**1. Introduction**

Human activities such as agricultural production and fossil fuel combustion add ~200 Tg/year of nitrogen (N) to global ecosystems, approximately equal to that provided by natural N fixation [1].  Numerous studies showed that plant functional traits and ecosystem functions changed significantly under N deposition increase and biodiversity loss [4–6]. Phenology, the periodic events in the life cycles of plants, which is sensitive to global changes [7], and thus understanding the influence of N addition, plant diversity, and its interactions on plant phenology is essential.

Flowering phenology, including flowering date and duration, is an important developmental stage in plant phenology and is known to be determined by numerous abiotic factors, such as temperature, photoperiod, and resource availability [8,9]. Recent research revealed that plant functional traits, such as plant height and leaf traits, may serve as direct determinants for flowering phenology [10–12]. For example, plant height is critical for a species' competitive ability to capture light; taller species with higher maximized light interception and faster relative growth rate often flower later than shorter ones [13,14]; specific leaf area (SLA) is linked to growth rates, and higher SLA was found to be associated

**Citation:** Ma, Y.; Zhao, X.; Li, X.; Hu, Y.; Wang, C. Intraspecific Variation in Functional Traits of *Medicago sativa* Determine the Effect of Plant Diversity and Nitrogen Addition on Flowering Phenology in a One-Year Common Garden Experiment. *Plants* **2023**, *12*, 1994. https://doi.org/10.3390/ plants12101994

Academic Editor: Luca Vitale

Received: 13 February 2023 Revised: 27 April 2023 Accepted: 8 May 2023 Published: 16 May 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

with stronger phenological shifts [15]; leaf carbon and N content are measures for the plants' investment in structural components and photosynthetic accumulation [16,17], whereas shifts in flowering phenology could be due to a trade-off between the investment between vegetative and reproductive growth [18]. Although the links between plant functional traits and flowering phenology have been reported, little is known about which traits are better for predicting the changes in flowering phenology.

Functional traits are measurable biotic properties related to the adaptation of plants to the environment [19,20]. Nitrogen addition stimulates plant growth through increasing soil-available nitrogen, resulting in changes in functional traits, such as plant height, leaf area, and nitrogen content, but varied with plant species [21,22]. Multiple changes in the biotic and abiotic environments along plant diversity gradients require a coordinated response in numerous traits to achieve a balance among different functions [4,23]. For instance, plants with slow growth rate may adjust morphological traits to tolerate low light availability through the formation of longer and thinner leaves [24]; variation in leaf nitrogen content (LNC) may serve as a physiological adjustment to improve photosynthetic carbon gain [25,26]. Hence, plant flowering phenology was significantly affected by N addition [27,28] and plant diversity [5,29], while our knowledge regarding how plant diversity and N deposition affect flowering phenology through plant functional traits was essential to step forward.

Here, we report on a common garden experiment investigating the influence of N addition and plant species richness on three flowering phenologies of *Medicago sativa* L. in an assemblage grassland (Figure S1). Specifically, we explored the effects of N addition and plant species richness on the first flowering day (FFD), last flowering day (LFD), flowering duration (FD), flower numbers (FN), environmental factors, and a series of functional traits. We hypothesized that: (a) increased N inputs and plant species richness would delay flowering phenology; (b) increased N inputs promote light acquisition traits (e.g., SLA and plant height), while decreased plant species richness promotes nutrient acquisition traits (e.g., leaf N concentration); and (c) intraspecific variation in functional traits and changes in abiotic factors would co-drive the response of flowering phenology to N addition and plant species richness.

#### **2. Results**

#### *2.1. The Effects of N Addition and Plant Diversity on Soil Environmental Conditions*

In our common garden experiment, soil temperature and soil moisture at a depth of 10 cm were significantly influenced by nitrogen addition and plant species richness (Table 1). Soil temperature significantly increased, but soil moisture did not change after nitrogen addition (Table 1 and Figure 1). Soil temperature and soil moisture changed markedly following plant species richness increase (Figure 1c,d). Soil temperature significantly decreased along plant species richness gradients under nitrogen addition (Figure 1c). Soil moisture showed no significant relationship with plant species richness under control and nitrogen addition treatments (Figure 1d).

