The loss of biodiversity is one of the major challenges of our civilization, and to stop or slow down it the effective use of limited resources is crucial. The conservation of the remaining natural and semi-natural sites needs prioritization and planning. Although insect orders are the most diverse terrestrial taxa, generally the vertebrates such as amphibians, birds and mammals are used in conservation prioritization (Ceballos and Ehrlich 2006). Databases including distribution data of different taxa can be successfully used for conservation prioritization through designation of biodiversity hotspots based on species richness, and number of rare and/or vulnerable species (Gaston and David 1994; Reid 1998; Sólymos and Fehér 2005; Sólymos et al. 2006). To regard the conservation value of species is more effective than prioritization based on the simple alpha diversity indices, which are usually affected by common or even invasive species (Matenaar et al. 2015).

In Central Europe secondary grasslands formed by long-term extensive use maintain especially high insect diversity endangered by habitat fragmentation and secondary succession caused by abandonment and intensification of land use (fertilization and intensive grazing or mowing) (Fischer and Stöcklin 1997; Bakker and Berendse 1999; Balmer and Erhardt 2000). In Hungary secondary grasslands of the Aggtelek Karst are among the most typical sites of these species-rich secondary grasslands. The invertebrate fauna considering molluscs (Deli 2002; Farkas 2008; Sólymos et al. 2009), isopods (Kontschán 2004; Vilisics et al. 2008), lepidopterans (Szabó et al. 2007; Végvári et al. 2015) and carabid beetles (Szél 1999; Magura and Lövei 2017) is well known, and in case of orthopterans this is the most studied region of Hungary (Rácz et al. 2003; Nagy and Rácz 2007a). Since 2005, when the last review of the Orthoptera fauna was made (Nagy and Rácz 2007b; Nagy 2008) intensive studies have been carried out in the National Biodiversity Monitoring Program (Kovács-Láng et al. 2000).

Because of their large abundance, relatively high species richness, diverse life forms and their crucial role in the food chain orthopterans are one of the most important taxa of grasslands all over the World (Sinclair 1975; Gardiner et al. 2005). They are sensitive indicators of changes in vegetation structure and naturalness (Marshall 2010; Benton 2012; Cherrill 2015) and widely used in grassland ecology and conservation planning (Noss 1990; Spellerberg 1991; Pearson 1994; Báldi and Kisbenedek 1997; Batáry et al. 2007; Torma et al. 2014; Kenyeres et al. 2020).

Using the detailed and carefully revised distribution data of the Orthoptera fauna of the Aggtelek Karst region (North Hungary) priorities of conservation and further studies of the fauna were designated based on alpha diversity and distribution of rare and protected species. Additionally, a new approach of Grasshopper Conservation Index (GCI, Matenaar 2015; Szanyi et al. 2021; Arnóczkyné and Nagy 2022) calculating with local and regional frequencies and moving ability of species was also used to evaluate the natural value of different sampling sites.

Materials and methods

Source of distribution data

The database includes Orthoptera distribution data from the Aggtelek National Park (Fig. 1) was built with former published and newly collected partly unpublished data of several researchers. The studies have four periods (Table 1). From the first period unpublished data of Barnabás Nagy, István Rácz and Zoltán Varga are available, and papers of Rácz (1992), Rácz et al. (2003), Parragh (1983) and Garay (2002) contain reliable data. Between 1981 and 1993 (in the 2nd period) samplings become more intensive and Parragh (1983, 1987), Mező (1991, 1992) and Garay (1995) published their results, and some unpublished data of István Rácz and Zoltán Varga also could be found. The most intensive studies were carried out in the 3rd period. Kirill M. Orci made intensive samplings in the grassland patches of the plateau above Jósvafő and in the former vineyards and hayfields of the Szőlő-hegy near the village. Between 1998 and 2005 Antal Nagy continued these samplings and parallelly studied many other parts of the karst region. Most of the results were published in Orci (1997a, 1997b), Rácz et al. (2003, 2007), Nagy (2008), Nagy and Rácz (2007a), Nagy and Sólymos (2002), Nagy et al. (2003, 2005), Jordán (2003), Jordán et al. (2003) and Pecsenye et al. (2003a, 2003b). By 2005 Orthoptera assemblages of 67 locations had been studied and considering the estimated species richness the exploration of the fauna was 97.8% (Nagy 2008).

