Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016

Spatial variability in herbaceous plant phenology is mostly explained by variability in temperature but also by photoperiod and functional traits

Whereas temporal variability of plant phenology in response to climate change has already been well studied, the spatial variability of phenology is not well understood. Given that phenological shifts may affect biotic interactions, there is a need to investigate how the variability in environmental factors relates to the spatial variability in herbaceous species' phenology by at the same time considering their functional traits to predict their general and species-specific responses to future climate change. In this project, we analysed phenology records of 148 herbaceous species, which were observed for a single year by the PhenObs network in 15 botanical gardens. For each species, we characterised the spatial variability in six different phenological stages across gardens. We used boosted regression trees to link these variabilities in phenology to the variability in environmental parameters (temperature, latitude and local habitat conditions) as well as species traits (seed mass, vegetative height, specific leaf area and temporal niche) hypothesised to be related to phenology variability. We found that spatial variability in the phenology of herbaceous species was mainly driven by the variability in temperature but also photoperiod was an important driving factor for some phenological stages. In addition, we found that early-flowering and less competitive species characterised by small specific leaf area and vegetative height were more variable in their phenology. Our findings contribute to the field of phenology by showing that besides temperature, photoperiod and functional traits are important to be included when spatial variability of herbaceous species is investigated.

Uniting Experiments and Big Data to advance ecology and conservation

Many ecologists increasingly advocate for research frameworks centered on the use of 'big data' to address anthropogenic impacts on ecosystems. Yet, experiments are often considered essential for identifying mechanisms and informing conservation interventions. We highlight the complementarity of these research frameworks and expose largely untapped opportunities for combining them to speed advancements in ecology and conservation. With nascent but increasing application of model integration, we argue that there is an urgent need to unite experimental and big data frameworks throughout the scientific process. Such an integrated framework offers potential for capitalizing on the benefits of both frameworks to gain rapid and reliable answers to ecological challenges.

Effect of chilling and salinity stress on photosynthetic performance and ultrastructure of chloroplast in faba beans (Vicia faba L.) leaves

Chilling (Ch) and salinity (S) are challenging stresses affecting plant physiology, growth, and productivity. The current study investigated the effects of these two stresses, singly and in combination, on photosynthetic performance and ultrastructure of chloroplast of faba beans (Vicia faba L. Cv. Aspani). Plants were exposed to 3 °C and 120 mM NaCl for 16 h in an optimized soil mixture (sand:clay 2:1) under optimized conditions. Results showed that both Ch and S significantly reduced photosynthetic rates, Fv/Fm, chlorophyll content, stomatal index, and stomatal conductance. Chilling caused changes in chloroplast ultrastructure (swelling, ruptured envelopes, and shrunk lamellae), while salinity caused more deformation of the thylakoid membrane and disorganization of the grana structure. However, there was an antagonistic effect between Ch x S. The tolerance of plant to 120 mM NaCl, in the present study, was improved by exposure to Ch which rather allowed the maintenance of chloroplast ultrastructure and morphology of stomata. Moreover, using SEM and TEM gave an effective insight of the ultrastructural damage in plant cells under stress and helps to consider the underlying mechanisms of stress effects. Our results suggest that Ch mitigates the noxious effect of S on the photosynthetic performance of Vicia faba plants.

Disorder or a new order: How climate change affects phenological variability

Advancing spring phenology is a well documented consequence of anthropogenic climate change, but it is not well understood how climate change will affect the variability of phenology year to year. Species' phenological timings reflect the adaptation to a broad suite of abiotic needs (e.g., thermal energy) and biotic interactions (e.g., predation and pollination), and changes in patterns of variability may disrupt those adaptations and interactions. Here, we present a geographically and taxonomically broad analysis of phenological shifts, temperature sensitivity, and changes in interannual variability encompassing nearly 10,000 long-term phenology time series representing more than 1000 species across much of the Northern Hemisphere. We show that the timings of leaf-out, flowering, insect first-occurrence, and bird arrival were the most sensitive to temperature variation and have advanced at the fastest pace for early-season species in colder and less seasonal regions. We did not find evidence for changing variability in warmer years in any phenophase groups, although leaf-out and flower phenology have become moderately but significantly less variable over time. Our findings suggest that climate change has not to this point fundamentally altered the patterns of interannual phenological variability.

Climate warming-driven phenological shifts are species-specific in woody plants: evidence from twig experiment in Kashmir Himalaya

Experimental evidences in support of climate warming-driven phenological shifts are still scarce, particularly from the developing world. Here, we investigated the effect of experimental warming on flowering phenology of selected woody plants in Kashmir Himalaya. We selected the twigs of four congeneric pairs of temperate woody species (Prunus, Populus, Ulmus, Viburnum)-typical spring-flowering plants in the region. Using randomised block design, we monitored these winter dormant twigs in controlled growth chambers to study the effect of different temperature regimes (9, 17, 20 and 23 °C) and species identity on the patterns of phenological shifts. We observed a significant phenological shift in all the species showing preponement in the first flower out and senescence phases ranging from 0.56 to 3.0 and 0.77 to 4.04 days per degree increase in temperature, respectively. The duration of flowering phase in all the species showed a corresponding decrease along the gradient of increasing temperature, which was more driven by preponement of the flower senescence than the start of flowering. The patterns of phenological shifts were highly species-specific, and the magnitude of these shifts significantly varied in all the four pairs of congeneric species despite their phylogenetic similarity. Our study provides experimental support to the previous long-term observation and herbarium-based studies showing that the patterns of phenological shifts in response to global climate warming are likely to vary between species, even those belonging to same evolutionary stock. Our findings highlight that a one-size-fits-all strategy to manage the likely impacts of climate warming-induced phenological shifts will seldom succeed, and should instead be designed for the specific phenological responses of species and regions.

