Plant Diversity and Ecological Indices of Naturally Established Native Vegetation in Permanent Grassy Strips of Fruit Orchards in Southern Romania

Abstract

This paper assesses the complexity and diversity of vegetation in grassy strips with spontaneous plants between tree rows in three fruit orchards (plum, cherry, apple) in Dolj County, Romania, using structural and biodiversity indices. It addresses the lack of data on spontaneous vegetation in Romanian orchards, supporting improved plantation management and native biodiversity conservation. The study found that grassy strips supported high wild herbaceous diversity and a complex, heterogeneous ecological structure, with the apple orchard showing the highest biodiversity. Species diversity, evaluated through species richness, evenness, and diversity indices (Shannon, Simpson, Menhinick, Gleason, etc.), showed species richness ranging from 30 species in the cherry orchard to 40 in the apple orchard. Several species, including Capsella bursa-pastoris, Geranium pusillum, Poa pratensis, Veronica hederifolia, Lolium perenne, and Convolvulus arvensis, were present in 100% of samples, making them constant species from a phytosociological perspective. Their presence indicates relatively stable plant communities in each orchard. From a phytocoenological view, an ecological plant community is defined not only by species composition but also by constancy and co-occurrence in sampling units. Dominance remained low in all orchards, indicating no single plant dominated, while evenness showed a uniform distribution of species.

1. Introduction

Agricultural intensification has led to the loss of ecological heterogeneity, consequently threatening the biodiversity of agricultural lands [1]. Fruits are an important part of a healthy diet and constitute a rich source of vitamins, minerals, and dietary fibre for humans. They account for 19% of the average global cost of a healthy human diet [2]. In recent years, the fruit industry has developed rapidly, and the area and production of orchards have increased year by year [3]. Soil management of row orchards is largely dependent on chemical herbicides and tillage, which has led to a decrease in biodiversity and soil quality, which has been shown to be detrimental to their sustainability [4]. Therefore, the pressure to identify sustainable solutions for agriculture is increasing [5]. Strategies that promote functional agrobiodiversity can enhance the ecosystem services of orchards [6]. In addition to the poor biodiversity of classical plantations, another problem is represented by pests, and a solution to these difficulties can be grass strips, which are the most implemented semi-natural habitats in agri-environmental measures [7]. They can mitigate these effects by providing resources for natural enemies, thus reducing the dependence on chemical pest control [8]. Grass strips can be excellent sources of pollen, nectar, and alternative prey for beneficial arthropods, such as generalist predators, and therefore represent a potentially ingenious and effective strategy for pest control [6,9]. Opting for natural grassing with spontaneous vegetation also brings more ecosystem services, such as increased biodiversity, protection of the soil from erosion, salinity and mechanical compaction, reduction in soil nutrient leaching, increase in organic matter content in the soil, and landscape and ornamental functions. Thus, botanical diversity supports the efficient performance of ecosystem services by weed communities in arable, horticultural, and industrial crops [10], with spontaneous flora thus becoming a source of plants with decorative qualities and some particular agri-biological characteristics, such as ecological plasticity, high resistance, etc. [11]. Due to their diverse adaptive strategies and strong self-organization capacity, these species can offer cost-effective approaches to supporting ecosystem rehabilitation, as they can provide ecosystem services distinct from those offered by cultivated plants [12]. Biodiversity loss is the process by which species are lost from local assemblages due to changes in ecological parameters. These changes can be sudden, such as droughts, fires, floods, and storms, or sustained, such as nutrient eutrophication, climate change, and land-use change [13]. Disturbances have an overall impact on plant community abundance, diversity, and structure [14]. Patterns of functional diversity are increasingly studied aspects of biodiversity that can influence how communities affect and are affected by the environment [15]. Plant communities can play a major role in shaping other soil life communities through root structure, as well as litter inputs and microclimate effects [16]. The stability of ecological communities is essential for the consistent provision of ecosystem services, and understanding the mechanisms that maintain this stability is essential. Most mechanisms of biodiversity stability at individual trophic levels involve some form of compensatory dynamics, which occur when year-to-year temporal fluctuations in the abundance of some species are offset by fluctuations in other species [17]. Species diversity is one of the most measured quantities in ecology, but how it is measured is complex and sometimes controversial [18]. The use of functional diversity analyses in ecology has grown exponentially over the past two decades, broadening our understanding of biological diversity and its change over space and time [19]. There are now a significant number of indices and models for measuring diversity [20]. These ecological indicators provide key insights into the health and sustainability of an ecosystem [21]. Biodiversity indices differ in their sensitivity to the number and evenness of species abundance [22]. Such studies play an important role in expressing quantitative relationships between species, thus clarifying the role of each [23], but above all, they provide essential clues about the functionality and role of ecosystem structure [24,25].

Previous case studies on plant communities in orchard grassy strips have shown patterns in species composition and the effects of management intensity on biodiversity [7,26]. However, gaps remain regarding the consistency of these patterns across orchard types and their implications for ecosystem services in temperate fruit systems. Modern fruit-growing systems face challenges related to sustainability and the integration of agroecological practices [27], and grassy strips with spontaneous vegetation are gaining importance for their multiple benefits [28]. While numerous international studies have addressed these vegetative strips [10,29,30,31,32], research in Romania remains scarce and fragmented [33,34]. Based on these gaps, this study investigates the structure and species composition of plant communities in grassy strips of orchards in southern Romania and examines how plant diversity relates to structural attributes of these semi-natural habitats under agri-environmental measures.

The aim of the present work was to evaluate the plant communities in the grassy strips of fruit plantations in southern Romania using structural and biodiversity indices in order to understand the role and importance of interspecific and structural relationships of the semi-natural habitats constituted by the vegetal carpet in fruit tree orchards where these agri-environmental measures are used. Orchards in Romania represent a unique study system due to the diversity of fruit species and local management practices. The grassy strips within these orchards are important semi-natural habitats that support biodiversity and ecological balance in regional agriculture [33,35].

