Sea ice cover and its influence on Adélie Penguin reproductive performance

The relationship between Adélie Penguins (Pygoscelis adeliae) and ice is well established, with sea ice influencing penguin populations through a variety of processes operating at different spatial and temporal scales. To further explain the relationship between sea ice and Adélie Penguin reproductive performance, we investigated the relative importance of various measures of sea ice cover on breeding success at Béchervaise Island, East Antarctica. Our results show a clear distinction in the response of penguins to different types of ice, as well as to the timing of the presence of sea ice. Nearshore sea ice, which is composed primarily of fast ice during the guard stage of the breeding season, had an overwhelmingly strong and negative impact on penguin reproductive performance. The influence of winter and offshore guard-stage ice was only evident in conjunction with nearshore ice. Predicting Adélie Penguin population growth in relation to changes in the sea ice environment may be complicated because penguin-ice interactions vary according to the type of sea ice present, the season in which it is present, and the processes contributing to population growth that are influenced by sea ice.     

Assessing competition between Steller sea lions and the commercial groundfishery in Alaska: A bioenergetics modelling approach

In the last three decades the western stock of the Steller sea lion (Eumetopias jubatus) has declined by more than 85%. Nutritional stress resulting in increased juvenile mortality is one of the leading hypotheses to account for this decline. Competition between Steller sea lions and the commercial groundfishery for walleye pollock (Theragra chalcogramma) has been proposed as a mechanism underlying the nutritional stress. In order to examine the competition component of the nutritional stress hypothesis, we developed a bioenergetics-based model to project the population trends of Steller sea lions under various scenarios of continued groundfish harvest. Annual energy budgets were calculated for the Gulf of Alaska population of Steller sea lions, and compared with projected available energy from walleye pollock under a variety of harvest scenarios. Model simulations produced 50-year Steller sea lion population projections consistent with current trends, as well as with published projections for stable and increasing populations from stable age distribution life table models. Model simulations were unable to produce energy deficits sufficient to account for the decline in Steller sea lions, but do suggest areas where existing data need supplementing.     

Life history consequences of variation in age at primiparity in northern elephant seals

Summary The age when female northern elephant seals, Mirounga angustirostris, bear their first young varies from 2 to 6 years. At Año Nuevo, California, a group of 77 females, primiparous at age 3, had a lower survivorship rate to each successive year up to age 8 than a group of 98 females that deferred initial pupping until age 4. The difference in survivorship appears to be due to the greater relative energetic costs of gestation and lactation incurred by the earlier breeding females during a period in their development when growth is rapid. An alternate hypothesis for the difference in survivorship — that young primiparous females are in poor condition from birth-is untenable; females that pupped early in life were larger at weaning age (a correlate of condition) than females that were primiparous 1 year later.Models based on the data show that differential survival of seals that vary in age at primiparity has important consequences for population growth and life history strategies. The effect of age at primiparity on the rate of increase of populations varies with colony density and juvenile survivorship. The optimal life history strategy for female elephant seals under most conditions existing today, including those at Ano Nuevo during the study period, is to bear the first offspring at age 4. Primiparity at age 3 is projected to be favored when harem density is very low and weaning success and juvenile survivorship are high; postponement of first breeding to age 5 is expected at high harem densities with intense competition for breeding space. Offprint requests to: B.J. Le Boeuf     

Spatially integrated assessment reveals widespread changes in penguin populations on the Antarctic Peninsula

As important marine mesopredators and sensitive indicators of Antarctic ecosystem change, penguins have been a major focus of long-term biological research in the Antarctic. However, the vast majority of such studies have been constrained by logistics and relate mostly to the temporal dynamics of individual breeding populations from which regional trends have been inferred, often without regard for the complex spatial heterogeneity of population processes and the underlying environmental conditions. Integrating diverse census data from 70 breeding sites across 31 years in a robust, hierarchical analysis, we find that trends from intensely studied populations may poorly reflect regional dynamics and confuse interpretation of environmental drivers. Results from integrated analyses confirm that Pygoscelis adeliae (Adélie Penguins) are decreasing at almost all locations on the Antarctic Peninsula. Results also resolve previously contradictory studies and unambiguously establish that P. antarctica (Chinstrap Penguins), thought to benefit from decreasing sea ice, are instead declining regionally. In contrast, another open-water species, P. papua (Gentoo Penguin), is increasing in abundance and expanding southward. These disparate population trends accord with recent mechanistic hypotheses of biological change in the Southern Ocean and highlight limitations of the influential but oversimplified "sea ice" hypothesis. Aggregating population data at the regional scale also allows us to quantify rates of regional population change in a way not previously possible.     

