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Abstract JEM-EUSO is an international program for the development of space-based Ultra-High Energy Cosmic Ray observatories. The program consists of a series of missions which are either under development or in the data analysis phase. All instruments are based on a wide-field-of-view telescope, which operates in the near-UV range, designed to detect the fluorescence light emitted by extensive air showers in the atmosphere. We describe the simulation software ESAF in the framework of the JEM-EUSO program and explain the physical assumptions used. We present here the implementation of the JEM-EUSO, POEMMA, K-EUSO, TUS, Mini-EUSO, EUSO-SPB1 and EUSO-TA configurations in ESAF. For the first time ESAF simulation outputs are compared with experimental data.

The data presented in this article are related to the research paper entitled “Observation of night-time emissions of the Earth in the near UV range from the International Space Station with the Mini-EUSO detector” (Remote Sensing of Environment, Volume 284, January 2023, 113336, https://doi.org/10.1016/j.rse.2022.113336).The data have been acquired with the Mini-EUSO detector, an UV telescope operating in the range 290-430 nm and located inside the International Space Station. The detector was launched in August 2019, and it has started operations from the nadir-facing UV-transparent window in the Russian Zvezda module in October 2019. The data presented here refer to 32 sessions acquired between 2019-11-19 and 2021-05-06. The instrument consists of a Fresnel-lens optical system and a focal surface composed of 36 multi-anode photomultiplier tubes, each with 64 channels, for a total of 2304 channels with single photon counting sensitivity. The telescope, with a square field-of-view of 44°, has a spatial resolution on the Earth surface of 6.3 km and saves triggered transient phenomena with a temporal resolution of 2.5 µs and 320 µs. The telescope also operates in continuous acquisition at a 40.96 ms scale.In this article, large-area night-time UV maps obtained processing the 40.96 ms data, taking averages over regions of some specific geographical areas (e.g., Europe, North America) and over the entire globe, are presented. Data are binned into 0.1° × 0.1° or 0.05° × 0.05° cells (depending on the scale of the map) over the Earth's surface. Raw data are made available in the form of tables (latitude, longitude, counts) and .kmz files (containing the .png images). These are – to the best of our knowledge – the highest sensitivity data in this wavelength range and can be of use to various disciplines.

The most intense ionospheric storm observed in recent times occurred between 29 and 31 October 2003. The disturbances to the high-latitude regions set off several large-scale travelling ionospheric disturbances (LSTIDs), wave-like perturbations in the ionospheric electron density. This paper investigates one particular TID on 31 October 2003 using North American Global Positioning System (GPS) receiver network data and a tomographic imaging technique. The TID has an estimated period of 30 min and an estimated horizontal wavelength of 700 km and propagates south-westward over North America. The tomographic reconstruction of the wave is validated using a simulation of the observations and with independent observations from ionosondes and the CHAMP planar Langmuir probe. The results are discussed in the context of the magnetic and ionospheric conditions that may have contributed to the launch of the wave. Large-scale TIDs are challenging to study over large regions of the Earth, and the GPS network here is shown to offer a unique perspective on the spatial and temporal variation of the TID. The experimental results are backed up by simulations that show a denser network of receivers, as is available in more recent years, would produce improved accuracy in the TID imaging.

