How does climate change cause extinction?

Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies.     

How does forest landscape structure explain tree species richness in a Mediterranean context?

Although the strong relationship between vegetation and climatic factors is widely accepted, other landscape composition and configuration characteristics could be significantly related with vegetation diversity patterns at different scales. Variation partitioning was conducted in order to analyse to what degree forest landscape structure, compared to other spatial and environmental factors, explained forest tree species richness in 278 UTM 10 × 10 km cells in the Mediterranean region of Catalonia (NE Spain). Tree species richness variation was decomposed through linear regression into three groups of explanatory variables: forest landscape (composition and configuration), environmental (topography and climate) and spatial variables. Additionally, the forest landscape characteristics which significantly contributed to explain richness variation were identified through a multiple regression model. About 60% of tree species richness variation was explained by the whole set of variables, while their joint effects explained nearly 28%. Forest landscape variables were those with a greater pure explanatory power for tree species richness (about 15% of total variation), much larger than the pure effect of environmental or spatial variables (about 2% each). Forest canopy cover, forest area and land cover diversity were the most significant composition variables in the regression model. Landscape configuration metrics had a minor effect on forest tree species richness, with the exception of some shape complexity indices, as indicators of land use intensity and edge effects. Our results highlight the importance of considering the forest landscape structure in order to understand the distribution of vegetation diversity in strongly human-modified regions like the Mediterranean.     

How fast and far might tree species migrate in the eastern United States due to climate change?

Aim We describe and use a model, SHIFT, to estimate potential migration due to climate change over the next 100 years. Location Eastern United States. Methods Five species, currently confined to the eastern half of the United States and not extending into Canada, were used to assess migration potential: Diospyros virginiana (persimmon), Liquidambar styraciflua (sweetgum), Oxydendrum arboreum (sourwood), Pinus taeda (loblolly pine), and Quercus falcata var. falcata (southern red oak). SHIFT is a matrix simulation model using simple inverse power functions to provide a distance decay of seed dispersal and is driven primarily by the abundance of the species near the boundary, the forest density within and beyond the boundary, and the distance between cells. For each cell outside the current boundary, the model creates an estimate of the probability that each unoccupied cell will become colonized over a period of 100 years. SHIFT is a ‘fat‐tailed’ migration model that allows rare very long distance dispersal events and colonization could occur up to 500 km beyond the current distribution boundary. Model outputs were analysed using transects through sections showing relatively low and high colonization probabilities as a result of low and high densities of target trees (high source strength) as well as high densities of forest (high sink strength). We also assess migration potential for species by concentric rings around the current boundary. Results Model outputs show the generally limited nature of migration for all five species over 100 years. There is a relatively high probability of colonization within a zone of 10–20 km (depending on habitat quality and species abundance) from the current boundary, but a small probability of colonization where the distance from the current boundary exceeds about 20 km. Whether biologically plausible or not, rare very long distance migration events are not sufficient to rescue migration. Species abundance (the source strength of migration) near the range boundary carried relatively more influence than percentage forest cover (sink strength) in determining migration rates. Main conclusion The transect evaluation revealed the importance of abundance of the species near the boundary, indicating that rare species may have much more difficulty in unassisted northward migration due to climate change. The concentric rings analysis of the model outputs showed that only the first 10–20 km of area would have a reasonably high probability of colonization. Rare, long‐distance events permit colonization of remote outliers, but much more needs to be understood about the likelihood of these rare events to predict the frequency of outlier establishment.     

What is the role of disturbance in catalyzing spatial shifts in forest composition and tree species biomass under climate change?

Mounting evidence suggests that climate change will cause shifts of tree species range and abundance (biomass). Abundance changes under climate change are likely to occur prior to a detectable range shift. Disturbances are expected to directly affect tree species abundance and composition, and could profoundly influence tree species spatial distribution within a geographical region. However, how multiple disturbance regimes will interact with changing climate to alter the spatial distribution of species abundance remains unclear. We simulated such forest demographic processes using a forest landscape succession and disturbance model (LANDIS-II) parameterized with forest inventory data in the northeastern United States. Our study incorporated climate change under a high-emission future and disturbance regimes varying with gradients of intensities and spatial extents. The results suggest that disturbances catalyze changes in tree species abundance and composition under a changing climate, but the effects of disturbances differ by intensity and extent. Moderate disturbances and large extent disturbances have limited effects, while high-intensity disturbances accelerate changes by removing cohorts of mid- and late-successional species, creating opportunities for early-successional species. High-intensity disturbances result in the northern movement of early-successional species and the southern movement of late-successional species abundances. Our study is among the first to systematically investigate how disturbance extent and intensity interact to determine the spatial distribution of changes in species abundance and forest composition.     

Predicting future distributions of mountain plants under climate change: does dispersal capacity matter?

