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Article

Temperature Induced Flowering Phenology of Olea ferruginea Royle: A Climate Change Effect

by
Sajid Khan
1,
Kailash S. Gaira
2,
Mohd Asgher
1,
Susheel Verma
1,3,*,
Shreekar Pant
4,
Dinesh K. Agrawala
5,
Saud Alamri
6,
Manzer H. Siddiqui
6 and
Mahipal Singh Kesawat
7,8
1
Department of Botany, Baba Ghulam Shah Badshah University, Jammu and Kashmir, Rajouri 185234, India
2
Sikkim Regional Centre, G. B. Pant National Institute of Himalayan Environment, Pangthang, Gangtok 737101, India
3
Department of Botany, University of Jammu, Jammu 180006, India
4
Centre for Biodiversity Studies, Baba Ghulam Shah Badshah University, Jammu and Kashmir, Rajouri 185234, India
5
Botanical Survey of India, Salt Lake City, Kolkata 700064, India
6
Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
7
Institute of Molecular Biology and Genetics, School of Biological Sciences, Seoul National University, Seoul 08826, Republic of Korea
8
Department of Genetics and Plant Breeding, Faculty of Agriculture, Sri Sri University, Cuttack 754006, India
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(8), 6936; https://doi.org/10.3390/su15086936
Submission received: 14 February 2023 / Revised: 24 March 2023 / Accepted: 11 April 2023 / Published: 20 April 2023
(This article belongs to the Special Issue Sustainable Forest Management and Environmental Sustainability: Challenges and Management Implications)
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Abstract

:
Studies from different parts of the world have generated pieces of evidence of climate change’s effects on plant phenology as indicators of global climate change. However, datasets or pieces of evidence are lacking for the majority of regions and species, including for the climate-sensitive Himalayan biodiversity hotspot. Realizing this gap in information, and the wide-ranging implications of such datasets, we integrated real-time field observations and long-term herbarium records to investigate the changes in the spring flowering phenology of Olea ferruginea Royle, commonly known as the Indian Olive, in response to the changing climate in the western Himalayas. We attempted to create phenological change model using the herbarium records and field observations after recording the current dates of flowering and overall temperature trends from the study area over the last four decades from the five regional meteorological observatories of the Jammu province managed by Indian Meteorological Department (IMD) in Jammu and Kashmir. When considering current flowering dates along with herbarium information (years 1878–2008) for O. ferruginea, our Generalized Additive Model (GAM) showed 15–21 days-early flowering over the last 100 years significantly (p < 0.01). Results of the Mann–Kendall test showed increasing trends of TMin for all seasons significantly (p < 0.05) for Jammu province whereas TMax was only for the spring season. The increasing TMin of spring, summer, and autumn seasons also influenced the flowering phenology of O. ferruginea significantly (p < 0.01). By demonstrating the integrated use of methodological tools for finding long-term phenological changes in response to climate change, this work bridges knowledge gaps in phenological research from the developing world in general and the Himalayas in particular.

