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Selection of an endemic flora reservenetwork and its biogeographicalsignificance in the Baetic ranges(Southern Spain)Francisco Javier Pérez-García a , Miguel Cueto a , Julio Peñas b

, Fabián Martínez-Hernández a , José Miguel Medina-Cazorla a ,Juan Antonio Garrido-Becerra a & Juan Francisco Mota aa Dpt. of Plant Biology and Ecology , University of Almería ,E-04120 , Almería E-mail:b Dpt. of Botany , University of Granada , E-18071 , GranadaPublished online: 27 Apr 2013.

To cite this article: Francisco Javier Pérez-García , Miguel Cueto , Julio Peñas , FabiánMartínez-Hernández , José Miguel Medina-Cazorla , Juan Antonio Garrido-Becerra & JuanFrancisco Mota (2007) Selection of an endemic flora reserve network and its biogeographicalsignificance in the Baetic ranges (Southern Spain), Acta Botanica Gallica, 154:4, 545-571, DOI:10.1080/12538078.2007.10516080

To link to this article: http://dx.doi.org/10.1080/12538078.2007.10516080

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Acta Bot. Gallica, 2007, 154 (4), 545-571.

Selection of an endemic flora reserve network and its biogeographicalsignificance in the Baetic ranges (Southern Spain)

by Francisco Javier Pérez-García(1), Miguel Cueto(1), Julio Peñas(2), Fabián Martínez-

Hernández(1), José Miguel Medina-Cazorla(1), Juan Antonio Garrido-Becerra(1) and Juan

Francisco Mota(1)

(1) Dpt. of Plant Biology and Ecology, University of Almería, E-04120 Almería; fpgarcia@ual.es

(2) Dpt. of Botany, University of Granada, E-18071 Granada

Abstract.- The Baetic mountains are a very important centre of plant diversityand endemicity. The current environmental legislation includes many of theselocalities. In order to assess the current reserves network and to propose aselection of protected areas, and to examine the biogeographic distinctivenessof that selection, we applied to the orophilous endemic flora a variety of algo-rithms (some of which were never used for Europe before) on the Baetic ranges.In order to preserve this natural heritage, it would be necessary to protect at leasttwelve massifs, considering the siliceous portion of Sierra Nevada as a greatpriority area. The most notable gaps in the legislation are the ranges of Gádor,Revolcadores and La Pandera. The selected localities were characterized bytheir great biogeographical distinctiveness. The distinctiveness of the obtainedselections stresses their reliability and also emphasizes the suitability of the bio-geographic researches of the flora of the Baetic ranges for conservation objec-tives.

Key words : biodiversity hot-spot - phytogeography - plant conservation - plantendemism - Tabu search.

Résumé.- Les montagnes bétiques sont un centre très important de diversité devégétaux et d’endémicité. La législation environnementale actuelle inclut plu-sieurs de ces localités. Afin d'évaluer le réseau de réserves actuel, le choix dessecteurs protégés et d’examiner les particularités biogéographiques de ce choix,nous avons appliqué à la flore endémique de la haute montagne quelques algo-rithmes (dont certains jamais employés pour l'Europe) aux cordillères bétiques.Afin de préserver cet héritage, il serait nécessaire de protéger au moins douzemassifs, la partie siliceuse de la Sierra Nevada etant un grand secteur prioritai-re. Les lacunes les plus notables dans la législation sont les chaînes de Gádor,de Revolcadores et de La Pandera. Les localités choisies ont été retenues pourleurs grandes particularités biogéographiques. La particularitié du choix obtenuindique son ajustement et montre la valeur des investigations sur la flore desmontagnes bétiques pour des objectifs de conservation.

Mots clés : hotspot de biodiversité - phytogéographie - conservation - endé-misme - Tabu search.

received December 12, 2006, accepted March 6, 2007

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I. INTRODUCTION

The current species extinction crisis and the consequent loss of biodiversity are of seriousconcern to the scientific community, which demonstrated the urgent need to propose net-works of reserves for the conservation of the biodiversity (Margules & Pressey, 2000),especially in those regions of the world with high values of biodiversity and prominentrates of endemicity. These regions are called « hot-spots » (Myers, 1988; Mittermeier etal., 1998).

