Early emergence in a butterfly causally linked to anthropogenic warming

There is strong correlative evidence that human-induced climate warming is contributing to changes in the timing of natural events. Firm attribution, however, requires cause-and-effect links between observed climate change and altered phenology, together with statistical confidence that observed regional climate change is anthropogenic. We provide evidence for phenological shifts in the butterfly Heteronympha merope in response to regional warming in the southeast Australian city of Melbourne. The mean emergence date for H. merope has shifted −1.5 days per decade over a 65-year period with a concurrent increase in local air temperatures of approximately 0.16°C per decade. We used a physiologically based model of climatic influences on development, together with statistical analyses of climate data and global climate model projections, to attribute the response of H. merope to anthropogenic warming. Such mechanistic analyses of phenological responses to climate improve our ability to forecast future climate change impacts on biodiversity.     

The annual cycles of phytoplankton biomass

Terrestrial plants are powerful climate sentinels because their annual cycles of growth, reproduction and senescence are finely tuned to the annual climate cycle having a period of one year. Consistency in the seasonal phasing of terrestrial plant activity provides a relatively low-noise background from which phenological shifts can be detected and attributed to climate change. Here, we ask whether phytoplankton biomass also fluctuates over a consistent annual cycle in lake, estuarine–coastal and ocean ecosystems and whether there is a characteristic phenology of phytoplankton as a consistent phase and amplitude of variability. We compiled 125 time series of phytoplankton biomass (chlorophyll a concentration) from temperate and subtropical zones and used wavelet analysis to extract their dominant periods of variability and the recurrence strength at those periods. Fewer than half (48%) of the series had a dominant 12-month period of variability, commonly expressed as the canonical spring-bloom pattern. About 20 per cent had a dominant six-month period of variability, commonly expressed as the spring and autumn or winter and summer blooms of temperate lakes and oceans. These annual patterns varied in recurrence strength across sites, and did not persist over the full series duration at some sites. About a third of the series had no component of variability at either the six- or 12-month period, reflecting a series of irregular pulses of biomass. These findings show that there is high variability of annual phytoplankton cycles across ecosystems, and that climate-driven annual cycles can be obscured by other drivers of population variability, including human disturbance, aperiodic weather events and strong trophic coupling between phytoplankton and their consumers. Regulation of phytoplankton biomass by multiple processes operating at multiple time scales adds complexity to the challenge of detecting climate-driven trends in aquatic ecosystems where the noise to signal ratio is high.     

Spatial Match-Mismatch between Juvenile Fish and Prey Provides a Mechanism for Recruitment Variability across Contrasting Climate Conditions in the Eastern Bering Sea

Understanding mechanisms behind variability in early life survival of marine fishes through modeling efforts can improve predictive capabilities for recruitment success under changing climate conditions. Walleye pollock (Theragra chalcogramma) support the largest single-species commercial fishery in the United States and represent an ecologically important component of the Bering Sea ecosystem. Variability in walleye pollock growth and survival is structured in part by climate-driven bottom-up control of zooplankton composition. We used two modeling approaches, informed by observations, to understand the roles of prey quality, prey composition, and water temperature on juvenile walleye pollock growth: (1) a bioenergetics model that included local predator and prey energy densities, and (2) an individual-based model that included a mechanistic feeding component dependent on larval development and behavior, local prey densities and size, and physical oceanographic conditions. Prey composition in late-summer shifted from predominantly smaller copepod species in the warmer 2005 season to larger species in the cooler 2010 season, reflecting differences in zooplankton composition between years. In 2010, the main prey of juvenile walleye pollock were more abundant, had greater biomass, and higher mean energy density, resulting in better growth conditions. Moreover, spatial patterns in prey composition and water temperature lead to areas of enhanced growth, or growth ‘hot spots’, for juvenile walleye pollock and survival may be enhanced when fish overlap with these areas. This study provides evidence that a spatial mismatch between juvenile walleye pollock and growth ‘hot spots’ in 2005 contributed to poor recruitment while a higher degree of overlap in 2010 resulted in improved recruitment. Our results indicate that climate-driven changes in prey quality and composition can impact growth of juvenile walleye pollock, potentially severely affecting recruitment variability.     

