Research Article |
Corresponding author: Leonardo Lorenzato ( leonardo.lorenzato@unive.it ) Academic editor: Daniela Gigante
© 2023 Edy Fantinato, Leonardo Lorenzato, Gabriella Buffa.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Fantinato E, Lorenzato L, Buffa G (2023) Patterns of floral resources and pollination interactions along dry grassland succession. Plant Sociology 60(2): 93-103. https://doi.org/10.3897/pls2023602/06
|
Succession following the abandonment of traditional management practices can pose severe consequences for the conservation of semi-natural dry grassland communities. In the present study, we investigated whether the quantity of floral resources changes during succession of semi-natural dry grasslands and how this is related to pollinator richness and the number of pollination interactions at the community level. We addressed this issue by quantifying floral resources (i.e., number of flowers, nectar volume and number of pollen grains) and monitoring pollination interactions in dry grassland communities at different stages of succession, defined as the total cover of plant species of forest edges. The relationship between the quantity of floral resources and cover of plant species of forest edges was significantly hump-shaped, i.e., regardless of the type of floral resource, all peaked at intermediate values of cover of plant species of forest edges. The richness of animal-pollinated plants in bloom also showed a hump-shaped relationship with the cover of plant species of forest edges, while the richness of pollinator species and the number of pollination contacts were indirectly related to the cover of plant species of forest edges, as they were significantly associated with the number of flowers and the richness of animal-pollinated plants in bloom. Results suggest that succession of dry grasslands after abandonment may affect a crucial function in terrestrial ecosystems, namely animal-mediated pollination. Nevertheless, the conditions of early succession, which could be achieved by the presence of scattered shrubs, could ultimately be favourable for the pollination function in dry grasslands.
Abandonment, flowers, nectar, pollen, pollinators
Human-induced environmental transformations are leading to biodiversity loss and ecosystem degradation (
In rural areas, two contrasting processes are affecting local biodiversity and ecosystem functioning, namely agricultural intensification and land abandonment, especially in remote, less productive areas (Cramer et al. 2008;
While the impacts of intensification have been extensively studied (see e.g.,
This is especially true for semi-natural grasslands, which are secondary formations, created and maintained through centuries of traditional and low-intensity human practices (
Like all other semi-natural habitats, semi-natural dry grasslands are particularly vulnerable to abandonment (
Several studies have investigated changes in plant species composition and structure during the succession process (e.g.,
Although the relationship between grassland succession and plant and animal species richness and composition has been widely studied (e.g.,
In light of the above, this research aimed to answer the following questions: (i) How does the quantity of different types of floral resources (i.e., number of flowers, nectar volume, and number of pollen grains) change during succession of semi-natural dry grasslands? (ii) How does the species richness of plants and pollinators and their interactions change during the succession of semi-natural dry grasslands?
Sampling took place in semi-natural dry grasslands of the Euganean Hills in northeastern Italy (45.265706 N, 11.698977 E; Fig.
The study focused on meso-xerophilous semi-natural grasslands that establish on shallow calcareous soils. Based on
When subjected to proper management, the community is dominated by few, highly covering, anemophilous species (e.g., Bromopsis erecta, Bothriochloa ischaemum, Carex halleriana, Koeleria pyramidata) and several entomophilous species, including Bupleurum baldense, Convolvulus cantabrica, Fumana procumbens, Globularia bisnagarica, Helianthemum nummularium subsp. obscurum, and Scabiosa triandra. The proximity of roads and cultivated fields causes the entry of ruderal opportunistic species such as Avena barbata, Euphorbia falcata, Melampyrum barbatum subsp. carstiense, Sonchus oleraceus and Trifolium angustifolium.
