|Production: Background Information|
Note: hot linked bold faced terms
are in the Glossary
|Understanding Production and its Limiting Factors|
In the first unit, we began to familiarize ourselves with some principles of biogeography and how biogeography and the human dimensions of global change are related. One of the questions raised there was how production (in agriculture, forestry, and so forth) may change as the climate and other environmental factors change. In this second unit, we look at this question in detail.
Let's begin with the basic question, what is production? We commonly associate production with yield. The units can be volume or mass. Increases in mass may be defined as the increase in gross biomass (for example, the growth of trees), as the increase in the number of individuals (as in the case of population increase), or as the increase in a subset of mass production (for example, in seed, fruit, or forage yield, a subset of total production).
Organism types, species, and individuals differ in their productivity and in the efficiency with which they convert resources into biomass. Efficiency varies throughout the life cycle of the organism and depends on the environmental setting. The organismic and the environmental factors that influence this efficiency and productivity are called limiting factors, because in combination, they determine (limit) efficiency and productivity. For example, cool-season plants optimize the conversion of atmospheric carbon dioxide to plant carbon at about 20o C. Cool-season plants, like wheat, rice, and soybeans, use the C3 photosynthetic process, in which the first product in the sequence of biochemical reactions involved in photosynthesis has three carbon atoms. C3-plants use some of the solar energy they absorb in a process known as photorespiration in which CO2 fixed by plants gets reoxidized and released again as CO2. Because photorespiration is repressed under conditions of increased CO2, the photosynthesis of C3-plants under conditions of increased CO2 will lead to the production of more biomass (i.e., increased productivity). Warm-season plants on the other hand, like corn, sorghum, millet, and sugarcane, optimize the conversion of atmospheric carbon dioxide to plant carbon at about 35o C. They use the C4 photosynthetic process in which the first product in the sequence of biochemical reactions involved in photosynthesis has four carbon atoms, a more efficient process than the C3 process. C4-plants are optimal photosynthesizers under current CO2 conditions, and thus are likely to be less efficient photosynthesizers in a carbon dioxide enriched world (cf. Rosenzweig and Hillel 1993: 209).
In commercial agriculture, economic yield is usually more important than biomass yield. For example, farmers may choose to plant a low-yield, but high-price crop instead of a high-yield, low-price crop. In this case, efficiency is defined as the return on cash investment rather than biomass production return on energy and carbon input. Much of what drives the intensification of agriculture through technological innovation, resource inputs, and structural changes is the search for financial efficiency, or in other words, profit. For example, government crop subsidy programs are a major driving force that farmers respond to by selecting which crops to grow. This aspect of global biomass production is not predicted by the production potential of the environment and for that reason is not considered any further here. Instead, let's direct our attention toward the non-agricultural biogeographical systems.
What factors govern how much biomass is produced? We discuss six that apply to all biogeographical systems and two additional ones that apply in the case of managed ecosystems and/or agricultural systems.
Not all sharing relationships are harmonious, nor do all mutually beneficial relationships maximize production. Such a relationship may have benefited buffalo grass populations, but it probably replaced more productive plants. Some plants have a positive growth response to being grazed on, but the grazers' presence is not required. Winter wheat is sown in the fall and is sometimes grazed to stimulate tillering of the newly emerged seedlings before winter dormancy sets in. Tillering, the increase in the number of emergent reproductive and vegetal shoots, creates more robust plants that produce a higher seed yield. The truest form of mutual benefit/dependence is in the symbiotic relationship between two organisms, a relationship in which both organisms mutually require the presence of the other. A good example is the symbiosis between fungi and algae that form lichens. Though these species evolved as independent species, they are now so mutually evolved that neither can survive alone. Similar relations exist between animals and digestive bacteria.
|The Food Web|
Places in which biotic interactions take place --
habitats for short -- can be viewed as systems in order to understand the
process of production. The concept of the food
web is one example of place as a system. In the food web, each
organism and energy reservoir interacts with its surroundings by transfers
of mass and energy
(Cunningham 1994). The flows of mass and energy can be expressed in transfer
budgets. They are altered by direct human intrusion into the process (e.g.,
harvesting, fertilizing, irrigating) and by indirect human alteration (habitat
reduction, forage removal affecting grazers and carnivore production, deliberate
or accidental introduction of a new organism, inadvertent changes in atmospheric
temperature or chemistry affecting plant life, wildlife habitat, and crops).
