|Título||A new method to quantify and compare the multiple components of fitness--a study case with kelp niche partition by divergent microstage adaptations to temperature.|
|Publication Type||Journal Article|
|Authors||Vieira, V, Oppliger, LValeria, Engelen, AH, Correa, JA|
|Year of Publication||2015|
|Palavras-chave||Adaptation, Physiological, Algorithms, Biomass, Ecosystem, Genetic Fitness, Hot Temperature, Laminaria, Models, Biological, Spores|
POINT 1: Management of crops, commercialized or protected species, plagues or life-cycle evolution are subjects requiring comparisons among different demographic strategies. The simpler methods fail in relating changes in vital rates with changes in population viability whereas more complex methods lack accuracy by neglecting interactions among vital rates.POINT 2: The difference between the fitness (evaluated by the population growth rate λ) of two alternative demographies is decomposed into the contributions of the differences between the pair-wised vital rates and their interactions. This is achieved through a full Taylor expansion (i.e. remainder = 0) of the demographic model. The significance of each term is determined by permutation tests under the null hypothesis that all demographies come from the same pool.POINT 3: An example is given with periodic demographic matrices of the microscopic haploid phase of two kelp cryptic species observed to partition their niche occupation along the Chilean coast. The method provided clear and synthetic results showing conditional differentiation of reproduction is an important driver for their differences in fitness along the latitudinal temperature gradient. But it also demonstrated that interactions among vital rates cannot be neglected as they compose a significant part of the differences between demographies.POINT 4: This method allows researchers to access the effects of multiple effective changes in a life-cycle from only two experiments. Evolutionists can determine with confidence the effective causes for changes in fitness whereas population managers can determine best strategies from simpler experimental designs.
|Alternate Journal||PLoS ONE|
|PubMed Central ID||PMC4379098|