Variation In Phenology Research Articles

Advances in Optical and Thermal Remote Sensing of Vegetative Drought and Phenology

In recent decades, remote sensing of vegetative drought and phenology has gained considerable attention from researchers, leading to a significant increase in research activity in this area. While new drought indices are being proposed, there is also growing attention on how variations in phenology affect drought detection. This review begins by exploring the crucial role of satellite optical and thermal remote sensing technologies in monitoring vegetative drought. It presents common methods after revisiting the foundational concepts. Then, the review examines remote sensing of land surface phenology (LSP) due to its strong connection with vegetative drought. Subsequently, we investigate vegetative drought detection techniques that consider phenological variability and recommend approaches to improve the detection of vegetative drought, emphasizing the necessity to incorporate phenological metrics. Finally, we suggest potential future work and directions. Unlike other review papers on remote sensing of vegetative drought, this review uniquely surveys the comprehensive advancements in both detecting vegetative drought and estimating LSP through optical and thermal remote sensing. It also highlights the necessity and potential applications for these practices.

Intra‐ and inter‐specific variability in the temporal trends of butterfly phenology in the Northern Alps

Abstract Large‐scale declines in insect abundances and richness due to climate and land‐use change have been well documented during the past years. These changes are accompanied by shifts in insect phenology towards earlier appearance in spring and prolonged activity periods in late summer and autumn. The magnitude of these responses to climate change might be masked by intra‐ and inter‐specific variability in phenology and trait expression. Here, we used a large data set of museum records of butterflies from the northern Austrian Alps (380 m to >3000 m asl) and ask to which degree does intra‐ and inter‐specific variability in spring and autumn activity and in the numbers of generations affect the temporal trends in phenology during the last 30 years? For the 17 most abundant species, we found phenological variability to strongly differ among species, local habitats and study years. Ubiquitous mobile species were significantly more variable than habitat specialist and sedentary species. Intra‐specific variability was highest in ubiquitous habitat generalist species and increased during the study period. As consequence, seasonal appearance and composition of local butterfly communities are now less predictable than decades ago. It remains unclear whether this trend causes a rewiring of pollinator food webs.

Factors and effects of inter-individual variability in silver birch phenology using dense LiDAR time-series

Comprehending and quantifying local variability in plant phenology, alongside its impacts on tree growth, is challenging due to spatially and temporally heterogeneous environmental factors that interact to affect phenological events and periods. Although previous studies have focused on the climatic factors driving phenological events at the stand level, the influences of competition, neighborhood characteristics, species richness, and water availability on plant phenology remain unclear. In the present paper, we used hourly terrestrial LiDAR surveys performed between April 2020 and April 2021 to investigate the influence of local factors (neighborhood and topography) on the phenology of silver birch trees (Betula pendula Roth.). We also examined how phenological events affect growth in tree height and crown area. All response and explanatory variables were estimated using LiDAR time-series data and a field survey campaign. Our findings demonstrate a high within-species variability in plant phenology that is controlled by biotic and abiotic characteristics of the ecosystem. We found that between tree variation in leaf burst, completion of the leaf growth and length of canopy growth period were affected by tree size, neighborhood species richness, level of suppression and competition, which potentially indicate plant responses to light availability. The beginning of senescence, completion of leaf drop, and length of autumn phenology were mostly affected by topographic water index, which reflects water availability and can be linked to nutrient availability and exposure to wind. Furthermore, we demonstrated that an earlier leaf burst, and delayed beginning of senescence were associated with larger absolute growth in canopy area but found no clear relationship between height growth and phenology. Our study highlights the capability of dense, high-quality LiDAR time-series to detect significant phenological variation among individuals of the same species within the same locality, demonstrating the potential of LiDAR time-series as a tool for understanding phenology and its impacts.

