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This article appeared in a journal published by Elsevier. The attachedcopy is furnished to the author for internal non-commercial researchand education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling orlicensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of thearticle (e.g. in Word or Tex form) to their personal website orinstitutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies areencouraged to visit:
Optimizing protection efforts for amphibian conservation inMediterranean landscapes
Enrique García-Muñoz a,b,c,*, Francisco Ceacero d, Miguel A. Carretero c,Luis Pedrajas-Pulido a,b,c,d, Gema Parra b, Francisco Guerrero b
aCESAM, Centro de Estudios de Ambiente o do Mar, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, PortugalbDepartamento de Biología Animal, Biología Vegetal y Ecología, Campus de las Lagunillas, s/n. Universidad de Jaén, 23071 Jaén, SpaincCIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4485-661 Vairão, PortugaldDepartment of Animal Science and Food Processing. Faculty of Tropical AgriSciences. Czech University of Life Sciences. Kamycka 129, 165 21,Prague 6 e Suchdol, Czech Republic
a r t i c l e i n f o
Article history:Received 2 October 2011Accepted 25 February 2013Available online
Keywords:Amphibians declineExtinction riskManagement effortsPriority areasUmbrella species
a b s t r a c t
Amphibians epitomize the modern biodiversity crisis, and attract great attention from the scientificcommunity since a complex puzzle of factors has influence on their disappearance. However, thesefactors are multiple and spatially variable, and declining in each locality is due to a particular combi-nation of causes. This study shows a suitable statistical procedure to determine threats to amphibianspecies in medium size administrative areas. For our study case, ten biological and ecological variablesfeasible to affect the survival of 15 amphibian species were categorized and reduced through PrincipalComponent Analysis. The principal components extracted were related to ecological plasticity, repro-ductive potential, and specificity of breeding habitats. Finally, the factor scores of species were joined in apresence-absence matrix that gives us information to identify where and why conservation managementare requires. In summary, this methodology provides the necessary information to maximize benefits ofconservation measures in small areas by identifying which ecological factors need management effortsand where should we focus them on.
� 2013 Published by Elsevier Masson SAS.
1. Introduction
Amphibian populations are suffering significant decline world-wide. Several causes, such as habitat disturbance (Dunson et al.,1992; Blaustein et al., 1994), UV radiation (Bancroft et al., 2007),pathogens (Carey, 2000) and pollution (Carey and Bryant, 1995),have been proposed to explain the reduction in amphibian pop-ulations. If amphibian populations are in decline, it is also likelythat ecosystems in which they live are suffering a decrease inquality (D’Amen and Bombi, 2009). However, factors responsibleare multiple and spatially variable and, thus, declining in each lo-cality is likely to have its own particular combination of causes(Carey and Bryant, 1995). At least in most European landscapes,habitat alteration, fragmentation and destruction are probably themain causes of current and future amphibian populations declinesand species extinctions (Dodd and Smith, 2003; Stuart et al., 2004;Becker et al., 2007; Temple and Cox, 2009).
The main threat for amphibians in the study area is the intensiveolive tree monoculture, which occupies about 50% of the province(about 600,000 ha) and is the main cause of wetlands alteration(Ortega et al., 2003; Guerrero et al., 2006; García-Muñoz et al., 2009,2010a, 2010b, 2011a, 2011b). Among the species present in the studyarea are four urodels (Salamandra salamandra, Pleurodeles waltl, Tri-turus pigmaeus and Lisotriton boscai) four members of the familyAlytidae (Subfamily Alytidaewith twomembers:Alytes cisternasii andAlytes dickilleni; Subfamily Discoglosinae with two members: Dis-coglossus jeanneae and Discoglossus galganoi), two bufonids species(Bufo bufo and Bufo calamita), onemembers of the family Pelobatidae(Pelobates cultripes), two species of the family Pelodytidae (Pelodytespunctatus and Pelodytes ibericus), two species of the Family Hylidae(Hyla meridionalis and Hyla arborea) and one specie from the familyRanidae (Phelophylax perezi).
