Antler Size of Alaskan Moose Alces alces gigas: Effects of Population Density, Hunter Harvest and Use of Guides

Moose Alces alces gigas in Alaska, USA, exhibit extreme sexual dimorphism, with adult males possessing large, elaborate antlers. Antler size and conformation are influenced by age, nutrition and genetics, and these bony structures serve to establish social rank and affect mating success. Population density, combined with anthropogenic effects such as harvest, is thought to influence antler size. Antler size increased as densities of moose decreased, ostensibly a density-dependent response related to enhanced nutrition at low densities. The vegetation type where moose were harvested also affected antler size, with the largest-antlered males occupying more open habitats. Hunts with guides occurred in areas with low moose density, minimized hunter interference and increased rates of success. Such hunts harvested moose with larger antler spreads than did non-guided hunts. Knowledge and abilities allowed guides to satisfy demands of trophy hunters, who are an integral part of the Alaskan economy. Heavy harvest by humans was also associated with decreased antler size of moose, probably via a downward shift in the age structure of the population resulting in younger males with smaller antlers. Nevertheless, density-dependence was more influential than effects of harvest on age structure in determining antler size of male moose. Indeed, antlers are likely under strong sexual selection, but we demonstrate that resource availability influenced the distribution of these sexually selected characters across the landscape. We argue that understanding population density in relation to carrying capacity (K) and the age structure of males is necessary to interpret potential consequences of harvest on the genetics of moose and other large herbivores. Our results provide researchers and managers with a better understanding of variables that affect the physical condition, antler size, and perhaps the genetic composition of populations, which may be useful in managing and modeling moose populations.

Comparison of Endocrine Response to Stress Between Captive-Raised and Wild-Caught Bighorn Sheep

Stress hormones in Rocky Mountain bighorn sheep (Ovis canadensis canadensis), produced in response to environmental changes, road development, or high population density, may impact their immune systems to a threshold level that predisposes them to periodic, large-scale mortality. We compared the stress response to a novel environmental situation and repeated handling between bighorn sheep born and raised in captivity (CR) and bighorn sheep born in the wild (WC) and brought into captivity. We measured plasma epinephrine, norepinephrine, cortisol, and fecal glucocorticoid metabolites (FGM). Three weeks after each group’s arrival we used a one-time drop-net event to elicit an acute stress response, and we collected blood samples from each sheep over 35 minutes, as well as one fecal sample. We collected blood and fecal samples from both groups on 7 other occasions over the subsequent 6 months. We also collected fecal samples from the pen at approximately 24-hour intervals for 3 days following every handling event to monitor the stress response to handling. We found that CR sheep had a stronger autonomic nervous system response than WC sheep, as measured by epinephrine and norepinephrine levels, but we found a very similar hypothalamic–pituitary–adrenal axis (HPA) response, measured by cortisol levels, to the acute stress event of a drop-net restraint. We also found that once the WC sheep had acclimated, as indicated by the return to the initial baseline FGM levels within 12 weeks, the CR and WC groups’ HPA responses to sampling events were not significantly different from one another. Fecal samples can provide a noninvasive mechanism for managers to monitor baseline FGM for a given herd. Using long-term monitoring of FGM rather than values from a single point in time may allow managers to correlate these levels to outside influences on the herd and better understand the impacts of management changes, population density, or increased human developments on the health of the sheep population.

Deterministic Solutions for a Step-growth Polymerization

Chain topology, including branch node, chain link and cross-link dynamics that contribute to the number of elastically active strands and junctions, are calculated using purely deterministic derivations. Solutions are not coupled to population density distributions. An eigenzeit transformation assists in the conversion of expressions derived by chemical reaction principles from time to conversion space, yielding transport phenomena type expressions where the rate of change in the molar concentrations of branch nodes with respect to conversion is expressed as functions of the fraction of reactive sites on precursors and reactants. Analogies are hypothesized to exist in cross-linking space that effectively distribute branch nodes with i reacted moieties between cross-links having j bonds extending to the gel. To obtain solutions, reacted sites on nodes or links with finite chain extensions are examined in terms of stoichiometry associated with covalent bonding. Solutions replicate published results based on Miller and Macosko’s recursive procedure and results obtained from truncated weighted sums of population density distributions as suggested by Flory.

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

ANIMAL POPULATION ECOLOGY AND CONTROL FUNDAMENTALS

Expensive, extensive and apparently lethal control measures have been applied against many species of pest vertebrates and invertebrates for decades. In spite of this, few pests have been annihilated, and in many cases the stated goals have become progressively more modest, so that now we speak of saving foliage or a crop, rather than extermination. It is of interest to examine the reasons why animals are so difficult to exterminate, because this matter, of course, has implications for the type of control policy we pursue in the future. Also, it has implications for the problem of evaluating comparatively various resource management strategies. There are many biological mechanisms which could, in principle, enhance the performance of an animal population after control measures have been applied against it. These are of four main types: genetic, physiological, populationa1, and environmental. We are all familiar with the fact that in applying a control measure, we are, from the pest's point of view, applying intense selection pressure in favor of those individuals that may be preadapted to withstand the type of control being used. The well-known book by Brown (1958) documents, for invertebrates, a tremendous number of such cases. Presumably, vertebrates can show the same responses. Not quite so familiar is the evidence that sub-lethal doses of a lethal chemical may have a physiologically stimulating effect on population performance of the few individuals that happen to survive (Kuenen, 1958). With further research, we may find that this phenomenon occurs throughout the animal kingdom. Still less widely recognized is the fact that pest control elicits a populational homeostatic mechanism, as well as genetic and physiological homeostatic mechanisms. Many ecologists, such as Odum and Allee (1950, Slobodkin (1955), Klomp (1962) and the present author (1961, 1963) have pointed out that the curve for generation survival, or the curve for trend index as a function of last generations density is of great importance in population dynamics.