Spatio‐temporal variability in seed production of tree species: implications for restoration in the Cerrado–Amazonia transition zone

The use of propagules collected in ecotonal regions for restoration purposes is challenging because of the mix of species from different vegetation types and reproductive phenological variability. We used a database of the Xingu Seed Network in Brazil, which contains data on 139 native tree species for 8 years (2011–2018) in the Cerrado–Amazonia transition zone, to answer three questions: (1) What is the spatio‐temporal variability in the seed dispersal of tree species, and how does it relate to the species' preferential habitat? (2) Is there a relationship between the seed dispersal period and climate variables? (3) Is the frequency of tree species with different dispersal syndromes equally distributed among biomes and seed‐size classes? Independent of their preferred ecosystem (Amazonia or Cerrado), some species showed substantial spatio asynchrony in fruit dispersal, extending the dispersal period at a regional scale. The seed dispersal period was strongly correlated (rs > 0.6) with precipitation and minimum or maximum air temperature in 41% (n = 57) of the studied species. We showed that three‐quarters of the species (n = 105) dispersed seeds in the late dry and early rainy periods, with little variation among dispersal syndromes. Our findings will enhance the effectiveness of restoration initiatives by increasing the accuracy of predictions of the location and time for collecting seeds in the extensive Cerrado–Amazonia transition zone.

Intraspecific body size variation across distributional moments reveals trait filtering processes.

Natural populations are composed of individuals that vary in their morphological traits, timing and interactions. The distribution of a trait can be described by several dimensions, or mathematical moments-mean, variance, skew and kurtosis. Shifts in the distribution of a trait across these moments in response to environmental variation can help to reveal which trait values are gained or lost, and consequently how trait filtering processes are altering populations. To examine the role and drivers of intraspecific variation within a trait filtering framework, we investigate variation in body size among five wild bumblebee species in the Colorado Rocky Mountains. First, we examine the relationships between environmental factors (climate and floral food resources) and body size distributions across bumblebee social castes to identify demographic responses to environmental variation. Next, we examine changes in the moments of trait distributions to reveal potential mechanisms behind intraspecific shifts in body size. Finally, we examine how intraspecific body size variation is related to diet breadth and phenology. We found that climate conditions have a strong effect on observed body size variation across all distributional moments, but the filtering mechanism varies by social caste. For example, with earlier spring snowmelt queens declined in mean size and became negatively skewed and more kurtotic. This suggests a skewed filter admitting a greater frequency of small individuals. With greater availability of floral food resources, queens increased in mean size, but workers and males decreased in size. Observed shifts in body size variation also correspond with variation in diet breadth and phenology. Populations with larger average body size were associated with more generalized foraging in workers of short-tongued species and increased specialization in longer-tongued workers. Altered phenological timing was associated with species- and caste-specific shifts in skew. Across an assemblage of wild bumblebees, we find complex patterns of trait variation that may not have been captured if we had simply considered mean and variance. The four-moment approach we employ here provides holistic insight into intraspecific trait variation, which may otherwise be overlooked and reveals potential underlying filtering processes driving such variation within populations.

Extreme mismatch between phytoplankton and grazers during Arctic spring blooms and consequences for the pelagic food-web

Food-web structure determines the cycling pathways and fate of new production in marine ecosystems. Herbivorous zooplankton populations are usually seasonally coupled with pelagic primary producers. Synchrony of phytoplankton blooms with reproduction, recruitment and seasonal ascent of their main grazers ensures efficient transfer of organic carbon to higher trophic levels, including commercially harvested species, especially in high-latitude systems. Changes in light, nutrient, and sea-ice dynamics due to accelerating climate change in the Arctic, however, create large uncertainties in how these systems will function in the future. To address such knowledge gaps, we surveyed the pelagic ecosystem of the Barents Sea Polar Front in May of two consecutive years (2021 and 2022) to investigate the pelagic food-web from primary producers to planktivorous fish. In both years we observed unprecedentedly high phytoplankton chlorophyll a values in open as well as ice-covered waters, much of which was invisible to satellite remote sensing. We also measured very low densities of grazing zooplankton across a wide area and extending for at least one month. This extreme mismatch resulted in low feeding by capelin, and further suggests a high potential for vertical export of carbon to the benthos rather than efficient assimilation into the pelagic food web. As the Arctic continues to warm and is characterized by thinner and more mobile sea ice, we may expect higher variability in phytoplankton bloom phenology and more frequent mismatches with grazer life-histories. This could have significant impacts on ecosystem functioning by re-directing the flow of energy through the system towards seafloor rather than to the production of commercially valuable pelagic marine resources.

