Sharayu Paranjpe

Genotypic variation in the photosynthetic competence of Sorghum bicolor seedlings subjected to polyethylene glycol-mediated drought stress

Eleven varieties of Sorghum bicolor, subjected to PEG-mediated drought stress were compared for their photosynthetic performance. The varieties differed in their relative water content over a range of PEG concentrations (0-25%). CO2 assimilation, stomatal conductance and the quantum yield of PSII electron transport decreased with increasing PEG concentrations in all varieties. However the intercellular CO2 concentration showed a nonlinear PEG concentration-dependent change. At lower PEG concentrations there was a decrease in the levels of intercellular CO2 concentration in all varieties that could be attributed to stomatal closure. At higher PEG concentrations, some varieties showed an increase in the intercellular CO2 concentration, indicating an inhibition of photosynthetic activity due to non-stomatal effects, while others did not. It was seen that the varieties differed in the stress thresholds at which stomatal and metabolic limitations to photosynthesis occur. These differences in the photosynthetic adaptation of Sorghum varieties could be useful in identifying genotypes showing large differences in photosynthetic adaptation, which could be useful in mapping photosynthetic traits for drought stress tolerance.

Estimation of Abundance

Ecologists are interested in assessing the absolute or relative size of a population in a given community in many contexts. A forester wants to develop an inventory of the flora of an area. A conservationist wishes to monitor the effect of protection on an endangered species. A wildlife manager wishes to see if there is a reasonable balance between herbivore and carnivore animals. In all cases a statistical approach has to be adopted.

Optimal Decision Models in Animal Behavior Systems

In this last chapter we turn our attention from populations to individuals. We have done this earlier in Chapter 3 when modeling predation. In section 3.4.4 we have invoked the concept of functional response, the relation between availability of food and predator’s rate of assimilation. Now we will expand on a variety of themes of this type. We will consider many types of behavior, such as feeding, hunting, avoiding being hunted, fighting, parenting etc. We assume that in some sense the behavior or any specific feature being considered is optimal. Why should we make this assumption? A rather simplistic reasoning goes somewhat like this. Behavior is (at least in part) inherited and is subject to natural selection. Hence in a population with behavioral variability caused by random mutations, sub optimal behavior patterns decline progressively, leaving the optimal type or types to dominate the whole population. The models considered here aim at examining the nature of this optimality and producing testable predictions. A logical follow up involves experiments and observations to test these predictions. But we shall not pursue this latter aspect. References to experimental work can be found in the literature cited. We will restrict ourselves to stating what are the decision variables, what is to be optimized and what is the nature of the optimal choice.

Single Species Populations

In this chapter our aim is to discuss some models commonly used for describing growth of a single species. The idea is to study behavior of the models in the long run as population increases. Specifically there are two aspects of interest in these models. The first is rate of growth and the second is attainment of a steady state (equilibrium). In some models, there may be no such equilibrium while in others there may be multiple equilibria. Equilibrium is a population size at which growth rate becomes zero. If in case of a small shift away from the equilibrium, the system returns to the steady state, it is termed a stable equilibrium. Otherwise it is called unstable. Population models described here are used later in discussion of management of biological resources. Exploding pest population can cause damage to crops. Hence models for this growth are viewed as potentially useful in crop protection. As is inevitable in any modeling exercise, we shall keep the framework very simple (and somewhat unrealistic). Thus, for instance, we will disregard effect of other species on the population under consideration (that will be done in the next chapter). We ignore/neglect effects of immigration and emigration. We shall thus be dealing with a geographically closed population. In sections 1, 2 and 3 we also ignore ages of individuals.

Harvesting Biological Populations

Biological populations, both of plants and animals, constitute a very important resource for mankind. Moreover, unlike minerals or fossil fuels, plants and animals are a renewable resource. It replenishes itself automatically after being harvested. Hunting, fishing and gathering forest produce are among man’s oldest professions. Practitioners of these professions have always assumed implicitly, that whenever they go looking for more of the resource, it will be there. Perhaps this was the case when the rate of exploitation was low because of smaller human population size and primitive technology. Today this assumption that biological resources are unlimited is definitely not valid. Forest cover is declining in many countries at an alarming rate because timber is harvested at a rate faster than its growth. Yields of fisheries seem to go down in spite of ever increasing fishing effort because increasing number of trawlers have to chase decreasing number of fish. In India, male elephants with tusks are harvested (poached) for ivory. This has caused a steep decline in their numbers. Tigers are killed for their skins (for display) and bones (for medicine) in excessive numbers and hence face extinction. Similarly Ginsberg and Milner-Gulland (1994) have expressed fear that excessive trophy hunting of male impala in Africa may cause a collapse of that population.

Populations of Two Interacting Species

A single species never exists in isolation. It may draw sustenance from others or may share resources with others. There may be collaborations between species in their daily activities. Indeed a typical species interacts with a very large number of others in an ecosystem. Such interactions of course affect the growth or decline of that species. The task of modeling complex interactions among the multitude of species in an ecosystem is clearly a formidable one. Therefore following the usual strategy, only one small step is taken towards increasing realism in models. Here we shall discuss models describing interactions between two species. These models try to account for the fact that populations are affected by intraspecific and interspecific interactions simultaneously. The standard group of models for this purpose is the Lotka — Volterra system. Two mathematicians A. J. Lotka, an American and V. Volterra an Italian, developed the system independently at the same time. For a very readable history of this and related work, see Kingsland (1985). Of the intraspecific and interspecific interactions, the latter are generally classified into three types, namely, competition, symbiosis or mutualism and predation or parasitism. We shall begin with the discussion of competition.

Numeracy for everyone

Most techniques in statistics are used in many disciplines besides ecology and have a wide range of applications from anthropology to zoology. They are used in industry, agriculture, social sciences and business. That is why we have called this series ’Numeracy for Everyone’. In the forthcoming parts, we will discuss applications of statistics in some of these fields. But some techniques are developed specially for ecological problems. Let us briefly look at a selection of those techniques.