Assessing the frequency and drivers of early‐greening in broad‐leaved woodlands along a latitudinal gradient in southern Africa

Savannas are the only deciduous system where new leaf flush pre‐empts the onset of suitable conditions for growth, a phenological phenomenon known as early‐greening. Limited understanding of the frequency and drivers of the occurrence of early‐greening in southern African savanna trees exists. We aimed to estimate the frequency of early‐greening events across southern Africa and investigated potential environmental drivers of green‐up. We selected and compared seven broad‐leaved woodland sites where Burkea africana was a dominant species using remotely sensed data along a latitudinal gradient from South Africa to Zambia. Normalized difference vegetation index (NDVI) values were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery at each site from January 2002 to June 2014. Using an austral year (July 1st–June 30th), early‐greening was recorded if the green‐up start date occurred prior to the onset date of seasonal rainfall. A latitudinal gradient of early‐green‐up was detected across southern Africa (R² = 0.74) with the two most northerly (Zambian) sites showing the earliest and most consistent green‐up start dates (3 October ± 5.34 days). A strong latitudinal gradient was observed between the variability in the amount of rainfall in the first 6 months of green‐up and the green‐up start dates across southern Africa (R² = 0.92). Photoperiod appeared to play a role in areas where the onset of rainfall commenced late into the austral year. Mean maximum temperatures recorded 10 days prior to green‐up start dates suggested a potential threshold of about 35°C, which could drive early‐greening in the absence of rainfall. Correlations between the proportion of early‐greening years and the above mentioned environmental factors indicated that rainfall variability had the strongest influence over the observed phenological gradient (R² = 0.96). Understanding early‐greening in complex savanna systems is a vital step in furthering predictive phenological models under changing climatic conditions.     

Unexpected role of winter precipitation in determining heat requirement for spring vegetation green‐up at northern middle and high latitudes

Heat requirement, expressed in growing degree days (GDD), is a widely used method to assess and predict the effect of temperature on plant development. Until recently, the analysis of spatial patterns of GDD requirement for spring vegetation green‐up onset was limited to local and regional scales, mainly because of the sparse and aggregated spatial availability of ground phenology data. Taking advantage of the large temporal and spatial scales of remote sensing‐based green‐up onset data, we studied the spatial patterns of GDD requirement for vegetation green‐up at northern middle and high latitudes. We further explored the correlations between GDD requirement for vegetation green‐up and previous winter season chilling temperatures and precipitation, using spatial partial correlations. We showed that GDD requirement for vegetation green‐up onset declines towards the north at a mean rate of 18.8 °C‐days per degree latitude between 35°N and 70°N, and vary significantly among different vegetation types. Our results confirmed that the GDD requirement for vegetation green‐up is negatively correlated with previous winter chilling, which was defined as the number of chilling days from the day when the land surface froze in the previous autumn to the day of green‐up onset. This negative correlation is a well‐known phenomenon from local studies. Interestingly, irrespective of the vegetation type, we also found a positive correlation between the GDD requirement and previous winter season precipitation, which was defined as the sum of the precipitation of the month when green‐up onset occur and the precipitation that occurred during the previous 2 months. Our study suggests that GDD requirement, chilling and precipitation may have complex interactions in their effects on spring vegetation green‐up phenology. These findings have important implications for improving phenology models and could therefore advance our understanding of the interplay between spring phenology and carbon fluxes.     

The extent of shifts in vegetation phenology between rural and urban areas within a human‐dominated region