2. Materials and Methods

2.1. Study Area

The research area consisted of three plantations (plum, cherry, and apple) located in the Caraula commune of Dolj county, Romania. The climate of the area is temperate continental with an average annual temperature of 10.9 °C, with the minimum temperatures usually recorded in January and the maximum in July. Regarding the rainfall regime, the average annual amount of precipitation is 530 mm [33]. The dominant winds are from the northwest and northeast. The surface of the land is approximately horizontal, the soil is well drained, and the depth of the groundwater is >10 m. Currently, the orchard surface has a grassing system on the strips between the rows of trees, with spontaneous vegetation. The analyzed area features a reddish preluvosol with predominantly clay-loam texture in the Bt1 and Bt2 horizons (clay content over 45%) and balanced loam in the upper Ao horizon. Soil reaction ranges from slightly acidic to slightly alkaline, with the hygroscopic coefficient increasing with depth. High humus and total nitrogen contents were recorded in the surface layer, while mobile phosphorus and potassium decreased with depth. Total cation exchange capacity and base saturation indicate high fertility, but careful management is needed to avoid nutrient imbalances and soil compaction [35].

The plum orchard is 13 years old, with trees planted at 5 × 3 m, reaching an average height of 2.5 m and having a vase-shaped canopy, while the grassed strips between the rows are approximately 3.5 m wide. The cherry orchard is 11 years old, with trees planted at 4 × 1.8 m, reaching a height of 3.5 m with a thin, spindle-shaped canopy, while the grassed strips between the rows are approximately 3 m wide. The apple orchard was established 20 years ago, with trees planted at 3.5 × 1.5 m, featuring tiered palmette canopies and an average height of 3 m, while the grassed strips between the rows are approximately 2.5 m wide. All three conventionally managed orchards have untreated grassed strips with spontaneous herbaceous vegetation, mowed mechanically once a year without restoration. The surrounding landscape, mainly cereal crops with semi-natural meadows and ruderal vegetation, may provide propagules. The orchards are located about 1 km apart.

2.2. Data Collection

Data collection was carried out using the random sampling method (the squares were randomly placed inside the strips, ensuring balanced spatial coverage of each plantation) with square frames [23] in April 2025, with each sample having an area of 1 m² [36], following the grassy strips between the rows of trees. Ten samples were established for each fruit plantation (plum, cherry, apple), and 1 m² squares were used, as this size is suitable for assessing vegetation and small species. The compact size allows for accurate capture of floristic composition, frequency, and specific cover, including rare or dispersed ones. Each sample was placed at a minimum distance of approximately 50 m from the others. This approach aimed to ensure spatial independence of the sampling points and reduce the risk of ecological autocorrelation. The width of the strips varied depending on the species: 3.5 m in the plum plantation, 3 m in the cherry, and 2.5 m in the apple, which also influenced the sampling density. Thus, for an average length of the strips of 300 m, the areas available for sampling were approximately 1050 m² (plum), 900 m² (cherry), and 750 m² (apple), resulting in a sampling density of 1 square per 105 m², 90 m², and 75 m², respectively. The data were collected in a single period, which may constitute a methodological limitation, as some annual species with late phenology may not have yet emerged. Nevertheless, the study provides relevant information for understanding the composition and structure of vegetation in Romanian fruit plantations, a subject insufficiently documented in the local literature.

Plant species were identified taxonomically based on morphological characteristics, with the help of scientific reference works [37,38] for the vascular flora of Romania and with the help of the Euro+Med database [39]. For each sampling unit, the presence and abundance of species were recorded. In the case of clonal species, individuals were considered ramets and were counted only if they exhibited visible separation (e.g., distinct, rooted stems). Based on these data, absolute density and species richness were calculated. For each taxon, the biological type (annual or perennial) and invasive potential were noted.

2.3. Structural Indices of the Community

To describe the structure and ecological role of species in the grasslands, several phytosociological and structural indices recognized in the literature were calculated. These include mean abundance (X), standard deviation (SD), confidence limits (LCs), percentage density (DP), frequency (F), constancy class (C), ecological significance index (W–Dzuba index), and dominance index (ID). The definitions and calculation formulas for each index are presented in Table 1, together with the corresponding theoretical sources. This methodological approach strengthens the interpretative value of the data on the studied vegetation.

Table 1. Structural indices.

Index	Formula	Observations	Source
Absolute density	$\mathrm{D}\mathrm{A}={\displaystyle \frac{\mathrm{n}\mathrm{i}}{\mathrm{A}}}$	ni = number of individuals of species i; A = total sampled area.	[40]
Percentual density	$\mathrm{D}\mathrm{P}={\displaystyle \frac{\mathrm{D}\mathrm{i}}{\sum \mathrm{D}}}\times 100$	Di = the absolute density of species i; ∑D = the sum of the densities of all species in the studied community.	[40]
Frequency	$\mathrm{F}={\displaystyle \frac{\mathrm{p}\mathrm{i}}{\mathrm{P}}}\times 100$	pi = the number of samples in which species i is found; P = the total number of samples analyzed.	[41]
Constance	it depends on F	species with F ≥ 50% are constant species; species with F = 25–50% are accessory species; and species with F < 25% are accidental species.	[42]
Dzuba’s index	$\mathrm{W}={\displaystyle \frac{\mathrm{A}\times \mathrm{F}}{100}}$	A = abundance; F = frequency.	[43]
Dominance index	$\mathrm{I}\mathrm{D}={\displaystyle \frac{\mathrm{D}1+\mathrm{D}2}{\mathrm{D}}}\times 100$	D1 = the numerical density (the total number of individuals of a species divided by the total number of sampling units used) of the most numerous species; D2 = the numerical density of the secondary species; D = total density of all species in the community.	[44]

Table 1. Structural indices.

