Introduction

UNESCO (1964) defined a 5-year program at the global level under the title “Biological foundations of productivity and human well-being” UNESCO 2022; Udvardy 1975). This research program aimed to develop studies on the dynamics of ecosystems in their biogeography system and the consequences of their destruction on life. The necessity of preservation of the diversity of the inhabited biogeographic system based on this research became the basis of the World Conference of Biosphere in 1968 (UNESCO 1993). The results of this conference showed the destructive effects of human activities on biogeographic Realms and biomes that support biodiversity and life in the biosphere and also the conflict between the interests of people and protected areas. In addition, a new conservation program called Man and the Biosphere (MaB) was introduced (UNESCO 1964) and the biosphere reserves were registered in 1976 by UNESCO. The MaB program pioneered the approach of protecting the biogeographical system of the world along with sustainable development and protecting biocultural values, which abandoned the one-dimensional approach of protecting nature and paid attention to humans as well (UNESCO 1977; Meffe et al. 1995). The MaB program is an intergovernmental scientific program for creating a scientific foundation to strengthen the relationship between people and their natural environment. The MaB combines natural and social sciences to protect natural ecosystems and improve human livelihoods creatively and innovatively in land management. Therefore, innovative approaches are promoted in this program for economic development, which are socially and culturally appropriate and environmentally sustainable (UNESCO 2022). Biosphere Reserves are areas of terrestrial, coastal, or marine ecosystems with the objectives of conservation, sustainable economic development, research, and education based on triple zoning (UNESCO 2020). The representative criterion of global biogeographical diversity is one of the basic policy conditions of the MaB program for registering BRs (WNBRMinsk, 1983; UNESCO/MaB, 2013)Footnote 1.

In the 1960s and 1970s, selecting areas and even appropriate conservation titles was rarely based on the evaluation of biogeographic representative areas (Margules and Sarkar 2000; Rodrigues et al. 2004). Therefore, the protected areas were mainly selected from among the natural habitats that had little contribution to biodiversity protection (Soul and Terborgh 1999; Alborzimanesh et al. 2021; Margules et al. 2002).

Institutions such as WWF, IUCN, UNESCO/MaB, and Ramsar Convention aim to establish global scientific foundations of theorizing to identify the biogeography diversity, and land protection classifications, and monitor the challenges, create a global communication network for the exchange of experiences. The responsibility of the countries as the constituent parts of the unit body for protecting biogeographical values is to select, introduce, register, and manage different protection titles in the specific field of the countries.

Three spatial approaches in land conservation planning, including biogeographic provinces (186 provinces), biological hot patches (2.3% of the Earth’s surface), and ecoregions, were developed to select and introduce protected areas on a global scale and over time. The origins of the biogeography provinces approach included the Dasmann-Udvardy framework, which was developed between 1970 and 1975. The biological Hot patches and the International Endemic Bird Area approaches (IUCN-WWF) were developed between 1982 and 1992.

In addition, the ecoregion approach was developed based on Omernik and Bailey and WWF frameworks between 1985—2001. The map of ecoregions provides comprehensive coverage (867 ecoregions) for global and regional conservation planning (Olson et al. 2001).

The studies of Sayer (2020) continued the previous studies (Sayre et al. 2014, 2017), to identify and introduce 431 global terrestrial ecosystems based on the variables of temperature, humidity, landform, vegetation and land use. These studies have emphasized that many governments or non-governmental organizations use WWF ecoregions to select conservation areas. At the same time, it is more efficient to identify ecosystems at the local and national levels. In a case comparison for Kenya, the ecosystems that were identified based on these studies were 98 ecosystems against 13 WWF ecoregions.

When each country’s biodiversity covers its network of protected areas in appropriate locations, it can act as an ecosystem representative unit and complete the global protection network. The approach of representing the network of protected areas is based on the diversity of genes, species, and biological communities, as well as the processes and functions which support the potential of the evolution of natural systems to cover a complete variety of independent ecosystems in their geographical area (Olson et al. 2001). Representativeness for selecting protected areas has been emphasized in several studies (IUCN, Dasmann 1972, 73, IUCN 1974, 1978, 1980, 1992; Salm and Price 1995; Olson et al. 2001; Chape et al. 2005; IMO 2005; Dinerstein et al. 2017; Sayer 2020; Takhtajan 1986; Longhurst 2007; Baile 2009; Metzger et al. 2013; Sayre et al. 2014, 2017). In most of these studies, while emphasizing the importance of global divisions of biogeography as the basis of studies, the exploitation of regional and national studies has been emphasized to identify representative ecosystems of biogeography.

