Phenological Analysis Research Articles

Where to go when all options are terrible: ranging behavior of brown-throated three-toed sloths (Bradypus variegatus) in central Amazonian flooded igapó forests

Ranging behaviors performed by animals are influenced by both biotic and abiotic factors. For herbivorous mammals, seasonality in forage production is considered to be the main driver of movement patterns. Here, we investigated the home range and movement of one of the most abundant herbivores in the Americas and their relationship with plant phenology in an Amazon igapó — a seasonally flooded riverine forest with strongly pulsed leaf production phenology. Using a combination of telemetry and phenological analysis, the study recorded movement patterns of five brown-throated three-toed sloths (Bradypus variegatus Schinz, 1825) over a 6-month period and related these to seasonal and within-forest differences in food availability through monitoring young leaf production of 570 trees. All monitored animals were shown to be permanently resident within the igapó flooded forest, maintaining their home range even during flood periods when most trees lacked leaves. We found that seasonal variation in leaf production had no effect on the extent of displacement of the sloths. Accordingly, for herbivores with low metabolism, variation in young leaf availability may not be the main driver of their ranging behavior. In addition, an arboreal habit and well-developed swimming capacity allow igapó sloths to occupy a niche ecologically inaccessible to other mammals.

Long‐term surveys support declines in early season forest plants used by bumblebees

Abstract Populations of bumblebees and other pollinators have declined over the past several decades due to numerous threats, including habitat loss and degradation. However, we can rarely investigate the role of resource loss due to a lack of detailed long‐term records of forage plants and habitats. We used 22‐year repeated surveys of more than 262 sites located in grassland, forest, and wetland habitats across Illinois, USA to explore how the abundance and richness of bumblebee food plants have changed over the period of decline of the endangered rusty patched bumblebee Bombus affinis. We documented a decline in abundance of bumblebee forage plants in forest understories, which our phenology analysis suggests provide the primary nectar and pollen sources for foundress queens in spring, a critical life stage in bumblebee demography. By contrast, the per‐unit area abundance of food plants in primarily midsummer‐flowering grassland and wetland habitats had not declined. However, the total area of grasslands had declined across the region resulting in a net loss of grassland resources. Synthesis and applications. Our results suggest a decline in spring‐flowering forest understorey plants is a previously unappreciated bumblebee stressor, compounding factors like agricultural intensification, novel pathogen exposure and grassland habitat loss. These findings emphasize the need for greater consideration of habitat complementarity in bumblebee conservation. We conclude that the continued loss of early season floral resources may add additional stress to critical life stages of bumblebees and limit restoration efforts if not explicitly considered in pollinator conservation.

Botanical and phenological analysis of wild strawberry in JAAS

Botanical and phenological analysis of wild strawberry in JAAS

Spatial and temporal variability of cv. Tempranillo response within the Toro DO (Spain) and projected changes under climate change

This work aimed to analyse the spatial and temporal variability of the response of Tempranillo variety within the Toro Designation of Origin (DO) and the potential changes under climate change scenarios. The research included the analysis of phenology (bud break, bloom, veraison and maturity) and grape composition at harvest recorded in plots located at seven locations in the DO, at elevations between 667 and 779 m above the sea level (a.s.l.). Changes in phenology and composition were projected for 2050 and 2070 under two emission scenarios (Representative Concentration Pathways RCP4.5 and RCP8.5), considering the predicted changes in climate variables using an ensemble of models. Variations in the phenological timing of up to 28 days for bud break, bloom and veraison and up to 30 days for maturity were recorded during the period analysed and titratable acidity varied between 4 and 8 gL-1. The variability in phenology and grape acidity was mainly driven by temperature and available water in different periods between phenological stages, although the effect of soil properties was also confirmed. Under warmer conditions, an advance of all phenological phases was projected (up to 6, 6, 8 and 12 days by 2050 under the RCP4.5 scenario and near double under the RCP8.5 scenario). In addition, a decrease in titratable acidity is projected (about 1.1 and 1.4 gL-1 by 2050, respectively, under the RCP4.5 and the RCP8.5 scenario and up to 2.0 gL-1 by 2070 under the warmest scenario). The results were in agreement with the variability observed in years with contrasting weather conditions.