Trends in sea ice cover within habitats used by bowhead whales in the western Arctic.

We examined trends in sea ice cover between 1979 and 2002 in four months (March, June, September, and November) for four large (approximately 100,000 km2) and 12 small (approximately 10,000 km2) regions of the western Arctic in habitats used by bowhead whales (Balaena mysticetus). Variation in open water with year was significant in all months except March, but interactions between region and year were not. Open water increased in both large and small regions, but trends were weak with least-squares regression accounting for < or =34% of the total variation. In large regions, positive trends in open water were strongest in September. Linear fits were poor, however, even in the East Siberian, Chukchi, and Beaufort seas, where basin-scale analyses have emphasized dramatic sea ice loss. Small regions also showed weak positive trends in open water and strong interannual variability. Open water increased consistently in five small regions where bowhead whales have been observed feeding or where oceanographic models predict prey entrainment, including: (1) June, along the northern Chukotka coast, near Wrangel Island, and along the Beaufort slope; (2) September, near Wrangel Island, the Barrow Arc, and the Chukchi Borderland; and (3) November, along the Barrow Arc. Conversely, there was very little consistent change in sea ice cover in four small regions considered winter refugia for bowhead whales in the northern Bering Sea, nor in two small regions that include the primary springtime migration corridor in the Chukchi Sea. The effects of sea ice cover on bowhead whale prey availability are unknown but can be modeled via production and advection pathways. Our conceptual model suggests that reductions in sea ice cover will increase prey availability along both pathways for this population. This analysis elucidates the variability inherent in the western Arctic marine ecosystem at scales relevant to bowhead whales and contrasts basin-scale depictions of extreme sea ice retreats, thinning, and wind-driven movements.     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado     

The triple helix of Plantago lanceolata: genetics and the environment interact to determine population dynamics

The theory of evolution via natural selection predicts that the genetic composition of wild populations changes over time in response to the environment. Different genotypes should exhibit different demographic patterns, but genetic variation in demography is often impossible to separate from environmental variation. Here, we asked if genetic variation is important in determining demographic patterns. We answer this question using a long-term field experiment combined with general linear modeling of deterministic population growth rates (lambda), deterministic life table response experiment (LTRE) analysis, and stochastic simulation of demography by paternal lineage in a short-lived perennial plant, Plantago lanceolata, in which we replicated genotypes across four cohorts using a standard breeding design. General linear modeling showed that growth rate varied significantly with year, spatial block, and sire. In LTRE analysis of all cohorts, the strongest influences on growth rate were from year x spatial block, and cohort x year x spatial block interactions. In analysis of genetics vs. temporal environmental variation, the strongest impacts on growth rate were from year and year x sire. Finally, stochastic simulation suggested different genetic composition among cohorts after 100 years, and different population growth rates when genetic differences were accounted for than when they were not. We argue that genetic variation, genotype x environment interactions, natural selection, and cohort effects should be better integrated into population ecological studies, as these processes should result in deviations from projected deterministic and stochastic population parameters.     

Demographic Models and Reality in Reintroductions: Persian Fallow Deer in Israel

Abstract:  Because most reintroduced species are rare, data on their dynamics are scarce. Consequently, reintroduction programs often rely on data from other species or captive populations to project the performance of the reintroduced population in the wild. We compared the reproductive success and survival of a Persian fallow deer ( Dama mesopotamica ) population reintroduced in Israel over the first 5 years of the project with the survival and reproduction parameters estimated while planning the reintroduction. In addition, we compared the actual growth of the wild population with the growth originally projected by a computer model in the original reintroduction program. We monitored 74 radio-collared individuals (57 females and 17 males) released semiannually 1996–2001. Survival during the first year after release was lower than later years (0.90 and 0.82 versus 0.95 and 0.88, for females and males, respectively). Such an impact was not anticipated in the original plan, but overall survival was higher than originally projected. As assumed in the reintroduction program, reproductive success improved significantly with time since release and overall, was higher than expected. The mean number of animals released annually was lower than planned. Overall, the growth of the reintroduced population was slower than projected, but the deviation was close to confidence limits and the pattern similar. After 5 years it appears that the original time frame of 8–10 years for project completion can be met or at worst will cause a 1-year delay. Over the short term of 5 years, projection models in reintroduction programs are useful tools for assessing the sustained use of the breeding core, depicting the dynamics of the population in the wild, providing a relatively accurate time frame for the successful completion of the project, and assessing project success.     