Some countries have identified representativeness in the range of biogeographical diversity of their country to select protected areas while paying attention to global classifications (Shrestha et al. 2010; Djamali et al. 2011; Azizi Jalilian et al. 2020, Blasi et al. 2014, 2017; Aycrigg et al. 2013; Herbada et al. 2011; Rogers and Singers 2014, Capotorti et al. 2012).

Iran as one of the countries in the Asia and Pacific MaB region joined the MaB program in 1976 and has registered 13 BRs by 2022, all of which have other national protection titles. Table 1 shows the characteristics of BRs in Iran (Goshtasb et al. 2018).

Table 1 Characteristics of Iran’s Biosphere Reserves (UNESCO 2022)*
Full size table

The representativeness criterion of biogeography has not been identified in the resources related to the BRs of Iran. Recent studies in which the divisions of Iran’s biogeography are presented in the form of a map include the ecoregions (Olson et al. 2001) and the macroecosystems studies of Iran (Azizi et al. 2020). Based on the results of the review of the sources, none of these studies alone are sufficient to select the representative biosphere reserves in the country. Olson’s ecoregions based on two features, the distribution of species and the distribution of ecosystem units based on biogeography and ecological regions, have been produced, but in accordance with the topographical map of Iran, it is not accurate enough to introduce biogeographical divisions. Azizi Jalilian macroecosystems have been produced based on the Country’s landform, 30 climates, and the latest vegetation information, and are more accurate at the national level. In the studies of Sayre et al. (2020), it has been emphasized that the exploitation of WWF ecoregions in conservation planning is not sufficient and there is a need to exploit ecosystems at the national level as well.

Therefore, this study aimed to design a suitable biogeographical classification spatial framework to evaluate the representativeness criterion as a basic condition for selecting and covering natural ecosystems by BRs and predicting the capacity of new BRs for future decisions which has not been done for Iran so far.

Materials and methods

This analytical-documentary study was based on a map of representative ecosystem units (REU). Although the performance of this study is evaluated for the country of Iran, its results can facilitate the selection process of BRs at the international level. First, the most well-known divisions of biogeography that can be used to select BRs were reviewed, and the common coverage of existing BRs with them was considered. Then, the REU was determined for the country of Iran, the common coverage of BRs and the selection of future BRs were evaluated, and a decision algorithm was prepared.

The biogeography provinces of Udvardy’s, which were emphasized in the documents of the MaB for BRs selection, were examined. This macroscopic classification can be used on a global scale. Udvardy presented the biogeography approach based on biogeography provinces identification (186 units) in the form of 8 Realms and 14 biomes. Figure 1 presents the range of three geographical provinces of Udvardy in Iran .

Fig. 1
figure 1

General location of biogeographic provinces in the territory of Iran (Udvardy 1975) code 20: Anatolian-Iranian Desert; code 21: Turanian; code 34: Caucaso-Iranian Highlands

Full size image

Olson's ecoregions map as a regional classification indicated that Iran is in the Palearctic realm and includes 16 terrestrial ecoregions (Table 2) ((Dinerstein 2017; Olson 2001). Figure 2 demonstrates the location of 16 ecoregions identified in Iran and registered BRs in Iran.

Fig. 2
figure 2

Ecoregions identified in Iran (Dinerstein 2017; Olson 2001) along with Iran’s BRs

Full size image
Table 2 Ecoregions of Iran (Olson et al. 2001; Dinerstein, et al. 2017)
Full size table

Azizi Jalilian et al. (2020) published their research at the national level in this regard. This study used the information layers of the landform, the 30 climates of the country, and the vegetation map (Natural Resources and Watershed Organization) with a scale of 1:1,000,000 to divide Iran’s macroecosystems. Based on the results, 21 macroecosystems units were achieved in Iran. Table 3 presents the identified ecosystems, and Fig. 3 shows the 21 divisions of Iran’s macroecosystems in these studies along with the registered BRs in Iran.

