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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−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., Sampling strategies may bias tree-ring datasets to not accurately represent the regional response to climate change. Here, Klesse et al. use a new representative dataset to show that the International Tree-Ring Data Bank in the U.S. Southwest overestimates climate sensitivity of forests by 41–59%

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.

Integral Projection Models (IPMs) use information on how an individual's state influences its vital rates - survival, growth and reproduction - to make population projections. IPMs are constructed from regression models predicting vital rates from state variables (e.g., size or age) and covariates (e.g., environment). By combining regressions of vital rates, an IPM provides mechanistic insight into emergent ecological patterns such as population dynamics, species geographic distributions, or life history strategies.Here, we review important resources for building IPMs and provide a comprehensive guide, with extensive R code, for their construction. IPMs can be applied to any stage-structured population; here we illustrate IPMs for a series of plant life histories of increasing complexity and biological realism, highlighting the utility of various regression methods for capturing biological patterns. We also present case studies illustrating how IPMs can be used to predict species’ geographic distributions and life history strategies.IPMs can represent a wide range of life histories at any desired level of biological detail. Much of the strength of IPMs lies in the strength of regression models. Many subtleties arise when scaling from vital rate regressions to population-level patterns, so we provide a set of diagnostics and guidelines to ensure that models are biologically plausible. Moreover, IPMs can exploit a large existing suite of analytical tools developed for Matrix Projection Models.

a b s t r a c t 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.

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.

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.

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 evapo- transpiration, 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.

We used hand-pollination experiments to test the mating systems of and evaluate limits to seed production in two federally listed endangered plants endemic to the Lake Wales Ridge in Florida, USA: Dicerandra frutescens Shinners ssp. frutescens Huck and D. christmanii Huck and Judd (Lamiaceae). Both are nonclonal, short-lived perennials found in gaps created by disturbance (e.g., fire, roads) in Florida scrub. We found that both species require pollen and insect visitation to produce seeds. We detected pollinator limitation of seed production in D. christmanii but not D. frutescens ssp. fru- tescens, which we suggest is a function of time-since-disturbance or gap size rather than intrinsic differences between the two species. Both species are self-compatible. Inbreeding depression reduced seed set by 60% in D. frutescens ssp. frutescens but did not occur in D. christmanii. We conclude that pollinator limitation (in fire-suppressed populations of both species) and inbreeding depression (in D. frutescens ssp. frutescens) have the potential to limit seed production in these seed-dependent, rare species. Appropriate fire management should mitigate both of these risks, by maintaining large popu- lations and conditions attractive to pollinators. Although these two species are very similar in re- productive biology, comparisons with other Florida scrub endemics and with rare plants in general suggest that potential threats to conservation via reproductive biology are difficult to predict, depending on combinations of ecology, life-history, and phylogenetic history.

We investigated the reproductive biology of three plants endemic to rosemary scrub habitats on the Lake Wales Ridge of Florida, USA. We used hand-pollination experiments and observations of flowers and their insect visitors to determine their mating systems and pollination. Fruit or seed set after self pollination was 94, 97, and 8% of fruit or seed set after cross pollination in Eryngium cuneifolium (Apiaceae), Hypericum cumulicola (Hypericaceae), and Liatris ohlingerae (Asteraceae) respectively, indicating that the first two are self-compatible and the last is obligately outcrossing. All three depend on insects for seed production (4–7% fruit or seed set without insects). Diverse insects visit flowers of E. cuneifolium (101 species recorded), whereas L. ohlingerae is visited predominantly by butterflies and H. cumulicola by one genus of bees (Dialictus, Halictidae). Our data indicate pollinator visitation does not currently limit seed production in E. cuneifolium or H. cumulicola, but does in L. ohlingerae. Despite the features they share (habit, habitat, disturbance regime), we found unique aspects of these species’ reproductive biology yielding unique risks to population viability. We suggest that multispecies recovery plans must consider several aspects of the biology of species with superficial similarities to be successful. # 2003 Elsevier Science Ltd. All rights reserved.

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.

The demand for large-scale and long-term information on tree growth is increasing rapidly as environmental change research strives to quantify and forecast the impacts of continued warming on forest ecosystems. This demand, combined with the now quasi-global availability of tree-ring observations, has inspired researchers to compile large tree-ring networks to address continental or even global-scale research questions. However, these emergent spatial objectives contrast with paleo-oriented research ideas that have guided the development of many existing records. A series of challenges related to how, where, and when samples have been collected is complicating the transition of tree rings from a local to a global resource on the question of tree growth. Herein, we review possibilities to scale tree-ring data (A) from the sample to the whole tree, (B) from the tree to the site, and (C) from the site to larger spatial domains. Representative tree-ring sampling supported by creative statistical approaches is thereby key to robustly capture the heterogeneity of climate-growth responses across forested landscapes. We highlight the benefits of combining the temporal information embedded in tree rings with the spatial information offered by forest inventories and earth observations to quantify tree growth and its drivers. In addition, we show how the continued development of mechanistic tree-ring models can help address some of the non-linearities and feedbacks that complicate making inference from tree-ring data. By embracing scaling issues, the discipline of dendrochronology will greatly increase its contributions to assessing climate impacts on forests and support the development of adaptation strategies.