A species' response to spatial climatic variation does not predict its response to climate change.

The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here, we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.

Adding Tree Rings to North America's National Forest Inventories: An Essential Tool to Guide Drawdown of Atmospheric CO2.

Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and-ultimately-the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.

Ecological forecasting of tree growth: Regional fusion of tree-ring and forest inventory data to quantify drivers and characterize uncertainty.

Robust ecological forecasting of tree growth under future climate conditions is critical to anticipate future forest carbon storage and flux. Here, we apply three ingredients of ecological forecasting that are key to improving forecast skill: data fusion, confronting model predictions with new data, and partitioning forecast uncertainty. Specifically, we present the first fusion of tree-ring and forest inventory data within a Bayesian state-space model at a multi-site, regional scale, focusing on Pinus ponderosa var. brachyptera in the southwestern US. Leveraging the complementarity of these two data sources, we parsed the ecological complexity of tree growth into the effects of climate, tree size, stand density, site quality, and their interactions, and quantified uncertainties associated with these effects. New measurements of trees, an ongoing process in forest inventories, were used to confront forecasts of tree diameter with observations, and evaluate alternative tree growth models. We forecasted tree diameter and increment in response to an ensemble of climate change projections, and separated forecast uncertainty into four different causes: initial conditions, parameters, climate drivers, and process error. We found a strong negative effect of fall-spring maximum temperature, and a positive effect of water-year precipitation on tree growth. Furthermore, tree vulnerability to climate stress increases with greater competition, with tree size, and at poor sites. Under future climate scenarios, we forecast increment declines of 22%-117%, while the combined effect of climate and size-related trends results in a 56%-91% decline. Partitioning of forecast uncertainty showed that diameter forecast uncertainty is primarily caused by parameter and initial conditions uncertainty, but increment forecast uncertainty is mostly caused by process error and climate driver uncertainty. This fusion of tree-ring and forest inventory data lays the foundation for robust ecological forecasting of aboveground biomass and carbon accounting at tree, plot, and regional scales, including iterative improvement of model skill.

Climate-driven, but dynamic and complex? A reconciliation of competing hypotheses for species' distributions.

Estimates of the percentage of species "committed to extinction" by climate change range from 15% to 37%. The question is whether factors other than climate need to be included in models predicting species' range change. We created demographic range models that include climate vs. climate-plus-competition, evaluating their influence on the geographic distribution of Pinus edulis, a pine endemic to the semiarid southwestern U.S. Analyses of data on 23,426 trees in 1941 forest inventory plots support the inclusion of competition in range models. However, climate and competition together only partially explain this species' distribution. Instead, the evidence suggests that climate affects other range-limiting processes, including landscape-scale, spatial processes such as disturbances and antagonistic biotic interactions. Complex effects of climate on species distributions-through indirect effects, interactions, and feedbacks-are likely to cause sudden changes in abundance and distribution that are not predictable from a climate-only perspective.

Statistical age determination of tree rings.

Dendrochronology, the study of annual rings formed by trees and woody plants, has important applications in research of climate and environmental phenomena of the past. Since its inception in the late 19th century, dendrochronology has not had a way to quantify uncertainty about the years assigned to each ring (dating). There are, however, many woody species and sites where it is difficult or impossible to delimit annual ring boundaries and verify them with crossdating, especially in the lowland tropics. Rather than ignoring dating uncertainty or discarding such samples as useless, we present for the first time a probabilistic approach to assign expected ages with a confidence interval. It is proven that the cumulative age in a tree-ring time series advances by an amount equal to the probability that a putative growth boundary is truly annual. Confidence curves for the tree stem radius as a function of uncertain ages are determined. A sensitivity analysis shows the effect of uncertainty of the probability that a recognizable boundary is annual, as well as of the number of expected missing boundaries. Furthermore, we derive a probabilistic version of the mean sensitivity of a dendrochronological time series, which quantifies a tree's sensitivity to environmental variation over time, as well as probabilistic versions of the autocorrelation and process standard deviation. A computer code in Mathematica is provided, with sample input files, as supporting information. Further research is necessary to analyze frequency patterns of false and missing boundaries for different species and sites.

