Figures
Abstract
European terrestrial orchids inhabit a wide range of habitats, including forests, grasslands, wetlands and anthropogenic ecosystems. This study investigates the ecological preferences of seven wild orchid species in the Po Delta Regional Park (Northern Italy), focusing on how environmental gradients of soil properties such as moisture, salinity, pH, and nutrient availability shape species distribution and niche breadth. We conducted vegetation surveys and field measurements of soil variables across 27 sites. Species differentiation along environmental gradients was analysed through Multivariate Analysis of Variance (MANOVA), Principal Component Analysis (PCA), and Outlying Mean Index (OMI) analysis to assess niche breadth and marginality. We then compared normalized Ellenberg Indicator Values (EIVs) for Moisture, Reaction, Salinity, and Nutrients with measured soil variables [Volumetric Water Content, pH, salinity, ammonium (NH4+), nitrate (NO3−), and phosphate (PO43−) concentrations] using Linear regression. Moisture and salinity were key drivers of orchid distribution. Anacamptis laxiflora and Anacamptis palustris were associated with wet, saline environments, whereas Anacamptis pyramidalis and Anacamptis coriophora preferred drier, nutrient-poor soils. Anacamptis laxiflora exhibited highest marginality and narrowest niche breadth, indicating high specialization. In contrast, Ophrys apifera showed lowest marginality and highest tolerance, reflecting its generalist strategy and adaptability to a broad range of soil conditions. EIV-Moisture and EIV-Salinity showed strong correlations with field measurements, whereas EIV-Nutrients and EIV-Reaction were less predictive. These findings emphasize the importance of conserving environmental heterogeneity, especially in human-dominated ecosystems, to support both generalist and specialist orchid species.
Citation: Scramoncin L, Gerdol R, Cazzavillan A, Vincenzi F, Brancaleoni L (2026) Environmental drivers of wild orchid distribution: Soil properties shape habitat preferences in the Po Delta Regional Park (Italy). PLoS One 21(2): e0340676. https://doi.org/10.1371/journal.pone.0340676
Editor: Tzen-Yuh Chiang, National Cheng Kung University, TAIWAN
Received: September 26, 2025; Accepted: December 23, 2025; Published: February 18, 2026
Copyright: © 2026 Scramoncin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the article. Raw data related to this article have been deposited online on Zenodo and can be found at the DOI https://doi.org/10.5281/zenodo.18323794.
Funding: This work was supported by the University of Ferrara [2024-FAR.L_DISAP_BL to LB]. Funding did not include specific supports to study design, data collection and analysis, decision to publish, preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
1 Introduction
Ecological niche is a key concept in modern ecology, concerning both the range of conditions necessary for the survival of species and all mutual interactions among species and their interaction with the biotic and abiotic environment [1]. Many factors can shape the ecological niche. Macroclimate and evolutionary and migration histories influence the distribution of species across large geographical areas [2,3]. On a regional scale, factors such as soil physical and chemical characteristics, meso- and micro-climate, light regime, habitat type, community composition and disturbance regime play a key role in determining species abundance and richness [4,5]. Global climate change, habitat loss and fragmentation, overexploitation of wild species and abandonment of traditional habitat management are just some of the factors that can negatively affect plant species, particularly those with specific ecological niches, which depend on specific conditions for their germination, growth and reproduction [6,7]. Thus, a thorough understanding of the ecological preferences, along with analyses of the major drivers that influence the diversity and distribution patterns of species, is crucial for understanding how species respond to changing environmental conditions and, therefore, for the development of effective conservation strategies for both species and their habitats [8–11].
With over 28,000 species and 763 genera, Orchidaceae is among the largest families of flowering plants [12]. Orchids inhabit a wide range of environments worldwide, with most species thriving in tropical regions [13]. In Europe, the Mediterranean region is one of the most important hotspots for orchid diversity, where all orchid species are terrestrial and can be found in several different habitats, including forests, grasslands, bogs, marshlands, and even anthropogenic ecosystems [14]. Despite this great diversity, many orchid species faced a drastic decline in abundance and distribution over the past few decades due to habitat loss and changes in land-use practices [15]. Therefore, several species have turned rare or endangered, and many countries have prompted their protection under national and international legislation, as well as their inclusion in Red Data Books [16]. Moreover, native orchid species show a remarkable level of ecological specialisation, as they rely on complex ecological associations with specific pollinators and mycorrhizal fungi for their survival and reproduction [17]. Consequently, these plants are considered important bioindicators of the ecological quality of ecosystems due to their high vulnerability to environmental changes [18]. All these features highlight that, in highly industrialised European countries, conservation of orchid species presents a considerable challenge, primarily due to widespread habitat degradation and the absence of suitable environmental conditions necessary for their long-term survival [19].
