3. Results and discussion

orchid species [29–32], we suspected that these factors might be important for determination of the occurrence of these species and therefore we included them into the analyses. KVES without a number means the presence of the certain habitat class, therefore it is a categorical variable. If this proves to be statistically significant, it means that the occurrence of the corresponding orchid species depends on some habitat type. Sometimes also the environmental heterogeneity (here called KVES\_var—see Table 2), expressed as the number of different KVES types per unit area (sometimes also called "grain size" in the literature, especially in the landscape ecology jargon) may be important—large KVES\_var means that the landscape consists of a mosaic of many small units like fields, pastures, meadows, forests, and so on, which usually indicates low-intensity agriculture and subsequently a likely good habitat for protected species. Therefore, the KVES\_var is sometimes included in our analyses. Similarly, variable KVES\_maj provides information about

The KVES variable was used in Analysis 1, as described later. For any orchid species, particular vegetation types might be characteristic—for example, KVES\_4 (alluvial and wet meadows) may—according to our knowledge—characterize a typical habitat for Dactylorhiza majalis. Thus, in subsequent analyses, only those vegetation types, which we suspected as candidates for description of the presence of the corresponding orchid species, were selected, as described in Table 1. Detailed description of the particular KVES values is given in Table 2 only for those

In Analysis 1, the influence of climatic variables and other basic abiotic gradients on orchid distribution was studied. The list of these factors is shown in Table 1 and their description in Table 2. The climatic data were obtained from the Global Change Research Institute of the CAS and a climate character from a timeline of 1981–2011 was created. Besides of the climatic factors, we also added KVES and slope of the terrain [33] as additional factors that could influence the distribution of Dactylorhiza majalis and Platanthera bifolia. This analysis was aimed to test, to which extent climate may affect the occurrence of the studied orchid species. However, at least some of other most important environmental nonclimatic factors had to be included, too, in order not to indulge into a purely climatic model, which does not seem to be appropriate in our case—our knowledge and literature information tells us that climate itself is not able to fully explain presence of orchid species in these temperate and rather flat regions [29–32]. There was no risk in including these additional factors—if our expectation did not

As the results of Analysis 1 were not describing the presence of the studied species sufficiently in either of the studied species, we performed Analysis 2, which was more specific to selected environmental variables—particular KVES values. We selected these according to our experience and to the indications given in orchid literature—description of ecological requirements of the studied orchid species [29–32]. We also added the topographic position index (TPI), information about periodical floods (zapl\_pl), and the amount of arable land in the square of 500 to 500 m (orna\_p\_buff) and similarly the amount of arable land in the buffer zone of 250 m from particular orchid species (op\_buff), duration of vegetation season (veg\_sez), and vertical heterogeneity (vert\_het; see Table 1) as they might be important for the occurrence of particular orchid species. TPI classifies the landscape into slope position and landform category and

KVES factors used in the analyses. So, the three analyses were as follows.

come true, then these factors would just prove to be not significant.

dominant habitat type within the assessed zone.

138 Selected Studies in Biodiversity

#### 3.1. Dactylorhiza majalis (Rchb.) P.F.Hunt & Summerh

#### 3.1.1. Analysis 1: climatic factors

The jackknife procedure in Figure 2 indicates that many of the variables included in this analysis have a certain impact on this species. However, in Central Europe, because of the rather flat terrain, the mesoclimatic variables reflect the position in a particular region (such as South Bohemia, or Northern Moravia or so) rather than exact position of the point considered. In other words, the same set of mesoclimatic conditions characterizes a relatively large area, rather than a particular point. Therefore, the set of mesoclimatic variables found in the localities was characteristic for South Bohemia rather than for occurrence of orchids. For example, in Figure 3, there is not a clear trend, as the values are only precipitation values in the particular localities. Therefore, neither precipitation, nor other mesoclimatic variables were used for the

wet meadows (KVES\_4), mesophilic meadows (KVES\_6), in vegetation of standing waters (KVES\_18), and wetlands and coastal vegetation (KVES\_19). All these biotopes are wet, which is in agreement with ecological demands of this species [30–32]. According to our analysis, this species can also occur in urban green areas, gardens, parks, or cemeteries (KVES\_33), which was confirmed by our personal observation, and then in agricultural meadows (KVES\_39) that could become beneficial for orchid occurrence, if a suitable

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 141

Figure 3. Response of Dactylorhiza majalis to precipitation.

