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Journal articles on the topic 'Earthworms Population viability analysis'

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Published: 4 June 2021
Last updated: 7 February 2022

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1

Reed, J. Michael. "Population Viability Analysis." Auk 120, no. 1 (2003): 237. http://dx.doi.org/10.1642/0004-8038(2003)120[0237:pva]2.0.co;2.

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2

Cuthbert, Richard. "Population Viability Analysis." Biological Conservation 114, no. 1 (November 2003): 153. http://dx.doi.org/10.1016/s0006-3207(02)00402-0.

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3

Fieberg, John. "Population viability analysis." Journal of Biogeography 31, no. 3 (February 24, 2004): 515–16. http://dx.doi.org/10.1046/j.0305-0270.2003.01027.x.

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4

SHAFFER, MARK L. "Population Viability Analysis." Conservation Biology 4, no. 1 (March 1990): 39–40. http://dx.doi.org/10.1111/j.1523-1739.1990.tb00265.x.

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5

Boyce, M. S. "Population Viability Analysis." Annual Review of Ecology and Systematics 23, no. 1 (November 1992): 481–97. http://dx.doi.org/10.1146/annurev.es.23.110192.002405.

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6

Reed, J. Michael. "Population Viability Analysis." Auk 120, no. 1 (January 1, 2003): 237–39. http://dx.doi.org/10.1093/auk/120.1.237.

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Abstract The following critiques express the opinions of the individual evaluators regarding the strengths, weaknesses, and value of the books they review. As such, the appraisals are subjective assessments and do not necessarily reflect the opinions of the editors or any official policy of the American Ornithologists' Union.
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7

Rexstad, Eric. "Population Viability Analysis." Wildlife Society Bulletin 32, no. 2 (June 2004): 606–7. http://dx.doi.org/10.2193/0091-7648(2004)32[606:br]2.0.co;2.

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8

Beier, Paul, S. R. Beissinger, and D. R. McCullough. "Population Viability Analysis." Journal of Wildlife Management 67, no. 4 (October 2003): 890. http://dx.doi.org/10.2307/3802694.

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9

Diogéne, J., M. Dufour, G. G. Poirier, and D. Nadeau. "Extrusion of earthworm coelomocytes: comparison of the cell populations recovered from the species Lumbricus terrestris, Eisenia fetida and Octolasion tyrtaeum." Laboratory Animals 31, no. 4 (October 1, 1997): 326–36. http://dx.doi.org/10.1258/002367797780596068.

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Coelomocytes were extruded from three earthworm species: Lumbricus terrestris, Eisenia fetida and Octolasion tyrtaeum. Featuring a simple low-vacuum holding device, the proposed methodology allows the recovery of cells with minimum risk of contamination by faecal material. The viability of O. tyrtaeum coelomocytes was highly reproducible (average 93%), with an average yield of 0.92 × 106 viable cells per earthworm. Cell viability for L. terrestris and E. fetida averaged ~68% but the cell yields were higher (respectively 1.67 × 106 and 1.28 × 106). Large inter-individual differences in cell yields were observed with L. terrestris. Flow cytometric analyses indicated species to species differences in cell populations. Coelomocytes from E. fetida were the smallest with ~57% of the total viable cells recovered being monitored between 2 and 10 µm. Large granulated cells (≥20 µm) were detected in fairly large proportions in L. terrestris and O. tyrtaeum [~52 and ~96%, respectively) while they were less abundant in E.fetida (~9%). Using the vital dye neutral red to assess functional integrity, average cellular uptakes were significantly higher for L. terrestris and O. tyrtaeum than for E. fetida (2.94, 2.66 and 0.64 µg/2 × 105 cells, respectively). In summary, the extrusion methodology herein described is applicable for the recovery of coelomocytes from a wide range of earthworm sizes and species. Moreover, this study strengthens the fact that extruded coelomocytes could be used for the evaluation of cell dysfunction and/or cell death following an in vitro and/or in vivo treatment.
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10

Li, Yiming, and Li Dianmo. "Advance in population viability analysis." Biodiversity Science 02, no. 1 (1994): 1–10. http://dx.doi.org/10.17520/biods.1994001.