How sensitive are elasticities of long-run stochastic growth to how environmental variability is modelled?

A variable environment leaves a signature in a population's dynamics. Deriving statistical and mathematical models of how environmental variability affects population projections has - in the wake of reports of substantial climatic fluctuations - received much recent attention. If the model changes, then so too does the population projection. This is because a different model of environmental variability changes estimates of long-run stochastic growth, which is a function of demographic rates and their temporal sequence. Decomposing elasticities of long-run stochastic growth into constituent parts can assess the relative influence of different components. Here, we investigate the consequences of changing the environmental state definition, and therefore altering the shape of demographic rate distributions and their temporal sequence, by using age-structured matrix models to project vertebrate populations into the future under a range of environmental scenarios. The identity of the most influential demographic rate was consistent among all approaches that perturbed only the mean, but was not when only the variance was perturbed. Furthermore, the influence of each demographic rate fluctuated among projections by up to factors of six and two for changes to the variance and mean, respectively. These changes in influence depend in part upon how environmental variability - in particular, the color of environmental noise - is incorporated. In the light of predictions of increasing climatic variability in the future, these results suggest caution when drawing quantitative conclusions from stochastic population projections.     

Use of local tidal records to identify relative sea level change: accuracy and error for decision makers

The Intergovernmental Panel on Climate Change (IPCC) considers eustatic sea level rise to be a major impact driven by climate change. Relative sea level change, whether positive or negative, will affect industries, communities and ecology along the world??s coastlines and estuaries. Estimates of global eustatic sea level rise between 1961 and 2003 are 1.8?±?0.5?mm a^?1, reflecting results from validated global tide gauge records. Over the last two decades, several studies have used automatic tide gauge records with at least 80?years of data to generate global prediction models. The IPCC recognises that global change is not uniform, therefore local policy for flood management and coastal protection should rely on local change models that incorporate glacio-isostatic adjustment (GIA) and apply accurate data correction techniques. Some of the longest tidal records are held within the Northern Hemisphere, e.g. Cascais, Amsterdam, Aberdeen, Sheerness and Newlyn. The UK provides several important case studies highlighting changes in relative sea level between the north and the south, primarily due to variations in GIA rates of land uplift and subsidence. Tide gauge records are held by a variety of governmental, non-governmental and private organisations. However, each source may typically compile data in different ways, relying on diverse equipment and recording techniques, often with variations in frequency, length, quality and corrections applied. Even within a single organisation there may be differences in dataset quality. This paper examines some of the key sources of error when working with historical tidal datasets in local geographic areas and aims to identify the limitations of locally derived data thereby assisting in the determination of relative sea level trends that are of widespread value to infrastructure and policy makers.     

Trophic structure of coastal Antarctic food webs associated with changes in sea ice and food supply

Predicting the dynamics of ecosystems requires an understanding of how trophic interactions respond to environmental change. In Antarctic marine ecosystems, food web dynamics are inextricably linked to sea ice conditions that affect the nature and magnitude of primary food sources available to higher trophic levels. Recent attention on the changing sea ice conditions in polar seas highlights the need to better understand how marine food webs respond to changes in such broad-scale environmental drivers. This study investigated the importance of sea ice and advected primary food sources to the structure of benthic food webs in coastal Antarctica. We compared the isotopic composition of several seafloor taxa (including primary producers and invertebrates with a variety of feeding modes) that are widely distributed in the Antarctic. We assessed shifts in the trophic role of numerically dominant benthic omnivores at five coastal Ross Sea locations. These locations vary in primary productivity and food availability, due to their different levels of sea ice cover, and proximity to polynyas and advected primary production. The delta15N signatures and isotope mixing model results for the bivalves Laternula elliptica and Adamussium colbecki and the urchin Sterechinus neumeyeri indicate a shift from consumption of a higher proportion of detritus at locations with more permanent sea ice in the south to more freshly produced algal material associated with proximity to ice-free water in the north and east. The detrital pathways utilized by many benthic species may act to dampen the impacts of large seasonal fluctuations in the availability of primary production. The limiting relationship between sea ice distribution and in situ primary productivity emphasizes the role of connectivity and spatial subsidies of organic matter in fueling the food web. Our results begin to provide a basis for predicting how benthic ecosystems will respond to changes in sea ice persistence and extent along environmental gradients in the high Antarctic.     