Resources for conservation are limited and their allocation mustbe carefully decided. Here, a case study in the south-eastern IberianPeninsula is used to implement a different approach for localconservation needs. In this sense, it is intended to tackle theproblem of amphibian decline, to determine key ecological and lifehistory trait requirements of the analyzed species, in order to pri-oritize allocation of the limited funds for conservation. Specifically,
* Corresponding author. CESAM, Centro de Estudios de Ambiente o do Mar,Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro,Portugal.
the objective is developing a replicable methodology to categorizethe study area according to low scale needs for management stra-tegies based on the biological and ecological variables feasible toaffect the survival of amphibian species.
2. Methods
2.1. Study area
The study area includes the administrative area of the Jaénprovince, Southern Spain (Fig. 1), which is divided into 169 UTM10 � 10 km squares. The importance of this area for amphibians isevident since it harbours 60% of the autochthonous species in theIberian Peninsula, and 100% of species in Andalusia region (Montoriet al., 2005). The network of protected areas in this region isconstituted by a total of eleven areas, mostly mountainous andlowland wetlands. The whole study area covers 13,500 km2, withan altitude range between 230 and 2167 m a.s.l.. Geographically, itis characterized by two main fluvial depressions (Guadalquivir andGuadiana Menor), with strongly anthropic alterations, and sur-rounded by major mountain ranges (Sierras Béticas and SierraMorena) with different characteristics and geological history. Fromthe herpetological point of view, this situation promotes the
presence of Iberian and North African species, but also Baetic andAtlantic endemisms (Ceacero et al., 2007; Pleguezuelos et al., 2002).
2.2. Selected variables
We assumed that the reproductive and ecological strategies of thespecies analyzed here have evolved in natural undisturbed systems.However, sincemanyenvironments arenowhighlydegraded, someofthese strategies may have greater risks (“low number of clutches” or“long larval period”) under awide range of commonpractices or evenunpredictable alterations of human origin. In consequence, currentpresence/absence (P) together with nine biological and ecologicalvariables feasible to affect the survival of amphibian species underhighly disturbed environments, were selected, categorized andanalyzed. These were: distribution range (DR); altitudinal valence(AV); reproductive strategy (RS); eggs (offspring) number (EN);breedinghabitats (BH);maximumage (MA); larval period length (LP);adult habitat (AH); and anthropic impacts (AI) (Table 1). These vari-ables were considered to cover main aspects related to the distribu-tion, demography, reproduction, ecology, habitat requirements, andanthropic impacts previously reported for every species in the studyarea. Species values for these variables were obtained from the liter-ature (Pleguezuelos and Moreno, 1990; Pleguezuelos, 1997, 2002;
Fig. 1. Study area that includes the administrative area of the Jaén province.
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García-París et al., 2004; Ceacero et al., 2007; García-Muñoz et al.,2010a,b), as well as field data and observations by the authors. Datafor IberianPaintedFrog (D. galganoi)weremergedwith those fromtheSpanish Painted Frog (D. jeanneae) because of the difficulty to differ-entiateboth specieswithoutgeneticanalysis (García-París et al., 2004)and because there is even disagreement about their specific status(Zangari et al., 2006; Velo-Antón et al., 2008). Nonetheless, no
differences between the ecological and biological traits of both Dis-coglossus have been described.
2.3. Statistical analysis
Principal Components Analysis (PCA) was performed with theten studied ecological and biological variables to reduce
Table 1Variables and categories used to assess the local risk of extinction. Higher values imply higher risk. Data for these variables were obtained from literature review (Pleguezuelosand Moreno, 1990; Pleguezuelos, 1997, 2002; García-París et al., 2004; Ceacero et al., 2007; García-Muñoz et al., 2010a,b).