Urbanization is one of the major environmental challenges facing the world today. One of its particularly pressing effects is alterations to local and regional climate through, for example, the Urban Heat Island. Such changes in conditions are likely to have an impact on the phenology of urban vegetation, which will have knock‐on implications for the role that urban green infrastructure can play in delivering multiple ecosystem services. Here, in a human‐dominated region, we undertake an explicit comparison of vegetation phenology between urban and rural zones. Using satellite‐derived MODIS‐EVI data from the first decade of the 20th century, we extract metrics of vegetation phenology (date of start of growing season, date of end of growing season, and length of season) for Britain's 15 largest cities and their rural surrounds. On average, urban areas experienced a growing season 8.8 days longer than surrounding rural zones. As would be expected, there was a significant decline in growing season length with latitude (by 3.4 and 2.4 days/degree latitude in rural and urban areas respectively). Although there is considerable variability in how phenology in urban and rural areas differs across our study cities, we found no evidence that built urban form influences the start, end, or length of the growing season. However, the difference in the length of the growing season between rural and urban areas was significantly negatively associated with the mean disposable household income for a city. Vegetation in urban areas deliver many ecosystem services such as temperature mitigation, pollution removal, carbon uptake and storage, the provision of amenity value for humans and habitat for biodiversity. Given the rapid pace of urbanization and ongoing climate change, understanding how vegetation phenology will alter in the future is important if we wish to be able to manage urban greenspaces effectively.     

Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006

Aim We intend to characterize and understand the spatial and temporal patterns of vegetation phenology shifts in North America during the period 1982–2006. Location North America. Methods A piecewise logistic model is used to extract phenological metrics from a time‐series data set of the normalized difference vegetation index (NDVI). An extensive comparison between satellite‐derived phenological metrics and ground‐based phenology observations for 14,179 records of 73 plant species at 802 sites across North America is made to evaluate the information about phenology shifts obtained in this study. Results The spatial pattern of vegetation phenology shows a strong dependence on latitude but a substantial variation along the longitudinal gradient. A delayed dormancy onset date (0.551 days year^?1, P= 0.013) and an extended growing season length (0.683 days year^?1, P= 0.011) are found over the mid and high latitudes in North America during 1982–2006, while no significant trends in greenup onset are observed. The delayed dormancy onset date and extended growing season length are mainly found in the shrubland biome. An extensive validation indicates a strong robustness of the satellite‐derived phenology information. Main conclusions It is the delayed dormancy onset date, rather than an advanced greenup onset date, that has contributed to the prolonged length of the growing season over the mid and high latitudes in North America during recent decades. Shrublands contribute the most to the delayed dormancy onset date and the extended growing season length. This shift of vegetation phenology implies that vegetation activity in North America has been altered by climatic change, which may further affect ecosystem structure and function in the continent.     

Climatic factors controlling interannual variability of the onset of vegetation phenology in the northern Sub-Saharan Africa from 1988 to 2013

Satellite-based evaluations of change in vegetation phenology have been explored extensively but land cover-specific climate factors driving these anomalous changes are not fully understood in northern Sub-Saharan Africa. In this study, we identified the climatic factors controlling the start of the season (SOS) extracted from GIMMS NDVI from 1988 to 2013 with onset of rainy season (ORS), annual mean temperature (Temp) and precipitation (PP) through the stepwise regression analysis. The results showed that the SOS shifted towards a late onset in a northward direction with distinct earlier and later trends in grassland and cropland, respectively. The stepwise regression has successfully built a model between SOS and its drivers in 46.0% of the total pixels, where its primary factor differed regionally across land covers. The ORS explained the local anomalous SOS change primarily at 44.7% of the pixels where the model was built. Although the ORS was the primary dominant factor in savannah and cropland, the Temp and PP were leading in grassland and shrubland, respectively, and all factors contributed evenly in evergreen forest. The difference of land cover-specific primary factor implicates complex process in dependency of local vegetation phenology on physiological traits and climate regime across land cover in Sub-Saharan Africa.     

Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa

Questions: What are the patterns of remotely sensed vegetation phenology, including their inter‐annual variability, across South Africa? What are the phenological attributes that contribute most to distinguishing the different biomes? How well can the distribution of the recently redefined biomes be predicted based on remotely sensed, phenology and productivity metrics? Location: South Africa. Method: Ten‐day, 1 km, NDVI AVHRR were analysed for the period 1985 to 2000. Phenological metrics such as start, end and length of the growing season and estimates of productivity, based on small and large integral (SI, LI) of NDVI curve, were extracted and long‐term means calculated. A random forest regression tree was run using the metrics as the input variables and the biomes as the dependent variable. A map of the predicted biomes was reproduced and the differentiating importance of each metric assessed. Results: The phenology metrics (e.g. start of growing season) showed a clear relationship with the seasonality of rainfall, i.e. winter and summer growing seasons. The distribution of the productivity metrics, LI and SI were significantly correlated with mean annual precipitation. The regression tree initially split the biomes based on vegetation production and then by the seasonality of growth. A regression tree was used to produce a predicted biome map with a high level of accuracy (73%). Main conclusion: Regression tree analysis based on remotely sensed metrics performed as good as, or better than, previous climate‐based predictors of biome distribution. The results confirm that the remotely sensed metrics capture sufficient functional diversity to classify and map biome level vegetation patterns and function.     

Divergent carbon cycle response of forest and grass‐dominated northern temperate ecosystems to record winter warming

Northern temperate ecosystems are experiencing warmer and more variable winters, trends that are expected to continue into the foreseeable future. Despite this, most studies have focused on climate change impacts during the growing season, particularly when comparing responses across different vegetation cover types. Here we examined how a perennial grassland and adjacent mixed forest ecosystem in New Hampshire, United States, responded to a period of highly variable winters from 2014 through 2017 that included the warmest winter on record to date. In the grassland, record‐breaking temperatures in the winter of 2015/2016 led to a February onset of plant growth and the ecosystem became a sustained carbon sink well before winter ended, taking up roughly 90 g/m² more carbon during the winter to spring transition than in other recorded years. The forest was an unusually large carbon source during the same period. While forest photosynthesis was restricted by leaf‐out phenology, warm winter temperatures caused large pulses of ecosystem respiration that released nearly 230 g C/m² from February through April, more than double the carbon losses during that period in cooler years. These findings suggest that, as winters continue to warm, increases in ecosystem respiration outside the growing season could outpace increases in carbon uptake during a longer growing season, particularly in forests that depend on leaf‐out timing to initiate carbon uptake. In ecosystems with a perennial leaf habit, warming winter temperatures are more likely to increase ecosystem carbon uptake through extension of the active growing season. Our results highlight the importance of understanding relationships among antecedent winter conditions and carbon exchange across land‐cover types to understand how landscape carbon exchange will change under projected climate warming.     

Functional differences between summer and winter season rain assessed with MODIS‐derived phenology in a semi‐arid region

Questions: We asked several linked questions about phenology and precipitation relationships at local, landscape, and regional spatial scales within individual seasons, between seasons, and between year temporal scales. (1) How do winter and summer phenological patterns vary in response to total seasonal rainfall? (2) How are phenological rates affected by the previous season rainfall? (3) How does phenological variability differ at landscape and regional spatial scales and at season and inter‐annual temporal scales? Location: Southern Arizona, USA. Methods: We compared satellite‐derived phenological variation between 38 distinct 625‐km² landscapes distributed in the northern Sonoran Desert region from 2000 to 2007. Regression analyses were used to identify relationships between landscape phenology dynamics in response to precipitation variability across multiple spatial and temporal scales. Results: While both summer and winter seasons show increases of peak greenness and peak growth with more precipitation, the timing of peak growth was advanced with more precipitation in winter, while the timing of peak greenness was advanced with more precipitation in summer. Surprisingly, summer maximum growth was negatively affected by winter precipitation. The spatial variations between summer and winter phenology were similar in magnitude and response. Larger‐scale spatial and temporal variation showed strong differences in precipitation patterns; however the magnitudes of phenological spatial variability in these two seasons were similar. Conclusions: Vegetation patterns were clearly coupled to precipitation variability, with distinct responses at alternative spatial and temporal scales. Disaggregating vegetation into phenological variation, spanning value, timing, and integrated components revealed substantial complexity in precipitation‐phenological relationships.     

