Douglas‐fir plantations in Europe: a retrospective test of assisted migration to address climate change

We evaluate genetic test plantations of North American Douglas‐fir provenances in Europe to quantify how tree populations respond when subjected to climate regime shifts, and we examined whether bioclimate envelope models developed for North America to guide assisted migration under climate change can retrospectively predict the success of these provenance transfers to Europe. The meta‐analysis is based on long‐term growth data of 2800 provenances transferred to 120 European test sites. The model was generally well suited to predict the best performing provenances along north–south gradients in Western Europe, but failed to predict superior performance of coastal North American populations under continental climate conditions in Eastern Europe. However, model projections appear appropriate when considering additional information regarding adaptation of Douglas‐fir provenances to withstand frost and drought, even though the model partially fails in a validation against growth traits alone. We conclude by applying the partially validated model to climate change scenarios for Europe, demonstrating that climate trends observed over the last three decades warrant changes to current use of Douglas‐fir provenances in plantation forestry throughout Western and Central Europe.     

Effects of ecohydrological variables on current and future ranges,local suitability patterns,and model accuracy in big sagebrush

Forecasting of species and ecosystem responses to novel conditions, including climate change, is one of the major challenges facing ecologists at the start of the 21st century. Climate change studies based on species distribution models (SDMs) have been criticized because they extend correlational relationships beyond the observed data. Here, we compared conventional climate‐based SDMs against ecohydrological SDMs that include information from process‐based simulations of water balance. We examined the current and future distribution of Artemisia tridentata (big sagebrush) representing sagebrush ecosystems, which are widespread in semiarid western North America. For each approach, we calculated ensemble models from nine SDM methods and tested accuracy of each SDM with a null distribution. Climatic conditions included current conditions for 1970–1999 and two IPCC projections B1 and A2 for 2070–2099. Ecohydrological conditions were assessed by simulating soil water balance with SOILWAT, a daily time‐step, multiple layer, mechanistic, soil water model. Under current conditions, both climatic and ecohydrological SDM approaches produced comparable sagebrush distributions. Overall, sagebrush distribution is forecasted to decrease, with larger decreases under the A2 than under the B1 scenario and strong decreases in the southern part of the range. Increases were forecasted in the northern parts and at higher elevations. Both SDM approaches produced accurate predictions. However, the ecohydrological SDM approach was slightly less accurate than climatic SDMs (?1% in AUC, ?4% in Kappa and TSS) and predicted a higher number of habitat patches than observed in the input data. Future predictions of ecohydrological SDMs included an increased number of habitat patches whereas climatic SDMs predicted a decrease. This difference is important for understanding landscape‐scale patterns of sagebrush ecosystems and management of sagebrush obligate species for future conditions. Several mechanisms can explain the diverging forecasts; however, we need better insights into the consequences of different datasets for SDMs and how these affect our understanding of future trajectories.     

Effect of geographic background and equilibrium state on niche model transferability: predicting areas of invasion of Leptoglossus occidentalis

Niche conservatism providing support for using ecological niche modeling in biological invasions has been widely noticed, however, the equilibrium state and geographic background effect on niche model transferability has received scant attention. The western conifer seed bug, Leptoglossus occidentalis, native to western North America, has expanded its range eastward and has become an invasive pest in Europe and Asia. Niche models calibrated on the ranges of a small native population and two large expanding populations were compared. We found that the climate niche of L. occidentalis is conserved during its steady expansion in North America and rapid spread in Europe. Models based on the small western native range successfully captured the eastern expanding and introduced European populations, whereas the large area-based models varied with the presumed state of equilibrium. The equilibrium state based model succeeded but the non-equilibrium based model failed to predict the range in Europe. Our study estimates global invasion risk zones for L. occidentalis and suggests that, based on niche conservatism, modeling based on a reasonable geographic distribution at a climatic equilibrium of a species could guarantee the transferability of niche model prediction. Caution is warranted in interpreting low niche model transferability with niche differentiation and forwarding message for management strategy.     

