Moose

Genetic analysis of moose (Alces alces) in Ontario, Canada.

Contact: Dr. Paul Wilson

Photo Courtesy of Dr. Murray Lankester, Lakehead University

Why Study Moose?
In Ontario, the moose (Alces alces) represents an economically and culturally important big game species. Traditionally, moose management has depended on aerial surveys of density, sex ratios and age composition to determine harvest limits to maintain a sustainable population size in a particular area while at the same time satisfying hunting prerogatives. With the advent of highly specific and affordable molecular genetic techniques, the opportunity exists to expand current wildlife population knowledge. When used in conjunction with ecological population data, molecular genetics can provide a powerful monitoring application for populations under harvest regulation such as the moose. Furthermore, molecular genetics can also offer wildlife managers the ability to re-evaluate current management / harvest criteria as well as assist in law enforcement.

Objective: Define local populations and their dynamics to re-evaluate the practicality of wildlife management units.

Presently, moose harvest limits are assigned to individual wildlife management units (WMUs), which are not representative of local populations (Figure 1). As a consequence, harvest quotas may not accurately reflect the current status of moose populations leading to erroneous harvest reductions/closures or over-harvesting in particular units. In response, genetic analysis of Ontario moose is being implemented in order to identify local moose populations, and define their geographic boundaries. Such information will aid in the restructuring of practical moose management areas in order to facilitate accurate harvest quotas and protect of small moose populations experiencing low levels of recruitment.

FIGURE 1: Map of Current (WMUs) for the Province of Ontario, Canada including hypothetical moose population boundaries within a single unit or encompassing several units.

Dispersal is often associated with what we refer to as emigration and immigration. That is, movement from one population to another population. It is usually (not always) unidirectional. Knowing the dynamics of moose population dispersal, especially of the level of genetic exchange between different populations is also important for moose management. Since moose harvests typically set different bag-limits according to sex, identifying the sex cohort and the direction which gene flow occurs among adjacent populations can assist in developing responsible sex-biased management which assure animal numbers are kept at levels which maintain a high level of dispersal. It can also lead to the implementation of protected corridors between populations to help increase genetic exchange. This is very important for the rehabilitation of moose populations experiencing low recovery rates located adjacent to moose populations of sustainable size.

Specimen Collection

Specimens are being collected from both harvested and non-harvested moose populations. Tissue samples (muscle, skin and soft organs) will be taken from both hunter and road-killed animals.

Tissue samples can be easily obtained by co-operating Ontario Ministry of Natural Resources officials at mandatory check stations in all of the proposed sampling areas.

FIGURE 2: Distribution of moose tissue samples collected in 2002-2003.

Tissue samples collected here will also be added to the NRDPFC forensic DNA collection and utilized for casework.This year Conservation Officers have collected to date 396 tissue samples from across the province (FIGURE 2). Continued annual sampling offers the potential for a long-term monitoring strategy.

Data Analysis
DNA will be extracted from all samples using the CRS automated robotic system that utilizes DNeasy silica membrane extraction protocol. This automated system at the NRDPFC, offers the opportunity for cost-effective, high throughput DNA analysis and monitoring. Extracted DNA will then be amplified using the polymerase chain reaction (PCR) specific to the type of analysis being performed. Several different genetic marker techniques as well as spatial analysis will be employed for this particular study in order to obtain specific information. These include:

Microsatellites
Microsatellites are areas of the genome which contain short DNA sequences, including dinucleotides (such as “CT” or “GT”), trinucleotides (such as “CAG”), or tetranucleotide sequences, repeated in tandem up to several dozen times.

These markers are used to identify individuals, to determine paternity or parentage (as the sequences are usually passed on unchanged from parents to offspring) and to identify different populations of organisms quantify of allelic diversity, variation and dispersal events (Wilson et al. 2002).

Mitochondrial DNA markers

Mitochondrial DNA (mtDNA) is passed from one generation to the next, essentially unchanged, and solely through the maternal line of a family. MtDNA analysis can be used to trace maternal lineages in wildlife populations and determine population structure (Hedrick and Miller 1996).

Y-Chromosome markers

Y-Chromosome markers can trace generation lineages through a single parent.Only males possess Y-chromosomes, therefore, analyzing conserved regions DNA within this chromosome, one is able to trace male lineages and comment on male dispersal events among populations (Olivier et al., 1999).

Landscape Genetics (GIS)

Geographic Information Systems (GIS) is an environmental modeling tool, well established in habitat-based studies of animal populations to analyze remotely sensed databases.

One application still unexplored with GIS is the animal population dynamics as expressed by genetic parameters.

Incorporating moose DNA profiles of functional and neutral loci into GIS databases will be valuable in deciphering the effect different habitat types, hunting regimes and anthropogenic pressures are having on the diversity and fitness of local moose populations.

In Closing…

It is apparent that genetic techniques are quickly becoming the method of choice for management data collection. This moose genetics project will ensure the best data is available to wildlife mangers when enforcing their mandate to protect and conserve Ontario’s wildlife heritage.

References

Hedrick, P. W., and P. S. Miller. 1996. Rare alleles, MHC and captive breeding. Pages 187-204 in V. Loeschcke, J. Tomiuk, and S. K. Jain, editors. Conservation genetics. Birkhauser, Basel, Switzerland.
Miller, P. S., and P. W. Hedrick. 1991. MHC polymorphism and the design of captive breeding programs: simple solutions are not the answer. Conservation Biology 5:556-558.

Olivier, M., M. Breen, M.M. Binns and G. Lust. 1999. Localization and characterization of nucleotide sequences from the canine Y chromosome. Chromosome Res. 7: 223-233.

Wilson, P.J., S. Grewal, A. Sipak, A. Rodgers, R. Rempel, J. Saquet, H. Hristienko, F. Burrows, R. Peterson, and B.N. White. Accepted 2002. Genetic Variation and population structure of moose (Alces alces) at neutral and functional loci. Can. Jour. Zoo.

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