Natural history museum collections provide information on phenological change in British butterflies since the late-nineteenth century

Museum collections have the potential to provide valuable information on the phenological response of organisms to climate change. This is particularly useful for those species for which few data otherwise exist, but also to extend time series to the period before other observational data are available. To test this potential, we analysed data from 2,630 specimens of four species of British butterflies (Anthocharis cardamines, Hamearis lucina, Polyommatus bellargus and Pyrgus malvae), collected from 1876 to 1999 and stored in the Natural History Museum, London, UK (NHM). In A. cardamines, first-generation P. bellargus and P. malvae, we found that there was a strong significant negative relationship between spring temperature and 10th percentile collection dates, which approximates mean first appearance date, and median collection date, which approximates mean flight date. In all four species, there was a significant negative relationship between the 10th percentile collection date and the length of the collection period, which approximates flight period. In second-generation P. bellargus, these phenological measurements were correlated with summer temperature. We found that the rates of phenological response to temperature, based on NHM data, were similar to, or somewhat greater than, those reported for other organisms based on observational data covering the last 40 years. The lower rate of phenological response, and the significant influence of February rather than March or April temperatures, in recent decades compared with data from earlier in the twentieth century may indicate that early emerging British butterfly species are currently approaching the limits of phenological advancement in response to recent climate warming.     

Elevational trends in butterfly phenology: implications for species responses to climate change

1. Impacts of global change on the distribution, abundance, and phenology of species have been widely documented. In particular, recent climate change has led to widespread changes in animal and plant seasonality, leading to debate about its potential to cause phenological mismatches among interacting taxa. 2. In mountainous regions, populations of many species show pronounced phenological gradients over short geographic distances, presenting the opportunity to test for effects of climate on phenology, independent of variation in confounding factors such as photoperiod. 3. Here we show for 32 butterfly species sampled for five years over a 1700 m gradient (560–2260 m) in a Mediterranean mountain range that, on average, annual flight period is delayed with elevation by 15–22 days per kilometre. Species mainly occurring at low elevations in the region, and to some extent those flying earlier in the year, showed phenological delays of 23–36 days per kilometre, whereas the flight periods of species that occupy high elevations, or fly in late summer, were consistently more synchronised over the elevation gradient. 4. Elevational patterns in phenology appear to reflect a narrowing phenological window of opportunity for larval and adult butterfly activity of high elevation and late‐flying species. 5. Here, we speculate as to the causes of these patterns, and the consequences for our ability to predict species responses to climate change. Our results raise questions about the use of space–time substitutions in predicting phenological responses to climate change, since traits relating to flight period and environmental associations may influence the capacity of species to adapt to changing climates.     

Forecasting phenology: from species variability to community patterns

Shifts in species' phenology in response to climate change have wide-ranging consequences for ecological systems. However, significant variability in species' responses, together with limited data, frustrates efforts to forecast the consequences of ongoing phenological changes. Herein, we use a case study of three North American plant communities to explore the implications of variability across levels of organisation (within and among species, and among communities) for forecasting responses to climate change. We show how despite significant variation among species in sensitivities to climate, comparable patterns emerge at the community level once regional climate drivers are accounted for. However, communities differ with respect to projected patterns of divergence and overlap among their species' phenological distributions in response to climate change. These analyses and a review of hypotheses suggest how explicit consideration of spatial scale and levels of biological organisation may help to understand and forecast phenological responses to climate change.     

Climate Change May Alter Breeding Ground Distributions of Eastern Migratory Monarchs (Danaus plexippus) via Range Expansion of Asclepias Host Plants