Species distribution modelling as a macroecological tool: a case study using New World amphibians

Although species distribution modelling (SDM) is widely accepted among the scientific community and is increasingly used in ecology, conservation biology and biogeography, methodological limitations generate potential problems for its application in macroecology. Using amphibian species richness in North and South America, we compare species richness patterns derived from SDM maps and ‘expert’ maps to evaluate if: 1) richness patterns derived from SDM are biased toward climate‐based explanations for diversity when compared to expert maps, since SDM methods are typically based on climatic variables; and 2) SDM is a reliable tool for generating richness maps in hyperrich regions where point occurrence data are limited for many species. We found that although three widely used SDM methods overestimated amphibian species richness in grid cells when compared to expert richness maps in both North and South America due to systematic overestimation of range sizes, diversity gradients were reasonably robust at broad scales. Further, climatic variables statistically explained patterns of richness at similar levels among the different richness sources, although climatic relationships were stronger in the much better known North America than in South America. We conclude that in the face of the high deforestation rates coupled with incomplete data on species distributions, especially in the tropics, SDM represents a useful macroecological tool for investigating broad‐scale richness patterns and the dynamics between species richness and climate.     

Intra‐specific variability and plasticity influence potential tree species distributions under climate change

Aim To assess the effect of local adaptation and phenotypic plasticity on the potential distribution of species under future climate changes. Trees may be adapted to specific climatic conditions; however, species range predictions have classically been assessed by species distribution models (SDMs) that do not account for intra‐specific genetic variability and phenotypic plasticity, because SDMs rely on the assumption that species respond homogeneously to climate change across their range, i.e. a species is equally adapted throughout its range, and all species are equally plastic. These assumptions could cause SDMs to exaggerate or underestimate species at risk under future climate change. Location The Iberian Peninsula. Methods Species distributions are predicted by integrating experimental data and modelling techniques. We incorporate plasticity and local adaptation into a SDM by calibrating models of tree survivorship with adaptive traits in provenance trials. Phenotypic plasticity was incorporated by calibrating our model with a climatic index that provides a measure of the differences between sites and provenances. Results We present a new modelling approach that is easy to implement and makes use of existing tree provenance trials to predict species distribution models under global warming. Our results indicate that the incorporation of intra‐population genetic diversity and phenotypic plasticity in SDMs significantly altered their outcome. In comparing species range predictions, the decrease in area occupancy under global warming conditions is smaller when considering our survival–adaptation model than that predicted by a ‘classical SDM’ calibrated with presence–absence data. These differences in survivorship are due to both local adaptation and plasticity. Differences due to the use of experimental data in the model calibration are also expressed in our results: we incorporate a null model that uses survival data from all provenances together. This model always predicts less reduction in area occupancy for both species than the SDM calibrated with presence–absence. Main conclusions We reaffirm the importance of considering adaptive traits when predicting species distributions and avoiding the use of occurrence data as a predictive variable. In light of these recommendations, we advise that existing predictions of future species distributions and their component populations must be reconsidered.     

Forecasting the future of biodiversity: a test of single‐ and multi‐species models for ants in North America

The geographic distributions of many taxonomic groups remain mostly unknown, hindering attempts to investigate the response of the majority of species on Earth to climate change using species distributions models (SDMs). Multi‐species models can incorporate data for rare or poorly‐sampled species, but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single‐species models to those from a multi‐species modeling approach, Generalized Dissimilarity Modeling (GDM). We found that both single‐ and multi‐species models forecasted large changes in ant community composition in relatively warm environments. GDM predicted higher turnover than SDMs and across a larger contiguous area, including the southern third of North America and notably Central America, where the proportion of ants with relatively small ranges is high and where data limitations are most likely to impede the application of SDMs. Differences between approaches were also influenced by assumptions regarding dispersal, with forecasts being more similar if no‐dispersal was assumed. When full‐dispersal was assumed, SDMs predicted higher turnover in southern Canada than did GDM. Taken together, our results suggest that 1) warm rather than cold regions potentially could experience the greatest changes in ant fauna under climate change and that 2) multi‐species models may represent an important complement to SDMs, particularly in analyses involving large numbers of rare or poorly‐sampled species. Comparisons of the ability of single‐ and multi‐species models to predict observed changes in community composition are needed in order to draw definitive conclusions regarding their application to investigating climate change impacts on biodiversity.     

