Regional analysis of the impacts of climate change on cheatgrass invasion shows potential risk and opportunity

Interactions between climate change and non-native invasive species may combine to increase invasion risk to native ecosystems. Changing climate creates risk as new terrain becomes climatically suitable for invasion. However, climate change may also create opportunities for ecosystem restoration on invaded lands that become climatically unsuitable for invasive species. Here, I develop a bioclimatic envelope model for cheatgrass ( Bromus tectorum ), a non-native invasive grass in the western US, based on its invaded distribution. The bioclimatic envelope model is based on the Mahalanobis distance using the climate variables that best constrain the species' distribution. Of the precipitation and temperature variables measured, the best predictors of cheatgrass are summer, annual, and spring precipitation, followed by winter temperature. I perform a sensitivity analysis on potential cheatgrass distributions using the projections of 10 commonly used atmosphere–ocean general circulation models (AOGCMs) for 2100. The AOGCM projections for precipitation vary considerably, increasing uncertainty in the assessment of invasion risk. Decreased precipitation, particularly in the summer, causes an expansion of suitable land area by up to 45%, elevating invasion risk in parts of Montana, Wyoming, Utah, and Colorado. Conversely, increased precipitation reduces habitat by as much as 70%, decreasing invasion risk. The strong influence of precipitation conditions on this species' distribution suggests that relying on temperature change alone to project future change in plant distributions may be inadequate. A sensitivity analysis provides a framework for identifying key climate variables that may limit invasion, and for assessing invasion risk and restoration opportunities with climate change.     

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data‐based evaluations of emergent ecosystem responses to climate and CO₂ at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO₂ in ten ecosystem models with the sensitivities found in tree‐ring reconstructions of NPP and raw ring‐width series at six temperate forest sites. These model‐data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO₂ in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree‐ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm‐growing season temperatures, while tree‐ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO₂ drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO₂ sensitivity. Fire in model simulations reduced model sensitivity to climate and CO₂, but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO₂ in individual models.     

Global climate change will increase the abundance of symbiotic nitrogen‐fixing trees in much of North America

Symbiotic nitrogen (N)‐fixing trees can drive N and carbon cycling and thus are critical components of future climate projections. Despite detailed understanding of how climate influences N‐fixation enzyme activity and physiology, comparatively little is known about how climate influences N‐fixing tree abundance. Here, we used forest inventory data from the USA and Mexico (>125,000 plots) along with climate data to address two questions: (1) How does the abundance distribution of N‐fixing trees (rhizobial, actinorhizal, and both types together) vary with mean annual temperature (MAT) and precipitation (MAP)? (2) How will changing climate shift the abundance distribution of N‐fixing trees? We found that rhizobial N‐fixing trees were nearly absent below 15°C MAT, but above 15°C MAT, they increased in abundance as temperature rose. We found no evidence for a hump‐shaped response to temperature throughout the range of our data. Rhizobial trees were more abundant in dry than in wet ecosystems. By contrast, actinorhizal trees peaked in abundance at 5–10°C MAT and were least abundant in areas with intermediate precipitation. Next, we used a climate‐envelope approach to project how N‐fixing tree relative abundance might change in the future. The climate‐envelope projection showed that rhizobial N‐fixing trees will likely become more abundant in many areas by 2080, particularly in the southern USA and western Mexico, due primarily to rising temperatures. Projections for actinorhizal N‐fixing trees were more nuanced due to their nonmonotonic dependence on temperature and precipitation. Overall, the dominant trend is that warming will increase N‐fixing tree abundance in much of the USA and Mexico, with large increases up to 40° North latitude. The quantitative link we provide between climate and N‐fixing tree abundance can help improve the representation of symbiotic N fixation in Earth System Models.     