 Soil temperature (°C, at a depth of 10 cm) (**a**) and soil moisture (%, at a depth of 10 cm) (**b**) under different plant species richness and nitrogen addition levels from April to October 2019. Mean (±*se*, *n* = 4 or 8) soil temperature (**c**) and soil moisture (**d**) for the whole growing season along the plant species richness gradients under different nitrogen (N) addition levels in 2019. We applied the ordinary linear regression analysis to test the dynamic of soil temperature and soil moisture along plant species richness gradients. Points and lines with different shapes represent different nitrogen addition levels, and points with different colors represent different plant species richness levels. **Figure 1.** Soil temperature (◦C, at a depth of 10 cm) (**a**) and soil moisture (%, at a depth of 10 cm) (**b**) under different plant species richness and nitrogen addition levels from April to October 2019. Mean (±*se*, *n* = 4 or 8) soil temperature (**c**) and soil moisture (**d**) for the whole growing season along the plant species richness gradients under different nitrogen (N) addition levels in 2019. We applied the ordinary linear regression analysis to test the dynamic of soil temperature and soil moisture along plant species richness gradients. Points and lines with different shapes represent different nitrogen addition levels, and points with different colors represent different plant species richness levels.

#### *2.2. The Effects of N Addition and Plant Diversity on Flowering Phenology 2.2. The Effects of N Addition and Plant Diversity on Flowering Phenology*

The flowering phenology of *M. sativa* was significantly affected by nitrogen addition and plant species richness (Table 1), but the effects varied in different phenological phases (Figure 2). Nitrogen addition delayed the first flowering day of *M. sativa* by 1.9 ± 0.39 days, but plant species richness had no effects on it (Figure 2a). The last flowering day advanced by 1.2 ± 0.21 days after nitrogen addition (Figure 2b) and advanced by an average of 0.51 and 0.77 days per plant species increase under control and nitrogen addition treatments, respectively (Figure 2b). The delay of the first flowering day and the advancement of the last flowering day inevitably led to the shortening of the flowering duration. Nitrogen addition shortened the flowering duration of *M. sativa* by 3.2 ± 0.31 days, and it was short‐ ened by 1.08 and 0.82 days per species increase under control and nitrogen addition treat‐ ments, respectively (Figure 2c). Moreover, our study also showed that flower numbers significantly decreased after nitrogen addition but increased along the plant species rich‐ The flowering phenology of *M. sativa* was significantly affected by nitrogen addition and plant species richness (Table 1), but the effects varied in different phenological phases (Figure 2). Nitrogen addition delayed the first flowering day of *M. sativa* by 1.9 ± 0.39 days, but plant species richness had no effects on it (Figure 2a). The last flowering day advanced by 1.2 ± 0.21 days after nitrogen addition (Figure 2b) and advanced by an average of 0.51 and 0.77 days per plant species increase under control and nitrogen addition treatments, respectively (Figure 2b). The delay of the first flowering day and the advancement of the last flowering day inevitably led to the shortening of the flowering duration. Nitrogen addition shortened the flowering duration of *M. sativa* by 3.2 ± 0.31 days, and it was shortened by 1.08 and 0.82 days per species increase under control and nitrogen addition treatments, respectively (Figure 2c). Moreover, our study also showed that flower numbers significantly decreased after nitrogen addition but increased along the plant species richness gradients (Figure 2d).

#### *2.3. The Effects of N Addition and Plant Diversity on Functional Traits*

ness gradients (Figure 2d).

Nine different leaf traits of *M. sativa* were measured in our study. For light acquisition traits, nitrogen addition significantly increased leaf area but did not change leaf mass and specific leaf area (Table 1 and Figure 3). Specific leaf area significantly decreased with increasing plant species richness (Figure 3), but not for other traits (Table 1 and Figure 3). For nitrogen acquisition traits, nitrogen addition had minor effects on leaf carbon content, leaf nitrogen content, and leaf carbon/nitrogen ratio (Table 1). Leaf nitrogen content significantly decreased, but the leaf carbon/nitrogen ratio significantly increased with increasing plant species richness (Figure 3d,e). There is no interaction effect between nitrogen addition and plant species richness on functional traits (Table 1).