The study was conducted on four grasslands with an average area of 6.89 ± 1.11 ha (M ± SD) and a minimum distance between grasslands of 1.2 km. While in the past, study grasslands were regularly (i.e., yearly) exploited for haymaking or cattle grazing, nowadays they are irregularly mown every three years (
We placed 27 permanent plots of 2 m x 2 m in the four grasslands, in a number proportional to each grassland surface, using a stratified random sampling design (Random points inside polygons; Quantum Gis Development Team 2020). None of the 27 plots were closer than 25 m. Each plot was monitored every 15 days for a total of 12 surveys (from 1st April to 30th September of 2016). In each survey, we recorded the presence of entomophilous plants and the number of flowers per plant species. For plant species with flowers occurring together in a floral unit (e.g., Thymus pulegioides), we calculated the total number of flowers by multiplying the number of floral units by the average number of flowers per floral unit, based on counts of five specimens of each species. Flower heads of Asteraceae, Dipsacaceae and Plantaginaceae were treated as single flowers. We also recorded pollination interactions between plant and animal species during each survey. Animals were considered pollinators if they landed on the flowers, had direct contact with the reproductive organs of the flower and visited the flower for more than 1 second, so they were considered potential pollinators. Pollination interactions were recorded for 14 min in two 7-min sets per survey (between 10 a.m. and 1 p.m., and between 1 p.m. and 4 p.m.) to ensure observation of animals with different daily activity times (
At each survey, we also quantified for each plot the total volume of nectar (µl) and the number of pollen grains. The total volume of nectar and the number of pollen grains were determined by multiplying the number of flowers by the mean value of the nectar volume and the mean number of pollen grains for each species, respectively. The mean value of nectar and pollen grains was determined by averaging the quantity of nectar and pollen from 5-10 randomly selected flowers growing within a radius of 10 m from each plot (for details on floral resource quantification, see
During the peak of the community's growing season (from mid-May to mid-June), all vascular plant species were recorded, and their percentage cover was visually estimated. Plant nomenclature was standardised following
We assumed the cover of plant species typical of forest edges as a proxy of the degree of succession. In this way, different successional stages were detectable based on the total cover of species typical of forest edges, whether herbaceous or woody. As a first step, we determined the degree of succession towards forest edges of each plot, by summing the cover of all plant species of forest edges and scaled the results to 100%. To explore the relationship between the cover of plant species of forest edges and the number of flowers, the volume of nectar, the number of pollen grains and the richness of animal-pollinated plants in bloom we used generalised linear mixed models (GLMMs, R version 3.4.3; package lme4). Specifically, each model included the cover of plant species of forest edges as independent variable, the number of flowers, the volume of nectar, the number of pollen grains and the richness of animal-pollinated plants in bloom as dependent variables and the plot identity as random factor. Moreover, we included the quadratic term of the cover of plant species of forest edges in the GLMMs to account for possible nonlinear relationships (without removing the linear term). We performed GLMMs using (a) Gamma error distribution and log link functions for the number of flowers, the volume of nectar and the number of pollen grains and (b) Poisson error distribution and log link function for the richness of animal-pollinated plants in bloom (after checking data overdispersion; dispersiontest function; package AER;
Since the richness of pollinator species per plot showed an excess of zero counts, using a GLMM with Poisson marginal distribution would lead to a bias in the conclusions. Therefore, we opted for a zero-inflated model (
In both the GLMMs and zero-inflated models, the values of the response variables quantified for each survey were used as replicates.
The sampled plots had different cover of plant species of forest edges, varying from 0.33% to 90.21% (mean ± SD; 29.26% ± 24.21%), indicating that the dry grassland communities recorded in the sampled plots were at different stages of succession. Plant species of forest edges that firstly occurred in the plots were Brachypodium rupestre, Asparagus acutifolius, Teucrium chamaedrys, Geranium sanguineum and Cervaria rivini. As soon as succession progressed (namely the cover of plant species of forest edges increased), seedlings of shrubs and trees also occurred, such as Cornus sanguinea, Rosa canina, Spartium junceum, Fraxinus ornus, and Quercus pubescens.
The quantity of floral resources varied greatly between the sampled plots. The number of flowers varied from 0.00 to 18,512.60 flowers per plot (mean ± SD; 465.38 ± 1570.45), the volume of nectar varied from 0.00 µl to 2,885.28 µl (mean ± SD; 75.44 µl ± 283.52 µl), while the number of pollen grains varied from 0.00 to 912,733,383.23 (mean ± SD; 2,148,660.32 ± 8,371,645.95).