Spatial and Temporal Patterns of Maize Phenology in China From 2001 to 2020

AbstractClimate change has significantly altered crop phenology, which has further impacted crop growth and yield. Accurate monitoring of crop phenology is essential for managing agricultural production in response. However, regional monitoring requires high spatial resolution distribution data, as medium resolution data suffers from mixed pixel issues. This study based on a long‐term high spatiotemporal resolution fusion data set of Normalized Difference Vegetation Index and an annually updated maize distribution data set, used the relative threshold method to identify the maize phenology in 22 provinces of China from 2001 to 2020. We further analyzed the trend of maize phenology and assessed its responses to climate change. The results reveal large inter‐annual fluctuations and spatial variability in maize phenology from 2001 to 2020. The length of the growth season (LOS) of spring maize has prolonged by 4.28 days in the northern maize zone and has shortened by 4.90 days in the southern maize zone. Additionally, the LOS of summer maize in the Huang‐Huai‐Hai region has shortened by 2.24 days. We also found a positive correlation between the length of the vegetative growth stage and the mean temperature and a negative correlation between the length of the reproductive growth stage and accumulated precipitation. This study utilized large‐scale, high‐resolution maize phenology data to analyze the trend of maize phenology and its response to climate change. These findings are expected to provide valuable support for assessing maize growth status and developing agricultural adaptive practices.

A modified matrix model captures the population dynamics for the primary vector of Lyme disease in North America

AbstractLyme disease, the most prevalent tick‐borne disease in North America, is caused by the bacterium Borrelia burgdorferi, and in the eastern and central United States, it is spread to humans by the black‐legged tick (Ixodes scapularis). Due to the complex, multiyear and multihost life cycle of this species, a matrix modeling approach is needed to effectively estimate subseasonal, multistage survival and transition dynamics in order to better understand and predict when population growth is high. Of the three questing tick life stages (larvae, nymphs, and adults), nymphs are most often associated with transmitting the bacteria to humans, and previous work suggests a mix of abiotic and biotic drivers are associated with nymph abundance. However, understanding tick population growth requires understanding mortality and transition probabilities for each stage and each stage may be individually and uniquely impacted by climate and host availability. A larval tick, for example, may experience warming temperatures differently than nymph or adults, because they are present on the landscape at different times. Here, we describe and validate a model that accounts for field sampling design and evaluates abiotic (temperature, relative humidity, precipitation) and biotic (host abundance) drivers of variation in tick population growth. To account for the drivers of subseasonal and interannual variability in demography, phenology, and population density, we built stage‐structured population models that account for variability in meteorology and host population abundance throughout the full tick lifecycle. Our model is fit and validated with 11 years of tick and host data from the northeastern United States. In this context, we found that a four‐stage model that includes unique transitions to and from a dormant, overwintering nymph state outperforms a model that only includes the three questing stages, and that incorporating the abundance of the predominant host species, Peromyscus leucopus, and weather variables improved predictions and model fit. Additionally, the model accurately predicted all three questing stages at sites different than where they were calibrated, showing that this model structure is generally transferable. Overall, this model lays a foundation for the real‐time iterative forecasting of tick populations needed to effectively protect public health.