Assessing multitemporal calibration for species distribution models

Species distribution models (SDMs), the most prominent tool in modern biogeography, rely on the assumptions that (i) species distribution is in equilibrium with the environment and (ii) that climatic niche has been conserved throughout recent geological time. These issues affect the spatial and temporal transferability of SDMs, limiting their reliability for applications such as when studying effects of past climate change on species distribution and extinctions. The integration of paleontological and neontological data for a multitemporal calibration and validation of SDMs has been suggested for improving SDMs flexibility. Here, we provide an empirical test for a multitemporal calibration, employing virtual species (i.e., with perfectly-known distributions) and comparing them directly with monotemporal SDMs (i.e., SDM calibrated in a single time layer). We used 1kyr-interval scenarios throughout the last 22 kyr BP for two ecologically different species in South America (a “hot and wet” species and a “cold and dry” species). Models with multitemporal calibration performed similarly to models with monotemporal calibration, regardless of species, sample sizes, and time frame. However, multitemporal calibration performed better when dealing with non-analogous climates among time layers. By improving the temporal SDMs transferability, multitemporal calibration opens new avenues for integrating fossil and recent occurrence data, which may substantially benefit biogeography and paleoecology.     

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.     

Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

Using a climatic niche model to predict the direct and indirect impacts of climate change on the distribution of Douglas‐fir in New Zealand

Climate change is likely to have major impacts on the distribution of planted and natural forests. Herein, we demonstrate how a process‐based niche model (CLIMEX) can be extended to globally project the potential habitat suitable for Douglas‐fir. Within this distribution, we use CLIMEX to predict abundance of the pathogen P haeocryptopus gaeumannii and severity of its associated foliage disease, Swiss needle cast. The distribution and severity of the disease, which can strongly reduce growth rate of Douglas‐fir, is closely correlated with seasonal temperatures and precipitation. This model is used to project how climate change during the 2080s may alter the area suitable for Douglas‐fir plantations within New Zealand. The climate change scenarios used indicate that the land area suitable for Douglas‐fir production in the North Island will be reduced markedly from near 100% under current climate to 36–64% of the total land area by 2080s. Within areas shown to be suitable for the host in the North Island, four of the six climate change scenarios predict substantial increases in disease severity that will make these regions at best marginal for Douglas‐fir by the 2080s. In contrast, most regions in the South Island are projected to sustain relatively low levels of disease, and remain suitable for Douglas‐fir under climate change over the course of this century.     

Cryptic niche conservatism among evolutionary lineages of an invasive lizard

Aim There is increasing evidence that the quality and breadth of ecological niches vary among individuals, populations, evolutionary lineages and therefore also across the range of a species. Sufficient knowledge about niche divergence among clades might thus be crucial for predicting the invasion potential of species. We tested for the first time whether evolutionary lineages of an invasive species vary in their climate niches and invasive potential. Furthermore, we tested whether lineage‐specific models show a better performance than combined models. Location Europe. Methods We used species distribution models (SDMs) based on climatic information at native and invasive ranges to test for intra‐specific niche divergence among mitochondrial DNA (mtDNA) clades of the invasive wall lizard Podarcis muralis. Using DNA barcoding, we assigned 77 invasive populations in Central Europe to eight geographically distinct evolutionary lineages. Niche similarity among lineages was assessed and the predictive power of a combination of clade‐specific SDMs was compared with a combined SDM using the pooled records of all lineages. Results We recorded eight different invasive mtDNA clades in Central Europe. The analysed clades had rather similar realized niches in their native and invasive ranges, whereas inter‐clade niche differentiation was comparatively strong. However, we found only a weak correlation between geographic origin (i.e. mtDNA clade) and invasive occurrences. Clades with narrow realized niches still became successful invaders far outside their native range, most probably due to broader fundamental niches. The combined model using data for all invasive lineages achieved a much better prediction of the invasive potential. Conclusions Our results indicate that the observed niche differentiation among evolutionary lineages is mainly driven by niche realization and not by differences in the fundamental niches. Such cryptic niche conservatism might hamper the success of clade‐specific niche modelling. Cryptic niche conservatism may in general explain the invasion success of species in areas with apparently unsuitable climate.     