Method matters: pitfalls in analysing phenology from occurrence records.

Large occurrence datasets provide a sizable resource for ecological analyses, but have substantial limitations. Phenological analyses in Fric et al. (2020) were misleading due to inadequate curation and improper statistics. Reanalysing 22 univoltine species with sufficient data for independent analysis, we found substantively different macroscale phenological patterns, including later onset at higher latitude for most species.

Exploring job crafting as a response to abusive supervision

PurposeThe purpose of this qualitative exploratory study was to investigate the capacity of job crafting to serve as a viable response to abusive supervision. Although considerable literature has emerged on employee reactions to abusive supervision, the role of job crafting as a coping mechanism has received relatively little attention.Design/methodology/approachUsing qualitative exploration, we conducted semi-structured interviews to examine how individuals engage in job crafting as a means to respond to or cope with abusive supervision. Critical Incident Interview Technique (CIIT) was used to obtain in-depth details of this topic. We analyzed the interview-based data using the thematic analysis (TA) technique. We also integrated topic modeling to cluster the identified categories of job crafting behaviors within our TA. The cultural context of our findings was further analyzed using interpretive phenological analysis (IPA).FindingsThe results of our thematic analysis led to four recurring themes in the interview-data: (1) Job crafting as a viable coping response to abusive supervision; (2) The type of coping relates to the type of crafting: Approach and Avoidance; (3) The role of perceived control; (4) Emotions play a role in the type of crafting employed. Findings from our IPA generated the following super-ordinate themes. (1) Job crafting fluidity, (2) effectiveness of job crafting, (3) resilience and (4) cultural dynamics.Research limitations/implicationsThis research reveals the ways in which individuals may turn to job crafting behaviors as a means to cope following instances of abusive supervision. Given the qualitative exploration of our research approach, we identify generalizability to be an issue.Practical implicationsJob crafting is a proactive phenomenon that equips employees with coping abilities in the workplace. While Wrzesniewski and Dutton (2001) suggested that job crafting behaviors tend to be hidden from management, there may be merit in organizations explicitly acknowledging the benefits of allowing employees to be active agents in their work, capable of using multiple domains of job crafting to improve their personal and professional lives (Petrou et al., 2017).Originality/valueThe current research reveals the ways in which individuals may turn to job crafting behaviors as a means to cope, following instances of abusive supervision. We further fine-grained our analysis to explicate employee job crafting behaviors in response to abusive supervision within a cross-cultural domain.

Phenological Analysis of Sub-Alpine Forest on Jeju Island, South Korea, Using Data Fusion of Landsat and MODIS Products

Climate change poses a disproportionate risk to alpine ecosystems. Effective monitoring of forest phenological responses to climate change is critical for predicting and managing threats to alpine populations. Remote sensing can be used to monitor forest communities in dynamic landscapes for responses to climate change at the species level. Spatiotemporal fusion technology using remote sensing images is an effective way of detecting gradual phenological changes over time and seasonal responses to climate change. The spatial and temporal adaptive reflectance fusion model (STARFM) is a widely used data fusion algorithm for Landsat and MODIS imagery. This study aims to identify forest phenological characteristics and changes at the species–community level by fusing spatiotemporal data from Landsat and MODIS imagery. We fused 18 images from March to November for 2000, 2010, and 2019. (The resulting STARFM-fused images exhibited accuracies of RMSE = 0.0402 and R2 = 0.795. We found that the normalized difference vegetation index (NDVI) value increased with time, which suggests that increasing temperature due to climate change has affected the start of the growth season in the study region. From this study, we found that increasing temperature affects the phenology of these regions, and forest management strategies like monitoring phenology using remote sensing technique should evaluate the effects of climate change.

