Relevance of Life-History Parameter Estimation to Conservation Listing: Case of the Sharp-tailed Snake (Contia tenuis)

2011 ◽  
Vol 45 (3) ◽  
pp. 300-307 ◽  
Author(s):  
Purnima Govindarajulu ◽  
Leigh Anne Isaac ◽  
Christian Engelstoft ◽  
Kristiina Ovaska
Keyword(s):  
Parameter Estimation ◽  
Life History ◽  
Life History Parameter

Testing life history predictions in a long-lived seabird: a population matrix approach with improved parameter estimation

Oikos ◽  
2004 ◽  
Vol 105 (3) ◽  
pp. 606-618 ◽  
Author(s):  
P. F. Doherty, Jr. ◽  
E. A. Schreiber ◽  
J. D. Nichols ◽  
J. E. Hines ◽  
W. A. Link ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Life History ◽  
Matrix Approach ◽  
Population Matrix

scholarly journals Ensemble models for data-poor assessment: accounting for uncertainty in life-history information

2019 ◽  
Vol 76 (4) ◽  
pp. 870-883 ◽  
Author(s):  
Merrill B Rudd ◽  
James T Thorson ◽  
Skyler R Sagarese
Keyword(s):  
Life History ◽  
Learning Algorithm ◽  
Stock Assessment ◽  
Model Averaging ◽  
Biological Information ◽  
Parameter Distribution ◽  
Life History Parameter ◽  
Multivariate Distributions ◽  
Life History Parameters ◽  
Parameter Values

Abstract Length measurements from fishery catch can be used in data-limited assessments to estimate important population parameters to guide management, but results are highly sensitive to assumptions about biological information. Ideally, local life history studies inform biological parameters. In the absence of reliable local estimates, scientists and managers face the difficult task of agreeing on fixed values for life-history parameters, often leading to additional uncertainty unquantified in the assessment or indecision defaulting to status-quo management. We propose an ensemble approach for incorporating life history uncertainty into data-limited stock assessments. We develop multivariate distributions of growth, mortality, and maturity parameter values, then use bivariate interpolation and stacking as an ensemble learning algorithm to propagate uncertainty into length-based, data-limited stock assessment models. Simulation testing demonstrated that stacking across life history parameter values leads to improved interval coverage over simple model averaging or assuming the parameter distribution means when the true life-history parameter values are unknown. We then applied the stacking approach for a U.S. Caribbean stock where the Scientific and Statistical Committee did not accept the assessment due to uncertainty in life history parameters. Stacking can better characterize uncertainty in stock status whenever life-history parameters are unknown but likely parameter distributions are available.

Brain evolution: A matter of constraints and permissions?

2001 ◽  
Vol 24 (2) ◽  
pp. 284-286
Author(s):  
Emmanuel Gilissen ◽  
Robert M.T. Simmons
Keyword(s):  
Life History ◽  
Brain Evolution ◽  
Life History Parameter ◽  
Brain Architecture ◽  
The Brain

The article of Finlay et al. is an excellent example of identifying constraints in the development of the brain, and their implications on brain architecture in evolution. Here we further illustrate the importance of constraints by presenting a few examples of how a small number of biophysical mechanisms or even a single life history parameter can have an enormous impact on brain evolution.

scholarly journals Intraspecific demography of the silky shark (Carcharhinus falciformis): implications for fisheries management

2019 ◽  
Author(s):  
Michael I Grant ◽  
Jonathan J Smart ◽  
Cassandra L Rigby ◽  
William T White ◽  
Andrew Chin ◽  
...  
Keyword(s):  
Life History ◽  
Fisheries Management ◽  
Life Stage ◽  
Leslie Matrix ◽  
Parameter Estimates ◽  
Shark Species ◽  
Life History Parameter ◽  
Silky Shark ◽  
Carcharhinus Falciformis ◽  
Management Approaches

Abstract The silky shark (Carcharhinus falciformis) is one of the most heavily fished tropical shark species globally, and currently there is increasing concern for its conservation status. However, large differences and ambiguity in life history parameter estimates among regions complicates its conservation and fisheries management. Using a Leslie matrix model that incorporated stochastic effects, we analysed the intraspecific demography of C. falciformis using available life history data from seven regions. Among regions, large differences were observed in generation time and age-specific reproductive contributions. Carcharhinus falciformis generally had low resilience to fishing mortality (F) throughout its distribution. Age-at-first-capture and age-at-last-capture management approaches resulted in substantial differences among regions. This was largely influenced by age-at-maturity. However, in scrutinizing some regional life history studies, it is likely that sampling design and methodological differences among regions have resulted in inaccuracies in life history parameter estimates and subsequent demographic attributes. This implies that age and life-stage-dependent management approaches using these possibly inaccurate life history parameters may be inappropriate. We suggest that a greater emphasis needs to be placed on eliminating human sources of error in elasmobranch life history studies to ensure management for wide-ranging species, such as C. falciformis, is most effective.

Interrelationships of factors of social development are more complex than Life History Theory predicts

2019 ◽  
Vol 42 ◽  
Author(s):  
Boris Kotchoubey
Keyword(s):  
Life History ◽  
Social Development ◽  
Life History Theory ◽  
Strong Correlations ◽  
Behavioral Features

Abstract Life History Theory (LHT) predicts a monotonous relationship between affluence and the rate of innovations and strong correlations within a cluster of behavioral features. Although both predictions can be true in specific cases, they are incorrect in general. Therefore, the author's explanations may be right, but they do not prove LHT and cannot be generalized to other apparently similar processes.

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