The Mediterranean Basin has been recognized as important plant diversity centre(Myers, 1990; Mittermeier et al., 1998; Médail & Quézel, 1997, 1999) encompassing tenzones of special interest (Médail & Quézel, 1997, 1999). These zones fit with the endemi-city centres, placed in the Mediterranean Basin, principally in the mountainous chains andon the islands, especially the ones located near the zones where the tectonic plates collide(Verlaque et al., 1997).

A notable factor that contributes to the great floristic singularity of the mountains ofSouthern Spain is the Andalusian connection with the mountains of the North of Africa(Valdés, 1991). This is why the Rif and the Tell regions and the Baetic ranges constituteone of the main hot-spots and plant diversity centres (Médail & Quézel, 1997,1999).

Inside the Spanish state, The Andalusian government (Junta de Andalucía) has a largenetwork of natural reserves (called Red de Espacios Naturales Protegidos de Andalucía,i.e. Andalusian Natural Protected Areas Network-, RENPA). Nearly half of these reservesinclude high mountain areas, specifically, the Andalusian legislation on protected areasincludes the ranges of Las Nieves, Horconera, Mágina, the set of Cazorla-Segura andCastril, María, Baza, Tejeda, Almijara and Sierra Nevada as Parques Naturales (NaturalParks). The summit areas of the latter are also granted the status of Parque Nacional(National Park). At present, the legislations of the regions of Murcia and Castilla-LaMancha do not protect their Baetic high mountain areas, except for the declaration of Calardel Mundo as a Natural Park which, although legally passed, has not yet been effectivelyimplemented.

Is not surprising the wide protection of the high mountain areas in Andalusia if we takeinto account that the Red List of Spanish Vascular Flora (Bañares et al., 2003) and the RedList of Andalusian Vascular Flora (Cabezudo et al., 2005), show the Baetic territories asbeing the zone with most endangered plant taxa. With the exception of some sites in theCanary Islands, as far as the preservation of endangered flora is concerned (Del Valle etal., 2003), Sierra Nevada and Sierra de Gádor are the two most important sites.

Traditionally, the designers of natural reserves follow intuitive procedures, which intro-duce criteria that are alien to the conservation of the biodiversity such as aesthetic, econo-mic or political nature criteria (Pressey et al., 1996; Sarkar et al., 2002). Since theseventies, the need to select areas for conservation according to with scientific criteria hasspread to reach a synthetic consensus framework, called « adaptive management » (Sarkar,2002). A first fundamental stage of adaptive management is the selection of « surrogates »as representatives of biodiversity. Subsequently, the prioritization of places with a conser-vation target according to their biodiversity surrogates content is done. The method ofapproaching the second problem has developed from selecting areas according to theirrichness to algorithms based on the principle of complementarity (Sarkar et al., 2002). Thisprinciple establishes an iterative process that adds new places to a list of places alreadyselected, maximizing the number of new features.

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Most of complementarity-based algorithms are heuristic or meta-heuristic (Pappas etal., 2004). The heuristic algorithms were used satisfactorily on numerous occasions (Justus& Sarkar, 2002) and they were applied in several software packages.

Since the days of Von Humboldt and Wallace, the studies on the distribution of life orga-nisms have been widely spread; however, until the late decades of the 20th century was notsuggested that « Biogeography can play a basic role in (…) the protection of the plantworld » (Takhtajan, 1986), reaching the « conservation biogeography » synthesis (Grehan,1993; Whittaker et al., 2005). This new discipline, between other topics, deals with settingthe areas of conservation in situ and planning the design of natural protected areas, asHumphries et al. (1995) and Craw et al. (1999) reported.