**Figure 2.** The first flowering day (**a**), last flowering day (**b**), flowering duration (**c**), and flower num‐ bers (**d**) of *Medicago sativa* along the plant species richness gradients under different nitrogen (N) addition levels. All the analyses were performed using the ordinary linear regression analysis to test the dynamic of flower phenological events along plant species richness gradients. Points and lines with different shapes represent different N addition levels, and points with different colors repre‐ sent different species richness levels. Shaded areas show 95% confidence intervals of the fit. **Figure 2.** The first flowering day (**a**), last flowering day (**b**), flowering duration (**c**), and flower numbers (**d**) of *Medicago sativa* along the plant species richness gradients under different nitrogen (N) addition levels. All the analyses were performed using the ordinary linear regression analysis to test the dynamic of flower phenological events along plant species richness gradients. Points and lines with different shapes represent different N addition levels, and points with different colors represent different species richness levels. Shaded areas show 95% confidence intervals of the fit. *Plants* **2023**, *12*, x FOR PEER REVIEW 5 of 13

*2.3. The Effects of N Addition and Plant Diversity on Functional Traits*

**Figure 3.** The leaf mass (**a**), leaf area (**b**), specific leaf area (**c**), leaf carbon content (**d**), leaf nitrogen content (**e**), and leaf carbon/nitrogen ratio (**f**) of *Medicago sativa* along the plant species richness gra‐ dients under different nitrogen (N) addition levels. Points and lines with different shapes represent different nitrogen addition levels, and points with different colors represent different plant species richness levels. **Figure 3.** The leaf mass (**a**), leaf area (**b**), specific leaf area (**c**), leaf carbon content (**d**), leaf nitrogen content (**e**), and leaf carbon/nitrogen ratio (**f**) of *Medicago sativa* along the plant species richness gradients under different nitrogen (N) addition levels. Points and lines with different shapes represent different nitrogen addition levels, and points with different colors represent different plant species richness levels.

were positively correlated with last flowering day and flowering duration (Figure 4e,f).

The last flowering day was positively correlated with the first flowering day signifi‐

*2.4. Ecological Factors Influencing Flowering Phenology*

#### *2.4. Ecological Factors Influencing Flowering Phenology*

The last flowering day was positively correlated with the first flowering day significantly (Figure 4a); flowering duration was negatively correlated with the first flowering day and positively correlated with the last flowering day (Figure 4b,d); flower numbers were positively correlated with last flowering day and flowering duration (Figure 4e,f). *Plants* **2023**, *12*, x FOR PEER REVIEW 6 of 13

**Figure 4.** Plots showing the relationships between the four metrics of phenology. Points with differ‐ ent colors represent different plant species richness levels. Shaded areas show 95% confidence in‐ tervals of the fit. **Figure 4.** Plots showing the relationships between the four metrics of phenology. Points with different colors represent different plant species richness levels. Shaded areas show 95% confidence intervals of the fit.

Variation partitioning analysis indicated that nutrient acquisition traits and abiotic factors explained a much greater portion of the variance in the first flowering day (31% and 15%, Figure S5a), last flowering day (23% and 44%, Figure S5b), flowering duration (33% and 46%, Figure S5c), and flower numbers (32% and 44%, Figure S5d), respectively. The structural equation models showed that the changes in the first flowering day were positively correlated with soil‐available nitrogen but negatively correlated with leaf nitro‐ gen content and leaf carbon/nitrogen ratio (Figure 5a). The negative effects of plant species richness on the last flowering day and flowering duration were mainly through its nega‐ tive effects on leaf nitrogen content (Figure 5b,c). Plant species richness impacted flower numbers directly or through its negative effects on leaf carbon/nitrogen ratio indirectly (Figure 5d), and nitrogen addition impacted flower numbers directly or through its posi‐ Variation partitioning analysis indicated that nutrient acquisition traits and abiotic factors explained a much greater portion of the variance in the first flowering day (31% and 15%, Figure S5a), last flowering day (23% and 44%, Figure S5b), flowering duration (33% and 46%, Figure S5c), and flower numbers (32% and 44%, Figure S5d), respectively. The structural equation models showed that the changes in the first flowering day were positively correlated with soil-available nitrogen but negatively correlated with leaf nitrogen content and leaf carbon/nitrogen ratio (Figure 5a). The negative effects of plant species richness on the last flowering day and flowering duration were mainly through its negative effects on leaf nitrogen content (Figure 5b,c). Plant species richness impacted flower numbers directly or through its negative effects on leaf carbon/nitrogen ratio indirectly (Figure 5d), and nitrogen addition impacted flower numbers directly or through its positive effects on leaf mass indirectly (Figure 5d).