Recent climate hiatus revealed dual control by temperature and drought on the stem growth of Mediterranean Quercus ilex

A better understanding of stem growth phenology and its climate drivers would improve projections of the impact of climate change on forest productivity. Under a Mediterranean climate, tree growth is primarily limited by soil water availability during summer, but cold temperatures in winter also prevent tree growth in evergreen forests. In the widespread Mediterranean evergreen tree species Quercus ilex, the duration of stem growth has been shown to predict annual stem increment, and to be limited by winter temperatures on the one hand, and by the summer drought onset on the other hand. We tested how these climatic controls of Q. ilex growth varied with recent climate change by correlating a 40‐year tree ring record and a 30‐year annual diameter inventory against winter temperature, spring precipitation, and simulated growth duration. Our results showed that growth duration was the best predictor of annual tree growth. We predicted that recent climate changes have resulted in earlier growth onset (?10 days) due to winter warming and earlier growth cessation (?26 days) due to earlier drought onset. These climatic trends partly offset one another, as we observed no significant trend of change in tree growth between 1968 and 2008. A moving‐window correlation analysis revealed that in the past, Q. ilex growth was only correlated with water availability, but that since the 2000s, growth suddenly became correlated with winter temperature in addition to spring drought. This change in the climate–growth correlations matches the start of the recent atmospheric warming pause also known as the ‘climate hiatus’. The duration of growth of Q. ilex is thus shortened because winter warming has stopped compensating for increasing drought in the last decade. Decoupled trends in precipitation and temperature, a neglected aspect of climate change, might reduce forest productivity through phenological constraints and have more consequences than climate warming alone.     

Climatic water deficit,tree species ranges,and climate change in Yosemite National Park

Aim (1) To calculate annual potential evapotranspiration (PET), actual evapotranspiration (AET) and climatic water deficit (Deficit) with high spatial resolution; (2) to describe distributions for 17 tree species over a 2300‐m elevation gradient in a 3000‐km² landscape relative to AET and Deficit; (3) to examine changes in AET and Deficit between past (c. 1700), present (1971–2000) and future (2020–49) climatological means derived from proxies, observations and projections; and (4) to infer how the magnitude of changing Deficit may contribute to changes in forest structure and composition. Location Yosemite National Park, California, USA. Methods We calculated the water balance within Yosemite National Park using a modified Thornthwaite‐type method and correlated AET and Deficit with tree species distribution. We used input data sets with different spatial resolutions parameterized for variation in latitude, precipitation, temperature, soil water‐holding capacity, slope and aspect. We used climate proxies and climate projections to model AET and Deficit for past and future climate. We compared the modelled future water balance in Yosemite with current species water‐balance ranges in North America. Results We calculated species climatic envelopes over broad ranges of environmental gradients – a range of 310 mm for soil water‐holding capacity, 48.3°C for mean monthly temperature (January minima to July maxima), and 918 mm yr^?1 for annual precipitation. Tree species means were differentiated by AET and Deficit, and at higher levels of Deficit, species means were increasingly differentiated. Modelled Deficit for all species increased by a mean of 5% between past (c. 1700) and present (1971–2000). Projected increases in Deficit between present and future (2020–49) were 23% across all plots. Main conclusions Modelled changes in Deficit between past, present and future climate scenarios suggest that recent past changes in forest structure and composition may accelerate in the future, with species responding individualistically to further declines in water availability. Declining water availability may disproportionately affect Pinus monticola and Tsuga mertensiana. Fine‐scale heterogeneity in soil water‐holding capacity, aspect and slope implies that plant water balance may vary considerably within the grid cells of kilometre‐scale climate models. Sub‐grid‐cell soil and topographical data can partially compensate for the lack of spatial heterogeneity in gridded climate data, potentially improving vegetation‐change projections in mountainous landscapes with heterogeneous topography.     

An ecoregion assessment of projected tree species vulnerabilities in western North America through the 21st century

Forest ecosystems across western North America will likely see shifts in both tree species dominance and composition over the rest of this century in response to climate change. Our objective in this study was to identify which ecological regions might expect the greatest changes to occur. We used the process‐based growth model 3‐PG, to provide estimates of tree species responses to changes in environmental conditions and to evaluate the extent that species are resilient to shifts in climate over the rest of this century. We assessed the vulnerability of 20 tree species in western North America using the Canadian global circulation model under three different emission scenarios. We provided detailed projections of species shifts by including soil maps that account for the spatial variation in soil water availability and soil fertility as well as by utilizing annual climate projections of monthly changes in air temperature, precipitation, solar radiation, vapor pressure deficit and frost at a spatial resolution of one km. Projected suitable areas for tree species were compared to their current ranges based on observations at >40 000 field survey plots. Tree species were classified as vulnerable if environmental conditions projected in the future appear outside that of their current distribution ≥70% of the time. We added a migration constraint that limits species dispersal to <200 m yr^?1 to provide more realistic projections on species distributions. Based on these combinations of constraints, we predicted the greatest changes in the distribution of dominant tree species to occur within the Northwest Forested Mountains and the highest number of tree species stressed will likely be in the North American Deserts. Projected climatic changes appear especially unfavorable for species in the subalpine zone, where major shifts in composition may lead to the emergence of new forest types.     