Variable Categories and comments Assumptions
Presence/absencedata
Percentage of UTM 10 � 10 squaresoccupied by every species. 169squares were considered.
We assume that species with greaterdistribution area showed a lower riskof local extinction.
(P): 3: <25%; 2: 25e50%; 1: 50e75%;0 > 75%.
Distributionrange
Index of the distribution area ofspecies respect to its wholedistribution area.
We assume that endemic species havean intrinsic value per se due totheir rarity.
(DR): 3: Endemism; main distributionarea; 2: Isolated area; 1: Peripheralarea; 0: Area in the middle of thedistribution of the species.
Altitudinalvalence
Altitude ranges where every speciesmay occur.
We assume that species restrictedto a particular altitude are subjectto a higher probability of localextinction than those with awide range of altitudinaloccupation.
(AV): 3: Restricted by upper and loweraltitude constraint; 2: Only upperconstraint; 1: Only lower constraint; 0:Without altitude constraint.
Reproductivestrategy
Capability of every species to enjoyone or two breeding seasons per year,and how many clutches can they lay ineach one. This variable may be quitedifferent when applying this methodto other climatic regions.
We assume that species witha single clutch per year aremore likely to miss the singleclutch that species that performmultiple clutch per year.
(RS): 3: One reproductive period with onlyone clutch; 2: One reproductive periodwith several clutches; 1: Two reproductiveperiods (spring and autumn) with lonelyclutches; 0: Two reproductive periods with several clutches.
Eggs (offspring)number
Average number of eggs in everyclutch.
We assume that a lower investment in thenumber of eggs will result in less adaptivecapacity, in an ecosystem subject a significantvolume of changes in a very short period of time.
(EN): 3: <50; 2: 50e200; 1: 200e500; 0: >500 eggs/clutch.Breeding habitats Summatory of habitats where every species
may breed, and categorized ranging from 0 to 3:reservoirs, rivers, brooks or streams, lakes, semi-permanentponds, temporary ponds, great human facilities (pools,irrigation ditches, channels.), small humanfacilities (basins.).
Whether the species is capable of reproductionin a single type of habitat, this will mean a higherprobability of extinction, if the specific breedinghabitat changes or is destroyed.
(BH):
Maximum age Maximum age in the wild for every species. Whether the species is capable of living more years,there is a greater probability that a successful breedingseason occurs.
(MA): 3: 1 to 5 years; 2: 6 to 10; 1: 11 to 15; 0: >15.Larval period length Average duration of the larval period. If the larval period, usually aquatic, is long, the species
is more prone to suffer unavoidable exposure, such aspollutants, where the larvae can not avoid contaminationuntil they complete metamorphosis and move to theland environment.
(LP): 3: >6 months; 2: 3 to 6; 1: 2 to 3; 0: <2.Adult habitat Conservation degree beared by every species to survive
in an area.If a species is a generalist in terms of habitat selection,this species is supposed to be more adaptable to changesin the ecosystem and therefore less vulnerable to extinction.
Antropic impacts Number of anthropic impacts which affect everyspecies, further ranged from 0 to 3: aversion killing,road killing, emergent diseases, sensitivity to pesticides,sensitivity to exotic species, detectability degree.
We assume that not all species are affected similarly byhuman activities.
(AI):
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dimensionality among them. We considerer include also thePresence (P) in the study area in the PCA analysis, to take intoaccount the implicit risk of presenting a marginal distribution inthe study area. Factor with an eigenvalues greater or equal to 1.0were selected. In addition, factor coordinates of cases (species;value of each factor for the), the sum of the species factorial scoreswhen only considering the species present in the cell: whichmeans that the final score of a given cell, for each factorial axe, isboth influenced by the number of species present and the speciesscores on the considered factorial axe (Scores for each UTM squarecorrespond to:
PF*XSpi; where Fx: is the value of factor score for
the specie i; and Spi: denote the presence, 1, or absence, 0, of thespecie i).