1. Introduction

Phenological changes are associated with global climate change and are recognized as some of the potentially sensitive indicators worldwide [1,2,3]. Shifting plant phenology and changes in plant reproduction patterns and behavior are synchronized strongly with climatic variations [4,5,6,7,8]. It has been established that global warming affects biological processes [9] and influences the periodic events in plant life cycles. There are enough pieces of evidence from different parts of the world that global warming impacts plant phenology [10,11,12], which is considered as an easily measurable variable. Periodic events such as flowering and fruiting periods have arrived earlier or later due to seasonal climatic variations [13]. Early flowering in response to higher temperatures [14] is actually an advancement of the entire reproductive process that could potentially alter plant–pollinator interaction and successive reproductive stages [15]. The reproductive output and species redistribution constitute the second immediate consequence of this change. In addition, temperature has been identified as one of the most powerful drivers of plant phenological events, among all climatic factors [16,17,18,19,20,21,22,23]. The close correlation between temperature and the underlying metabolic processes in plants may account for the crucial function of temperature in plant phenology [24]. While precipitation also controls the soil’s moisture content, this influences the progression of the plant phenological events [25].
Climatic variations influence plant phenological traits in a wide geographical area. The Himalayan Mountain range has geographical and climatic complexity, and possesses unique biodiversity patterns across the elevational range. Therefore, the region is quite sensitive to climate change. Pieces of evidence on climate change patterns in the Himalayan ecosystem have been investigated as regional warming trends [26,27,28] and patterns in declining rainfall [29,30]. Also, several climate scenario-based prediction modeling on the habitat suitability of important medicinal plants have been studied in the western Himalaya region [31,32,33,34]. To understand the impact of climatic change on phenology traits, it is essential to have a long-term phenological and climatic database [3,35,36]. As an alternative, several studies are based on old herbarium records in order to track the shift in flowering seasons [36,37,38]. Few are based on real-time field observations and herbarium records [39]. Furthermore, the bulk of phenological research is limited by a dearth of long-term historical data, especially in the Himalayan region, where long-term phenological observation records are lacking [40]. Herbarium specimens and historical images provide tremendous chances to recreate the historical flowering phenology of plants in this regard [41,42,43].
The Himalayas are one of the most sensitive areas to climate change and have experienced significant environmental changes impacting snow cover, glacier conditions, and permafrost conditions over the last five decades [44,45]. The environmental changes in the Himalayas have affected local populations, ecosystem services, and biodiversity [46,47]. This region has experienced a considerable impact of global warming over the past few decades, particularly in the erratic behavior of seasonal temperature and precipitation regimes [48,49,50,51] and warming at a faster rate in comparison to the nearby Indian land mass [52]. Limited studies on the context of plant phenology changes due to climate change have been undertaken from the Himalayan landscape [3,6,30,53]. However, such long-term studies require long-term-based experimental or observational data and herbarium records. This analytical approach has not been used yet in this important part of the Himalayas, i.e., Jammu province, which is quite sensitive to global climate change. Here, an important medicinal plant i.e., O. ferruginea, is reported as sensitive to climatic variations [54].
Realizing the importance, we attempted to supplement historical herbarium and field-based observational data and seasonal climatic trends in order to identify changes in flowering phenology from the northwestern Himalayas. For this investigation, we used O. ferruginea (Family: Oleaceae), a spring flowering plant, as the model plant species in the western Himalayas. O. ferruginea is a wild species of olive lineage. It is widely distributed across Asia and Africa and is commonly identified as the Indian and African olive. The species grows in the subtropical climate of the Jammu division of the western Himalayas, and is ecologically and economically important for local communities. Traditional medicine recommended the use of the stem bark of O. ferruginea to treat fever [55], while fresh leaf extracts of this plant were utilized by those with bleeding gums, toothaches, skin disorders, skeletal muscle, and dental problems [56,57]. Additionally, O. ferruginea fruit is a rich source of oil that can be used as a massage ointment to treat rheumatism and the discomfort associated with broken bones [58]. Additionally, this plant’s various parts have considerable anti-malarial, anti-inflammatory, anti-periodic, anti-leprosy, astringent, antidiabetic, and anti-asthmatic properties [59]. Its overexploitation as fuelwood, excessive grazing, unauthorized cutting, and the expansion of cropland are grave threats to its survival.
The main objectives of the study were to investigate: (i) the shifts in flowering phenology of the target species over the years and (ii) the responsible seasonal climate warming indications or trends for the change in flower phenology.

2. Materials and Methods

2.1. Study Area

Jammu and Kashmir is blessed with high snow-capped peaks, deep gorges, glaciers, lush green meadows, and beautiful valleys. The Jammu and Kashmir region spans 42,241 km2 and is situated between the 33° and 27° North latitudes and 75° and 34° East longitudes. Here, the Jammu region comprises the Shiwalik plains in the south and the mighty PirPanjal mountain range in the north (Figure 1). This mountain range separates the Kashmir valley from the plains of the subcontinent. In the north of the outer plains lie the youngest mountains of the subcontinent, known as the Shiwalik hills, with an elevation range of 600–1400 m asl. From the north of the Shiwalik range lies the PirPanjal mountain range, with an average elevation of 1400–4100 m above sea level (asl). The PirPanjal range is the largest mountain range in the lesser Himalayas. Our study area comprises a vast range of habitats, which is reflected by a diverse range of biodiversity distribution. Based on mean temperature and precipitation, the climate of Jammu province falls under sub–tropical to temperate transitional with four seasons [51].

2.2. Herbarium Records

The herbarium records of the species deposited in different herbaria (FRI Dehradun, BSI Kolkatta, Dehradun, and Solan; University of Jammu; Kashmir University) covering 130 years were studied (1878–2008). Each of the available herbarium specimens was carefully examined, and only such specimens with mature flowering supplemented with collection date (day, month, and year) were retained. The herbarium specimens with fruits or only leaves and branches and incomplete or missing label information, i.e., with no date of the collection given, were excluded. Out of 89 herbarium specimens from the study area, only 41 were found appropriate for analysis. The collected data of the peak flowering dates were converted into a Julian day of the year (DOY). For example, in a given calendar year, if the flowering happened on 25 February, the DOY is 56 days after the 1st of January.

