Lithospheric deformation in the Africa-Iberia plate boundary:...

Lithospheric deformation in the Africa-Iberia plateboundary: Improved neotectonic modelingtesting a basal-driven Alboran plateM. Neres1,2, M. M. C. Carafa3, R. M. S. Fernandes4, L. Matias1, J. C. Duarte1,5, S. Barba6,and P. Terrinha1,2

1Instituto Dom Luiz, University of Lisbon, Lisbon, Portugal, 2Instituto Português do Mar e da Atmosfera, Lisbon, Portugal,3Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Tettonofisica e Sismologia, L’Aquila, Italy, 4Instituto Dom Luiz,University of Beira Interior, Covilhã, Portugal, 5School of Earth, Atmosphere andEnvironment,MonashUniversity,Melbourne,Victoria, Australia, 6Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Tettonofisica e Sismologia, Rome, Italy

Abstract We present an improved neotectonic numerical model of the complex NW Africa-SW Eurasiaplate boundary segment that runs from west to east along the Gloria Fault up to the northern Algerianmargin. We model the surface velocity field and the ongoing lithospheric deformation using the most recentversion of the thin-shell code SHELLS and updated lithospheric model and fault map of the region. To checkthe presence versus the absence of an independently driven Alboran domain, we develop two alternativeplate models: one does not include an Alboran plate; another includes it and determines the basal sheartractions necessary to drive it with known velocities. We also compare two alternative sets of Africa-Eurasiavelocity boundary conditions, corresponding to geodetic and geological-scale averages of plate motion.Finally, we perform an extensive parametric study of fault friction coefficient, trench resistance, and velocitiesimposed in Alboran nodes. The final run comprises 5240 experiments, each scored to geodetic velocities(estimated for 250 stations and here provided), stress direction data, and seismic strain rates. The model withthe least discrepancy to the data includes the Alboran plate driven by a basal WSW directed shear traction,slightly oblique to the westward direction of Alboran motion. We provide estimates of long-term strain ratesand slip rates for the modeled faults, which can be useful for further hazard studies. Our results support that amechanism additional to the Africa-Eurasia convergence is required to drive the Alboran domain, which canbe related to subduction processes occurring within the mantle.

1. Introduction

Understanding the Earth’s dynamics is essential for assessing natural hazards. Special attention should bepayed toplateboundaries,wheremostof the stress accumulationcausedbyplate tectonics is released throughearthquakeswhose frequency andmaximummagnitudesdependon several geological and kinematic factors,specificofeachboundary segment.Numericalmodels canprovideasignificantcontribution to theunderstand-ing of plate boundaries evolution and thus help predict future behavior. They can be updated, improved, andtuned by adjusting several parameters and by testing alternative scenarios. In some cases, a model’s outputscan thenbeusedas input in subsequent studies, e.g., for theestimationof the seismic and tsunamihazard asso-ciated with tectonic motions. For example, Bird and Liu [2007] and Carafa et al. [2015a] estimated long-termaverage seismicity based on outputs from kinematic and neotectonic numerical modeling.

The Africa (Nubia)-Eurasia plate boundary segment that runs from the Azores, in the North Atlantic, up to thenorth Algerianmargin, in theMediterranean, is particularly complex (Figure 1). To the east of the Azores TripleJunction the plate boundary coincides with a relative discrete transform/fracture zone (the Gloria Fault); how-ever, it becomes diffuse as it approaches the SW Iberianmargin. In the SW Iberian offshore, across the Strait ofGibraltar and up until the northern Algerian margin, many distinct structures accommodate the convergencebetween Africa and Iberia. The type of deformation on this area lies well within the definition of “plate bound-ary zone” of Stein and Sella [2002] or “orogen” of Bird [2003]; here the deformation is being distributed overmany discrete structures [Morel and Meghraoui, 1996; Hayward et al., 1999; Jimenez-Munt et al., 2001a;Terrinha et al., 2009; Zitellini et al., 2009; Duarte et al., 2013b] with the existence of some stranded tectonicblocks, the main being the Alboran terrane [e.g., Rosenbaum et al., 2002; Palano et al., 2015]. Over the years,several authors have defended the existence of an independent tectonic domain encompassing the

NERES ET AL. NEOTECTONIC MODELING IN AFRICA-IBERIA 6566

PUBLICATIONSJournal of Geophysical Research: Solid Earth

RESEARCH ARTICLE10.1002/2016JB013012

Key Points:• Long-term velocity field, deformation,and fault slip rates are modeled forAfrica-Iberia plate boundary

• Preferred scenario among severalincludes a third Alboran plate andAF-EU motion defined by geodeticvelocity model

• Alboran is driven by slab-related basalmechanisms, and slab dynamics haseffects on lithospheric processes

Supporting Information:• Supporting Information S1• Data Set S1• Data Set S2• Data Set S3• Data Set S4• Data Set S5• Data Set S6

Correspondence to:M. Neres,[email protected]

Citation:Neres, M., M. M. C. Carafa, R. M. S.Fernandes, L. Matias, J. C. Duarte,S. Barba, and P. Terrinha (2016),Lithospheric deformation in theAfrica-Iberia plate boundary: Improvedneotectonic modeling testing a basal-driven Alboran plate, J. Geophys.Res. Solid Earth, 121, 6566–6596,doi:10.1002/2016JB013012.

Received 24 MAR 2016Accepted 25 JUL 2016Accepted article online 29 JUL 2016Published online 17 SEP 2016

©2016. American Geophysical Union.All Rights Reserved.

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http://dx.doi.org/10.1002/2016JB013012

http://dx.doi.org/10.1002/2016JB013012

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http://dx.doi.org/10.1002/2016JB013012

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Alboran Sea and part of the Rif and Betics [e.g., Gutscher et al., 2002; Koulali et al., 2011]. Whereas some studiesmarked along this domain a linear transpressive plate boundary, sometimes diffuse or with zigzag geometry[McKenzie, 1970; Morel and Meghraoui, 1996; Bird, 2003], other studies considered the Alboran region as onemore piece in the complex puzzle of the Western Mediterranean boundary region, which is made of severaltectonic arcs, microplates, and back-arc basins (see Figure 1a) [e.g., Royden, 1993; Lonergan and White, 1997].Active rollback subduction below the Gibraltar Arc has been suggested as the driving mechanism for theAlboran domain [Royden, 1993; Lonergan and White, 1997; Gutscher et al., 2002], and the presence of a sub-ducted slab has been later imaged by tomographic studies [e.g., Bijwaard and Spakman, 2000; Calvert et al.,2000; Spakman and Wortel, 2004]. However, discussion still remains concerning the slab’s activity and its rolein driving motion and deformation of the Alboran domain [e.g., Cunha et al., 2012].

Figure 1. Geological setting of the study area. (a) Africa-Eurasia plate boundary from the Mid-Atlantic Ridge to the Anatolia (AN) plate. From the Azores to northTunisia the plate boundary was updated in this work, and an Alboran (AL) plate was defined (see section 4.3). In the Mediterranean region, several microplatesare recognized, such as the Adria (AD), Ionian Sea (IO), and Aegean Sea (AE) plates (shown boundaries are from Carafa et al. [2015a]). In this work, only EU and AFplates are considered for the 2plates configuration; for the 3plates configuration, the inclusion of the AL plate is modeled, through the imposition of surface velocityconditions in some internal nodes and inferred basal conditions (see section 5.3). (b) Study region for this work, with the main faults or fault zones marked in red.Abbreviations: AH: Al Hoceima fault; AR: Alboran Ridge; C-BS: Crevillente/Bajo Segura fault zone; CF: Cadiz Fault; CPR: Coral Patch Ridge; HF: Horseshoe fault; LTV:Lower Tagus Valley; MP: Marquês de Pombal fault; PB: Portimão bank; PF: Portimão fault; PS: Pereira de Sousa fault; SL: Seia-Lousã; TAP: Tagus Abyssal Plain fault;SV: São Vicente fault.

Journal of Geophysical Research: Solid Earth 10.1002/2016JB013012


In this work we aim at contributing to a better understanding of the geodynamics and neotectonics of thiscomplex segment of the Africa-Eurasia plate boundary, with particular emphasis in the Gulf of Cadiz-Gibraltar Arc-Alboran domain. We aim at bringing some insight into the following questions: How is deforma-tion accommodated among the different active faults and within the continuum of the Africa-Iberia plateboundary zone? Which kinematics (shortening, extension, strike slip) is expected to prevail along the differ-ent segments of this complex plate boundary? Is the existence of an independent Alboran plate necessary tojustify the abnormal velocities in GPS stations within the Alboran domain?