The aims of this paper are to establish the priorities for the selection of natural areas inorder to protect the orophilous endemic flora of the Baetic ranges and to evaluate the sui-tability of the current network of protected areas for such a purpose, by the use of heuris-tic and meta-heuristic algorithms. In addition, to examine the biogeographicdistinctiveness of that selection in order to asses the utility of biogeographic suggestionsfor vegetal conservation.

II. MATERIAL AND METHODS

A. Study area

This paper deals with areas located in the high Baetic ranges on the oromediterranean(over 1,800 m above sea level approximately) and cryoromediterranean belts (over2,900 m above sea level), according to the bioclimatic classification of Rivas-Martínez etal. (2002). In order to clearly define these areas we have used the vegetation mapping pro-vided by Rivas-Martínez (1987) and Valle (2003). The use of vegetation mapping to defi-ne areas suitable for biodiversity conservation is a very common practice (Scott et al.,1993; Rivas-Martínez et al., 1993). These ranges are situated in the eastern portion ofAndalusia, the NW section of Murcia and the most southern area of Castille-La Mancha.

With respect to our previous survey (Peñas et al., 2005), this time we have included thelocalities of Alcaraz, Orce, Lúcar and La Grillimona, since they present areas with oro-philous vegetation according to the above mentioned maps. In addition, the complex ofCazorla-Segura and Castril has been itemized in three localities (Cazorla-Pozo, Segura-Banderillas and Empanadas-Cabrilla-Castril) in accordance with the already mentionedvegetation maps, a fact which will allow a more detailed analysis. Finally, we have alsoincluded three localities (Grazalema, Horconera and Loja) because, despite their lackingan oromediterranean belt (at least with an extension worthy of mapping), they play a signi-ficant role in the Andalusian environment and it must not be forgotten that as a result ofthe microclimatic effects, some of the orophilous taxa appear on the peaks of lower moun-tains (Mota, 1990). Due to this peculiarity, this study considers 28 localities (Table I, Fig.1).

From a biogeographical point of view, all the sierras considered here have been inclu-ded in the units of the Holarctic kingdom, the Mediterranean region and the Baetic pro-vince, within the limits of this last chorological unit, six sectors (Rivas-Martínez et al.,1997) have been distinguished. In the other hand, four centres of endemicity have beenproposed exclusively for these high mountains areas, which show a radical distinctivenessbetween calcareous and siliceous sierras (Mota et al., 2002).

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B. Methods

A matrix was created with columns for the above mentioned 28 high mountain areas androws for the 249 plant taxa under consideration. Occurrence (1) or absence (0) are recor-ded in the respective cells. Although the matrix is based on previously available data (Motaet al., 2002; Peñas et al., 2005), the information has also been extended with bibliogra-phical data and field research following the methods of the already mentioned works.

Of the 249 plant taxa, 19 taxa are catalogued as « Critically Endangered », 16 taxa as« Endangered », 70 taxa as « Vulnerable », 11 taxa as « Data Deficient », and 28 taxa as« Near Threatened » (Cabezudo et al., 2005). We considered these 249 plant taxa as sur-rogates. Vascular plants are often used as a surrogate for total biodiversity in the selectionof reserves and play a critical role in land management (Dasmann, 1972; Noss, 1987).Plants are used as an umbrella group because they constitute the bulk of primary producerbiomass, reflect the environmental conditions, provide physical structure for other orga-nisms, and are relatively easily surveyed (Ryti, 1992). There are evidences of the capabi-lity of using plants as surrogates of other groups of organisms (Panzer & Schwartz, 1998).

Table I.- Localities under study with the geologic profile, provinces, biogeographical sectors(Rivas-Martínez et al., 1997, 2002), the range of designation (P), number of Baetic ende-mic taxa (BE), exclusive endemic taxa (EE), oromediterranean area in ha (OS) andhighest altitude in masl (H).

Tableau I.- Localités étudiées avec profil géologique, provinces, secteurs biogéographiques(Rivas-Martínez et al., 1997, 2002), gamme de la désignation (P), nombre de végétauxendémiques bétiques (BE), végétaux endémiques exclusifs (EE), secteur de hautes mon-tagnes en hectare (OS) et points culminants en m ANMM (H).