Index	Formula	Observations	Source
Absolute density	$\mathrm{D}\mathrm{A}={\displaystyle \frac{\mathrm{n}\mathrm{i}}{\mathrm{A}}}$	ni = number of individuals of species i; A = total sampled area.	[40]
Percentual density	$\mathrm{D}\mathrm{P}={\displaystyle \frac{\mathrm{D}\mathrm{i}}{\sum \mathrm{D}}}\times 100$	Di = the absolute density of species i; ∑D = the sum of the densities of all species in the studied community.	[40]
Frequency	$\mathrm{F}={\displaystyle \frac{\mathrm{p}\mathrm{i}}{\mathrm{P}}}\times 100$	pi = the number of samples in which species i is found; P = the total number of samples analyzed.	[41]
Constance	it depends on F	species with F ≥ 50% are constant species; species with F = 25–50% are accessory species; and species with F < 25% are accidental species.	[42]
Dzuba’s index	$\mathrm{W}={\displaystyle \frac{\mathrm{A}\times \mathrm{F}}{100}}$	A = abundance; F = frequency.	[43]
Dominance index	$\mathrm{I}\mathrm{D}={\displaystyle \frac{\mathrm{D}1+\mathrm{D}2}{\mathrm{D}}}\times 100$	D1 = the numerical density (the total number of individuals of a species divided by the total number of sampling units used) of the most numerous species; D2 = the numerical density of the secondary species; D = total density of all species in the community.	[44]

2.4. Biodiversity Indices

Biodiversity indices (Table 2) followed-up were Simpson dominance (D), Simpson diversity (1 − D), Shannon–Wiener index (H′), Pielou index (E), maximum entropy (H_max), Menhinick index (D_Mn), Gleason index (G), McIntosh index (U), and Margalef index (D_Mg).

Table 2. Biodiversity indices.

Index	Formula	Observations	Source
Simpson dominance	$\mathrm{D}=\sum {\displaystyle \frac{\mathrm{n}\mathrm{i}(\mathrm{n}\mathrm{i}-1)}{\mathrm{N}(\mathrm{N}-1)}}$	ni = number of individuals of species i; S = number of species.	[45]
Simpson diversity	1 − D	D = Simpson dominance.	[46]
Shannon–Wiener index	${\mathrm{H}}^{\prime }=-\sum _{\mathrm{i}=1}^{\mathrm{s}}{\displaystyle \frac{\mathrm{n}\mathrm{i}}{\mathrm{n}}}\mathrm{l}\mathrm{o}\mathrm{g}{\displaystyle \frac{\mathrm{n}\mathrm{i}}{\mathrm{n}}}$	s = total number of species; ni = number of individuals of species i; n = total number of individuals in the sample analyzed.	[47]
Pielou index	$\mathrm{E}={\displaystyle \frac{{\mathrm{H}}^{\prime }}{\log \mathrm{S}}}$	H′ = Shannon–Wiener function; S = number of species.	[48]
Maximum entropy	Hmax = log(S)	S = total number of species in the community.	[49]
Menhinick index	${\mathrm{D}}_{\mathrm{M}\mathrm{n}}={\displaystyle \frac{\mathrm{S}}{\sqrt{\mathrm{N}}}}$	S = number of species; N = total number of individuals in the population.	[50]
Gleason index	$\mathrm{G}={\displaystyle \frac{\mathrm{S}}{\ln \mathrm{N}}}$	S = number of species; N = total number of individuals in the population.	[51]
McIntosh index	$\mathrm{U}=\sqrt{{\displaystyle \sum _{\mathrm{i}=1}^{\mathrm{S}}}{\mathrm{n}\mathrm{i}}^2}$	ni = number of individuals of species i; S = number of species.	[52]
Margalef index	${\mathrm{D}}_{\mathrm{M}\mathrm{g}}={\displaystyle \frac{\mathrm{S}-1}{\ln \mathrm{N}}}$	S = number of species; N = total number of individuals in the population.	[53]

Table 2. Biodiversity indices.

Index	Formula	Observations	Source
Simpson dominance	$\mathrm{D}=\sum {\displaystyle \frac{\mathrm{n}\mathrm{i}(\mathrm{n}\mathrm{i}-1)}{\mathrm{N}(\mathrm{N}-1)}}$	ni = number of individuals of species i; S = number of species.	[45]
Simpson diversity	1 − D	D = Simpson dominance.	[46]
Shannon–Wiener index	${\mathrm{H}}^{\prime }=-\sum _{\mathrm{i}=1}^{\mathrm{s}}{\displaystyle \frac{\mathrm{n}\mathrm{i}}{\mathrm{n}}}\mathrm{l}\mathrm{o}\mathrm{g}{\displaystyle \frac{\mathrm{n}\mathrm{i}}{\mathrm{n}}}$	s = total number of species; ni = number of individuals of species i; n = total number of individuals in the sample analyzed.	[47]
Pielou index	$\mathrm{E}={\displaystyle \frac{{\mathrm{H}}^{\prime }}{\log \mathrm{S}}}$	H′ = Shannon–Wiener function; S = number of species.	[48]
Maximum entropy	Hmax = log(S)	S = total number of species in the community.	[49]
Menhinick index	${\mathrm{D}}_{\mathrm{M}\mathrm{n}}={\displaystyle \frac{\mathrm{S}}{\sqrt{\mathrm{N}}}}$	S = number of species; N = total number of individuals in the population.	[50]
Gleason index	$\mathrm{G}={\displaystyle \frac{\mathrm{S}}{\ln \mathrm{N}}}$	S = number of species; N = total number of individuals in the population.	[51]
McIntosh index	$\mathrm{U}=\sqrt{{\displaystyle \sum _{\mathrm{i}=1}^{\mathrm{S}}}{\mathrm{n}\mathrm{i}}^2}$	ni = number of individuals of species i; S = number of species.	[52]
Margalef index	${\mathrm{D}}_{\mathrm{M}\mathrm{g}}={\displaystyle \frac{\mathrm{S}-1}{\ln \mathrm{N}}}$	S = number of species; N = total number of individuals in the population.	[53]

2.5. Statistical Analysis

The structural composition of the herbaceous vegetation in the strips between the tree rows of three types of fruit orchards was assessed by recording the number of individuals per species within each 1 m² sample. Based on these data, several structural and ecological indices were calculated, including mean abundance, standard deviation, confidence intervals, percentage density, frequency, constancy class, ecological significance index (Dzuba’s index), and dominance index. The data were organized according to orchard type and species, and the average values of each index were calculated at the orchard level. Statistical analyses were performed using Microsoft Excel 2010 and SPSS Trial Version 26.0 (SPSS Inc., Chicago, IL, USA). One-way ANOVA tests followed by Duncan’s post hoc tests for multiple comparisons were applied to compare differences among orchard types, with statistical significance set at p < 0.05. The relationships between the herbaceous vegetation structure and orchard types were evaluated using canonical correspondence analysis (CCA) performed with the PAST software v4.03.