2.3. Real–Time Field Observations

After a reconnaissance during the spring season, a total of 21 sites with an abundance of O. ferruginea and an altitudinal range of 600 m to 1600 m were identified in the Jammu province of the western Himalayas and monitored frequently for 3 years during the early to ending phase of flowering (2018–2021). According to three years of field observations, the flowering time of O. ferruginea starts in mid-April and ends in mid-May. Therefore, the peak flowering time was observed to be during the last week of April and 1st week of May.

2.4. Climatic Data

For the current study, time series data on monthly mean maximum and minimum temperature and precipitation were collected for a period of 41 years (1980–2020) from a total of five regional meteorological stations of the Indian Meteorological Department (IMD), Ministry of Earth Sciences, Government of India (www.imd.gov.in) (accessed on 21 May 2021). These stations cover different areas of the Jammu province. In order to achieve homogeneity among all the stations, we selected the time series data for 41 years from 1980 to 2020, except for the Jammu regional station, for which we had data for the temporal period from 1982–2020. Since the changing climate during the spring (March–May) season is crucial for studying the phenological changes of our selected species (O. ferruginea), we calculated the climatic variables of seasonal mean maximum temperature (TMax) and mean minimum temperature (TMin) for spring seasons.
By following Dad et al. [51], we adopted the non-parametric Mann–Kendall test [60,61] to study the significance of trends in time series climatic variables on seasonal and annual scales. Additionally, to quantify the magnitude of detected trends in the climatic time series, we used the most popular non-parametric method, Sen’s slope method [51,62]. Finally, we analyzed seasonal trends in climatic variables, as well as their relationship with the mean flowering date (MFD) of the targeted species over the last century.

2.5. Statistical Analysis

For the phenological change study, we combined both herbarium and field observational data, which provides a response variable i.e., flowering time (DOY). The response variable as flowering time is complex with non-normality and non-linearity; therefore, parametric techniques may not be appropriate. This is because of herbarium-based flowering data complications such as (i) vast elevation ranges, (ii) several recordings each year, (iii) non-constant series of collections, and (iv) irregular data-collecting frequency [39,53]. Also, the combined database on response variables is not found to be suitable for parametric and linear applications. Hence, GAM-based phenological modeling has been adopted after the reconstruction of long-term herbarium records and field observations of target species.
The generalized additive model (GAM) was used in the current investigation, where the response variable i.e., flowering time (DOY) is associated with the explanatory variables like year, elevation, and warming temperature. The concept of GAM is derived from the Generalized Linear Model (GLM) (Equation (1)):
g i ( Y ) = S i f i ( X i )
which allows using normal and non-normal distributions along with an additive link function. This allows one to predict flowering-time changes as a response variable with respect to the explanatory variables (year, elevation, and warming temperature). The GAM finally calculated (Equation (2)) the partial residuals as adjusted flowering time thus:
R j i = Y − S 0 − ∑ h ≡ ≠ j S k X k
The StatSoft STATISTICA (8.0.360) software was used for the GAM. To predict the change in flowering time due to increasing temperature, the data of flowering was considered from 1980–2020.

3. Results

3.1. Flowering Phenological Shift

Considering current flowering dates along with herbarium information (1878–2008) for Olea ferruginea, GAM predicted early flowering (i.e., 15–21 days) over the last 100 years (GAM coefficient = −0.181, SE = 0.027, R2 = 46.93) significantly (p < 0.01) (Figure 2). Furthermore, while estimating the responses of flowering time along the increasing altitudinal gradient, GAM showed non-significant responses for the targeted species (p > 0.01) (Figure 3).

3.2. Seasonal Temperature Trends

To understand the early flowering responses due to climate change, seasonal warming trends of Jammu Province were projected using the Mann–Kendall test. The increasing trend in TMax of the spring season (March–May) was only for the entire Jammu province; similarly, increasing trends in TMin of all seasons were projected for Jammu province significantly (p < 0.05) (Table 1).
The results of Sen’s test for calculating the magnitude of the seasonal trend for temperature (TMax and TMin) are summarized in Table 2. A significant increase of 0.052 °C for TMax for the spring season (February–April) was observed for the entire Jammu province (Table 2). In contrast, for TMin, a significant increasing trend was observed for all four seasons, with a larger increase during the spring (0.067 °C a−1), and the smallest increase during the summer season (0.052 °C a−1) (Table 2).

