Population viability analysis (PVA) has been used for three decades to assess threats and evaluate conservation options for wildlife populations. What has been learned from PVA on in situ populations ...are valuable lessons also for assessing and managing viability and sustainability of ex situ populations. The dynamics of individual populations are unpredictable, due to limited knowledge about important factors, variability in the environment, and the probabilistic nature of demographic events. PVA considers such uncertainty within simulations that generate the distribution of likely fates for a population; management of ex situ populations should also take into consideration the uncertainty in our data and in the trajectories of populations. The processes affecting wildlife populations interact, with feedbacks often leading to amplified threats to viability; projections of ex situ populations should include such feedbacks to allow for management that foresees and responds to the cumulative and synergistic threats. PVA is useful for evaluating conservation options only if the goals for each population and measures of success are first clearly identified; similarly, for ex situ populations to contribute maximally to species conservation, the purposes for the population and definitions of sustainability in terms of acceptable risk must be documented. PVA requires a lot of data, knowledge of many processes affecting the populations, modeling expertize, and understanding of management goals and constraints. Therefore, to be useful in guiding conservation it must be a collaborative, trans‐disciplinary, and social process. PVA can help integrate management of in situ and ex situ populations within comprehensive species conservation plans.
Thousands of small populations are at increased risk of extinction because genetics and evolutionary biology are not well‐integrated into conservation planning–a major lost opportunity for effective ...actions. We propose that if the risk of outbreeding depression is low, the default should be to evaluate restoration of gene flow to small inbred populations of diploid outbreeding organisms that were isolated by human activities within the last 500 years, rather than inaction. We outline the elements of a scientific‐based genetic management policy for fragmented populations of plants and animals, and discuss the reasons why the current default policy is, inappropriately, inaction.
Fragmentation of animal and plant populations typically leads to genetic erosion and increased probability of extirpation. Although these effects can usually be reversed by re-establishing gene flow ...between population fragments, managers sometimes fail to do so due to fears of outbreeding depression (OD). Rapid development of OD is due primarily to adaptive differentiation from selection or fixation of chromosomal variants. Fixed chromosomal variants can be detected empirically. We used an extended form of the breeders' equation to predict the probability of OD due to adaptive differentiation between recently isolated population fragments as a function of intensity of selection, genetic diversity, effective population sizes, and generations of isolation. Empirical data indicated that populations in similar environments had not developed OD even after thousands of generations of isolation. To predict the probability of OD, we developed a decision tree that was based on the four variables from the breeders' equation, taxonomic status, and gene flow within the last 500 years. The predicted probability of OD in crosses between two populations is elevated when the populations have at least one of the following characteristics: are distinct species, have fixed chromosomal differences, exchanged no genes in the last 500 years, or inhabit different environments. Conversely, the predicted probability of OD in crosses between two populations of the same species is low for populations with the same karyotype, isolated for <500 years, and that occupy similar environments. In the former case, we recommend crossing be avoided or tried on a limited, experimental basis. In the latter case, crossing can be carried out with low probability of OD. We used crosses with known results to test the decision tree and found that it correctly identified cases where OD occurred. Current concerns about OD in recently fragmented populations are almost certainly excessive. La fragmentación de poblaciones animales y vegetales típicamente lleva a la erosión genética y al incremento de la probabilidad de extirpación. Aunque estos efectos generalmente se pueden revertir mediante el restablecimiento del flujo genético entre los fragmentos de poblaciones, los manejadores a veces fallan debido al temor a la depresión exogámica (DEX). El rápido desarrollo de la DEX se debe principalmente a la diferenciación adaptativa de la selección o fijación de variantes cromosómicas. Las variantes cromosómicas fijadas pueden ser detectadas empíricamente. Utilizamos una forma extendida de la ecuación de criadores para predecir la probabilidad de DEX debido a la diferenciación adaptativa entre fragmentos de poblaciones aisladas recientemente como una función de la intensidad de selección, la diversidad genética, el tamaño poblacional efectivo y las generaciones en aislamiento. Los datos empíricos indicaron que poblaciones en ambientes similares no habían desarrollado DEX aun después de mil generaciones en aislamiento. Para predecir la probabilidad de DEX, desarrollamos un árbol dedecisiones basado en las 4 variables de la ecuación de criadores, el estatus taxonómico y el flujo génico durante los últimos 500 años. La probabilidad predicha de DEX es alta en cruzas entre dos poblaciones cuando las poblaciones tienen por lo menos una de las siguientes características: son especies diferentes, tienen diferencias en cromosomas fijados, no intercambiaron genes durante los últimos 500 años o habitan en ambientes diferentes. Por el contrario, la probabilidad predicha de DEX es baja en cruzas entre dos poblacionesde la misma especie cuando las poblaciones tienen el mismo cariotipo, han estado aisladas por <500 años y ocupan ambientes similares. En el primer caso, recomendamos evitar la cruza o probarla en un nivel limitado, experimental. En el segundo caso, la cruza puede llevarse a cabo con baja probabilidad de DEX. Utilizamos cruzas con resultados conocidos para probar el árbol de decisiones y encontramos que este identifico casos correctamente cuando ocurrió DEX. Las preocupaciones actuales sobre DEX en poblaciones fragmentadas recientemente con toda seguridad son excesivas.
