affected by temperatures.
There are instruments on satellites that monitor the radiation
reflected from surfaces in the visible and near-infra-red wavebands. The amount
of foliage carried by vegetation in any pixel can be estimated from the
reflectance ratios in different wavebands. The optics in satellite sensors can
also indicate differences in the greenness of the leaves, in the same way that
our eyes can detect those differences. Conventional physiological research has
shown that leaf greenness can be equated with different nitrogen content in the
leaves, which is associated with changes in photosynthetic capacity. The
water status of forests – that is, whether they are well-watered or suffering
from drought – is also indicated by the reflective properties of the leaves, so
the development of drought, which affects the uptake of carbon dioxide by vegetation,
can be identified from sequential scans and factored into estimates of
photosynthesis rates.
So satellite measurements allow us to estimate the amount of foliage
per unit ground area. They provide data on solar radiation and allow us to keep
track of changes in greenness, and of indices of plant water status. Land
surface temperatures can be estimated from their emissions of long-wave
radiation. Putting all this
information into our models, and integrating over seasons, we can calculate how
much carbon dioxide has been fixed by the forest and used for
above-ground and below-ground growth.
The obvious question that now has to be answered is: what evidence
do we have that these modeled estimates of forest growth rates, based on
satellite measurements, are correct? Do they accurately reflect reality?
To estimate growth rates from conventional forest biometrics the
whole on-ground measurement exercise has to be repeated at intervals. These are
usually a few years. Growth is then calculated as the difference between
sequential sets of measurements, but the uncertainty in the results is
considerable. Also, because soils, topography and microclimate all vary, the results
are not transportable: that means you can’t, with any confidence, apply
estimates of growth rates obtained from one forest region – or even one stand –
to another. And the growth of trees is determined by weather, acting on
physiological processes, so even if the forest is undisturbed we can’t assume
that the growth rates determined over some interval will apply over the next
one – particularly if the climate is changing. Finally, when there is a
disturbance, caused by harvesting or fire or storm or insect attack, there’s no
way, on the basis of conventional measurements, that you can predict with any
confidence how the forest is going to recover.
Despite all that, areas for which good biometrics data exist serve
as benchmarks against which modelled estimates of forest biomass and growth,
derived from satellite measurements, can be compared. Many such comparisons
have been made. The satellite-derived estimates are usually within the error of
the ground-based measurements.
We can also test models against direct measurements of the rate of
carbon dioxide capture by forests.
The rate of exchange of carbon dioxide between forests and the
atmosphere, and the flow of water vapour into the atmosphere from forests, can
be measured continuously using sophisticated instruments placed on towers
situated above different types of vegetation. The towers have to be placed in
quite large areas – a square kilometre or more - with uniform topography
covered by forest of uniform age and composition. The difference between the
downward flow of carbon dioxide because of uptake by photosynthesis during the
day, and the upward flow because of respiration, at night – gives a direct
measure of the rate of carbon capture by photosynthesis, and hence forest
growth rates. Around the world, hundreds of these ‘flux’ towers, as they are
called, have been installed in different types of forest. They provide the
‘gold standard’ against which to compare our models. We have seven of them over
forests in Australia, covering tropical rainforest and several types of
eucalyptus.
There have been many comparisons between measurements of forest
photosynthesis, made from flux towers over days, weeks and seasons, and
estimates derived from models using satellite measurements of forest structure,
foliage area, radiation interception and foliage condition, associated with the
area round the towers. The results
indicate that the models can be used with confidence to predict the rates at
which forests capture carbon dioxide and convert it into carbohydrates.
So the evidence from two entirely independent techniques indicates
that we can satisfactorily model forest growth rates from measurements made in
space.
And we can do more. Forests are disturbed and damaged by logging,
wildfires, insect attacks or climate change. The remarkable array of sensors on
earth-observing satellites allows us to identify these disturbances, and the
areas affected across the whole globe. We can monitor, over time, the recovery
– or progressive degradation – of the forests. To identify the effects of
climate change we need models that allow us to evaluate the importance of
extended droughts or increasing temperatures. We also need to evaluate the effects
of pollutants or other factors that change the structure and productivity of
forests. The ubiquitous satellites above us provide us with the information we
need to do all this.
The whole business
is fascinating, exciting and very important. I just regret that I am no longer
involved with it – but then I’m even older than Robyn Williams so am
comfortably retired.