3.3. Impacts of Warming Seasons on Flowering Phenology

Considering the significant increasing trends of minimum temperature (TMin) for all seasons, their responses on flowering phenology were estimated. The GAM indicated significant (p < 0.01) early flowering with increasing TMin of all seasons except winter (Table 3). The flower phenology was responded significantly (p < 0.01) early at the rate of 6–9 days/1 °C of the summer season and followed by days/1 °C of autumn season and ~3 days/1 °C of the spring season (Figure 4).

4. Discussion

This study demonstrates how the observed rising temperatures in the region had an impact on the trends of advancement in phenological phases observed for wild olive species in the Jammu province, located in the northwestern Himalayas. These findings are consistent with comparable variations of the plant’s life cycle that have been documented globally [63,64], in Europe [65,66,67], and regionally in the Himalaya region [36,39,53,68]. With advancements in the study, it has become clear that plant phenology responses to climate variability and change are both location-and species-specific [69]. The degree to which plants are influenced by rising temperature, as well as their inherent adaptability capabilities, will ultimately decide the possibility for long-term ecological stability and ecosystem services.
In recent years, phenological analyses based on herbarium specimens have attracted attention to investigate the climate change impacts on biodiversity, but these are very limited in the Indian Himalayan Region (IHR). However, Gaira and Dhar [3] compared 654 herbarium specimens of five medicinal plants in the IHR and projected significant advancement in flowering time over the last 100 years only for alpine/sub–alpine species. In addition, Gaira et al. [39,53] compared herbarium specimens of Aconitum heterophyllum Wall. ex Royle and Rhododendron arboreum Sm. and found evidence of earlier flowering of 19–27 and 88–97 days, respectively, over the last 100 years. Such indications from the above studies from the IHR are quite supported by the current study.
Phenological studies using herbarium specimens are well-established mechanisms and are recognized as indicators of climate change globally. In this series, similar inferences were established by Mohandass et al. [6], and estimated early blooming over time. Hassan et al. [36] examined how early blooming responses changed as the temperature rose in the Kashmir Himalaya. Robbirt et al. [70] used herbarium and field observations to study flowering-period responses to spring temperature. In this work, along with the flowering time, we also took into account the target species’ flowering pattern as a function of elevation, which is important in the Himalayas, particularly for phenological activities. The flowering period is generally agreed to be delayed at higher elevations. However, we discovered that there is no significant relationship between elevation and flowering phenology over a period of time for the studied species. Our model, which takes into account the flowering pattern throughout the year, shows that O. ferruginea flowering has advanced (15–21 days) in the twenty-first century. Similarly, using 216 herbarium specimens, Lavoie and Lachance [71] reported (15–31 days) earlier flowering of Tussilago farfara L.in the twenty-first century than in around 1920. Several herbarium-based studies report earlier flowering in different plants [12,42,72]. The early-spring-flowering species of bluebell, cuckoo flower, coltsfoot, garlic mustard, and wood anemone responded to increasing temperatures by advancing their first flowering day (FFD) [73]. The early flowering pattern of O. ferruginea may also be linked with a warming spring, which shows that on average, flowering time is earlier (15–21 days) with an increase in mean spring temperature. While the effect of photoperiod is only noticeable in a small percentage of plants, experimental data has shown that the late autumn plays a critical role in modulating spring phenology [74,75]. However, Hassan et al. [36] compared herbarium and field records to examine the relationship between phenology and winter temperature, and found 11.8 days and 27.8 days early flowering per 1 °C in Sternbergia vernalis Mill. in the Kashmir Himalaya. Also, the winter temperature is the most important variable affecting the initial and peak flowering of Rhododendron arboreum [76]. The sensitivity of flowering is determined by the temperature of the previous month, and the majority of the changes in flowering time are caused by increased winter and spring temperatures [11,77].
In contrast to TMin, which showed a statistically significant rising trend throughout all the seasons, our study observed a substantial increase for TMax during the spring season. This study’s seasonal difference is consistent with several other studies carried out in the Himalayas [78,79,80]; Lancang Valley, China [81]; and Tibet [82], where almost all stations recorded a higher increase in winter and spring temperatures compared to autumn and summer temperatures. Our studies appear comparable to earlier studies like Dad et al. [51] and Jaswal and Rao [83] who, for the time series 1980–2017 and 1967–2010, respectively, noted that the temperature is increasing over Jammu and Kashmir, with significant increase in maximum temperature in the Kashmir region. However, when compared with the increase in minimum temperature, our studies show different results. Trend values show that the greater rise in the minimum temperature is having an increasing impact on the mean temperature in the Jammu region. Changes in precipitation and temperature in the area can have a significant impact on the distribution of forests [84] and the availability of water [85]. The region’s biodiversity and ecological stability could be adversely impacted by the changing pattern of temperature.
This study has established the basis of available records of herbarium specimens along with real-time field observations and the availability of long-term climatic time series data of the area of occurrence of the target species by using GAM. However, the majority of the herbarium-based phenological investigations used the same response variable (flowering time) and used standard statistical methods (i.e., linear regression model). The fitness of species within their current ranges may be immediately impacted by this climatechange, but it may also—and maybe more subtly—affect their ecological relationships [86]. As far as pollination mode is concerned, O. ferruginea is ambophilous [87], therefore, pollination success may partially impacted by plant-pollinator mismatch in this species. However, this warming trend and phenological change will negatively impact species that are solely entomophilous.
These data show that temperature changes in spring have resulted in the early flowering of an important medicinal plant and a significant advance in flowering over the last century. Thus, our study on O. ferruginea, a spring flowering plant, can be a useful predictor for monitoring how changing climate can change a plant’s flowering phenology in response to warmer temperatures on a regional, national, and global level.