Figure 4. Graph of the jackknife procedure of environmental factors for Dactylorhiza majalis.

Figure 2. Graph of the jackknife procedure of climatic factors for Dactylorhiza majalis.

final analysis, even if their impact (especially that of precipitation) was high according to Figure 2. The only factor used for the final Analysis 3 was KVES.

#### 3.1.2. Analysis 2: environmental factors of biotope and surroundings

Figure 4 shows the effect of various factors examined to the distribution of D. majalis, according to this analysis. Clearly, KVES\_6 (mesophilic meadows) is the most important (the corresponding dark-blue bar is long). Also KVES\_var (habitat heterogeneity) and orna\_p\_buff (amount of arable land in the square of 500 to 500 m) are important.

A closer look at pictures of environmental variables that had a significant effect on the distribution of D. majalis (Figure 5) reveals certain patterns:


wet meadows (KVES\_4), mesophilic meadows (KVES\_6), in vegetation of standing waters (KVES\_18), and wetlands and coastal vegetation (KVES\_19). All these biotopes are wet, which is in agreement with ecological demands of this species [30–32]. According to our analysis, this species can also occur in urban green areas, gardens, parks, or cemeteries (KVES\_33), which was confirmed by our personal observation, and then in agricultural meadows (KVES\_39) that could become beneficial for orchid occurrence, if a suitable

Figure 3. Response of Dactylorhiza majalis to precipitation.

final analysis, even if their impact (especially that of precipitation) was high according to

Figure 4 shows the effect of various factors examined to the distribution of D. majalis, according to this analysis. Clearly, KVES\_6 (mesophilic meadows) is the most important (the corresponding dark-blue bar is long). Also KVES\_var (habitat heterogeneity) and orna\_p\_buff

A closer look at pictures of environmental variables that had a significant effect on the distri-

• Figure 5A indicates the impact of mesophilic meadows (KVES\_6) on the distribution of this species. It is clearly visible that the more mesophilic meadows are present, the bigger

• Figure 5B shows that D. majalis prefers landscape consisting of a mosaic of many smaller biotopes. This confirms our expectation that this species is more likely to occur in such

• Figure 5C shows that D. majalis is less likely to occur in landscapes with a large proportion of arable land. This is in accord with the published literature, which confirms that Dactylorhiza majalis is sensitive to any kind of eutrophication from arable fields that contain artificial fertilizers full of nitrogen and phosphorus [29–32]. These fertilizers are the cause of extinction of some localities because the more arable land is present around a

• Figure 5D shows the dependence of the likelihood of presence of D. majalis to various subfactors of KVES. The most suitable biotopes indicated by this figure are alluvial and

landscapes, probably because they are characteristic for low-intensity agriculture.

suitable locality, the lower is the probability of occurrence of this species.

Figure 2. The only factor used for the final Analysis 3 was KVES.

Figure 2. Graph of the jackknife procedure of climatic factors for Dactylorhiza majalis.

140 Selected Studies in Biodiversity

3.1.2. Analysis 2: environmental factors of biotope and surroundings

(amount of arable land in the square of 500 to 500 m) are important.

bution of D. majalis (Figure 5) reveals certain patterns:

likelihood of occurrence of the studied species.

Figure 4. Graph of the jackknife procedure of environmental factors for Dactylorhiza majalis.

and dried. Because of this, some of the existing localities are in the vicinity of wet meadows and some are not. But still we can see a trend that higher occurrence of D. majalis is in the vicinity of alluvial and wet meadows, and therefore use this factor in the

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 143

• Figure 5F shows the impact of vertical heterogeneity on the occurrence of D. majalis. According to this graph, this species occurs more in flat areas without stronger ripple of terrain. This is not surprising, because it is a meadow species. This factor was not used in

