No abstract

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models.

Climate projections are essential for studying ecological responses to climate change, and their use is now common in ecology. However, the lack of integration between ecology and climate science has restricted understanding of the available climate data and their appropriate use. We provide an overview of climate model outputs and issues that need to be considered when applying projections of future climate in ecological studies. We outline the strengths and weaknesses of available climate projections, the uncertainty associated with future projections at different spatial and temporal scales, the differences between available downscaling methods (dynamical, statistical downscaling, and simple scaling of global circulation model output), and the implications these have for ecological models. We describe some of the changes in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), including the new representative concentration pathways. We highlight some of the challenges in using model projections in ecological studies and suggest how to effectively address them. WIREs Clim Change 2014, 5:621–637. doi: 10.1002/wcc.291 This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models Future of Global Energy > Scenario Development and Application Climate, Ecology, and Conservation > Modeling Species and Community Interactions

Fire is a complex process involving interactions and feedbacks between biological, socioeconomic, and physical drivers across multiple spatial and temporal scales. This complexity limits our ability to incorporate fire into Earth system models and project future fire activity under climate change. Conceptual, empirical, and process models have identified the mechanisms and processes driving fire regimes, and provide a useful basis to consider future fire activity. However, these models generally deal with only one component of fire regimes, fire frequency, and do not incorporate feedbacks between fire, vegetation, and climate. They are thus unable to predict the location, severity or timing of fires, the socioecological impacts of fire regime change, or potential non‐linear responses such as biome shifts into alternative stable states. Dynamic modeling experiments may facilitate more thorough investigations of fire–vegetation–climate feedbacks and interactions, but their success will depend on the development of dynamic global vegetation models (DGVMs) that more accurately represent biological drivers. This requires improvements in the representation of current vegetation, plant responses to fire, ecological dynamics, and land management to capture the mechanisms behind fire frequency, intensity, and timing. DGVMs with fire modules are promising tools to develop a globally consistent analysis of fire activity, but projecting future fire activity will ultimately require a transdisciplinary synthesis of the biological, atmospheric, and socioeconomic drivers of fire. This is an important goal because fire causes substantial economic disruption and contributes to future climate change through its influence on albedo and the capacity of the biosphere to store carbon. WIREs Clim Change 2016, 7:910–931. doi: 10.1002/wcc.428 This article is categorized under: Climate Models and Modeling > Model Components Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change Climate, Ecology, and Conservation > Observed Ecological Changes

Daily values of McArthur Forest Fire Danger Index were generated at ~10-km resolution over Tasmania, Australia, from six dynamically downscaled CMIP3 climate models for 1961–2100, using a high (A2) emissions scenario. Multi-model mean fire danger validated well against observations for 2002–2012, with 99th percentile fire dangers having the same distribution and largely similar values to those observed over the same time. Model projections showed a broad increase in fire danger across Tasmania, but with substantial regional variation – the increase was smaller in western Tasmania (district mean cumulative fire danger increasing at 1.07 per year) compared with parts of the east (1.79 per year), for example. There was also noticeable seasonal variation, with little change occurring in autumn, but a steady increase in area subject to springtime 99th percentile fire danger from 6% in 1961–1980 to 21% by 2081–2100, again consistent with observations. In general, annually accumulated fire danger behaved similarly. Regional mean sea level pressure patterns resembled observed patterns often associated with days of dangerous fire weather. Days of elevated fire danger displaying these patterns increased in frequency during the simulated twenty-first century: in south-east Tasmania, for example, the number of such events detected rose from 101 (across all models) in 1961–1980 to 169 by 2081–2100. Correspondence of model output with observations and the regional detail available suggest that these dynamically downscaled model data are useful projections of future fire danger for landscape managers and the community.

Aim  We explore geographic variation in body size within the wingless grasshopper, Phaulacridium vittatum, along a latitudinal gradient, and ask whether melanism can help explain the existence of clinal variation. We test the hypotheses that both male and female grasshoppers will be larger and lighter in colour at lower latitudes, and that reflectance and size will be positively correlated, as predicted by biophysical theory. We then test the hypothesis that variability in size and reflectance is thermally driven, by assessing correlations with temperature and other climatic variables. Location  Sixty‐one populations were sampled along the east coast of Australia between latitudes 27.63° S and 43.10° S, at elevations ranging from 10 to 2000 m a.s.l. Methods  Average reflectance was used as a measure of melanism and femur length as an index of body size for 198 adult grasshoppers. Climate variables were generated by BIOCLIM for each collection locality. Hierarchical partitioning was used to identify those variables with the most independent influence on grasshopper size and reflectance. Results  Overall, there was no simple relationship between size and latitude in P. vittatum. Female body size decreased significantly with latitude, while male body size was largest at intermediate latitudes. Rainfall was the most important climatic variable associated with body size of both males and females. Female body size was also associated with radiation seasonality and male body size with reflectance. The reflectance of females was not correlated with latitude or body size, while male reflectance was significantly higher at intermediate latitudes and positively correlated with body size. Analyses of climate variables showed no significant association with male reflectance, while female reflectance was significantly related to the mean temperature of the driest quarter. Main conclusions  Geographic variation in the body size of the wingless grasshopper is best explained in terms of rainfall and radiation seasonality, rather than temperature. However, melanism is also a significant influence on body size in male grasshoppers, suggesting that thermal fitness does play a role in determining adaptive responses to local conditions in this sex.

No abstract

Altitudinal clines in melanism are generally assumed to reflect the fitness benefits resulting from thermal differences between colour morphs, yet differences in thermal quality are not always discernible. The intra-specific application of the thermal melanism hypothesis was tested in the wingless grasshopper Phaulacridium vittatum (Sjöstedt) (Orthoptera: Acrididae) first by measuring the thermal properties of the different colour morphs in the laboratory, and second by testing for differences in average reflectance and spectral characteristics of populations along 14 altitudinal gradients. Correlations between reflectance, body size, and climatic variables were also tested to investigate the underlying causes of clines in melanism. Melanism in P. vittatum represents a gradation in colour rather than distinct colour morphs, with reflectance ranging from 2.49 to 5.65%. In unstriped grasshoppers, darker morphs warmed more rapidly than lighter morphs and reached a higher maximum temperature (lower temperature excess). In contrast, significant differences in thermal quality were not found between the colour morphs of striped grasshoppers. In support of the thermal melanism hypothesis, grasshoppers were, on average, darker at higher altitudes, there were differences in the spectral properties of brightness and chroma between high and low altitudes, and temperature variables were significant influences on the average reflectance of female grasshoppers. However, altitudinal gradients do not represent predictable variation in temperature, and the relationship between melanism and altitude was not consistent across all gradients. Grasshoppers generally became darker at altitudes above 800 m a.s.l., but on several gradients reflectance declined with altitude and then increased at the highest altitude.