5. Conclusions

A well-documented fingerprint of climate change that can have direct effects on the supply of ecosystem goods and services is the advancement or shift in flowering phenology. The current study examined the impact of long-term climatic changes on the phenology of spring flowering in the western Himalayas. Over the course of one century in this Himalayan region, we saw a dramatic advancement in the flowering phenology of the spring flowering plant, O. ferruginea. The early flowering of our model plants is seen to be more strongly projected with warming seasons (minimum temperature) than with precipitation, and relative humidity suggesting that continued global warming would most likely have a significant impact on flowering phenology in this Himalayan region. We observed that higher TMin values during the spring were significantly more strongly connected with flowering advancement than TMax, suggesting that the phenological response is probably more closely tied to comparatively warmer nights than days. Future research must take additional impacts of spring TMin into account since they were more important in advancing flowering phenology in our model plant species. Further, the warming seasons of TMin, especially spring, summer, and autumn, influence the early flowering of the target species. Our assessments of long-term monitoring records supported prior experimental and field investigations carried out in other regions of the world and were compatible with warming results from experiments. The findings of the current study provide important methodological insights that may be applied to future phenological research investigations in order to identify emerging patterns in plant phenology from the Himalayas.

Author Contributions

Conceptualization, S.K. and S.V.; methodology, S.K. and K.S.G.; software, S.K. and K.S.G.; validation, M.A., S.V. and K.S.G.; investigation, S.V.; resources, S.K. and S.V.; data curation, M.A., S.K., K.S.G. and D.K.A.; writing—original draft preparation, S.K; writing—review and editing, S.A., M.H.S., S.P. and M.S.K.; supervision, S.V.; project administration, S.K. and S.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Mission on Himalayan studies (NMHS) under fellowship Grant No: GBPNI/NMHS–2018–19/HSF–24–02/153 and Researchers Supporting Project number (RSP2023R347), King Saud University, Riyadh, Saudi Arabia.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We express gratitude to the Indian Meteorological Department (IMD), Srinagar for providing climatic data for this study. Botanical Survey of India Kolkata and BSI regional centre Dehradun and High Altitude Western Himalayan Regional Centre (HAWHRC), Solan; and Forest Research Institute Dehradun, University of Jammu, and University of Kashmir are duly acknowledged for providing herbarium specimens. The authors would like to extend their sincere appreciation to the Researchers Supporting Project number (RSP2023R347), King Saud University, Riyadh, Saudi Arabia. National Mission on Himalayan studies (NMHS) is greatly acknowledged for financial support under fellowship Grant No: GBPNI/NMHS–2018–19/HSF–24–02/153.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) Location map of the study area (real time field observations), (b) representative herbarium specimen and some field photographs of the model plant species (Olea ferruginea).
Figure 1. (a) Location map of the study area (real time field observations), (b) representative herbarium specimen and some field photographs of the model plant species (Olea ferruginea).
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Figure 2. GAM-predicted changes in flowering time as partial residual of O. ferruginea across the years from 1878–2021 using long-term herbarium records (1878–2008) and field observations (2019–2021).
Figure 2. GAM-predicted changes in flowering time as partial residual of O. ferruginea across the years from 1878–2021 using long-term herbarium records (1878–2008) and field observations (2019–2021).