Climate change can profoundly alter species’ distributions due to changes in temperature, precipitation, or seasonality. Migratory monarch butterflies (Danaus plexippus) may be particularly susceptible to climate-driven changes in host plant abundance or reduced overwintering habitat. For example, climate change may significantly reduce the availability of overwintering habitat by restricting the amount of area with suitable microclimate conditions. However, potential effects of climate change on monarch northward migrations remain largely unknown, particularly with respect to their milkweed (Asclepias spp.) host plants. Given that monarchs largely depend on the genus Asclepias as larval host plants, the effects of climate change on monarch northward migrations will most likely be mediated by climate change effects on Asclepias. Here, I used MaxEnt species distribution modeling to assess potential changes in Asclepias and monarch distributions under moderate and severe climate change scenarios. First, Asclepias distributions were projected to extend northward throughout much of Canada despite considerable variability in the environmental drivers of each individual species. Second, Asclepias distributions were an important predictor of current monarch distributions, indicating that monarchs may be constrained as much by the availability of Asclepias host plants as environmental variables per se. Accordingly, modeling future distributions of monarchs, and indeed any tightly coupled plant-insect system, should incorporate the effects of climate change on host plant distributions. Finally, MaxEnt predictions of Asclepias and monarch distributions were remarkably consistent among general circulation models. Nearly all models predicted that the current monarch summer breeding range will become slightly less suitable for Asclepias and monarchs in the future. Asclepias, and consequently monarchs, should therefore undergo expanded northern range limits in summer months while encountering reduced habitat suitability throughout the northern migration.     

Capital and income breeding traits differentiate trophic match–mismatch dynamics in large herbivores

For some species, climate change has altered environmental conditions away from those in which life-history strategies evolved. In such cases, if adaptation does not keep pace with these changes, existing life-history strategies may become maladaptive and lead to population declines. We use life-history theory, with a specific emphasis on breeding strategies, in the context of the trophic match–mismatch framework to form generalizable hypotheses about population-level consumer responses to climate-driven perturbations in resource availability. We first characterize the income and breeding traits of sympatric caribou and muskoxen populations in western Greenland, and then test trait-based hypotheses about the expected reproductive performance of each population during a period of high resource variability at that site. The immediate reproductive performance of income breeding caribou decreased with trophic mismatch. In contrast, capital breeding muskoxen were relatively unaffected by current breeding season resource variability, but their reproductive performance was sensitive to resource conditions from previous years. These responses matched our expectations about how capital and income breeding strategies should influence population susceptibility to phenological mismatch. We argue for a taxon-independent assessment of trophic mismatch vulnerability based on a life-history strategy perspective in the context of prevailing environmental conditions.     

植物物候学研究进展

植物物候变化在研究陆地生态系统对气候变化的响应时被誉为"矿井中的金丝雀",全球气候变化愈演愈烈,重新引起了人们对植物物候研究的广泛关注。随着观测技术的发展,在各种空间和生态尺度上收集到的物候观测数据迅速累积,尽管已经在多个尺度上（物种、群落和景观尺度）观察到物候变化,但物候变化的机理仍然没有得到很好的理解。回顾了国内外植物物候研究的发展历程;总结了物候数据收集技术进展和全球物候变化的主要趋势;归纳了植物物候变化的机理与驱动因素;探讨了物候模型研究及物候对气候变化响应研究的主要方向。随着物候观测技术在不同尺度上应用的增加,物候研究进入了一个新的阶段。未来物候研究需要制定跨区域标准化观测指南,融合所有相关学科,改进物候模型,拓展研究区域;同时融合有效的历史物候资料,采用新技术和长期收集的物候数据为大数据时代植物物候学研究提供基础。     

Investigating the impact of climate change on crop phenological events in Europe with a phenology model

Predicting regional and global carbon and water dynamics requires a realistic representation of vegetation phenology. Vegetation models including cropland models exist (e.g. LPJmL, Daycent, SIBcrop, ORCHIDEE-STICS, PIXGRO) but they have various limitations in predicting cropland phenological events and their responses to climate change. Here, we investigate how leaf onset and offset days of major European croplands responded to changes in climate from 1971 to 2000 using a newly developed phenological model, which solely relies on climate data. Net ecosystem exchange (NEE) data measured with eddy covariance technique at seven sites in Europe were used to adjust model parameters for wheat, barley, and rapeseed. Observational data from the International Phenology Gardens were used to corroborate modeled phenological responses to changes in climate. Enhanced vegetation index (EVI) and a crop calendar were explored as alternative predictors of leaf onset and harvest days, respectively, over a large spatial scale. In each spatial model simulation, we assumed that all European croplands were covered by only one crop type. Given this assumption, the model estimated that the leaf onset days for wheat, barley, and rapeseed in Germany advanced by 1.6, 3.4, and 3.4 days per decade, respectively, during 1961–2000. The majority of European croplands (71.4%) had an advanced mean leaf onset day for wheat, barley, and rapeseed (7.0% significant), whereas 28.6% of European croplands had a delayed leaf onset day (0.9% significant) during 1971–2000. The trend of advanced onset days estimated by the model is similar to observations from the International Phenology Gardens in Europe. The developed phenological model can be integrated into a large-scale ecosystem model to simulate the dynamics of phenological events at different temporal and spatial scales. Crop calendars and enhanced vegetation index have substantial uncertainties in predicting phenological events of croplands. Caution should be exercised when using these data.     

