Giraffe translocation population viability analysis

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 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

Hierarchical multi-population viability analysis

Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long-term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi-population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub-models. We present a case study in which we customized this model for historical population monitoring data (1985-2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi-pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical multi-population viability analysis bridges the gap between site-level field observations and population-level processes, making effective use of existing datasets to support management decisions with robust estimates of population dynamics, extinction risks, and uncertainties

A vortex population viability analysis model for the Chacoan peccary (catagonus wagneri)

El quimilero o taguá (Catagonus wagneri) es una especie amenazada, endémica del Chaco Seco, para la cual disponemos de poca información. Para estimar cuantitativamente el riesgo de disminución y extinción de sus poblaciones silvestres generamos modelos de viabilidad poblacional. Con estos modelos matemáticos se pueden identificar factores naturales y antrópicos complejos que interactúan y que influyen en la persistencia y la salud de una población. Los modelos también se pueden utilizar para evaluar los efectos de diferentes estrategias de gestión, permitiendo identificar las acciones de conservación más efectivas para una población o especie. Además, estos modelos se pueden usar para identificar las necesidades de investigación debido a que ponen en evidencia los vacíos de información sobre la especie. Utilizando estos modelos, evaluamos la proyección poblacional en las condiciones actuales y en comparación con posibles variaciones existentes en el sistema. Para generar los parámetros ingresados en los modelos realizamos una reunión de especialistas y una revisión bibliográfica. Trabajó con valores de línea de base (base), mínimos (mín.) y máximos (máx.). Generamos diferentes modelos ante diferentes escenarios y testeamos la sensibilidad a la incertidumbre de cada modelo. Esto permitió establecer prioridades de investigación. Además, determinamos los tamaños mínimos de población viable considerando la incertidumbre y analizamos los posibles efectos de la caza en una población de esta especie.Fil: Leus, Kritin. International Union for Conservation of Nature. Species Survival Commission; DinamarcaFil: Altrichter, Mariana. International Union for Conservation of Nature. Species Survival Commission; Estados UnidosFil: Desbiez, Arnaud. International Union for Conservation of Nature. Species Survival Commission; BrasilFil: Camino, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Giordano, Anthony J.. S.P.E.C.I.E.S.; Estados UnidosFil: Campos Krauer, Juan Manuel. University of Florida. Department of Wildlife Ecology and Conservation; Estados Unidos. Centro Chaqueño para la Conservación y la Investigación; ParaguayFil: Brooks, Daniel M.. Houston Museum Of Natural Science; Estados UnidosFil: Thompson, Jeffrey. Consejo Nacional de Ciencia y Tecnología; ParaguayFil: Núñez Regueiro, Mauricio Manuel. University of Florida. Department of Wildlife Ecology and Conservation; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

A comparison of population viability measures

The viability of populations can be quantified with several measures, such as the probability of extinction, the mean time to extinction, or the population size. While conservation management decisions can be based on these measures, it has not yet been explored systematically if different viability measures rank species and scenarios similarly and if one viability measure can be converted into another to compare studies. To address this challenge, we conducted a quantitative comparison of eight viability measures based on the simulated population dynamics of more than 4500 virtual species. We compared (a) the ranking of scenarios based on different viability measures, (b) assessed direct correlations between the measures, and (c) explored if parameters in the simulation models can alter the relationship between pairs of viability measures. We found that viability measures ranked species similarly. Despite this, direct correlations between the different measures were often weak and could not be generalized. This can be explained by the loss of information due to the aggregation of raw data into a single number, the effect of model parameters on the relationship between viability measures, and because distributions, such as the probability of extinction over time, cannot be ranked objectively. Similar scenario rankings by different viability measures show that the choice of the viability metric does in many cases not alter which population is regarded more viable or which management option is the best. However, the more two scenarios or populations differ, the more likely it becomes that different measures produce different rankings. We thus recommend that PVA studies publish raw simulation data, which not only describes all risks and opportunities to the reader but also facilitates meta-analyses of PVA studies

Sustainability, optimality, and viability in the Ramsey model

The Ramsey model of economic growth is revisited from the point of view of viability. A viable state is a state from which there exists at least one tra jectory that remains in the set of constraints of minimal consumption and positive wealth. Viability is presented with a constraint of minimal consumption, then with an additional criterion of economic sustainability. The comparison of viability kernels with or without sustainability shows how much consumption should be reduced and when. The viable-optimal solution in the sense of inter-temporal consumption is obtained on the viability boundary of an auxiliary system. Technological progress works against population growth to favor the possibility for a given state of being viable or viable-sustainable.viability theory, optimization, sustainability, Ramsey model

Environmental factors influence both abundance and genetic diversity in a widespread bird species.

Genetic diversity is one of the key evolutionary variables that correlate with population size, being of critical importance for population viability and the persistence of species. Genetic diversity can also have important ecological consequences within populations, and in turn, ecological factors may drive patterns of genetic diversity. However, the relationship between the genetic diversity of a population and how this interacts with ecological processes has so far only been investigated in a few studies. Here, we investigate the link between ecological factors, local population size, and allelic diversity, using a field study of a common bird species, the house sparrow (Passer domesticus). We studied sparrows outside the breeding season in a confined small valley dominated by dispersed farms and small-scale agriculture in southern France. Population surveys at 36 locations revealed that sparrows were more abundant in locations with high food availability. We then captured and genotyped 891 house sparrows at 10 microsatellite loci from a subset of these locations (N = 12). Population genetic analyses revealed weak genetic structure, where each locality represented a distinct substructure within the study area. We found that food availability was the main factor among others tested to influence the genetic structure between locations. These results suggest that ecological factors can have strong impacts on both population size per se and intrapopulation genetic variation even at a small scale. On a more general level, our data indicate that a patchy environment and low dispersal rate can result in fine-scale patterns of genetic diversity. Given the importance of genetic diversity for population viability, combining ecological and genetic data can help to identify factors limiting population size and determine the conservation potential of populations