This final analysis was prepared on the basis of the most important factors, which were determined from the previous analyses mentioned above. These factors are KVES\_6 (presence of mesophilic meadows around the locality), KVES\_4 (presence of alluvial and wet meadows around the locality), KVES (consolidated layer of ecosystems) in general, op\_buff (cover of arable land in the buffer zone of 250 m from particular orchid species), and KVES\_var (habitat heterogeneity). Alkalinity and reactivity of rocks in the bedrock near the selected locality were also added into this analysis. The resolution of the final potential distribution map (Figure 6) was set to a square grid of 50 50 m to make the map more precise and detailed for determining possible new localities with suitable conditions for D. majalis. This map shows there are other suitable localities for potential occurrence of the studied species in the region of South Bohemia; they are located in the surroundings of cities of Vyšší Brod, Jistebnice, Blatná, and Stachy. Suitable places are also around the Šumava National park and to the east of Kunžak city and the city of Jindřichův Hradec. This distribution map can help us to find new, yet unknown localities of D. majalis and be useful for conservation strategies of this endan-

Figure 7 shows the effect of the most important factors examined to the distribution of D. majalis. The responses of the species to selected factors are quite high, so we were right with the selection of environmental factors. Clearly, the most important factor is KVES (consolidated layer of ecosystems). Other important factors are also KVES\_6 (presence of mesophilic meadows around the locality) and KVES\_var (habitat heterogeneity). According to this analysis, alkalinity and reactivity of rocks, the newly added factors, have the lowest impact on occurrence of D. majalis. It is caused by broad ecological demands of this species to pH

A closer look at pictures of the most important variables that had a significant effect on the

• Figure 8A shows the dependence of the likelihood of presence of D. majalis to various subfactors of KVES after the accuracy improvement of resolution. According to this figure, the most suitable biotopes for this species are alluvial and wet meadows (KVES\_4), mesophilic meadows (KVES\_6), wetlands and coastal vegetation (KVES\_19), peat bogs and water springs (KVES\_20), and green urbans areas, gardens, or parks (KVES\_33). The occurrence of this species was also recorded in natural shrubs (KVES\_17), swamps and

distribution of D. majalis (Figure 8) reveals some interesting patterns:

the final analysis, however, because the dependence found was not strong.

3.1.3. Analysis 3: final analysis of the most important factors from the two previous analyses

final Analysis 3.

gered species in the Czech Republic.

conditions in the soil [29–32].

Figure 5. Response of Dactylorhiza majalis to: (A) presence of mesophilic meadows around the locality (KVES\_6), (B) habitat heterogeneity (KVES\_var), (C) cover of arable land around the locality (orna\_p\_buff;), (D) consolidated layer of ecosystems (KVES), (E) presence of alluvial and wet meadows around the locality (KVES\_4), and (F) vertical heterogeneity (vert\_het).

management is applied. We can also see some inconsistencies in occurrence of D. majalis: its occurrence in dry pine groves (KVES\_13) and mixed forests (KVES\_30). Dry pine groves are not a suitable habitat for this species; this strange result could have been caused by border zone of two different habitat types. In mixed forests, a clearing could be a possible habitat.

• Figure 5E shows the dependence of the probability of occurrence of D. majalis on the presence of alluvial and wet meadows around the locality. The curve in the graph implies that there is a larger probability of occurrence of this species in areas with at least some of these types of habitats. We expected that there will be bigger dependence on wet meadows, but our data did not confirm this, which is interesting. We assume this might have been caused by human impact, because the studied area lies outside of larger protected areas. Wet meadows are not suitable for agriculture, because agricultural machinery is not able to work here and some of such meadows were extensively changed and dried. Because of this, some of the existing localities are in the vicinity of wet meadows and some are not. But still we can see a trend that higher occurrence of D. majalis is in the vicinity of alluvial and wet meadows, and therefore use this factor in the final Analysis 3.

• Figure 5F shows the impact of vertical heterogeneity on the occurrence of D. majalis. According to this graph, this species occurs more in flat areas without stronger ripple of terrain. This is not surprising, because it is a meadow species. This factor was not used in the final analysis, however, because the dependence found was not strong.

#### 3.1.3. Analysis 3: final analysis of the most important factors from the two previous analyses

This final analysis was prepared on the basis of the most important factors, which were determined from the previous analyses mentioned above. These factors are KVES\_6 (presence of mesophilic meadows around the locality), KVES\_4 (presence of alluvial and wet meadows around the locality), KVES (consolidated layer of ecosystems) in general, op\_buff (cover of arable land in the buffer zone of 250 m from particular orchid species), and KVES\_var (habitat heterogeneity). Alkalinity and reactivity of rocks in the bedrock near the selected locality were also added into this analysis. The resolution of the final potential distribution map (Figure 6) was set to a square grid of 50 50 m to make the map more precise and detailed for determining possible new localities with suitable conditions for D. majalis. This map shows there are other suitable localities for potential occurrence of the studied species in the region of South Bohemia; they are located in the surroundings of cities of Vyšší Brod, Jistebnice, Blatná, and Stachy. Suitable places are also around the Šumava National park and to the east of Kunžak city and the city of Jindřichův Hradec. This distribution map can help us to find new, yet unknown localities of D. majalis and be useful for conservation strategies of this endangered species in the Czech Republic.