American trees shift their niches when invading Western Europe: evaluating invasion risks in a changing climate

Four North American trees are becoming invasive species in Western Europe: Acer negundo, Prunus serotina, Quercus rubra, and Robinia pseudoacacia. However, their present and future potential risks of invasion have not been yet evaluated. Here, we assess niche shifts between the native and invasive ranges and the potential invasion risk of these four trees in Western Europe. We estimated niche conservatism in a multidimensional climate space using niche overlap Schoener's D, niche equivalence, and niche similarity tests. Niche unfilling and expansion were also estimated in analogous and nonanalogous climates. The capacity for predicting the opposite range between the native and invasive areas (transferability) was estimated by calibrating species distribution models (SDMs) on each range separately. Invasion risk was estimated using SDMs calibrated on both ranges and projected for 2050 climatic conditions. Our results showed that native and invasive niches were not equivalent with low niche overlap for all species. However, significant similarity was found between the invasive and native ranges of Q. rubra and R. pseudoacacia. Niche expansion was lower than 15% for all species, whereas unfilling ranged from 7 to 56% when it was measured using the entire climatic space and between 5 and 38% when it was measured using analogous climate only. Transferability was low for all species. SDMs calibrated over both ranges projected high habitat suitability in Western Europe under current and future climates. Thus, the North American and Western European ranges are not interchangeable irrespective of the studied species, suggesting that other environmental and/or biological characteristics are shaping their invasive niches. The current climatic risk of invasion is especially high for R. pseudoacacia and A. negundo. In the future, the highest risks of invasion for all species are located in Central and Northern Europe, whereas the risk is likely to decrease in the Mediterranean basin.     

Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change

Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs) are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records--as assessed using widespread metrics--need not indicate a model's ability to predict the future.     

The biogeography of prediction error: why does the introduced range of the fire ant over‐predict its native range?

Aim The use of species distribution models (SDMs) to predict biological invasions is a rapidly developing area of ecology. However, most studies investigating SDMs typically ignore prediction errors and instead focus on regions where native distributions correctly predict invaded ranges. We investigated the ecological significance of prediction errors using reciprocal comparisons between the predicted invaded and native range of the red imported fire ant (Solenopsis invicta) (hereafter called the fire ant). We questioned whether fire ants occupy similar environments in their native and introduced range, how the environments that fire ants occupy in their introduced range changed through time relative to their native range, and where fire ant propagules are likely to have originated. Location We developed models for South America and the conterminous United States (US) of America. Methods We developed models using the Genetic Algorithm for Rule‐set Prediction (GARP) and 12 environmental layers. Occurrence data from the native range in South America were used to predict the introduced range in the US and vice versa. Further, time‐series data recording the invasion of fire ants in the US were used to predict the native range. Results Native range occurrences under‐predicted the invasive potential of fire ants, whereas occurrence data from the US over‐predicted the southern boundary of the native range. Secondly, introduced fire ants initially established in environments similar to those in their native range, but subsequently invaded harsher environments. Time‐series data suggest that fire ant propagules originated near the southern limit of their native range. Conclusions Our findings suggest that fire ants from a peripheral native population established in an environment similar to their native environment, and then ultimately expanded into environments in which they are not found in their native range. We argue that reciprocal comparisons between predicted native and invaded ranges will facilitate a better understanding of the biogeography of invasive and native species and of the role of SDMs in predicting future distributions.     