Different studies pointed out that orchid distribution can be closely linked to factors such as soil moisture content, nutrient availability, light regime, climatic variables and competition levels [20,21]. Although several European studies examined the relationship between terrestrial orchid diversity and ecological factors across large geographic extents [22–24], the impact of these drivers can differ among regions so that a universally consistent pattern of orchid diversity cannot be generalized across all species and geographic areas. Therefore, studies at local scale are crucial for enhancing the understanding of how species richness interacts with environmental variables, enabling effective local conservation and habitat management [25,26]. The Orchidaceae family is well represented in Italy’s native vascular flora, comprising 236 taxa across 27 genera with 87 endemic taxa [27]. All species are legally protected at the regional level by Regional Law No. 2 (24 January 1977), and at the national and international levels by the Habitat 92/43/EEC Directive, the Convention on the conservation of European wildlife and natural habitats (Bern Convention) and the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) [28]. Our case study was conducted in different semi-natural grasslands of the Po Delta (Northern Italy), which is regarded as one of the most important natural areas in Europe [29]. However, this territory has undergone substantial anthropogenic alteration due to urbanization, tourism and agricultural expansion [30]. As a matter of fact, many natural habitats, including pine forests, wet and dry meadows and grasslands, have been destroyed or converted into urban green spaces. Over time, these areas experienced an increase in non-native plant species with a high tolerance for a wide range of environmental conditions, leading to a decline in the natural populations of wild orchids, which are generally weaker competitors [31]. Furthermore, these semi-natural grasslands are subject to additional pressures such as uncontrolled herbivory and inappropriate mowing regimes. Specifically, both frequent mowing, driven by urban aesthetic policies, and the complete abandonment of traditional management practices led to the degradation of these habitats, resulting in the loss of key ecological niches and a decline in vascular plant species richness [32,33].
This study investigates the ecological preferences of seven wild orchid species, focusing on site-specific soil properties and associated vegetation assemblages. The main objectives were: (i) to measure species’ niche breadth and marginality, (ii) to identify the main environmental drivers influencing their occurrence and (iii) to verify the correlation between Ellenberg Indicator Values (EIVs) and field measurements to assess their reliability as predictors of environmental conditions. These insights are relevant for implementing appropriate management strategies for semi-natural meadows and for preventing both habitat degradation and species decline.
2 Materials and methods
2.1 Study area and species selection
The study was conducted in the Po Delta Regional Park Emilia-Romagna, located along the North Adriatic coast of Northern Italy (ca. 44°32′–44°56′ N; 12°08′–12°16′ E; Fig 1). The Park has a total area of 54,000 ha and encompasses a great variety of habitats, including pine forests, wetlands, dunes, and dry grasslands. Consequently, several sites of community importance and special areas for biodiversity conservation are currently present in this region [https://www.parks.it/parco.delta.po.er/Epar.php (accessed on 23 April 2025)]. In addition, the northern section of this area contains the National Nature Reserve Bosco della Mesola. Based on the Köppen climate classification, the study area has a temperate continental climate, with a mean annual temperature of about 14 °C. Mean monthly temperatures vary from 3°C in January, the coldest month, to approximately 24°C in July, the warmest month. The mean total annual precipitation ranges from 600 to 700 mm, with a short period of mild summer aridity. The average annual relative humidity is approximately 70–75% [34].
The red square indicates the location of the study area in Italy (panel a). The detailed map in panel b shows the sampling sites distributed along the coastal zones of the Provinces of Ferrara and Ravenna. Basemap from the U.S. Geological Survey (USGS ImageryOnly, The National Map) – public domain. Sampling sites were added by the authors.
We have been investigating wild orchids in the Po Delta Park since 2012. Fifteen species of native orchids are currently present in this study area [35]. In this study, we aimed to analyse the ecological niche of native orchid species by including both the highest possible number of different habitat types and ensuring the presence of sample replicates. On this basis, we selected seven orchid species: Ophrys sphegodes Mill.; Anacamptis morio (L.) R.M. Bateman, Pridgeon et M.W. Chase; Anacamptis laxiflora (Lam.) R.M.Bateman, Pridgeon & M.W. Chase; Anacamptis palustris (Jacq.) R.M.Bateman, Pridgeon & M.W. Chase; Ophrys apifera Huds.; Anacamptis pyramidalis (L.) Rich. and Anacamptis coriophora (L.) R.M. Bateman, Pridgeon et M.W. Chase. Specifically, O. sphegodes, A. morio, A. pyramidalis and A. coriophora inhabit dry or semi-dry grasslands that lie on sandy flat areas corresponding to the ancient dunes levelled by atmospheric agents whereas A. laxiflora and A. palustris typically occur in wet meadows [35].
2.2 Data collection and laboratory analyses
Field sampling was conducted from March to June 2023. We visited a total of 27 selected sites several times throughout the spring and early summer, following the species’ phenology. Eight of these sites hosted more than one of the orchid species included in the study, making a total of 35 site occurrences (Table 1). For each study site, we estimated both the spatial extent and the number of orchid individuals present. Three 1-m2 quadrats were established at representative points in all the sites. Within each quadrat, all vascular plant species were identified, and their abundance was visually estimated using a categorical scale: 1 = 1–10%, 2 = 11–20%, 3 = 21–30%, 4 = 31–40%, 5 = 41–50%, 6 = 51–60%, 7 = 61–70%, 8 = 71–80%, 9 = 81–90%, 10 = 91–100%. Total vegetation cover was recorded at each plot using a percentage scale. Data were collected at the peak of species flowering season following the protocol described in Braun-Blanquet (1932) [36]. Three repeated measurements of soil Volumetric Water Content (VWC) were carried out at each site using a FieldScout time domain reflectometer TDR 100 Soil Moisture Meter (Spectrum Technologies Inc, Aurora, IL, USA). Soil VWC measurements were performed several times throughout the sampling season. Three replicates of about 100 g of soil were collected at each site to a maximum depth of 5–10 cm. A Data Logger (HOBO® Pendant Temperature/Light Data Logger, Onset, Bourne, MA, USA) was deployed at each site to continuously measure soil temperature hourly.