基于生态地理分区的大兴安岭植被物候时空变化

植被与气候的关系十分密切,植被物候可作为全球气候变化的指示器.大兴安岭位于我国最北部,对气候变化较为敏感,研究该区植被物候的时空变化对评估全球变化对陆地生态系统的影响具有重要意义.依据中国生态地理区划图,将大兴安岭划分为4个生态研究区域,本文利用GIMMS NDVI 3g遥感数据集分析1982—2012年大兴安岭整体及各生态地理分区植被物候变化.结果表明: 研究期间,所有分区植被生长季开始日期均表现为提前趋势,生长季结束日期均表现为推迟趋势.植被物候对气候因子变化敏感,尤其是对气温的敏感程度高于降水,其中,北段山地落叶针叶林区植被生长季开始日期与春季温度呈显著负相关;除南段草原区外,其他3个分区植被生长季结束日期均与秋季降水呈显著负相关.从整体来看,植被物候随海拔、纬度的变化趋势明显.     

Land Surface Phenology in the Tropics: The Role of Climate and Topography in a Snow-Free Mountain

Leaf phenology represents a major temporal component of ecosystem functioning, and understanding the drivers of seasonal variation in phenology is essential to understand plant responses to climate change. We assessed the patterns and drivers of land surface phenology, a proxy for leafing phenology, for the meridional Espinhaço Range, a South American tropical mountain comprising a mosaic of savannas, dry woodlands, montane vegetation and moist forests. We used a 14-year time series of MODIS/NDVI satellite images, acquired between 2001 and 2015, and extracted phenological indicators using the TIMESAT algorithm. We obtained precipitation data from the Tropical Rainfall Measuring Mission, land surface temperature from the MODIS MOD11A2 product, and cloud cover frequency from the MODIS MOD09GA product. We also calculated the topographic wetness index and simulated clear-sky radiation budgets based on the SRTM elevation model. The relationship between phenology and environmental drivers was assessed using general linear models. Temporal displacement in the start date of the annual growth season was more evident than variations in season length among vegetation types, indicating a possible temporal separation in the use of resources. Season length was inversely proportional to elevation, decreasing 1.58 days per 100 m. Green-up and senescence rates were faster where annual temperature amplitude was higher. We found that water and light availability, modulated by topography, are the most likely drivers of land surface phenology in the region, determining the start, end and length of the growing season. Temperature had an important role in determining the rates of leaf development and the strength of vegetation seasonality, suggesting that tropical vegetation is also sensitive to latitudinal temperature changes, regardless of the elevational gradient. Our work improves the current understanding of phenological strategies in the seasonal tropics and emphasizes the importance of topography in shaping light and water availability for leaf development in snow-free mountains.     

When to start and when to stop: Effects of climate on breeding in a multi‐brooded songbird

Climate warming has been shown to affect the timing of the onset of breeding of many bird species across the world. However, for multi‐brooded species, climate may also affect the timing of the end of the breeding season, and hence also its duration, and these effects may have consequences for fitness. We used 28 years of field data to investigate the links between climate, timing of breeding, and breeding success in a cooperatively breeding passerine, the superb fairy‐wren (Malurus cyaneus). This multi‐brooded species from southeastern Australia has a long breeding season and high variation in phenology between individuals. By applying a “sliding window” approach, we found that higher minimum temperatures in early spring resulted in an earlier start and a longer duration of breeding, whereas less rainfall and more heatwaves (days > 29°C) in late summer resulted in an earlier end and a shorter duration of breeding. Using a hurdle model analysis, we found that earlier start dates did not predict whether or not females produced any young in a season. However, for successful females who produced at least one young, earlier start dates were associated with higher numbers of young produced in a season. Earlier end dates were associated with a higher probability of producing at least one young, presumably because unsuccessful females kept trying when others had ceased. Despite larger scale trends in climate, climate variables in the windows relevant to this species’ phenology did not change across years, and there were no temporal trends in phenology during our study period. Our results illustrate a scenario in which higher temperatures advanced both start and end dates of individuals’ breeding seasons, but did not generate an overall temporal shift in breeding times. They also suggest that the complexity of selection pressures on breeding phenology in multi‐brooded species may have been underestimated.     