Table 3 Terrestrial ecosystems of Iran at the National level (Azizi Jalilian et al. 2020)
Full size table
Fig. 3
figure 3

Macroecosystem units in Iran (Azizi Jalilian et al. 2020) along with Iran’s BRs

Full size image

Both maps overlapped at the national level to integrate Olson et al. ecoregions and Jalilian et al. macroecosystems within Iran’s borders. The Minimum Legible Delineation (MLD) was determined to be 40 square millimeters according to the Cornell University group method after overlapping these two maps (Forbes et al. 1982). Given that this study was performed at the national level and on a scale of 1:1,000,000, patches smaller than 4000 hectares were eliminated in the neighboring patch. Table 4 shows the overlap matrix of these two maps. The integrated units identified are the representative ecosystem unit (REU) used to select the BRS. Then, the current location of BRS was overlaid with the REU map.

Table 4 matrix of ecoregions and ecosystems of Iran for defining the integration map
Full size table

Decision-making indicators of the representativeness of BRS

Iran’s REUs were identified based on two principles and prioritized based on 5 indicators.

Selection principles

The representativeness was used to select BRs based on the following two principles:

  • Use approaches from similar experiences

According to Olson et al., ecoregion units cover about 15 million hectares or about 0.1% of the earth’s terrestrial. The average units of biogeographic provinces in Udvardy’s (1975) classification are about 74 million hectares and about 0.5% of the earth’s terrestrial. To identify wildlife hot spots on the planet, Myers et al. (2000) used subdivision units 79 million hectares, about 0.5% of the Earth's terrestrial. Therefore, REU is representative for selecting the BR when the total area of its patches is more than 0.5% of the country’s size (Derived from the approach Myers et al., 2000; Udvardy 1975), and the area of its largest patch should be at least 0.1% of the country’s size (Derived from the approach Dinerstein et al. 2017; Olson et al. 2001).

  • Attaining the minimum area that is possible to select Core Zone in REU

The Core Zone occupancy level of the BR is recommended between 5 and 25% in global experiences in the field of zoning of BRs (Germany MaB-National Committee 2007; Günter 2013; Labourdette 2010; Dudley et al. 2013; Lourival et al. 2011; Naughton 2007). Therefore, the common area of the BRs with REU should be recognizable as the minimum area allocated to the Core Zone (5%).

For this purpose, if the common season of the existing BRs with REU is less than 20%, it is not considered representative.

Prioritization indicators

The prioritization of identified REUs for the proposal to register a new BR consists of the following five indicators:

  • The number of patches for each REU was used as a limitation index based on Diamond’s principles and geometric scales (Diamond 1975) for planning nature reserves, which was approved by the World Conservation Strategy (WCS 1980).

  • When the relative occupancy level of REUs in a country increases, it becomes a stronger factor indicator.

  • Larger relative area of the largest REU patch in the country makes the indicator more representative with higher priority as a factor indicator.

  • More adjacent REUs led to a higher priority for selection as a factor indicator.

  • The presence of existing BRs inside the mentioned REU with a low occupancy level (less than 20%) was considered as a restriction indicator.

Entropy-VIKOR was used to prioritize REU based on the mentioned indicators. The Shannon entropy model weighted each index was applied in the VIKOR model in order to determine the factors and limitations of the indicators for VIKOR ranking (Q). The VIKOR model is one of the multi-criteria decision-making methods for prioritizing options, which was used for criteria with different and even contradictory measurement units. The lowest VIKOR index rank (Q) has the highest priority (Saner et al. 2022; Sunarsih et al. 2020; Zavadskas and Bausys 2015).

Results and discussion

Table 5 shows the results of Iran’s BRs on Udvardy biogeography provinces. Based on the knowledge of Iran’s natural geography, many natural ecosystems do not correspond to the mentioned geographical provinces. Therefore, the inadequacy of the Udvardy system to express the representativeness of BRs is observed at the national level. For example, the Golestan forests cannot be considered representative of the Caucasian-Iranian highlands, and the Miankaleh wetland or Urmia lake can also be considered in the same geographical provinces.