Geology Sector Localities Province P BE EE OS H

Calcareous Rondeño Grazalema Cádiz-Málaga Yes 20 0 0 1,665

Las Nieves Málaga Yes 31 1 121 1,918

Loja Granada No 12 0 0 1,671

Alpujarreño- Lújar Granada No 13 0 28 1,824

Gadorense Gádor Almería No 48 5 2,256 2,240

Malacitano- Tejeda Málaga-Granada Yes 55 2 206 2,065

Almijarense Almijara Málaga-Granada Yes 47 0 28 1,832

Calcareous Sierra Nevada Granada Yes 80 7 632 2,450

Subbético Harana Granada No 37 0 725 2,027

La Pandera Jaén No 38 1 252 1,872

Mágina Jaén Yes 64 2 3,291 2,167

Horconera Córdoba Yes 25 0 0 1,570

Cazorla-Pozo Jaén Yes 75 2 1,372 2,028

Segura-Banderillas Jaén Yes 51 0 1,721 1,993

Empanadas-Cabrilla-Castril Jaén-Granada Yes 91 4 8,335 2,133

La Sagra Granada No 78 0 688 2,383

La Grillimona Granada-Albacete No 43 0 14,852 2,064

Las Cabras Albacete No 34 0 1,865 2,081

Calar del Mundo Albacete Yes 47 0 524 1,897

Alcaraz Albacete No 31 0 284 1,798

Revolcadores Murcia No 43 1 659 2,018

Guadiciano- María Almería Yes 46 1 563 2,045

Bacense Orce Granada Yes 29 0 419 1,826

Calcareous Los Filabres Almería No 25 0 528 2,080

Lúcar Almería No 29 0 40 1,722

Calcareous Baza Granada Yes 68 0 4,358 2,269

Siliceous Nevadense Siliceous Los Filabres-Baza Granada-Almería No 34 1 7,128 2,168

Siliceous Sierra Nevada Granada-Almería Yes 121 56 60,688 3,482

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The information of the database was expressed in a geographic information system(ArcView GIS 3.2 for Windows, ESRI, Redland, CA, USA). In this process, we took intoconsideration the areas covered by the high mountain vegetation represented in the mapsof Rivas-Martínez (1987) and Valle (2003).

We carried out the natural areas reserve selection using the software packages thatimplement heuristic and meta-heuristic algorithms. Just as Kelly et al. (2002) assessed andrecommended the combined use of different software, our combined use of programmesbased on different philosophies (heuristic and meta-heuristic ones) was demonstrated as apowerful tool.

Among the packages including heuristic algorithms, the most notable is ResNet, whichimplements a hierarchically controlled, rarity-complementarity-based selection algorithm(Aggarwal et al., 2000; Sarkar et al., 2002). We utilized ResNet to initiate the selectionusing as item criteria both rarity and richness, as well as considering the RENPA localitiesin the input set. In view of the isolated and disjunt character (« island within mainland »)of the high mountain areas, we did not consider the adjacency criterion. Each algorithmruns with the target of representation of surrogates equal to one.

Among the most frequently used meta-heuristic procedures for the selection of reservesare some based on the Simulated Annealing Algorithm (Kirkpatrick, 1983), which was

Fig. 1.- Oromediterranean areas of the Baetic ranges. Each sierra is followed by its abbrevia-ted name and the number of Baetic endemic taxa and exclusive endemic taxa. ALC:Alcaraz; ALM: Almijara; CAB: Las Cabras; CBZ: Calcareous Baza; CFI: Calcareous LosFilabres; CMU: Calar del Mundo; CSN: Calcareous Sierra Nevada; CZP: Cazorla-Pozo;ECC: Empanadas-Cabrilla-Castril; GAD: Gádor; GRA: Grazalema; GRI: La Grillimona;HAR: Harana; HOR: Horconera; LOJ: Loja; LUC: Lúcar; LUJ: Lújar; MGN: Mágina; MRI:María; NIE: Las Nieves; ORC: Orce; PAN: La Pandera; REV: Revolcadores; SAG: LaSagra; SFB: Siliceous Los Filabres-Baza; SGB: Segura-Banderillas; SSN: SiliceousSierra Nevada and TEJ: Tejeda.