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11

Lee, DE, E. Fienieg, C. Van Oosterhout, Z. Muller, M. Strauss, KD Carter, CPJ Scheijen, and F. Deacon. "Giraffe translocation population viability analysis." Endangered Species Research 41 (February 27, 2020): 245–52. http://dx.doi.org/10.3354/esr01022.

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Most populations of giraffes have declined in recent decades, leading to the recent IUCN decision to upgrade the species to Vulnerable status, and some subspecies to Endangered. Translocations have been used as a conservation tool to re-introduce giraffes to previously occupied areas or establish new populations, but guidelines for founding populations are lacking. To provide general guidelines for translocation projects regarding feasibility, we simulated various scenarios of translocated giraffe populations to identify viable age and sex distributions of founding populations using population viability analysis (PVA) implemented in Vortex software. We explored the parameter space for demography and the genetic load, examining how variation in founding numbers and sex ratios affected 100 yr probability of population extinction and genetic diversity. We found that even very small numbers of founders (N ≤ 10 females) can appear to be successful in the first decades due to transient positive population growth, but with moderate population growth rate and moderate genetic load, long-term population viability (probability of extinction <0.01) was only achieved with ≥30 females and ≥3 males released. To maintain >95% genetic diversity of the source population in an isolated population, 50 females and 5 males are recommended to compose the founding population. Sensitivity analyses revealed first-year survival and reproductive rate were the simulation parameters with the greatest proportional influence on probability of extinction and genetic diversity. These simulations highlight important considerations for translocation success and data gaps including true genetic load in wild giraffe populations.
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12

Ellner, Stephen P., John Fieberg, Donald Ludwig, and Chris Wilcox. "Precision of Population Viability Analysis." Conservation Biology 16, no. 1 (February 2002): 258–61. http://dx.doi.org/10.1046/j.1523-1739.2002.00553.x.

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13

Drechsler, Martin, and Mark A. Burgman. "Combining Population Viability Analysis with Decision Analysis." Biodiversity and Conservation 13, no. 1 (January 2004): 115–39. http://dx.doi.org/10.1023/b:bioc.0000004315.09433.f6.

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14

Ruggiero, Leonard F., Gregory D. Hayward, and John R. Squires. "Viability Analysis in Biological Evaluations: Concepts of Population Viability Analysis, Biological Population, and Ecological Scale." Conservation Biology 8, no. 2 (June 1994): 364–72. http://dx.doi.org/10.1046/j.1523-1739.1994.08020364.x.

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15

Reed, J. Michael, L. Scott Mills, John B. Dunning, Eric S. Menges, Kevin S. McKelvey, Robert Frye, Steven R. Beissinger, Marie-Charlotte Anstett, and Philip Miller. "Emerging Issues in Population Viability Analysis." Conservation Biology 16, no. 1 (February 2002): 7–19. http://dx.doi.org/10.1046/j.1523-1739.2002.99419.x.

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16

Horino, S., and S. Miura. "Population viability analysis of a Japanese black bear population." Population Ecology 42, no. 1 (April 29, 2000): 37–44. http://dx.doi.org/10.1007/s101440050007.

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17

Horino, S., and S. Miura. "Population viability analysis of a Japanese black bear population." Researches on Population Ecology 42, no. 1 (2000): 0037. http://dx.doi.org/10.1007/s101440050042.

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18

Chisholm, Ryan A., and Brendan A. Wintle. "INCORPORATING LANDSCAPE STOCHASTICITY INTO POPULATION VIABILITY ANALYSIS." Ecological Applications 17, no. 2 (March 2007): 317–22. http://dx.doi.org/10.1890/05-1580.

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19

Roberts, James H., Paul L. Angermeier, and Gregory B. Anderson. "Population Viability Analysis for Endangered Roanoke Logperch." Journal of Fish and Wildlife Management 7, no. 1 (February 1, 2016): 46–64. http://dx.doi.org/10.3996/032015-jfwm-026.