Ecosystem service value losses from coastal erosion in Europe: historical trends and future projections

Coastal zones experience increased rates of coastal erosion, due to rising sea levels, increased storm surge frequencies, reduced sediment delivery and anthropogenic transformations. Yet, coastal zones host ecosystems that provide associated services which, therefore, may be lost due to coastal erosion. In this paper we assess to what extent past and future coastal erosion patterns lead to losses in land cover types and associated ecosystem service values. Hence, historical (based on CORINE land cover information) and projected (based on Dynamic and Interactive Vulnerability Assessment - DIVA - simulations) coastal erosion patterns are used in combination with a benefits transfer approach. DIVA projections are based on regionalized IPCC scenarios. Relative to the period 1975–2050, a case study is provided for selected European coastal country member states. For historical (1975–2006) coastal erosion trends, we observe territory losses in coastal agricultural, water body and forest & semi-natural areas – total coastal erosion equaling over 4,500 km². Corresponding coastal ecosystem service values decrease from about €22.3 billion per year in 1975 to about €21.6 billion per year in 2006. For future (2006–2050) coastal erosion projections, total territory losses equal between ~3,700 km² and ~5,800 km² – coastal wetland areas being affected most severely. Corresponding coastal ecosystem service values decrease to between €20.1 and €19.4 billion per year by 2050. Hence, we argue that the response strategy of EU member states to deal with coastal erosion and climate change impacts should be based on the economic as well as the ecological importance of their coastal zones.     

Arctic marine mammal population status,sea ice habitat loss,and conservation recommendations for the 21st century

Arctic marine mammals (AMMs) are icons of climate change, largely because of their close association with sea ice. However, neither a circumpolar assessment of AMM status nor a standardized metric of sea ice habitat change is available. We summarized available data on abundance and trend for each AMM species and recognized subpopulation. We also examined species diversity, the extent of human use, and temporal trends in sea ice habitat for 12 regions of the Arctic by calculating the dates of spring sea ice retreat and fall sea ice advance from satellite data (1979–2013). Estimates of AMM abundance varied greatly in quality, and few studies were long enough for trend analysis. Of the AMM subpopulations, 78% (61 of 78) are legally harvested for subsistence purposes. Changes in sea ice phenology have been profound. In all regions except the Bering Sea, the duration of the summer (i.e., reduced ice) period increased by 5–10 weeks and by >20 weeks in the Barents Sea between 1979 and 2013. In light of generally poor data, the importance of human use, and forecasted environmental changes in the 21st century, we recommend the following for effective AMM conservation: maintain and improve comanagement by local, federal, and international partners; recognize spatial and temporal variability in AMM subpopulation response to climate change; implement monitoring programs with clear goals; mitigate cumulative impacts of increased human activity; and recognize the limits of current protected species legislation.     

Bayesian hierarchical spatio-temporal modelling of trends and future projections in the ocean wave climate with a \text{ CO }_2 regression component

Bad weather and rough seas continue to be a major cause for ship losses and is thus a significant contributor to the risk to maritime transportation. This stresses the importance of taking severe sea state conditions adequately into account, with due treatment of the uncertainties involved, in ship design and operation in order to enhance safety. Hence, there is a need for appropriate stochastic models describing the variability of sea states. These should also incorporate realistic projections of future return levels of extreme sea states, taking into account long-term trends related to climate change and inherent uncertainties. The stochastic ocean wave model presented in this paper exploits the flexible framework of Bayesian hierarchical space-time models. It allows modelling of complex dependence structures in space and time and incorporation of physical features and prior knowledge, yet at the same time remains intuitive and easily interpreted. Furthermore, by taking a Bayesian approach, the uncertainties of the model parameters are also taken into account. A regression component with $\text{ CO }_2$ as an explanatory variable has been introduced in order to extract long-term trends in the data. The model has been fitted by monthly maximum significant wave height data for an area in the North Atlantic ocean. The different components of the model will be outlined in the paper, and the results will be discussed. Furthermore, a discussion of possible extensions to the model will be given.     