3. Results and Discussions

3.1. Analysis of Structural Indices

To understand the organization, diversity, and stability of communities, their structure provides essential clues on the functionality and role in the ecosystem in which they are located [40]. Following the analysis of the structural indices of the community for the plum plantation (

Table 3. Analysis of structural indices of the community for the plum plantation.

No.	Species	X	SD	LC	DP	F	C	W	ID	Lifespan	Invasivity
1.	Capsella bursa-pastoris	44.80	42.37	26.6	19.80	100.00	Constant	19.80	33.59	Annual–biennial	Non-invasive
2.	Poa angustifolia	34.60	57.42	35.59	15.29	30.00	Accessory	4.59		Perennial	Non-invasive
3.	Veronica hederifolia	28.20	21.71	13.46	12.46	90.00	Constant	11.22		Annual	Non-invasive
4.	Geranium pusillum	22.10	18.79	11.64	9.77	100.00	Constant	9.77		Annual	Non-invasive
5.	Poa pratensis	15.80	44.80	27.77	6.98	30.00	Accessory	2.09		Perennial	Non-invasive
6.	Lamium amplexicaule	11.80	9.82	6.09	5.21	70.00	Constant	3.65		Annual	Non-invasive
7.	Setaria pumila	9.00	14.39	8.92	3.98	40.00	Accessory	1.59		Annual	Non-invasive
8.	Lepidium draba	6.80	10.58	6.56	3.00	40.00	Accessory	1.20		Perennial	Non-invasive
9.	Lamium purpureum	6.80	12.88	7.98	3.00	60.00	Constant	1.80		Annual	Non-invasive
10.	Rorippa austriaca	6.10	11.72	7.27	2.70	30.00	Accessory	0.81		Perennial	Non-invasive
11.	Senecio leucanthemifolius subsp. vernalis	5.80	3.79	2.35	2.56	90.00	Constant	2.31		Annual	Non-invasive
12.	Bromus hordeaceus	5.40	11.67	7.24	2.39	30.00	Accessory	0.72		Annual–biennial	Non-invasive
13.	Trifolium arvense	4.10	12.97	8.04	1.81	10.00	Accidental	0.18		Annual	Non-invasive
14.	Convolvulus arvensis	3.40	4.30	2.67	5.48	50.00	Constant	2.74		Perennial	Non-invasive
15.	Achillea setacea	3.20	10.12	6.27	1.41	10.00	Accidental	0.14		Perennial	Non-invasive
16.	Veronica polita	3.10	9.80	6.08	1.37	10.00	Accidental	0.14		Annual	Non-invasive
17.	Ornithogalum umbellatum	2.80	4.54	2.81	1.24	60.00	Constant	0.74		Perennial	Non-invasive
18.	Taraxacum officinale	2.30	3.77	2.34	1.02	40.00	Accessory	0.41		Perennial	Non-invasive
19.	Filago arvensis	1.60	4.38	2.71	0.71	30.00	Accessory	0.21		Annual	Non-invasive
20.	Rumex crispus	1.40	2.46	1.52	0.62	30.00	Accessory	0.19		Perennial	Non-invasive
21.	Rubus caesius	1.10	1.60	0.99	0.49	50.00	Constant	0.24		Perennial	Non-invasive
22.	Lathyrus pratensis	0.90	1.10	0.68	0.40	50.00	Constant	0.20		Perennial	Non-invasive
23.	Vicia sepium	0.90	2.51	1.56	0.40	20.00	Accidental	0.08		Perennial	Non-invasive
24.	Arenaria serpyllifolia	0.80	1.87	1.16	0.35	30.00	Accessory	0.11		Annual	Non-invasive
25.	Stellaria media	0.80	1.62	1.00	0.35	30.00	Accessory	0.11		Annual	Non-invasive
26.	Calepina irregularis	0.50	1.58	0.98	0.22	10.00	Accidental	0.02		Annual–biennial	Non-invasive
27.	Hypericum perforatum	0.40	1.26	0.78	0.18	10.00	Accidental	0.02		Perennial	Non-invasive
28.	Alopecurus pratensis	0.30	0.67	0.42	0.13	20.00	Accidental	0.03		Perennial	Non-invasive
29.	Potentilla argentea	0.30	0.95	0.59	0.13	10.00	Accidental	0.01		Perennial	Non-invasive
30.	Sonchus arvensis	0.30	0.67	0.42	0.61	20.00	Accidental	0.12		Perennial	Non-invasive
31.	Ornithogalum boucheanum	0.20	0.63	0.39	0.09	10.00	Accidental	0.01		Perennial	Non-invasive
32.	Tragopogon pratensis subsp. orientalis	0.20	0.63	0.39	0.09	10.00	Accidental	0.01		Biennial–perennial	Non-invasive
33.	Carduus acanthoides	0.10	0.32	0.20	0.04	10.00	Accidental	0.01		Perennial	Non-invasive
34.	Centaurea sp.	0.10	0.32	0.20	0.04	10.00	Accidental	0.01		Perennial	Non-invasive
35.	Festuca valesiaca	0.10	0.32	0.20	0.04	10.00	Accidental	0.01		Perennial	Non-invasive
36.	Veronica arvensis	0.10	0.32	0.20	0.04	10.00	Accidental	0.01		Annual	Non-invasive
37.	Xeranthemum cylindraceum	0.10	0.32	0.20	0.04	10.00	Accidental	0.01		Annual	Non-invasive

Note: X = arithmetic mean of individuals; SD = standard deviation; LC = confidentiality limit; DP = percentage density; F = frequency; C = constancy; W = index of relative significance; ID = dominance index.

