Frog survival and population viability in an agricultural landscape with a drying climate

Amphibians are the most threatened class of vertebrate in the world. Although a number of causes of the amphibian decline phenomenon are emerging, there is a need for robust demographic data to be able to monitor current and future threats such as climate change. Despite this, few studies on amphibians have the life-history data available to undertake these analyses and fewer still have looked at the challenges to population viability posed by fragmentation—a feature inherent in agricultural landscapes where the matrix is highly modified. Our aim was to investigate the population viability of a large burrowing frog in an agricultural landscape. Specifically, we aimed to investigate the future persistence of populations under a range of scenarios including populations connected by various levels of dispersal and reduced rainfall. We used the life-history parameters of Heleioporus albopunctatus, a frog species widely distributed in the extensively cleared agricultural regions of south-western Australia. We investigated the viability of 24 partially connected populations under a range of scenarios using the program Vortex Version 10.1.6.0. Metapopulations were consistently more robust to extinction than isolated local populations. Both meta- and local populations were more susceptible to increases in age-specific mortality rates than to variation in the estimated ability of H. albopunctatus to disperse between breeding ponds, the survival rate of dispersers, or the frequency of drought. Our results reinforce the importance of metapopulations for survival in fragmented landscapes and point to the need to manage amphibian breeding ponds across landscapes to ensure high survival rates, particularly for juveniles.     

Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO₂ may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.     

Using climatic suitability thresholds to identify past,present and future population viability

Often climatic niche models predict that any change in climatic conditions will impact species abundance or distribution. However, the accuracy of models that just incorporate climatic information to predict future species habitat use is widely debated. Alternatively, environmental conditions may simply need to be above some minimum threshold of climatic suitability, at which point, other factors drive population size. Using the example of nesting sites of loggerhead sea turtles (Caretta caretta) in the Mediterranean (n = 105), we developed climatic niche models to examine whether a climatic suitability threshold could be identified as a climatic indicator in order for large populations of a widespread species to exist. We then assessed the climatic suitability of sites above and below this threshold in the past (∼1900) and future (∼2100). Most large sites that are currently above the climatic threshold were above the threshold in the past and future, particularly when future nesting seasonality shifted to start 1–2 months earlier. Our analyses highlight the importance of future phenological shifts for maintaining suitability. Our results provide a positive outlook for sea turtle conservation, suggesting that climatic conditions may remain suitable in the future at sites that currently support large nesting populations. Our study also provides an alternative way of interpreting the outputs of climatic niche models, by generating a threshold as an index of a minimum climatic suitability required to sustain large populations. This type of approach offers the possibility to benefit from information provided by climate-driven models, while reducing their inherent uncertainties.     

Evolutionary responses to a changing climate: Implications for reindeer population viability

If we want to understand how climate change affects long‐lived organisms, we must know how individuals allocate resources between current reproduction and survival. This trade‐off is affected by expected environmental conditions, but the extent to which density independent (DI) and density dependent (DD) processes interact in shaping individual life histories is less clear. Female reindeer (or caribou: Rangifer tarandus) are a monotocous large herbivore with a circumpolar distribution. Individuals that experience unpredictable and potentially harsh winters typically adopt risk averse strategies where they allocate more resources to building own body reserves during summer and less to reproduction. Such a strategy implies that the females do not reproduce or that they produce fewer or smaller offspring. A risk averse strategy thus results in females with large autumn body reserves, which is known to increase their survival probabilities if the coming winter is harsh. In contrast, females experiencing predictable winters may adopt a more risk prone strategy in which they allocate more resources to reproduction as they do not need as many resources to buffer potentially adverse winter conditions. This study uses a seasonal state‐dependent model showing that DD and DI processes interact to affect the evolution of reproductive strategies and population dynamics for reindeer. The model was run across a wide range of different winter climatic scenarios: One set of simulations where the average and variability of the environment was manipulated and one set where the frequency of good and poor winters increased. Both reproductive allocation and population dynamics of reindeer were affected by a combination of DI and DD processes even though they were confounded (harsh climates resulted in lowered density). Individual strategies responded, in line with a risk sensitive reproductive allocation, to climatic conditions and in a similar fashion across the two climatic manipulations.     

Predicting the distribution of a novel bark beetle and its pine hosts under future climate conditions

相似文献   

Flying in the face of climate change: a review of climate change, past, present and future

The distribution and abundance of birds is known to depend critically upon climate variability at a range of temporal and spatial scales. In this paper we review historical changes in climate in the context of what is known about climate variability over the last millennium, with particular reference to the British Isles. The climate of Britain is now warmer than it has been in at least 340 years, with the 1990s decade 0.5 °C warmer than the 1961–1990 average. In addition, the frequency of cold days (mean temperature below 0 °C), particularly during March and November, has declined and there has been a marked shift in the seasonality of precipitation, with winters becoming substantially wetter and summers becoming slightly drier. Current understanding is that the rate of future warming is likely to accelerate with more frequent and more intense summer heatwaves, milder winters, an increase in winter rainfall, an increased risk of winter river floods, and an increase in mean sea-level and associated coastal flooding. All of these aspects of climate change are likely to impact on coastal birds. A range of potential future climate scenarios for the British Isles are presented derived from recently completed global climate model experiments. For migrant bird species, changes in the British climate have also to be seen within the context of remote climate change in both the breeding and the overwintering grounds.     