Population dynamics of Hawaiian seabird colonies vulnerable to sea-level rise

Globally, seabirds are vulnerable to anthropogenic threats both at sea and on land. Seabirds typically nest colonially and show strong fidelity to natal colonies, and such colonies on low-lying islands may be threatened by sea-level rise. We used French Frigate Shoals, the largest atoll in the Hawaiian Archipelago, as a case study to explore the population dynamics of seabird colonies and the potential effects sea-level rise may have on these rookeries. We compiled historic observations, a 30-year time series of seabird population abundance, lidar-derived elevations, and aerial imagery of all the islands of French Frigate Shoals. To estimate the population dynamics of 8 species of breeding seabirds on Tern Island from 1980 to 2009, we used a Gompertz model with a Bayesian approach to infer population growth rates, density dependence, process variation, and observation error. All species increased in abundance, in a pattern that provided evidence of density dependence. Great Frigatebirds (Fregata minor), Masked Boobies (Sula dactylatra), Red-tailed Tropicbirds (Phaethon rubricauda), Spectacled Terns (Onychoprion lunatus), and White Terns (Gygis alba) are likely at carrying capacity. Density dependence may exacerbate the effects of sea-level rise on seabirds because populations near carrying capacity on an island will be more negatively affected than populations with room for growth. We projected 12% of French Frigate Shoals will be inundated if sea level rises 1 m and 28% if sea level rises 2 m. Spectacled Terns and shrub-nesting species are especially vulnerable to sea-level rise, but seawalls and habitat restoration may mitigate the effects of sea-level rise. Losses of seabird nesting habitat may be substantial in the Hawaiian Islands by 2100 if sea levels rise 2 m. Restoration of higher-elevation seabird colonies represent a more enduring conservation solution for Pacific seabirds.     

Improved estimates of certainty in stable-isotope-based methods for tracking migratory animals.

The use of stable-hydrogen isotopes (deltaD) has become a common tool for estimating geographic patterns of movement in migratory animals. This method relies on broad and relatively predictable geographic patterning in deltaD values of precipitation, but these patterns are not estimated without error. In addition, deltaD measurements are relatively imprecise, particularly for organic tissue. Most models for estimating geographic locations have ignored these sources of error. Common modeling approaches include regression, range-matching, and likelihood-based assignment tests (including discriminant analysis). Here, we show the benefits of a simple stochastic extension to likelihood-based assignment tests that incorporates two estimable sources of error and describe the resulting influence on the certainty of assigning breeding origins for wintering American Redstarts (Setophaga ruticilla), a small Nearctic-Neotropical migratory bird. Through simulation, we incorporated both spatial interpolation error associated with models of deltaD in precipitation and analytical error associated with the measurement of deltaD in tissue samples. In general, assignments that did not include these sources of error fell within the ranges of the stochastic results, but the difference in proportion of birds assigned to any one breeding region varied by as much as 54%. To explore how the distribution of assignments generated from error models influenced the application of these results, we developed a simple model of winter habitat loss. We removed the proportion of Redstarts wintering at a particular site from the global population and then used the isotope-based assignments to predict the resulting population declines for each breeding region. This gave distributions of change in population sizes, some of which included no change or even a population increase. The sources of error we modeled may challenge the degree of certainty in the use of stable-isotope-based data on connectivity to predict population dynamics of migratory animals. We suggest that stronger inference will result from incorporating these sources of error into future studies that use deltaD or other stable isotopes to infer the geographic origin of individuals.     

A Behaviorally Explicit Demographic Model Integrating Habitat Selection and Population Dynamics in California Sea Lions

Abstract: Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral‐based PVA approaches require detailed individual‐based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage‐structured matrix model that includes the costs and benefits of movement associated with 2 habitat‐selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations.     