Demographic viability of populations of \u3cem\u3eSilene regis\u3c/em\u3e in midwestern prairies: relationships with fire management, genetic variation, geographic location, population size and isolation

We studied the demographic viability of populations of a long-lived iteroparous prairie perennial, Silene regia, in relation to management regimes, population sizes, geographical region (Ohio and Indiana vs. Missouri and Arkansas), degree of isolation and amount of genetic variation. Demographic data were collected from 16 populations for up to 7 years. This species has high survivorship, slow growth, frequent flowering and episodic seedling recruitment. Matrix projection methods were used to summarize population performance with and without recruitment. Median finite rates of increase by population varied from 0.57 to 1.82 and from 0.44 to 0.99, respectively. Populations with the highest rates of increase had been burned. Six of eight populations, for which stochastic modelling predicted persistence for 1000 years, included fire in their management. None of the five populations with predicted 100-year extinction probabilities of 100% was managed for conservation or burned. An intermediate group of three populations with at least 10% probability of extinction between 100 and 1000 years was not managed, but was none the less kept open by mowing and herbicide application. Analysis of composite elasticities showed that growth and fecundity terms were higher for growing (vs. declining) populations and that growth elasticity was higher in burned than unburned populations. Lack of burning shifts the elasticity spectrum from that typical of open habitat herbs (higher growth and fecundity elasticities) to values usually found for closed habitat herbs (higher survival elasticities). In multivariate analyses predicting finite rates of increase (with and without recruitment), fire management and region were the strongest predictors, followed by genetic variation, population size, isolation and interactions of population size and fire, and region and fire. Populations with the highest rates of increase were burned, eastern, more genetically diverse, larger and less isolated. Discrimination of populations with different extinction risks (three classes) was related mainly to fire, genetic variation and region. Most of these conclusions support conservation biology predictions that population viability will be highest in larger, less-isolated, more genetically diverse populations. However, management and geographic trends have overriding roles affecting demographic viability. Habitat fragmentation and genetic depletion have the potential to threaten residual prairie populations of S. regia, but lack of fire management appears to be the primary short-term threat

Reintroduction of North Island robins to Paengaroa Scenic Reserve : factors limiting survival, nest success, and population viability in a mainland restoration area : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Ecology at Massey University

Forty North Island robins (Petroica australis longipes) were reintroduced to Paengaroa Scenic Reserve in March 1999. I monitored the survival and breeding success of this population for two years post-release. This study aims to assess survival, nest success, and population viability of robins in Paengaroa in an attempt to discover whether habitat in the reserve is likely to support a population of robins. Survival from the time of release to the start of the first breeding season was lower at Paengaroa than at two other release sites, Boundary Stream Scenic Reserve and Tiritiri Matangi Island. This may be due to higher predator levels at Paengaroa or dispersal out of the reserve. Methods of estimating nest success were compared, and Stanley's (2000) method was found to have advantages over the traditional and Mayfield methods. Daily survival rates of nests at Paengaroa depended on both the stage in the nesting cycle and stage of the breeding season, with the survival rate lowest for early nests at the incubation stage. Nest success for the first two breeding seasons after translocation was compared to that for the first two seasons after release at Tiritiri Matangi and Boundary Stream. Paengaroa had a similar nest success rate to Tiritiri Matangi (25% and 26% respectively), and both of these sites had lower nest success than Boundary Stream (47%). Survival at Paengaroa was most affected by whether a bird was recently-translocated. a juvenile, or an adult. Recently-translocated birds and juveniles suffered similarly low survival rates, suggesting that this high mortality may be due to problems faced when finding and establishing a territory. The survival of juveniles from January to September was estimated to be 29%. The annual adult survival rate was also low (59%). Fecundity and survival estimates were used in a stochastic simulation model to predict the viability of the Paengaroa population. Under current conditions, the population was predicted to have a 17% probability of surviving 10 years. However, variation of parameters to lower and upper 95% confidence limits gave survival probabilities of 0% to 100% over 10 years. When data from the first year after translocation were excluded, the population was predicted to have a 100% probability of surviving 100 years. These results demonstrate the large uncertainly associated with small sample sizes and short-term studies. To assess whether habitat quality is likely to account for the poor overall viability predicted at Paengaroa, the habitat quality at Paengaroa was compared to that at Waimarino forest, where robins still persist. Food supply and predator levels were used to assess habitat quality, as these are obvious factors that may limit viability. Data on food and predator levels provided no indication of why robins may be non-viable at Paengaroa. The power of statistical tests was low due to small sample size, but results suggest Paengaroa has more food as well as fewer rats and stoats than Waimarino. There is a need for further research to improve our understanding of why robins are present and common in some mainland areas but have disappeared from others without any obvious difference in habitat quality. Continued research is also required to reduce the uncertainty regarding population viability at Paengaroa and to determine whether improved management is needed

Will Social Security and Medicare Remain Viable as the U.S. Population is Aging? An Update

Yes, subject to concerns about Medicare inefficiencies and potentially self-confirming skepticism. The U.S. social security system-broadly defined to include Medicare-faces significant financial problems as the result of an aging population. But demographic change is also likely to raise savings, increase wages, and reduce interest rates, and up to a point, a growing GDP-share of medical spending is an efficient response to an aging population. Thus viability is more a political economy than an economic feasibility issue. To examine the political viability of social security, I focus on intertemporal cost-benefit tradeoffs in a median voter setting. For a variety of assumptions and policy alternatives, I find that social security should retain majority support.