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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.

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.

Drought legacies in radial tree growth are an important feature of variability in biomass accumulation and are widely used to characterize forest resilience to climate change. Defined as a deviation from normal growth, the statistical significance of legacy effects depends on the definition of “normal”—expected growth under average conditions—which has not received sufficient scrutiny. We re-examined legacy effect analyses using the International Tree-Ring Data Bank (ITRDB) and then produced synthetic tree-ring data to disentangle four key variables influencing the magnitude of legacy effects. We hypothesized that legacy effects (i) are mainly influenced by the auto-correlation of the radial growth time series (phi), (ii) depend on climate-growth cross-correlation (rho), (iii) are directly proportional to the inherent variability of the growth time series (standard deviation, SD), and (iv) scale with the chosen extreme event threshold. Using a data simulation approach, we were able to reproduce observed lag patterns, demonstrating that legacy effects are a direct outcome of ubiquitous biological memory. We found that stronger legacy effects for conifers compared to angiosperms is a consequence of their higher auto-correlation, and that the detectability of legacy effects following rare drought events at individual sites is compromised by strong background stochasticity. Synthesis. We propose two pathways forward to improve the assessment and interpretation of legacy effects: First, we highlight the need to account for auto-correlated residuals of climate-growth regression models a posteriori, thereby retrospectively adjusting expectations for “normal” growth variability. Alternatively, we recommend including lagged climate variables in regression models a priori. By doing so, the magnitude of detected legacy effects is greatly reduced and biological memory is directly attributed to antecedent climatic drivers. We argue that future analyses should focus on understanding the functional reasons for how and why key statistical parameters describing this biological memory differ across species and sites. These two pathways should also stimulate improved process-based representation of vegetation carbon dynamics in mechanistic models.

Biogenic time series data can be generated in a single sampling effort, offering an appealing alternative to the slow process of revisiting or recapturing individuals to measure demographic rates. Annual growth rings formed by trees and in the ear bones of fish (i.e. otoliths) are prime examples of such biogenic time series. They offer insight into not only the process of growth but also birth, death, movement, and evolution, sometimes at uniquely deep temporal and large spatial scales, well beyond 5–30 years of data collected in localised study areas. This chapter first reviews the fundamentals of how tree-ring and otolith time series data are developed and analysed (i.e. dendrochronology and sclerochronology), then surveys growth rings in other organisms, along with microstructural or microcompositional variation in growth rings, and other records of demographic processes. It highlights the answers to demographic questions revealed by these time series data, such as the influence of environmental (atmospheric or ocean) conditions, competition, and disturbances on demographic processes, and the genetic versus plastic basis of individual growth and traits that influence growth. Lastly, it considers how spatial networks of biogenic, annually resolved time series data can offer insights into the importance of macrosystem atmospheric and ocean dynamics on multispecies, trophic dynamics. The authors encourage demographers to integrate the complementary information contained in biogenic time series data into population models to better understand the drivers of vital rate variation and predict the impacts of global change.

Warming alters the variability and trajectories of tree growth around the world by intensifying or alleviating energy and water limitation. This insight from regional to global-scale research emphasizes the susceptibility of forest ecosystems and resources to climate change. However, globally-derived trends are not necessarily meaningful for local nature conservation or management considerations, if they lack specific information on present or prospective tree species. This is particularly the case towards the edge of their distribution, where shifts in growth trajectories may be imminent or already occurring.Importantly, the geographic and bioclimatic space (or “niche”) occupied by a tree species is not only constrained by climate, but often reflects biotic pressure such as competition for resources with other species. This aspect is underrepresented in many species distribution models that define the niche as a climatic envelope, which is then allowed to shift in response to changes in ambient conditions. Hence, distinguishing climatic from competitive niche boundaries becomes a central challenge to identifying areas where tree species are most susceptible to climate change.Here we employ a novel concept to characterize each position within a species’ bioclimatic niche based on two criteria: a climate sensitivity index (CSI) and a habitat suitability index (HSI). The CSI is derived from step-wise multiple linear regression models that explain variability in annual radial tree growth as a function of monthly climate anomalies. The HSI is based on an ensemble of five species distribution models calculated from a combination of observed species occurrences and twenty-five bioclimatic variables. We calculated these two indices for 11 major tree species across the Northern Hemisphere.The combination of climate sensitivity and habitat suitability indicated hotspots of change, where tree growth is mainly limited by competition (low HSI and low CSI), as well as areas that are particularly sensitive to climate variability (low HSI and high CSI). In the former, we expect that forest management geared towards adjusting the competitive balance between several candidate species will be most effective under changing environmental conditions. In the latter areas, selecting particularly drought-tolerant accessions of a given species may reduce forest susceptibility to the predicted warming and drying.

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.

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.

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.