The relationship between the number of flowers, the volume of nectar and the number of pollen grains with the cover of plant species of forest edges were all significantly hump-shaped, suggesting that regardless of the type of floral resource, all peaked at intermediate values of cover of plant species of forest edges (Table
Overall, 42 animal-pollinated plant species and 76 pollinator species were recorded in sampled plots. The richness of animal-pollinated plants in bloom per plot varied from 0.00 to 7.00 (mean ± SD; 1.51 ± 1.63); most frequent animal-pollinated plants in bloom were Thymus pulegioides (59% of sampled plots), Helianthemum nummularium subsp. obscurum (56%), Globularia bisnagarica (52%) and Stachys recta (48%). The richness of pollinator species varied from 0.00 to 8.00 (mean ± SD; 1.00 ± 1.50); the most frequent pollinator species were Apis mellifera (63% of sampled plots), Bombus hortorum (56%), Epicometis hirta (48%), Episyrphus balteatus (41%) and Eristalis tenax (41%). The number of pollination contacts varied from 0.00 to 16.00 (mean ± SD; 1.73 ± 3.04). The most visited plant species per plot were Globularia bisnagarica (mean ± SD; 7.70 ± 8.36), Potentilla pusilla (mean ± SD; 4.66 ± 2.88), Pilosella officinarum (mean ± SD; 2.85 ± 3.07) and Geranium sanguineum (mean ± SD; 2.15 ± 2.65).
The relationship between the richness of animal-pollinated plants in bloom with the cover of plant species of forest edges was significantly hump-shaped (Table
Statistics of the relationships between the number of flowers, the volume of nectar, the number of pollen grains and the richness of animal-pollinated plants in bloom and the cover of plant species of forest edges.
Dependent variable | Independent variable | t-value | p | χ2 | R2c | R2m |
Number of flowers | Cover of plant species of forest edges^2 | -2.154 | 0.048 | 3.884 | 0.033 | 0.432 |
Volume of nectar | Cover of plant species of forest edges^2 | -4.697 | <0.001 | 15.191 | 0.077 | 0.581 |
Number of pollen grains | Cover of plant species of forest edges^2 | -2.159 | 0.038 | 4.288 | 0.030 | 0.597 |
Richness of animal-pollinated plants in bloom | Cover of plant species of forest edges^2 | -2.209 | 0.044 | 4.047 | 0.059 | 0.321 |
Relationship between the number of flowers, the volume of nectar (µl), the number of pollen grains and the richness of animal-pollinated plants in bloom and the cover of plant species of forest edges. The line represents the estimate of the Generalised Linear Mixed Model (GLMM). Fuzzy grey points are original data points (color intensity increases from light grey to black when points overlap), while the grey band represents 95% confidence interval around the regression line.
Results of the zero-inflated Poisson model. Here π is the probability of not observing any individual pollinator or pollination contact in a plot, while λ is the expected richness of pollinators or the expected number of pollination contacts. Positive values of βπ indicate positive associations between covariates and the absence of pollinators or of pollination contact, while positive values of βλ indicate positive associations between covariates and the expected richness of pollinators or the expected number of pollination contacts. Only coefficients of significant covariates were included.
Dependent variable | Covariate variable | Estimate βπ | Standard Error βπ | P-value βπ | Estimate βλ | Standard Error βλ | P-value βλ |
Richness of pollinator species | Number of flowers (ln-transformed) | -6.818 | 1.629 | <0.001 | . | . | . |
Richness of animal-pollinated plants in bloom (ln-transformed) | . | . | . | 0.814 | 0.149 | <0.001 | |
Number of pollination contacts | Number of flowers (ln-transformed) | -1.199 | 0.189 | <0.001 | . | . | . |
Richness of animal-pollinated plants in bloom (ln-transformed) | . | . | . | 0.643 | 0.131 | <0.001 |
The abandonment of traditional management practices has been shown to lead to significant changes in the environmental characteristics and structural attributes of dry grassland communities (
In the present study, we have shown that succession of dry grasslands after abandonment affects structural properties of plant communities and has critical implication for a crucial function in terrestrial ecosystems, namely animal-mediated pollination, even in correspondence of the first dynamic stages.