To do so, we have compiled an up-to-date simplified tectonic map of the Africa-Iberia plate boundary thatextends from the Gloria Fault up to the northern Algerian margin. We then performed a series of finite ele-ment numerical experiments to test different parameters and plate scenarios; in particular, including orexcluding an independent Alboran plate. We scored each experiment according to its agreement with geo-detic velocities, stress data, and earthquake catalog, through two separate scoring evaluations, in which weconsider respectively the whole modeled region and a restrict region of main interest, centered in the Gulf ofCadiz-Alboran domains. Finally, we discuss the implications of our results on geodynamics and neotectonicsof the study area.

2. Tectonic Setting

The study area corresponds to a segment of the Africa (Nubia)-Eurasia (Iberia) plate boundary that extendsfrom the eastern termination of the Azores plateau (the Triple Junction zone between the Nubian,Eurasian, and North American plates) up to the northern Algerian margin (Figure 1).

Note that in this work, when we mention the Africa (AF) plate motion, we specifically refer to the Nubia plate.Even though the African continent is divided into various tectonic units [Fernandes et al., 2013], the study areais restricted to the Nubia-Eurasia plate convergence zone.

2.1. Northeastern Atlantic and Southwest Iberian Margin

In the westernmost segment of the study area, the deformation resulting from the relative motion betweenAfrica and Eurasia is mostly accommodated along a transform plate boundary, the Gloria Fault (see Figure 1).To the east of the Gloria Fault, SW of Iberia, the deformation becomes diffuse [Sartori et al., 1994] and is parti-tioned [Terrinha et al., 2009] among several different thrust and wrench faults (e.g., Portimão Fault, CoralPatch Ridge Fault, and SWIM strike-slip faults; see Figure 1). These faults result from the reactivation of oldcontinental and oceanic tectonic fabrics that formed during the opening of the Atlantic and the formationof an oceanic passage (the westernmost part of the Neotethys) that linked with the Atlantic duringJurassic-Cretaceous times [e.g., Duarte et al., 2011; Sallares et al., 2011; Martínez-Loriente et al., 2013].

The SW Iberia-Gulf of Cadiz segment of the plate boundary is characterized by a WNW-ESE oblique dextralconvergence between Africa (Nubia plate) and Eurasia (Iberia block) of 4–5mm/yr [Fernandes et al., 2003;Stich et al., 2006; Nocquet, 2012]. The strain is accommodated by moderate- to large-magnitude earthquakesat shallow to intermediate depths, up to 60 km, most of them clustering along lineations with preferredorientation of NNE-SSW and WNW-ESE [Buforn et al., 1995; Stich et al., 2005a; Geissler et al., 2010; Custódioet al., 2015; Grevemeyer et al., 2016], which mostly coincide with segments of thrust and strike-slip faults andsometimes localize at fault intersections [Rosas et al., 2012]. An important cluster in south Portugal trendsENE-WSW, along the Cadiz fault, possibly accommodating perpendicular shortening by thrusting and right-lateral tectonics [Duarte et al., 2009, 2013b].

High to very high magnitude historical and instrumental events occurred in this region, such as theMw 8.5–9Great Lisbon earthquake in 1755 and the 1969 Mw 7.9 earthquake [Fukao, 1973; Abe, 1979; Johnston, 1996;Solares and Arroyo, 2004], whose tectonic origin remains a matter of discussion [e.g., Gutscher et al., 2002;Thiebot and Gutscher, 2006; Terrinha et al., 2009; Rosas et al., 2016].

Some of the ongoing deformation offshore SW Iberia seems to be propagating northward, away from theeast-west trending Africa-Eurasia plate boundary zone, along a NE-SW thrust system composed of theHorseshoe, Marquês de Pombal, Gorringe, and Tagus Abyssal Plain thrust faults, i.e., parallel to the westIberia continental margin (Figure 1b). This system is depicted on the subseafloor by a set of deep-rootedthrust faults, some of which reactivate extensional (rift) structures [e.g., Terrinha et al., 2009; Zitellini et al.,



2009; Duarte et al., 2013b]. These structures are spatially associated to seismicity clusters and deform the sea-floor with escarpments that can reach 5 km in height and 200 km in length. Over the years, this thrust systemhas been considered by several authors as a possible locus of subduction initiation [Purdy, 1975; McKenzie,1977; Mueller and Phillips, 1991; Royden, 1993; Ribeiro et al., 1996; Duarte et al., 2013b].

2.2. Gibraltar Arc

The central region of the study area is characterized by the presence of an orogenic arc, the Gibraltar Arc, alsoknown as the Betics-Rif Arc. The Gibraltar Arc resulted from lateral thrusting of a subduction zone that devel-oped as part of the Western Mediterranean tectonic back-arc system during the Cenozoic as a consequenceof the deceleration of the convergence of Africa toward Eurasia and the southward retreat of the subductionzones [Royden, 1993; Lonergan and White, 1997; Gutscher et al., 2002; Rosenbaum et al., 2002; Gutscher et al.,2012]. The arcs eventually collided with continental northern Africa, ceasing the activity of subduction zones,with the exception of two segments that escaped laterally: the Calabria and the Gibraltar Arcs [Gutscher et al.,2002; Rosenbaum et al., 2002] (Figure 1a). The Gibraltar Arc reached its present position during the LateMiocene, leading to the ephemeral closure of the Mediterranean, the development of the Alboran back-arc basin, and the emplacement of an accretionary wedge in the Gulf of Cadiz [Royden, 1993; Lonerganand White, 1997]. During the westward migration of the Gibraltar subduction zone, due to slab rollback, acontinental portion of the overriding plate (sometimes called terrane or block) was ripped off from northeast-ern Iberia and transported southwestward until it collided and became stranded between Africa and Iberia,forming the Betics and Rif mountain chains and constituting the present-day expression of the Gibraltar Arc.Since then, due to the continuing convergence between Africa and Eurasia, it is believed that the subductionzone decreased its activity, with the slab being partially delaminated below the Betics [Duarte et al., 2013b(for a discussion); Mancilla et al., 2013; Levander et al., 2014;Mancilla et al., 2015]. Nonetheless, based on geo-detic data, several works suggest that the Alboran domain is still an independent tectonic block [e.g., Fadilet al., 2006; Koulali et al., 2011], and some authors have attributed this apparent independent motion tothe fact that subduction-induced slab pull is still being exerted at the surface [Gutscher et al., 2012; Duarteet al., 2013b]. The Alboran back-arc basin is made of extended continental lithosphere, and calc-alkalinearc magmatism is known in the region, in particular along the Alboran Ridge and several other isolatedvolcanoes [Duggen et al., 2004; Gill et al., 2004]. It is crosscut and bounded by several NE-SW transcurrentstructures and fault zones, such as Nekor and Al Hoceima in the south and the Carboneras fault in the north-east (which define the Trans-Alboran shear zone).

The seismicity in the Gibraltar Arc region is mostly of twomain types: (a) shallow to intermediate seismicity alongthe Betics-Rif Mountains and the NE-SW Alboran Ridge, Carboneras, and northern fault systems (Figure 1b)[d’Acremont et al., 2014]; and (b) intermediate to deep seismicity related to the presence of the subducted slab[Mancilla et al., 2013, 2015]. One striking observation is that the accretionary wedge is absent of seismicity, a factthat has led some authors to interpret it as an inactive structure [e.g., Zitellini et al., 2009] and others to suggestthat the stress could be accumulating aseismically or that the megathrust would be locked [Gutscher et al., 2002].The latter authors have suggested the Gibraltar subduction zone as the source of the 1775 Great Lisbon earth-quake, while others favor a location farther to the west, along the NE-SW thrusts [e.g., Zitellini et al., 2009].