Figure 7 shows the effect of the most important factors examined to the distribution of D. majalis. The responses of the species to selected factors are quite high, so we were right with the selection of environmental factors. Clearly, the most important factor is KVES (consolidated layer of ecosystems). Other important factors are also KVES\_6 (presence of mesophilic meadows around the locality) and KVES\_var (habitat heterogeneity). According to this analysis, alkalinity and reactivity of rocks, the newly added factors, have the lowest impact on occurrence of D. majalis. It is caused by broad ecological demands of this species to pH conditions in the soil [29–32].

management is applied. We can also see some inconsistencies in occurrence of D. majalis: its occurrence in dry pine groves (KVES\_13) and mixed forests (KVES\_30). Dry pine groves are not a suitable habitat for this species; this strange result could have been caused by border zone of two different habitat types. In mixed forests, a clearing could be a

Figure 5. Response of Dactylorhiza majalis to: (A) presence of mesophilic meadows around the locality (KVES\_6), (B) habitat heterogeneity (KVES\_var), (C) cover of arable land around the locality (orna\_p\_buff;), (D) consolidated layer of ecosystems (KVES), (E) presence of alluvial and wet meadows around the locality (KVES\_4), and (F) vertical heterogene-

• Figure 5E shows the dependence of the probability of occurrence of D. majalis on the presence of alluvial and wet meadows around the locality. The curve in the graph implies that there is a larger probability of occurrence of this species in areas with at least some of these types of habitats. We expected that there will be bigger dependence on wet meadows, but our data did not confirm this, which is interesting. We assume this might have been caused by human impact, because the studied area lies outside of larger protected areas. Wet meadows are not suitable for agriculture, because agricultural machinery is not able to work here and some of such meadows were extensively changed

possible habitat.

ity (vert\_het).

142 Selected Studies in Biodiversity

A closer look at pictures of the most important variables that had a significant effect on the distribution of D. majalis (Figure 8) reveals some interesting patterns:

• Figure 8A shows the dependence of the likelihood of presence of D. majalis to various subfactors of KVES after the accuracy improvement of resolution. According to this figure, the most suitable biotopes for this species are alluvial and wet meadows (KVES\_4), mesophilic meadows (KVES\_6), wetlands and coastal vegetation (KVES\_19), peat bogs and water springs (KVES\_20), and green urbans areas, gardens, or parks (KVES\_33). The occurrence of this species was also recorded in natural shrubs (KVES\_17), swamps and marshes (KVES\_23), and in sports and recreational areas (KVES\_34). These types of biotopes could be also suitable for D. majalis because most of them are wet or somehow maintained, for example, by mowing (such as recreational areas or parks) and this species was really found in the field in these kinds of biotopes. Biotope of dry pine groves

(KVES\_13) was correctly excluded from the analysis as an unsuitable biotope for the

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 145

• Figure 8B shows another factor, which has an important impact on the occurrence of this species. It indicates that D. majalis prefers landscape consisting of a mosaic of many smaller biotopes, as was proved in the previous analysis. This confirms our expectation that this species could more likely be found in these types of landscapes, probably because

• Figure 8C shows the impact of alkalinity of rocks in bedrock of the locality on the occurrence of D. majalis. It is visible that this species occurs on many types of rocks from the point of view of their pH values and does not prefer any specific type of bedrock. However, its occurrence is more frequent on more acidic soils, probably because wet

• Figure 8D shows the impact of mesophilic meadows (KVES\_6) on the distribution of D. majalis. According to the final jackknife procedure (Figure 7), this factor had an important impact on the occurrence of studied species. Figure 8D indicates that this species is more likely to occur in areas in the vicinity of at least some part of this biotope. But there is no curve of growth or decline in the graph that could be clearly interpretable. So we could presume that D. majalis prefers an area where mesophilic meadows are present, because

Figure 8. Response of Dactylorhiza majalis to: (A) consolidated layer of ecosystems (KVES), (B) habitat heterogeneity (KVES\_var), (C) alkalinity of rocks in a bedrock (alkali), and (D) presence of mesophilic meadows around the locality

occurrence of D. majalis because of the accuracy improvement of resolution.

they are not changed so much by the intensity of agriculture.

localities have usually lower pH values.