Patterns of animal-mediated pollination interactions at community level are related to the type and quantity of floral resources (
Dry grasslands are biodiversity hotspots harbouring a large diversity of animal-pollinated species (
Interestingly, the richness of pollinator species and the number of pollination contacts were not directly related to the percentage cover of plant species of forest edges, but rather indirectly, as they were significantly related to the number of flowers and the richness of animal-pollinated plants in bloom. Our results showed that the probability of absence of pollinators and of pollination contacts decreased to zero once at least ten flowers were present. In other words, the probability of pollinator presence and pollination contact was significantly related to the presence of flowers. Although the presence of floral resources such as nectar and pollen may ultimately lead pollinators to develop floral fidelity and therefore continue to visit flowers of the same species because they have learned that floral resources are present (
The richness of plant species then significantly influenced the richness of pollinator species and the number of pollination contacts. These results can be explained by the fact that taxonomic richness usually positively correlates with functional richness (e.g.,
The abandonment of traditional management practices and the subsequent succession of dry grasslands towards forest edges has been shown to lead to biodiversity conservation issues and ecosystem changes, such as changes in soil properties and grassland productivity. In the present study, we have shown that the succession of dry grasslands also affects animal-mediated pollination, even in correspondence of early stages. Although animal-pollinated shrubs (e.g., Cornus sanguinea, Rosa canina, Spartium junceum) and trees (e.g., Fraxinus ornus) can provide floral resources, they only flower for a limited period of the year (usually in early spring) and rarely for more than a month. Beside showing restricted blooming periods, in some cases, shrubs and trees show high degrees of pollinator specialisation, namely, their floral morphology can be effectively handled only by a narrow group of pollinator species. This is the case, for example, of S. junceum, which shows mass blooming in late spring. However, the high degree of pollination specialisation of S. junceum, resulting from the complexity of its floral morphology and the thickness of its flowers, which allow only a few pollinators to forage, means that it occupies a peripheral position in the network of pollination interactions (i.e., it cannot sustain a broad community of pollinators on its own). Ultimately, this means that the contribution of dry grasslands to pollinator conservation cannot be replaced by shrub and forest communities.
Our results could provide useful insights for planning management practices that optimise the conservation of plants and pollinators in dry grasslands as well as pollination interactions.
The hump-shaped relationships that both the richness of animal-pollinated plants and the quantity of floral resources evidenced with the cover of plant species of forest edges suggest that the first dynamic stages ensure both an increase in plant species richness and in the quantity of floral resources supplied. Such a situation cannot be achieved through complete abandonment or even irregular management, that over time predictably lead to passive rewilding and grassland loss. Rather, improving grassland heterogeneity, leaving spatially scattered small areas where the frequency of mowing is temporarily slowed down to create conditions of early succession, can increase the number of niches for plant and animal species and improve the pollination function in dry grasslands.
This approach allows to create and maintain conditions of early succession, that contribute to increase the number of niches for plant and animal species and improve the pollination function in dry grasslands.
Association between the probability of absence of pollinator species and the number of flowers (ln-transformed), the probability of absence of pollination contacts and the number of flowers (ln-transformed), the richness of pollinator species and the richness of animal-pollinated plants in bloom (ln-transformed) and the number of pollination contacts and the richness of animal-pollinated plants in bloom (ln-transformed). For each covariate, the probability of absence was estimated as function of the selected covariate, setting the other covariates equal to their mean values.