The soil analyses were carried out at the Laboratory of Plant Ecology (Department of Environmental and Prevention Sciences), University of Ferrara. A 10 g subsample of dry soil was extracted in a 1:2.5 (vol/vol) aqueous solution and used to determine soil pH with a pH meter [Hanna Edge, Villafranca Padovana (PD), Italy]. Electrical conductivity and salinity were determined with a Crison CM35 conductivity-meter (Hach-Lange, L’Hospitalet de Llobregat, Spain). A 10 g subsample of dry soil, sieved with a 0.125 mm mesh, was extracted in 100 mL of H2O, filtered with Whatman 25-mm GD/X syringe filters (pore size 0.45 μm) and colorimetrically analysed for ammonium (NH4+) and nitrate (NO3−) concentrations. The Olsen method was used to analyze phosphate (PO43−) concentration from a dry sieved soil sample [37]. These analyses were conducted using a continuous-flow autoanalyzer (Systea Flowsys, Anagni, Italy). Specifically, ammonium was determined by the salicylate method in the presence of hypochlorite [38], nitrate by the cadmium-reduction method through a column [39], and phosphate by the molybdenum-blue method [40].
2.3 Data compilation and statistical analyses
To assess the ecological preferences of orchid species from both a vegetation-based and an abiotic perspective, we applied a combination of statistical approaches. Ecological differentiation analyses based on measured soil variables were performed in the R environment using the ADE-4 package [41]. To this aim, a Principal Component Analysis (PCA) was conducted to examine the overall differences among species in terms of their ecological preferences for soil properties, taking into consideration all 35 site occurrences. Subsequently, we performed an Outlying Mean Index (OMI) analysis to determine niche marginality and breadth [42]. For the analysis, we considered the 27 sites to highlight the associations between orchid species. We used two datasets: the first dataset consisted of the species presences in the sites, while the second dataset included the explanatory soil variables, i.e., soil VWC, pH, salinity, and soil nutrient contents (ammonium, nitrate, and phosphate concentrations). Species with high OMI values (niche marginality) are considered to occupy marginal niches, for being associated with environmental conditions that are relatively uncommon in the study area. Conversely, species with low OMI values inhabit non-marginal niches, reflecting their association with more typical or widespread habitat conditions. Species exhibiting low tolerance values (niche breadth) are confined to a narrow range of environmental conditions and are thus classified as specialists, whereas those with high tolerance values occupy a broader range of conditions, indicating a generalist strategy. A random permutation test with 10,000 permutations was employed to test the statistical significance of each species’ marginality.
A Multivariate Analysis of Variance (MANOVA) was performed using normalized EIVs derived from field floristic surveys for Light (L), Temperature (T), Moisture (M), Reaction (R), Salinity (S), and Nutrients (N) as dependent variables, to investigate which ecological factors most strongly influenced the occurrence of each orchid species [43]. The EIVs were normalized prior to analysis based on species composition at each site, ensuring comparability across gradients using Formula (1):
where Ai is the mean abundance of the i-th species resulting from the three vegetation surveys, EIVi is the corresponding Ellenberg Indicator value, and is the total sum of mean abundances. Statistical significance was assessed via permutation tests. To evaluate whether normalized EIVs (for Moisture, Reaction, Salinity, and Nutrients) reflected the actual environmental conditions, we tested the relationships between normalized EIVs and measured soil variables (soil VWC, pH, salinity, and inorganic nitrogen and phosphorus concentrations) using Linear Regressions. The MANOVA and the linear regressions were performed using PAST 4.16c [44].
3 Results
3.1 Soil properties and ecological niches
The patterns resulting from the PCA emphasized the ecological differentiation of orchid species based on measured soil variables (Fig 2a). The first two axes (PC1 and PC2) explained 48.6% and 27.3% of the dataset’s variance, respectively. PCA 1 primarily reflected a multiple gradient of soil moisture, salinity, ammonium and, to a lesser extent, soil pH. Indeed, PCA 1 separated species primarily associated with drier and less saline habitats from species associated with wetter habitats (Fig 2b). In particular, O. apifera, A. pyramidalis, and A. coriophora were mostly clustered along the negative side of PCA 1, corresponding to lower values of moisture and salinity. A. laxiflora and A. palustris were located on the positive side of PCA 1, indicating their association with high moisture and salinity in the soil. PCA 2 explained most of the variation in soil nutrient contents, namely soil nitrate and phosphate concentrations. O. sphegodes and A. morio had positive scores along PCA 2, denoting their association with more nutrient-rich environments. The other species had generally lower or intermediate scores on the PCA 2 axis, indicating more variation in their nutrient preference. Interestingly, O. apifera tended to occupy a broader range of ecological conditions, including nutrient-poor, dry habitats, as well as more saline and wet habitats.