Environmental effects on growth phenology of co-occurring Eucalyptus species

Growth is one of the most important phenological cycles in a plant’s life. Higher growth rates increase the competitive ability, survival and recruitment and can provide a measure of a plant’s adaptive capacity to climate variability and change. This study identified the growth relationship of six Eucalyptus species to variations in temperature, soil moisture availability, photoperiod length and air humidity over 12 months. The six species represent two naturally co-occurring groups of three species each representing warm-dry and the cool-moist sclerophyll forests, respectively. Warm-dry eucalypts were found to be more tolerant of higher temperatures and lower air humidity than the cool-moist eucalypts. Within groups, species-specific responses were detected with Eucalyptus microcarpa having the widest phenological niche of the warm-dry species, exhibiting greater resistance to high temperature and lower air humidity. Temperature dependent photoperiodic responses were exhibited by all the species except Eucalyptus tricarpa and Eucalyptus sieberi, which were able to maintain growth as photoperiod shortened but temperature requirements were fulfilled. Eucalyptus obliqua exhibited a flexible growth rate and tolerance to moisture limitation which enables it to maintain its growth rate as water availability changes. The wider temperature niche exhibited by E. sieberi compared with E. obliqua and Eucalyptus radiata may improve its competitive ability over these species where winters are warm and moisture does not limit growth. With climate change expected to result in warmer and drier conditions in south-east Australia, the findings of this study suggest all cool-moist species will likely suffer negative effects on growth while the warm-dry species may still maintain current growth rates. Our findings highlight that climate driven shifts in growth phenology will likely occur as climate changes and this may facilitate changes in tree communities by altering inter-specific competition.     

Phenological indices of avian reproduction: cryptic shifts and prediction across large spatial and temporal scales

Climate change‐induced shifts in phenology have important demographic consequences, and are frequently used to assess species' sensitivity to climate change. Therefore, developing accurate phenological predictions is an important step in modeling species' responses to climate change. The ability of such phenological models to predict effects at larger spatial and temporal scales has rarely been assessed. It is also not clear whether the most frequently used phenological index, namely the average date of a phenological event across a population, adequately captures phenological shifts in the distribution of events across the season. We use the long‐tailed tit Aegithalos caudatus (Fig. 1) as a case study to explore these issues. We use an intensive 17‐year local study to model mean breeding date and test the capacity of this local model to predict phenology at larger spatial and temporal scales. We assess whether local models of breeding initiation, termination, and renesting reveal phenological shifts and responses to climate not detected by a standard phenological index, that is, population average lay date. These models take predation timing/intensity into account. The locally‐derived model performs well at predicting phenology at the national scale over several decades, at both high and low temperatures. In the local model, a trend toward warmer Aprils is associated with a significant advance in termination dates, probably in response to phenological shifts in food supply. This results in a 33% reduction in breeding season length over 17 years – a substantial loss of reproductive opportunity that is not detected by the index of population average lay date. We show that standard phenological indices can fail to detect patterns indicative of negative climatic effects, potentially biasing assessments of species' vulnerability to climate change. More positively, we demonstrate the potential of detailed local studies for developing broader‐scale predictive models of future phenological shifts.     