Fig. 1
figure 1

Map of the Aggtelek National Park and its surroundings with Orthoptera sampling sites (n = 98) have been studied since 1958

Table 1 Researchers of the Orthoptera fauna of the Aggtelek Karst and the periods of the studies: 1st period: 1958–1980., 2nd period: 1981–1993., 3rd period: 1994–2005, 4th period: 2006–2022

After 2005 most of the samplings were made by Antal Nagy in the National Biodiversity Monitoring Project and the results were recorded in scientific reports made for the Aggtelek National Park. In this latter period some studies designed on the basis of the priorities designated in the first review of the fauna (Nagy and Rácz 2007b; Nagy 2008) were also carried out (e.g. samplings of the Szalonna Karst and Rudabánya Hills and samplings for validation of doubtful data of Isophya stysi Cejchan). The result of reanalysis of Pholidoptera transsylvanica Fischer habitat network was published by Benedek et al. (2011), while studies on the wing polymorphism of the Roeseliana roeselii Hagenbach were published by Szanyi et al. (2014).

The critical review of the sampling sites and distribution data was made in 2007. After that only valid and complete data (with site name, coordinate, date, species name and collector name) were upload to the database.

The samplings were made mainly with sweep-netting and transect count, additionally between 1994 and 1999 dish traps were also used. P. transsylvanica included in habitat directive Annex II and N2000 was sampled also with the acoustic detection method during the mapping of its distribution and estimation of population size.

In 2022 the actualized and revised database contained data of 98 sites (Fig. 1) and 77 species (Appendix Tables 4 and 5). Considering Acheta domestica, Conocephalus dorsalis, Leptophyes punctatissima, Stethophyma grossum, Myrmeleotettix maculatus, Platycleis affinis, Polysarcus denticauda and Poecilimon intermedius only data collected in the first and second periods (> 30 year) of the studies were available. Additionally, A. domestica and P. denticauda data are localized only with village names. These species were excluded from the further analysis, and thus, it was performed with 69 species and 98 sites. Considering nomenclature and taxonomy the Fauna Europaea online database was followed (; Heller and Willemse 2023).

Table 2 Result of the area selection of simple ranking and complementary areas methods using different indices in the Aggtelek National Park

Identifying diversity hotspots

The sites were prioritized based on both simple ranking and complementarity using the actualized distribution data of local Orthoptera fauna (Williams et al. 1996; Reid 1998; Margules and Pressey 2000). During the ranking of sites species richness (S), rarity weighted species richness (SR) and number of rare species (SQ) were used as scoring indices. Species richness of the areas and the sampling intensity showed significant correlation (Pearson r = 0.736, p < 0.001). Methods for estimation of species richness (Soberón and Llorente 1993; Colwell and Coddington 1994) can be limitedly used in area prioritization since they can correct only the species richness, but do not regard the qualitative composition of the fauna. During the analysis the equal sampling intensity was assumed, and species richness (S) were determined as the number of species of orthopterans recorded in each site. The rarity weighted species richness (SR) is a sum of rarity scores (Rc) calculated from country wide relative frequency (spatial constancy) (xic) of the species using Rc = 1−xic equation. The xic values were provided by Nagy and Rácz (2007a) based on the ratio of UTM cells occupied by a given species to all Hungarian 10 × 10 km UTM cells with Orthoptera data. Rc is maximal if a given species occupies only one UTM cell and 0 if a given species appears in all occupied cells. The number of rare species (SQ) were established based on the quartile definition of rarity (Gaston 1994) using country wide relative frequencies of the species (xic) provided by Nagy and Rácz (2007a).

During simple ranking areas was arranged by the single indices listed above. After that 5% and 10% of sites with the highest values (5 and 10 sites) were chosen. In the case of the complementarity algorithm sites minimally necessary for cover the whole fauna were selected. This algorithm tries to cover the highest species richness with selection of the lowest number of sites (Church et al. 1996; Justus and Sarkar 2002). During the analysis first the site with highest score were selected and all species represented there were removed from the data set. Then the selection criteria scores were recalculated, and this process was repeated until all the species were accounted for. The analysis was carried out manually with MS Excel environment. During the ranking, if two or more areas have equal values their selection lead to the same result. To improve the performance of the algorithms redundancy check was carried out (Csuti et al. 1997). The ties between complementary sites were broken with species richness (S) as secondary and rarity weighted species richness (SR) as tertiary variable, and we chose the highest-ranking sites.