(KVES\_6).

Figure 6. Potential distribution map of Dactylorhiza majalis in the region of South Bohemia.

Figure 7. Graph of the final jackknife procedure of the most important factors for Dactylorhiza majalis.

(KVES\_13) was correctly excluded from the analysis as an unsuitable biotope for the occurrence of D. majalis because of the accuracy improvement of resolution.

marshes (KVES\_23), and in sports and recreational areas (KVES\_34). These types of biotopes could be also suitable for D. majalis because most of them are wet or somehow maintained, for example, by mowing (such as recreational areas or parks) and this species was really found in the field in these kinds of biotopes. Biotope of dry pine groves

144 Selected Studies in Biodiversity

Figure 6. Potential distribution map of Dactylorhiza majalis in the region of South Bohemia.

Figure 7. Graph of the final jackknife procedure of the most important factors for Dactylorhiza majalis.


Figure 8. Response of Dactylorhiza majalis to: (A) consolidated layer of ecosystems (KVES), (B) habitat heterogeneity (KVES\_var), (C) alkalinity of rocks in a bedrock (alkali), and (D) presence of mesophilic meadows around the locality (KVES\_6).

these types of meadows are suitable for its occurrence [29, 30, 32]. However, an interpretation that the occurrence of D. majalis is strongly dependent on the presence of mesophilic meadows near the locality would be incorrect.

#### 3.2. Platanthera bifolia (L.) Rich.

#### 3.2.1. Analysis 1: climatic factors

The results of the jackknife procedure in Figure 9 revealed that the consolidated layer of ecosystem (KVES) is the most important factor influencing the distribution of Platanthera bifolia. Other important factors are solar radiation (solar\_rad) and slope of the terrain (slope). Again, we did not use the precipitation for further analyses because of reasons described earlier (in Analysis 1 for Dactylorhiza majalis).

A closer look at pictures of factors from Analysis 1 that had a significant effect on the distribution of P. bifolia (Figure 10) shows interesting results.


• Figure 10C shows the impact of a slope of terrain on the occurrence of P. bifolia. According to this picture, there is a low possibility to find this species in a completely flat landscape.

Figure 10. Response of Platanthera bifolia to: (A) consolidated layer of ecosystems (KVES), (B) solar radiation (solar\_rad),

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 147

Figure 11 shows the effect of various environmental factors examined on the distribution of Platanthera bifolia, according to this analysis. Clearly, the presence of dry grasslands (KVES\_5) is the most important factor. Other important factors are habitat heterogeneity (KVES\_var), vertical heterogeneity (vert\_het), and the amount of arable land in the square of 500 500 m

A closer look at the pictures of environmental variables that had a significant effect on the

• Figure 12A shows the impact of vertical heterogeneity on the occurrence of studied species. This factor explains how much rolling is the landscape near the selected locality (amount of different altitudes). It is visible that there is almost zero probability of occurrence of this species in a flat landscape which means that P. bifolia prefers a heterogeneous landscape with hills and valleys. This is in accordance with the results of Analysis 1 of this species (Figure 10C), where the slope of terrain was one of the most important factors.

This means that it prefers a specific change of altitudes in given area.

3.2.2. Analysis 2: environmental factors of biotope and surroundings

distribution of Platanthera bifolia (Figure 12) reveals certain patterns:

(orna\_p\_buff).

and (C) slope of the terrain (slope).

Figure 9. Graph of the jackknife procedure of climatic factors for Platanthera bifolia.

Figure 10. Response of Platanthera bifolia to: (A) consolidated layer of ecosystems (KVES), (B) solar radiation (solar\_rad), and (C) slope of the terrain (slope).

• Figure 10C shows the impact of a slope of terrain on the occurrence of P. bifolia. According to this picture, there is a low possibility to find this species in a completely flat landscape. This means that it prefers a specific change of altitudes in given area.