Implications of future climate and atmospheric CO2 content for regional biogeochemistry,biogeography and ecosystem services across East Africa

We model future changes in land biogeochemistry and biogeography across East Africa. East Africa is one of few tropical regions where general circulation model (GCM) future climate projections exhibit a robust response of strong future warming and general annual‐mean rainfall increases. Eighteen future climate projections from nine GCMs participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment were used as input to the LPJ dynamic global vegetation model (DGVM), which predicted vegetation patterns and carbon storage in agreement with satellite observations and forest inventory data under the present‐day climate. All simulations showed future increases in tropical woody vegetation over the region at the expense of grasslands. Regional increases in net primary productivity (NPP) (18–36%) and total carbon storage (3–13%) by 2080–2099 compared with the present‐day were common to all simulations. Despite decreases in soil carbon after 2050, seven out of nine simulations continued to show an annual net land carbon sink in the final decades of the 21st century because vegetation biomass continued to increase. The seasonal cycles of rainfall and soil moisture show future increases in wet season rainfall across the GCMs with generally little change in dry season rainfall. Based on the simulated present‐day climate and its future trends, the GCMs can be grouped into four broad categories. Overall, our model results suggest that East Africa, a populous and economically poor region, is likely to experience some ecosystem service benefits through increased precipitation, river runoff and fresh water availability. Resulting enhancements in NPP may lead to improved crop yields in some areas. Our results stand in partial contradiction to other studies that suggest possible negative consequences for agriculture, biodiversity and other ecosystem services caused by temperature increases.     

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan‐tropical belt (30°N–30°S). We analyzed decadal‐scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982–2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid‐1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time‐dependent regression parameters to study the time evolution of NDVI–climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature‐induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global‐scale effects of climate warming and associated moisture stresses.     

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States

A cross‐site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2‐CC, MIROC5, and MRI‐CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET‐BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO₂ effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce‐fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO₂ effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.     

Species distribution models predict temporal but not spatial variation in forest growth

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree‐ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate‐based habitat suitability with volume measurements from ~50‐year‐old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree‐ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree‐ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as ?.31. We conclude that tree responses to projected climate change are highly site‐specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.     

Climate–growth relationships of tropical tree species in West Africa and their potential for climate reconstruction

Most tropical regions are facing historical difficulties of generating biologically reconstructed long‐term climate records. Dendrochronology (tree‐ring studies) is a powerful tool to develop high‐resolution and exactly dated proxies for climate reconstruction. Owing to the seasonal variation in rainfall we expected the formation of annual tree rings in the wood of tropical West African tree species. In the central‐western part of Benin (upper Ouémé catchment, UOC) and in northeastern Ivory Coast (Comoé National Park, CNP) we investigated the relationship between climate (precipitation, sea surface temperature (SST)) and tree rings and show their potential for climate reconstruction. Wood samples of almost 200 trees belonging to six species in the UOC and CNP served to develop climate‐sensitive ring‐width chronologies using standard dendrochronological techniques. The relationship between local precipitation, monthly SST anomalies in the Gulf of Guinea, El Niño‐ Southern Oscillation (ENSO) and ring‐width indices was performed by simple regression analyses, two sample tests and cross‐spectral analysis. A low‐pass filter was used to highlight the decadal variability in rainfall of the UOC site. All tree species showed significant relationships with annual precipitation proving the existence of annual tree rings. ENSO signals could not be detected in the ring‐width patterns. For legume tree species at the UOC site significant relationships could be found between SST anomalies in the Gulf of Guinea indicating correlations at periods of 5.1–4.1 and 2.3 years. Our findings accurately show the relationship between tree growth, local precipitation and SST anomalies in the Gulf of Guinea possibly associated with worldwide SST patterns. A master chronology enabled the reconstruction of the annual precipitation in the UOC to the year 1840. Time series analysis suggest increasing arid conditions during the last 160 years which may have large impacts on the hydrological cycles and consequently on the ecosystem dynamics and the development of socio‐economic cultures and sectors in the Guinea‐Congolian/Sudanian region.     