Grasshopper Conservation Index

Orthopterans are sensitive indicators of changes in vegetation structure and naturalness of open habitats. Their species richness, qualitative composition, dominance rank structure and life form spectra of assemblages are all may be useful variables. As a novel approach, Matenaar et al. (2015) suggested the Grasshopper Conservation Index (GCI) based upon the endemism, dispersal capacity and rarity as a tool for conservation prioritization and made a case study in the extraordinary species rich diversity hotspot of Cape Floral Region in South Africa. In the original GCI each of the three parameters regarded were grouped into three classes and were summed for each species and divided by nine (the maximum value) to obtain a value between zero and one.

Since in the temperate zone and especially in Central Europe the endemism is a less important factor the index should be modified as Szanyi et al. (2021) and Arnóczkyné and Nagy (2022) did in the case of orthopterans of two regions in the Carpathian Lowland.

Our modified Grasshopper Conservation Index (GCI”) uses variables grouped into four classes. Instead of endemism we used European distribution of species based on Heller et al. (1998): distributed in all 12 European regions (= 1), distributed in 9–11 regions (= 2), distributed in 6–8 regions (= 3), distributed in 1–5 regions (= 4). In the case of dispersal capacity and rarity, the original method was followed but parameters were grouped into four categories as in case of European distribution. Considering dispersal capacity, the groups of well flying (= 1), poorly flying (= 2), wing-dimorphic (= 3) (also contains mesopterous mainly flightless species) and flightless (= 4) (wingless, macropterous and mesopterous flightless species) species were used. In the case of rarity, the categorization of Rácz (1998) and Nagy and Rácz (2007a) was followed. The local rarity was measured using spatial constancy (SC) of the species calculated based on revised Orthoptera data of 98 sites. Using the quartile definition of rarity (Gaston 1994) species was considered as common (= 1; SC ≥ 0.4), frequent (= 2; 0.4 > SC ≥ 0.19), low frequent (= 3; 0.19 > SC ≥ 0.06) and rare (= 4; SC < 0.06). The three parameters were summed and divided by 12 (the maximum value) to obtain a GCI” value between zero and one. The GCI” values of the sites were calculated as the sum of the GCI” scores of the species recorded on the given site.

The standardized grasshopper conservation index (GCIn”) was also calculated for each area as dividing GCI” by the number of species (S) living in the given site. While the GCI value is affected by both to species richness and conservation value of the species, the GCIn’’ is independent from the species richness (Matenaar et al. 2015).

Between the used indices there were significant correlations (Pearson r = 0.2942–0.998, p < 0.003) that was higher among S, SR, SQ and GCI”, while in the case of GCIn” it was less characteristic. The S-SR and SR-GCI” showed the highest correlations. The GCI” and GCIn” values were also used as ranking variables of area selection both in simple ranking and complementary area methods.


The use of different indices led to different results with both selection methods. The simple ranking with 5% and 10% limits resulted in site combinations that did not represent all the local Orthoptera fauna, independently the index used (Tables 2 and 3). Simple ranking based on species richness and rarity weighted species richness showed nearly the same result considering both representation of species and set of the selected sites. The set of the sites selected differed only in the case of the 10th site and the most widespread species were represented multiple times at them (Table 3). The sites selected based on the number of rare species (SQ) differed and the representation of the species was lower selecting 5% of sites. In this case four new sites were selected, but species-rich ones were absent among them. The sites selected using modified Grasshopper Conservation Index (GCI”) were the same as that were selected based on species richness and rarity weighted species richness only their order differed. The sites selected with the above mentioned highly correlated indices except one all located in the plateau north to Aggtelek and Jósvafő villages. These are isolated remains of former hayfields maintained by nature conservation. Additionally, grasslands of the Szőlő-hegy of Jósvafő also were selected. This small hill is isolated from the plateau and it is covered with remains of a mosaic of formerly extensively used vineyards, hayfields, orchards and forests. The use of the standardized formula of the index (GCIn”) resulted in a quite different composition of sites selected. Using 5% limit five new sites, while in case of 10% limit seven new sites were selected. The representation of the local Orthoptera fauna was also especially lower than in other cases (Tables 2 and 3).

