Population Viability Analysis of the Epiphytic Ghost Orchid (Dendrophylax lindenii) in Cuba

To design feasible conservation and management policies for wild species, it is critical to understand the effects of periodic disturbances, be they natural or anthropogenic. The Caribbean Basin is characterized by high cyclonic activity that has a strong impact on the demography and population dynamics of many taxa, including epiphytic orchids. We conducted a 5‐yr study of rare ghost orchid demography, Dendrophylax lindenii, to assess the stability of a protected population of this species in Cuba. Using both stochastic and deterministic integral projection models, we found that mean annual population growth rates are negative (λ = 0.975). However, we found both population growth rate and extinction risk are highly sensitive to survival rates and reproduction, a difficult to quantify rate for many orchids including our study species. While this species is fairly long‐lived, its relatively slow increase in annual survival with increasing size may reflect the lack of a protected (i.e., subterranean) storage organ—a life‐history trait that may typify other epiphytic species and increase susceptibility to disturbance events. Hurricanes, which are predicted to increase in frequency as a result of climate change, dramatically increase adult mortality. Simulations of these effects indicate that hurricanes and similar disturbances could result in near certain extinction in short time horizons (25 yr) if their annual probability of occurrence exceeds 14 percent. These results suggest a need to better quantify recruitment rates, as well as the sensitivity of population dynamics of this and other orchid species to hurricanes and other periodic disturbances.     

The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models

Autumn senescence regulates multiple aspects of ecosystem function, along with associated feedbacks to the climate system. Despite its importance, current understanding of the drivers of senescence is limited, leading to a large spread in predictions of how the timing of senescence, and thus the length of the growing season, will change under future climate conditions. The most commonly held paradigm is that temperature and photoperiod are the primary controls, which suggests a future extension of the autumnal growing season as global temperatures rise. Here, using two decades of ground‐ and satellite‐based observations of temperate deciduous forest phenology, we show that the timing of autumn senescence is correlated with the timing of spring budburst across the entire eastern United States. On a year‐to‐year basis, an earlier/later spring was associated with an earlier/later autumn senescence, both for individual species and at a regional scale. We use the observed relationship to develop a novel model of autumn phenology. In contrast to current phenology models, this model predicts that the potential response of autumn phenology to future climate change is strongly limited by the impact of climate change on spring phenology. Current models of autumn phenology therefore may overpredict future increases in the length of the growing season, with subsequent impacts for modeling future CO₂ uptake and evapotranspiration.     

Terrestrial insects and climate change: adaptive responses in key traits

Understanding and predicting how adaptation will contribute to species' resilience to climate change will be paramount to successfully managing biodiversity for conservation, agriculture, and human health‐related purposes. Making predictions that capture how species will respond to climate change requires an understanding of how key traits and environmental drivers interact to shape fitness in a changing world. Current trait‐based models suggest that low‐ to mid‐latitude populations will be most at risk, although these models focus on upper thermal limits, which may not be the most important trait driving species' distributions and fitness under climate change. In this review, we discuss how different traits (stress, fitness and phenology) might contribute and interact to shape insect responses to climate change. We examine the potential for adaptive genetic and plastic responses in these key traits and show that, although there is evidence of range shifts and trait changes, explicit consideration of what underpins these changes, be that genetic or plastic responses, is largely missing. Despite little empirical evidence for adaptive shifts, incorporating adaptation into models of climate change resilience is essential for predicting how species will respond under climate change. We are making some headway, although more data are needed, especially from taxonomic groups outside of Drosophila, and across diverse geographical regions. Climate change responses are likely to be complex, and such complexity will be difficult to capture in laboratory experiments. Moving towards well designed field experiments would allow us to not only capture this complexity, but also study more diverse species.     

Historical and projected interactions between climate change and insect voltinism in a multivoltine species

Climate change can cause major changes to the dynamics of individual species and to those communities in which they interact. One effect of increasing temperatures is on insect voltinism, with the logical assumption that increases in surface temperatures would permit multivoltine species to increase the number of generations per year. Though insect development is primarily driven by temperature, most multivoltine insect species rely on photoperiodic cues, which do not change from year‐to‐year or in response to climate warming, to initiate diapause. Thus, the relationship between climate change and voltinism could be complex. We use a phenology model for grape berry moth, Paralobesia viteana (Clemens), which incorporates temperature‐dependent development and diapause termination, and photoperiod‐dependent diapause induction, to explore historical patterns in year‐to‐year voltinism fluctuations. We then extend this model to predict voltinism under varying scenarios of climate change to show the importance of both the quality and quantity of accumulated heat units. We also illustrate that increases in mean surface temperatures > 2 °C can have dramatic effects on insect voltinism by causing a shift in the ovipositional period that currently is subject to diapause‐inducing photoperiods.     