Many studies have investigated the potential impacts of climate change on the distribution of plant species, but few have attempted to constrain projections through plant dispersal limitations. Instead, most studies published so far have simplified dispersal as either unlimited or null. However, depending on the dispersal capacity of a species, landscape fragmentation, and the rate of climatic change, these assumptions can lead to serious over- or underestimation of the future distribution of plant species.
To quantify the discrepancies between simulations accounting for dispersal or not, we carried out projections of future distribution over the 21st century for 287 mountain plant species in a study area of the western Swiss Alps. For each species, simulations were run for four dispersal scenarios (unlimited dispersal, no dispersal, realistic dispersal, and realistic dispersal with long-distance dispersal events) and under four climate change scenarios.
Although simulations accounting for realistic dispersal limitations did significantly differ from those considering dispersal as unlimited or null in terms of projected future distribution, the unlimited dispersal simplification did nevertheless provide good approximations for species extinctions under more moderate climate change scenarios. Overall, simulations accounting for dispersal limitations produced, for our mountainous study area, results that were significantly closer to unlimited dispersal than to no dispersal. Finally, analysis of the temporal pattern of species extinctions over the entire 21st century revealed that important species extinctions for our study area might not occur before the 2080–2100 period, due to the possibility of a large number of species shifting their distribution to higher elevation.     

How much evolutionary advantage does sex confer?

In discussing the long term advantage of sex, Crow & Kimura (1965) andMaynard Smith (1971) have argued that the advantage of a reproductive system allowing recombination (sex) is greatest for large populations. However the validity of this conclusion depends upon the model used for evolution. We propose two simple models: the bootstrap model, where the number of loci at which favourable mutations may take place remains constant over long time periods; and the environment-led model, where evolution is at a constant rate dictated by the environment (and does not depend on the organism's ability to evolve). While the bootstrap model leads to conclusions similar to those mentioned above, the conclusions for environment-led evolution are the opposite: as the size of the population decreases the advantage for sex increases.     

How much water does a river need?

1. This paper introduces a new approach for setting streamflow-based river ecosystem management targets and this method is called the 'Range of Variability Approach' (RVA). The proposed approach derives from aquatic ecology theory concerning the critical role of hydrological variability, and associated characteristics of timing, frequency, duration, and rates of change, in sustaining aquatic ecosystems. The method is intended for application on rivers wherein the conservation of native aquatic biodiversity and protection of natural ecosystem functions are primary river management objectives.
2. The RVA uses as its starting point either measured or synthesized daily streamflow values from a period during which human perturbations to the hydrological regime were negligible. This streamflow record is then characterized using thirty-two different hydrological parameters, using methods defined in Richter et al . (1996). Using the RVA, a range of variation in each of the thirty-two parameters, e.g. the values at ± 1 standard deviation from the mean or the twenty-fifth to seventy-fifth percentile range, are selected as initial flow management targets.
3. The RVA targets are intended to guide the design of river management strategies (e.g. reservoir operations rules, catchment restoration) that will lead to attainment of these targets on an annual basis. The RVA will enable river managers to define and adopt readily interim management targets before conclusive, long-term ecosystem research results are available. The RVA targets and management strategies should be adaptively refined as suggested by research results and as needed to sustain native aquatic ecosystem biodiversity and integrity.     

Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes?

Aim Species distribution models and geographical information system (GIS) technologies are becoming increasingly important tools in conservation planning and decision‐making. Often the rich data bases of museums and herbaria serve as the primary data for predicting species distributions. Yet key assumptions about the primary data often are untested, and violation of such assumptions may have consequences for model predictions. For example, users of primary data assume that sampling has been random with respect to geography and environmental gradients. Here we evaluate the assumption that plant voucher specimens adequately sample the climatic gradient and test whether violation of this assumption influences model predictions. Location Bolivia and Ecuador. Methods Using 323,711 georeferenced herbarium collections and nine climatic variables, we predicted the distribution of 76 plant species using maximum entropy models (MAXENT) with training points that sampled the climate environments randomly and training points that reflected the climate bias in the herbarium collections. To estimate the distribution of species, MAXENT finds the distribution of maximum entropy (i.e. closest to uniform) subject to the constraint that the expected value for each environmental variable under the estimated distribution matches its empirical average. The experimental design included species that differed in geographical range and elevation; all species were modelled with 20 and 100 training points. We examined the influence of the number of training points and climate bias in training points, elevation and range size on model performance using analysis of variance models. Results We found that significant parts of the climatic gradient were poorly represented in herbarium collections for both countries. For the most part, existing climatic bias in collections did not greatly affect distribution predictions when compared with an unbiased data set. Although the effects of climate bias on prediction accuracy were found to be greater where geographical ranges were characterized by high spatial variation in the degree of climate bias (i.e. ranges where the bias of the various climates sampled by collections deviated considerably from the mean bias), the greatest influence on model performance was the number of presence points used to train the model. Main conclusions These results demonstrate that predictions of species distributions can be quite good despite existing climatic biases in primary data found in natural history collections, if a sufficiently large number of training points is available. Because of consistent overprediction of models, these results also confirm the importance of validating models with independent data or expert opinion. Failure to include independent model validation, especially in cases where training points are limited, may potentially lead to grave errors in conservation decision‐making and planning.     