), it was found that of the thirty-seven identified species, only two recorded a maximum frequency (F), namely Capsella bursa-pastoris and Geranium pusillum, with these being the only species present in all the samples studied within this plantation. However, from a quantitative point of view, it was observed that the most representative species were C. bursa-pastoris and P. angustifolia, with these having an average (X) of 44.80 individuals per sample and 34.60 individuals per sample, respectively. In the case of the species P. angustifolia, the average (X = 43.60 individuals) and the percentage density (DP = 15.29%) were increased, but the frequency took a rather low value (30%) compared to other species from the same plantation, such as Veronica hederifolia or Senecio leucanthemifolius subsp. vernalis, which indicates that the distribution of this species was not uniform, with a high number of individuals in a small number of samples. A similar case was present for another species of the genus Poa, namely P. pratensis, where the average was 15.80 individuals, the percentage density was 6.98%, and the frequency was 30%, with this representing one of the accessory species. Regarding constancy (C), a total of 10 constant species, 11 accessory species, and 16 accidental species were identified. The relative significance index (W) presented the highest value in the case of the species C. bursa-pastoris (W = 19.80%), with this species influencing the community the most, and the dominance (ID) was given by C. bursa-pastoris together with Poa angustifolia, with a value of 33.59%. Although the species C. bursa-pastoris had the highest values for the mean and percentage density, in terms of confidence limits (LCs) and standard deviation (SD), the maximum value was reached within the species P. angustifolia (LC = 35.59 and SD = 57.42). The consistent presence of the species C. bursa-pastoris is due to its high adaptability to different habitats; thus, it is an annual plant of the Brassicaceae family that presents a considerable variety of habitat forms [54,55]. It prefers well-drained, fertile and poorly fertile, slightly alkaline, and sunny soils, being frequently found in human-made habitats [56]. The study by Rayia et al. [56] suggests that C. bursa-pastoris is usually found in plant associations with species belonging to families such as Brassicaceae, Poaceae, Chenopodiaceae, and Fabaceae, as was also observed in the case of the plum plantation. And Ahmed et al. [57] stated that it is usually found in gardens, orchards, vineyards, pastures, meadows, and beaches in association with species such as Stellaria media, Lamium amplexicaule, Polygonum aviculare, Ochlopoa annua, or Lolium perenne.

Based on the above, the analysis of interspecific and structural relationships of semi-natural habitats formed by the vegetation cover of plum orchards managed through agri-environmental measures highlights the essential role of plant diversity in maintaining the ecological balance and functionality of the agricultural ecosystem. The constant presence and dominance of species such as Capsella bursa-pastoris and Poa angustifolia reflect their ability to adapt to anthropogenic conditions and their significant influence on the structure of the plant community. Also, the uneven distribution of some species, the variability of frequency, and the presence of a high number of accessory and accidental species indicate a high degree of ecological heterogeneity, favourable to the maintenance of biodiversity. Thus, the vegetal carpet in fruit tree orchards, supported by agri-environmental measures, not only contributes to ecological stability but also provides a conducive framework for complex biological interactions, essential for the conservation of natural resources and the sustainability of agroecosystems.

The analysis of the lifespan of species in plum plantations shows a better representation of perennial species. This can be explained by the greater row spacing in this case and the lower soil shading.

For the cherry plantation, from the structural index analysis (

Table 4. Analysis of structural indices of the community for the cherry plantation.

No.	Species	X	SD	LC	DP	F	C	W	ID	Lifespan	Invasivity
1.	Poa pratensis	28.40	19.04	11.80	30.41	100.00	Constant	30.41	40.90	Perennial	Non-invasive
2.	Trifolium repens	9.80	22.24	13.78	10.49	30.00	Accessory	3.15		Perennial	Non-invasive
3.	Medicago minima	9.60	13.07	8.10	10.28	70.00	Constant	7.19		Perennial	Non-invasive
4.	Veronica arvensis	8.70	10.03	6.22	9.31	80.00	Constant	7.45		Annual	Non-invasive
5.	Veronica polita	7.50	11.62	7.20	8.03	60.00	Constant	4.82		Annual	Non-invasive
6.	Veronica hederifolia	5.40	7.23	4.48	5.78	60.00	Constant	3.47		Annual	Non-invasive
7.	Stellaria media	4.40	3.84	2.38	4.71	80.00	Constant	3.77		Annual	Non-invasive
8.	Arenaria serpyllifolia	3.60	10.37	6.43	3.85	20.00	Accidental	0.77		Annual	Non-invasive
9.	Lathyrus pratensis	3.40	5.80	3.59	3.64	50.00	Constant	1.82		Perennial	Non-invasive
10.	Geranium pusillum	1.70	3.30	2.05	1.82	40.00	Accessory	0.73		Annual	Non-invasive
11.	Senecio leucanthemifolius subsp. vernalis	1.50	4.06	2.52	1.61	30.00	Accessory	0.48		Annual	Non-invasive
12.	Capsella bursa-pastoris	1.20	2.30	1.43	1.28	30.00	Accessory	0.39		Annual–biennial	Non-invasive
13.	Vicia sepium	1.20	1.55	0.96	1.28	60.00	Constant	0.77		Perennial	Non-invasive
14.	Convolvulus arvensis	0.80	1.48	0.91	0.86	30.00	Accessory	0.26		Perennial	Non-invasive
15.	Euphorbia esula subsp. tommasiniana	0.80	2.53	1.57	0.86	10.00	Accidental	0.09		Perennial	Non-invasive
16.	Lamium purpureum	0.80	0.92	0.57	0.86	50.00	Constant	0.43		Annual	Non-invasive
17.	Nonea pulla	0.80	2.53	1.57	0.86	10.00	Accidental	0.09		Perennial	Non-invasive
18.	Lamium amplexicaule	0.70	2.21	1.37	0.75	10.00	Accidental	0.07		Annual	Non-invasive
19.	Setaria pumila	0.60	1.35	0.84	0.64	20.00	Accidental	0.13		Annual	Non-invasive
20.	Taraxacum officinale	0.60	0.84	0.52	0.64	40.00	Accessory	0.26		Perennial	Non-invasive
21.	Daucus carota	0.50	0.85	0.53	0.54	30.00	Accessory	0.16		Annual	Non-invasive
22.	Rubus caesius	0.50	1.08	0.67	0.54	20.00	Accidental	0.11		Perennial	Non-invasive
23.	Cichorium intybus	0.20	0.63	0.39	0.21	10.00	Accidental	0.02		Perennial	Non-invasive
24.	Carduus acanthoides	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Biennial	Non-invasive
25.	Euphorbia cyparissias	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Perennial	Non-invasive
26.	Filago arvensis	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Annual	Non-invasive
27.	Geranium dissectum	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Annual	Non-invasive
28.	Rorippa austriaca	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Perennial	Non-invasive
29.	Sonchus arvensis	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Perennial	Non-invasive
30.	Vicia villosa	0.10	0.32	0.20	0.11	10.00	Accidental	0.01		Annual–Biennial	Non-invasive