Lessons Learned While Integrating Habitat,Dispersal, Disturbance,and Life-History Traits into Species Habitat Models Under Climate Change

We present an approach to modeling potential climate-driven changes in habitat for tree and bird species in the eastern United States. First, we took an empirical-statistical modeling approach, using randomForest, with species abundance data from national inventories combined with soil, climate, and landscape variables, to build abundance-based habitat models for 134 tree and 147 bird species. We produced lists of species for which suitable habitat tends to increase, decrease, or stay the same for any region. Independent assessments of trends of large trees versus seedlings across the eastern U.S. show that 37 of 40 species in common under both studies are currently trending as modeled. We developed a framework, ModFacs, in which we used the literature to assign default modification factor scores for species characteristics that cannot be readily assessed in such models, including 12 disturbance factors (for example, drought, fire, insect pests), nine biological factors (for example, dispersal, shade tolerance), and assessment scores of novel climates, long-distance extrapolations, and output variability by climate model and emission scenario. We also used a spatially explicit cellular model, SHIFT, to calculate colonization potentials for some species, based on their abundance, historic dispersal distances, and the fragmented nature of the landscape. By combining results from the three efforts, we can create projections of potential climate change impacts over the next 100 years or so. Here we emphasize some of the lessons we have learned over 16 years in hopes that they may help guide future experiments, modeling efforts, and management.     

A Geographic Mosaic of Climate Change Impacts on Terrestrial Vegetation: Which Areas Are Most at Risk?

Changes in climate projected for the 21^st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21^st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions.     

The effects of seasonal and long-term climatic variability on Neotropical flowering phenology: An ecoinformatic analysis of aerial pollen data

The phenological behavior of tropical forests changes in response to seasonal, annual, and long-term variation in temperature, precipitation, and solar irradiance. However, detecting the respective influence of these variables is difficult due to the relatively small range of change that is observed in the tropics. Analysis is further constrained by the limited duration of many phenological datasets. To address these limitations, we developed a predictive ecoinformatic model using multivariate linear regression and slope correlation analysis that can uncover statistically significant biological responses within short, noisy ecological time series. Our approach correlates all possible combinations of climatic and taxonomic variables using a series of random determination trials on shuffled environmental data. Seasonal and annual fluctuations in temperature, precipitation, and sunlight were used to predict the reproductive response of each individual taxon. This predictive model was applied to two seasonally sampled aerial pollen records collected between 1996 and 2006 from two Panamanian forests, Barro Colorado Island and Parque Nacional San Lorenzo. Our results highlight the degree to which pollen output responds to fine-scale variability in climate. Our results lend support to the hypothesis that the pollen output of tropical species is diminished with prolonged periods of heavy rainfall and that pollen output is sensitive to small, seasonal increases in temperature. Our ecoinformatic approach can be expanded to other observational phenological datasets to better understand how communities will respond to climate change and our results demonstrate the ability of aerial pollen data to track long-term changes in flowering phenology.     

Climate change,phenological shifts,eco-evolutionary responses and population viability: toward a unifying predictive approach

The debate on emission targets of greenhouse gasses designed to limit global climate change has to take into account the ecological consequences. One of the clearest ecological consequences is shifts in phenology. Linking these shifts to changes in population viability under various greenhouse gasses emission scenarios requires a unifying framework. We propose a box-in-a-box modeling approach that couples population models to phenological change. This approach unifies population modeling with both ecological responses to climate change as well as evolutionary processes. We advocate a mechanistic embedded correlative approach, where the link from genes to population is established using a periodic matrix population model. This periodic model has several major advantages: (1) it can include complex seasonal behaviors allowing an easy link with phenological shifts; (2) it provides the structure of the population at each phase, including the distribution of genotypes and phenotypes, allowing a link with evolutionary processes; and (3) it can incorporate the effect of climate at different time periods. We believe that the way climatologists have approached the problem, using atmosphere–ocean coupled circulation models in which components are gradually included and linked to each other, can provide a valuable example to ecologists. We hope that ecologists will take up this challenge and that our preliminary modeling framework will stimulate research toward a unifying predictive model of the ecological consequences of climate change.     