On thin ice: Linking elevation and long‐term losses of lake ice cover

AbstractDespite long‐term analyses of lake ice phenology globally, comparatively little is known about high‐elevation lakes, for which climate shifts are thought to be occurring faster than at lower elevations. Using a 36‐yr dataset (1983–2018) on alpine lakes (> 3000 m ASL) from the Green Lakes Valley, Colorado (GLV), we found that ice‐cover duration decreased by an average of ~ 24 d, due to both earlier ice‐off (9 d) and especially later ice‐on (15 d). Spring ice thickness also decreased by 0.88 cm yr−1. By comparison, ice‐cover duration in the GLV is decreasing ~ 50% faster than for Northern Hemisphere lakes (n = 215), which translates to an increase in open water duration ~ 2.5 times more in the GLV than the average of the Northern Hemisphere. Our analytical comparison demonstrated more rapid trends in this alpine region compared to lakes more broadly, and especially emphasized the influence of elevation on lake ice phenology.

Phenological Response in the Trophic Levels to Climate Change in Korea.

The response of the phenological events of individual species to climate change is not isolated, but is connected through interaction with other species at the same or adjacent trophic level. Using long-term phenological data observed since 1976 in Korea, whose temperature has risen more steeply than the average global temperature, this study conducted phenological analysis (differ-ences in the phenology of groups, differences in phenological shifts due to climate change, differ-ences in phenological sensitivity to climate by groups, and the change of phenological day differ-ences among interacting groups). The phenological shift of the producer group (plants) was found to be negative in all researched species, which means that it blooms quickly over the years. The regression slope of consumers (primary consumers and secondary consumers) was generally posi-tive which means that the phenological events of these species tended to be later during the study period. The inter-regional deviation of phenological events was not large for any plant except for plum tree and Black locust. In addition, regional variations in high trophic levels of secondary consumers tended to be greater than that of producers and primary consumers. Among the studied species, plum was the most sensitive to temperature, and when the temperature rose by 1 °C, the flowering time of plum decreased by 7.20 days. As a result of checking the day differences in the phenological events of the interacting species, the phenological events of species were reversed, and butterflies have appeared earlier than plum, Korean forsythia, and Korean rosebay since 1990. Using long-term data from Korea, this study investigated differences in phenological reactions among trophic groups. There is a possibility of a phenological mismatch between trophic groups in the future if global warming continues due to differences in sensitivity to climate and phenological shifts between trophic levels.

Exploring the Impact of Weather Variability on Phenology, Length of Growing Period, and Yield of Contrast Dryland Wheat Cultivars

This study aimed at investigating the response of two most common dryland wheat cultivars to temperature and rainfall variability between 2005 and 2015 in Iran. The results indicated sharp changes in the temperature (increase) and rainfall (decrease) of the study area between 2010 and 2015. Based on the plot analysis of cultivars phenology and grain yield variations, cultivar Azar2 showed more instability compared to Sardari during 2005–2015. The results of the regression analysis showed extended length of growing period (LGP) and the length of vegetative phase (LVP) for Sardari and Azar2 cultivars as well as extended length of grain filling period (LGFP) and increased grain yield for Azar2 during 2005–2015. For Azar2, shortened LGP, LVP, and decreased grain yield were observed during 2010–2015. Overall, temperature (maximum and minimum) had more determining effects on Sardari grain yield compared with rainfall. The results also indicated that the phenology and yield of both cultivars were more dependent on the weather conditions during April and May. This study concluded that variations in LGFP led to more significant changes in grain yield of both cultivars (i.e., Sardari and Azar2). This study further concluded that phenology and grain yield of Azar2 were more affected by weather variability than Sardari.

Formation characteristics of watermelon seed productivity under intercropping

Characteristics of watermelon seed formation in intercropping were studied. Different growing methods of watermelon seeds depending on its interaction with intercrops (sugar maize and common bean) and their planting schemes in melon fields were investigated. The developed elements of the watermelon seed growing technology reduced the impact of high temperatures on this melon crop (the number of fruits with sunburn decreased by 7.1 % compared to control). The results of phenological observations and analysis of yield components, seed productivity and quality of Favoryt watermelon variety in the intercropping with sugar maize and common bean were presented. It was established that the developed elements of the watermelon growing technology in intercropping under high temperatures and low relative air humidity in the Northern Steppe of Ukraine increased of watermelon yield and the full-value seed formation. It was found that intercropping of watermelon with sweet corn under proper cultivation gave positive results (watermelon seed yield gain by 12.4 % and 0.7 t/ha ears of sweet maize in milky-wax ripeness were received additionally), and with common bean (watermelon seed yield gain by 8.9 % and additional 75 kg/ha of beans). Methods and planting schemes of watermelon and intercrops were established: sugar maize in the rows of watermelon according to scheme 2.8 x 1 m, common bean in the rows of watermelon according to scheme 1.4 x 0.5 m. It was found that under intercropping of watermelon with sweet maize the full-value seed yield per one fruit increased up to 88.5 %, and with common bean – to 84.9 %. Key words: watermelon, sugar maize, common bean, intercropping, seed yield.