Viability analysis of a threatened amphibian population: modelling the past,present and future

Conservation actions that have maintained populations in the past may not necessarily do so in the future. Population viability analysis provides one tool for exploring the impact of management actions on large temporal scales. However, there are relatively few long‐term data sets that provide the demographic and environmental data demanded by such models. Using a 37‐yr data set, we used RAMAS Metapop to model the persistence of natterjack toads Epidalea (Bufo) calamita on a heathland in southern Britain. A retrospective analysis showed that the best fit between the predicted population trajectories and the real population was when the management carried out was modelled as an increase in K of 150 toads yr^?1. However, even if ongoing management continues to improve K by a further 40–60 toads yr^?1 over the next 50 yr, the population still has an extinction risk of at least 60% if other factors remain unchanged. Sensitivity analyses and simulated management scenarios indicated that the population was most sensitive to changes in the survival of juvenile (i.e. 1–2 yr old) toads. In addition, if the frequency and severity of pond desiccation increases, the risk of extinction was predicted to increase as a result of reduced recruitment. Low levels of extinction risk occurred irrespective of K when juvenile survival was enhanced in combination with low frequency and severity of pond desiccation. The models suggest that populations that are responding to management against a background of natural fluctuations may remain vulnerable to extinction for several decades. These extinction risks may increase if habitat management fails to offset reductions in recruitment and juvenile survival caused by environmental change.     

Long-term ecological vulnerability assessment of Indian Sundarban region under present and future climatic conditions under CMIP6 model

Vulnerability assessment of ecosystem bestows an idea about the ecosystem health and its ability to resist environmental stress. Indian Sundarban region situated at the southwest part of Ganga-Brahmaputra-Meghna delta has been under constant threat of frequent climate hazards and long-term climate change. Various attempts have been made for vulnerability assessment of this mangrove ecosystem focusing only on static non-temporal variables. The present work hypothesises that mangrove ecosystems are highly adaptive and respond to the changing environment by various natural resilience strategies at the ecosystem level. So, a better understanding of the dynamics of mangrove ecosystem will provide an idea about the state of vulnerability for this ecosystem. The present study uses 16 parameters to create exposure, sensitivity and adaptive capacity risk indices and constructs the vulnerability status for the Indian Sundarban. The results showed that the sea-level rise will happen between 0.7 m to 0.9 m under baseline climate conditions. The CMIP6 multi-model ensemble showed that the future minimum temperature for the region will go up to 29.48 °C, thereby reducing the max and min temperature difference for the region. The fuzzy AHP-based vulnerability assessment revealed that the western Sundarban is more prone to climate vulnerability. The island-like Surendranagar, Lothian, and West-Ajmalmari are extremely vulnerable. The proximity to human habitat will play an important role in climate change sensitivity to the Sundarban region. The time series analysis of mangrove forests showed the Mann-Kendall ‘τ’ value varies between 0.82 to −0.83. The central Sundarban forests area shows a varying degree of forest health deterioration. The assessments from the present study and the maps will help the environmental and risk-managers to identify the regions needing more climate change adaptation strategy.     

Linking environmental and demographic data to predict future population viability of a perennial herb

Recent advances in stochastic demography provide tools to examine the importance of random and periodic variation in vital rates for population dynamics. In this study, we explore with simulations the effect of disturbance regime on population dynamics and viability. We collected 7 years of demographic data in three populations of the perennial herb Primula farinosa, and used these data to examine how variation in vital rates affected population viability parameters (stochastic growth rate, λ_S), and how vital rates were related to weather conditions. Elasticity analysis indicated that the stochastic growth rate was very sensitive to changes in regeneration, quantified as the production, survival, and germination of seeds. In one of the study years, all seedlings and mature plants in the demography plots died. This extinction coincided with the driest summer during the study period. Simulations suggested that a future increase in the frequency of high-mortality years due to climate change would result in reduced population growth rate, and an increased importance of survival in the seed bank for population viability. The results illustrate how the limited demographic data typically available for many natural systems can be used in simulation models to assess how environmental change will affect population viability.     

Pollen viability of Euro‐Mediterranean orchids under different storage conditions: The possible effects of climate change

• The future impact of climate change and a warmer world is a matter of great concern. We therefore aimed to evaluate the effects of temperature on pollen viability and fruit set of Mediterranean orchids.
• The in vitro and controlled pollination experiments were performed to evaluate the ability of pollinia stored at lower and higher temperatures to germinate and produce fruits and seeds containing viable embryos.
• In all of the examined orchids, pollen stored at ?20 °C remained fully viable for up to 3 years, reducing its percentage germination from year 4 onwards. Pollinia stored at higher temperatures had a drastic reduction in vitality after 2 days at 41–44 °C, while pollinia stored at 47–50 °C did not show any pollen tube growth.
• The different levels of pollen viability duration among the examined orchids can be related to their peculiar reproductive biology and pollination ecology. The germinability of pollinia stored at lower temperatures for long periods suggests that orchid pollinia can be conserved ex situ. In contrast, higher temperatures can have harmful effects on the vitality of pollen and consequently on reproductive success of the plants. To our knowledge, this is the first report demonstrating the effects of global change on orchid pollen, and on pollen ability to tolerate, or not, higher air temperatures. Although vegetative reproduction allows orchids to survive a few consecutive warm years, higher temperatures for several consecutive years can have dramatic effects on reproductive success of orchids.