2.3. Tell-North Algerian Margin

The formation of the Tell-north Algerian margin is also related to the development and migration of theWestern Mediterranean arc-back-arc system until collision with north Africa [e.g., Lonergan and White,1997; Rosenbaum et al., 2002] (Figure 1a). During the Neogene, a subduction system that once plungedbelow continental Iberia retreated southward transporting several (fore-arc) continental terranes, theKabylies, which collided with the northern African continent leading to cessation of that segment of thesubduction system and formation of the Tell thrust belt [e.g., Roure et al., 2012]. While the subductionmigrated, a Neogene back-arc basin was open, the Algerian basin. Recent geophysical studies support thatthe continued Africa-Eurasia convergence is leading to the reactivation of the southern segment of the pas-sive margin of the back-arc basin and possible forced subduction initiation [Déverchère et al., 2005].Moderate- to high-magnitude thrust earthquakes on the Algerian margin express the transpressional tec-tonics resulting from present-day convergence between Eurasia and Africa in the west Mediterranean[Kherroubi et al., 2009; Billi et al., 2011; Hamai et al., 2015]. Onshore, even though in the Tell front theTethyan slab has broken off and subduction is no longer active, it still shows some moderate seismicity



and active faulting [Billi et al., 2011]. Also, several active thrust faults mark the contact between the Kabyliesand the Tell (e.g., the El Asnam and Djurdjura faults; Figure 1b), which are offset by transfer faults. In theoffshore region, the North Africa offshore thrust (Figure 1b) marks the domain corresponding to the reac-tivation of the margin.

2.4. Africa and Iberia Intraplate Deformation

As described above, to the east of the Gloria fault most of the deformation related to the Africa-Iberia conver-gence is accommodated along a diffuse plate boundary zone. However, there are also significant tectonicallyactive intraplate structures, both within Iberia and Africa. Within northern Africa, the Atlas Mountains and theTell front are the most active structures. Within continental Iberia there are also several active structures(Figure 1b) that include the late Variscan NE-SW sinistral strike slips (Vilariça-Bragança and Régua-Verin faults),the Serra da Estrela pop-up (bounded by Ponsul and Seia-Lousã faults), and the Lower Tagus Valley fault zone,the latter known for its moderate shallow seismicity. Other important structures in the offshore of Iberia are thethrusts that delineate the Estremadura Spur. All these structures seem to be reactivating Paleozoic tectonicfabrics and have low to moderate seismicity.

3. Modeling Approach3.1. Deformation Models

There are two main ways of modeling lithospheric deformation: the kinematic approach and the dynamicapproach. In kinematic modeling long-term horizontal velocity field is constrained by simultaneously invert-ing all available geophysical information, such as GPS-derived velocities and stress data records. Models ofthis type rarely explain the fundamental tectonic mechanisms and leave no independent data sets availablefor postprocessing testing. The kinematic approach emphasizes the role of geodetic data, and it is often thepreferred method for modeling on-land deformation. However, it does not allow a consistent estimation ofthe offshore long-term deformation, where the subjective choice of the active faults to insert into the modelstrongly determines the localization of deformation, with negligible influence left to other geophysical data.On the other hand, in the dynamic modeling approach the stress equilibrium equation is solved using esti-mated rock rheologies, layer thicknesses, and boundary conditions; i.e., the velocity field is forward calculatedfrom the known structure and physics of the Earth. In this case, several data sets (e.g., geodetic velocities, faultslip rates, and stress directions) can be used to assess the accuracy of the model predictions.

In the last years, a variety of multilayered 3-D dynamic models unraveled different aspects of lithosphere andmantle dynamics, with particular emphasis in the process of subduction [e.g., Stegman et al., 2006; Chertovaet al., 2014] and rifting [e.g., Brune et al., 2014; Püthe and Gerya, 2014]. Even though these models succeed inmodeling the large-scale viscoplastic behavior of tectonic plates and underlying mantle, they lack the appro-priate resolution to model the upper crustal volume of the lithosphere, making them still elusive for seismichazard purposes or better understanding of upper crustal processes.

Here we use the thin-shell (2.5-D) finite element numerical code SHELLS [Kong and Bird, 1995; Bird, 1999; Birdet al., 2008], which in its last version [Bird et al., 2008] can be seen as a “hybrid” code, as it merges some char-acteristics of both kinematic and dynamic modeling (see section 3.2). As SHELLS is very cost effective, it allowsan extensive exploration of the parameter space and testing of different geodynamic scenarios.

3.2. SHELLS and Computation Summary

The code SHELLS [Bird, 1999, and references therein] solves the stress equilibrium equation for a finite ele-ment grid, based on vertically integrated and laterally varying lithospheric data; estimated rock strengthsand densities; and lateral, basal, and/or internal boundary conditions. SHELLS determines the long-termaverages of tectonic strain and motion over many earthquake cycles and outputs results such as horizontalsurface velocities, slip rates on faults, strain rates in the continuum elements, and stress orientation.

The lithosphere is two-layered (crust and lithospheric mantle), and for each layer the rheology (relationshipbetween integrated stress and strain rate tensors) is given by a rigid-plastic stress contribution from its upperfrictional part and a power law dislocation creep term for its lower part (for details on the rheology used inSHELLS please refer to Bird and Piper [1980], Bird [1999], and Carafa and Barba [2011]). Faults are assumed(inserted in the FEG as special curvilinear elements), and their rheology is identical to continuum elements,



except for a lower friction coefficient applied to the fault surfaces (FFRIC; see modeled values in Table 2) than onthe continuum elements (CFRIC= 0.85). The lithosphere can deform laterally and continuously: slipping faultscan be placed not only along plate boundaries but also in plate interiors, and permanent deformation can beaccommodated everywhere.

We use the last released version of SHELLS (August 2006), described in detail by Bird et al. [2008]. This last ver-sion guarantees the balance of lithostatic, side, and basal torques for each plate; the respective final force tri-plet, the meaning of which is extensively described by Bird et al. [2008], can be used for discussion of drivingversus resisting mechanisms for each plate. However, each of these torques incorporate the contribution ofseveral driving mechanisms that cannot be individually distinguished. For example, the basal strength torquecorresponds to the sum of basal drag (widely distributed), net slab pull (sum of opposed slab pull and sub-duction resistance), and slab suction (trench-directed traction induced by asthenospheric convection arounda sinking slab and applied to both adjacent plates); however, only the resultant basal traction can be deter-mined by SHELLS, regardless of its causing mechanism(s) [see Bird et al., 2008, sections 1 and 2].

A further advantage of this last version of SHELLS is the enhanced feature of additional velocity regulation byapplying distributed shear tractions at the base of the plates, as well as the possibility of defining velocity bound-ary conditions in internal nodes. The result is a “hybrid” code, in which kinematic constraints (edge and internalboundary conditions) are used to drive modeling toward results that better reproduce real Earth observations.

In this work basal shear tractions are applied under all the plates (see section 4.3). The initial punctual velocityconditions are reproduced in terms of distributed basal shear tractions that (approximately) impose the long-term motion to the whole plate. The shear tractions are calculated iteratively through the following steps:

1. Compute an initial model with no basal shear tractions but with velocity boundary conditions (imposedon edge and/or in internal nodes).

2. For each plate, compute the torque that is due to the velocity output from the previous model [Bird et al.,2008, equation (A9)]. Find a set of distributed basal shear tractions exerting the same torque. Run SHELLSagain imposing these basal shear tractions and maintaining the velocity conditions.

3. Iterate step 2 as needed, until the residual torques, generated by the artificial boundary conditions,become smaller than the torque associated with distributed basal tractions.

4. Compute a final model in which the internal velocity conditions are removed and the plates are driven bythe distributed basal shear tractions that most correctly reproduce the initial velocity conditions.

During the iteration process, the lithostatic pressure torques remain constant, and the side strength torquesslightly fluctuate according to basal strength torque variation, for maintaining the torque balance on each plate.

In this work, for each experiment, velocity convergence was achieved after five iterations of step 2, and so awhole experiment was complete after seven runs of SHELLS.