Continental-scale tree-ring-based projection of Douglas-fir growth: Testing the limits of space-for-time substitution.

A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree-ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space-for-time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today. Here we evaluated an SFTS approach to projecting future growth of Douglas-fir (Pseudotsuga menziesii), a species that occupies an exceptionally large environmental space in North America. We fit a hierarchical mixed-effects model to capture ring-width variability in response to spatial and temporal variation in climate. We found opposing gradients for productivity and climate sensitivity with highest growth rates and weakest response to interannual climate variation in the mesic coastal part of Douglas-fir's range; narrower rings and stronger climate sensitivity occurred across the semi-arid interior. Ring-width response to spatial versus temporal temperature variation was opposite in sign, suggesting that spatial variation in productivity, caused by local adaptation and other slow processes, cannot be used to anticipate changes in productivity caused by rapid climate change. We thus substituted only climate sensitivities when projecting future tree growth. Growth declines were projected across much of Douglas-fir's distribution, with largest relative decreases in the semiarid U.S. Interior West and smallest in the mesic Pacific Northwest. We further highlight the strengths of mixed-effects modeling for reviving a conceptual cornerstone of dendroecology, Cook's 1987 aggregate growth model, and the great potential to use tree-ring networks and results as a calibration target for next-generation vegetation models.

Sampling bias overestimates climate change impacts on forest growth in the southwestern United States.

Climate-tree growth relationships recorded in annual growth rings have recently been the basis for projecting climate change impacts on forests. However, most trees and sample sites represented in the International Tree-Ring Data Bank (ITRDB) were chosen to maximize climate signal and are characterized by marginal growing conditions not representative of the larger forest ecosystem. We evaluate the magnitude of this potential bias using a spatially unbiased tree-ring network collected by the USFS Forest Inventory and Analysis (FIA) program. We show that U.S. Southwest ITRDB samples overestimate regional forest climate sensitivity by 41-59%, because ITRDB trees were sampled at warmer and drier locations, both at the macro- and micro-site scale, and are systematically older compared to the FIA collection. Although there are uncertainties associated with our statistical approach, projection based on representative FIA samples suggests 29% less of a climate change-induced growth decrease compared to projection based on climate-sensitive ITRDB samples.

Predicting the abundance of forest types across the eastern United States through inverse modelling of tree demography.

Global environmental change is expected to induce widespread changes in the geographic distribution and biomass of forest communities. Impacts have been projected from both empirical (statistical) and mechanistic (physiology-based) modelling approaches, but there remains an important gap in accurately predicting abundance across species' ranges from spatial variation in individual-level demographic processes. We address this issue by using a cohort-based forest dynamics model (CAIN) to predict spatial variation in the abundance of six plant functional types (PFTs) across the eastern United States. The model simulates tree-level growth, mortality, and recruitment, which we parameterized from data on both individual-level demographic rates and population-level abundance using Bayesian inverse modelling. Across a set of 1° grid cells, we calibrated local growth, mortality, and recruitment rates for each PFT to obtain a close match between predicted age-specific PFT basal area in forest stands and that observed in 46,603 Forest Inventory and Analysis plots. The resulting models produced a strong fit to PFT basal area across the region (R2  = 0.66-0.87), captured successional changes in PFT composition with stand age, and predicted the overall stem diameter distribution well. The mortality rates needed to accurately predict basal area were consistently higher than observed mortality, possibly because sampling effects led to biased individual-level mortality estimates across spatially heterogeneous plots. Growth and recruitment rates did not show consistent directional changes from observed values. Relative basal area was most strongly influenced by recruitment processes, but the effects of growth and mortality tended to increase as stands matured. Our study illustrates how both top-down (population-level) and bottom-up (individual-level) data can be combined to predict variation in abundance from size, environmental, and competitive effects on tree demography. Evidence for how demographic processes influence variation in abundance, as provided by our model, can help in understanding how these forests may respond to future environmental change.

Towards Process-based Range Modeling of Many Species.