The alteration of these flows sometimes involves the redirection of resources
to other uses (e.g., water capture for agricultural crop irrigation or
car washing). Humans also invade the ecosystem energy storage compartments
for particular purposes. For example, plowing soil increases the oxidation
of soil carbon (organic matter), and forest cutting removes carbon and
nutrients stored in the standing biomass.
Modeling Material and Energy Flows Through the Food Web
Modeling is one way to enhance our understanding of nutrient and energy flows. It is important to remember that models are simplifications of reality; they are never as complete and dynamic as the real system we try to understand. Precisely because in building a model we select what we think are the most important elements and processes of a system, models are a helpful means to understand some of the interactions taking place and the relative importance of the elements in a system. The food web shown in the food web slide show is no exception (see FOODWEB.FLC).
Models like the food web can be operationalized as simulation models. We use simulations as tools to understand the interdependence among parts of a system (e.g., between nutrients and production) and to see how a system behaves if one of the elements is changed, or in other words, how sensitive the overall functioning of a system is to a change in one of its components. For instance, we can use such models to explore how production might change if we alter the availability of water or nutrients from the atmosphere. A test of this kind is called sensitivity analysis.
With regard to global change studies, such analyses are extremely useful and are also frequently used in the common case where we do not know what impacts, say, a temperature increase of 2 ºC would have on the productivity of wheat. The questions are: how sensitive is wheat to such a change in temperature, and in which direction will its productivity change; toward higher or lower productivity?
The simple three-compartment simulation model of the nutrient cycle (Gersmehl 1976) we will use in the activities operates under the laws of conservation of mass and energy (which says that mass and energy may change the form in which they appear, but they can't really be lost). This simulation model is formulated as an equilibrium or steady state model in which, after a certain number of iterations, the relative allocation of nutrients among compartments stabilizes. In the real world, forces that control the fluxes among compartments are not constant, not synchronous (they do not occur at the same time), and are seldom predictable. Thus, we cannot use the model to predict the future. We can, however, use it to illustrate how changes in one part of the system cascade through the system to produce different futures, providing all other things are held constant. This, of course, can be done only in the abstract world of models.
With a model such as the nutrient cycle simulation model we can see why plant biomass, soil, and litter conditions differ dramatically over large geographic areas or at different points in time. The quality of the modeling outcomes depends on how adequately we know the relevant attributes of the range of places we try to model.
|Human Interactions with the Food Web|
All human activities that affect land cover change mass and energy balances. Loss of vegetation accelerates erosion and deposition elsewhere. Release of greenhouse gasses alters the loss of long-wave-length terrestrial radiation and is thought to result in climate warming. Many other feedbacks in the global system, their nature and magnitude, remain unknown. Specifically we do not know how much of the greenhouse effect will be mitigated by increases in humidity and cloud cover that reduce incoming solar radiation.
We also do not understand how simple policies aimed
at mitigating problems in part of the system stimulate radically different
responses from place to place. Some of these mitigation strategies stimulate
responses that are the opposite of what the strategies were meant to do.
Just as business managers try to minimize tax impacts (by maximizing benefits
from the tax code), farmers respond to land conservation reserve programs
by conserving some land and at the same time plowing other land to maintain
the same base. Alternatively, they may quite intentionally fail to use
effective soil conservation measures in order to qualify for another government
program aimed at paying farmers to retire vulnerable lands. A third example
of unintended effects of mitigation strategies is the case where the government
pays farmers not to plant so as to keep marginal pieces of land out of
production while maintaining farmers' income. In some dramatic cases, this
led to a perceived scarcity of land and consequently caused the land values
of both the cultivated and the preserved land to go up. Finally, this resulted
in the ironic situation of farmers plowing under the (marginal) "virgin"
rangeland to meet the market demands for cultivated land and to boost their
incomes. Thus the attempt to conserve land ultimately lead to greater use
(and in some cases to degradation) of the land.