Better understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources, tree-ring and forest inventory data. A Bayesian hierarchical model was used to gain inference on the effects of many factors on tree growth-individual tree size, climate, biophysical conditions, stand-level competitive environment, tree-level canopy status, and forest management treatments-using both diameter at breast height (dbh) and tree-ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. This model was applied to a data set of similar to 130 increment cores and similar to 500 repeat measurements of dbh at a single site in the Jemez Mountains of north-central New Mexico, USA. The tree-ring data serve as the only source of information on how annual growth responds to climate variation, whereas both data types inform non-climatic effects on growth. Inferences from the model included positive effects on growth of seasonal precipitation, wetness index, and height ratio, and negative effects of dbh, seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model were confirmed by a den-droclimatic analysis. Combining the two data sources substantially reduced uncertainty about non-climate fixed effects on radial increments. This demonstrates that forest inventory data measured on many trees, combined with tree-ring data developed for a small number of trees, can be used to quantify and parse multiple influences on absolute tree growth. We highlight the kinds of research questions that can be addressed by combining the high-resolution information on climate effects contained in tree rings with the rich tree-and stand-level information found in forest inventories, including projection of tree growth under future climate scenarios, carbon accounting, and investigation of management actions aimed at increasing forest resilience.

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.

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.

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.

Understanding and predicting changes in the abundance of natural populations is a central goal of ecology. These changes are influenced by a variety of exogenous processes (weather, floods, fire); variation in these processes leads to variation in vital rates (survival, fecundity) that may be positively or negatively correlated across the life cycle. We used 20 years of data and a hierarchical Bayesian model to estimate vital rates and their covariation in an endangered plant, Dicerandra frutescens ssp. frutescens (Lamiaceae), as a function of time since fire and random year effects. Germination and the number of flowering branches declined with time since fire, and all plants were increasingly likely to become nonreproductive with time since fire. Time since fire had negative effects on survival of seedlings, vegetative plants, and small flowering plants, and positive effects on survival of medium and large flowering plants. Model comparison strongly supported inclusion of time-since-fire effects and weakly supported inclusion of year effects influencing all vital rates (''model-wide'' year effects). We used samples from the joint posterior distribution of model parameters to simulate population dynamics as a function of fire regime and year-to-year environmental variation. These simulations suggest that populations of Dicerandra frutescens ssp. frutescens are least likely to go extinct if the average time between fires is ;24-30 years. The design of the simulations allowed us to distinguish variation in stochastic population growth associated with process variability (fire, year effects, and demographic stochasticity) from variation associated with parameter uncertainty (finite amounts of data). Even with 20 years of data, half or more of the uncertainty in population growth rates was due to parameter uncertainty. This hierarchical Bayesian population viability analysis illustrates a general analytical framework for (1) estimating vital rates as a function of an exogenous environmental factor, (2) accounting for covariation among vital rates, and (3) simulating population dynamics as a function of stochastic environmental processes while taking into account uncertainty about their effects. We discuss future areas of development 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.

Restoration ecologists are tasked with the challenge of returning an ecological system to a configuration that approximates its natural state (Hobbs and Norton 1996, 2001). Restoring any altered ecosystem comprises a sizeable challenge in that it is critical to determine the appropriate target for restoration (chap. 1), especially prior to disturbances such as novel anthropogenic impacts as well as the relevant scales thereof. Determining the target for restoration involves four main considerations: (1) the “natural” state of the system might include pre-European human influences (e.g., widespread colonialism); (2) change is normal in ecological systems (i.e., systems exhibit a historical range of variation in disturbance regimes and species composition); (3) some system changes are completely irreversible (e.g., legacy effects), or nearly so (e.g., ecological tipping points); and (4) stochasticity plays a crucial role in shaping ecosystem state (Jackson and Hobbs 2009). Moreover, some historically important steady states may not be attainable because of legacy effects such as the emergence of novel configurations and the spread of invasive species (e.g., establishing new biotic interactions and ecosystems; Hobbs et al. 2014), prevalence of historical contingencies (e.g., immigration of despotic breeders to isolated populations; Hedrick et al. 2014), or altered boundary constraints (e.g., climatic thresholds such as critical thermal maxima; Lee and Rinne 1980). Nevertheless, historical knowledge of ecosystems may still play a critical role in the success of future restoration efforts in the face of modern-day ecological novelties (Higgs et al. 2014).

Madagascar is renowned for its impressive species richness and high level of endemism, which led to the island being recognized as one of the world’s most important biodiversity hotspots. As in many other regions, Madagascar’s biodiversity is highly threatened by unsustainable anthropogenic disturbance, leading to widespread habitat loss and degradation. Although the country has significantly expanded its network of protected areas (PAs), current protocols for identifying priority areas are based on traditional measures that could fail to ensure maximal inclusion of the country’s biodiversity. In this study, we use Madagascar’s largest endemic plant family, Sarcolaenaceae, as a model to identify areas with high diversity and to explore the potential conservation importance of these areas. Using phylogenetic information and species distribution data, we employ three metrics to study geographic patterns of diversity: species richness, Phylogenetic Diversity (PD) and Mean Phylogenetic Diversity (MPD). The distributions of species richness and PD show considerable spatial congruence, with the highest values found in a narrow localized region in the central-northern portion of the eastern humid forest. MPD is comparatively uniform spatially, suggesting that the balanced nature of the phylogenetic tree plays a role in the observed congruence between PD and species richness. The current network of PAs includes a large part of the family’s biodiversity, and three PAs (Ankeniheny Zahamena Forest Corridor, the Bongolava Forest Corridor and the Itremo Massif) together contain almost 85 % of the PD. Our results suggest that PD could be a valuable source of complementary information for determining the contribution of Madagascar’s existing network of PAs toward protecting the country’s biodiversity and for identifying priority areas for the establishment of new parks and reserves.