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Abstract A common strategy for recovering endangered species is ensuring that populations exceed the minimum viable population size (MVP), a demographic benchmark that theoretically ensures low long-term extinction risk. One method of establishing MVP is population viability analysis, a modeling technique that simulates population trajectories and forecasts extinction risk based on a series of biological, environmental, and management assumptions. Such models also help identify key uncertainties that have a large influence on extinction risk. We used stochastic count-based simulation models to explore extinction risk, MVP, and the possible benefits of alternative management strategies in populations of Roanoke logperch Percina rex, an endangered stream fish. Estimates of extinction risk were sensitive to the assumed population growth rate and model type, carrying capacity, and catastrophe regime (frequency and severity of anthropogenic fish kills), whereas demographic augmentation did little to reduce extinction risk. Under density-dependent growth, the estimated MVP for Roanoke logperch ranged from 200 to 4200 individuals, depending on the assumed severity of catastrophes. Thus, depending on the MVP threshold, anywhere from two to all five of the logperch populations we assessed were projected to be viable. Despite this uncertainty, these results help identify populations with the greatest relative extinction risk, as well as management strategies that might reduce this risk the most, such as increasing carrying capacity and reducing fish kills. Better estimates of population growth parameters and catastrophe regimes would facilitate the refinement of MVP and extinction-risk estimates, and they should be a high priority for future research on Roanoke logperch and other imperiled stream-fish species.
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20

Chaudhary, Vratika, and Madan K. Oli. "A critical appraisal of population viability analysis." Conservation Biology 34, no. 1 (September 16, 2019): 26–40. http://dx.doi.org/10.1111/cobi.13414.

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21

MENGES, ERIC S. "Population Viability Analysis for an Endangered Plant." Conservation Biology 4, no. 1 (March 1990): 52–62. http://dx.doi.org/10.1111/j.1523-1739.1990.tb00267.x.

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22

Elliott, Graeme P. "Mohua and stoats: A population viability analysis." New Zealand Journal of Zoology 23, no. 3 (January 1996): 239–47. http://dx.doi.org/10.1080/03014223.1996.9518083.

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23

McCarthy, M. A., H. P. Possingham, J. R. Day, and A. J. Tyre. "Testing the Accuracy of Population Viability Analysis." Conservation Biology 15, no. 4 (August 3, 2001): 1030–38. http://dx.doi.org/10.1046/j.1523-1739.2001.0150041030.x.

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24

McCarthy, Michael A., Mark A. Burgman, and Scott Ferson. "Sensitivity analysis for models of population viability." Biological Conservation 73, no. 2 (1995): 93–100. http://dx.doi.org/10.1016/0006-3207(95)90029-2.

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25

Breen, Paul A., David J. Gilbert, and Paul J. Starr. "Comment on sea lion population viability analysis." Polar Biology 35, no. 10 (July 19, 2012): 1617–18. http://dx.doi.org/10.1007/s00300-012-1218-z.

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26

Holmes, Elizabeth E., and William F. Fagan. "VALIDATING POPULATION VIABILITY ANALYSIS FOR CORRUPTED DATA SETS." Ecology 83, no. 9 (September 2002): 2379–86. http://dx.doi.org/10.1890/0012-9658(2002)083[2379:vpvafc]2.0.co;2.

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27

Coulson, Tim, Georgina M. Mace, Elodie Hudson, and Hugh Possingham. "The use and abuse of population viability analysis." Trends in Ecology & Evolution 16, no. 5 (May 2001): 219–21. http://dx.doi.org/10.1016/s0169-5347(01)02137-1.

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28

GRIMM, VOLKER, ELOY REVILLA, JURGEN GROENEVELD, STEPHANIE KRAMER-SCHADT, MONIKA SCHWAGER, JORG TEWS, MATTHIAS C. WICHMANN, and FLORIAN JELTSCH. "Importance of Buffer Mechanisms for Population Viability Analysis." Conservation Biology 19, no. 2 (April 2005): 578–80. http://dx.doi.org/10.1111/j.1523-1739.2005.000163.x.

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29

Brook, Barry W. "Pessimistic and Optimistic Bias in Population Viability Analysis." Conservation Biology 14, no. 2 (April 2000): 564–66. http://dx.doi.org/10.1046/j.1523-1739.2000.99039.x.

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30

McCarthy, Michael A., Sandy J. Andelman, and Hugh P. Possingham. "Reliability of Relative Predictions in Population Viability Analysis." Conservation Biology 17, no. 4 (August 2003): 982–89. http://dx.doi.org/10.1046/j.1523-1739.2003.01570.x.