Climatic variation and risk assessment in a highly seasonal mammal

Abstract Climate change and its resulting effects on seasonality are known to alter a variety of animal behaviors including those related to foraging, phenology, and migration. While many studies focus on the impacts of phenological changes on physiology or fitness enhancing behaviors, fewer have investigated the relationship between variation in weather and phenology on risk assessment. Fleeing from predators is an economic decision that incurs costs and benefits. As environmental conditions change, animals may face additional stressors that affect their decision to flee and influence their ability to effectively assess risk. Flight initiation distance (FID)–the distance at which animals move away from threats–is often used to study risk assessment. FID varies due to both internal and external biotic and physical factors as well as anthropogenic activities. We asked whether variation in weather and phenology is associated with risk-taking in a population of yellow-bellied marmots (Marmota flaviventer). As the air temperature increased marmots tolerated closer approaches, suggesting that they either perceived less risk or that their response to a threat was thermally compromised. The effect of temperature was relatively small and was largely dependent upon having a larger range in the full data set that permitted us to detect it. We found no effects of either the date that snow disappeared or July precipitation on marmot FID. As global temperatures continue to rise, rainfall varies more and drought becomes more common, understanding climate-related changes in how animals assess risk should be used to inform population viability models.

Pearl millet phenology assessment: An integration of field, a review, and in silico approach

AbstractPearl millet [Pennisetum glaucum (L.) R.Br.] is an essential subsistence cereal for food security in dryland farming systems of the semiarid tropics (e.g., in sub‐Saharan Africa) and has improved tolerance to drought, heat, and salinity stress compared to other domesticated cereals. Assessing the variation on phenology is critical toward devising effective adaptative management strategies for crop adaptation to current and future climate change. In this context, pearl millet presents a vast genetic diversity, exhibiting sensitivity to temperature and photoperiod. Hence, this study aims to describe the genotypic variability in the phenological responses of pearl millet to temperature and photoperiod, particularly affecting leaf number with implications on the overall total time to flowering. The dataset encompassed 21 publications from seven countries, with experiments conducted from 1965 to 2023, including three field studies from the United States. Broad variability has been reported for phyllochron values ranging from 45 to 111°Cd leaf−1, with a mean value of 67°Cd leaf−1. Thermal time to panicle initiation ranged from 340 to 594°C, but no response to photoperiod duration was found due to the nature of dataset. Maximum number of leaves per shoot ranged from 11 to 25, showing response (1.55–2.15 leaf h−1) to photoperiod due to variations in thermal time to flowering (from 875 to 1346°Cd). Thermal time to flowering increased ca. 323°Cd h−1 under day durations longer than 13.3 h, below which basic vegetative phase duration was close to 1033°Cd. Based on the Agricultural Production Systems sIMulator simulations, different combinations of the above responses (in silico cultivars) generated a great range of times to flowering (44–120 days) for locations in Senegal, Brazil, India, and United States. The findings of this study can help breeders to explore the phenological genetic variability of pearl millet and provide inputs for crop growth models to evaluate future in silico scenarios.

Using of high spatial resolution images to evaluate the thematic accuracy of land use and occupation maps with the Kappa index

The objective from this article evaluates the thematic quality of automatic mappings with supervised classification for land use and land cover, using high spatial resolution satellite images as "ground truth". This consider the advancement of remote sensing technologies has enabled the acquisition of satellite images with various spatial resolutions, which are essential for thematic mapping and automatic classifiers in the context of land use and land cover mapping. In fact, the wide availability of high, medium, and low spatial resolution satellite images has significantly optimized the time and resources required by using more accurate classifiers during data processing. The image used for verification of this paper was GeoEye, with a spatial resolution of 0.5m, dated October 2023. The images submitted to the automatic classifier were Sentinel-2A with a spatial resolution of 10m and Planet with a spatial resolution of 5m, both from the same satellite pass period (October 2023) over the study area, aiming to avoid seasonal and phenological variations in vegetation, as well as changes in the environment due to anthropogenic intervention. The classification method adopted was Maximum Likelihood (MAXVER). The classification accuracy was rigorously evaluated to ensure the reliability of the results using the Kappa index, assessing the agreement between the observed and expected classifications. Based on the methods presented, the set of mapped classes in this study showed good accuracy for the Planet image and very good accuracy for the Sentinel image.

Flower position within plants influences reproductive success both directly and via phenology.