tive effects on leaf mass indirectly (Figure 5d).

**Figure 5.** Structural equation modellings of plant species richness and nitrogen (N) addition impact on the first flowering day (**a**), last flowering day (**b**), flowering duration (**c**), and flower number (**d**). Red and black arrows represent significant positive and negative pathways, respectively. Solid and dashed arrows indicate significant and non‐significant pathways, respectively. Numbers near the arrow indicate the standardized path coefficients indicating the effect size of the relationship with \* indicating *p* < 0.05, \*\* indicating *p* < 0.01, and \*\*\* indicating *p* < 0.001. The arrow width is proportional to the strength of the relationship. *R*2 represents the proportion of variance explained for each de‐ pendent variable. The goodness‐of‐fit statistics for the structural equation modeling are shown be‐ low each model. C, carbon. **3. Discussion Figure 5.** Structural equation modellings of plant species richness and nitrogen (N) addition impact on the first flowering day (**a**), last flowering day (**b**), flowering duration (**c**), and flower number (**d**). Red and black arrows represent significant positive and negative pathways, respectively. Solid and dashed arrows indicate significant and non-significant pathways, respectively. Numbers near the arrow indicate the standardized path coefficients indicating the effect size of the relationship with \* indicating *p*< 0.05, \*\* indicating *p* < 0.01, and \*\*\* indicating *p* < 0.001. The arrow width is proportional to the strength of the relationship. *R* 2 represents the proportion of variance explained for each dependent variable. The goodness-of-fit statistics for the structural equation modeling are shown below each model. C, carbon.

#### *3.1. The Effects of N Addition and Plant Diversity on Flowering Phenology* **3. Discussion**

#### The flowering phenology is one of the more important factors determining the repro‐ *3.1. The Effects of N Addition and Plant Diversity on Flowering Phenology*

ductive success of plants because the timing of flowering represents when plants expose their reproductive organs to the changing biotic and abiotic environments [30,31]. Flow‐ ering phenology changed after N addition in our study was consistent with the results from natural grasslands [27,32]. Soil‐available N increased following N addition, which delayed the plant switches from vegetative to reproductive growth and shortened the re‐ productive duration [28], resulting in a delay in FFD and advancement in LFD. FD was positively correlated with LFD and negatively correlated with FFD, and then the FD was shortened after N addition. A previous study found that plants delayed the switches from vegetative to reproductive growth due to the stimulation of growth through enhancement in soil N availability [28], which led to lower investment in plant reproduction, resulting in a reduction in FD in the N addition treatment. Similar to the effects of N addition, plant species richness did not change FFD but advanced LFD, which resulted in a shortening in FD. The effects of plant species richness The flowering phenology is one of the more important factors determining the reproductive success of plants because the timing of flowering represents when plants expose their reproductive organs to the changing biotic and abiotic environments [30,31]. Flowering phenology changed after N addition in our study was consistent with the results from natural grasslands [27,32]. Soil-available N increased following N addition, which delayed the plant switches from vegetative to reproductive growth and shortened the reproductive duration [28], resulting in a delay in FFD and advancement in LFD. FD was positively correlated with LFD and negatively correlated with FFD, and then the FD was shortened after N addition. A previous study found that plants delayed the switches from vegetative to reproductive growth due to the stimulation of growth through enhancement in soil N availability [28], which led to lower investment in plant reproduction, resulting in a reduction in FD in the N addition treatment.