Using Modeling to Improve Monitoring of Structured Populations: Are We Collecting the Right Data?

Abstract:  Population monitoring is central to most demographic studies and conservation efforts, but it may not always be directed at the most appropriate life stage. We used stochastic simulation modeling to evaluate the effectiveness of a monitoring program for a well-studied population of Eastern Imperial Eagles ( Aquila heliaca ) in Kazakhstan. Specifically, we asked whether the most appropriate data were being collected to understand system state and population dynamics. Our models were parameterized with data collected over the course of 25 years of study of this population. We used the models to conduct simulation experiments to evaluate relationships between monitored or potentially monitored parameters and the demographic variables of interest—population size ( N ) and population growth (λ). Static analyses showed that traditional territory-based monitoring was a poor indicator of eagle population size and growth and that monitoring survivorship would provide more information about these parameters. Nevertheless, these same traditionally monitored territory-based parameters had greater power to detect long-term changes in population size than did survivorship or population structure. Regardless of the taxa considered, threats can have immediate impacts on population size and growth or longer-term impacts on population dynamics. Prudently designed monitoring programs for any species will detect the demographic effects of both types of threats.     

Effect of predicted sea level rise on tourism facilities along Ghana’s Accra coast

Recent sea-level rise has mostly been attributed to global warming and this process is expected to continue for centuries. The extent of the impact of sea level rise on tourism in Ghana is unknown though there are predictions that some prominent tourism facilities are at risk. This paper assessed the potential impact of enhanced sea level rise (ESLR) for different IPCC scenarios on tourism facilities along the coast of Accra. Shorelines for 1974 and 2005 were extracted from orthophotos and topographic maps, and vulnerability for tourism facilities estimated. Mean sea level measurements indicated an average rise of 3.3 mm/year, while the shoreline eroded by as much as 0.86 m/year. Predictions for Ghana showed 10 cm, 23.4 cm and 36.4 cm sea level rise for 2020, 2060 and 2100 respectively with 1990 as base year. Modelled predictions for the years 2020, 2060 and 2100 based on A2 (enhanced regional economic growth) and B2 (more environmentally focused) IPCC scenarios indicated that 13 tourism facilities are at risk to sea level rise. Out of the total number of tourism facilities at risk, 31 % cannot physically withstand the event of sea level rise hazard. In terms of socio-economic vulnerability, accommodation facilities are the most susceptible. Salinization and sanitation problems along the coast will adversely affect tourism.     

Dependence of the Endangered Black‐Capped Vireo on Sustained Cowbird Management

Conservation‐reliant species depend on active management, even after surpassing recovery goals, for protection from persistent threats. Required management may include control of another species, habitat maintenance, or artificial recruitment. Sometimes, it can be difficult to determine whether sustained management is required. We used nonspatial stochastic population projection matrix simulation and a spatially explicit population model to estimate the effects of parasitism by a brood parasite, the Brown‐headed Cowbird (Moluthrus ater), on a population of endangered Black‐capped Vireos (Vireo atricapilla). We simulated parasitism as a percentage of breeding vireo pairs experiencing decreased fecundity due to cowbirds. We estimated maximum sustainable parasitism (i.e., highest percentage of parasitized vireo breeding pairs for which population growth is ≥1) with the nonspatial model under multiple scenarios designed to assess sensitivity to assumptions about population growth rate, demographic effects of parasitism, and spatial distribution of parasitism. We then used the spatially explicit model to estimate cumulative probabilities of the population falling below the population recovery target of 1000 breeding pairs for a range of parasitism rates under multiple scenarios. We constructed our models from data on vireos collected on the Fort Hood Military Reservation, Texas (U.S.A.). Estimates of maximum sustainable parasitism rates ranged from 9–12% in scenarios with a low (6%) vireo population growth rate to 49–60% in scenarios with a high (24%) growth rate. Sustained parasitism above 45–85%, depending on the scenario, would likely result in the Fort Hood Vireo population dropping below its recovery goal within the next 25 years. These estimates suggest that vireos, although tolerant of low parasitism rates, are a conservation‐reliant species dependent on cowbird management. Dependencia de Vireo atricapilla, Especie en Peligro, hacia el Manejo Sostenido de Moluthurs ater