Flower Detection Using Object Analysis: New Ways to Quantify Plant Phenology in a Warming Tundra Biome

Rising temperatures caused by global warming are affecting the distributions of many plant and animal species across the world. This can lead to structural changes in entire ecosystems, and serious, persistent environmental consequences. However, many of these changes occur in vast and poorly accessible biomes and involve myriad species. As a consequence, conventional methods of measurement and data analysis are resource-intensive, restricted in scope, and in some cases, intractable for measuring species changes in remote areas. In this article, we introduce a method for detecting flowers of tundra plant species in large data sets obtained by aerial drones, making it possible to understand ecological change at scale, in remote areas. We focus on the sedge species E. vaginatum that is dominant at the investigated tundra field site in the Canadian Arctic. Our system is a modified version of the Faster R-CNN architecture capable of real-world plant phenology analysis. Our model outperforms experienced human annotators in both detection and counting, recording much higher recall and comparable level of precision, regardless of the image quality caused by varying weather conditions during the data collection. (K. Stanski, GitHub - karoleks4/flower-detection: Flower detection using object analysis: New ways to quantify plant phenology in a warming tundra biome. GitHub. Accessed: Sep. 17, 2021. [Online]. Available: https://github.com/karoleks4/flower-detection .)

Mapping Spatiotemporal Changes in Vegetation Growth Peak and the Response to Climate and Spring Phenology over Northeast China

Global climate change has led to significant changes in seasonal rhythm events of vegetation growth, such as spring onset and autumn senescence. Spatiotemporal shifts in these vegetation phenological metrics have been widely reported over the globe. Vegetation growth peak represents plant photosynthesis capacity and responds to climate change. At present, spatiotemporal changes in vegetation growth peak characteristics (timing and maximum growth magnitude) and their underlying governing mechanisms remain unclear at regional scales. In this study, the spatiotemporal dynamics of vegetation growth peak in northeast China (NEC) was investigated using long-term NDVI time series. Then, the effects of climatic factors and spring phenology on vegetation growth peak were examined. Finally, the contribution of growth peak to vegetation production variability was estimated. The results of the phenological analysis indicate that the date of vegetation green up in spring and growth peak in summer generally present a delayed trend, while the amplitude of growth peak shows an increasing trend. There is an underlying cycle of 11 years in the vegetation growth peak of the entire study area. Air temperature and precipitation before the growing season have a small impact on vegetation growth peak amplitude both in its spatial extent and magnitude (mainly over grasslands) but have a significant influence on the date of the growth peak in the forests of the northern area. Spring green-up onset has a more significant impact on growth peak than air temperature and precipitation. Although green-up date plays a more pronounced role in controlling the amplitude of the growth peak in forests and grasslands, it also affects the date of growth peak in croplands. The amplitude of the growth peak has a significant effect on the inter-annual variability of vegetation production. The discrepant patterns of growth peak response to climate and phenology reflect the distinct adaptability of the vegetation growth peak to climate change, and result in different carbon sink patterns over the study area. The study of growth peak could improve our understanding of vegetation photosynthesis activity over various land covers and its contribution to carbon uptake.