The data presented in this article are related to the research paper entitled " Observation of night-time emissions of the Earth in the near UV range from the International Space Station with the Mini-EUSO detector " (Remote Sensing of Environment, Volume 284, January 2023, 113336, https://doi.org/10.1016/j.rse.2022.113336). The data have been acquired with the Mini-EUSO detector, an UV telescope operating in the range 290-430 nm and located inside the International Space Station. The detector was launched in August 2019, and it has started operations from the nadir-facing UV-transparent window in the Russian Zvezda module in October 2019. The data presented here refer to 32 sessions acquired between 2019-11-19 and 2021-05-06. The instrument consists of a Fresnel-lens optical system and a focal surface composed of 36 multi-anode photomultiplier tubes, each with 64 channels, for a total of 2304 channels with single photon counting sensitivity. The telescope, with a square field-of-view of 44°, has a spatial resolution on the Earth surface of 6.3 km and saves triggered transient phenomena with a temporal resolution of 2.5 µs and 320 µs. The telescope also operates in continuous acquisition at a 40.96 ms scale. In this article, large-area night-time UV maps obtained processing the 40.96 ms data, taking averages over regions of some specific geographical areas (e.g., Europe, North America) and over the entire globe, are presented. Data are binned into 0.1 °  × 0.1 ° or 0.05 °  × 0.05 ° cells (depending on the scale of the map) over the Earth's surface. Raw data are made available in the form of tables (latitude, longitude, counts) and .kmz files (containing the .png images). These are - to the best of our knowledge - the highest sensitivity data in this wavelength range and can be of use to various disciplines., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Arctic plants are adapted to climatic variability, but their long-term responses to warming remain unclear. Responses may occur by range shifts, phenological adjustments in growth and reproduction, or both. Here, we compare distribution and phenology of 83 arctic and boreal mountain species, sampled identically in the early 20th (1917-1919) and 21st centuries (2017-2018) from a region of northern Sweden that has warmed significantly. We test two compensatory hypotheses to high-latitude warming-upward shifts in distribution, and earlier or extended growth and reproduction. For distribution, we show dramatic upward migration by 69% of species, averaging 6.1 m per decade, especially boreal woodland taxa whose upward expansion has reduced arctic montane habitat by 30%. Twenty percent of summit species showed distributional shifts but downward, especially moisture-associated snowbed flora. For phenology, we detected wide inter-annual variability in the onset of leafing and flowering in both eras. However, there was no detectable change in growing-season length, relating to two mechanisms. First, plot-level snow melt data starting in 1917 demonstrated that melt date, rather than vernal temperatures, better predicts plant emergence, with snow melt influenced by warmer years having greater snowfall-warmer springs did not always result in earlier emergence because snowbeds can persist longer. Second, the onset of reproductive senescence between eras was similar, even when plant emergence was earlier by a month, possibly due to intensified summer heat stress or hard-wired 'canalization' where senescence occurs regardless of summer temperature. Migrations in this system have possibly buffered arctic species against displacement by boreal expansion and warming, but ongoing temperature increases, woody plant invasion, and a potential lack of flexibility in timing of senescence may foreshadow challenges., (© 2021 John Wiley & Sons Ltd.)

Temperature sums are widely used to predict the seasonal timing of yearly recurring biological events, such as flowering, budburst, and hatching. We use a classic energy allocation model for annual plants to compare a strategy for reproductive timing that follows a temperature sum rule (TSR) with a strategy that follows an optimal control rule (OCR) maximizing reproductive output. We show that the OCR corresponds to a certain TSR regardless of how temperature is distributed over the growing season as long as the total temperature sum over the whole growing season is constant between years. We discuss such scenarios, thus outlining under which type of variable growth conditions TSR maximizes reproductive output and should be favored by natural selection. By providing an ultimate explanation for a well-documented empirical pattern this finding enhances the credibility of temperature sums as predictors of the timing of biological events. However, TSR and OCR respond in opposite directions when the total yearly temperature sum changes between years, representing, for example, variation in the length of the growing season. Our findings have implications for predicting optimal responses of organisms to climatic changes and suggest under which conditions natural selection should favor photoperiod versus temperature control., Competing Interests: None declared., (© 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Phenological responses to climate change (e.g., earlier leaf-out or egg hatch date) are now well documented and clearly linked to rising temperatures in recent decades. Such shifts in the phenologies of interacting species may lead to shifts in their synchrony, with cascading community and ecosystem consequences. To date, single-system studies have provided no clear picture, either finding synchrony shifts may be extremely prevalent [Mayor SJ, et al. (2017) Sci Rep 7:1902] or relatively uncommon [Iler AM, et al. (2013) Glob Chang Biol 19:2348-2359], suggesting that shifts toward asynchrony may be infrequent. A meta-analytic approach would provide insights into global trends and how they are linked to climate change. We compared phenological shifts among pairwise species interactions (e.g., predator-prey) using published long-term time-series data of phenological events from aquatic and terrestrial ecosystems across four continents since 1951 to determine whether recent climate change has led to overall shifts in synchrony. We show that the relative timing of key life cycle events of interacting species has changed significantly over the past 35 years. Further, by comparing the period before major climate change (pre-1980s) and after, we show that estimated changes in phenology and synchrony are greater in recent decades. However, there has been no consistent trend in the direction of these changes. Our findings show that there have been shifts in the timing of interacting species in recent decades; the next challenges are to improve our ability to predict the direction of change and understand the full consequences for communities and ecosystems., Competing Interests: The authors declare no conflict of interest.