In plants, within-individual trait variation might result from mechanisms related to ontogenetic contingency, i.e., to the position of a particular structure within the plant, previous developmental events, and/or the developmental environment. Flower position within inflorescences as well as inflorescence position within plants can influence resource provisioning, phenology, biotic interactions, and reproductive success. Despite the potential implications of within-individual variation in plant reproductive phenotypes, its causes and effects on reproductive success are still little explored. We assessed how reproductive success, in terms of fruit and seed set, and seed predation of 5883 flowers in Lathyrus vernus were influenced by their position within and among racemes, to what extent relationships between flower position and reproductive success and seed predation were mediated by phenology, and if positional effects on reproductive success depended on the external environment. In three years, basal flowers and racemes opened earlier and had higher fruit set than distal. Basal flowers also experienced higher seed predation. Differences among racemes in fruit and seed set were largely related to phenology, while differences in fruit set, seed set, and seed predation within racemes were not. In one year, differences in fruit set among flowers at different positions depended on flowering duration. Our results highlight the important role of ontogenetic contingency for within-individual variation in phenology and reproductive success. As the spatial distribution of reproductive structures affects both within-plant trait distributions and fitness, it is a likely target for natural selection.

Genetic variation in phenology of wild Arabidopsis thaliana plants.

Phenology and the timing of development are often under selection, but at the same time influence selection on other traits by controlling how traits are expressed across seasons. Plants often exhibit high natural genetic variation in phenology when grown in controlled environments, and many genetic and molecular mechanisms underlying phenology have been dissected. There remains considerable diversity of germination and flowering time within populations in the wild and the contribution of genetics to phenological variation of wild plants is largely unknown. We obtained collection dates of naturally inbred Arabidopsis thaliana accessions from nature and compared them to experimental data on the descendant inbred lines that we synthesized from two new and 155 published controlled experiments. We tested whether the genetic variation in flowering and germination timing from experiments predicted the phenology of the same inbred lines in nature. We found that genetic variation in phenology from controlled experiments significantly, but weakly, predicts day of collection from the wild, even when measuring collection date with accumulated photothermal units. We found that experimental flowering time breeding values were correlated to wild flowering time at location of origin estimated from herbarium collections. However, local variation in collection dates within a region was not explained by genetic variation in experiments, suggesting high plasticity across small-scale environmental gradients. This apparent low heritability in natural populations may suggest strong selection or many generations are required for phenological adaptation and the emergence of genetic clines in phenology.

Improved Winter Wheat Yield Estimation by Combining Remote Sensing Data, Machine Learning, and Phenological Metrics

Accurate yield prediction is essential for global food security and effective agricultural management. Traditional empirical statistical models and crop models face significant limitations, including high computational demands and dependency on high-resolution soil and daily weather data, that restrict their scalability across different temporal and spatial scales. Moreover, the lack of sufficient observational data further hinders the broad application of these methods. In this study, building on the SCYM method, we propose an integrated framework that combines crop models and machine learning techniques to optimize crop yield modeling methods and the selection of vegetation indices. We evaluated three commonly used vegetation indices and three widely applied ML techniques. Additionally, we assessed the impact of combining meteorological and phenological variables on yield estimation accuracy. The results indicated that the green chlorophyll vegetation index (GCVI) outperformed the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) in linear models, achieving an R2 of 0.31 and an RMSE of 396 kg/ha. Non-linear ML methods, particularly LightGBM, demonstrated superior performance, with an R2 of 0.42 and RMSE of 365 kg/ha for GCVI. The combination of GCVI with meteorological and phenological data provided the best results, with an R2 of 0.60 and an RMSE of 295 kg/ha. Our proposed framework significantly enhances the accuracy and efficiency of winter wheat yield estimation, supporting more effective agricultural management and policymaking.