Proxy measures of genome-wide heterozygosity based on approximately 10 microsatellites have been used to uncover heterozygosity fitness correlations (HFCs) for a wealth of important fitness traits in ...natural populations. However, effect sizes are typically very small and the underlying mechanisms remain contentious, as a handful of markers usually provides little power to detect inbreeding. We therefore used restriction site associated DNA (RAD) sequencing to accurately estimate genome-wide heterozygosity, an approach transferrable to any organism. As a proof of concept, we first RAD sequenced oldfield mice (Peromyscus polionotus) from a known pedigree, finding strong concordance between the inbreeding coefficient and heterozygosity measured at 13,198 single-nucleotide polymorphisms (SNPs). When applied to a natural population of harbor seals (Phoca vitulina), a weak HFC for parasite infection based on 27 microsatellites strengthened considerably with 14,585 SNPs, the deviance explained by heterozygosity increasing almost fivefold to a remarkable 49%. These findings arguably provide the strongest evidence to date of an HFC being due to inbreeding depression in a natural population lacking a pedigree. They also suggest that under some circumstances heterozygosity may explain far more variation in fitness than previously envisaged.
Many wildlife species are propagated in captivity as models for behavioral, physiological, and genetic research or to provide assurance populations to protect threatened species. However, very little ...is known about how animals evolve in the novel environment of captivity. The histories of most laboratory strains are poorly documented, and protected populations of wildlife species are usually too small and too short-term to allow robust statistical analysis. To document the evolutionary change in captive breeding programs, we monitored reproduction and behavior across 18 generations in six experimental populations of Peromyscusleucopus mice started from a common set of 20 wild-caught founders. The mice were propagated under three breeding protocols: a strategy to retain maximal genetic diversity, artificial selection against stereotypic behaviors that were hypothesized to reflect poor adaptation to captivity, and random bred controls. Two replicates were maintained with each protocol, and inter-replicate crosses at generations 19 and 20 were used to reverse accumulated inbreeding. We found that one of the stereotypic behaviors (repetitive flipping) was positively associated with reproductive fitness, while the other (gnawing) was relatively invariant. Selection to reduce these stereotypic behaviors caused marked reduction in reproduction, and populations not under artificial selection to reduce these behaviors responded with large increases in flipping. In non-selected populations, there was rapid evolution toward much higher proportion of pairs breeding and more rapid conception. Litter size, pup survival, and weaning mass all declined slowly, to the extent that would be predicted based on inbreeding depression. Inter-crossing between replicate populations reversed these declines in fitness components but did not reverse the changes in behavior or the accelerated breeding. These findings indicate that adaptation to captivity can be rapid, affecting reproductive patterns and behaviors, even under breeding protocols designed to minimize the rate of genetic change due to random drift and inadvertent selection.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
1. Sensitivity analyses that assess the impact of changing vital rates on population growth have been widely used to guide conservation. If implemented with caution, they can provide guidance as to ...which management actions will optimize conservation outcomes. 2. In this review, we first focus on the commonly used proportional sensitivity and elasticity analyses that change each vital rate by equal proportions, to assess their importance for wildlife management. These types of analyses also feature potential pitfalls and limitations, including (1) Each vital rate is usually on a different scale. Without appropriate scaling this can result in a flawed evaluation of the importance of vital rates. (2) Vital rates rarely change at equal proportions in nature. This can bring about misguided management recommendations on the basis of vital rate changes that are unrealistic. (3) Proportional sensitivity analyses often do not reflect the feasibility and effectiveness of altering particular demographic parameters. Consequently, relying solely on proportional sensitivities or elasticities can lead to flawed evaluation of the importance of vital rates and thus prioritization of management options that are unrealistic or ineffective. 3. We outline alternative approaches, which involve assessing the impact of threats, the relative demography of stable and declining populations, the effect of observable variation of vital rates on population viability, and the potential effects of feasible management scenarios. 4. Synthesis and applications. Sensitivity analyses are useful tools to guide wildlife management. If implemented and interpreted with care, sensitivity analyses can identify key demographic parameters and threats to population viability. However, their usefulness is limited, when applied without careful evaluation as to whether the perturbations evaluated are realistic, feasible and meet the need of wildlife managers. We caution against the over-reliance on proportional sensitivity and elasticity analyses and point to alternative approaches, including life-stage simulation analysis, vital rate sensitivity analysis or manual perturbations.