3.3. Previous Models and Improvements

Several thin-shell finite element models, using the code SHELLS, have been published for this region of theAfrica-Eurasia plate boundary. Some completely overlap our targeted area [Jimenez-Munt et al., 2001b;Jimenez-Munt and Negredo, 2003; Bird et al., 2008; Cunha et al., 2012; Carafa et al., 2015a], while others onlycover it partially [Negredo et al., 2002; Jimenez-Munt et al., 2003]. The most recent models, published byCunha et al. [2012] (centered in the Gulf of Cadiz) and Carafa et al. [2015a] (covering the whole Azores-Mediterranean-Europe region), significantly improved upon their predecessors. On the one hand, Cunhaet al. [2012] considerably updated the tectonic and geodetic data set with respect to previous models,which allowed achieving a detailed modeling of the strain distribution of the area. However, these authorshave used an earlier version of the SHELLS code, which had meanwhile undergone significant improve-ments (the modifications are described in Bird et al. [2008]). Moreover, updated lithospheric, geodetic,and stress data sets have meanwhile become available. On the other hand, Carafa et al. [2015a] alreadyused the updated SHELLS version. However, they carried a large-scale modeling and focused on discussingthe driving mechanisms of the Central and Eastern Mediterranean tectonic plates. Therefore, their modelingdoes not allow a detailed study of the sources recognized in our study area. They in fact acknowledge thattheir model needed to be improved in this area, given the high geodetic and stress misfits. Finally andimportantly, none of these models tested the effects of the presence of a subducting slab below theGibraltar-Alboran region, the existence of which is now undisputable. The slab, even if partially detached



[Mancilla et al., 2015], continues sinking into the upper mantle, induces a mantle flow, and affects thedynamics of the lithospheric plates [e.g., Duarte et al., 2013a]. It was, therefore, imperative to improvethe neotectonic model in this region, incorporating and testing the effect of a dynamic system with the pre-sence of an independent slab-related Alboran block, driven by a mechanism modeled through tractionsapplied at its base (see section 3.2).

We accomplish this by (i) integrating all the new available lithospheric data; (ii) combining fault databases(SHARE [Basili et al., 2013] and QAFI [García-Mayordomo et al., 2012]) with our expertise in fault mappingand regional geology; (iii) gathering the most complete and updated geodetic, stress, and earthquake scor-ing data sets; and (vi) testing the presence of an Alboran plate and inferring about the importance of basaldriving mechanisms.

4. Buildup of Finite Element Model4.1. Finite Element Grid—Geometry and Faults

For building our finite element grid (FEG) we divided our study area in nearly identical, almost equilateralspherical triangles with about 27 km of side length. Then we edited the grid for inserting the active faults,by moving nodes to coincide with fault traces and refining the grid around them.

Along thewell-recognizedGloria fault and thenorthern offshoreAlgerianmargin, continuous fault traceswereinserted along the plate boundaries. However, in the Gulf of Cadiz no continuum fault trace was defined alongthe plate boundary, to avoid favoring any single fault as the main deforming structure, since deformationthere is more diffuse. The on-land and offshore faults inserted in the grid correspond in general to the seismo-genic sources present in the European Database of Seismogenic Sources [Basili et al., 2013], in the QuaternaryActive Faults Database of Iberia [García-Mayordomo et al., 2012], and to other seismogenic sources documen-ted in the literature (see section 2 and Figure 1). Fault dipswere assigned according to available information onthe fault geometry and kinematics. We acknowledge that in some areas our model may be affected by anincomplete mapping of active faults, in particular in offshore areas where data about blind or quiescent faultsare scarce. However, the fact that SHELLS considers a continuum deformable lithosphere allows that fault sliprates of any missing faults will appear in our models as nearby off-fault deformation (see section 3.2).

The final 2-D grid consists of 5922 nodes, 11,031 triangular continuum elements, and 325 curvilinear faultelements (Figure 2). The respective FEG file is available as supporting information in Data Set S1, and the faultdatabase is available as Data Set S2.

4.2. Nodal Data and Lithosphere Structure

The structure, density, and strength of the lithosphere were described by six scalar data values, defined on eachnode of the finite element grid: elevation, heat flow, thickness of the crust, thickness of the lithospheric mantle,density anomaly due to lithological variations, and curvature of the geotherm due to transient heating or cool-ing. Calculations and data assignment to each grid node were done using the code OrbData5 (http://peterbird.name/oldFTP/neotec/Shells/OrbData/). Elevation data come from ETOPO1 grid [Amante and Eakins, 2009], a1 arcmin global relief model that integrates land topography and ocean bathymetry. It is represented inFigure 1. For model parameters not described or quantified here, please refer to Table 1 of Bird et al. [2008].4.2.1. Heat FlowIndividual heat flow data were downloaded from the International Heat Flow Data Commission database (lastupdated on 12 January 2011, available at http://www.heatflow.und.edu/data.html). In order to account forseveral difficulties in dealing with these data (nonuniform spatial distribution of real data and possible biasesdue to sampling scheme and local surface processes), we followed Bird et al. [2008] and Carafa et al. [2015a] infiltering data to values between 0.037Wm�2 (which corresponds to typical values in the thermally stationaryold European shield rocks) and 0.14Wm�2 (a limit that corresponds to atypical geothermal and volcanicareas) and also assigning a value of 0.054Wm�2 in points 50 km spaced to regions absent in data points,to help stabilize the interpolation. In the Sahara region, some data points having implausibly high valuesfor stable continental shields (most probably for being affected by surface processes) were thus lowered to0.058Wm�2. We then interpolated using a spline smooth with a 0.5° resolution grid. The resulting heat flowgridded data are represented in Figure 3a (see also section 4.2.4).



http://peterbird.name/oldFTP/neotec/Shells/OrbData/

http://peterbird.name/oldFTP/neotec/Shells/OrbData/

http://www.heatflow.und.edu/data.html

Contrarily to previous works using this version of SHELLS [Bird et al., 2008; Carafa et al., 2015a], we decided tonot infer heat flow from seafloor age, because of uncertainties about the age and nature of the oceanic crust insignificant parts of the modeled region (Atlantic margin of Iberia) [e.g., Sibuet et al., 2007; Bronner et al., 2011;Sallares et al., 2011]. We further verified that combining both approaches (data interpolation for continentalareas and inference from seafloor age for oceanic areas) in a regional and detailed model would originatestrong and likely artificial discontinuities in the lithosphere structure, which could bias the lateral variationof velocity and stress fields. By performing several tests, we found that using only interpolated data is a betteroption, leading to smoother variation and better approximation of modeled results to natural observations.4.2.2. Crustal ThicknessCrustal thickness was assumed from the EPcrust model of Molinari and Morelli [2011], which is derived fromthe collection and critical integration of information selected from the literature, such as active source stu-dies, receiver functions, surface waves, and geologic information. It represents the crust in three layers (sedi-ments, upper crust, and lower crust) in a 0.5° resolution grid. We took the total crustal thickness as the sum ofsediment layer, upper crust, and lower crust (Figure 3b).4.2.3. Thickness of Lithospheric MantleThe thickness of the lithospheric mantle was inferred seismically, following the approach described by Birdet al. [2008]. S wave traveltime anomalies above 400 km were calculated from the most recent S wave tomo-graphy model (S40RTS) [Ritsema et al., 2011] and corrected for the crustal thickness [see Carafa et al., 2015a,Figure 4]. Then, assuming that Swave traveltime anomalies are proportional to the lithospheric mantle thick-ness (i.e., anomalies are neglected for sublithospheric depths up to 400 km), the latter was calculated using aregression law calibrated in the oceanic lithosphere (see Bird et al. [2008] for details).

The total lithospheric thickness, represented in Figure 3c, was calculated as the sum of the crustal and litho-spheric mantle thicknesses for all oceanic and continental nodes.4.2.4. Geotherm Quadratic CorrectionInput heat flow and lithospheric thickness values can eventually be incompatible, leading to implausible hightemperatures at the lithosphere-asthenosphere interface. To better approximate the temperature, OrbData5calculates and stores a nodal value that represents a perturbation to the geotherm associated with transientcooling [Bird et al., 2008]. This perturbation is zero at the top and bottom of the lithosphere and maximum at

Figure 2. Finite element grid used for neotectonic finite element model. Continuum elements as black-sided triangles (typical size is about 27 km) and curvilinearfault elements as red traces. Tick marks indicate the assigned dip: filled triangle: 19° (seismogenic portion of subduction zone); open triangle: 30° (thrust faults); box:45°; straight: 55°; none: 90°. The grid is over the ETOPO1 elevation model used in this work [Amante and Eakins, 2009].



middle depth, varying in a quadratic way. The midlithosphere thermal anomaly originated by this correction isrepresented in supporting information Figure S4b. While preventing too high temperatures at the base of thelithosphere, this correction can eventually generate temperatures that are too high within the lithosphere,making it hotter than the asthenosphere. To prevent this, OrbData5 lowers the surface heat flow so that themaximum temperature within the lithosphere equals 1673K (1400°C; upper temperature limit for

Figure 3. Input lithospheric data. (a) Heat flow obtained from spline smooth interpolation of International Heat FlowCommission data, after assigning a value of 0.054Wm�2 to regions for which data are absent. (b) Crustal thickness fromEPcrust model [Molinari and Morelli, 2011]. (c) Total lithospheric thickness, calculated as the sum of crustal thickness andseismically inferred lithospheric mantle thickness.



lithosphere-asthenosphere boundary). Then, as described and used by Bird et al. [2008] OrbData5 assumes thepoint at which this temperature is achieved as the base of the lithosphere, thus lowering its thickness and pri-vileging a thermal definition for the base of the lithosphere (1673 K). In this work, similarly to Carafa et al.[2015a], we only allowed for the heat flow correction and disregarded the rescaling of the lithosphere thickness,thus keeping a seismic definition of the lithosphere thickness. The resulting heat flow is shown in Figure 3a.4.2.5. Density Anomaly of Lithological OriginThe versions of SHELLS and OrbData5 here used (released 29 August 2006) [Bird et al., 2008] guarantee localisostasy by calculating for each node of the grid the vertically averaged density anomaly of the whole litho-sphere and restricting its value to the ±50 kgm�3 range (represented in supporting information Figure S4a).This nodal parameter represents a laterally varying density anomaly of lithological origin.