Note: X = arithmetic mean of individuals; SD = standard deviation; LC = confidentiality limit; DP = percentage density; F = frequency; C = constancy; W = index of relative significance; ID = dominance index.

), it was found that there is only one species with a frequency of 100%, namely P. pratensis, which also has the highest value in terms of average and percentage density (X = 28.40 individuals and DP = 30.41%). The species is part of the Poaceae family and presents increased ecological adaptability, representing a grass resistant to stress, drought, and climate change [58], and it is frequently used in fodder, presenting resistance to grazing and mowing [59]. Other species, such as Veronica arvensis (F = 80%), Stellaria media (F = 80%), or Medicago minima (F = 70%), also showed increased frequencies, but they had a somewhat lower percentage density of 9.31%, 4.71%, and 10.28%, respectively. Thus, they were identified in a high number of samples but were represented within them by a small number of individuals. Of the total of thirty herbaceous species identified in the sector planted with cherry, nine species were constant, seven were accessories, and fourteen species were accidental. The highest ecological impact within the community was also given by P. pratensis (W = 30.41%), and the dominance was determined between P. pratensis and Trifolium repens (ID = 40.90%). Regarding the species T. repens, even though it is ranked second according to the average value (X = 9.80 individuals) and percentage density (DP = 10.49%), its frequency is quite low (F = 30%), representing one of the identified accessory species, which suggests an uneven distribution within the habitat. Based on the above, it appears that the interspecific relationships and the structure of the plant community in the cherry orchard managed through agri-environmental measures highlight the importance of semi-natural habitats in maintaining biodiversity and ecosystem stability. The dominance and adaptability of the species Poa pratensis, together with the presence of species with high frequencies but low densities, reflect a balanced plant structure, essential for the resilience of the agri-ecosystem and the support of ecological services in the long term. Regarding the share of annual and perennial species, this is a fair one.

Following the data collection from the apple orchard (

Table 5. Analysis of structural indices of the community for the apple plantation.

No.	Species	X	SD	LC	DP	F	C	W	ID	Lifespan	Invasivity
1.	Veronica hederifolia	11.50	10.07	6.24	11.33	100.00	Constant	11.33	21.87	Annual	Non-invasive
2.	Lepidium draba	10.70	18.32	11.35	10.54	60.00	Constant	6.33		Perennial	Non-invasive
3.	Lolium perenne	9.60	9.95	6.16	9.46	100.00	Constant	9.46		Perennial	Non-invasive
4.	Convolvulus arvensis	8.40	6.92	4.29	8.28	100.00	Constant	8.28		Perennial	Non-invasive
5.	Polygonum aviculare	6.80	8.42	5.22	6.70	70.00	Constant	4.69		Annual	Non-invasive
6.	Artemisia absinthium	5.20	16.44	10.19	5.12	10.00	Accidental	0.51		Perennial	Non-invasive
7.	Capsella bursa-pastoris	4.50	4.58	2.84	4.43	100.00	Constant	4.43		Annual–biennial	Non-invasive
8.	Verbena officinalis	4.30	13.60	8.43	4.24	10.00	Accidental	0.42		Annual–perennial	Non-invasive
9.	Rumex crispus	4.20	3.61	2.24	4.14	90.00	Constant	3.72		Perennial	Non-invasive
10.	Medicago arabica	3.70	11.70	7.25	3.65	10.00	Accidental	0.36		Annual	Non-invasive
11.	Senecio leucanthemifolius subsp. vernalis	3.50	5.52	3.42	3.45	90.00	Constant	3.10		Annual	Non-invasive
12.	Sonchus arvensis	3.30	5.40	3.34	3.25	60.00	Constant	1.95		Perennial	Non-invasive
13.	Bromus hordeaceus	2.90	4.25	2.64	2.86	50.00	Constant	1.43		Annual–biennial	Non-invasive
14.	Senecio leucanthemifolius subsp. vulgaris	2.60	3.78	2.34	2.56	70.00	Constant	1.79		Annual	Non-invasive
15.	Medicago minima	2.40	5.25	3.26	2.36	40.00	Accessory	0.95		Annual	Non-invasive
16.	Stellaria media	2.20	2.04	1.27	2.17	80.00	Constant	1.73		Annual	Non-invasive
17.	Taraxacum officinale	2.20	1.62	1.00	2.17	90.00	Constant	1.95		Perennial	Non-invasive
18.	Chenopodium album	2.00	4.14	2.56	1.97	30.00	Accessory	0.59		Annual	Non-invasive
19.	Veronica polita	2.00	2.11	1.31	1.97	70.00	Constant	1.38		Annual	Non-invasive
20.	Cirsium arvense	1.50	1.35	0.84	1.48	60.00	Constant	0.89		Perennial	Non-invasive
21.	Rubus caesius	1.20	2.20	1.36	1.18	40.00	Accessory	0.47		Perennial	Non-invasive
22.	Ochlopoa annua	1.00	1.76	1.09	0.99	30.00	Accessory	0.30		Annual	Non-invasive
23.	Plantago major	0.90	1.20	0.74	0.89	40.00	Accessory	0.35		Perennial	Non-invasive
24.	Geranium dissectum	0.80	2.20	1.36	0.79	20.00	Accidental	0.16		Annual	Non-invasive
25.	Poa pratensis	0.70	1.64	1.01	0.69	20.00	Accidental	0.14		Perennial	Non-invasive
26.	Trifolium repens	0.50	1.08	0.67	0.49	20.00	Accidental	0.10		Perennial	Non-invasive
27.	Daucus carota	0.40	0.70	0.43	0.39	30.00	Accessory	0.12		Annual	Non-invasive
28.	Galium aparine	0.40	0.97	0.60	0.39	20.00	Accidental	0.08		Annual	Non-invasive
29.	Carex divulsa	0.30	0.67	0.42	0.30	20.00	Accidental	0.06		Perennial	Non-invasive
30.	Geranium pusillum	0.30	0.67	0.42	0.30	20.00	Accidental	0.06		Annual	Non-invasive
31.	Vicia hirsuta	0.30	0.95	0.59	0.30	10.00	Accidental	0.03		Annual	Non-invasive
32.	Veronica persica	0.20	0.63	0.39	0.20	10.00	Accidental	0.02		Annual	Non-invasive
33.	Vicia grandiflora	0.20	0.42	0.26	0.20	20.00	Accidental	0.04		Annual	Non-invasive
34.	Vicia sepium	0.20	0.63	0.39	0.20	10.00	Accidental	0.02		Perennial	Non-invasive
35.	Amaranthus powellii	0.10	0.32	0.20	0.10	10.00	Accidental	0.01		Annual	Invasive
36.	Carduus acanthoides	0.10	0.32	0.20	0.10	10.00	Accidental	0.01		Perennial	Non-invasive
37.	Cerastium glomeratum	0.10	0.32	0.20	0.10	10.00	Accidental	0.01		Annual	Non-invasive
38.	Lathyrus tuberosus	0.10	0.32	0.20	0.10	10.00	Accidental	0.01		Perennial	Non-invasive
39.	Malva sylvestris	0.10	0.32	0.20	0.10	10.00	Accidental	0.01		Biennial–perennial	Non-invasive
40.	Tripleurospermum inodorum	0.10	0.32	0.20	0.10	10.00	Accidental	0.01		Annual–biennial	Non-invasive