Fig. 1.- Les secteurs élevés de montagnes des cordillères bétiques. Chaque chaîne est sui-vie de son nom abrégé et du nombre de ses espèces endémiques exclusives.

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implemented in the program Sites (Andelman et al., 1999) and Marxan (Ball &Possingham, 2000). These software packages offer the portfolios with the selected placesby means of a cost equation that calculates the sum of the set of weighted components inan iterative process.

The programmes Sites and Marxan were used to complete up to 10,000 runs for everyportfolio. The costs were considered to be identical for all the localities and, therefore, irre-levant in the analyses. The first analysis was performed considering equal species penaltyfactors for all the taxa. In the second one, we considered a value for this factor accordingto the different taxa on the basis of the category of risk (Cabezudo et al., 2005). We esta-blished a logarithmic scale, where one corresponds to the Not Threatened taxa, two tothose in the category of Data Deficient, four to the Vulnerable ones, eight to Endangeredones and 16 to the Critically Endangered taxa. With this scale, we tried to show that therisk of increase in the different endangered categories is not lineal (from Not Threatenedto Critical Endangered) but exponential. While ResNet ranked the localities, Sites andMarxan did not. We needed to establish priorities related to conservation evaluation andland management. We were able to elude this apparent drawback of the meta-heuristic pro-cedures by stressing their summed solution. This solution was the means to establish therobustness of a proposal, to assess priorities of the same (Andelman et al., 1999) and com-pare it to the ResNet dataset (Kelly et al., 2002).

Another metaheuristic strategy used for optimizations is the « Tabu Search » (Glover &Laguna, 1997), implemented in the RTS programme (Pappas et al., 2004). The fundamen-tal advantage of this method is that it provides a result really close to optimicity, and des-pite the fact that it is possible to expend the computational effort to find an optimalsolution, the inherent inaccuracies in the biogeographical input data do not make this effortworthwhile (Pappas et al., 2004). Although this algorithm has been widely used for opti-mizations, such as those dealing with fuel storage (Li et al., 2002), only recently has it beensuggested as a criterion for selecting the reserves for biodiversity conservation (Pappas etal., 2004). So far, it has never been applied to deal with the problems of the European eco-systems. We have implemented the Tabu Search method with the RTS Programme after 24hours of iteration. Like the Simulated Annealing, RTS does not rank the localities.

III. RESULTS AND DISCUSSION

The solution obtained after running ResNet on the basis of rarity and richness selected 12localities (Table II, Fig. 2). Among these places, Siliceous Sierra Nevada stands out with121 taxa (48.6% of the total), and Gádor and Las Nieves too. The obtained dataset whenResNet considered the already protected localities showed that it is necessary to protectfour more localities, especially sierra de Gádor (Table III). Most of the taxa (96.4%) havepopulations in protected areas; only nine of them remain out of the RENPA. Among all ofthem, two taxa are catalogued as Critically Endangered, one as Endangered and two taxaas Vulnerable (according to Bañares et al., 2003).

The best solution of the programme Sites offers a portfolio with 11 sierras (having igno-red, previously, the species penalty factor; Table IV). The solution obtained considering thespecies penalty factor is similar to the previous one; in fact 12 ranges were selected(Revolcadores was added in this solution run). The analysis of the summed solution sho-wed (having ignored, previously, the species penalty factor) that one locality (SiliceousSierra Nevada) is selected in all the 10,000 runs and another nine localities are extensive-

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Table II.- ResNet dataset with the order of selection (OS), the number of selected attributes(NSA) and the percentage of the total attributes that have been selected (PAS).

Tableau II.- Ensemble de données de ResNet avec l’ordre du choix (OS), le nombre d’at-tributs choisis (NSA) et le pourcentage des attributs de total qui ont été choisis (PAS).