4.3. Definition of Plate Boundaries

As SHELLS requires each node to belong to a single plate, a plate model must be input. We redefined the plateboundary along the study region, based on recent bathymetry to more accurately follow the Gloria fault’strace, on seismic profiles in the Eastern Atlantic, on state-of-the-art knowledge of the Gulf of Cadiz tectonics[e.g., Duarte et al., 2013b], and in recent works that propose the existence of an incipient subduction devel-oping at the north Algerian margin [Déverchère et al., 2005; Billi et al., 2011]. The resulting trace is representedin Figure 1a and provided in Data Set S3.

It is now widely recognized that the plate boundary east of the Gloria fault cannot be assigned to a single faultor fault system. Recent marine surveys [Zitellini et al., 2009] greatly improved the bathymetric maps in the SWIberia margins and allowed identifying several structures that were likely to accommodate the plate movement[Terrinha et al., 2009;Duarte et al., 2011]. Nonetheless, as a linear trace was required, we chose to define the plateboundary mostly as a straight line passing through the SWIM1 fault and the southern Rif region, i.e., near thesouthern limit of the distributed deformation. We note that the previous PB2002 boundary by Bird [2003]was marked by several zigzag segments, reflecting topographic lineaments and epicenter alignments.

The Alboran (AL) plate geometry (Figure 1a), used only for the 3plates experiments (see section 5.1), reflectsthe region within which the GPS velocities look incompatible with Africa or Iberia (see section 7.1) and islimited on the east by the Trans-Alboran shear zone.

5. Geodynamic Scenarios and Boundary Conditions

We tested different geodynamic scenarios, each corresponding to a different setting of (side, internal, andbasal) boundary conditions (see section 3.2). Four scenarios are presented, resulting from the combinationof two different plate configuration models with two distinct angular velocity models.

5.1. Plate Models: 2plates Versus 3plates

We modeled the presence versus the absence of an independently driven plate in the Alboran domain bytesting two alternative plate models: 2plates scenarios—with only Africa (AF) and Eurasia (EU) plates, and3plates scenarios—with an independent Alboran (AL) plate between EU and AF plates in the Gibraltar-Alboran domain (Figure 1a).

The introduction of the AL plate intends to test whether imposing additional forces below the Alborandomain might lead the model to better results. We aim to discuss the force balance on AL plate, in particularthe role of basal tractions; however, note that it is not possible through SHELLS to distinguish among distinctbasal driving mechanisms or directly determine their origin (see section 3.2).

5.2. Boundary Conditions in AF and EU Plates

Boundary conditions in nodes belonging to AF and EU plates are the same in all experiments, for both 2platesand 3plates scenarios. The two types of boundary conditions applied (velocity-fixed conditions in the edgesnodes, and basal tractions) are described next.5.2.1. Side Boundary Conditions: SEGAL2013 Versus MORVELThe boundaries of themodel were chosen to lie within the relatively rigid lithosphere, so that fixed velocity con-ditions based on rigid plate motion models could be applied to nodes along the model boundary (side bound-ary conditions). EU plate was arbitrarily chosen as the fixed reference frame; therefore, edge nodes belonging to



EU were assigned a fixed null velocity. Edge nodes lying in AF plate were assigned fixed velocities calculatedfrom the angular velocity model governing the Africa-Eurasia relative movement (poleBC).\ We tested two dis-tinct poleBC conditions that represent different timescales over which the plate motions are averaged:

1. MORVEL [DeMets et al., 2011] is the most recent and complete global plate motion model based on geo-logical and geophysical data, where the long-term angular velocity of the plates are averaged over the last3Myr. In this model, the angular velocity of Africa (Nubia, NU) with respect to Eurasia (EU) is calculatedfrom the plate circuit NU-NA-EU (NA: North America). MORVEL uses the seafloor spreading rates deter-mined in mid-ocean ridges of the Central Atlantic and North Atlantic for the two plate pairs NU-NA andNA-EU (both averaged over the past 3.16Ma) and also transform fault azimuths on the three plate bound-ary pairs. The resulting “geological-scale” poleBC considered for this work is listed as MORVEL in Table 1.

2. SEGAL2013 [Fernandes et al., 2003, 2013] is a kinematic model based solely on the integration of space-geodetic observations, namely, GPS observations from permanent stations, which permit to estimatethe present-day secular velocity with subcentimeter accuracy. We estimated the Africa-Eurasia relativemotion by differentiating the angular velocity calculated for the EU absolute velocity (abs EU) byFernandes et al. [2003] and the NU absolute velocity (abs NU) by Fernandes et al. [2013]. The respective“geodetic-scale” poleBC (= abs NU� abs EU) is listed in Table 1 as SEGAL2013.

In this work, the use ofMORVEL versus SEGAL2013 to define velocity boundary conditions represents a test onwhether the ongoing deformation and resulting seismicity predominantly reflect the geological long-termplate motion or are mostly determined by the present-day kinematics, respectively.5.2.2. Basal Conditions in AF and EUA major concern during this work was to obtain a model that reflects as closely as possible the natural pro-totype, i.e., a model that, accepting SHELLS assumptions and simplifications and inputting the most updatedlithospheric information, most correctly reproduces the observed geodetic, stress, and seismic data. Wefound that considerable improvement of results could be achieved by applying shear tractions under AFand EU plates (see section 3.2). In fact, this was showed to be a powerful computational way to accuratelytransmit the intraplate deformation imposed by the plate convergence, by distributing the strain throughthe whole plates instead of concentrating it around the edges where side velocity conditions are imposed.We conducted several test experiments aiming at computationally finding the set of basal conditions thatwould better achieve this goal. From these tests it was possible to conclude the following:

1. Maximum limits should be imposed to the traction magnitudes, in a similar way as Bird et al. [2008]imposed a THRMAX limit to avoid implausible high tractions under their small plates.

2. Distinct limits should apply for each plate, instead of a single value applied globally. To implement this, wehavemodified the SHELLS code to allow it to accept distinct maximum basal traction values for each of theplates, by introducing new input parameters: trmxAL, trmxAF, and trmxEU—maximum shear tractionsallowed under AL, AF, and EU plates, respectively.

3. Determination of the best traction values is mostly independent of other varying parameters, such asFFRIC or poleBC.

4. Optimized values are trmxAF= 12MPa and trmxEU= 4MPa.

These optimized basal conditions—combined with the side boundary conditions on model edges—can beseen as the best way to reproduce the driving effect of the unmodeled parts of AF and EU plates on the mod-eled region. We note that imposing a limit to the basal traction affects the force balance on the plate.Moreover, as AF and EU are only partially included in the model area, torques cannot be correctly determinedfor these plates, and plate equilibrium is not guaranteed; therefore, we will not discuss their force balance.

5.3. Boundary Conditions in AL Plate

Boundary conditions for the AL plate only apply to the 3plates scenarios. They consist of imposed surfacevelocities and basal tractions that allow AL to be driven independently.