Table 3 Sampling sites chosen with different selection methods and different indices

In contrast, the complementary area method covered the total local fauna selecting 5.1–12.2% of the sites depending on used indices. With redundancy check all algorithms showed similar result except the use of standardized Grasshopper Conservation Index (Table 2). This algorithm showed the worst result with the higher number of both selected and redundant sites. Considering the other indices both species richness and Grasshopper Conservation Index produced higher number of redundant sites than the rarity weighted species richness and the number of rare species (Table 2). Two of the sites (Szőlő-hegy of Jósvafő and Karst research station) were selected with each index. Three other sites (Százholdas, Szelcepuszta and Erdészeti-kaszáló) were selected using three different indices, while other six sites were selected using only one algorithm. In the case of standardized Grasshopper Conservation Index (GCIn”) 12 sites had to be selected to represent all the local fauna. Although eight of them were not selected with other indices, one was also selected with four, another one with two, while the others with one other indices (Table 3).


The Orthoptera fauna of Hungary is relatively well studied compared to other insect taxa, and the Aggtelek National Park including the Aggtelek and Szalonna Karst and the Rudabánya Hills is one of the most intensively studied part of the country (Nagy and Rácz 2007a). Although relatively poor data may be effective in the representation of the species (Gaston and Rodrigues 2003); however, even the quality of our actual and relatively accurate data might have influenced the efficiency of the area selection. Eight species were excluded from the analysis because they have only dubious more than 30-year-old data. Because of natural (e.g. climate change, secondary succession, etc.) and anthropogenic (e.g. changes of land use, abandonment, etc.) processes, and data collected during revision of dubious data and samplings based on gap analysis, the known distribution of the species are continuously changing, thus the results of area selection need reconsideration for time to time.

The scoring indices we used were correlated with one another. The species richness (S) and the rarity weighted species richness (SR) were essentially similar regarding both the correlation between them and the results of the area selection. The Grasshopper Conservation Index (GCI") and the SR showed similar performance using both simple ranking and complementarity methods; however, the number of the redundant sites was higher using GCI" values. Although the use of indices considering the conservation value of species is generally more effective than prioritization simply with species richness (Matenaar et al. 2015), in our study the combined indices did not perform significantly better than the simple alpha diversity, which performed well in both simple ranking and complementarity analyses.

High correlation between species richness and number of rare and protected species indicated that the protected species and species rare at country-level inhabit mainly the most species-rich sites of the Aggtelek National Park. Nevertheless, the number of rare or protected species is not certainly a good predictor of species richness as it could be seen, e.g. in case of the Hungarian land snail fauna (Sólymos and Fehér 2005).

The similarities were the lowest in case of the standardized Grasshopper Conservation Index (GCIn”) which provided the worst performance considering the representation of the total fauna, rare and protected species and even the representation of species-site records. The differences between the site sets provided by simple ranking and complementarity analysis refers to the opposing integration and segregation model of nature conservation, respectively (Mader 1991). Sites on the Szőlő-hegy (Jósvafő) and the plateau above Jósvafő and Aggtelek villages selected with simple ranking showed multiple representations of both rare and common species. In case of the complementary areas this kind of multiple representation of species did not decrease the efficiency of the area selection and both the simple and combined indices could provide a good performance except the standardized GCIn”. In many cases researchers focus to the protected and rare species disregarding the less interesting ones leading to the overestimation of their number and ratio, which highly affect the value of GCIn", and makes it less effective in area selection.

Despite the correlation between the simple and the combined indices considering variables of conservation value, they provide slightly different combination of hotspots. Since these scoring indices showed similar efficiency, they could not be ranked but sites selected based on two or more of them at the same time can be highly prioritized. In this way the combined use of efficient indices provides an additional ranking of sites that may help the area prioritization and efficient use of limited resources of nature conservation.

Conclusion for future biology

Our study provided data on the efficiency of formerly used and newly developed scoring indices of area prioritization. To develop the methodology of the combined use of alpha diversity and indices regarding conservation value of species (rarity weighted species richness, number of rare species and Grasshopper Conservation Index (GCI)) and to integrate these data into the conservation practices further studies should be carried out at wider range of geographical regions.