     

Rapid assessment of metapopulation viability under climate and land-use change

In order to predict species response to climate and land-use change, numerically fast and easily applicable assessment tools for species survival are required. We present a set of formulae to calculate the mean lifetime of a metapopulation in a spatially heterogeneous and dynamic landscape subject to habitat patch diminution, loss and/or spatial shift of the habitat network. The formulae require as inputs (i) information about the number, location and size of the habitat patches for several time steps to quantify landscape dynamics in terms of patch destruction, diminution or shifting rates and (ii) data on species traits such as their vulnerability to environmental variation and their dispersal ability to quantify local colonisation and extinction rates. We validate the formulae with a spatially explicit simulation. The analysis is complemented by a protocol for the easy use of the approach and practical application examples. A software implementation is available on request from the authors.     

Successions in the forest-steppe under climate changes: a modelling approach

The paper represents an attempt to apply the general principles of modelling vegetation dynamics under climate changes to a study of the long-term vegetation dynamics in the forest-steppe zone of the European territory of Russia, with a purpose to forecast under special climatic scenarios. An original technique is used to construct a Markov chain as a model of vegetation succession. The technique emanated from gebotanic knowledge generalized as a scheme of successional transitions with estimates of the average duration for certain stages of succession. Whenever the knowledge related the stage duration to certain (climate-sensitive) factors of the environment, the fundamental potentiality arises to model the temporal course of succession as a function of a given scenario for how the key factors change. In the formal terms, the model represents a random chain of the Markov kind with a finite number of states and discrete time of transitions by the given scheme. Relative square distributions of succession stages under concern at any time moment (within an adopted scenario) appear as the model outcome (forecasts), as well as estimates of the attainment time for certain states of the vegetation in the territory under study. A method is proposed to describe dynamics of the phytomass production and stores (and the corresponding model trajectories are obtained) for a given scenario.     

Frog oocyte glycogen synthase: enzyme regulation under in vitro and in vivo conditions

Frog oocyte glycogen synthase properties differ significantly under in vitro or in vivo conditions. The K(mapp) for UDP-glucose in vivo was 1.4mM (in the presence or absence of glucose-6-P). The in vitro value was 6mM and was reduced by glucose-6-P to 0.8mM. Under both conditions (in vitro and in vivo) V(max) was 0.2 m Units per oocyte in the absence of glucose-6-P. V(max) in vivo was stimulated 2-fold by glucose-6-P, whereas, in vitro, a 10-fold increase was obtained. Glucose-6-P required for 50% activation in vivo was 15 microM and, depending on substrate concentrations, 50-100 microM in vitro. The prevailing enzyme obtained in vitro was the glucose-6-P-dependent form, which may be converted to the independent species by dephosphorylation. This transformation could not be observed in vivo. We suggest that enzyme activation by glucose-6-P in vivo is due to allosteric effects rather than to dephosphorylation of the enzyme. Regulatory mechanisms other than allosteric activation and covalent phosphorylation are discussed.     

Beyond species distribution modeling: A landscape genetics approach to investigating range shifts under future climate change

Understanding how biodiversity will respond to future climate change is a major conservation and societal challenge. Climate change is predicted to force many species to shift their ranges in pursuit of suitable conditions. This study aims to use landscape genetics, the study of the effects of environmental heterogeneity on the spatial distribution of genetic variation, as a predictive tool to assess how species will shift their ranges to track climatic changes and inform conservation measures that will facilitate movement. The approach is based on three steps: 1) using species distribution models (SDMs) to predict suitable ranges under future climate change, 2) using the landscape genetics framework to identify landscape variables that impede or facilitate movement, and 3) extrapolating the effect of landscape connectivity on range shifts in response to future climate change. I show how this approach can be implemented using the publicly available genetic dataset of the grey long-eared bat, Plecotus austriacus, in the Iberian Peninsula. Forest cover gradient was the main landscape variable affecting genetic connectivity between colonies. Forest availability is likely to limit future range shifts in response to climate change, primarily over the central plateau, but important range shift pathways have been identified along the eastern and western coasts. I provide outputs that can be directly used by conservation managers and review the viability of the approach. Using landscape genetics as a predictive tool in combination with SDMs enables the identification of potential pathways, whose loss can affect the ability of species to shift their range into future climatically suitable areas, and the appropriate conservation management measures to increase landscape connectivity and facilitate movement.     

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. AVAILABILITY: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.