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31

Lindenmayer, David B., Robert C. Lacy, and Matthew L. Pope. "TESTING A SIMULATION MODEL FOR POPULATION VIABILITY ANALYSIS." Ecological Applications 10, no. 2 (April 2000): 580–97. http://dx.doi.org/10.1890/1051-0761(2000)010[0580:tasmfp]2.0.co;2.

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32

Ferchichi, A., M. Jerry, and S. Ben Miled. "Viability Analysis of Fisheries Management on Hermaphrodite Population." Acta Biotheoretica 62, no. 3 (June 18, 2014): 355–69. http://dx.doi.org/10.1007/s10441-014-9228-6.

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33

McGowan, Conor P., Michael C. Runge, and Michael A. Larson. "Incorporating parametric uncertainty into population viability analysis models." Biological Conservation 144, no. 5 (May 2011): 1400–1408. http://dx.doi.org/10.1016/j.biocon.2011.01.005.

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34

Fujiwara, Masami. "EXTINCTION-EFFECTIVE POPULATION INDEX: INCORPORATING LIFE-HISTORY VARIATIONS IN POPULATION VIABILITY ANALYSIS." Ecology 88, no. 9 (September 2007): 2345–53. http://dx.doi.org/10.1890/06-1405.1.

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35

Legault, Christopher M. "Population Viability Analysis of Atlantic Salmon in Maine, USA." Transactions of the American Fisheries Society 134, no. 3 (May 2005): 549–62. http://dx.doi.org/10.1577/t04-017.1.

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36

Reed, J. Michael. "Population Viability Analysis Steven R. Beissinger Dale R. McCullough." Auk 120, no. 1 (January 2003): 237–39. http://dx.doi.org/10.2307/4090171.

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37

Zhou, Zhihua, and Wenshi Pan. "Analysis of the Viability of a Giant Panda Population." Journal of Applied Ecology 34, no. 2 (April 1997): 363. http://dx.doi.org/10.2307/2404882.

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38

Hertz, Morten, Iben Ravnborg Jensen, Laura Østergaard Jensen, Iben Vejrum Nielsen, Jacob Winde, Astrid Vik Stronen, Torsten Nygaard Kristensen, and Cino Pertoldi. "Population viability analysis on a native Danish cattle breed." Animal Genetic Resources/Ressources génétiques animales/Recursos genéticos animales 59 (October 26, 2016): 105–12. http://dx.doi.org/10.1017/s2078633616000205.

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SummaryMany domestic breeds face challenges concerning genetic variability, because of their small population sizes along with a high risk of inbreeding. Therefore, it is important to obtain knowledge on their extinction risk, along with the possible benefits of certain breeding strategies. Since many domestic breeds face the same problems, results from such studies can be applied across breeds and species. Here a Population Viability Analysis (PVA) was implemented to simulate the future probability of extinction for a population of the endangered Danish Jutland cattle (Bos taurus), based on the software Vortex. A PVA evaluates the extinction risk of a population by including threats and demographic values. According to the results from the PVA the population will go extinct after 122 years with the current management. Four scenarios were created to investigate which changes in the breeding scheme would have the largest effect on the survival probabilities, including Scenario 1: More females in the breeding pool, scenario 2: More males in the breeding pool, scenario 3: Increased carrying capacity, and scenario 4: Supplementing males to the population through artificial insemination using semen from bulls used in the populations in past generations. All scenarios showed a positive effect on the population's probability of survival, and with a combination of the different scenarios, the population size seems to be stabilized.
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39

武, 祥伟. "A Preliminary Analysis on Population Viability for Triplophysa venusta." Open Journal of Fisheries Research 02, no. 03 (2015): 31–41. http://dx.doi.org/10.12677/ojfr.2015.23004.

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40

Hernández-Camacho, CJ, and AW Trites. "Population viability analysis of Guadalupe fur seals Arctocephalus townsendi." Endangered Species Research 37 (December 13, 2018): 255–67. http://dx.doi.org/10.3354/esr00925.