Potential geographic distribution of brown marmorated stink bug invasion (Halyomorpha halys)

Background

The Brown Marmorated Stink Bug (BMSB), Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), native to Asia, is becoming an invasive species with a rapidly expanding range in North America and Europe. In the US, it is a household pest and also caused unprecedented damage to agriculture crops. Exploring its climatic limits and estimating its potential geographic distribution can provide critical information for management strategies.

Methodology/Principals

We used direct climate comparisons to explore the climatic niche occupied by native and invasive populations of BMSB. Ecological niche modelings based on the native range were used to anticipate the potential distribution of BMSB worldwide. Conversely, niche models based on the introduced range were used to locate the original invasive propagates in Asia. Areas with high invasion potential were identified by two niche modeling algorithms (i.e., Maxent and GARP).

Conclusions/Significance

Reduced dimensionality of environmental space improves native model transferability in the invade area. Projecting models from invasive population back to native distributional areas offers valuable information on the potential source regions of the invasive populations. Our models anticipated successfully the current disjunct distribution of BMSB in the US. The original propagates are hypothesized to have come from northern Japan or western Korea. High climate suitable areas at risk of invasion include latitudes between 30°–50° including northern Europe, northeastern North America, southern Australia and the North Island of New Zealand. Angola in Africa and Uruguay in South America also showed high climate suitability.     

Integrating anthropogenic factors into regional‐scale species distribution models—A novel application in the imperiled sagebrush biome

Species distribution models (SDMs) that rely on regional‐scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local‐scale anthropogenic variables, including wildfire history, land‐use change, invasive species, and ecological restoration practices can override regional‐scale variables to drive patterns of species distribution. Incorporating these human‐induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human‐induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field‐sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America. Models including fire attributes and restoration treatments performed better than those including only climate and topographic variables. Number of fires and fire occurrence had the strongest relative effects on big sagebrush occurrence and cover, respectively. The models predicted that the probability of big sagebrush occurrence decreases by 1.2% (95% CI: ?6.9%, 0.6%) when one fire occurs and cover decreases by 44.7% (95% CI: ?47.9%, ?41.3%) if at least one fire occurred over the 36 year period of record. Restoration practices increased the probability of big sagebrush occurrence but had minimal effect on cover. Our results demonstrate the potential value of including disturbance and land management along with climate in models to predict species distributions. As an increasing number of datasets representing land‐use history become available, we anticipate that our modeling framework will have broad relevance across a range of biomes and species.     

Survival and growth patterns of white spruce (Picea glauca [Moench] Voss) rangewide provenances and their implications for climate change adaptation

Intraspecific assisted migration (ISAM) through seed transfer during artificial forest regeneration has been suggested as an adaptation strategy to enhance forest resilience and productivity under future climate. In this study, we assessed the risks and benefits of ISAM in white spruce based on long‐term and multilocation, rangewide provenance test data. Our results indicate that the adaptive capacity and growth potential of white spruce varied considerably among 245 range‐wide provenances sampled across North America; however, the results revealed that local populations could be outperformed by nonlocal ones. Provenances originating from south‐central Ontario and southwestern Québec, Canada, close to the southern edge of the species' natural distribution, demonstrated superior growth in more northerly environments compared with local populations and performed much better than populations from western Canada and Alaska, United States. During the 19–28 years between planting and measurement, the southern provenances have not been more susceptible to freezing damage compared with local populations, indicating they have the potential to be used now for the reforestation of more northerly planting sites; based on changing temperature, these seed sources potentially could maintain or increase white spruce productivity at or above historical levels at northern sites. A universal response function (URF), which uses climatic variables to predict provenance performance across field trials, indicated a relatively weak relationship between provenance performance and the climate at provenance origin. Consequently, the URF from this study did not provide information useful to ISAM. The ecological and economic importance of conserving white spruce genetic resources in south‐central Ontario and southwestern Québec for use in ISAM is discussed.     