(a): Plot of environmental variables; (b): Distribution of species along environmental gradients; (c): Ecological niche breadth.
The OMI analysis showed marginality and breadth values to vary considerably, indicating different levels of ecological specialization among species (Fig 2c; Table 2). A. laxiflora exhibited the highest OMI value, and thus the highest niche marginality. A. laxiflora also exhibited the lowest tolerance and relatively low residual tolerance, which confirms its narrow niche breath, indicating a strong association with highly distinctive environmental conditions, particularly wet and saline habitats. A. palustris showed the second highest marginality value, indicating a potential ecological preference for moist and nutrient-rich soils. It had a broader niche breadth, implying somewhat higher ecological plasticity compared to A. laxiflora. A. pyramidalis had intermediate values of all parameters, suggesting a moderately wide niche with limited specialization. A. coriophora showed low marginality, low tolerance, and highest residual tolerance, indicating that its distribution may be influenced by other environmental or biotic factors not captured in our analyses. O. sphegodes and A. morio, can be considered ecological generalists due to their low marginality values, which suggests their distribution to be centered close to average environmental conditions. O. apifera showed the lowest marginality value and the highest tolerance value, indicating a great capacity to adapt to a wide range of ecological conditions. Overall, the mean OMI across all species was significantly higher than expected under random distribution (OMI.mean = 3.77; p < 0.01), indicating that the orchid species investigated were non-randomly distributed along the environmental gradients (Fig 2c, Table 2). This supports the view that habitat filtering played an important role in shaping their distribution.
3.1 Ellenberg indicator values
The MANOVA revealed significant differences in the ecological factors inferred from species composition in the sampling sites (p < 0.01, Table 3). Specifically, A. morio was distinguished by notably low normalized EIV values for Salinity, Moisture, Reaction and Nutrients, which highlights its preference for dry, nutrient-poor, and slightly acidic soils. A. laxiflora had a strong positive association with normalized Moisture EIV value, confirming its preference for wetter environments. Similarly, A. palustris exhibited high positive scores for normalized Moisture and Salinity EIV values, indicating its preference for wet and saline habitats. O. apifera was negatively associated with normalized Light EIV value, suggesting a preference for more shaded conditions. A. coriophora showed a strongly negative correlation with normalized Moisture EIV value, highlighting its preference for dry soils.
Linear regression analyses showed varying levels of agreement between normalized EIVs and measured soil variables (Fig 3a-f). The strongest relationship was found for the Salinity index (Fig 3c), indicating that species composition effectively captured soil salinity variation across sites. Soil VWC also showed a significant correlation with the Moisture index, confirming the reliability of EIV-M in reflecting soil moisture gradients (Fig 3a). Weaker relationships were observed between the Reaction index and soil pH (Fig 3b), as well as between the Nutrient index and the concentrations of nitrate, ammonium and phosphate (Fig 3d-f). Although statistically significant, the lower r2 values associated with nutrient variables suggest a weaker predictive power of EIV-N for capturing local soil fertility conditions.
(a): EIV-Moisture/Volumetric Water Content (VWC); (b): EIV-Reaction/pH; (c): EIV-Salinity/Salinity; (d): EIV-Nutrient/Nitrate concentration (NO3-); (e): EIV-Nutrient/Ammonium concentration (NH4+); (f): EIV-Nutrient/Phosphate concentration (PO43-). r-squared and p-values are indicated within each panel.
4 Discussion
Our study provided consistent evidence that soil properties had a pivotal role in shaping the distribution of orchids. The PCA 1 axis separated A. coriophora and A. pyramidalis, both associated with drier and less saline soil conditions on one side, from A. laxiflora and A. palustris, which both preferred more humid and saline habitats on the other side. Soil moisture is generally considered as a major ecological factor affecting the distribution and population density of orchid species, even at the microsite scale [45,46]. Beyond its direct influence on plant growth, soil moisture significantly affects nutrient cycling, soil chemistry and thermal properties of the soil [47,48]. The PCA revealed that most of the species were found in nutrient-poor habitats, especially A. coriophora and A. pyramidalis. It is well known that many terrestrial orchid species prefer nutrient-poor soils where they depend on fungal associates for acquiring nutrients [49,50]. Infertile conditions may themselves promote both the establishment and the long-term stability of these mutualistic relationships and hence the creation of a balanced ecological niche. In such conditions, competition with fast-growing plants adapted to nutrient-rich conditions is reduced, while orchids benefit from their efficient capability of acquiring nutrients by their symbionts [51]. On the other hand, O. sphegodes and A. morio were generally found at sites with higher nitrate and phosphate contents in the soil, probably due to increased nutrient input from adjacent crops. Interestingly, high phosphorus availability has been found to enhance the diversity of mycorrhizal fungal communities associated with two Bipinnula species in Chile [52]. Overall, this suggests that soil nutrient availability not only affects the distribution of wild orchid species but also modulates their fungal associations, potentially promoting specialization in nutrient-enriched habitats. Both the PCA and the OMI analyses showed that O. apifera had the lowest marginality and the highest tolerance. Previous studies found that O. apifera can colonize different types of semi-natural habitats, including anthropogenic environments, primarily on xerophilous or mesoxerophilous soils [53–55]. In our study area, O. apifera proved to be adapted