Table 1. Euler Rotation Poles Used in This Work to Define the Angular Velocity of AF With Respect to the EU Fixed Reference Frame

poleBC (AF-EU) Longitude (°E) Latitude (°N) ω (deg/Ma) Reference

SEGAL2013 �24.651 �2.443 0.0735 Fernandes et al. [2003] (abs EU); Fernandes et al. [2013] (abs NU)MORVEL �20.40 21.63 0.131 [DeMets et al., 2011]



5.3.1. Surface Velocity Imposed in AL Internal NodesWe constrain and test different solutions for AL kinematics by imposing surface velocity conditions to somenodes in the interior of the AL plate. To accomplish this, we introduced a new parameter in the code, vbcAL,which assigns a velocity magnitude to some AL nodes during steps 1 and 2 of the iterative process describedin section 3.2. Specifically, vbcALmagnitude is imposed on two nodes in the Rif, and the imposed velocity vec-tor is west directed. The two chosen nodes coincide with stations where observed GPS velocities are westdirected. Note that vbcAL is regarded as a model parameter; the changes in the velocity field within AL willresult from the imposed vbcAL conditions in these two nodes and also from the inferred basal shear tractionsapplied to the whole plate. The range of variation of this parameter corresponds to values proposed in theliterature for the residual velocity of an independent domain in the Alboran Sea region with respect to theEU and AF plates [Koulali et al., 2011; Gutscher et al., 2012; Palano et al., 2015].5.3.2. Basal Conditions in ALThe independent motion of the AL plate was mainly achieved by allowing it to be driven by basal shear trac-tions (see section 3.2). As AL plate lies within the modeled area, we did not impose any limit to its basal trac-tion magnitude (in practice, trmxAL was set to a value sufficiently high to not be reached during theexperiments), so that the force equilibrium is not affected. This way, the balance of lithostatic versus basalversus side strength forces can be discussed for the AL plate.

6. Parameter Space Investigated for Each Geodynamic Scenario

For each scenario of [plate model + poleBC] we investigated the variation of the parameters FFRIC, vbcAL, andTAUMAX. Table 2 summarizes the tested geodynamic scenarios and the respective ranges of variation of eachparameter within the parameter space. The final run comprised a total of 5240 experiments.

7. Scoring Data Sets

Each model was evaluated by comparing its predictions with three data sets of observed data: geodetic hor-izontal velocities, most compressive stress directions, and seismic strain. These comparisons were performedusing the code OrbScore2 (http://peterbird.name/oldFTP/neotec/SHELLS/OrbScore/). Input scoring data setsand the corresponding calculations are described below.

7.1. Geodetic Velocities

The first misfit compares the predicted horizontal velocities with geodetic velocities derived from GPS obser-vations. The geodetic velocities were calculated at SEGAL (Space & Earth Geodetic Analysis Laboratory; http://segal.ubi.pt/) for 232 permanent stations in Portugal (including Madeira Islands), Spain, and Morocco and 18episodic (campaign) stations in Morocco (Figure 4). The snx files with the geodetic velocities are provided asData Set S4 and the gps file necessary to run SHELLS as Data Set S5.

The positional time series were obtained by computing daily solutions using the GIPSY-OASIS v6.3 [Webb andZumberge, 1995] software package. Each station is processed independently using the PPP—Precise PointPositioning strategy [Zumberge et al., 1997] but fixing the ambiguities using corrections obtained from a fixedglobal network. The daily solutions are mapped into ITRF2008 [Altamimi et al., 2011] by applying a Helmerttransformation computed using IGS (International GNSS Service) stations globally distributed. Finally, forthe permanent stations, the HECTOR software [Bos et al., 2012] was used to estimate the motion of the sta-tions (together with jumps and periodical—annual and semiannual—signals). HECTOR uses a power law+white noise model to take into account the existing noise signals in the trend. Such approach permits tocompute more realistic uncertainties for the velocities. For the episodic stations, a different strategy is usedto compute the motion since it is not possible to estimate the seasonal signals using few observations distrib-uted over several years. First, a single combined solution is computed for each campaign by averaging theexisting daily solutions. This approach permits to detect (and remove) eventual outliers. After, and usingGIPSY and developed SEGAL tools, a best linear fitting through the campaign solutions is applied to estimatethe motion. The minimum acquisition period for each station was 3.5 years (with a minimum of three occu-pations for episodic stations), and residuals were calculated with respect to a fixed EU reference frame.



http://peterbird.name/oldFTP/neotec/SHELLS/OrbScore/

http://segal.ubi.pt/


Individual differences between modeled and geodetic velocities were calculated and inverse weighted bythe datum standard deviation. No area weighting was applied. The square root of the mean weighted squaredifference is assumed as the geodetic misfit, gps (in units of mm/yr).

7.2. Most Compressive Stress Directions

A second misfit test evaluates the accuracy of predicted stress orientations. We built an initial data set of themost compressive principal stress directions (SHmax) by gathering (1) focal mechanisms compiled from sev-eral sources by Custódio et al. [2016]. These were used to compute SHmax and a quality rank was ascribed,following the guidelines provided in Zoback [1992] for the World Stress Map Project; and (2) all other typesof stress indicators available in the World Stress Map database [Heidbach et al., 2008], with the exceptionof focal mechanisms (including well bore breakout orientation, hydraulic fracturing, and geological fault slipdata). This data set is represented in Figure 5a and provided in Data Set S6.

Figure 4. Input scoring data set: GPS residual velocities with respect to the Eurasia tectonic plate, calculated using velocities estimated at SEGAL (http://segal.ubi.pt/)for 232 permanent stations and 18 episodic stations. Provided as Data Sets S4 and S5. For each experiment two independent scoring evaluations were performed:considering the whole modeled region (ALL) and considering only elements inside the RoI box (see section 7.5).

Table 2. Parameter Space Investigated in This Work, for Each Geodynamic Settinga

Plate Configuration poleBC Parameter Minimum Maximum Step Number of Experiments

2plates SEGAL2013 FFRIC 0.025 0.500 0.025 20MORVEL FFRIC 0.025 0.500 0.025 20

3plates SEGAL2013 FFRIC 0.025 0.500 0.025vbcAL 0.0 6.0 0.5

TAUMAX 1.0 10.0 1.0 2600

MORVEL FFRIC 0.025 0.500 0.025vbcAL 0.0 6.0 0.5

TAUMAX 1.0 10.0 1.0 2600

apoleBC: Africa-Eurasia Euler rotation pole used to define side boundary conditions in AF edge nodes; FFRIC: fault fric-tion coefficient; TAUMAX: maximum vertical integral of traction in the subduction zone; vbcAL: magnitude of the westdirected surface velocities imposed in internal AL nodes.




In order to increase the regional significance of stress orientations—compensating for irregular sampling andinadequate description of the uncertainties—we used the SHINE interpolation algorithm for clustered datadesigned by Carafa and Barba [2013] and Carafa et al. [2015b] and available online at http://shine.rm.ingv.it/index.phtml, to interpolate the data to a 0.5° spacing grid. For each grid point, we imposed a minimumof three clusters, a maximum searching distance of 96 km, and a maximum 90% confidence limit (“conf”)of 45°. We rated each interpolated datum according to: A if conf< 20°; B if conf< 25°; C if conf< 40°; andD if conf< 45°. The interpolated data set is provided as Only interpolated data ranked as A and B were usedfor scoring. This final scoring data set is shown in Figure 5b.

For each experiment, modeled principal axes of permanent strain rate were compared to A and B qualityinterpolated stress directions. The quality-weighted mean value of their difference was taken as the SHmaxmisfit (in units of degrees).

7.3. Seismic Catalog and Strain Rates

The third misfit evaluates the similarity between the predicted strain rates and the strain rate from theearthquake catalog.

The studied region is mainly a slowly deforming region, with the seismic cycle for large earthquakes beingmuch longer than the instrumental observation period. For this reason we limited our earthquake catalogto the instrumental period (after 1900). Events were downloaded from the European-MediterraneanEarthquake Catalogue (EMEC) [Grünthal and Wahlström, 2012] for the period 1900–2006 and from theInternational Seismic Centre (ISC) catalog for the period 2006–2012. EMEC data have originally an assignedmoment magnitude (Mw), calculated based on local relations or regressions developed by Grünthal et al.[2009] and Grünthal and Wahlström [2012]. ISC data are reported in several different magnitude types andwere all converted to moment magnitudeMw following Shapira [2007]. We limited the catalog to events withmagnitudes (Mw) larger than 3.0 (to account for asymmetries in measurement of small earthquakes beforeand after main developments in network quality during the twentieth century) and smaller than 6.0 (to avoidthe extreme localization of seismic strain around epicenters of the rare very large events) [see Cunha et al.,2012, section 4.1 and Figure 6]. The resulting catalog is represented in Figure 6 with scaled dots.