Linear regression of each extinction risk component (F1, F2, andF3), were performed regarding the percentage of protected UTM10 � 10 squares where every species occurs. This analysis providesinformation about which species are infra- or overprotected in thestudy area respect to every extinction risk component.
Statistica 7 software for Windows (StatSoft Inc., 2005) was usedfor all statistical analysis.
3. Results
The scores for the independent variables considered to affectsurvival of amphibian species in the study area are shown inTable 2. The first three principal components (PC1, PC2, and PC3) inthe PCA analysis had eigenvalues higher than 1 and accounted for72.30% of the total variance among the studied biological andecological variables (Table 3). The first principal component (PC1:39.73%) was positively correlated with the species presence in thestudy area, altitudinal valence, eggs number, larval period lengthand adult habitat. The second principal component (PC2: 20.16%)was positively correlated with the reproductive strategy. Finally,the third principal component (PC3: 12.42%) was negativelycorrelated with breeding habitats used. Thus, these PrincipalComponents (PC1, PC2 and PC3) were interpreted as a gradient oflow ecological plasticity (PC1), as a gradient of the inability ofspecies to breed several times during the season (PC2), and asspecificity in breeding habitat (PC3). In Fig. 2 are shows the factorialmaps F1eF2 and F2eF3 for both species and traits.
Fig. 3 shows those areas where more species are present withgreater needs (greater scores) for management measures related toeach selected component. These scores for each cell were calcu-lated as the sum of the species factorial scores when only consid-ering the species present in the cell: which means that the final
score of a given cell, for each factorial axe, is both influenced by thenumber of species present and the species scores on the consideredfactorial axe. In Fig. 3a, those areas needing management measuresfor habitat conservation are indicated in darker squares. Fig. 3bshows those areas where disturbances in breeding habitats shouldbe avoided during the breeding periods. Fig. 3c shows areas with ahigh number of species with high breeding habitat specificity, andthus, individual management measures are needed for everyinvolved species.
Linear regressions showed which species were underprotected,considering every extinction risk component (Fig. 4). Only F1(R ¼ 0.573, p ¼ 0.025) correlates with the percentage of protectedUTM 10 � 10 squares where every species occurs. In contrast, F2(R ¼ 0.341, p ¼ 0.214) and F3 (R ¼ 0.242, p ¼ 0.286) are not coveredby the current protected areas network. Triturus pygmaeus,L. boscai, Alytes dickhilleni, A. cisternasii and H. meridionalis areinfraprotected species regarding the extinction risk component F1.P. walt, L. boscai, P. cultripes and B. bufo are underprotectedregarding the extinction risk component F2. Finally, B. calamita andP. cultripes are underprotected species regarding F3.
4. Discussion
Using an amphibian community in Southern Iberian Peninsulaas study case, a methodological procedure has been developed toidentify those areas where conservation actions should be focused.Specifically, this method indicates which factors constitute thegreatest extinction risk for each species and for each 10 � 10 UTM
Table 2Scores for the independent variables considered to affect survival of amphibian species in the study area (presence/absence data (P); distribution range (DR); altitudinalvalence (AV); reproductive strategy (RS); eggs (offspring) number (EN); breeding habitats (BH); maximum age (MA); larval period length (LP); adult habitat (AH); antropicimpacts (AI)), and factors coordinates of cases (F1, F2, F3).
Table 3Scores of the ten ecological and biological variables used in the factor analysis. Thesignificant structuring variables (>0.7, following Budaev, 2010 for small sample size)relative to each axis are indicated in bold characters. See Table 1 for further expla-nation about values and abbreviations.