to moderately wet conditions. A. morio and O. sphegodes also presented low marginality values, indicating their ecological flexibility and adaptation to habitats close to the regional average. Generalistic strategies are often associated with broader ecological tolerance, higher phenotypic plasticity, varied resource usage, and stronger resilience to environmental disturbances [56]. However, such adaptability can sometimes mask subtle fine-scale dependency on microhabitat features or mycorrhizal associations, which require further investigation. On the other hand, specialistic species tend to occupy narrow, often extreme ecological niches [56], in fragmented micro-habitats sensitive to disturbance, which makes specialistic plants particularly vulnerable. Among the species investigated, A. laxiflora exemplifies this trend since it exhibited highest marginality and lowest tolerance, which indicates a narrow ecological niche, primarily defined by high moisture and salinity. Similarly, A. palustris showed substantial marginality, although combined with slightly broader tolerance, suggesting considerable ecological plasticity within its preferred wet environments. On the opposite end of the gradient, A. pyramidalis was typically found in drier, infertile soils with a preference for open, xeric grasslands. Although seemingly more resilient, these dry habitats are equally subject to degradation through land abandonment or encroachment of more competitive species [57]. These findings are in line with the general ecological principle that most highly specialized species are found at the extreme ends of environmental gradients [58]. Therefore, many orchid specialists inhabit either wet habitats, such as fens or wet meadows, or dry and warm environments like calcareous grasslands [47]. From a conservation perspective, ecologically marginal species seem to be generally more affected by ongoing events as climate change, genetic drift and human influence, leading to disturbances in their survival [59]. As a result, they are more likely to experience range contractions or local extinctions under changing conditions compared to generalist species, although some variation in the occurrence and rarity of orchid species may be found due to the biogeographical context [60,61]. A recent study [62] highlighted that the geographic ranges of European orchids are shaped more by species-specific biological characteristics and abiotic conditions rather than by evolutionary history. As shown by our results and previous studies [4,63], soil properties play a major role in affecting orchid distribution. Therefore, conservation efforts should focus on preserving a broad range of environmental conditions across landscapes [64]. Our results stress the importance of maintaining environmental heterogeneity to sustain orchid diversity, since it allows species to respond and adapt to environmental changes as an urgent need in the context of climate change and habitat degradation [65]. Local studies addressed to orchid species with narrow ecological ranges can offer valuable insight for regional planning and habitat restoration, especially in Mediterranean ecosystems facing increasing anthropogenic pressure [66,67]. This perspective is particularly relevant in the context of the Po Delta Regional Park, a complex mosaic of protected and non-protected areas heavily impacted by growing urbanization and agricultural expansion, where the actual environmental protection and policy are not effective in the conservation of wild orchid populations [33]. Under such conditions, the preservation of microhabitats that support niche-specific conditions, such as saline depressions, wet meadows, and calcareous dry grasslands, becomes even more critical. Fragmentation, land-use change, and alien plant invasion can disproportionately affect ecologically marginal species, which are often confined to narrow habitat patches within this landscape. We used EIVs to test whether floristic composition reflects the same environmental gradients revealed by soil measurements. The MANOVA confirmed that the strongest interspecific differences were observed along the moisture and salinity gradients, with A. palustris and A. laxiflora standing out for their affinity for wet saline habitats, mirroring the environmental gradients detected in the PCA.
Linear regression analyses revealed different degrees of correspondence between normalized EIVs and soil properties measured in the field. Weaker correlations were observed for the reaction index (EIV-R) and especially for the nutrient index (EIV-N), indicating a lower effectiveness of these indicators in predicting soil pH and fertility, which supports the results of previous studies. For example, Schaffers and Sýkora [68] found weak correlation between EIV-N and soil nutrient concentrations in 14 different Dutch roadside plant communities, probably due to the high temporal variability of soil nutrient contents and their complex interaction with community structure. The low correlation between EIV-N and the concentrations of nitrate, ammonium and phosphate in the soil could also reflect indirect effects of unmeasured edaphic factors, such as soil retention capacity, or interspecific competition for resources which may influence vegetation composition in a non-linear manner [69]. Moreover, soil nutrient contents can undergo strong seasonal fluctuations related to microenvironmental heterogeneity [70,71]. The reaction index (EIV-R) also had weak correlation with soil pH, probably because most of the orchid species investigated usually occur on soils with a narrow pH range from slightly acidic to slightly alkaline [72]. In contrast, the strongest correlation was found between the Salinity index and soil salinity, followed by a high correlation between the Moisture index and soil Volumetric Water Content. This suggests that floristic composition was an effective indicator of soil salinity and moisture variability in the habitats investigated. In summary, our results support both the reliability of EIVs as ecological proxies in vegetation-based analyses, with better performance for temporally stable variables (e.g., moisture, salinity) and weaker performance for dynamic variables such as soil nutrients [73,74].