on FFD was inconsistent with the results (ranging from advancement of 1.8 d per species lost to a delay of 0.7 d per species lost; the average is 0.6 d advance) reported from the serpentine grasslands in North America [5], suggesting that the effects of plant species richness on FFD varied among plant species. Moreover, we noticed that the amplitude of changes (0.64 d) in LFD was larger than that in FFD after per species change, which re‐ vealed that LFD might be more sensitive to plant species richness. Soil‐available N in‐ creased along the plant species richness gradients (Figure S4), which delayed the plant switches from vegetative to reproductive growth and shortened reproductive duration Similar to the effects of N addition, plant species richness did not change FFD but advanced LFD, which resulted in a shortening in FD. The effects of plant species richness on FFD was inconsistent with the results (ranging from advancement of 1.8 d per species lost to a delay of 0.7 d per species lost; the average is 0.6 d advance) reported from the serpentine grasslands in North America [5], suggesting that the effects of plant species richness on FFD varied among plant species. Moreover, we noticed that the amplitude of changes (0.64 d) in LFD was larger than that in FFD after per species change, which revealed that LFD might be more sensitive to plant species richness. Soil-available N increased along the plant species richness gradients (Figure S4), which delayed the plant switches from vegetative to reproductive growth and shortened reproductive duration [28], resulting in advancement in LFD. FD was positively correlated with LFD, resulting in a shortening in FD.

#### *3.2. The Effects of N Addition and Plant Diversity on Functional Traits*

We found evidence to support our second hypothesis that increased N inputs promote light acquisition traits. Specifically, the leaf area of *M. sativa* was promoted after N addition may vary due to the increasing demand for light [33]. These results were inconsistent with that reported on the grasses and forbs from the alpine grasslands in China [6,34], which may be partly caused by the differences in plant species. *M. sativa*, legumes, can fix N using symbionts to relieve their N limitation [35], and thus N addition had no effects on the nutrient acquisition traits of *M. sativa*, which may lead to no interactions with plant species richness.

Our findings for plant species richness also support our second hypothesis that both light (SLA) and nutrient (LNC and relative abundance) acquisition traits were promoted with decreasing plant species richness. These results were inconsistent with the results reported from the grasslands in Germany [4], which may be caused by the differences in plant species. Closed canopies are characterized by pronounced gradients in spectral light quality and quantity [36]. In the present study, plant species richness impacts on morphological traits associated with light acquisition were mainly attributable to the changes in the relative height of *M. sativa*. Relative height increased along the plant species richness gradients, indicating less effort for light acquisition should be allocated by plants [37,38]. Hence, *M. sativa* exhibited low SLA in adjustment to decreasing competition for light. Moreover, nitrogen is not the limited resource of *M. sativa*. Lower light acquisition traits are accompanied by lower nutrient acquisition traits [33], resulting in a decrease in LNC along with plant species richness gradients.

#### *3.3. Intraspecific Variation in Functional Traits Determines Flowering Phenology*

Our findings did not support our third hypothesis that intraspecific variation in functional traits and alteration in abiotic factors co-drove the response of flowering phenology to N addition and plant species richness; the contributions of intraspecific variation in functional traits for changes in flowering phenology was far greater than abiotic factors (Figures 5 and S5). Specifically, the delay in FFD along the plant species richness gradients was mainly induced by an increase in soil-available N, which was consistent with the result from Wolf et al. in American serpentine grasslands [5]. Higher soil available N delayed the plant switches from vegetative to reproductive growth [28] and then led to the delay in FFD in the monocultures. However, the changes in LFD and FD were mainly driven by the intraspecific variation in LNC. Leaf nutrients could influence the strength of shifts in flowering phenology as plant performance is positively associated with phenological shifts [15,39] and the alteration in the natural selection of plants [12,40,41]. In the monocultures, lower intraspecific competition for resources and light [38] led to higher LNC and SLA and minimized light interception [42], resulting in advancing FFD, delaying LFD, and extending FD (Figure 2). As plant species richness increases, the intraspecific competition decreases, but the interspecific competition among species increases [43,44]. *M. sativa* is more conservative in resource utilization, with low SLA, LNC, and maximized light interception, and thus the "slow" growth strategy [45–47] led to advancement in LFD and shortened in FD. Therefore, the intraspecific variation in leaf traits caused the alteration in the growth strategy of *M. sativa* due to interspecific competition increased with increasing plant species richness, which resulted in changes in flowering phenology. Furthermore, the survival pressure of *M. sativa* increased due to higher interspecific competition in the mixed communities, which may cause *M. sativa* to invest more resources in reproductive growth [10], resulting in a positive relationship between FN and plant species richness.