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Fig. 2. Factorial maps F1eF2 and F2eF3 for both species and traits. Species coding: S. salamandra (1), P. waltl (2), T. pymaeus (3), L. boscai (4), A. dickhilleni (5), A. cisternasii (6),Discoglossus sp. (7), P. punctatus (8), P. ibericus (9), P. cultripes (10), B. calamita (11), B. bufo (12), H. meridionalis (13), H. arborea (14), P. perezi (15). Traits coding: Presence/absence data(P); distribution range (DR); altitudinal valence (AV); reproductive strategy (RS); eggs (offspring) number (EN); breeding habitats (BH); maximum age (MA); larval period length(LP); adult habitat (AH); Antropic impacts (AI).
Fig. 3. Priority areas (in darker squares) are those where more species with greater needs for especific management measures are present. Thus, Fig. 3A shows those areas needinghabitat conservation and permanent aquatic ecosystems. Fig. 3B shows those areas where disturbances in breeding habitats should be avoided during the breeding periods. Fig. 3Cshows those areas with a high number of species with high breeding habitat specificity, and thus, individual management measures are needed for every involved species.
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square; and thus, where measures to minimize extinction riskshould be enacted, and which kind of measures should beimplemented.
As has been shown the first principal component synthesizesinformation from several traits and species, and was related withlow ecological plasticity. B. calamita, P. perezi and Discoglosus sp.were shown to be species with greater ecological plasticity thatinhabit from polluted and altered areas, to unpolluted andconserved habitats. However, Discoglosus sp. has experienced adrastic decline in the study area in the last decade (authors’ per-sonal observation). This disappearance could be related with thelarval pollution sensitivity (García-Muñoz et al., 2010a,b) on thecontrary adults of this specie could be found in high polluted
habitat. Future studies will be necessary in order to detect thecauses of that decline. Two urodeles (Salamandra salamandra andL. boscai), both Alytes sp. and H. arborea were shown the specieswith lower ecological plasticity. Regardless H. arborea that presenta marginal distribution in the study area (Ceacero et al., 2007), theother three species showed low ecological plasticity. These speciesneed permanent or semi-permanent water bodies to completetheir larval development and this is a limited factor in Mediterra-nean habitat. On the other hand, the low tolerance to wetlandalteration is relegating the presence of these species only to themost conserved habitat (García-Muñoz et al., 2010a,b). In the casefor axis 2 and 3 (eachmainly based on one trait, i.e. RS for F2 and BHfor F3) give us information of those areas where disturbances inbreeding habitats should be avoided during the breeding periodsand areas with a high number of species with high breeding habitatspecificity, and where individual management measures need to bedeveloped in order to cover needed for every involved species.
This methodology provides the information for adequatelyallocating conservation resources in order to maximize theireffectiveness. Administrative authorities may then focus on certainareas where many species needing similar management measuresoccur. Additionally, management action plans focused on one orfew priority species may be useful for many others, getting synergicbenefits and enhancing the effect of these ‘umbrella species’ (seeamong others: Murphy and Wilcox, 1986; Noss, 1983; Franklin,1994; Tracy and Brussard, 1994). Therefore, we provide a system-atic procedure to objectively determine to what extent protectingputative “umbrella species” is covering the conservation need ofnot target species or, in other words, testing for their “umbrella”character. If it is indeed possible to manage ecosystem by focusingon the needs of one or a few species, then, the seemingly intractableproblem of considering the needs of all species may be solved.
Such a simple approach can be easily used by local adminis-trations to improve the efficiency of local management measuresbased on realistic available information. The use of bibliographicdata on life history to determine vulnerability to extinction andguide local conservation measures has previously been carried out(Reca et al., 1994, 1996; Ojeda et al., 2008). However, this kind ofevidence only provides an estimate of species richness, losing theinformation about biology and ecology of each species. On the otherhand, PCA, which has also been employed to establish criteria onstatus of populations and ecosystems, is now widely used in pro-tection and restoration (e.g. Andreone and Luiselli, 2000; Ortegaet al., 2004; De Meester and Declerck, 2005; Statzner andMérigoux, 2005; Egea-Serrano et al., 2006; Reed, 2006; García-Muñoz et al., 2010a,b).