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO₂, and few studies have considered how and to what extent climate change and CO₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP‐DGVM coupled with CLM3 and CLM4‐CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO₂ concentration. In the temperature sensitivity tests, warming reduced the global area‐averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP‐DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP‐DGVM and in semiarid and arid regions for CLM4‐CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO₂ concentration.     

Nonannual tree rings in a climate‐sensitive Prioria copaifera chronology in the Atrato River,Colombia

In temperate climates, tree growth dormancy usually ensures the annual nature of tree rings, but in tropical environments, determination of annual periodicity can be more complex. The purposes of the work are as follows: (1) to generate a reliable tree‐ring width chronology for Prioria copaifera Griseb. (Leguminoceae), a tropical tree species dwelling in the Atrato River floodplains, Colombia; (2) to assess the climate signal recorded by the tree‐ring records; and (3) to validate the annual periodicity of the tree rings using independent methods. We used standard dendrochronological procedures to generate the P. copaifera tree‐ring chronology. We used Pearson correlations to evaluate the relationship of the chronology with the meteorological records, climate regional indices, and gridded precipitation/sea surface temperature products. We also evaluated 24 high‐precision ¹⁴C measurements spread over a range of preselected tree rings, with assigned calendar years by dendrochronological techniques, before and after the bomb spike in order to validate the annual nature of the tree rings. The tree‐ring width chronology was statistically reliable, and it correlated significantly with local records of annual and October–December (OND) streamflow and precipitation across the upper river watershed (positive), and OND temperature (negative). It was also significantly related to the Oceanic Niño Index, Pacific Decadal Oscillation, and the Southern Oscillation Index, as well as sea surface temperatures over the Caribbean and the Pacific region. However, ¹⁴C high‐precision measurements over the tree rings demonstrated offsets of up to 40 years that indicate that P. copaifera can produce more than one ring in certain years. Results derived from the strongest climate–growth relationship during the most recent years of the record suggest that the climatic signal reported may be due to the presence of annual rings in some of those trees in recent years. Our study alerts about the risk of applying dendrochronology in species with challenging anatomical features defining tree rings, commonly found in the tropics, without an independent validation of annual periodicity of tree rings. High‐precision ¹⁴C measurements in multiple trees are a useful method to validate the identification of annual tree rings.     

Trait‐based climate vulnerability assessments in data‐rich systems: An application to eastern Bering Sea fish and invertebrate stocks

Trait‐based climate vulnerability assessments based on expert evaluation have emerged as a rapid tool to assess biological vulnerability when detailed correlative or mechanistic studies are not feasible. Trait‐based assessments typically view vulnerability as a combination of sensitivity and exposure to climate change. However, in some locations, a substantial amount of information may exist on system productivity and environmental conditions (both current and projected), with potential disparities in the information available for data‐rich and data‐poor stocks. Incorporating this level of detailed information poses challenges when conducting, and communicating uncertainty from, rapid vulnerability assessments. We applied a trait‐based vulnerability assessment to 36 fish and invertebrate stocks in the eastern Bering Sea (EBS), a data‐rich ecosystem. In recent years, the living marine resources of the EBS and Aleutian Islands have supported fisheries worth more than US $1 billion of annual ex‐vessel value. Our vulnerability assessment uses projections (to 2039) from three downscaled climate models, and graphically characterizes the variation in climate projections between climate models and between seasons. Bootstrapping was used to characterize uncertainty in specific biological traits and environmental variables, and in the scores for sensitivity, exposure, and vulnerability. The sensitivity of EBS stocks to climate change ranged from “low” to “high,” but vulnerability ranged between “low” and “moderate” due to limited exposure to climate change. Comparison with more detailed studies reveals that water temperature is an important variable for projecting climate impacts on stocks such as walleye pollock (Gadus chalcogrammus), and sensitivity analyses revealed that modifying the rule for determining vulnerability increased the vulnerability scores. This study demonstrates the importance of considering several uncertainties (e.g., climate projections, biological, and model structure) when conducting climate vulnerability assessments, and can be extended in future research to consider the vulnerability of user groups dependent on these stocks.     