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Premise of the Study: Herbarium specimens provide a robust record of historical plant phenology (the timing of seasonal events such as flowering or fruiting). However, the difficulty of aggregating phenological data from specimens arises from a lack of standardized scoring methods and definitions for phenological states across the collections community., Methods and Results: To address this problem, we report on a consensus reached by an iDigBio working group of curators, researchers, and data standards experts regarding an efficient scoring protocol and a data-sharing protocol for reproductive traits available from herbarium specimens of seed plants. The phenological data sets generated can be shared via Darwin Core Archives using the Extended MeasurementOrFact extension., Conclusions: Our hope is that curators and others interested in collecting phenological trait data from specimens will use the recommendations presented here in current and future scoring efforts. New tools for scoring specimens are reviewed.

Phenological changes among plants due to climate change are well documented, but often hard to interpret. In order to assess the adaptive value of observed changes, we study how annual plants with and without growth constraints should optimize their flowering time when productivity and season length changes. We consider growth constraints that depend on the plant's vegetative mass: self-shading, costs for nonphotosynthetic structural tissue and sibling competition. We derive the optimal flowering time from a dynamic energy allocation model using optimal control theory. We prove that an immediate switch (bang-bang control) from vegetative to reproductive growth is optimal with constrained growth and constant mortality. Increasing mean productivity, while keeping season length constant and growth unconstrained, delayed the optimal flowering time. When growth was constrained and productivity was relatively high, the optimal flowering time advanced instead. When the growth season was extended equally at both ends, the optimal flowering time was advanced under constrained growth and delayed under unconstrained growth. Our results suggests that growth constraints are key factors to consider when interpreting phenological flowering responses. It can help to explain phenological patterns along productivity gradients, and links empirical observations made on calendar scales with life-history theory., (© 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.)

Many migratory bird species have advanced their spring arrival during the latest decades, most probably due to climate change. However, studies on migratory phenology in the period before recent global warming are scarce. We have analyzed a historical dataset (1873-1917) of spring arrival to southern and central Sweden of 14 migratory bird species. In addition, we have used relative differences between historical and present-day observations (1984-2013) to evaluate the effect of latitude and migratory strategy on day of arrival over time. There was a larger change in spring phenology in short-distance migrants than in long-distance migrants. Interestingly, the results further suggest that climate change has affected the phenology of short-distance migrants more in southern than in central Sweden. The results suggest that the much earlier calculated arrival to southern Sweden among short-distance migrants mirrors a change in location of wintering areas, hence, connecting migration phenology and wintering range shifts.

Climate change is affecting high-altitude and high-latitude communities in significant ways. In the short growing season of subarctic habitats, it is essential that the timing and duration of phenological phases match favorable environmental conditions. We explored the time of the first appearance of flowers (first flowering day, FFD) and flowering duration across subarctic species composing different communities, from boreal forest to tundra, along an elevational gradient (600-800 m). The study was conducted on Mount Irony (856 m), North-East Canada (54°90'N, 67°16'W) during summer 2012. First, we quantified phylogenetic signal in FFD at different spatial scales. Second, we used phylogenetic comparative methods to explore the relationship between FFD, flowering duration, and elevation. We found that the phylogenetic signal for FFD was stronger at finer spatial scales and at lower elevations, indicating that closely related species tend to flower at similar times when the local environment is less harsh. The comparatively weaker phylogenetic signal at higher elevation may be indicative of convergent evolution for FFD. Flowering duration was correlated significantly with mean FFD, with later-flowering species having a longer flowering duration, but only at the lowest elevation. Our results indicate significant evolutionary conservatism in responses to phenological cues, but high phenotypic plasticity in flowering times. We suggest that phylogenetic relationships should be considered in the search for predictions and drivers of flowering time in comparative analyses, because species cannot be considered as statistically independent. Further, phenological drivers should be measured at spatial scales such that variation in flowering matches variation in environment.