Understanding and forecasting species' geographic distributions in the face of global change is a central priority in biodiversity science. The existing view is that one must choose between correlative models for many species versus process-based models for few species. We suggest that opportunities exist to produce process-based range models for many species, by using hierarchical and inverse modeling to borrow strength across species, fill data gaps, fuse diverse data sets, and model across biological and spatial scales. We review the statistical ecology and population and range modeling literature, illustrating these modeling strategies in action. A variety of large, coordinated ecological datasets that can feed into these modeling solutions already exist, and we highlight organisms that seem ripe for the challenge.

Observed forest sensitivity to climate implies large changes in 21st century North American forest growth.

Predicting long-term trends in forest growth requires accurate characterisation of how the relationship between forest productivity and climatic stress varies across climatic regimes. Using a network of over two million tree-ring observations spanning North America and a space-for-time substitution methodology, we forecast climate impacts on future forest growth. We explored differing scenarios of increased water-use efficiency (WUE) due to CO2 -fertilisation, which we simulated as increased effective precipitation. In our forecasts: (1) climate change negatively impacted forest growth rates in the interior west and positively impacted forest growth along the western, southeastern and northeastern coasts; (2) shifting climate sensitivities offset positive effects of warming on high-latitude forests, leaving no evidence for continued 'boreal greening'; and (3) it took a 72% WUE enhancement to compensate for continentally averaged growth declines under RCP 8.5. Our results highlight the importance of locally adapted forest management strategies to handle regional differences in growth responses to climate change.

Are species' responses to global change predicted by past niche evolution?

Predicting how and when adaptive evolution might rescue species from global change, and integrating this process into tools of biodiversity forecasting, has now become an urgent task. Here, we explored whether recent population trends of species can be explained by their past rate of niche evolution, which can be inferred from increasingly available phylogenetic and niche data. We examined the assemblage of 409 European bird species for which estimates of demographic trends between 1970 and 2000 are available, along with a species-level phylogeny and data on climatic, habitat and trophic niches. We found that species' proneness to demographic decline is associated with slow evolution of the habitat niche in the past, in addition to certain current-day life-history and ecological traits. A similar result was found at a higher taxonomic level, where families prone to decline have had a history of slower evolution of climatic and habitat niches. Our results support the view that niche conservatism can prevent some species from coping with environmental change. Thus, linking patterns of past niche evolution and contemporary species dynamics for large species samples may provide insights into how niche evolution may rescue certain lineages in the face of global change.

Estimating covariation between vital rates: a simulation study of connected vs. separate generalized linear mixed models (GLMMs).

Covariation between vital rates is recognized as an important pattern to be accounted for in demographic modeling. We recently introduced a model for estimating vital rates and their covariation as a function of known and unknown effects, using generalized linear mixed models (GLMM's) implemented in a hierarchical Bayesian framework (Evans et al., 2010) In particular, this model included a model-wide year effect (YEAR) influencing all vital rates, which we used to estimate covariation between vital rates due to exogenous factors not directly included in the model. This YEAR effect connected the GLMMs of vital rates into one large model; we refer to this as the "connected GLMMs" approach. Here we used a simulation study to evaluate the performance of a simplified version of this model, compared to separate GLMMs of vital rates, in terms of their ability to estimate correlations between vital rates. We simulated data from known relationships between vital rates and a covariate, inducing correlations among the vital rates. We then estimated those correlations from the simulated data using connected vs. separate GLMMs with year random effects. We compared precision and accuracy of estimated vital rates and their correlations under three scenarios of the pervasiveness of the exogenous effect (and thus true correlations). The two approaches provide equally good point estimates of vital rate parameters, but connected GLMMs provide better estimates of covariation between vital rates than separate GLMMs, both in terms of accuracy and precision, when the common influence on vital rates is pervasive. We discuss the situations where connected GLMMs might be best used, as well as further areas of investigation for this approach.

Extreme environments select for reproductive assurance: evidence from evening primroses (Oenothera).

