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Biomedical subjects

Charles J Krebs

Publications and source records attributed to Charles J Krebs.

3 recordsLinked to original sources

Two complementary paradigms for analysing population dynamics.

To understand why population growth rate is sometimes positive and sometimes negative, ecologists have adopted two main approaches. The most common approach is through the density paradigm by plotting population growth rate against population density. The second approach is through the mechanistic paradigm by plotting population growth rate against the relevant ecological processes affecting the population. The density paradigm is applied a posteriori, works sometimes but not always and is remarkably useless in solving management problems or in providing an understanding of why populations change in size. The mechanistic paradigm investigates the factors that supposedly drive density changes and is identical to Caughley's declining population paradigm of conservation biology. The assumption that we can uncover invariant relationships between population growth rate and some other variables is an article of faith. Numerous commercial fishery applications have failed to find the invariant relationships between stock and recruitment that are predicted by the density paradigm. Environmental variation is the rule, and non-equilibrial dynamics should force us to look for the mechanisms of population change. If multiple factors determine changes in population density, there can be no predictability in either of these paradigms and we will become environmental historians rather than scientists with useful generalizations for the population problems of this century. Defining our questions clearly and adopting an experimental approach with crisp alternative hypotheses and adequate controls will be essential to building useful generalizations for solving the practical problems of population management in fisheries, wildlife and conservation.

Animals↗

Complex numerical responses to top-down and bottom-up processes in vertebrate populations.

Population growth rate is determined in all vertebrate populations by food supplies, and we postulate bottom-up control as the universal primary standard. But this primary control system can be overridden by three secondary controls: top-down processes from predators, social interactions within the species and disturbances. Different combinations of these processes affect population growth rates in different ways. Thus, some relationships between growth rate and density can be hyperbolic or even have multiple nodes. We illustrate some of these in marsupial, ungulate and rabbit populations. Complex interactions between food, predators, environmental disturbance and social behaviour produce the myriad observations of population growth in nature, and we need to develop generalizations to classify populations. Different animal groups differ in the combination of these four processes that affect them, in their growth rates and in their vulnerability to extinction. Because conservation and management of populations depend critically on what factors drive population growth, we need to develop universal generalizations that will relieve us from the need to study every single population before we can make recommendations for management.

Animals↗

Population genetic structure of the cyclic snowshoe hare (Lepus americanus) in southwestern Yukon, Canada.

Spatial population structure has important ecological and evolutionary consequences. Little is known about the population structure of snowshoe hares (Lepus americanus), despite their ecological importance in North American boreal forests. We used seven variable microsatellite DNA loci to determine the spatial genetic structure of snowshoe hares near Kluane Lake, Yukon during a cyclic population peak. We sampled 317 hares at 12 sites separated by distances ranging from 3 to 140 km, and used 46 additional samples from Alaska and Montana. The level of genetic variation was high (13.4 alleles/locus, 0.67 expected heterozygosity) and the distribution of alleles and genotypes was not homogeneous across the sites. The degree of differentiation was low among Yukon sites (FST = 0.015) and between Yukon and Alaska (FST = 0.012), but the Montana site was highly differentiated (FST = 0.20). A weak pattern of isolation by distance was found over the Yukon study area, with an indication that local genetic drift may be important in shaping the regional genetic structure. Landscape barriers expected to influence gene flow did not consistently affect genetic structure, although there was evidence for a partial barrier effect of Kluane Lake. The high level of inferred gene flow confirms that snowshoe hare dispersal is widespread, successful and equal between the sexes. A stepping-stone model of gene flow, potentially influenced by the synchronous density cycle, appears to best explain the observed genetic structure. Our results suggest that despite their dramatic fluctuations in density, snowshoe hares in the northern boreal forest have a large evolutionary effective population size and are not strongly subdivided by either physical or social barriers to gene flow.

Alaska↗