For each ith node of the grid, this catalog was translated into scalar seismic strain rate ( _εcat ), through aGaussian smoothing function [Jimenez-Munt et al., 2001a]:

_εcat ið Þ ¼ 12π μLsσ2Δt

XNn¼1

M0 nð Þexp � ri;n2

σ2

� �

where N is the total number of earthquakes in the catalog; μ is the shear modulus; Ls is the average thicknessof the seismogenic layer; M0(n) is the seismic moment of the nth earthquake; ri,n is the distance from the ithnode to the nth earthquake; and Δt is the time length of the earthquake catalog. The parameter σ, the widthof the Gaussian function, was set to 20 km. The calculated seismic strain rate is shown as a color map inFigure 6.

To calculate the model strain rate ( _εmod), we first averaged the velocities of all nodes that share a commonlocation, thus forcing the velocity field to be continuous and eliminating infinite strain rates in fault elements.Then we computed the horizontal strain rates within each element ( _ε1h; _ε2h; with _ε1h≤ _ε2h). Because all per-manent strain mechanisms conserve volume (to a first approximation, neglecting any changes in porosity), _ε1þ_ε2 þ _ε3 � 0 and the vertical strain rate _εrr (which is equal to one of _ε1, _ε2, and _ε3) can be determined from thetwo horizontal strain rates: _ε1h þ _ε2h þ _εrr ¼ 0. Given that _ε1 < 0 < _ε3, only the sign of _ε2 can vary. Therefore,the model maximum absolute value of strain rate of the ith element is

_εmod ið Þ ¼max 2 _ε2hj j; 2 ε̇ rrj j; ε̇2h � ε̇ rrj jð Þmax 2 _ε1hj j; 2 ε̇ rrj j; ε̇1h � ε̇ rrj jð Þmax 2 _ε1hj j; 2 ε̇ rrj j; ε̇2h � ε̇1hj jð Þ

for _ε2h _εrr > 0

for _ε1h _εrr > 0

otherwise

8>><>>:

9>>=>>;

For both catalog andmodel scalar strain rate, we performed a smoothing cycle by assigning to each node thestrain rate average of the connected elements and then interpolating from nodes to element centers. Werepeated this smoothing cycle three times.



http://shine.rm.ingv.it/index.phtml

http://shine.rm.ingv.it/index.phtml

Finally, the performance of each model was evaluated by a measure of the normalized strain rate correlationcoefficient between the logarithm of the catalog seismic strain rate and the logarithm of the model maximumabsolute strain rate, calculated as

seismi ¼ 1�X

iA ið Þ log _εmod ið Þ � log _εmod

� �� log _εcat ið Þ � log _εcat� ��

XiA ið Þ log _εmod ið Þ � log _εmod

� �2 �XiA ið Þ log _εcat ið Þ � log _εcat

� �2h i1=2

Where A(i) is the area of the ith element; and the overbar designates the average of the function over themodel region. seismi is assumed as the third scoring misfit (dimensionless).

Figure 5. Input scoring data set: (a) Stress direction data gathered from a compilation of focal mechanisms and from WSM(World Stress Map) data (provided as Data Set S6). (b) Interpolation of the previous data using the SHINE interpolationalgorithm [Carafa et al., 2015b]. Only A and B quality data (ranked after interpolation) are shown and were used for scoring.See section 7.2 for details.



7.4. Combined Misfit

For each experiment a combinedmisfit was calculated, defined as the geometric mean of the three individual

misfits: m ¼ gps� SHmax �1-seismið Þ1=3 . This value is independent of the units in which each misfit isexpressed.

To ensure that the choice of the best model was independent of the definition of the combined misfit, wealso performed an alternative scoring: we normalized gps and SHmaxmisfits to the [0, 1] range, turning themadimensional (seismi already satisfies these conditions), and for each experiment a combined misfit was cal-culated as the arithmetic mean of the three normalized misfits. We verified that results considering either thegeometric mean or the arithmetic mean of misfits were equivalent in model ranking, ensuring the scoringrobustness. For simplicity only the geometric mean will be here considered.

7.5. Scored Areas and Misfit Significance

Some characteristics and differences among the described scoring data sets are noteworthy beforefurther analysis of scoring results. The calculation of gps and SHmax misfits use only punctual datawell distant from the model edges (Figures 4 and 5), while the seismi misfit coefficient is calculated forall grid elements (Figure 6). As a consequence, when calculating scoring misfits for the whole modeledarea, the seismi misfit is considerably sensible to boundary effects in the model edges, while gps andSHmax are not.

To avoid biases caused by boundary effects and guarantee that the chosen preferred model is accurate in thewhole modeled region, we performed for each experiment two independent calculations of the scoring mis-fits: (1) ALL: evaluation of misfits considering all elements of the modeled region and (2) RoI: evaluation ofmisfits considering only the elements of the grid belonging to the region of main interest of the model.See Figures 4–6 for location of the RoI.

Figure 6. Input scoring data set: Seismic strain rates calculated using EMEC (1900–2006) and ISC (2007–2012) earthquake catalogs withMw ranging between 3.0 and6.0 (epicenters represented as dots). See section 7.3 for details on data set choice and calculations. Color indicates the common logarithm of the magnitude of theseismic scalar strain rate (in units of s�1). See text for details.



Therefore, besides avoiding boundary effects, this duplication of misfit calculations is also a means to study indetail the accuracy of the model in the Gulf of Cadiz-Alboran region.

8. Scoring Results

In this section we present and analyze the scoring results of our experiments. We start by showing the varia-tion of scoring misfits within the studied parameter spaces, for each geodynamic setting. For each setting wepick the best model as being the experiment having the lowest combined misfit value, i.e., that betterreproduces simultaneously the three sets of scoring data. We then compare the final set of four best modelsto choose the preferred model.

8.1. The 2plates Scenarios

In 2plates scenarios, FFRIC is the only varying parameter. Scoring misfits (gps, SHmax, seismi, and m) arerepresented in Figure 7 for each used poleBC and for scoring in ALL and in RoI.

One important observation is that scoring in ALL and scoring in RoI lead to very similar trends of variation ofall misfits and using both poleBC. This indicates that the location of the preferred model within the parameterspace is independent of the scored region.

8.2. The 3plates Scenarios

For the 3plates scenarios there are three varying parameters: FFRIC, vbcAL, and TAUMAX; thus, the analysis isnot straightforward. We start by plotting the variation of scoring misfits in a 3-D parameter space, as shown inFigure 8 (for scoring in RoI) and in supporting information Figure S1 (for scoring in ALL). In these plots, eachscattered point corresponds to one experiment, and both its color and size are scaled to the respective misfitvalue. It is immediately noticed that the variation with TAUMAX is negligible when compared to the variationwith FFRIC and vbcAL; thus, we next represent the variation of the misfits in 2-D contour plots in the [FFRIC,vbcAL] space, for a fixed TAUMAX value that corresponds in each case to the TAUMAX of the best model(see respective caption and Table 3). These 2-D plots are shown in Figure 9 (for scoring in RoI) and in

Figure 7. Scoring results: misfits for the 2plates scenario. The investigated parameter space corresponds only to FFRICvariation. For each of the two settings (using SEGAL2013 and MORVEL as poleBC) are shown scoring results evaluated inALL and in the RoI.



Figure 8. Scoring results: misfits evaluated in the RoI for the 3plates scenario with poleBC being (a) SEGAL2013 and (b)MORVEL. The whole 3-D investigated parameter space [FFRIC, vbcAL, TAUMAX] is represented. Each scatter point corre-sponds to one experiment, and its color and size are scaled to the respective misfit value.



supporting information Figure S2 (for scoring in ALL). The location of the preferred model (the one having thelowest combined misfit) is shown as a star in each misfit space.

8.3. Selection of the Preferred Model and Preferred Scenario

Results for each of the four best models (respective to each of the four geodynamic settings) are compared inFigure 10. Scoring values are listed in Table 3, together with the modeling parameters of the respectivebest experiment.

For both ALL and RoI scoring calculations, the best model performances were achieved with the 3plates-SEGAL2013 setting, pointing it out as the preferred geodynamic scenario. However, best scoring for ALLand RoI locate in a slightly different position in the parameter space (FFRIC is 0.200 for ALL best model and0.225 for RoI best model; see Table 3 and compare Figure 9 with supporting information Figure S2).Despite this, we decided to choose the preferred model based on the RoI scoring, because it is free of even-tual biases due to boundary effects at the model edges (see section 7.5) and because it includes the area ofmost interest in terms of plate boundary dynamics and associated strain rates: SW Iberia, Gulf of Cadiz,Alboran domain, and north Algeria.