Rarity Richness

OS Localities NSA PAS Localities NSA PAS

1 Siliceous Sierra Nevada 121 48.6 Siliceous Sierra Nevada 121 48.6

2 Gádor 145 58.2 Las Nieves 145 58.2

3 Las Nieves 163 65.5 Gádor 163 65.5

4 Empanadas-Cabrilla-Castril 207 83.1 Empanadas-Cabrilla-Castril 207 83.1

5 Cazorla-Pozo 214 85.9 Cazorla-Pozo 214 85.9

6 Tejeda 226 90.7 Tejeda 226 90.7

7 Siliceous Los Filabres-Baza 229 92.0 Siliceous Los Filabres-Baza 229 92.0

8 María 233 93.6 María 233 93.6

9 Calcareous Sierra Nevada 243 97.6 Calcareous Sierra Nevada 243 97.6

10 La Pandera 246 98.8 La Pandera 246 98.8

11 Mágina 248 99.6 Mágina 248 99.6

12 Revolcadores 249 100 Revolcadores 249 100.0

Fig. 2.- Selected localities by ResNet. Each sierra is followed by its abbreviated name.CSN: Calcareous Sierra Nevada; CZP: Cazorla-Pozo; ECC: Empanadas-Cabrilla-Castril;GAD: Gádor; MGN: Mágina; MRI: María; NIE: Las Nieves; PAN: La Pandera; REV:Revolcadores; SFB: Siliceous Los Filabres-Baza; SSN: Siliceous Sierra Nevada andTEJ: Tejeda.

Fig. 2.- Localités choisies par ResNet. Chaque chaîne est suivie de son nom abrégé.

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ly selected. This fact clearly reveals the importance of these areas for plant preservation.Two ranges (Siliceous Los Filabres-Baza and La Pandera) show intermediate values, whileanother 16 ranges are selected in a very low number of runs. If we consider the speciespenalty factor, the summed solution shows a similar response, except for the fact that thereare seven absolutely irreplaceable ranges and not just one (Siliceous Sierra Nevada, Gádor,Empanadas-Cabrilla-Castril, Tejeda, Cazorla-Pozo, Mágina and Calcareous SierraNevada).

When we ignored the species penalty factor, Marxan’s best solution involved 10 mas-sifs (Table V and Fig. 3). If we consider the species penalty factor, best solution is almostequal to the previous one: 12 sierras were selected (La Pandera, Siliceous Los Filabres-

Table III.- ResNet dataset based on RENPA, with theorder of selection (OS), the number of selectedattributes (NSA), the percentage of the total attri-butes that have been selected (PAS).

Tableau III.- Ensemble de données de Resnet basésur RENPA, avec l’ordre du choix (OS), le nombred’attributs choisis (NSA), le pourcentage des attri-buts de total choisis (PAS).

OS Localities NSA PAS

1-14 RENPA 240 96.4

15 Gádor 245 98.4

16 Revolcadores 247 99.2

17 La Pandera 248 99.6

18 Siliceous Los Filabres-Baza 249 100.0

Table IV.- Sites portfolios with the selection in the « best solution » (in regular type), thelocalities not selected (in italics) and the summed solution of all of them.

Tableau IV.- Portefeuilles de Sites avec le choix dans la « meilleure solution » (dans le typerégulier), les localités non choisies (en italiques) et la solution additionnée de tous.

