An investigation of genetic variation in Carthamus lanatus in New South Wales, Australia, using intersimple sequence repeats (ISSR) analysis

Weed Research ◽  
2003 ◽  
Vol 43 (3) ◽  
pp. 208-213 ◽  
Author(s):  
G J Ash ◽  
R Raman ◽  
N S Crump
Keyword(s):  
Genetic Variation ◽  
New South ◽  
New South Wales ◽  
Issr Analysis ◽  
South Wales

Integrating demographic and genetic studies of the Greater Glider Petauroides volans in fragmented forests: predicting movement patterns and rates for future testing

1999 ◽  
Vol 5 (1) ◽  
pp. 2 ◽  
Author(s):  
D. B. Lindenmayer ◽  
R. C. Lacy ◽  
H. Tyndale-Biscoe ◽  
A. C. Taylor ◽  
K. L. Viggers ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Habitat Fragmentation ◽  
National Parks ◽  
New South ◽  
New South Wales ◽  
Genetic Structuring ◽  
Genetic Studies ◽  
Genetic Characteristics ◽  
Eucalypt Forest ◽  
South Wales

Habitat loss and habitat fragmentation can have major effects on the distribution and abundance of species (Saunders et al. 1987), often in unpredictable ways (Klein 1989; Tilman et al. 1994; Lacy and Lindenmayer 1995; Cunningham and Moritz 1998). An understanding of responses of species, which lead to persistence or extinction in such disturbed systems, is important for the effective management of many taxa in fragmented multi-use landscapes. One way to examine population dynamics in fragmented systems is to analyse the genetic characteristics of subpopulations in remnant habitat patches (Sarre 1995), borrowing from the population genetics literature for the interpretation of key effects. For example, it is well established that a small, completely isolated population will lose genetic variation rapidly due to genetic drift (Lacy 1987). However, loss of genetic variation within, and increasing differentiation between, subpopulations will be counteracted by inter-population dispersal. Theoretical models of metapopulation structure which describe connectivity and stability can be examined using various demographic input parameters. Importantly, such models can also produce predictions for genetic structuring, making the combined use of modelling and empirical genetic data an extremely powerful tool in examining the effects of habitat fragmentation. On this basis, we have recently commenced a series of integrated demographic and genetic studies of the Greater Glider Petauroides volans at Tumut in southern New South Wales. The study area near Tumut in southeastern New South Wales is characterized by an array of remnant patches of eucalypt forest (0.2?125 ha in size) that were created 15?65 years ago by the establishment of an extensive (50 000 ha) plantation of exotic softwood, Radiata Pine Pinus radiata and known as the Buccleuch State Forest (Routley and Routley 1975). Large areas of continuous native eucalypt forest occur at the boundaries of the plantation (Fig. 1), including those within the Brindabella and Kosciuszko National Parks, and the Bondo and Bungongo State Forests.

Genetic variation in liveweight and ultrasonic fat depth in Australian Poll Dorset sheep

1991 ◽  
Vol 42 (4) ◽  
pp. 629 ◽  
Author(s):  
KD Atkins ◽  
JI Murray ◽  
AR Gilmour ◽  
AL Luff
Keyword(s):  
Genetic Variation ◽  
Genetic Parameters ◽  
New South ◽  
New South Wales ◽  
Genetic Correlations ◽  
Age Group ◽  
Genetic Response ◽  
Evaluation Procedures ◽  
South Wales ◽  
Breed Improvement

Genetic and phenotypic variances and covariances were estimated for liveweight and ultrasonic fat depth in the Australian Poll Dorset. The data were obtained from the New South Wales Meatsheep Testing Service between 1983 and 1986, and involved 28 159 records from 50 stud flocks. A total of 681 sires were used to derive the half-sib genetic parameters. The data were further grouped according to average age at measurement, so that parameters were estimated for animals within age ranges of 4-6 months, 7-11 months and 12-16 months. Heritabilities for liveweight were between 0.21 and 0.31, with the highest value obtained in the oldest age group. Heritabilities for fat depth varied between 0.26 and 0.31, with the highest value again obtained in the oldest age group. Genetic correlations between liveweight and fat depth were about 0.4 except in 4-6-month-old animals where the estimate was about 0.7. The implications of these parameters to breed improvement programmes are discussed. In particular, the scope for genetic response in producing faster growing, leaner animals at a constant liveweight is highlighted. Information on sire-son generation intervals and apparently limited between-flock genetic variation is reported. The results indicate the need to improve the evaluation procedures for sires within the breed at both the between- and within-flock level.

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