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41

Lacy, RC. "VORTEX: a computer simulation model for population viability analysis." Wildlife Research 20, no. 1 (1993): 45. http://dx.doi.org/10.1071/wr9930045.

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Population Viability Analysis (PVA) is the estimation of extinction probabilities by analyses that incorporate identifiable threats to population survival into models of the extinction process. Extrinsic forces, such as habitat loss, over-harvesting, and competition or predation by introduced species, often lead to population decline. Although the traditional methods of wildlife ecology can reveal such deterministic trends, random fluctuations that increase as populations become smaller can lead to extinction even of populations that have, on average, positive population growth when below carrying capacity. Computer simulation modelling provides a tool for exploring the viability of populations subjected to many complex, interacting deterministic and random processes. One such simulation model, VORTEX, has been used extensively by the Captive Breeding Specialist Group (Species Survival Commission, IUCN), by wildlife agencies, and by university classes. The algorithms, structure, assumptions and applications of VORTEX are described in this paper. VORTEX models population processes as discrete, sequential events, with probabilistic outcomes. VORTEX simulates birth and death processes and the transmission of genes through the generations by generating random numbers to determine whether each animal lives or dies, to determine the number of progeny produced by each female each year, and to determine which of the two alleles at a genetic locus are transmitted from each parent to each offspring. Fecundity is assumed to be independent of age after an animal reaches reproductive age. Mortality rates are specified for each pre-reproductive age-sex class and for reproductive-age animals. Inbreeding depression is modelled as a decrease in viability in inbred animals. The user has the option of modelling density dependence in reproductive rates. As a simple model of density dependence in survival, a carrying capacity is imposed by a probabilistic truncation of each age class if the population size exceeds the specified carrying capacity. VORTEX can model linear trends in the carrying capacity. VORTEX models environmental variation by sampling birth rates, death rates, and the carrying capacity from binomial or normal distributions. Catastrophes are modelled as sporadic random events that reduce survival and reproduction for one year. VORTEX also allows the user to supplement or harvest the population, and multiple subpopulations can be tracked, with user-specified migration among the units. VORTEX outputs summary statistics on population growth rates, the probability of population extinction, the time to extinction, and the mean size and genetic variation in extant populations. VORTEX necessarily makes many assumptions. The model it incorporates is most applicable to species with low fecundity and long lifespans, such as mammals, birds and reptiles. It integrates the interacting effects of many of the deterministic and stochastic processes that have an impact on the viability of small populations, providing opportunity for more complete analysis than is possible by other techniques. PVA by simulation modelling is an important tool for identifying populations at risk of extinction, determining the urgency of action, and evaluating options for management.
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42

Brook, Barry W., Julian J. O'Grady, Andrew P. Chapman, Mark A. Burgman, H. Resit Akçakaya, and Richard Frankham. "Predictive accuracy of population viability analysis in conservation biology." Nature 404, no. 6776 (March 2000): 385–87. http://dx.doi.org/10.1038/35006050.

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43

King, Richard B., Callie K. Golba, Gary A. Glowacki, and Andrew R. Kuhns. "Blanding's Turtle Demography and Population Viability." Journal of Fish and Wildlife Management 12, no. 1 (April 1, 2021): 112–38. http://dx.doi.org/10.3996/jfwm-20-063.