#### 3.2.2. Analysis 2: environmental factors of biotope and surroundings

these types of meadows are suitable for its occurrence [29, 30, 32]. However, an interpretation that the occurrence of D. majalis is strongly dependent on the presence of mesophilic

The results of the jackknife procedure in Figure 9 revealed that the consolidated layer of ecosystem (KVES) is the most important factor influencing the distribution of Platanthera bifolia. Other important factors are solar radiation (solar\_rad) and slope of the terrain (slope). Again, we did not use the precipitation for further analyses because of reasons described

A closer look at pictures of factors from Analysis 1 that had a significant effect on the distribu-

• Figure 10A indicates which type of biotope (KVES) this species prefers. It was found mostly in oak and oak-hornbeam forests (KVES\_10), beech forests (KVES\_12), and also in mixed forests (KVES\_30). These results are in agreement with our knowledge and information from the literature [29, 30, 32], because this is a forest species and prefers similar

• Figure 10B shows a response of the studied species to solar radiation (solar\_rad), a typical mesoclimatic factor. In the Czech Republic, the extent of solar radiation is not different across the whole country so this factor tells us, whether P. bifolia prefers shadow or sunny places. From this graph, it is clearly visible that it is more likely to find this species in shady places. As it was said before, it is in accordance with information from literature [29–32].

meadows near the locality would be incorrect.

3.2. Platanthera bifolia (L.) Rich.

earlier (in Analysis 1 for Dactylorhiza majalis).

types of deciduous forests.

tion of P. bifolia (Figure 10) shows interesting results.

Figure 9. Graph of the jackknife procedure of climatic factors for Platanthera bifolia.

3.2.1. Analysis 1: climatic factors

146 Selected Studies in Biodiversity

Figure 11 shows the effect of various environmental factors examined on the distribution of Platanthera bifolia, according to this analysis. Clearly, the presence of dry grasslands (KVES\_5) is the most important factor. Other important factors are habitat heterogeneity (KVES\_var), vertical heterogeneity (vert\_het), and the amount of arable land in the square of 500 500 m (orna\_p\_buff).

A closer look at the pictures of environmental variables that had a significant effect on the distribution of Platanthera bifolia (Figure 12) reveals certain patterns:

• Figure 12A shows the impact of vertical heterogeneity on the occurrence of studied species. This factor explains how much rolling is the landscape near the selected locality (amount of different altitudes). It is visible that there is almost zero probability of occurrence of this species in a flat landscape which means that P. bifolia prefers a heterogeneous landscape with hills and valleys. This is in accordance with the results of Analysis 1 of this species (Figure 10C), where the slope of terrain was one of the most important factors.

• Figure 12B shows the relationship between the presence of P. bifolia and habitat heterogeneity (KVES\_var). Clearly, this species prefers areas with higher heterogeneity of the environment; it means areas which consist of many small habitats. The probability of presence of this species in an area made of only one single habitat is almost zero. An increasing amount

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 149

• The impact of a presence of dry grasslands (KVES\_5) near the locality with P. bifolia is shown in Figure 12C. This species prefers areas, the surroundings of which consist of dry grasslands. We can imagine a suitable locality as small patches of forests surrounded mainly by grasslands. Clearly, this factor is related with the previous one, the environmental heterogeneity. This species does not occur in the cultural landscape, but it prefers

• Figure 12D shows a relationship between the occurrence of the study species and amount of arable land. From this picture, it follows that P. bifolia favors an area without arable land in its surroundings. If there are some areas with arable fields, the probability of occurrence

The choice of the most important factors influencing the occurrence of Platanthera bifolia was based on the results of the two previous analyses mentioned above. For the final analysis, consolidated layer of ecosystems (KVES), solar radiation (solar\_rad), vertical heterogeneity (vert\_het), habitat heterogeneity (KVES\_var), amount of arable land in the buffer zone of 250 m from the corresponding orchid species site (op\_buff), and the presence of dry grassland (KVES\_5) were chosen as the most important factors. Alkalinity and reactivity of rocks in the bedrock were also added into this final analysis. The resolution of the final potential distribution map of P. bifolia (Figure 13) was again set to a square grid of 50 50 m to make the map more precise, as was the same case with the previous species. According to this map, there are still some places in the studied region that are suitable for a new occurrence of this species. The most suitable places for finding new localities are around the city of Sezimovo Ústí, Tábor, and Písek, then also to the south of Strakonice city and along the upper stretch of the Vltava River. This map could encourage orchid conservationists to find new, yet unknown, localities of this