Linking population genetics and tree height growth models to predict impacts of climate change on forest production

Changes to forest growth models used widely in global change research and sustainable forest management are needed to account for expected climate change impacts. We provide a new approach that dynamically merges height–age functions prevalent in forest growth models with transfer functions prevalent in population adaptation research to better represent changes to forest productivity as climates gradually change. Our simulations with data from an extensive provenance test of lodgepole pine (Pinus contorta) in British Columbia, Canada, suggest that climate change will reduce production in lodgepole pine forests established today by at least 7–13% at the end of this century – considerably less than most predictions based solely on transfer or response functions, which do not integrate impacts as climate gradually changes. This work illustrates the need for forest productivity models to consider the changing climate in which a population is growing relative to the static climate of its origin. It also demonstrates the value of long‐term provenance trials in assessing the dynamic impact of climate change on forest productivity, and serves as an example of how provenance trials may be exploited in other forest productivity models or other research fields to assess plant responses to climate.     

Niche models tell half the story: spatial context and life‐history traits influence species responses to global change

Aim While niche models are typically used to assess the vulnerability of species to climate change, they have been criticized for their limited assessment of threats other than climate change. We attempt to evaluate this limitation by combining niche models with life‐history models to investigate the relative influence of climate change and a range of fire regimes on the viability of a long‐lived plant population. Specifically, we investigate whether range shift due to climate change is a greater threat to an obligate seeding fire‐prone shrub than altered fire frequency and how these two threatening processes might interact. Location Australian sclerophyll woodland and heathland. Methods The study species is Leucopogon setiger, an obligate seeding fire‐prone shrub. A spatially explicit stochastic matrix model was constructed for this species and linked with a dynamic niche model and fire risk functions representing a suite of average fire return intervals. We compared scenarios with a variety of hypothetical patches, a patch framework based upon current habitat suitability and one with dynamic habitat suitability based on climate change scenarios A1FI and A2. Results Leucopogon setiger was found to be sensitive to fire frequency, with shorter intervals reducing expected minimum abundances (EMAs). Spatial decoupling of fires across the landscape reduced the vulnerability of the species to shortened fire frequencies. Shifting habitat, while reducing EMAs, was less of a threat to the species than frequent fire. Main conclusions Altered fire regime, in particular more frequent fires relative to the historical regime, was predicted to be a strong threat to this species, which may reflect a vulnerability of obligate seeders in general. Range shifts induced by climate change were a secondary threat when habitat reductions were predicted. Incorporating life‐history traits into habitat suitability models by linking species distribution models with population models allowed for the population‐level evaluation of multiple stressors that affect population dynamics and habitat, ultimately providing a greater understanding of the impacts of global change than would be gained by niche models alone. Further investigations of this type could elucidate how particular bioecological factors can affect certain types of species under global change.     

Stochastic stable population growth in integral projection models: theory and application

Stochastic matrix projection models are widely used to model age- or stage-structured populations with vital rates that fluctuate randomly over time. Practical applications of these models rest on qualitative properties such as the existence of a long term population growth rate, asymptotic log-normality of total population size, and weak ergodicity of population structure. We show here that these properties are shared by a general stochastic integral projection model, by using results in (Eveson in D. Phil. Thesis, University of Sussex, 1991, Eveson in Proc. Lond. Math. Soc. 70, 411-440, 1993) to extend the approach in (Lange and Holmes in J. Appl. Prob. 18, 325-344, 1981). Integral projection models allow individuals to be cross-classified by multiple attributes, either discrete or continuous, and allow the classification to change during the life cycle. These features are present in plant populations with size and age as important predictors of individual fate, populations with a persistent bank of dormant seeds or eggs, and animal species with complex life cycles. We also present a case-study based on a 6-year field study of the Illyrian thistle, Onopordum illyricum, to demonstrate how easily a stochastic integral model can be parameterized from field data and then applied using familiar matrix software and methods. Thistle demography is affected by multiple traits (size, age and a latent "quality" variable), which would be difficult to accommodate in a classical matrix model. We use the model to explore the evolution of size- and age-dependent flowering using an evolutionarily stable strategy (ESS) approach. We find close agreement between the observed flowering behavior and the predicted ESS from the stochastic model, whereas the ESS predicted from a deterministic version of the model is very different from observed flowering behavior. These results strongly suggest that the flowering strategy in O. illyricum is an adaptation to random between-year variation in vital rates.     