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Abstract In anticipation of U.S. federal status classification (warranted, warranted but precluded, not warranted), scheduled for 2023, we provide population viability analysis of the Blanding's turtle Emydoidea blandingii, a long-lived, late-maturing, semi-aquatic species of conservation concern throughout its range. We present demographic data from long-term study of a population in northeastern Illinois and use these data as the basis for viability and sensitivity analyses focused on parameter uncertainty and geographic parameter variation. We use population viability analysis to identify population sizes necessary to provide population resiliency to stochastic disturbance events and catastrophes, and demonstrate how alternative definitions of ‘foreseeable future' might affect status decisions. Demographic parameters within our focal population resulted in optimistic population projections (probability of extinction = 0% over 100 y) but results were less optimistic when catastrophes or uncertainty in parameter estimates were incorporated (probability of extinction = 3% and 16%, respectively). Uncertainty in estimates of age-specific mortality had the biggest impact on population viability analysis outcomes but uncertainty in other parameters (age of first reproduction, environmental variation in age-specific mortality, percent of females reproducing, clutch size) also contributed. Blanding's turtle demography varies geographically and incorporating this variation resulted in both mortality- and fecundity-related parameters affecting population viability analysis outcomes. Possibly, compensatory variation among demographic parameters allows for persistence across a wide range of parameter values. We found that extinction risk decreased and retention of genetic diversity increased rapidly with increasing initial population size. In the absence of catastrophes, demographic conservation goals could be met with a smaller initial population size than could genetic conservation goals; ≥20–50 adults were necessary for extinction risk &lt;5%, whereas ≥50–110 adults were necessary to retain &gt;95% of existing genetic diversity over 100 y. These thresholds shifted upward when catastrophes were included; ≥50–200 adults were necessary for extinction risk &lt;5% and ≥110 to &gt;200 adults were necessary to retain &gt;95% of existing genetic diversity over 100 y. Impediments to Blanding's turtle conservation include an incomplete understanding of geographic covariation among demographic parameters, the large amount of effort necessary to estimate and monitor abundance, and uncertainty regarding the impacts of increasingly frequent extreme weather events.
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44

Lee, Sang-Don. "Long-term population monitoring with population viability analysis of river otter in Korea." Journal of Environmental Impact Assessment 22, no. 5 (October 31, 2013): 525–28. http://dx.doi.org/10.14249/eia.2013.22.5.525.

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45

LaMontagne, Jalene M., Robyn L. Irvine, and Elizabeth E. Crone. "Spatial patterns of population regulation in sage grouse (Centrocercus spp.) population viability analysis." Journal of Animal Ecology 71, no. 4 (July 2002): 672–82. http://dx.doi.org/10.1046/j.1365-2656.2002.00629.x.

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46

Thirstrup, J. P., L. A. Bach, V. Loeschcke, and C. Pertoldi. "Population viability analysis on domestic horse breeds (Equus caballus)1." Journal of Animal Science 87, no. 11 (November 1, 2009): 3525–35. http://dx.doi.org/10.2527/jas.2008-1760.

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47

Bocetti, Carol I. "New Book Evaluates Population Viability Analysis as a Conservation Tool." Ecology 84, no. 2 (February 2003): 536–37. http://dx.doi.org/10.1890/0012-9658(2003)084[0536:nbepva]2.0.co;2.

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48

Al-Atiyat, Raed M. "Extinction probabilities of Jordan indigenous cattle using population viability analysis." Livestock Science 123, no. 2-3 (August 2009): 121–28. http://dx.doi.org/10.1016/j.livsci.2008.10.016.

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49

Armstrong, E., A. Postiglioni, and S. González. "Population viability analysis of the Uruguayan Creole cattle genetic reserve." Animal Genetic Resources Information 38 (April 2006): 19–33. http://dx.doi.org/10.1017/s1014233900002029.

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SummaryUruguayan Creole cattle are descended from animals brought by the Spanish conquerors. The population grew extensively without directional management and became semi-wild before the introduction of commercial breeds in the 19th century. Today only 575 animals remain, restricted to the San Miguel National Park. We performed a population viability analysis of this reserve using VORTEX v. 8.31 to study its demographic and genetic parameters, assess the environmental factors that affect its development, evaluate its future risk of extinction and test different management options. The probability of extinction in the next 100 years was always zero, even in the more pessimistic scenarios. The growth rate of the population was always positive and mostly affected by the mortality rate of calves. Population size increased rapidly up to carrying capacity, this being the only limiting factor for population growth. Retained heterozygosity was always above 90% and the inbreeding coefficient below 0.10. The analysis shows that the population is not at risk due to its genetic diversity and demographic structure, however all the individuals are concentrated in only one place. We suggest its subdivision into sub-populations located in different regions and connected by gene flow, decreasing the risk of extinction and accomplishing the conservation and self-sustainability goals.
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50

Jager, Henriëtte I., Ken Lepla, James Chandler, Phil Bates, and Webb Van Winkle. "Population viability analysis of white sturgeon and other riverine fishes." Environmental Science & Policy 3 (September 2000): 483–89. http://dx.doi.org/10.1016/s1462-9011(00)00063-0.

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