Captive breeding programs are often initiated to prevent species extinction until reintroduction into the wild can occur. However, the evolution of captive populations via inbreeding, drift, and ...selection can impair fitness, compromising reintroduction programs. To better understand the evolutionary response of species bred in captivity, we used nearly 5500 single nucleotide polymorphisms (SNPs) in populations of white-footed mice (Peromyscus leucopus) to measure the impact of breeding regimes on genomic diversity. We bred mice in captivity for 20 generations using two replicates of three protocols: random mating (RAN), selection for docile behaviors (DOC), and minimizing mean kinship (MK). The MK protocol most effectively retained genomic diversity and reduced the effects of selection. Additionally, genomic diversity was significantly related to fitness, as assessed with pedigrees and SNPs supported with genomic sequence data. Because captive-born individuals are often less fit in wild settings compared to wild-born individuals, captive-estimated fitness correlations likely underestimate the effects in wild populations. Therefore, minimizing inbreeding and selection in captive populations is critical to increasing the probability of releasing fit individuals into the wild.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The goal of captive breeding programmes is often to maintain genetic diversity until re‐introductions can occur. However, due in part to changes that occur in captive populations, approximately ...one‐third of re‐introductions fail. We evaluated genetic changes in captive populations using microsatellites and mtDNA. We analysed six populations of white‐footed mice that were propagated for 20 generations using two replicates of three protocols: random mating (RAN), minimizing mean kinship (MK) and selection for docility (DOC). We found that MK resulted in the slowest loss of microsatellite genetic diversity compared to RAN and DOC. However, the loss of mtDNA haplotypes was not consistent among replicate lines. We compared our empirical data to simulated data and found no evidence of selection. Our results suggest that although the effects of drift may not be fully mitigated, MK reduces the loss of alleles due to inbreeding more effectively than random mating or docility selection. Therefore, MK should be preferred for captive breeding. Furthermore, our simulations show that incorporating microsatellite data into the MK framework reduced the magnitude of drift, which may have applications in long‐term or extremely genetically depauperate captive populations.
Summary
Applied ecologists continually advocate further research, under the assumption that obtaining more information will lead to better decisions. Value of information (VoI) analysis can be used ...to quantify how additional information may improve management outcomes: despite its potential, this method is still underused in environmental decision‐making. We provide a primer on how to calculate the VoI and assess whether reducing uncertainty will change a decision. Our aim is to facilitate the application of VoI by managers who are not familiar with decision‐analytic principles and notation, by increasing the technical accessibility of the tool.
Calculating the VoI requires explicit formulation of management objectives and actions. Uncertainty must be clearly structured and its effects on management outcomes evaluated. We present two measures of the VoI. The expected value of perfect information is a calculation of the expected improvement in management outcomes that would result from access to perfect knowledge. The expected value of sample information calculates the improvement in outcomes expected by collecting a given sample of new data.
We guide readers through the calculation of VoI using two case studies: (i) testing for disease when managing a frog species and (ii) learning about demographic rates for the reintroduction of an endangered turtle. We illustrate the use of Bayesian updating to incorporate new information.
The VoI depends on our current knowledge, the quality of the information collected and the expected outcomes of the available management actions. Collecting information can require significant investments of resources; VoI analysis assists managers in deciding whether these investments are justified.
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