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf‐out times across groupings of species in a dynamic vegetation model

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf‐out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf‐out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970–2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf‐out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf‐out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.     

Public Internet‐connected cameras used as a cross‐continental ground‐based plant phenology monitoring system

Plant phenology is highly sensitive to changes in environmental conditions and can vary widely across landscapes. Current observation methods are either manual for small‐scale, high precision measurements or by satellite remote sensing for large‐scale, low spatial resolution measurement. The development of inexpensive approaches is necessary to advance large scale, high precision phenology monitoring. The use of publicly available, Internet‐connected cameras, often associated with airports, national parks, and roadway conditions, for detecting and monitoring plant phenology at a continental scale can augment existing ground and satellite‐based methodologies. We collected twice‐daily images from over 1100 georeferenced public cameras across North America from February 2008 to 2009. Using a test subset of these cameras, we compared modeled spring ‘green‐up’ with that from co‐occurring remote sensing products. Although varying image exposure and color correction introduced noise to camera measurements, we were able to correlate spring green‐up across North America with visual validation from images and detect a latitudinal trend. Public cameras had an equivalent or higher ability to detect spring compared with satellite‐based data for corresponding locations, with fewer numbers of poor quality days, shorter continuous bad data days, and significantly lower errors of spring estimates. Manual image segmentation into deciduous, evergreen, and understory vegetation allowed detection of spring and fall onset for multiple vegetation types. Additional advantages of a public camera‐based monitoring system include frequent image capture (subdaily) and the potential to detect quantitative responses to environmental changes in organisms, species, and communities. Public cameras represent a relatively untapped and freely available resource for supporting large‐scale ecological and environmental monitoring.     

Cambial Growth Season of Brevi-Deciduous Brachystegia spiciformis Trees from South Central Africa Restricted to Less than Four Months

We investigate cambial growth periodicity in Brachystegia spiciformis, a dominant tree species in the seasonally dry miombo woodland of southern Africa. To better understand how the brevi-deciduous (experiencing a short, drought-induced leaf fall period) leaf phenology of this species can be linked to a distinct period of cambial activity, we applied a bi-weekly pinning to six trees in western Zambia over the course of one year. Our results show that the onset and end of cambial growth was synchronous between trees, but was not concurrent with the onset and end of the rainy season. The relatively short (three to four months maximum) cambial growth season corresponded to the core of the rainy season, when 75% of the annual precipitation fell, and to the period when the trees were at full photosynthetic capacity. Tree-ring studies of this species have found a significant relationship between annual tree growth and precipitation, but we did not observe such a correlation at intra-annual resolution in this study. Furthermore, a substantial rainfall event occurring after the end of the cambial growth season did not induce xylem initiation or false ring formation. Low sample replication should be taken into account when interpreting the results of this study, but our findings can be used to refine the carbon allocation component of process-based terrestrial ecosystem models and can thus contribute to a more detailed estimation of the role of the miombo woodland in the terrestrial carbon cycle. Furthermore, we provide a physiological foundation for the use of Brachystegia spiciformis tree-ring records in paleoclimate research.     

Landscape controls on the timing of spring,autumn, and growing season length in mid‐Atlantic forests

The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field‐based and remote‐sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium‐resolution remote sensing data, organized by day of year, to explore the influence of climate‐related landscape factors on the timing of spring and autumn leaf‐area trajectories in mid‐Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape‐scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.     