Without species penalty factor With species penalty factor

Localities Summed solution Localities Summed solution

Siliceous Sierra Nevada 10000 Siliceous Sierra Nevada 10000

Gádor 9943 Gádor 10000

Empanadas-Cabrilla-Castril 9938 Empanadas-Cabrilla-Castril 10000

Tejeda 9936 Tejeda 10000

Cazorla-Pozo 9925 Cazorla-Pozo 10000

Mágina 9924 Mágina 10000

Calcareous Sierra Nevada 9914 Calcareous Sierra Nevada 10000

Las Nieves 9910 Las Nieves 9484

María 9908 La Pandera 9364

Revolcadores 9867 María 9288

Siliceous Los Filabres-Baza 5082 Siliceous Los Filabres-Baza 9210

La Pandera 5076 Revolcadores 9033

La Sagra 262 Grazalema 826

Calcareous Baza 227 La Grillimona 632

La Grillimona 198 Calcareous Baza 606

Calar del Mundo 168 La Sagra 588

Almijara 131 Las Cabras 543

Grazalema 131 Lúcar 542

Orce 119 Calar del Mundo 536

Las Cabras 118 Segura-Banderillas 536

Lújar 117 Horconera 530

Lúcar 113 Alcaraz 530

Horconera 108 Orce 490

Segura-Banderillas 107 Almijara 488

Alcaraz 106 Harana 446

Loja 106 Calcareous Los Filabres 404

Calcareous Los Filabres 96 Lújar 402

Harana 87 Loja 378

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Table V.- Marxan solutions with the selection in the « best solution » (in regular type) andthe localities not selected (in italics) and the summed solution of all of them.

Tableau V.- Solutions de Marxan avec le choix dans la « meilleure solution » (dans le typerégulier), les localités non choisies (en italiques) et la solution additionnée de tous.

Without species penalty factor With species penalty factor

Localities Summed solution Localities Summed solution

Siliceous Sierra Nevada 10000 Siliceous Sierra Nevada 10000

Gádor 10000 Gádor 10000

Empanadas-Cabrilla-Castril 10000 Empanadas-Cabrilla-Castril 10000

Tejeda 10000 Tejeda 10000

Cazorla-Pozo 10000 Cazorla-Pozo 10000

Mágina 10000 Mágina 10000

Calcareous Sierra Nevada 10000 Calcareous Sierra Nevada 10000

Las Nieves 10000 Las Nieves 10000

María 10000 María 10000

Revolcadores 10000 Revolcadores 10000

Siliceous Los Filabres-Baza 4975 Siliceous Los Filabres-Baza 10000

La Pandera 4974 La Pandera 10000

La Sagra 0 La Sagra 0

Calcareous Baza 0 Calcareous Baza 0

La Grillimona 0 La Grillimona 0

Calar del Mundo 0 Calar del Mundo 0

Almijara 0 Almijara 0

Grazalema 0 Grazalema 0

Orce 0 Orce 0

Las Cabras 0 Las Cabras 0

Lújar 0 Lújar 0

Lúcar 0 Lúcar 0

Horconera 0 Horconera 0

Segura-Banderillas 0 Segura-Banderillas 0

Alcaraz 0 Alcaraz 0

Loja 0 Loja 0

Calcareous Los Filabres 0 Calcareous Los Filabres 0

Harana 0 Harana 0

Baza and Revolcadores were added). The proposal of Marxan’s summed solution is more

solid than Sites, in which 10 ranges are selected in all cases, two show intermediate values

and 16 ranges were never selected. When considering the species penalty factor, the results

are also clearer: 12 ranges are selected in all the runs and another 16 ranges were never

selected.

The RTS programme suggests a solution of 12 ranges (Table VI and Fig. 4). Note that

these 12 localities coincide with those seen in the solutions of other software packages.

In order to protect all the Baetic orophilous endemisms, it would be necessary to inclu-

de 12 localities in the protected areas network. The absolute agreement between the total-

ly different approaches demonstrates the solidness of the final solution. These results also

confirm the advantage of the combined use of different software packages, as Kelly et al.

(2002) reported.

Among the ranges included in the dataset, the siliceous portion of Sierra Nevada is the

principal priority for conservation issues. The value of the above mentioned locality as a

centre of biodiversity was widely recognized (Blanca et al., 2002; Del Valle et al., 2003).

This richness is probably due to the fact that this range not only has a higher altitude than

the rest but also presents a wider oromediterranean surface (see Table I and Fig. 1).

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Consequently, Sierra Nevada’s declaration as National Park wasone of the greatest conservation achievements of the last few years.