Will changes in phenology track climate change? A study of growth initiation timing in coast Douglas‐fir

Under climate change, the reduction of frost risk, onset of warm temperatures and depletion of soil moisture are all likely to occur earlier in the year in many temperate regions. The resilience of tree species will depend on their ability to track these changes in climate with shifts in phenology that lead to earlier growth initiation in the spring. Exposure to warm temperatures (‘forcing’) typically triggers growth initiation, but many trees also require exposure to cool temperatures (‘chilling’) while dormant to readily initiate growth in the spring. If warming increases forcing and decreases chilling, climate change could maintain, advance or delay growth initiation phenology relative to the onset of favorable conditions. We modeled the timing of height‐ and diameter‐growth initiation in coast Douglas‐fir (an ecologically and economically vital tree in western North America) to determine whether changes in phenology are likely to track changes in climate using data from field‐based and controlled‐environment studies, which included conditions warmer than those currently experienced in the tree's range. For high latitude and elevation portions of the tree's range, our models predicted that warming will lead to earlier growth initiation and allow trees to track changes in the onset of the warm but still moist conditions that favor growth, generally without substantially greater exposure to frost. In contrast, toward lower latitude and elevation range limits, the models predicted that warming will lead to delayed growth initiation relative to changes in climate due to reduced chilling, with trees failing to capture favorable conditions in the earlier parts of the spring. This maladaptive response to climate change was more prevalent for diameter‐growth initiation than height‐growth initiation. The decoupling of growth initiation with the onset of favorable climatic conditions could reduce the resilience of coast Douglas‐fir to climate change at the warm edges of its distribution.     

Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities

Aim Species distribution models (SDMs) have been used to address a wide range of theoretical and applied questions in the terrestrial realm, but marine‐based applications remain relatively scarce. In this review, we consider how conceptual and practical issues associated with terrestrial SDMs apply to a range of marine organisms and highlight the challenges relevant to improving marine SDMs. Location We include studies from both marine and terrestrial systems that encompass many geographic locations around the globe. Methods We first performed a literature search and analysis of marine and terrestrial SDMs in ISI Web of Science to assess trends and applications. Using knowledge from terrestrial applications, we critically evaluate the application of SDMs in marine systems in the context of ecological factors (dispersal, species interactions, aggregation and ontogenetic shifts) and practical considerations (data quality, alternative modelling approaches and model validation) that facilitate or create difficulties for model application. Results The relative importance of ecological factors to be considered when applying SDMs varies among terrestrial and marine organisms. Correctly incorporating dispersal is frequently considered an important issue for terrestrial models, but because there is greater potential for dispersal in the ocean, it is often less of a concern in marine SDMs. By contrast, ontogenetic shifts and feeding have received little attention in terrestrial SDM applications, but these factors are important to many marine SDMs. Opportunities also exist for applying more advanced SDM approaches in the marine realm, including mechanistic ecophysiological models, where water balance and heat transfer equations are simpler for some marine organisms relative to their terrestrial counterparts. Main conclusions SDMs have generally been under‐utilized in the marine realm relative to terrestrial applications. Correlative SDM methods should be tested on a range of marine organisms, and we suggest further development of methods that address ontogenetic shifts and feeding interactions. We anticipate developments in, and cross‐fertilization between, coupled correlative and process‐based SDMs, mechanistic eco‐physiological SDMs, and spatial population dynamic models for climate change and species invasion applications in particular. Comparisons of the outputs of different model types will provide insight that is useful for improved spatial management of marine species.     

Benchmarking novel approaches for modelling species range dynamics

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process‐based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process‐based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species.