Temperature and snowfall trigger alpine vegetation green‐up on the world's roof

Rapid temperature increase and its impacts on alpine ecosystems in the Qinghai–Tibetan Plateau, the world's highest and largest plateau, are a matter of global concern. Satellite observations have revealed distinctly different trend changes and contradicting temperature responses of vegetation green‐up dates, leading to broad debate about the Plateau's spring phenology and its climatic attribution. Large uncertainties in remote‐sensing estimates of phenology significantly limit efforts to predict the impacts of climate change on vegetation growth and carbon balance in the Qinghai–Tibetan Plateau, which are further exacerbated by a lack of detailed ground observation calibration. Here, we revealed the spatiotemporal variations and climate drivers of ground‐based herbaceous plant green‐up dates using 72 green‐up datasets for 22 herbaceous plant species at 23 phenological stations, and corresponding daily mean air temperature and daily precipitation data from 19 climate stations across eastern and southern parts of the Qinghai–Tibetan Plateau from 1981 to 2011. Results show that neither the continuously advancing trend from 1982 to 2011, nor a turning point in the mid to late 1990s as reported by remote‐sensing studies can be verified by most of the green‐up time series, and no robust evidence for a warmer winter‐induced later green‐up dates can be detected. Thus, chilling requirements may not be an important driver influencing green‐up responses to spring warming. Moreover, temperature‐only control of green‐up dates appears mainly at stations with relatively scarce preseason snowfall and lower elevation, while coupled temperature and precipitation controls of green‐up dates occur mostly at stations with relatively abundant preseason snowfall and higher elevation. The diversified interactions between snowfall and temperature during late winter to early spring likely determine the spatiotemporal variations of green‐up dates. Therefore, prediction of vegetation growth and carbon balance responses to global climate change on the world's roof should integrate both temperature and snowfall variations.     

Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis

The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite‐derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green‐up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green‐up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green‐up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green‐up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green‐up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature.     

Predicting bird phenology from space: satellite‐derived vegetation green‐up signal uncovers spatial variation in phenological synchrony between birds and their environment

Population‐level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite‐derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green‐up for a 385‐ha mixed‐deciduous woodland. Using data spanning 13 years, we demonstrate that annual population‐level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite‐derived spring vegetation phenology. We go on to show that timing of local vegetation green‐up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote‐sensed vegetation phenology and reproductive phenology in both species. Marked within‐population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small‐scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within‐population variation could broaden the scale and scope of studies exploring phenological synchrony between organisms and their environment.     

Optimal germination timing in unpredictable environments: the importance of dormancy for both among‐ and within‐season variation

For organisms living in unpredictable environments, timing important life‐history events is challenging. One way to deal with uncertainty is to spread the emergence of offspring across multiple years via dormancy. However, timing of emergence is not only important among years, but also within each growing season. Here, we study the evolutionary interactions between germination strategies that deal with among‐ and within‐season uncertainty. We use a modelling approach that considers among‐season dormancy and within‐season germination phenology of annual plants as potentially independent traits and study their separate and joint evolution in a variable environment. We find that higher among‐season dormancy selects for earlier germination within the growing season. Furthermore, our results indicate that more unpredictable natural environments can counter‐intuitively select for less risk‐spreading within the season. Furthermore, strong priority effects select for earlier within‐season germination phenology which in turn increases the need for bet hedging through among‐season dormancy.     

Biocontrolled soil nutrient distribution under the influence of an oxalogenic-oxalotrophic ecosystem

Background and aims

Root phenology is important in controlling carbon and nutrient fluxes in terrestrial ecosystems, yet, remains largely unexplored, especially in the Arctic. We compared below- and aboveground phenology and ending of the growing season in two contrasting vegetation types of subarctic tundra: heath and meadow, and their response to experimental warming in autumn.

Methods

Root phenology was measured in-situ with minirhizotrons and compared with aboveground phenology assessed with repeat digital photography.

Results

The end of the growing season, both below- and aboveground, was similar in meadow and heath and the belowground growing season ended later than aboveground in the two vegetation types. Root growth was higher and less equally distributed over time in meadow compared to heath. The warming treatment increased air and soil temperature by 0.5 °C and slightly increased aboveground greenness, but did not affect root growth or prolong the below- and aboveground growing season in either of the vegetation types.

Conclusions

These results imply that vegetation types differ in root dynamics and suggest that other factors than temperature control autumnal root growth in these ecosystems. Further investigations of root phenology will help to identify those drivers, in which including responses of functionally contrasting vegetation types will help to estimate how climate change affects belowground processes and their roles in ecosystem function.