Butterfly phenology in Mediterranean mountains using space‐for‐time substitution

Inferring species' responses to climate change in the absence of long‐term time series data is a challenge, but can be achieved by substituting space for time. For example, thermal elevational gradients represent suitable proxies to study phenological responses to warming. We used butterfly data from two Mediterranean mountain areas to test whether mean dates of appearance of communities and individual species show a delay with increasing altitude, and an accompanying shortening in the duration of flight periods. We found a 14‐day delay in the mean date of appearance per kilometer increase in altitude for butterfly communities overall, and an average 23‐day shift for 26 selected species, alongside average summer temperature lapse rates of 3°C per km. At higher elevations, there was a shortening of the flight period for the community of 3 days/km, with an 8.8‐day average decline per km for individual species. Rates of phenological delay differed significantly between the two mountain ranges, although this did not seem to result from the respective temperature lapse rates. These results suggest that climate warming could lead to advanced and lengthened flight periods for Mediterranean mountain butterfly communities. However, although multivoltine species showed the expected response of delayed and shortened flight periods at higher elevations, univoltine species showed more pronounced delays in terms of species appearance. Hence, while projections of overall community responses to climate change may benefit from space‐for‐time substitutions, understanding species‐specific responses to local features of habitat and climate may be needed to accurately predict the effects of climate change on phenology.     

Variation in breeding phenology provides insights into drivers of long-term population change in harbour seals

Phenological trends provide important indicators of environmental change and population dynamics. However, the use of untested population-level measures can lead to incorrect conclusions about phenological trends, particularly when changes in population structure or density are ignored. We used individual-based estimates of birth date and lactation duration of harbour seals (Phoca vitulina) to investigate energetic consequences of changes in pupping phenology. Using generalized linear mixed models, we first demonstrate annual variation in pupping phenology. Second, we show a negative relationship between lactation duration and the timing of pupping, indicating that females who pup early nurse their pups longer, thereby highlighting lactation duration as a useful proxy of female condition and resource availability. Third, individual-based data were used to derive a population-level proxy that demonstrated an advance in pupping date over the last 25 years, co-incident with a reduction in population abundance that resulted from fisheries-related shootings. These findings demonstrate that phenological studies examining the impacts of climate change on mammal populations must carefully control for changes in population density and highlight how joint investigations of phenological and demographic change provide insights into the drivers of population declines.     

西安和宝鸡木本植物花期物候变化及温度敏感度对比

植物物候是指示生态系统对气候变化响应的重要证据。已有研究多基于代表性站点的物候观测数据研究物候特征及其对气候变化的响应规律。同一气候区内,不同站点的物候变化及对温度变化响应的敏感度是否一致仍需深入探讨。本文选择同属于暖温带湿润区汾渭平原气候区的西安和宝鸡为研究区,利用"中国物候观测网"在两个站点21个共有物种的开花始期和开花末期数据,比较了1987—2016年两站点各植物花期物候变化特征及其对温度变化响应的敏感度差异。结果表明,西安和宝鸡各物种的开花始期和开花末期均以提前趋势为主。大部分物种开花始期在西安的提前趋势(平均趋势-0.57 d/a)明显强于在宝鸡的提前趋势(平均趋势-0.29 d/a),但开花末期趋势差异不显著。除紫薇和迎春的敏感度差异较大外,其他物种开花始期和开花末期的温度敏感度在两站点间非常接近,无显著差异。由此可见,在同一气候区的不同站点,因增温幅度不同,植物的始花期变化存在较大差异,不能用单站点的物候变化反映整个气候区的物候变化。但同一植物在单站点的温度敏感度可以较好的反映同一气候区其他站点的植物物候-气候关系。本文研究结果可为利用有限站点的物候观测数据分析区域物候...     

Bias in phenology assessments based on first appearance data of butterflies

Data on the first appearance of species in the field season are widely used in phenological studies. However, there are probabilistic arguments for bias in estimates of phenological change if sampling methods or population abundances change. We examined the importance of bias in three measures of phenological change: (1) the date of the first X appearances, (2) the date of the first Y% of all first appearances and (3) the date of the first Z% of the individuals observed during the entire flight period. These measures were tested by resampling the data of the Dutch Butterfly Monitoring Scheme and by simulations using artificial data. We compared datasets differing in the number of sampling sites, population abundance and the start of the observation period. The date of the first X appearances proved to be sensitive to the number of sampling sites. Both the date of the first X appearances and the date of the first Y% of all first appearances were sensitive to population trend. No such biases were found for estimates of the first Z% of the flight period, but all three measures were sensitive to changes in the start of the observation period. The conclusions were similar for both the study on butterfly data and the simulation study. Bias in phenology assessments based on first appearance data may be considerable and should no longer be ignored in phenological research.