According to the results, there are still substantial parts of theprovince that require protection. As shows in Fig. 3A, small pro-tected areas surrounded by agricultural land need to conservenatural habitat and more permanent water bodies in order toprotect species with a longer aquatic larval development, such asAlytes sp. In the case of Fig. 3B, the results showed how Cazorla,Segura and Las Villas National park need to avoiding disturbancesin breeding habitats during the breeding seasons. The high level oftourism to this area, which involves cleaning of fountains in orderto improve the aesthetics of tourism (personal observation), in-volves the loss of newcohorts of individuals especially in the case ofAlytes dickhilleni and S. Salamandra, that breed opportunistically inthis artificial water points. In the case of Fig. 3C, a black square ishighlights in the middle of Guadalquivir basin, in this point alivestock watering (Fuente la Zarza) need urgent management inorder to preserve the high diversity of amphibians that breed in thissmall aquatic point (approx. 1 m3).
The protected areas network certainly maintains importantterritories for amphibians’ conservation. However, according to the
Fig. 4. Linear regression plot of extinction risk components (F1, F2, and F3) values forthe studied species regarding the percentage of the squares where they are presentholding protected areas. Confidence intervals at 95% show which species are infrap-rotected [above the interval for F1 and F2; below the interval for F3 because correlationof this factor with breeding habitat is negative] regarding the studied extinction riskcomponent. Coding: S. salamandra (1), P. waltl (2), T. pymaeus (3), L. boscai (4),A. dickhilleni (5), A. cisternasii (6), Discoglossus sp. (7), P. punctatus (8), P. ibericus (9),P. cultripes (10), B. calamita (11), B. bufo (12), H. meridionalis (13), H. arborea (14),P. perezi (15).
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results, there are still substantial parts of our study area whichrequire protection. As previously shown, there are species withhigh risk of extinction (P. waltl, T. pygmaeus, L. boscai, A. cisternasii,A. dickhilleni, B. bufo, B. calamita, H. meridionalis, and P. cultripes)which are not adequately covered by the protected areas (seesimilar data in the same study area in García-Muñoz et al., 2010a,b).Preventing the local extinction of these species goes throughexpanding protected areas or by performing specific conservationplans to minimize their threats. Developing a replicable method-ology (especially based on standardized local data) is, hence, rele-vant, especially because it can be applied at different spatial andtemporal scale to determine conservation priorities.
Our method provides an alternative way to estimate conserva-tion risks based on a statistical approach, easily interpretable. Inaddition, the factors responsible for amphibian decline (see amongothers, Schuytema and Nebeker, 1999; Houlahan et al., 2000;Tejedo, 2003) do not affect to different populations of the samespecies in the same way, since these factors vary locally (Carey andBryant, 1995). Thus, the results calculated for different areas may beused to link conservation plans at large scale. On the other hand,this methodology produces similar outputs than habitat suitabilitymodels (e.g. Sillero, 2010) without needing so many detailed re-cords, whereas uses ecological and biological variables of species toproduce mechanistic models instead of usual correlative ones.Nevertheless, further research may combine both approaches todevelop conservation models in response to novel ecosystemsituations.
5. Conclusions
In conclusion, developing a replicable methodology (based onlocal data) is hence relevant, especially because it can be applied atdifferent spatial scale to determine conservation priorities. Insummary, understanding amphibian decline, as a sum of factorsthat vary locally, could be used in developing indices applicable tomedium size areas. In last term, this provides tools for protectingamphibians more successfully and at reasonable costs for conser-vation authorities.
Acknowledgments
Authors wish to thank Asociación Española de Herpetología,Luis Pedrajas and Antonio Hidalgo-Pontiveros for providing distri-bution data. Neftalí Sillero assisted during construction of Fig. 3.EGM was supported by post-doc funding (SFRH/BPD/72806/2010)by Fundação para a Ciência e a Tecnologia, Portugal.
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