Bird species richness is associated with phylogenetic relatedness,plant species richness,and altitudinal range in Inner Mongolia

Bird species richness is mediated by local, regional, and historical factors, for example, competition, environmental heterogeneity, contemporary, and historical climate. Here, we related bird species richness with phylogenetic relatedness of bird assemblages, plant species richness, topography, contemporary climate, and glacial‐interglacial climate change to investigate the relative importance of these factors. This study was conducted in Inner Mongolia, an arid and semiarid region with diverse vegetation types and strong species richness gradients. The following associated variables were included as follows: phylogenetic relatedness of bird assemblages (Net Relatedness Index, NRI), plant species richness, altitudinal range, contemporary climate (mean annual temperature and precipitation, MAT and MAP), and contemporary‐Last Glacial Maximum (LGM) change in climate (change in MAT and change in MAP). Ordinary least squares linear, simultaneous autoregressive linear, and Random Forest models were used to assess the associations between these variables and bird species richness across this region. We found that bird species richness was correlated negatively with NRI and positively with plant species richness and altitudinal range, with no significant correlations with contemporary climate and glacial–interglacial climate change. The six best combinations of variables ranked by Random Forest models consistently included NRI, plant species richness, and contemporary‐LGM change in MAT. Our results suggest important roles of local ecological factors in shaping the distribution of bird species richness across this semiarid region. Our findings highlight the potential importance of these local ecological factors, for example, environmental heterogeneity, habitat filtering, and biotic interactions, in biodiversity maintenance.     

Tree growth variation in the tropical forest: understanding effects of temperature,rainfall and CO2

Tropical forest responses to climatic variability have important consequences for global carbon cycling, but are poorly understood. As empirical, correlative studies cannot disentangle the interactive effects of climatic variables on tree growth, we used a tree growth model (IBTREE) to unravel the climate effects on different physiological pathways and in turn on stem growth variation. We parameterized the model for canopy trees of Toona ciliata (Meliaceae) from a Thai monsoon forest and compared predicted and measured variation from a tree‐ring study over a 30‐year period. We used historical climatic variation of minimum and maximum day temperature, precipitation and carbon dioxide (CO₂) in different combinations to estimate the contribution of each climate factor in explaining the inter‐annual variation in stem growth. Running the model with only variation in maximum temperature and rainfall yielded stem growth patterns that explained almost 70% of the observed inter‐annual variation in stem growth. Our results show that maximum temperature had a strong negative effect on the stem growth by increasing respiration, reducing stomatal conductance and thus mitigating a higher transpiration demand, and – to a lesser extent – by directly reducing photosynthesis. Although stem growth was rather weakly sensitive to rain, stem growth variation responded strongly and positively to rainfall variation owing to the strong inter‐annual fluctuations in rainfall. Minimum temperature and atmospheric CO₂ concentration did not significantly contribute to explaining the inter‐annual variation in stem growth. Our innovative approach – combining a simulation model with historical data on tree‐ring growth and climate – allowed disentangling the effects of strongly correlated climate variables on growth through different physiological pathways. Similar studies on different species and in different forest types are needed to further improve our understanding of the sensitivity of tropical tree growth to climatic variability and change.     

Climate change and annual survival in a temperate passerine: partitioning seasonal effects and predicting future patterns