**2. Nanotechnology in combination with PDT**

#### **2.1 Main hindrances of PDT**

There is a plethora of photosensitizing compounds available, but the majority of them did not present the requirements for clinical trials, i.e. good solubility, target selectivity, sufficient light absorption on the desired wavelength, and low accumulation in distant sites, especially the skin [1]. One of the biggest hindrances of photosensitizers is their hydrophobicity and consequent tendency to aggregate in aqueous environments, making the intravenous administration difficult unless some kind of delivery system is used [2, 3]. Besides, it is desirable that the photosensitizers accumulate preferentially in the target tissue rather than in healthy sites in order to avoid toxicity, therefore strategies of targeted delivery are often necessary to increase the therapeutic efficiency, and nanoparticle systems offer great advantages in this regard [1].

Besides the tendency to aggregate when photosensitizers are injected intravenously, they tend to be distributed to the whole body in a non-specific way, and to be taken up by plasma proteins or phagocytes, decreasing significantly the efficiency of PDT. To increase the specific delivery and avoid side effects, several carriers have been developed to take advantage of the enhanced permeation and retention (EPR) effect or to actively target tumors and enhance specific accumulation, such as polymer and metal nanoparticles, micelles and liposomes, and magnetic nanoparticles. The EPR effect is caused by the leaky vasculature common to tumor tissues, due to the sinusoid capillaries and the fenestrated endothelial cells, plus the inefficient lymphatic drainage from tumor sites. The active targeting, on the other hand, is actually a plethora of strategies to increase specific tumor accumulation of a drug or therapeutic compound [3].

Another obstacle for photodynamic therapy is the limited penetration of light, so it is used mostly for superficial tumors, or with the help of optic fibers introduced in the patient. Recently, researchers have been developing strategies to produce light inside of the body with the help of nanoparticle scintillators. These materials are able to convert external X-ray photons, which can reach deeper sites in the organism, into visible light photons that could excite a photosensitizer in a process called X-PDT. Another approach to excite photosensitizers with endogenous light is with Cherenkov radiation in a process referred as CR-PDT. Cherenkov radiation is generated when a particle exceeds the speed of light in a defined medium, and is common with the decay of several medical radioactive isotopes [4].

Photosensitizers that absorb in the NIR region, such as indocyanine green (absorption around 800 nm) and aluminum sulfophthalocyanine (absorption around 790 nm), although being able to be used in deeper regions due to the deeper penetration of NIR light, tend to be less efficient in generating singlet oxygen than other photosensitizers that absorb in lower wavelengths. Upconversion nanoparticles (UCNs) can overcome these limitations. The process where the absorption of multiple photons – usually two or three – from a given wavelength leads to the

*Nanomaterials for Enhanced Photodynamic Therapy DOI: http://dx.doi.org/10.5772/intechopen.94255*

emission of photons from a shorter wavelength is referred as photon upconversion. This can be used as a strategy to reach deeper tissues with longer wavelengths and excite photosensitizers that absorb in shorter wavelengths and would not be reachable by light otherwise [5].

UCNs usually consist in inorganic luminescent materials, usually made with lanthanide elements that absorb NIR light and emit UV-visible light that can be used to excite more efficient photosensitizers. Other than the possibility of exciting photosensitizers in deeper regions and prevent photobleaching, enhancing PDT efficacy, they can carry a plethora of hydrophobic photosensitizers, either loaded physically or chemically [6, 7].


**Author details**

Sripriya Das1 \*, Manoj Kumar Singh2 , Sneha Kumari2 and Manimala Mahato1

1 Department of Agronomy, Bidhan Chandra Krishi Viswavidyalaya, Nadia, West Bengal, India

2 Department of Agronomy, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Recent Advances in Crop Establishment Methods in Rice-Wheat Cropping System: A Review DOI: http://dx.doi.org/10.5772/intechopen.98743*