Figure 14 shows responses of P. bifolia to the most important factors that influence its distribution in studied region. Clearly, the most important factors were consolidated layer of ecosystems (KVES), the presence of dry grasslands (KVES\_5), the alkalinity of rocks in a bedrock (alkali), and vertical heterogeneity (vert\_het). But all of factors that were chosen for final

A closer look at the picture of all factors used in Analysis 3 (Figure 15) revealed some important information about the influence of individual factors on the distribution of P. bifolia: • Figure 15A shows the dependence of the likelihood of the distribution of P. bifolia on various subfactors of KVES. Clearly, the highest occurrence of this species was in dry

analysis had an interesting impact on the occurrence of this species.

of agricultural areas and arable lands make P. bifolia more and more endangered.

heterogeneous environment made of meadows and small patches of forests.

3.2.3. Analysis 3: final analysis of the most important factors from the two previous analyses

of studied species rapidly decreases to almost zero.

endangered species of the Czech flora.

Figure 11. Graph of the jackknife procedure of environmental factors for Platanthera bifolia.

Figure 12. Response of Platanthera bifolia to: (A) vertical heterogeneity (vert\_het), (B) habitat heterogeneity (KVES\_var), (C) presence of dry grasslands (KVES\_5), and (D) amount of arable land in the square of 500 to 500 m (orna\_p\_buff).


#### 3.2.3. Analysis 3: final analysis of the most important factors from the two previous analyses

Figure 11. Graph of the jackknife procedure of environmental factors for Platanthera bifolia.

148 Selected Studies in Biodiversity

Figure 12. Response of Platanthera bifolia to: (A) vertical heterogeneity (vert\_het), (B) habitat heterogeneity (KVES\_var), (C) presence of dry grasslands (KVES\_5), and (D) amount of arable land in the square of 500 to 500 m (orna\_p\_buff).

The choice of the most important factors influencing the occurrence of Platanthera bifolia was based on the results of the two previous analyses mentioned above. For the final analysis, consolidated layer of ecosystems (KVES), solar radiation (solar\_rad), vertical heterogeneity (vert\_het), habitat heterogeneity (KVES\_var), amount of arable land in the buffer zone of 250 m from the corresponding orchid species site (op\_buff), and the presence of dry grassland (KVES\_5) were chosen as the most important factors. Alkalinity and reactivity of rocks in the bedrock were also added into this final analysis. The resolution of the final potential distribution map of P. bifolia (Figure 13) was again set to a square grid of 50 50 m to make the map more precise, as was the same case with the previous species. According to this map, there are still some places in the studied region that are suitable for a new occurrence of this species. The most suitable places for finding new localities are around the city of Sezimovo Ústí, Tábor, and Písek, then also to the south of Strakonice city and along the upper stretch of the Vltava River. This map could encourage orchid conservationists to find new, yet unknown, localities of this endangered species of the Czech flora.

Figure 14 shows responses of P. bifolia to the most important factors that influence its distribution in studied region. Clearly, the most important factors were consolidated layer of ecosystems (KVES), the presence of dry grasslands (KVES\_5), the alkalinity of rocks in a bedrock (alkali), and vertical heterogeneity (vert\_het). But all of factors that were chosen for final analysis had an interesting impact on the occurrence of this species.

A closer look at the picture of all factors used in Analysis 3 (Figure 15) revealed some important information about the influence of individual factors on the distribution of P. bifolia:

• Figure 15A shows the dependence of the likelihood of the distribution of P. bifolia on various subfactors of KVES. Clearly, the highest occurrence of this species was in dry

grasslands (KVES\_5) and in oak and oak-hornbeam forests (KVES\_10). This species has a broad ecological valence and occurs both in forest and meadow biotopes that are poor in nutrients [29–31]. Because of this, all depicted biotopes in the picture that have a higher