Competing evolutionary forces shape plant breeding systems (e.g. inbreeding depression, reproductive assurance). Which of these forces prevails in a given population or species is predicted to depend upon such factors as life history, ecological conditions, and geographical context. Here, we examined two such predictions: that self-compatibility should be associated with the annual life history or extreme climatic conditions. We analyzed data from a clade of plants remarkable for variation in breeding system, life history and climatic conditions (Oenothera, sections Anogra and Kleinia, Onagraceae). We used a phylogenetic comparative approach and Bayesian or hybrid Bayesian tests to account for phylogenetic uncertainty. Geographic information system (GIS)-based climate data and ecological niche modeling allowed us to quantify climatic conditions. Breeding system and reproductive life span are not correlated in Anogra and Kleinia. Instead, self-compatibility is associated with the extremes of temperature in the coldest part of the year and precipitation in the driest part of the year. In the 60 yr since this pattern was anticipated, this is the first demonstration of a relationship between the evolution of self-compatibility and climatic extremes. We discuss possible explanations for this pattern and possible implications with respect to anthropogenic climate change.

Breeding system variation in 10 evening primroses (Oenothera sections Anogra and Kleinia; Onagraceae).

PREMISE OF THE STUDY: We examined two accounts of the relationship between breeding system and life history variation in a clade of evening primroses (Oenothera, Onagraceae): (1) selection for reproductive assurance should generate an association between self-compatibility and monocarpy and (2) phylogenetic conservatism leads to retention of breeding system and life history traits among closely related taxa. • METHODS: We performed over 4000 hand pollinations under greenhouse conditions to determine the compatibility of 10 Oenothera taxa (sections Anogra [17 taxa] and Kleinia [2 taxa)] for which breeding systems had not previously been reported. We used generalized linear mixed models to evaluate the influence of pollination treatment, parents, and population on fruiting success. • KEY RESULTS: Among the taxa tested, six were self-incompatible, two were variable in compatibility, and two were self-compatible. We combined these data with published studies in Anogra and Kleinia and mapped breeding system and life history onto a published phylogeny. • CONCLUSIONS: We found no evidence for phylogenetic conservatism, but detected considerable evolutionary lability in both traits. Additionally, we found no evidence for a consistent relationship between breeding system and life history. Only eight of 19 taxa followed the predicted association between self-incompatibility and polycarpy vs. self-compatibility and monocarpy. Instead, many taxa have retained self-incompatibility, regardless of monocarpy or polycarpy.

Ecological conditions affect evolutionary trajectory in a predator-prey system.

The arms race of adaptation and counter adaptation in predator-prey interactions is a fascinating evolutionary dynamic with many consequences, including local adaptation and the promotion or maintenance of diversity. Although such antagonistic coevolution is suspected to be widespread in nature, experimental documentation of the process remains scant, and we have little understanding of the impact of ecological conditions. Here, we present evidence of predator-prey coevolution in a long-term experiment involving the predatory bacterium Bdellovibrio bacteriovorus and the prey Pseudomonas fluorescens, which has three morphs (SM, FS, and WS). Depending on experimentally applied disturbance regimes, the predator-prey system followed two distinct evolutionary trajectories, where the prey evolved to be either super-resistant to predation (SM morph) without counter-adaptation by the predator, or moderately resistant (FS morph), specialized to and coevolving with the predator. Although predation-resistant FS morphs suffer a cost of resistance, the evolution of extreme resistance to predation by the SM morph was apparently unconstrained by other traits (carrying capacity, growth rate). Thus we demonstrate empirically that ecological conditions can shape the evolutionary trajectory of a predator-prey system.

Climate, niche evolution, and diversification of the "bird-cage" evening primroses (Oenothera, sections Anogra and Kleinia).