Table 5 Provinces of biogeography (Udvardy, 1975) and distribution of BRs
Full size table

Comparing Iran’s ecoregions (Olson et al. 2001; Dinerstein et al. 2017) and the BRs showed that 10 of 16 ecoregions identified in Iran currently have BRs (Table 6). However, 5 of 6 ecoregions without BR occupy less than 0.5% of the country’s areas. The lack of BRs in These ecoregions cannot be considered a deficiency in their representativeness since their small size cannot provide them with suitable representatives for ecological units in Iran.

Table 6 The occupancy level of ecoregions in Iran (Olson et al. 2001) and distribution of BRs
Full size table

Biosphere reserves should represent terrestrial and aquatic ecosystems in each ecoregion. According to the ecoregion of Dinerstein et al. (2017), only the aquatic ecosystem in the Eastern Anatolian Montane Steppe and Registan–North Pakistan Sandy Desert ecoregions has BRs (Urmia and Hamoun BRs) with no representative of enough terrestrial ecosystem. As shown in Table 6, the Alborz Range forest steppe ecoregion with 3.4% of the area in Iran includes 2 different patches, which represent the smaller patch of Arasbaran BR well. However, only a small part of the Golestan BR is located in the larger patch, which can be doubted based on the exact matching of the topographical position by matching the DEM map of the Alborz mountain range to this ecoregion. Therefore, it seems necessary to select and register the BR in this ecoregion.

Based on the results in Table 6 and ecoregions (Dinerstein et al. 2017) in Iran, the following units are suitable for introducing the BRs:

  • Kuh Rud and Eastern Iran Montane Woodlands (KRD) Ecoregion with an area of about 7.5% of the country

  • Alborz Range forest steppe (ARF) Ecoregion with an area of about 3.4% of the country

The adaptation results of BRs and Iran’s macroecosystems (Azizi et al. 2020) (Table 7) indicated that 17 of 21 identified ecosystems in Iran have BRs. In addition, the following macroecosystems do not have BRs:

  • Moderate and Arid Bare diverse landforms Ecosystem (MAD) (1.91% of the size of the country),

  • Cold and Humid Prairies Ecosystem (CAM) (0.82% of the country)

  • Humid and Moderate Bare Hill Lowlands Ecosystem (HMB) (0.32% of the country)

  • Warm and Arid Bare Hills Ecosystem (WAB) (0.04% of the country)

  • Warm—Desert Bare Hill Mountains Ecosystem (WDB) (0.02% of the country)

Table 7 The occupancy level of macroecosystem units in Iran (Azizi et al. 2020) and the distribution of BRs
Full size table

HMB, WAB and WDB are not given priority for choosing due to the size and occupancy level of the above ecosystems (occupancy level is less than 0.5%). Nevertheless, choosing the BRs among the CAM and MAD ecosystems is a priority due to their level of occupation in the country.

The research indicators are depicted in Fig. 4 step-by-step to generate the REU map and screen the decision-making stages for evaluating the existing BRs and selecting new BRs schematically in the logical framework of the decision-making algorithm. This algorithm shows the ways to achieve the results for prioritizing the location and features of the selected REU and facilitates the exploitation of the results of this research by users and decision-makers.

Fig. 4
figure 4

The proposed decision-making algorithm for identifying and determining REUs to select the BRs at the national level

Full size image

Figure 5 displays the REU map and the location of BRs in Iran. Table 8 presents those REUs that has an area of more than 0.5% of the country’s area, and the largest patch is at least 0.1% of the area in Iran. The results revealed that 33 REU can be identified at this stage. As shown in Table 9, Iran’s BRs are located in 26 REUs, but only 15 REUs are consistent with the considered indicators and the decision algorithm (Fig. 4). Therefore, this decision-making algorithm led to the identification of 18 REUs in Iran for future BRs.

Fig. 5
figure 5

Map of REU with guide codes and the location of the BRs in the country

Full size image
Table 8 Famous REUs for the selection of BRs according to the defined indicators
Full size table
Table 9 REUs covered by the BRs of the country
Full size table

The prioritization results based on Entropy-Shannon in Table 10 represent the area of the largest patch, the number of patches in each REU, the percentage of REU occupancy in the country, the proximity of REUs, and the presence of a BR with an occupancy level of less than 20% in REU can affect the selection of REUs for BRs. As shown in Table 11, the priority of REUs for selecting BRs based on representative criteria is displayed based on VIKOR’s method and based on the weight of the indicators in Table 10. Figure 6 shows the map of REUs based on priority.