Modeling temperature‐dependent development rate and phenology in insects: review of major developments,challenges, and future directions

The study of insect responses to temperature has a long tradition in science, starting from Réaumur's work on caterpillars in the 18th century. In 1932, Ernst Janisch wrote: ‘The problem is (and will be more and more in the future) one of the most important ones in entomology […]’. Almost 90 years after this paper, its prediction still holds true, with a sustained interest of the scientific community for the study of insect responses to temperature, especially in the context of climate change. We present a review of the major developments in the field of insect development responses to temperature and analyze the growing importance of modeling approaches in the literature using a bibliographic analysis. We discuss recent advances and future directions for phenology‐modeling based on temperature‐dependent development rate. Finally, we highlight the need for a change of paradigm toward a system‐based approach in order to overcome current challenges and to predict insect phenology more accurately, with direct implications in agriculture, conservation biology, and epidemiology.     

Phenology model from surface meteorology does not capture satellite-based greenup estimations

Seasonal temperature change in temperate forests is known to trigger the start of spring growth, and both interannual and spatial variations in spring onset have been tied to climatic variability. Satellite dates are increasingly being used in phenology studies, but to date that has been little effort to link remotely sensed phenology to surface climate records. In this research, we use a two‐parameter spring warming phenology model to explore the relationship between climate and satellite‐based phenology. We employ daily air temperature records between 2000 and 2005 for 171 National Oceanographic and Atmospheric Administration weather stations located throughout New England to construct spring warming models predicting the onset of spring, as defined by the date of half‐maximum greenness (D₅₀) in deciduous forests as detected from Moderate Resolution Imaging Spectrometer. The best spring warming model starts accumulating temperatures after March 20th and when average daily temperatures exceed 5°C. The accumulated heat sums [heating degree day (HDD)] required to reach D₅₀ range from 150 to 300 degree days over New England, with the highest requirements to the south and in coastal regions. We test the ability of the spring warming model to predict phenology against a null photoperiod model (average date of onset). The spring warming model offers little improvement on the null model when predicting D₅₀. Differences between the efficacies of the two models are expressed as the ‘climate sensitivity ratio’ (CSR), which displays coherent spatial patterns. Our results suggest that northern (beech‐maple‐birch) and central (oak‐hickory) hardwood forests respond to climate differently, particularly with disparate requirements for the minimum temperature necessary to begin spring growth (3 and 6°C, respectively). We conclude that spatial location and species composition are critical factors for predicting the phenological response to climate change: satellite observations cannot be linked directly to temperature variability if species or community compositions are unknown.     

Climate change alters elevational phenology patterns of the European spruce bark beetle (Ips typographus)

The European spruce bark beetle Ips typographus is the most important insect pest in Central European forests. Under climate change, its phenology is presumed to be changing and mass infestations becoming more likely. While several studies have investigated climate effects across a latitudinal gradient, it remains an open question how phenology will change depending on elevation and topology. Knowing how an altered climate is likely to affect bark beetle populations, particularly across diverse topographies and elevations, is essential for adaptive management. We developed a time‐varying distributed delay model to predict the phenology of I. typographus. This approach has the particular advantage of capturing the variability within populations and thus representing its stage structure at any time. The model is applied for three regional climate change scenarios, A1B, A2 and RCP3PD, to the diverse topography of Switzerland, covering a large range of elevations, aspects and slopes. We found a strong negative relationship between voltinism and elevation. Under climate change, the model predicts an increasing number of generations over the whole elevational gradient, which will be more pronounced at low elevations. In contrast, the pre‐shift in spring swarming is expected to be greater at higher elevations. In comparison, the general trend of faster beetle development on steep southern slopes is only of minor importance. Overall, the maximum elevation allowing a complete yearly generation will move upwards. Generally, the predicted increase in number of generations, earlier spring swarming, more aggregated swarming, together with a projected increase in drought and storm events, will result in a higher risk of mass infestations. This will increase the pressure on spruce stands particularly in the lowlands and require intensified management efforts. It calls for adapted long‐term silvicultural strategies to mitigate the loss of ecosystem services such as timber production protection against rockfall and avalanches and carbon storage.     