The linkage between functional traits and drone-derived phenology of 74 Northern Hemisphere tree species

Tree phenology is a major component of the global carbon and water cycle, serving as a fingerprint of climate change, and exhibiting significant variability both within and between species. In the emerging field of drone monitoring, it remains unclear whether this phenological variability can be effectively captured across numerous tree species. Additionally, the drivers behind interspecific variations in the phenology of deciduous trees are poorly understood, although they may be linked to plant functional traits. In this study, we derived the start of season (SOS), end of season (EOS), and length of season (LOS) for 3099 individuals from 74 deciduous tree species of the Northern Hemisphere at a unique study site in southeast Germany using drone imagery. We validated these phenological metrics with in-situ data and analyzed the interspecific variability in terms of plant functional traits. The drone-derived SOS and EOS showed high agreement with ground observations of leaf unfolding (R2 = 0.49) and leaf discoloration (R2 = 0.79), indicating that this methodology robustly captures phenology at the individual level with low temporal and human effort. Both intra- and interspecific phenological variability were high in spring and autumn, leading to differences in the LOS of up to two months under almost identical environmental conditions. Functional traits such as seed dry mass, chromosome number, and continent of origin played significant roles in explaining interspecific phenological differences in SOS, EOS, and LOS, respectively. In total, 55 %, 39 %, and 45 % of interspecific variation in SOS, EOS, and LOS could be explained by the Boosted Regression Tree (BRT) models based on functional traits. Our findings encourage new research avenues in tree phenology and advance our understanding of the growth strategies of key tree species in the Northern Hemisphere.

Mapping forest phenological shift in Nilgiri Biosphere Reserve, Western Ghats: Response to climate change

In the present study, the spatiotemporal alterations in phenological metrics were analyzed in different forest types of Nilgiri Biosphere Reserve (NBR), Western Ghats, India with special reference to the impacts of changing climate on the forest phenology over two-phase periods (Phase 1: 2001–2010 and Phase 2: 2011–2020). Three phenological measures including the start/end/length of the season (SOS/EOS/LOS) were obtained using 16 days of MODIS Enhanced Vegetation Index (EVI) dataset over the two decades. The study exhibited a gradual delay in SOS during phase 1, and an advancing SOS during phase 2 in the tropical forests of NBR. Delayed EOS was observed in all forest types in NBR barring Moist Deciduous Forests (MDF) during phase 1, while opposite trend of advancing EOS was observed in deciduous forests (MDF and DDF: Dry Deciduous Forests), but delayed EOS was observed in evergreen forests (SEF: Semi Evergreen Forests and WEF: Wet Evergreen Forests) during phase 2. These variations in forest phenology are linked with an increase in annual mean temperature (0.01 °C year−1) along with a decrease in annual mean precipitation (3.97 mm year−1) during 1950–2018 as observed using IMD-based meteorological datasets. The results highlighted reduction in the total LOS with a delayed SOS and advanced EOS in NBR, which were prevalent during phase 1 conversely to phase 2 due to the varied intensity of changes in climatic conditions. However, disaggregating decade-long intervals into 5-year segments enables a finer resolution analysis of phenological trends. The study contributes to the development of long-term strategies for forest ecosystem restoration under the influence of global climate change by providing an insightful understanding of the non-systematic shifts in forest phenology attributed by rising warming impacts and erratic precipitation patterns.

Effect of Different Seasons and Development Stages on the Chemical Composition and Bioactive Potential of Cardoon.

Cynara cardunculus L. (cardoon) is a wild species of the Mediterranean basin and is highly appreciated due to its rich nutritional value and versatile industrial applications. It is widely known that environmental conditions, such as air temperature, humidity, and solar radiation, among others, play a crucial role in plant phenological variations and the chemical composition and bioactive properties of different plant tissues of cardoon. This study applied several statistical methods to uncover the variations in biomolecules of different cardoon tissues collected in Greece over the growth cycle. The influence of the different seasons on the species is evident, resulting in a clear discrimination between the samples harvested throughout the growth cycle. In addition, the observed fluctuations in chemical composition are consistent with each vegetable tissue's functions and the plant's different physiological processes. This work allows for a better understanding and knowledge of the species, encouraging more profitable and sustainable use of all the plant parts.