List of plant species recorded on sampled plots. For each species, the habitat preferences, the number of plot in which they were recorded and the mean percentage cover (± standard deviation) are provided. Species nomenclature follows
HABITAT PREFERENCES | PLOT PRESENCE | MEAN COVER (%) ± SD | |
---|---|---|---|
Bromopsis erecta | Grassland | 27 | 50.56 ± 24.63 |
Poterium sanguisorba | Grassland | 25 | 1.42 ± 1.30 |
Artemisia alba | Grassland | 22 | 14.55 ± 13.91 |
Dactylis glomerata | Grassland | 20 | 4.48 ± 5.35 |
Thymus pulegioides | Grassland | 16 | 1.94 ± 1.38 |
Helianthemum nummularium subsp. obscurum | Grassland | 15 | 3.50 ± 4.02 |
Globularia bisnagarica | Grassland | 14 | 2.07 ± 1.48 |
Silene vulgaris subsp. tenoreana | Grassland | 14 | 0.75 ± 0.43 |
Stachys recta | Grassland | 13 | 3.00 ± 2.84 |
Koeleria pyramidata | Grassland | 11 | 2.91 ± 3.74 |
Galium verum | Grassland | 11 | 3.82 ± 6.10 |
Eryngium amethystinum | Grassland | 10 | 2.35 ± 1.70 |
Euphorbia cyparissias | Grassland | 10 | 1.10 ± 0.91 |
Linum tenuifolium | Grassland | 10 | 1.35 ± 1.42 |
Scabiosa triandra | Grassland | 10 | 1.25 ± 1.40 |
Bupleurum baldense | Grassland | 9 | 3.28 ± 3.08 |
Medicago falcata | Grassland | 8 | 2.38 ± 1.98 |
Bothriochloa ischaemum | Grassland | 7 | 24.36 ± 21.20 |
Plantago lanceolata | Grassland | 7 | 0.57 ± 0.19 |
Convolvulus cantabrica | Grassland | 7 | 6.86 ± 4.10 |
Fumana procumbens | Grassland | 7 | 5.64 ± 5.45 |
Lotus corniculatus | Grassland | 7 | 0.57 ± 0.19 |
Odontites luteus | Grassland | 7 | 0.71 ± 0.57 |
Ononis reclinata | Grassland | 7 | 3.00 ± 2.63 |
Salvia pratensis | Grassland | 7 | 3.00 ± 2.06 |
Cleistogenes serotina | Grassland | 6 | 6.50 ± 6.66 |
Lotus dorycnium subsp. herbaceus | Grassland | 6 | 3.67 ± 3.44 |
Thliphthisa purpurea | Grassland | 5 | 2.20 ± 1.89 |
Medicago minima | Grassland | 5 | 0.70 ± 0.27 |
Potentilla pusilla | Grassland | 5 | 1.40 ± 1.08 |
Carex halleriana | Grassland | 4 | 2.25 ± 0.50 |
Anacamptis pyramidalis | Grassland | 4 | 0.88 ± 0.25 |
Galatella linosyris | Grassland | 4 | 1.00 ± 0.00 |
Hippocrepis comosa | Grassland | 4 | 1.75 ± 2.18 |
Onobrychis arenaria | Grassland | 4 | 8.25 ± 5.38 |
Ononis natrix | Grassland | 4 | 9.50 ± 7.59 |
Thymus oenipontanus | Grassland | 4 | 1.13 ± 0.63 |
Trifolium campestre | Grassland | 4 | 4.75 ± 4.50 |
Carex flacca | Grassland | 3 | 3.67 ± 2.31 |
Allium sphaerocephalon | Grassland | 3 | 0.50 ± 0.00 |
Colchicum autumnale | Grassland | 3 | 0.67 ± 0.29 |
Galium lucidum | Grassland | 3 | 2.67 ± 2.08 |
Pilosella officinarum | Grassland | 3 | 4.00 ± 1.73 |
Catapodium rigidum | Grassland | 2 | 1.25 ± 1.06 |
Centaurea scabiosa | Grassland | 2 | 1.75 ± 1.77 |
Crupina vulgaris | Grassland | 2 | 0.50 ± 0.00 |