Managing populations, either for conservation, harvesting, or control, requires a mechanistic or semi-mechanistic understanding of population dynamics. Here, we investigate how time-since-fire affects demographic transitions in an endangered plant, Dicerandra frutescens ssp. frutescens (Lamiaceae), which is specialized to gaps created by fire. We used a hierarchical Bayesian model to estimate transition probabilities (i.e., the elements of population projection matrices) as a function of time-since-fire and random effects, from 13 years of data on marked individuals in five populations. Using a standard Bayesian criterion to compare models, we find that death becomes increasingly probable and progression increasingly improbable with time-since-fire. The magnitude of some of the time-since-fire effects is substantial: death is 3–5 times more likely for flowering plants >6 years versus 3–6 years post-fire, 3-step progression is almost 7 times less likely, and large flowering plants are more than 6 times more likely to stop flowering. These insights inspire new hypotheses about the underlying cause of decline with time-since-fire, and how it can be managed. Our approach can be used by others who wish to model the effect of an exogenous factor on demography, while rigorously accounting for uncertainty and variability.

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.

Patterns of adaptation in response to environmental variation are central to our understanding of biodiversity, but predictions of how and when broad-scale environmental conditions such as climate affect organismal form and function remain incomplete. Succulent plants have evolved in response to arid conditions repeatedly, with various plant organs such as leaves, stems, and roots physically modified to increase water storage. Here, we investigate the role played by climate conditions in shaping the evolution of succulent forms in a plant clade endemic to Madagascar and the surrounding islands, part of the hyper-diverse genus Euphorbia (Euphorbiaceae). We used multivariate ordination of 19 climate variables to identify links between particular climate variables and three major forms of succulence—succulent leaves, cactiform stem succulence, and tubers. We then tested the relationship between climatic conditions and succulence, using comparative methods that account for shared evolutionary history. We confirm that plant water storage is associated with the two components of aridity, temperature, and precipitation. Cactiform stem succulence, however, is not prevalent in the driest environments, countering the widely held view of cactiforms as desert icons. Instead, leaf succulence and tubers are significantly associated with the lowest levels of precipitation. Our findings provide a clear link between broad-scale climatic conditions and adaptation in land plants, and new insights into the climatic conditions favoring different forms of succulence. This evidence for adaptation to climate raises concern over the evolutionary future of succulent plants as they, along with other organisms, face anthropogenic climate change. (Adaptation; climate; comparative analysis; Euphorbia; ordination; phylogeny.)

Carter’s mustard ( Warea carteri) is an endangered, fire-stimulated annual endemic of the Lake Wales Ridge, Florida, USA. This species is characterized by seed banks and large fluctuations in plant numbers, with increases occurring in postdisturbance habitat. We investigated the mating system, patterns of isozyme variation, and effective population sizes of W. carteri to better understand its population biology and to comment on reserve designs and management proposals relevant to this species. Warea carteri is self-compatible and autogamous, and probably largely selfing. Measures of genetic variation in W. carteri were lower than values reported for species with similar ecological and life history traits (6.6% of loci polymorphic within populations, 1.87 alleles per polymorphic locus, and 0.026 and 0.018 expected and observed heterozygosity, respectively). The high average value for Nei’s genetic identity (0.989) reflects the paucity of genetic diversity. Genetic variation within populations was not correlated with aboveground population size, effective population size estimates (N e), or recent disturbance history. Much of the diversity detected was found among populations (FST 5 0.304). A significant cline in allele frequencies at one locus and a significant negative correlation between geographic distance and Nei’s genetic identity also point to spatial organization of genetic diversity. As a result we propose that reserve design should include the entire geographic range of W. carteri. We also recommend that the natural fire regime be mimicked.

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.

 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 infl uence 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.

Summary • 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.

Many species produce eggs or seeds that refrain from hatching despite developmental preparedness and favorable environmental conditions. Instead, these propagules hatch in intervals over long periods. Such variable hatch or germination tactics may represent bet-hedging against future catastrophes. Empiricists have independently recognized these approaches in diverse species. Terms such as seed banking, delayed egg hatching, and embryonic diapause have been used to describe these tactics, but connections between fields of study have been rare. Here we suggest a general term, germ banking, to incorporate all previous terms, unifying many seemingly disparate biological strategies under a single definition. We define the phenomenon of germ banking and use several biological examples to illustrate it. We then discuss the different causes of variation in emergence timing, delineate which constitute germ banking, and distinguish between germ banking and optimal timing of diapause. The wide-ranging consequences of germ banking are discussed, including modification of the age structure of a population, the alteration of microevolutionary dynamics, the migration of alleles from the past, the maintenance of genetic and species diversity, and the promotion of species coexistence. We end by posing questions to direct future research.

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.

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.