On the other hand, sierra de Gádor is the most important omis-sion. The contribution that its flora makes to the Andalusian andSpanish natural heritages was widely taken into consideration(Mota et al., 2003; Del Valle et al., 2003). This range is extremelyimportant since it has very restricted endemic species linked to spe-cial habitats. Another singularity of this massif is the occurrence ofxerophilous taxa peculiar to the neighbouring arid zones (Pérez-García et al., 2001). Taking into account the long history of man-made alterations, which trace back even to Neolithic times (Carriónet al., 2003), the preservation of the richness in this range is mostremarkable.

Revolcadores, the highest mountain of the Murcian Regionshould be rescued from oblivion, at least, in a local context. Thevalue of the mountains of North-Western Murcia was indicated bySánchez-Gómez & Guerra (2003) and Del Valle et al. (2003). Amongst the localities selec-

554

Fig. 3.- Marxan’s best solution when we ignored the species penalty factor. Each sierra isfollowed by its abbreviated name (see Fig. 2) and the number of runs where it was selec-ted (with a maximum of 10,000 times).

Fig. 3.- La meilleure solution de Marxan quand on ignore le facteur de pénalité d’espèces.Chaque chaîne est suivie de son nom abrégé (cf. Fig. 2) et le nombre d’exécutions duprogramme où il a été choisi (avec un maximum de 10 000 fois).

Table VI.- RTS solu-tion.

Tableau VI.- Solutionde RTS.

Range

Siliceous Sierra Nevada

Gádor

Empanadas-Cabrilla-Castril

Tejeda

Cazorla-Pozo

Mágina

Calcareous Sierra Nevada

Las Nieves

María

Revolcadores

Siliceous Los Filabres-Baza

La Pandera

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Fig. 4.- RTS selection (see Fig. 2 for abbreviations).Fig. 4.- Choix de RTS (cf. Fig. 2 pour les abréviations).

ted in our analyses which are not under legal protection measures nowadays, it is necessa-

ry to mention La Pandera and Siliceous Los Filabres-Baza. Almost all the omissions men-

tioned will be corrected with the future European Network of Protected Areas which, in its

Sites of Community Interest (SCIs), includes all the selected localities (Orella et al., 1998),

except for La Pandera, which will remain unprotected and will be the most prominent gap

in the Natura 2000 Network.

The analysis matches up the first eight selected localities by ResNet to the six chorolo-

gical units established by Rivas-Martínez et al. (1997) and Rivas-Martínez et al. (2002) in

the Baetic ranges. If the biogeographic work of Sainz-Ollero and Hernández-Bermejo

(1985) is taken into consideration, the first four localities selected by ResNet correspond

to the four different sectors proposed for the Baetic high mountains by these authors. If we

take into account the four endemicity centres recognized by Mota et al. (2002), the cor-

respondence is also remarkably exact. In fact, the first five localities are sufficient to inclu-

de a representation of each of these centres. The diversity that signifies the radical

difference between the siliceous localities and the calcareous ones (Mota et al., 2002) is

also gathered in the dataset, since Siliceous Sierra Nevada appears among the most impor-

tant massifs while the following nine massifs are of calcareous nature. The great biogeo-

graphical distinctiveness of the proposed solution stresses its reliability and, also,

emphasises the suitability of the phytogeographic researches of the flora of the Baetic

ranges for the development of the conservation biogeography discipline.

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Acknowledgements - This work has been funded by the Spanish Organismo Autónomo de Parques Nacionales(Ministerio de Medio Ambiente) through the project 77/2002. We want to express our gratitude to A. Benavente, J.Algarra and F. Marchal for their comments on particular ranges, and to the very helpful staff of the HUAL, ALME andGDA-GDAC herbaria. We also want to express our thanks to S. Sarkar and H. Possingham for their comments andto C. Pappas and S. Sarkar for having provided us with the RTS software package. We are also indebted to E.Purbrick and F.J. Mota of Modus-Ponens Co. for the English translation.

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APPENDIX. Whole matrix of the 249 endemic taxa and its localities(next pages)

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