Investigating fish reproduction phenology and essential habitats by identifying the main spatio-temporal patterns of fish distribution

Abstract Fish spawning phenology is a major concern for conservation and fisheries management. New intensive data sources, such as GPS-based tracking data and high-resolution catch declaration data, are becoming increasingly available in the field of marine ecology. These data benefit from high spatiotemporal resolution and open new research avenues for investigating the interannual variability in fish phenology. In this paper, we demonstrate how an integrated species distribution model informed by commercial catch data combined with spatiotemporal dimension reduction methods known as empirical orthogonal functions (EOFs) can be used to synthesize spatiotemporal signals in fish reproduction phenology. Specifically, we address the following questions: (1) Can we identify seasonal spatial patterns that can be interpreted in terms of reproductive phenology and essential habitats? (2) Can we identify changes in reproductive phenology over time? (3) Are these changes related to environmental drivers? The analysis illustrates the reproductive phenology of three key commercial species in the Bay of Biscay (sole, hake, and sea bass). The EOF analysis emphasized strong seasonal spatiotemporal patterns that correspond to reproduction patterns and feeding patterns. Based on this methodology, we identified seasonal variations in the timing of reproduction, and we related these variations to sea surface temperature, a key driver of fish reproduction.

Variation in Phenology and Morphological Traits of Seed-Propagated Laggera alata and Laggera crispata Forms

The phenological and morphological variation studies among forms of Laggera Sch. Bip. Ex. Benth. and Hook species are limited, despite the medicinal use of the genus. Therefore, this study aimed to document phenology and morphological variation in cultivated populations of Laggera alata and Laggera crispata forms from seedling to maturity. The forms were categorized as Laggera alata with a small capitulum (LA-SC), Laggera alata with a large capitulum (LA-BC), Laggera crispata from South Africa (LC-SA), and Laggera crispata from Zimbabwe (LC-ZIM). Seeds were germinated in Petri dishes, transplanted to plug trays, and later to field plots at 60 days. Phenological events were recorded when observed in at least one plant. Twelve qualitative and four morphometric traits were measured monthly on five plants per Laggera form. Analysis of variance and Tukey’s Honestly Significant Difference test (p < 0.05) were used for data analysis. Results indicated significant variation in phenology, qualitative traits, leaf traits, plant height, and stem diameter both within and between L. crispata and L. alata forms. Morphometric traits, such as leaf size and the number of leaves per plant, were identified as key descriptors for differentiating L. alata forms. These findings provide a foundation for the introduction of Laggera forms into farming systems for medicinal and commercial purposes.

Effects of climate on the phenology of Annona senegalensis Pers. (Annonaceae) and the distribution of associated insects in Burkina Faso.

Climate change and global warming in the Sahelian region cause dramatic drought and advancing of the desert. This phenomenon could affect the plant survival and community composition, but even for surviving plants, it could affect their phenology and the insect community associated with them. In a space-for-time approach, we studied the case of Annona senegalensis Pers. (Annonaceae), a common shrub in tropical areas, to determine the impact of climate change on its phenology and the insects associated with its flowers and fruits. We determined the phenology phases of Annona senegalensis during a 1-year period and assessed the abundance and diversity of insects in the Sudanian and the Sudano-Sahelian climatic zones of Burkina Faso. Temperature, rainfall and relative humidity were recorded during 12 months in two sites per zone. Leafing of Annona senegalensis lasted 10 months in the Sudanian zone, flowering and fruiting were 3 months long. In the Sudano-Sahelian zone, leafing lasted 8 months while flowering and fruiting were 3 and 4 months long, respectively. A total of 10,040 insects belonging to 48 species were collected in the two climatic zones. Forty-six species were found in the Sudanian zone while 25 species were recorded in the Sudano-Sahelian one. The variations in the plant phenology and the insect community were mainly due to the variation in rainfall across both climatic zones. Our results emphasize that advancing of the desert due to climate change could not only affect the survival of plants but for resistant species it also affect their interactions with insects and the whole insect community associated.