We integrate climatic niche models and dated phylogenies to characterize the evolution of climatic niches in Oenothera sections Anogra and Kleinia (Onagraceae), and from that we make inferences on diversification in relation to climate. The evolution of climatic tolerances in Anogra + Kleinia has been heterogeneous, across phylogenetic groups and across different dimensions of climate. All the extant taxa occur in semiarid to arid conditions (annual precipitation of 10.1-49.1 cm and high temperatures in the warmest month of 28.5 degrees-40.1 degrees C), but there is striking variation among taxa in their climatic tolerances, especially temperature (minimum temperatures in the coldest month of -14.0 degrees to 5.3 degrees C) and summer versus winter precipitation (precipitation in the warmest quarter of 0.6-19.4 cm). Climatic disparity is especially pronounced in two subclades (californica, deltoides) that radiated in the southwestern United States and California, apparently including both divergent and convergent evolution of climatic tolerances. This niche evolution is remarkable, given the probable timescale of the radiation (approximately 1 million years). We suggest that the spatiotemporal climatic heterogeneity of western North America has served as a driver of diversification. Our data are also consistent with Axelrod's hypothesis that the spread of arid conditions in western North America stimulated diversification of arid-adapted lineages.

Bet hedging via seed banking in desert evening primroses (Oenothera, Onagraceae): demographic evidence from natural populations.

Bet hedging is one solution to the problem of an unpredictably variable environment: fitness in the average environment is sacrificed in favor of lower variation in fitness if this leads to higher long-run stochastic mean fitness. While bet hedging is an important concept in evolutionary ecology, empirical evidence that it occurs is scant. Here we evaluate whether bet hedging occurs via seed banking in natural populations of two species of desert evening primroses (Oenothera, Onagraceae), one annual and one perennial. Four years of data on plants and 3 years of data on seeds yielded two transitions for the entire life cycle. One year was exceptionally dry, leading to reproductive failure in the sample areas, and the other was above average in precipitation, leading to reproductive success in four of five populations. Stochastic simulations of population growth revealed patterns indicative of bet hedging via seed banking, particularly in the annual populations: variance in fitness and fitness in the average environment were lower with seed banking than without, whereas long-run stochastic mean fitness was higher with seed banking than without across a wide range of probabilities of the wet year. This represents a novel, unusually rigorous demonstration of bet hedging from field data.

Climate and life-history evolution in evening primroses (Oenothera, Onagraceae): a phylogenetic comparative analysis.

Evolutionary ecologists have long sought to understand the conditions under which perennial (iteroparous) versus annual (semelparous) plant life histories are favored. We evaluated the idea that aridity and variation in the length of droughts should favor the evolution of an annual life history, both by decreasing adult survival and by increasing the potential for high seedling survival via reduced plant cover. We calculated phylogenetically independent contrasts of climate with respect to life history in a clade of winter-establishing evening primroses (sections Anogra and Kleinia; Oenothera; Onagraceae), which includes seven annuals, 12 perennials, and two variable taxa. Climate variables were quantified from long-term records at weather stations near collection localities. To explicitly account for phylogenetic uncertainty, contrasts were calculated on a random sample of phylogenetic trees from the posterior distribution of a Bayesian analysis of DNA sequence data. Statements of association are based on comparing the per-tree mean contrast, which has a null expectation of zero, to a set of per-tree mean contrasts calculated on the same trees, after randomizing the climate data. As predicted, increased annual aridity, increased annual potential evapotranspiration, and decreased annual precipitation were associated with transitions to the annual habit, but these trends were not significantly different from the null pattern. Transitions to the annual habit were not significantly associated with increases in one measure of aridity in summer nor with increased summer drought, but they were associated with significantly increased maximum summer temperatures. In winter, increased aridity and decreased precipitation were significantly associated with transitions to the annual habit. Changes in life history were not significantly associated with changes in the coefficient of variation of precipitation, either on an annual or seasonal (summer vs. winter) basis. Though we cannot attribute causality on the basis of a correlational, historical study, our results are consistent with the idea that increased heat and drought at certain times of the year favor the evolution of the annual habit. Increased heat in summer may cause adult survival to decline, while increased aridity and decreased precipitation in the season of seedling recruitment (winter) may favor a drought-avoiding, short-lived annual strategy. Not all of the predicted patterns were observed: the capability for drought-induced dormancy may preclude change in habit in response to summer drought in our study group.