Population responses to perturbations: the importance of trait-based analysis illustrated through a microcosm experiment

Environmental change continually perturbs populations from a stable state, leading to transient dynamics that can last multiple generations. Several long-term studies have reported changes in trait distributions along with demographic response to environmental change. Here we conducted an experimental study on soil mites and investigated the interaction between demography and an individual trait over a period of nonstationary dynamics. By following individual fates and body sizes at each life-history stage, we investigated how body size and population density influenced demographic rates. By comparing the ability of two alternative approaches, a matrix projection model and an integral projection model, we investigated whether consideration of trait-based demography enhances our ability to predict transient dynamics. By utilizing a prospective perturbation analysis, we addressed which stage-specific demographic or trait-transition rate had the greatest influence on population dynamics. Both body size and population density had important effects on most rates; however, these effects differed substantially among life-history stages. Considering the observed trait-demography relationships resulted in better predictions of a population's response to perturbations, which highlights the role of phenotypic plasticity in transient dynamics. Although the perturbation analyses provided comparable predictions of stage-specific elasticities between the matrix and integral projection models, the order of importance of the life-history stages differed between the two analyses. In conclusion, we demonstrate how a trait-based demographic approach provides further insight into transient population dynamics.     

Evolutionary tracking is determined by differential selection on demographic rates and density dependence

Recent ecological forecasts predict that ~25% of species worldwide will go extinct by 2050. However, these estimates are primarily based on environmental changes alone and fail to incorporate important biological mechanisms such as genetic adaptation via evolution. Thus, environmental change can affect population dynamics in ways that classical frameworks can neither describe nor predict. Furthermore, often due to a lack of data, forecasting models commonly describe changes in population demography by summarizing changes in fecundity and survival concurrently with the intrinsic growth rate (r). This has been shown to be an oversimplification as the environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). This differential pressure may alter population response to density, in each demographic rate, further diluting the information combined to produce r. Thus, when we consider the potential for persistence via adaptive evolution, populations with the same r can have different abilities to persist amidst environmental change. Therefore, we cannot adequately forecast population response to climate change without accounting for demography and selection on density dependence. Using a continuous‐time Markov chain model to describe the stochastic dynamics of the logistic model of population growth and allow for trait evolution via mutations arising during birth events, we find persistence via evolutionary tracking more likely when environmental change alters birth rather than the death rate. Furthermore, species that evolve responses to changes in the strength of density dependence due to environmental change are less vulnerable to extinction than species that undergo selection independent of population density. By incorporating these key demographic considerations into our predictive models, we can better understand how species will respond to climate change.     

Changes in seasonal climate outpace compensatory density‐dependence in eastern brook trout

Understanding how multiple extrinsic (density‐independent) factors and intrinsic (density‐dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density‐dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) vs. density‐dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10‐year capture‐mark‐recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete‐time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type, and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density‐dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate‐driven environmental change.     

The forgotten season: the impact of autumn phenology on a specialist insect herbivore community on oak

1. Variation in spring phenology – like tree budburst – affects the structure of insect communities, but impacts of autumn phenology have been neglected. Many plant species have recently delayed their autumn phenology, and the timing of leaf senescence may be important for herbivorous insects. 2. This study explored how an insect herbivore community associated with Quercus robur is influenced by variation in autumn phenology. For this, schools were asked to record, across the range of oak in Sweden, the autumn phenology of oaks and to conduct a survey of the insect community. 3. To tease apart the relative impacts of climate from that of tree phenology, regional tree phenology was first modelled as a function of regional climate, and the tree‐specific deviation from this relationship was then used as the metric of relative tree‐specific phenology. 4. At the regional scale, a warmer climate postponed oak leaf senescence. This was also reflected in the insect herbivore community: six out of 15 taxa occurred at a higher incidence and five out of 18 taxa were more abundant, in locations with a warmer climate. Similarly, taxonomic richness and herbivory were higher in warmer locations. 5. Trees with a relatively late autumn phenology had higher abundances of leaf miners (Phyllonorycter spp.). This caused lower community diversity and evenness on trees with later autumn phenology. 6. The findings of the present study illustrate that both regional climate‐driven patterns and local variation in oak autumn phenology contribute to shaping the insect herbivore community. Community patterns may thus shift with a changing climate.     

Ontogeny constrains phenology: opportunities for activity and reproduction interact to dictate potential phenologies in a changing climate

As global warming has lengthened the active seasons of many species, we need a framework for predicting how advances in phenology shape the life history and the resulting fitness of organisms. Using an individual‐based model, we show how warming differently affects annual cycles of development, growth, reproduction and activity in a group of North American lizards. Populations in cold regions can grow and reproduce more when warming lengthens their active season. However, future warming of currently warm regions advances the reproductive season but reduces the survival of embryos and juveniles. Hence, stressful temperatures during summer can offset predicted gains from extended growth seasons and select for lizards that reproduce after the warm summer months. Understanding these cascading effects of climate change may be crucial to predict shifts in the life history and demography of species.     