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Figure 3. GAM–predicted changes in flowering time as partial residual of O. ferruginea across the elevation gradients from 500–1800 masl using long-term herbarium records (1878–2008) and field observations (2019–2021).
Figure 3. GAM–predicted changes in flowering time as partial residual of O. ferruginea across the elevation gradients from 500–1800 masl using long-term herbarium records (1878–2008) and field observations (2019–2021).
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Figure 4. GAM–predicted changes in flowering time (as partial residual) with respect to increasing seasonal minimum temperature (TMin) (Winter, Spring, Summer, Autumn) of the observed time series data of Jammu Province from 1980–2020.
Figure 4. GAM–predicted changes in flowering time (as partial residual) with respect to increasing seasonal minimum temperature (TMin) (Winter, Spring, Summer, Autumn) of the observed time series data of Jammu Province from 1980–2020.
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Table
Table 1. Seasonal time series trends analysis for temperature (TMax and TMin) using Mann–Kendall test for Jammu province from 1980–2020.
Table 1. Seasonal time series trends analysis for temperature (TMax and TMin) using Mann–Kendall test for Jammu province from 1980–2020.
Season TMax (°C)TMin (°C)
SpringZ-score2.01054.0213
p-value0.040.00005
TrendPositivePositive
SummerZ-score−0.98864.9988
p-value0.325.768 × 10−7
TrendNo trendPositive
AutumnZ-score−0.1914.8756
p-value0.850.000001
TrendNo trendPositive
WinterZ-score1.71923.6394
p-value0.080.0002
TrendNo trendPositive
Table
Table 2. Estimated slope change using Sen’s test for seasonal temperature (TMax and TMin), across the years (1980–2020) for the entire Jammu province.
Table 2. Estimated slope change using Sen’s test for seasonal temperature (TMax and TMin), across the years (1980–2020) for the entire Jammu province.
SeasonSen’s Slope Estimation
TMax
(°C a−1)		TMin
(°C a−1)
Spring0.052 *
(0.003 to 0.093)		0.067 ***
(0.036 to 0.100)
Summer−0.012 ns
(−0.033 to 0.011)		0.052 ***
(0.035 to 0.070)
Autumn−0.003 ns
(−0.027 to 0.018)		0.060 ***
(0.042 to 0.079)
Winter0.027 ns
(−0.002 to 0.071)		0.057 ***
(0.027 to 0.089)
Statistical significances: *** denotes p < 0.001 and * denotes p < 0.05; ns denotes p > 0.05.
Table
Table 3. GAM coefficient (β) of flowering changes with respect to increasing seasonal minimum temperature (Winter, Spring, Summer, Autumn) of the observed time series data of Jammu Province from 1980–2020.
Table 3. GAM coefficient (β) of flowering changes with respect to increasing seasonal minimum temperature (Winter, Spring, Summer, Autumn) of the observed time series data of Jammu Province from 1980–2020.
SeasonnFlowering Change (DoF)
GAM Coefficient (β)SER2p Value
Winter505.42.3214.90.623
Spring50−1.052.0225.780.004
Summer50−7.59971.72441.3470.0153
Autumn50−5.8872.14233.390.0047
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Khan, S.; Gaira, K.S.; Asgher, M.; Verma, S.; Pant, S.; Agrawala, D.K.; Alamri, S.; Siddiqui, M.H.; Kesawat, M.S. Temperature Induced Flowering Phenology of Olea ferruginea Royle: A Climate Change Effect. Sustainability 2023, 15, 6936. https://doi.org/10.3390/su15086936

AMA Style

Khan S, Gaira KS, Asgher M, Verma S, Pant S, Agrawala DK, Alamri S, Siddiqui MH, Kesawat MS. Temperature Induced Flowering Phenology of Olea ferruginea Royle: A Climate Change Effect. Sustainability. 2023; 15(8):6936. https://doi.org/10.3390/su15086936

Chicago/Turabian Style

Khan, Sajid, Kailash S. Gaira, Mohd Asgher, Susheel Verma, Shreekar Pant, Dinesh K. Agrawala, Saud Alamri, Manzer H. Siddiqui, and Mahipal Singh Kesawat. 2023. "Temperature Induced Flowering Phenology of Olea ferruginea Royle: A Climate Change Effect" Sustainability 15, no. 8: 6936. https://doi.org/10.3390/su15086936

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