Dianthus sylvestris | Grassland | 2 | 0.50 ± 0.00 |
Leontodon hispidus | Grassland | 2 | 0.75 ± 0.35 |
Filago pyramidata | Grassland | 1 | 1.00 |
Achillea roseoalba | Grassland | 1 | 1.00 |
Cynanchica pyrenaica | Grassland | 1 | 5.00 |
Centaurea deusta | Grassland | 1 | 5.00 |
Crepis taraxacifolia | Grassland | 1 | 0.50 |
Pilosella piloselloides | Grassland | 1 | 0.50 |
Teucrium montanum | Grassland | 1 | 1.00 |
Tragopogon pratensis | Grassland | 1 | 0.50 |
Trifolium scabrum | Grassland | 1 | 1.00 |
Euphorbia falcata | Ruderal | 6 | 1.33 ± 1.81 |
Erigeron annuus | Ruderal | 3 | 0.50 ± 0.00 |
Triticum vagans | Ruderal | 3 | 3.00 ± 1.73 |
Melampyrum barbatum subsp. carstiense | Ruderal | 2 | 3.00 ± 0.00 |
Sonchus oleraceus | Ruderal | 2 | 0.50 ± 0.00 |
Centaurium erythraea | Ruderal | 2 | 0.50 ± 0.00 |
Arabis hirsuta | Ruderal | 1 | 0.50 |
Myosotis arvensis | Ruderal | 1 | 0.50 |
Allium vineale | Ruderal | 1 | 0.50 |
Avena barbata | Ruderal | 1 | 0.50 |
Campanula rapunculus | Ruderal | 1 | 0.50 |
Cota tinctoria | Ruderal | 1 | 0.50 |
Erigeron canadensis | Ruderal | 1 | 0.50 |
Muscari neglectum | Ruderal | 1 | 0.50 |
Trifolium angustifolium | Ruderal | 1 | 1.00 |
Brachypodium rupestre | Forest edge | 22 | 36.57 ± 34.8 |
Teucrium chamaedrys | Forest edge | 14 | 8.00 ± 13.52 |
Asparagus acutifolius | Forest edge | 10 | 3.10 ± 1.96 |
Geranium sanguineum | Forest edge | 8 | 8.56 ± 12.43 |
Cervaria rivini | Forest edge | 8 | 1.19 ± 0.70 |
Fraxinus ornus | Forest edge | 5 | 1.10 ± 0.55 |
Rubus caesius | Forest edge | 5 | 2.10 ± 1.88 |
Vitis vinifera | Forest edge | 4 | 4.00 ± 4.08 |
Hypericum perforatum | Forest edge | 4 | 0.63 ± 0.25 |
Cornus sanguinea | Forest edge | 3 | 2.00 ± 2.60 |
Lathyrus latifolius | Forest edge | 3 | 1.50 ± 0.87 |
Rosa canina | Forest edge | 3 | 2.83 ± 2.25 |
Spartium junceum | Forest edge | 3 | 0.50 ± 0.00 |
Ligustrum vulgare | Forest edge | 2 | 1.50 ± 0.71 |
Quercus pubescens | Forest edge | 2 | 1.25 ± 1.06 |
Trifolium rubens | Forest edge | 2 | 1.50 ± 0.71 |
Agrimonia eupatoria | Forest edge | 2 | 1.50 ± 0.71 |
Berberis vulgaris | Forest edge | 2 | 0.75 ± 0.35 |
Buphthalmum salicifolium | Forest edge | 2 | 0.50 ± 0.00 |
Crataegus monogyna | Forest edge | 2 | 1.50 ± 0.71 |
Cytisus hirsutus | Forest edge | 2 | 6.50 ± 4.95 |
Pentanema spiraeifolium | Forest edge | 2 | 1.00 ± 0.00 |
Orchis purpurea | Forest edge | 2 | 0.75 ± 0.35 |
Viburnum lantana | Forest edge | 2 | 0.50 ± 0.00 |
Cotinus coggygria | Forest edge | 1 | 3.00 |
Ostrya carpinifolia | Forest edge | 1 | 1.00 |
Clematis vitalba | Forest edge | 1 | 2.00 |
Genista tinctoria | Forest edge | 1 | 0.50 |
Himantoglossum adriaticum | Forest edge | 1 | 0.50 |
Muscari comosum | Forest edge | 1 | 0.50 |
Robinia pseudoacacia | Forest edge | 1 | 0.50 |