Note: X = arithmetic mean of individuals; SD = standard deviation; LC = confidentiality limit; DP = percentage density; F = frequency; C = constancy; W = index of relative significance; ID = dominance index.

), the largest number of herbaceous species was identified in the three analysed areas, namely 40 species. Of these, four species recorded a frequency of 100% (V. hederifolia, Lolium perenne, Convolvulus arvensis, and C. bursa-pastoris). The species V. hederifolia recorded the highest values for the average of individuals (X = 11.50) and the percentage density (DP = 11.33), followed by Lepidium draba, a species that although had a value of the average of individuals of 10.70 and a percentage density of 10.54%, quite close to the previous species, had a very low frequency compared to it, of only 60%, but representing one of the constant species. The relative significance index reached the maximum value this time in the case of the species V. hederifolia (W = 11.33%), and together with L. draba, they recorded a dominance of 21.87% over the plant community. Compared to the other two plantations, the number of constant species was the highest, namely 15 species, as was the case with the accidental ones, which were 19 species. On the other hand, the number of accessory species took the lowest value this time, being represented by only six species. It is worth noting the constant presence of species from the genus Veronica in all three locations, their significant number, and also the increased frequency with which they presented; thus, the species of this genus show increased adaptability, being considered invasive species in some regions of the globe [60,61,62]. These species have a high germination capacity, possible in both light and dark conditions, which has a special competitive effectiveness [63]. The vegetation cover in the apple orchard, managed through agri-environmental measures, highlights the importance of interspecific and structural relationships in maintaining the diversity and stability of semi-natural habitats. The large number of species identified, together with the high frequency of adaptable plants such as Veronica hederifolia or Capsella bursa-pastoris, reflects a complex and well-balanced plant community. These relationships contribute to the sustainable functioning of the agri-ecosystem, supporting its resilience to stress factors and promoting essential ecological services.

Analyzing the lifespan of the plants identified in the apple orchards, a slightly higher weight is noted in the case of annual species. It can be said that in the three types of orchards, there is an equity in terms of annual and perennial species. Biennial species have a very low representation. In the understanding of Richardson et al. [64] regarding the terminology recommended in the ecology of plant invasions, the analyzed species fall at most under “Weeds”. If we compare the most recent studies on invasive and potentially invasive species in Romania [65], we can see that only Amaranthus powellii is present in the plantations studied, and the rest of the species are native. From the analysis of the invasive potential of certain identified native taxa in the field, we can say that in plum plantations, there are no species with invasive potential; in cherry plantations, we more frequently encounter Veronica hederifolia, Geranium pusillum, or Lolium perenne, and in apple plantations, Lepidium draba and Lolium perenne.

3.2. Analysis of the Biodiversity Indices

The analysis of the biodiversity indices for the herbaceous vegetation in the grassy strips of the three plantations (

Table 6. Analysis of the biodiversity indices for the plants in the three plantations.

Plantation	D	1 − D	H′	E	Hmax	DMn	G	U	DMg
Plum	0.22 ± 0.07 ab	0.78 ± 0.07 ab	0.81 ± 0.11 b	0.74 ± 0.07 a	1.09 ± 0.10 b	0.88 ± 0.23 b	2.38 ± 0.51 b	106.47 ± 49.69 a	3.13 ± 1.27 a
Cherry	0.24 ± 0.13 a	0.76 ± 0.13 b	0.75 ± 0.20 b	0.74 ± 0.13 a	0.99 ± 0.12 c	4.80 ± 2.03 a	2.27 ± 0.67 b	47.00 ± 20.52 b	2.05 ± 0.66 b
Apple	0.15 ± 0.05 b	0.85 ± 0.05 a	0.97 ± 0.11 a	0.80 ± 0.08 a	1.21 ± 0.07 a	1.70 ± 0.38 b	3.64 ± 0.65 a	40.96 ± 16.75 b	3.42 ± 0.65 a
Total	0.20 ± 0.09	0.80 ± 009	0.85 ± 0.17	0.76 ± 0.10	1.10 ± 0.14	2.46 ± 2.07	2.76 ± 0.87	64.81 ± 43.45	2.87 ± 1.06

Note: different letters indicate statistically significant differences (ANOVA–Duncan test with multiple intervals, p < 0.05); D—Simpson dominance; 1 − D—Simpson diversity; H′—Shannon–Wiener index; E—Pielou index; H_max—maximum enthropy; D_Mn—Menhinick index; G—Gleason index; U—McIntosh index; D_Mg—Margalef index.