A review of the methods for studying biotic interactions in phenological analyses

Abstract Phenological events play a key role modulating ecosystem services; however, the complex and interlinked nature of ecosystems indicates that interactions among different taxa during phenological events can have consequences for the entire ecosystem. Currently, there is a lack of a unified criteria on the methodologies studying phenology and biotic interactions. We performed an extensive integrative review of works evaluating phenology and biotic interactions. We identified four broad categories of studies that have explored biotic interactions within phenology research: (a) spatial and temporal asynchronies, (b) biotic factors as covariates, (c) simulation studies and (d) interaction indices. We found that spring phenology has received much more attention than any other season, while mutualistic and obligated interactions, as well as trophic interactions and networks have been explored more routinely than facilitation or competition. Authors tend to interpret coexistence among species as biotic interactions without any direct measurement, particularly in spatial and temporal asynchrony studies, but this also occurs to a certain extent in all categories. We also found a lack of formal examination in most studies exploring phenological mismatches in response to climate change. We propose a conceptual framework for the inclusion of phenology in the study of biotic interactions that apportions research into the conceptualisation and modelling of biotic interactions. Conceptualisation explores phenological data, types of interactions and the spatiotemporal dimensions, which all determine the representation for biotic interactions within the modelling framework, and the type of models that are applicable. Finally, we identify emerging opportunities to investigate biotic interactions in phenology research, including spatially and temporally explicit species distribution models as proxies for phenological events and the combination of novel technologies (e.g. acoustic recorders, telemetry data) to quantify interactions.

Analysis of vegetation dynamics using remote sensing and GIS: a case study of Madhya Pradesh, India

This paper is aimed to study the correct growth cycle of two staple foods (i.e., wheat and rice), of Madhya Pradesh state of India through an approach of vegetation dynamics which focuses on analysing various parameters, such as rainfall, soil temperature, soil moisture, and crop growth trend over time using temporal data based on regression analysis to generate crop maps. This paper analyses various stages of growth for two major staple crops in Madhya Pradesh (M.P.) region. Wheat and rice farming in M.P. is facing issues related to climate change, drought, fertilizer application, low selling prices, and other. Nature of growth and effect of various parameters like rainfall, temperature, was studied and a proper graph analysis was done for a better understanding of plant growth, and generation of various phenological maps. In multiple regression analysis, R2 value of 0.24 and 0.45 was found highest for HH and VV polarization for wheat and rice, respectively. This means that multi-linear regression for HH and VV explains 24% and 45% for wheat and rice, respectively. Analysis and simulation of crop phenology was done by using the trend analysis approach with the help of the various graphs values that explains the different stages of crop growth and the effect of changing temperature and rainfall over the growth of the crops, Use of ArcGIS 10.5 software simplifies the study process and helped in developing a better understanding.

Exploring Spring Onset at Continental Scales: Mapping Phenoregions and Correlating Temperature and Satellite-Based Phenometrics

Each spring many plants put on new leaves and/or open their flowers creating a “green-wave” that can be tracked using phenological data. Various phenological datasets can be used to study spring onset at continental to global scales. Here we present a novel exploratory analysis where we link two multi-decadal and high-spatial resolution datasets: temperature-based phenological indices and land surface phenological metrics derived from satellite images. Our exploratory analysis, illustrated with data for the conterminous US, focuses on identifying regions with similar spring onset, and on mapping the coherence between these phenological products. Our results show that the spring onset patterns captured by the satellite are more complex than the ones identified using temperature-based phenological indices. They also highlight areas with stable and unstable spring onsets (i.e., areas that tend to remain or change of phenoregion from year to year). Finally, our results reveal that temperature-based indices are both positively and negatively correlated with the phenological information that can be derived from satellites. This opens the door to the definition of rules to integrate multi-source phenological data. To cope with the computational challenges of analyzing big geospatial rasters, we executed our analysis on a cloud platform running Apache Spark and various of its extensions (e.g., Geotrellis, SparkMLlib). This platform performed well and allowed the execution of user-tailored analyses. Hence, we believe that our computational platform paves the path towards the efficient analysis of global vegetation phenology at very high spatial resolution and, more generally, to the analysis of the ever-increasing collections of geospatial data about our planet.