5 Conclusions
Our study revealed distinct environmental gradients shaping wild orchid species distribution and highlighted differences in their ecological strategies, distinguishing generalist orchids (O. apifera) from specialists with narrow ecological ranges (A. laxiflora). These findings highlight that conservation strategies must account for habitat specialization and environmental heterogeneity, particularly where specialist species occur at the extremes of ecological gradients. Therefore, integrating fine-scale ecological data into regional conservation planning is essential to ensure that the full range of orchid diversity is protected in the long term, especially within human-dominated ecosystems like the Po Delta.
Acknowledgments
We thank Massimiliano Costa, Po Delta Regional Park Emilia-Romagna, for authorizing sampling in the protected areas and Carabinieri Forestali – Reparto Biodiversità for logistical support
References
- 1.
Polechová J, Storch D. Ecological niche. In: Fath B, editor. Encyclopedia of Ecology. 2nd edition. Amsterdam, the Netherlands: Elsevier; 2019. p. 72–80.
- 2. Evans A, de Kort H, Brys R, Duffy KJ, Jersáková J, Kull T, et al. Historical biogeography and local adaptation explain population genetic structure in a widespread terrestrial orchid. Ann Bot. 2023;131(4):623–34. pmid:36680796
- 3. Sheth SN, Morueta-Holme N, Angert AL. Determinants of geographic range size in plants. New Phytol. 2020;226(3):650–65. pmid:31901139
- 4. Djordjević V, Tsiftsis S, Lakušić D, Jovanović S, Stevanović V. Factors affecting the distribution and abundance of orchids in grasslands and herbaceous wetlands. Syst Biodivers. 2016;14:355–70.
- 5. Tsiftsis S, Tsiripidis I, Karagiannakidou V, Alifragis D. Niche analysis and conservation of the orchids of east Macedonia (NE Greece). Acta Oecologica. 2008;33(1):27–35.
- 6. Dengler J, Janišová M, Török P, Wellstein C. Biodiversity of Palaearctic grasslands: a synthesis. Agric Ecosyst Environ. 2014;182:1–14.
- 7. Helm A, Hanski I, Pärtel M. Slow response of plant species richness to habitat loss and fragmentation. Ecol Lett. 2006;9(1):72–7. pmid:16958870
- 8. Likens GE, Lindenmayer DB. Integrating approaches leads to more effective conservation of biodiversity. Biodivers Conserv. 2012;21:3323–41.
- 9. Possingham HP, Wilson KA. Biodiversity: turning up the heat on hotspots. Nature. 2005;436(7053):919–20. pmid:16107821
- 10. Tsiftsis S, Tsiripidis I, Karagiannakidou V. Identifying areas of high importance for orchid conservation in east Macedonia (NE Greece). Biodivers Conserv. 2009;18:1765–80.
- 11. Lussu M, Ancillotto L, Labadessa R, Di Musciano M, Zannini P, Testolin R. Prioritizing conservation of terrestrial orchids: A gap analysis for Italy. Biol Conserv. 2024;289:110385.
- 12. Christenhusz MJM, Byng JW. The number of known plants species in the world and its annual increase. Phytotaxa. 2016;261(3).
- 13. Swarts ND, Dixon KW. Terrestrial orchid conservation in the age of extinction. Ann Bot. 2009;104(3):543–56. pmid:19218582
- 14. Fay MF, Chase MW. Orchid biology: from Linnaeus via Darwin to the 21st century. Preface. Ann Bot. 2009;104(3):359–64. pmid:19654223
- 15. Reiter N, Whitfield J, Pollard G, Bedggood W, Argall M, Dixon K, et al. Orchid re-introductions: an evaluation of success and ecological considerations using key comparative studies from Australia. Plant Ecol. 2016;217(1):81–95.
- 16. Fay MF. Orchid conservation: how can we meet the challenges in the twenty-first century? Bot Stud. 2018;59(1):16. pmid:29872972
- 17. Gale SW, Fischer GA, Cribb PJ, Fay MF. Orchid conservation: bridging the gap between science and practice. Bot J Linn Soc. 2018;186:425–34.
- 18. Bianco PM. Le orchidee come indicatori di qualità degli habitat. Biol Ital. 2012;42:35–48.
- 19. Vogt-Schilb H, Munoz F, Richard F, Schatz B. Recent declines and range changes of orchids in Western Europe (France, Belgium and Luxembourg). Biol Conserv. 2015;190:133–41.
- 20. McCormick MK, Jacquemyn H. What constrains the distribution of orchid populations? New Phytologist. 2013;202(2):392–400.
- 21. Traxmandlová I, Jersáková J, Kindlmann P. Orchid seed sensitivity to nitrate reflects habitat preferences and soil nitrate content. Plant Biol. 2018;21.
- 22. Djordjević V, Tsiftsis S. Patterns of orchid species richness and composition in relation to geological substrates. Wulfenia. 2019;26:1–21.
- 23. Landi M, Frignani F, Lazzeri C, Angiolini C. Abundance of orchids on calcareous grasslands in relation to community species, environmental, and vegetational conditions. Russ J Ecol. 2009;40:486–94.
- 24. Tsiftsis S, Štípková Z, Kindlmann P. Role of way of life, latitude, elevation and climate on the richness and distribution of orchid species. Biodiv Conserv. 2019;28:75–96.