Predicting climate change impacts on population size requires detailed understanding of how climate influences key demographic rates, such as survival. This knowledge is frequently unavailable, even in well‐studied taxa such as birds. In temperate regions, most research into climatic effects on annual survival in resident passerines has focussed on winter temperature. Few studies have investigated potential precipitation effects and most assume little impact of breeding season weather. We use a 19‐year capture–mark–recapture study to provide a rare empirical analysis of how variation in temperature and precipitation throughout the entire year influences adult annual survival in a temperate passerine, the long‐tailed tit Aegithalos caudatus. We use model averaging to predict longer‐term historical survival rates, and future survival until the year 2100. Our model explains 73% of the interannual variation in survival rates. In contrast to current theory, we find a strong precipitation effect and no effect of variation in winter weather on adult annual survival, which is correlated most strongly to breeding season (spring) weather. Warm springs and autumns increase annual survival, but wet springs reduce survival and alter the form of the relationship between spring temperature and annual survival. There is little evidence for density dependence across the observed variation in population size. Using our model to estimate historical survival rates indicates that recent spring warming has led to an upward trend in survival rates, which has probably contributed to the observed long‐term increase in the UK long‐tailed tit population. Future climate change is predicted to further increase survival, under a broad range of carbon emissions scenarios and probabilistic climate change outcomes, even if precipitation increases substantially. We demonstrate the importance of considering weather over the entire annual cycle, and of considering precipitation and temperature in combination, in order to develop robust predictive models of demographic responses to climate change. Synthesis Prediction of climate change impacts demands understanding of how climate influences key demographic rates. In our 19‐year mark‐recapture study of long‐tailed tits Aegithalos caudatus, weather explained 73% of the inter‐annual variation in adult survival; warm springs and autumns increased survival, wet springs reduced survival, but winter weather had little effect. Robust predictions thus require consideration of the entire annual cycle and should not focus solely on temperature. Unexpectedly, survival appeared not to be strongly density‐dependent, so we use historical climate data to infer that recent climate change has enhanced survival over the four decades in which the UK long‐tailed tit population has more than doubled. Furthermore, survival rates in this species are predicted to further increase under a wide range of future climate scenarios.     

Vulnerability of stream community composition and function to projected thermal warming and hydrologic change across ecoregions in the western United States

Shifts in biodiversity and ecological processes in stream ecosystems in response to rapid climate change will depend on how numerically and functionally dominant aquatic insect species respond to changes in stream temperature and hydrology. Across 253 minimally perturbed streams in eight ecoregions in the western USA, we modeled the distribution of 88 individual insect taxa in relation to existing combinations of maximum summer temperature, mean annual streamflow, and their interaction. We used a heat map approach along with downscaled general circulation model (GCM) projections of warming and streamflow change to estimate site‐specific extirpation likelihood for each taxon, allowing estimation of whole‐community change in streams across these ecoregions. Conservative climate change projections indicate a 30–40% loss of taxa in warmer, drier ecoregions and 10–20% loss in cooler, wetter ecoregions where taxa are relatively buffered from projected warming and hydrologic change. Differential vulnerability of taxa with key functional foraging roles in processing basal resources suggests that climate change has the potential to modify stream trophic structure and function (e.g., alter rates of detrital decomposition and algal consumption), particularly in warmer and drier ecoregions. We show that streamflow change is equally as important as warming in projected risk to stream community composition and that the relative threat posed by these two fundamental drivers varies across ecoregions according to projected gradients of temperature and hydrologic change. Results also suggest that direct human modification of streams through actions such as water abstraction is likely to further exacerbate loss of taxa and ecosystem alteration, especially in drying climates. Management actions to mitigate climate change impacts on stream ecosystems or to proactively adapt to them will require regional calibration, due to geographic variation in insect sensitivity and in exposure to projected thermal warming and hydrologic change.     

Geographical variation and environmental correlates of functional trait distributions in palms (Arecaceae) across the New World

Functional traits play a key role in driving biodiversity effects on ecosystem functioning. Here, we examine the geographical distributions of three key functional traits in New World palms (Arecaceae), an ecologically important plant group, and their relationships with current climate, soil and glacial–interglacial climate change. We combined range maps for the New World (N = 541 palm species) with data on traits (leaf size, stem height and fruit size), representing the leaf–height–seed plant strategy scheme of Westoby, to estimate median trait values for palm species assemblages in 110 × 110‐km grid cells. Spatial and non‐spatial multi‐predictor regressions were used with the Akaike Information Criterion to identify minimum adequate models. Present‐day seasonality in temperature and precipitation played a major role in explaining geographical variation of all traits. Mean annual temperature and annual precipitation were additionally important for median leaf size. Glacial–interglacial temperature change was the most important predictor for median fruit size. Large‐scale soil gradients played only a minor role overall. These results suggest that current climate (larger median trait values with increasing seasonality) and glacial–interglacial temperature change (larger median fruit size with increasing Quaternary temperature anomaly) are important drivers for functional trait distributions of New World palms. © 2015 The Linnean Society of London, Botanical Journal of the Linnean Society, 2015, 179 , 602–617.