Premise of the Study: Numerous long-term studies in seasonal habitats have tracked interannual variation in first flowering date (FFD) in relation to climate, documenting the effect of warming on the FFD of many species. Despite these efforts, long-term phenological observations are still lacking for many species. If we could forecast responses based on taxonomic affinity, however, then we could leverage existing data to predict the climate-related phenological shifts of many taxa not yet studied., Methods: We examined phenological time series of 1226 species occurrences (1031 unique species in 119 families) across seven sites in North America and England to determine whether family membership (or family mean FFD) predicts the sensitivity of FFD to standardized interannual changes in temperature and precipitation during seasonal periods before flowering and whether families differ significantly in the direction of their phenological shifts., Key Results: Patterns observed among species within and across sites are mirrored among family means across sites; early-flowering families advance their FFD in response to warming more than late-flowering families. By contrast, we found no consistent relationships among taxa between mean FFD and sensitivity to precipitation as measured here., Conclusions: Family membership can be used to identify taxa of high and low sensitivity to temperature within the seasonal, temperate zone plant communities analyzed here. The high sensitivity of early-flowering families (and the absence of early-flowering families not sensitive to temperature) may reflect plasticity in flowering time, which may be adaptive in environments where early-season conditions are highly variable among years.

Phenological shifts linked to global warming reflect the ability of organisms to track changing climatic conditions. However, different organisms track global warming differently and there is an increasing interest in the link between phenological traits and plant abundance and distribution. Long-term data sets are often used to estimate phenological traits to climate change, but so far little has been done to evaluate the quality of these estimates. Here, we use a 73-year long data series of first flowering dates for 25 species from north-temperate Sweden to evaluate (i) correlations between first flowering dates and year for different time periods and (ii) linear regression models between first flowering date and mean monthly temperatures in preceding months. Furthermore, we evaluate the potential of this kind of data to estimate the phenological temperature sensitivities (i.e. number of days phenological change per degree temperature change, β60) in such models. The sign of the correlations between first flowering dates and year were highly inconsistent among different time periods, highlighting that estimates of phenological change are sensitive to the specific time period used. The first flowering dates of all species were correlated with temperature, but with large differences in both the strength of the response and the period(s) of the year that were most strongly associated with phenological variation. Finally, our analyses indicated that legacy data sets need to be relatively long-term to be useful for estimating phenological temperature sensitivities (β60) for inter-specific comparisons. In 10-year long observation series only one out of 24 species reached ≥80 % probability of estimating temperature sensitivity (β60) within a ±1 range, and 17 out of 24 species reached ≥80 % probability when observation series were 20 years or shorter. The standard error for β60 ranged from 0.6 to 2.0 for 10-year long observation series, and 19 out of 24 species reached SE < 1 after 15 years. In general, late flowering species will require longer time series than early flowering species.

Long-term phenology monitoring has documented numerous examples of changing flowering dates during the last century. A pivotal question is whether these phenological responses are adaptive or not under directionally changing climatic conditions. We use a classic dynamic growth model for annual plants, based on optimal control theory, to find the fitness-maximizing flowering time, defined as the switching time from vegetative to reproductive growth. In a typical scenario of global warming, with advanced growing season and increased productivity, optimal flowering time advances less than the start of the growing season. Interestingly, increased temporal spread in production over the season may either advance or delay the optimal flowering time depending on overall productivity or season length. We identify situations where large phenological changes are necessary for flowering time to remain optimal. Such changes also indicate changed selection pressures. In other situations, the model predicts advanced phenology on a calendar scale, but no selection for early flowering in relation to the start of the season. We also show that the optimum is more sensitive to increased productivity when productivity is low than when productivity is high. All our results are derived using a general, graphical method to calculate the optimal flowering time applicable for a large range of shapes of the seasonal production curve. The model can thus explain apparent maladaptation in phenological responses in a multitude of scenarios of climate change. We conclude that taking energy allocation trade-offs and appropriate time scales into account is critical when interpreting phenological patterns., (© 2012 Blackwell Publishing Ltd.)

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

Biotic pollination is thought to correlate with increased interspecific competition for pollination among plants and a higher speciation rate. In this study we compared patterns of flowering phenology and species richness between abiotically (wind) and biotically pollinated plants, using phylogenetically independent contrasts. We compiled phenological data from eight local seasonal floras, in which we found geographically overlapping sister clades. Of 65 documented origins of wind pollination, we were able to use up to 17 independent contrasts. In contrast to previous studies we found no difference in global species richness between wind- and biotically pollinated sister clades. Regarding phenology, we found wider phenological spread in biotically pollinated clades, earlier flowering onset in wind-pollinated trees, but no difference in duration of flowering between pollination modes. These results corroborate previous views that niche space is more constrained for wind-pollinated species, and that niche partitioning is less important between wind-pollinated plants compared to plants pollinated by animals.