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage‐structured, seasonal, nonlinear, two‐sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture‐mark‐recapture analysis, we find that seasonal sea ice concentration anomalies (SIC_a) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SIC_a, because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SIC_a. We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SIC_a, which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems.     

Plant functional traits mediate reproductive phenology and success in response to experimental warming and snow addition in Tibet

Global climate change is predicted to have large impacts on the phenology and reproduction of alpine plants, which will have important implications for plant demography and community interactions, trophic dynamics, ecosystem energy balance, and human livelihoods. In this article we report results of a 3‐year, fully factorial experimental study exploring how warming, snow addition, and their combination affect reproductive phenology, effort, and success of four alpine plant species belonging to three different life forms in a semiarid, alpine meadow ecosystem on the central Tibetan Plateau. Our results indicate that warming and snow addition change reproductive phenology and success, but responses are not uniform across species. Moreover, traits associated with resource acquisition, such as rooting depth and life history (early vs. late flowering), mediate plant phenology, and reproductive responses to changing climatic conditions. Specifically, we found that warming delayed the reproductive phenology and decreased number of inflorescences of Kobresia pygmaea C. B. Clarke, a shallow‐rooted, early‐flowering plant, which may be mainly constrained by upper‐soil moisture availability. Because K. pygmaea is the dominant species in the alpine meadow ecosystem, these results may have important implications for ecosystem dynamics and for pastoralists and wildlife in the region.     

Influence of bioclimatic variables on tree-line conifer distribution in the Greater Yellowstone Ecosystem: implications for species of conservation concern

Aim Tree‐line conifers are believed to be limited by temperature worldwide, and thus may serve as important indicators of climate change. The purpose of this study was to examine the potential shifts in spatial distribution of three tree‐line conifer species in the Greater Yellowstone Ecosystem under three future climate‐change scenarios and to assess their potential sensitivity to changes in both temperature and precipitation. Location This study was performed using data from 275 sites within the boundaries of Yellowstone and Grand Teton national parks, primarily located in Wyoming, USA. Methods We used data on tree‐line conifer presence from the US Forest Service Forest Inventory and Analysis Program. Climatic and edaphic variables were derived from spatially interpolated maps and approximated for each of the sites. We used the random‐forest prediction method to build a model of predicted current and future distributions of each of the species under various climate‐change scenarios. Results We had good success in predicting the distribution of tree‐line conifer species currently and under future climate scenarios. Temperature and temperature‐related variables appeared to be most influential in the distribution of whitebark pine (Pinus albicaulis), whereas precipitation and soil variables dominated the models for subalpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii). The model for whitebark pine substantially overpredicted absences (as compared with the other models), which is probably a result of the importance of biological factors in the distribution of this species. Main conclusions These models demonstrate the complex response of conifer distributions to changing climate scenarios. Whitebark pine is considered a ‘keystone’ species in the subalpine forests of western North America; however, it is believed to be nearly extinct throughout a substantial portion of its range owing to the combined effects of an introduced pathogen, outbreaks of the native mountain pine beetle (Dendroctonus ponderosae), and changing fire regimes. Given predicted changes in climate, it is reasonable to predict an overall decrease in pine‐dominated subalpine forests in the Greater Yellowstone Ecosystem. In order to manage these forests effectively with respect to future climate, it may be important to focus attention on monitoring dry mid‐ and high‐elevation forests as harbingers of long‐term change.     

Best environmental predictors of breeding phenology differ with elevation in a common woodland bird species

Temperatures in mountain areas are increasing at a higher rate than the Northern Hemisphere land average, but how fauna may respond, in particular in terms of phenology, remains poorly understood. The aim of this study was to assess how elevation could modify the relationships between climate variability (air temperature and snow melt‐out date), the timing of plant phenology and egg‐laying date of the coal tit (Periparus ater). We collected 9 years (2011–2019) of data on egg‐laying date, spring air temperature, snow melt‐out date, and larch budburst date at two elevations (~1,300 m and ~1,900 m asl) on a slope located in the Mont‐Blanc Massif in the French Alps. We found that at low elevation, larch budburst date had a direct influence on egg‐laying date, while at high‐altitude snow melt‐out date was the limiting factor. At both elevations, air temperature had a similar effect on egg‐laying date, but was a poorer predictor than larch budburst or snowmelt date. Our results shed light on proximate drivers of breeding phenology responses to interannual climate variability in mountain areas and suggest that factors directly influencing species phenology vary at different elevations. Predicting the future responses of species in a climate change context will require testing the transferability of models and accounting for nonstationary relationships between environmental predictors and the timing of phenological events.