- 25. Kirillova IA, Dubrovskiy YA, Degteva SV, Novakovskiy AB. Ecological and habitat ranges of orchids in the northernmost regions of their distribution areas: A case study from Ural Mountains, Russia. Plant Divers. 2023;45(2):211–8. pmid:37069927
- 26. Štípková Z, Ramportl D, Černocká V, Kindlmann P. Factors associated with the distributions of orchids in the Jeseníky Mountains, Czech Republic. Eur J Environ Sci. 2017;7:135–45.
- 27. Bartolucci F, Peruzzi L, Galasso G, Albano A, Alessandrini A, Ardenghi NMG, et al. An updated checklist of the vascular flora native to Italy. Plant Biosyst. 2018;152(2):179–303.
- 28. Ticktin T, Charitonidou M, Douglas J, Halley JM, Hernández-Apolinar M, Liu H. Wild orchids: a framework for identifying and improving sustainable harvest. Biol Conserv. 2023;277:109816.
- 29. Cencini C. Physical processes and human activities in the evolution of the Po delta, Italy. J Coast Res. 1998;:775–93.
- 30. Simeoni U, Corbau C. A review of the Delta Po evolution (Italy) related to climatic changes and human impacts. Geomorphology. 2009;107(1–2):64–71.
- 31. Slaviero A, Del Vecchio S, Pierce S, Fantinato E, Buffa G. Plant community attributes affect dry grassland orchid establishment. Plant Ecol. 2016;217(12):1533–43.
- 32. Ignatieva M, Hedblom M. An alternative urban green carpet: how can we move to sustainable lawns in a time of climate change?. Science. 2018;362:148–9.
- 33. Scramoncin L, Gerdol R, Brancaleoni L. How Effective Is Environmental Protection for Ensuring the Vitality of Wild Orchid Species? A Case Study of a Protected Area in Italy. Plants (Basel). 2024;13(5):610. pmid:38475457
- 34.
Alessandrini A, Balboni G, Brancaleoni L, Gerdol R, Nobili G, Pellizzari M. The vascular flora of the Bosco della Mesola Nature Reserve (Northern Italy). Cham, Switzerland: Springer Nature Switzerland AG; 2021.
- 35.
Piccoli F, Pellizzari M, Alessandrini A. Flora del Ferrarese. Ravenna, Italy: Istituto per i Beni Artistici Culturali e Naturali della Regione Emilia-Romagna; 2014.
- 36.
Braun-Blanquet J. Plant sociology: The study of plant communities. New York: McGraw-Hill; 1932.
- 37. Olsen SR, Cole CV, Watanabe FS, Dean LA. Estimation of available phosphorus in soils by extraction with sodium bicarbonate. USDA Circular. 1954;939:19.
- 38. Kempers AJ, Zweers A. Ammonium determination in soil extracts by the salicylate method. Commun Soil Sci Plant Anal. 1986;17(7):715–23.
- 39. Armstrong FAJ, Stearns CR, Strickland JDH. The measurement of upwelling and subsequent biological process by means of the Technicon Autoanalyzer® and associated equipment. Deep Sea Res Oceanogr Abstr. 1967;14(3):381–9.
- 40. Kedrowski RA. Extraction and analysis of nitrogen, phosphorus and carbon fractions in plant material. J Plant Nutr. 1983;6(11):989–1011.
- 41.
R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing; 2022.
- 42. Dolédec S, Chessel D, Gimaret-Carpentier C. Niche separation in community analysis: a new method. Ecol. 2000;81:2914–27.
- 43. Tichý L, Axmanová I, Dengler J, Guarino R, Jansen F, Midolo G, et al. Ellenberg-type indicator values for European vascular plant species. J Veg Sci. 2023;34:e13168.
- 44. Hammer O, Harper D, Ryan P. PAST: Paleontological Statistics Software Package for Education and Data Analysis. PE. 2001;4:1–9.
- 45. Diez JM, Pulliam HR. Hierarchical analysis of species distributions and abundance across environmental gradients. Ecology. 2007;88(12):3144–52. pmid:18229848
- 46. Wolken PM, Sieg CH, Williams SE. Quantifying Suitable Habitat of the Threatened Western Prairie Fringed Orchid. J Range Manag. 2001;54(5):611.
- 47. Araya YN, Gowing DJ, Dise N. Does soil nitrogen availability mediate the response of grassland composition to water regime? J Veg Sci. 2013;24:506–17.
- 48. Moeslund JE, Arge L, Bøcher PK, Dalgaard T, Ejrnaes R, Odgaard MV. Topographically controlled soil moisture drives plant diversity patterns within grasslands. Biodivers Conserv. 2013;22:21512166.
- 49.
Dearnaley J, Perotto S, Selosse MA. Structure and development of orchid mycorrhizas. In: Martin F, editor. Molecular Mycorrhizal Symbiosis. Hoboken (NJ): Wiley-Blackwell; 2016. pp. 63–86.
- 50. McCormick MK, Whigham DF, Canchani-Viruet A. Mycorrhizal fungi affect orchid distribution and population dynamics. New Phytol. 2018;219(4):1207–15. pmid:29790578
- 51. Wotavová K, Balounová Z, Kindlmann P. Factors affecting persistence of terrestrial orchids in wet meadows and implications for their conservation in a changing agricultural landscape. Biol Conserv. 2004;118:271–9.