Examining land surface phenology in the tropical moist forest eco-zone of South America

Using leaf area index (LAI) data from 1981 to 2014 in the tropical moist forest eco-zone of South America, we extracted start (SOS) and end (EOS) dates of the active growing season in forest and savanna at each pixel. Then, we detected spatiotemporal characteristics of SOS and EOS in the two vegetation types. Moreover, we analyzed relationships between interannual variations of SOS/EOS and climatic factors, and simulated SOS/EOS time series based on preceding mean air temperature and accumulated rainfall. Results show that mean SOS and EOS ranged from 260 to 330day of year (DOY) and from 150 to 260DOY across the study region, respectively. From 1981 to 2014, SOS advancement is more extensive than SOS delay, while EOS advancement and delay are similarly extensive. For most pixels of forest and savanna in tropical moist forest eco-zone, preceding rainfall correlates predominantly negatively with SOS but positively with EOS, while the relationship between preceding temperature and phenophases is location-specific. In addition, preceding rainfall is more extensive than preceding temperature in simulating SOS, while both preceding rainfall and temperature play an important role for simulating EOS. This study highlights the reliability of using LAI data for long-term phenological analysis in the tropical moist forest eco-zone.

Updated checklist and assemblages of grasshoppers (Orthoptera: Acridomorpha) associated with various habitats, including oases of Central Sahara in Algeria

The grasshopper communities of central Saharan ecosystems (Adrar region, Algeria) were studied at two scales: the first scale considered different biotopes in 23 localities. Random sampling with different traps from February 2016 to February 2019 made it possible to capture two families comprising 20 species, of which 13 are recorded for the first time in the region. The second scale concerned the desert oases. Monthly sampling from March 2017 to November 2018 captured 11 species belonging to two families and four different subfamilies. A comparative study of the grasshopper community in three palm groves with two types of habitat (cultivated and uncultivated) indicated homogeneity in fauna diversity, although their composition was very different. Phenological analysis of species in three oasis habitats revealed the presence of three groups of species: (1) a group of hygrophilic species with a reproduction period concentrated in summer, (2) xerophilic species only present during the spring and autumn, (3) a group of mesophilic species remaining present almost throughout the year and moving between the two types of habitats. Despite three years of field work with several trips and in different biotopes, we believe that the list of species presented here is not exhaustive, but only an updated list, and we consider the new data as an important resource for various future studies, especially genetic studies.

Spatial analysis of rice phenology using Sentinel-1 and Sentinel-2 in Karawang Regency

Karawang Regency is the top rice producer within West Java, Indonesia. Accurate information about the number of harvest area is essential in rice production in Indonesia. The Sentinel imageries (Sentinel-1 and Sentinel-2) which have a spatial resolution of 10 meters can provide spectral information on the earth surface in relatively narrow temporal resolution. The study aims to spatially analyze the rice field phenology using Sentinel-1 and Sentinel-2 imagery and estimate the rice productivity in Karawang Regency. The study used Synthetic Aperture Radar (SAR) Sentinel-1, with the C-Band, which are capable of monitoring rice phenology and Sentinel-2. The combination of polarization from SAR and vegetation index algorithm from the optical image are used to determine the age of rice plants, which then used to estimate rice productivity. The stage of rice was land preparation, vegetative, generative, and harvesting. The result from the estimation of harvest area is between 102,965.00 - 109,338.27 hectares, and the estimation of rice productivity is 5-6 tons/hectares in Karawang Regency.

Spatial analysis of rice phenology using Sentinel-2 and UAV in Parakan Salak, Sukabumi Regency

West Java is the third province with the largest area of paddy field. On the province scale, there are five districts with more than 60,000 hectares of the paddy field area. Sukabumi is fifth largest districts with 6.8% of the area covered with paddy field. Although it is not the greatest number, Sukabumi is the largest producer of paddy with more than 6 ton per hectare, especially in 2011. Rice is the primary food for most of Indonesian. Therefore, monitoring the rice planting regarding the phenology, planting area, and productivity is a critical process. Information from the process is very important to address the national issue of food security. This study aims to generate spatial and temporal information on rice phenology. This study uses the excellence of remote sensing technology to cover a big area of paddy field. Sentinel-2 imageries and photos from Unmanned Aerial Vehicle (UAV) are being applied to generate Normalized Difference Vegetation Index (NDVI). With NDVI, this study determines the growth stage of paddy by discriminating each stage based on the spectral value. The planting phases that have discovered in the area are land preparation, vegetative, generative, and harvesting. Based on the NDVI value, it is known that the vegetative stage ranges from 0.181 to 0.80. The study concludes that result from Sentinel-2 and UAV can be used to show the distribution of paddy based on different growth stage.