Table 10 The results of calculating the weights of criteria using the Shannon entropy model
Full size table
Table 11 VIKOR model for the priority of REU requiring biosphere reserve in Iran
Full size table
Fig. 6
figure 6

The priority of the REUs for selecting the country’s new BRs

Full size image

Conclusion

Biogeography representative is considered one of the keys and basic criteria for selecting BRs, which affects the zoning pattern of the BRs, especially the location and number of the core zones. Representation of BRs can be done at different levels as global, regional, and national levels. However, the relationship between these levels is based on the use of almost similar criteria but on different scales. Udvardy biogeographical provinces (1975) is considered the first attempt to create a global network of ecological units that is acceptable for imaging and arrangement of ecosystems at the global level. Udvardy introduced biogeographic provinces based on plant types representative of biomes in different realms; however, this study has been conducted on a global scale. The results of this research identified representative ecosystem units, where the presence or absence of vegetation, type, and coverage is one of the components of ecosystem unit recognition, similar to Udvardy’s studies. Nevertheless, the identified REU has a national resolution and is more accurate than the Udvardyan classification in terms of scale. The identified REU in this study is a combination of the ecoregion (Olson et al. 2001) for Iran at the regional level and macroecosystems identified in Iran (Azizi Jalilian et al. 2020). These REUs combined ecological aspects with habitat functions, which were more effective than the two mentioned classifications for identifying REUs at the national level and associated with more classes and more precise diagnosis compared to the two previous classifications which Integration of ecological and ecosystem functions. In this study, the identified REUs are indicative of choosing a BR at the national level when the total area of its patches is greater than 0.5% of the country’s size, which is consistent with the approach of Myers et al. (2000) and Udvardy (1975). Selecting representative REUs for the BRs was also dependent on the area of the largest patch, which was considered to be more than 0.1% of the country and in line with Dinerstein et al. (2017) and Olson et al. (2001). One of the bases for selecting REU for the selection of future BRs is the spatial occupation level of an existing BRs with REU and the minimum intersection of 20%, which is similar to the study of Dudley (2013) and Labourdette (2010).

Based on the results, selecting representative BRs should be based on a more accurate ecosystem separation at the national level, as well as trans-national performance. Udvardy’s approach is acceptable and promising only when there is no integrated national information. The conformity of Olson ecoregions with physiographic units requires more detailed investigations for national application despite the arrangement of ecological units from the global to regional level. Relying on national ecological classifications is the best situation for the typology of macroecosystems. The countries which have made such a classification have created the chance to select the BRs based on the exact reality of the biomes from the bottom up and link the accuracy of the selection to the global network while maintaining the national performance.

This study provided a framework to select the BRs based on the criterion of representativeness at the national level, which was introduced in the form of a decision algorithm (Fig. 4) to select the mechanism of the BRs in a methodical and integrated manner. Occupancy percentage criteria, number and area of REU patches, REU’s contiguity, and the level of occupancy of existing BRs were used to prioritize the selected REUs for selecting the BRs. The arrangement of suitable REUs is also suggested to be considered for selecting large multi-core BRs to be more effective than smaller and single-core BRs as the basis of other studies for the future. In addition, the present study represented the capacities of selecting transboundary BRs. Adapting the map of REUs to the existing BRs according to Fig. 7 also showed that the representative capacity of the BRs can be improved by modifying some boundaries.

Fig. 7
figure 7

Result of Iran’s BR representativeness based on REU map and decision-making algorithm

Full size image

All proposed BRs can be selected in more than one REU and provide the possibility to cover ecosystem diversity by selecting fewer BRs. The registration of seven new priority BRs covers 15 REUs with about 17% of the country’s area.

The production of the independent REU map at the national level enables countries to use the appropriate representative biogeography coverage to select the network of protected areas in their country, which is also recommended for Iran. The result of this approach potentially enables the network of national protected areas to play the transnational role and function for the protection of biogeography at the global level.