- 52. Mujica MI, Saez N, Cisternas M, Manzano M, Armesto JJ, Pérez F. Relationship between soil nutrients and mycorrhizal associations of two Bipinnula species (Orchidaceae) from central Chile. Ann Bot. 2016;118(1):149–58. pmid:27311572
- 53. Fekete R, Löki V, Urgyán R, Süveges K, Lovas-Kiss Á, Vincze O, et al. Roadside verges and cemeteries: Comparative analysis of anthropogenic orchid habitats in the Eastern Mediterranean. Ecol Evol. 2019;9(11):6655–64. pmid:31236250
- 54. GardiNer T, Vaughan A. Scrub clearance and soil disturbance increases bee orchid Ophrys apifera frequency in calcareous grassland at Norton Heath road-side verge, Essex, England. Conserv Evid. 2009;6:39–41.
- 55. Popovich AV, Averyanova EA, Shagarov LM. Orchids of the Black Sea coast of Krasnodarsky Krai (Russia): current state, new records, conservation. Nat Conserv Res. 2020;5(Suppl 1):46–68.
- 56. Kirsch A, Kaproth MA. Defining plant ecological specialists and generalists: Building a framework for identification and classification. Ecol Evol. 2022;12(11):e9527. pmid:36440310
- 57. Poschlod P, WallisDeVries MF. The historical and socioeconomic perspective of calcareous grasslands–lessons from the distant and recent past. Biol Conserv. 2002;104:361–76.
- 58. Boulangeat I, Lavergne S, Van Es J, Garraud L, Thuiller W. Niche breadth, rarity and ecological characteristics within a regional flora spanning large environmental gradients. J Biogeogr. 2012;39:204–14.
- 59. de Medeiros CM, Hernández-Lambraño RE, Ribeiro KAF, Sánchez Agudo JA. Living on the edge: do central and marginal populations of plants differ in habitat suitability? Plant Ecol. 2018;219:1029–43.
- 60. Evans A, Jacquemyn H. Range size and niche breadth as predictors of climate-induced habitat change in Epipactis (Orchidaceae). Front Eco Evol. 2022;10:894616.
- 61. Tsiftsis S, Tsiripidis I. Temporal and spatial patterns of orchid species distribution in Greece: implications for conservation. Biodivers Conserv. 2020;29:3461–89.
- 62. Jacquemyn H, De Coensel B, Evans A, Deyi W, Merckx V. The relationship between phylogeny, range size, niche breadth and niche overlap in European orchids (Orchidaceae). J Biogeogr. 2024;51:409–21.
- 63. Hrivnák M, Slezák M, Galvánek D, Vlčko J, Belanová E, Rízová V, et al. Species Richness, Ecology, and Prediction of Orchids in Central Europe: Local-Scale Study. Diversity. 2020;12(4):154.
- 64. Kassen R. The experimental evolution of specialists, generalists, and the maintenance of diversity. J Evol Biol. 2002;15:173–90.
- 65. Stein A, Gerstner K, Kreft H. Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales. Ecol Lett. 2014;17(7):866–80. pmid:24751205
- 66. Blondel J. The ‘design’ of Mediterranean landscapes: a millennial story of humans and ecological systems during the historic period. Hum Ecol. 2006;34:713–29.
- 67. Tsirintanis K, Azzurro E, Crocetta F, Dimiza M, Froglia C, Gerovasileiou V, et al. Bioinvasion impacts on biodiversity, ecosystem services, and human health in the Mediterranean Sea. Aquat Invasions. 2022;17(3):308–52.
- 68. Schaffers AP, Sýkora KV. Reliability of Ellenberg indicator values for moisture, nitrogen and soil reaction: a comparison with field measurements. J Veg Sci. 2000;11:225–44.
- 69. Diekmann M. Species indicator values as an important tool in applied plant ecology – a review. Basic Appl Ecol. 2003;4(6):493–506.
- 70. Kukowski S, Ruser R, Piepho H, Gayler S, Streck T. Nitrogen dynamics of grassland soils with differing habitat quality: high temporal resolution captures the details. Ecosphere. 2023;14(4).
- 71. Rusjan S, Mikoš M. Seasonal variability of diurnal in-stream nitrate concentration oscillations under hydrologically stable conditions. Biogeochemistry. 2009;97(2–3):123–40.
- 72.
Djordjević V, Tsiftsis S. The role of ecological factors in distribution and abundance of terrestrial orchids. In: Merillon JM, Kodja H, editors. Orchids Phytochemistry, Biology and Horticulture. Cham, Switzerland: Springer Nature Switzerland AG; 2020. p. 3–72.
- 73. Wamelink GWW, Joosten V, van Dobben HF, Berendse F. Validity of Ellenberg indicator values judged from physico-chemical field measurements. J Veg Sci. 2002;113:269–78.
- 74. Zolotova E, Ivanova N, Ivanova S. Global Overview of Modern Research Based on Ellenberg Indicator Values. Diversity. 2023;15:14.