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 151

• In Figure 15B, the impact of dry grasslands (KVES\_5) on the occurrence of P. bifolia is depicted. It is clearly visible that with higher amount of grasslands near the selected locality, there is also a higher probability of the occurrence of the studied species. It means that this species prefers an area where grasslands are the dominating biotope in the surrounding of the selected locality. We can assume that this kind of biotope is preferable for P. bifolia because it is not managed intensively by humans and therefore no damage to

Figure 15. Response of Platanthera bifolia to: (A) consolidated layer of ecosystems (KVES), (B) presence of dry grasslands (KVES\_5), (C) alkalinity of rocks in a bedrock (alcali), (D) vertical heterogeneity (vert\_het), (E) habitat heterogeneity (KVES\_var), (F) amount of arable land in the buffer zone of 250 m from particular orchid species (op\_buff), (G) solar

radiation (solar\_rad), and (H) reactivity of rocks in a bedrock (reactivity).

probability of presence than 0.3 are suitable for presence of P. bifolia.

suitable places by eutrophication or agricultural activities happens.

Figure 13. Potential distribution map of Platanthera bifolia in the region of South Bohemia.

Figure 14. Graph of the final jackknife procedure of the most important factors influencing the occurrence of Platanthera bifolia.

grasslands (KVES\_5) and in oak and oak-hornbeam forests (KVES\_10). This species has a broad ecological valence and occurs both in forest and meadow biotopes that are poor in nutrients [29–31]. Because of this, all depicted biotopes in the picture that have a higher probability of presence than 0.3 are suitable for presence of P. bifolia.

• In Figure 15B, the impact of dry grasslands (KVES\_5) on the occurrence of P. bifolia is depicted. It is clearly visible that with higher amount of grasslands near the selected locality, there is also a higher probability of the occurrence of the studied species. It means that this species prefers an area where grasslands are the dominating biotope in the surrounding of the selected locality. We can assume that this kind of biotope is preferable for P. bifolia because it is not managed intensively by humans and therefore no damage to suitable places by eutrophication or agricultural activities happens.

Figure 13. Potential distribution map of Platanthera bifolia in the region of South Bohemia.

bifolia.

150 Selected Studies in Biodiversity

Figure 14. Graph of the final jackknife procedure of the most important factors influencing the occurrence of Platanthera

Figure 15. Response of Platanthera bifolia to: (A) consolidated layer of ecosystems (KVES), (B) presence of dry grasslands (KVES\_5), (C) alkalinity of rocks in a bedrock (alcali), (D) vertical heterogeneity (vert\_het), (E) habitat heterogeneity (KVES\_var), (F) amount of arable land in the buffer zone of 250 m from particular orchid species (op\_buff), (G) solar radiation (solar\_rad), and (H) reactivity of rocks in a bedrock (reactivity).

• Figure 15C indicates the dependence of the occurrence of the studied species on the alkalinity of rocks in the vicinity of a locality (alcali). According to literature information, this species favors slightly acidic, as well as alkaline soils [30–32]. Clearly, this species mostly occurred in the soil type number 4 and prefers soils with high index of alkalinity between 0.25 and 0.4 mol/kg. This index is a ratio of different amounts of components in a rock and corresponds to alkaline soils [34].

flora and their conservation to focus only on certain areas with the highest probability of

Basically, this work should serve as tool for better conservation of orchids and clear the way for understanding of important factors determining their distribution in the Czech Republic.

This work was supported by the Ministry of Education, Youth, and Sports of the CR within the

1 Global Change Research Institute, Czech Academy of Science, Brno, Czech Republic 2 Institute for Environmental Studies, Faculty of Science, Charles University, Prague,

3 Department of Physical Geography and Geoecology, Faculty of Science, Charles University,

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[2] Possingham HP, Wilson KA. Biodiversity - turning up the heat on hotspots. Nature. 2005;

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[4] Efimov PG. Revealing the decline and expansion of orchids of NW European Russia.

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, Dušan Romportl1,3 and Pavel Kindlmann1,2

Determinants of Orchid Occurrence: A Czech Example http://dx.doi.org/10.5772/intechopen.74851 153

National Sustainability Program I (NPU I), grant number LO1415.

occurrence of the selected species.

Zuzana Štípková1,2\*, Kristina Kosánová2

436:919-920. DOI: 10.1038/436919a

University Press; 1993. 321 p

\*Address all correspondence to: zaza.zuza@seznam.cz

Acknowledgements

Author details

Czech Republic

References

Prague, Czech Republic