How do climate change experiments alter plot‐scale climate?

To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot‐scale climate data from 15 active‐warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6 C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1 C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2 C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non‐temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species’ responses.     

How do disturbances and environmental heterogeneity affect the pace of forest distribution shifts under climate change?

Although it is widely predicted that the geographic distributions of tree species and forest types will undergo substantial shifts in future, modelling approaches used to date are largely unable to project the pace at which forest distributions will respond to environmental change. The expansion and contraction of forest distributions act against considerable demographic inertia in the present composition and size‐structure of forest stands as climate‐induced changes in growth, mortality, and recruitment alter population dynamics through time. We aimed to better understand how shifts in forest distributions reflect long‐term changes in tree demographic rates and population dynamics, and how such shifts are influenced by 1) disturbance from forest harvesting and 2) local environmental heterogeneity. Using a simple, data‐constrained gap model, we simulated regional forest dynamics in the eastern United States over the next 500 yr. We then compared the geographic distributions of five different forest types through time under present and altered climatic conditions, in scenarios that variously included and excluded forest harvesting and environmental heterogeneity. Although we held climate fixed after 100 yr, it took another 160 yr after this for these forest types to collectively experience 90% of their eventual climate‐related distribution gains and losses. Competition strongly affected the nature of responses to climate change. Harvesting accelerated and amplified gains by an early‐successional forest type at the expense of a late‐successional one, but these gains did not occur faster than those for other forest types. Environmental heterogeneity had little effect on distribution gains or losses through time. These findings indicate that forest distributions should respond quite slowly to climate change, with the leading and trailing edges of different forest types shifting over a span of centuries. Disturbances can expedite some transitions, but are unlikely to lead to wholesale changes in forest types in the coming decades.     

How does insect visitation trigger floral colour change?

Abstract.  1. Visitation by the key pollinator, Bombus terrestris , was implicated in inducible flower colour change in Lupinus pilosus . Behaviour at the flower and rate of visitation by these bumble bees had specific effects; exclusion of this flower visitor led to retarded onset, and reduced rate, of colour change.
2. The foraging behaviour of B. terrestris was influenced by floral colour change in L. pilosus . Choice of pre-change flowers was greater than random in relation to the proportion of colour phases available within the plant population.
3. Levels of floral manipulation that mimicked the flower handling characteristics of visiting bumble bees confirmed that triggering of the pollen release mechanism is necessary for the instigation of colour change.
4. Moreover, this study suggests that, in L. pilosus , an aspect of pollination (pollen deposition by bees and/or subsequent pollen tube growth within the style) is linked with colour change and may act as the trigger for such change.     

Is subarctic forest advance able to keep pace with climate change?

Recent climate warming and scenarios for further warming have led to expectations of rapid movement of ecological boundaries. Here we focus on the circumarctic forest–tundra ecotone (FTE), which represents an important bioclimatic zone with feedbacks from forest advance and corresponding tundra disappearance (up to 50% loss predicted this century) driving widespread ecological and climatic changes. We address FTE advance and climate history relations over the 20th century, using FTE response data from 151 sites across the circumarctic area and site‐specific climate data. Specifically, we investigate spatial uniformity of FTE advance, statistical associations with 20th century climate trends, and whether advance rates match climate change velocities (CCVs). Study sites diverged into four regions (Eastern Canada; Central and Western Canada and Alaska; Siberia; and Western Eurasia) based on their climate history, although all were characterized by similar qualitative patterns of behaviour (with about half of the sites showing advancing behaviour). The main associations between climate trend variables and behaviour indicate the importance of precipitation rather than temperature for both qualitative and quantitative behaviours, and the importance of non‐growing season as well as growing season months. Poleward latitudinal advance rates differed significantly among regions, being smallest in Eastern Canada (~10 m/year) and largest in Western Eurasia (~100 m/year). These rates were 1–2 orders of magnitude smaller than expected if vegetation distribution remained in equilibrium with climate. The many biotic and abiotic factors influencing FTE behaviour make poleward advance rates matching predicted 21st century CCVs (~10³–10⁴ m/year) unlikely. The lack of empirical evidence for swift forest relocation and the discrepancy between CCV and FTE response contradict equilibrium model‐based assumptions and warrant caution when assessing global‐change‐related biotic and abiotic implications, including land–atmosphere feedbacks and carbon sequestration.