Spatiotemporal Variation of Land Surface Temperature in Henan Province of China from 2003 to 2021

Land surface temperature (LST) is a key parameter closely related to various land surface processes and surface-atmosphere interactions. Analysis of spatiotemporal variation of time-series LST may provide useful information to understand eco-climatic characteristics. In this study, the spatiotemporal pattern of LST and its trend characteristics in Henan Province were examined based on MODIS LST products from 2003 to 2021. In addition, the influences of land cover types, Nighttime Light data (NTL) and Normalized Difference Moisture Index (NDMI) on LST variation were analyzed. The results indicated that: (i) The LST showed slight and rapid decreasing trend for 2004–2010 and 2018–2020, respectively, whereas an obvious increasing and slight increasing trend occurred for 2010–2013 and 2014–2018. In terms of spatial pattern, high-temperature, and sub-high-temperature were mainly distributed in the central part of the province with higher level of industrialization and urbanization at the annual, spring, summer, and daytime scales. While in fall, winter, and the nighttime, the spatial distribution of LST exhibited decreased trend from the southern part to the northern part of the province, the largest Standard Deviation (STD) was observed in summer. (ii) The interannual variation rate of LST was 0.08 °C/Y. The increasing trend mainly occurred in urban and built-up areas. At the seasonal scales, the rising rate decreased sequentially in the order of fall, winter, spring, and summer. In addition, the rising rate in the daytime was higher than that in the nighttime. (iii) LST increased along with the expansion of urban and built-up lands, except in winter. At the annual scales, 84.69% of areas with NTL data exhibited a positive correlation with LST, and NDMI in the western part with high elevation presented a significantly positive correlation to LST, while a significantly negative correlation occurred in urban and built-up areas. The cooling effect of NDMI on LST in the daytime was greater than that in the nighttime. In cropland areas, LST showed a non-significant correlation with NDMI at the annual scale, and a significantly negative correlation with NDMI in spring, summer, and fall. The influence mechanism of cropland on the variation of LST at different timescales needs to be further explored. These findings might provide some hints to understand climate change and its causes in the province.

Testing the match-mismatch hypothesis in bighorn sheep in the context of climate change

In species with long gestation, females commit to reproduction several months before parturition. If cues driving conception date are uncoupled from spring conditions, parturition could be mistimed. Mismatch may increase with global change if the rate of temporal changes in autumn cues differs from the rate of change in spring conditions. Using 17 years of data on climate and vegetation phenology, we show that autumn temperature and precipitation, but not vegetation phenology, explain parturition date in bighorn sheep. Although autumn cues drive the timing of conception, they do not predict conditions at parturition in spring. We calculated the mismatch between individual parturition date and spring green-up, assessed whether mismatch increased over time and investigated the consequences of mismatch on lamb neonatal survival, weaning mass and overwinter survival. Mismatch fluctuated over time but showed no temporal trend. Temporal changes in green-up date did not lead to major fitness consequence of mismatch. Detailed data on individually marked animals revealed no effect of mismatch on neonatal or overwinter survival, but lamb weaning mass was negatively affected by mismatch. Capital breeders might be less sensitive to mismatch than income breeders because they are less dependent on daily food acquisition. Herbivores in seasonal environments may access sufficient forage to sustain lactation before or after the spring 'peak' green-up, and partly mitigate the consequences of a mismatch. Thus, the effect of phenological mismatch on fitness may be affected by species life history, highlighting the complexity in quantifying trophic mismatches in the context of climate change.

Natural and Political Determinants of Ecological Vulnerability in the Qinghai–Tibet Plateau: A Case Study of Shannan, China

Changing land-use patterns in the Qinghai–Tibet Plateau (QTP) due to natural factors and human interference have led to higher ecological vulnerability and even more underlying issues related to time and space in this alpine area. Ecological vulnerability assessment provides not only a solution to surface-feature-related problems but also insight into sustainable eco-environmental planning and resource management as a response to potential climate changes if driving factors are known. In this study, the ecological vulnerability index (EVI) of Shannan City in the core area of the QTP was assessed using a selected set of ecological, social, and economic indicators and spatial principal component analysis (SPCA) to calculate their weights. The data included Landsat images and socio-economic data from 1990 to 2015, at five-year intervals. The results showed that the total EVI remains at a medium vulnerability level, with minor fluctuations over 25 years (peaks in 2000, when there was a sudden increase in slight vulnerability, which switched to extreme vulnerability), and gradually increases from east to west. In addition, spatial analysis showed a distinct positive correlation between the EVI and land-use degree, livestock husbandry output, desertification area, and grassland area. The artificial afforestation program (AAP) has a positive effect by preventing the environment from becoming more vulnerable. The results provide practical information and suggestions for planners to take measures to improve the land-use degree in urban and pastoral areas in the QTP based on spatial-temporal heterogeneity patterns of the EVI of Shannan City.