) revealed significant differences between them. The highest values of the biodiversity indices were recorded in the apple plantation, both in terms of the Shannon–Wiener index (H′ = 0.97), as well as for evenness (E = 0.80) and maximum entropy (H_max = 1.21), suggesting a much higher specific diversity and uniformity of species distribution compared to the other two plantations studied.

In turn, the Gleason index (G = 3.64) also reached its maximum value within the apple plantation. On the other hand, the Menhinick index had the highest value for the cherry plantation, and the McIntosh index within the plum plantation, but these two plantations had much weaker values in terms of uniformity, specific diversity, or the theoretical maximum value of diversity. Regarding Simpson dominance, it remained low in all three study areas, ranging from 0.15 in the case of the apple orchard to 0.24 in the case of the cherry orchard, and Simpson diversity ranged from 0.76 for cherry to 0.85 for apple. The results obtained suggest that the grassy strips in the apple orchard have a much higher floristic diversity compared to the reality in the other two orchards. The data obtained are lower than those presented in the study by Gómez et al. [66], carried out on an olive orchard in southern Spain, where the Shannon–Wiener indices ranged between 1.77 and 1.94, but were much closer to those found in the study by Juárez et al. [67] on several peach, pear, and apple orchards in northern Spain, where the Shannon–Wiener index was 1.36 for flood-irrigated plots and 1.08 for drip-irrigated plots. The study highlights differences in the structure and diversity of plant communities in the grassed strips of plum, apple, and cherry orchards, comparable to other European research studies [68,69]. The ecological index values obtained fall within similar ranges reported in the literature, indicating a high level of spontaneous biodiversity. The analyzed orchards show strong potential for conserving spontaneous diversity, and proper management can support the protection of local flora and improve fruit production quality [70]. For example, vegetation diversity can reduce soil compaction and the number of mechanical interventions, positively affecting soil health and agricultural output. However, the study has limitations, being conducted over a single season and on a limited number of sites, which restricts the regional applicability of the conclusions. Nevertheless, this research fills an important gap in the Romanian literature, demonstrating that factors such as orchard architecture, tree age, and management practices influence the structure and diversity of plant communities in the grassed strips.

3.3. Canonical Correspondence Analysis (CCA)

The canonical correspondence analysis (CCA) (Figure 1) revealed a strong relationship between the composition of plant species and the ecological variables (tree age, tree height, canopy cover, width of grassy strips, and orchard size) assessed across the three orchards. The results identified two significant canonical axes that explained the majority of the variation in the dataset. The first axis had an eigenvalue of 0.558 and accounted for 52.28% of the constrained variation, while the second axis had an eigenvalue of 0.509, explaining an additional 47.72%. Together, the two axes explained 100% of the variation influenced by environmental variables.

Axis 1 was closely related to orchard characteristics and was influenced by tree age, orchard size, and canopy cover. On the right side of this axis, samples from the apple orchard (A1–A10) were clustered, indicating that this orchard is associated with a larger area and mature trees with dense canopies. Among the herbaceous species favoring such ecological conditions and found in the apple orchard were Geranium dissectum, Vicia hirsuta, Sonchus arvensis, and Convolvulus arvensis. Conversely, on the left side of the axis were the cherry orchard samples (C1–C10), associated with smaller orchard areas, less dense canopies, and younger trees. These conditions favored the development of generalist species typical of semi-natural, open habitats, such as Lathyrus pratensis, Arenaria serpyllifolia, Veronica arvensis, Trifolium repens, and Vicia villosa. Thus, Axis 1 appears to highlight the contrast between a more sheltered and stable environment, such as the apple orchard, and a more open one, such as the cherry orchard, where external factors have a greater influence on the structure of the herbaceous layer.

In contrast, Axis 2 highlighted the dominance of a single ecological factor, namely the width of the grassy strips. In the upper part of the diagram, samples from the plum orchard were clustered, clearly separated from those of the other two orchards. This pattern suggests that areas with wider grassy strips support species such as Rorippa austriaca, Setaria pumila, Lamium purpureum, and Geranium pusillum. Plant communities in the apple and cherry orchards, by contrast, were positioned in the lower half of the diagram and are, therefore, associated with narrower grassy strips. The CCA results suggest that orchard type, tree age and height, orchard area, and grassy strip width can be determining factors in shaping the structure of plant communities in fruit orchards. For example, species such as Poa pratensis, Vicia sepium, and Veronica polita, located near the center of the diagram, appear to be more tolerant of variation in these environmental factors, being found across all three orchard types. A similar pattern was observed for Veronica hederifolia and Carduus acanthoides. This confirms that the first two axes well represent the main relationships between plant communities and environmental variables. The differences revealed by the CCA emphasize the potential of each orchard type in maintaining plant diversity and highlight the importance of adjusting agroforestry practices according to conservation goals.

4. Conclusions

The assessment of plant communities in the grassy strips of fruit orchards in southern Romania revealed distinct patterns of species diversity and distribution across orchard types. Notably, the apple orchard exhibited the highest species richness and evenness, indicating a more balanced community structure. The presence of indicator species related to soil quality and drainage confirms the ecological health of these habitats. However, the detection of invasive species highlights potential risks that require targeted management strategies. These findings demonstrate that maintaining diverse and structurally complex grassy strips is crucial for supporting ecosystem functions, enhancing biodiversity conservation, and reducing the need for chemical inputs. This study provides concrete evidence that agri-environmental measures focused on preserving native vegetation can effectively contribute to sustainable orchard management.