Accordingly, the elected preferred model corresponds to the experiment with 3plates configuration,SEGAL2013 pole, FFRIC=0.225, vbcAL=3.5mm/yr, and TAUMAX= 5.0 × 1012 Nm�1.

9. Discussion9.1. Scoring Results

We here discuss the significance of the variation of misfits within the various studied parameter spaces andthe robustness of the choice of the preferred model and preferred scenario.9.1.1. SEGAL2013 Versus MORVELA first result of this work is that the SEGAL2013 angular velocity model outperforms MORVEL for both 2platesand 3plates scenarios, leading to an improvement of ~10% in terms of combined misfit (see Table 3).Comparing the performance of both poleBC in Figure 7, for 2plates, and Figure 9, for 3plates, one verifies thatthis result is true for all misfit evaluation but strikingly evident for the SHmax scoring: SEGAL2013 leads tomisfits below 14° for most of the parameter space, while with MORVEL misfits are rarely under 16°.

We recall that using SEGAL2013 or MORVEL poles implies considering different geodynamic timescales.MORVEL pole was calculated from 3.16Myr average seafloor spreading rates [DeMets et al., 2011] and thusis not able to resolve changes in plate velocity or Euler pole location during this period of time. However,Calais et al. [2003] showed, from comparison of GPS and seafloor spreading data, that both Nubia-NorthAmerica and North America-Eurasia motion have changed significantly since 3Ma; it is thus likely thatMORVEL is, in fact, the average of different stages of relative Nubia-Eurasia plate motion. In contrast, theSEGAL2013 pole is calculated from geodetic data obtained using several stations located both in stable

Table 3. Comparison of Scoring Results of the Best Models Found for Each of the Four Geodynamic Settings (See Also Figure 10)a

Setting (This Work) Scored Region

Best Model Parameters Best Model Scoring

FFRIC vbcAL (mm/yr) TAUMAX (×1012 Nm�1) gps (mm/yr) SHmax (deg) seismi m

2plates-SEGAL2013 RoI 0.250 0.0 0.0 0.983 12.39 0.3565 1.63143plates-SEGAL2013 RoI 0.225 3.5 5.0 0.911 12.22 0.3180 1.52412plates-MORVEL RoI 0.200 0.0 0.0 1.109 15.10 0.3555 1.81243plates-MORVEL RoI 0.225 4.0 1.0 0.904 16.93 0.3170 1.6929

2plates-SEGAL2013 ALL 0.225 0.0 0.0 0.832 13.40 0.3755 1.61173plates-SEGAL2013 ALL 0.200 3.5 4.0 0.790 13.51 0.3776 1.59142plates-MORVEL ALL 0.200 0.0 0.0 0.912 15.46 0.3733 1.73953plates-MORVEL ALL 0.200 3.5 1.0 0.825 16.19 0.3745 1.7102

aEach experiment was scored for the whole model region (ALL) and also a restricted region of interest (RoI), and selection of the best model for each geody-namic setting was made independently for each scoring case. The selection of the preferred model (for the whole experiment) was made considering the com-bined m misfit for RoI scoring.



Figure 9. Scoring results: misfits evaluated in the RoI for the 3plates scenario with poleBC being (a) SEGAL2013 and (b)MORVEL. Here only the 2-D parameter space [FFRIC, vbcAL] is represented respective to a slice on the previous 3-Drepresentation (Figure 8) along a horizontal plane with constant TAUMAX corresponding to the best model value(5.0 × 1012 Nm�1; see Table 3). Misfit data are represented as contour plots. The yellow star indicates the respective bestmodel (see Table 3), selected as minimum combined misfit. To allow a direct comparison between SEGAL2013 andMORVELresults, the respective misfits are represented in the same scale in Figures 9a and 9b.



Nubia and Eurasia [Fernandes et al., 2003, 2013] and thus reflects the present-day relative Africa-Eurasiamotion. For comparison of the velocity fields implied by SEGAL2013 andMORVEL see supporting informationFigure S3.

The present work shows that not only the velocity field but also the stress field and the strain are controlledby the present-day kinematics rather than by the geological-time-scaled plate velocities (Figures 7, 9, and 10and supporting information Figure S2). Thus, geodetically deduced angular velocities are preferred for asses-sing active tectonics, in line with Cunha et al. [2012], who reached a similar conclusion by comparing resultsusing DEOS2K (geodetic) and NUVEL-1A (geologic) poles.9.1.2. The 2plates Versus 3plates and Parameter SpaceFigure 10 shows that the 3plates configuration is preferred to the 2plates configuration for all scoring data setsand for both tested poleBC, SEGAL2013, and MORVEL. To strengthen this conclusion, we show in Figure 11 therepresentation of scoring misfits for a comparable set of 2plates and 3plates models, where FFRIC is the onlyvarying parameter: for 3plates, vbcAL and TAUMAX are constant (based on previous conclusions, we restrict thisanalysis to SEGAL2013 angular velocity model and to scoring in RoI). The preferred (3plates) model represents animprovement of 6.5% in the combined misfit m, with respect to the best 2plates model.

The gps scoring clearly favors the 3plates setting, for all modeled scenarios and for both RoI and ALL (Table 3and Figures 10 and 11). The main difference between 2plates and 3plates models is the velocity pattern andmagnitude in the Alboran domain: the best 3platesmodel predicts for the Alboran domain velocities varyingfrom west directed 3.5mm/yr at the Rif (where initial velocity conditions were imposed) down to WSWdirected ~3.0m/yr at the Betics. For the best 2plates model, the modeled velocities are WNW directed anddo not exceed 2.0mm/yr in the AL region (see supporting information Figure S3). The fact that misfits arehigher when considering RoI than when considering ALL highlights the difficulty in modeling velocities inthe Alboran region, where sometimes there is a sharp variation in magnitude and direction betweenclosed stations.

Figure 10. Decision on preferred model: summary of scoring misfits for the four best models found for each geodynamicscenario, for both evaluations in ALL and RoI. Note that only one model (the one with the lowest combined misfit) isrepresented for each scenario. See Table 3 for information about corresponding parameters.



The seismi scoring is the one that most favors high vbcAL values in the parameter space and thus an indepen-dent and faster motion of AL relative to AF and EU (Figures 8 and 9). Moreover, if the decision of 2plates versus3plates configuration in terms of seismi scoring is not conclusive for the ALL evaluation (likely due to sensibil-ity to boundary effects; see section 7.5), it is clear that the 3plates setting is preferred when the evaluation isrestricted to RoI (Figure 10). This supports that 3plates is the setting that most correctly models the seismicstrain in the AL domain and surrounding zones. Moreover, the preferred model is the most accurate indescribing fault slip rates, as confirmed by the fact that seismi is the most sensitive misfit to FFRIC variationsand thus also to variations in fault slip rates (Figure 9) [Bird et al., 2008; Carafa et al., 2015a].

The SHmaxmisfit is the less sensitive to the plate configuration (Figures 10 and 11); instead, it turns out to bemuch more determined by the boundary conditions (poleBC), FFRIC, and vbcAL. In particular, Figures 8 and 9show that the SHmax scoring is better when the stress field is less deflected by the presence of faults (i.e., highFFRIC and moderate vbcAL).

Table 4 and Figure 12 show that our models are surprisingly accurate in the modeling of stress directions,when compared with previous models. We partly attribute this result to the performed extensive search tofind the most realistic boundary conditions, which lead us to verify that basal tractions under AF and EUplates were in fact very effective means for approximating model predictions to natural observations.9.1.3. Implications for Fault FrictionThe FFRIC and TAUMAX values of our preferred model are higher than values found in previous numericalmodels but still well below the range of values reported in classical laboratory results from static experiments.As discussed by Carafa et al. [2015a], low values of FFRICmay have real causes, like weakening due to differ-ent phenomena in several modeled regions, or may be ascribed to modeling causes, such as insufficient oroversimplified fault database. Despite this ambiguity, the coherence with previous long-term models[Jimenez-Munt et al., 2001a; Cunha et al., 2012; Carafa et al., 2015a] leads us to suspect that low FFRIC valuesfound for the Mediterranean may have real causes, possibly related to high pore fluids at seismogenic depthswithin evaporite (and carbonate) sequences, which are typical of the Mediterranean region. In different partsof the Mediterranean the active faults are hosted by weak clay-bearing rocks, which reduce the fault resis-tance. In the Gulf of Cadiz and Alboran domains, in particular, several processes may be responsible for thereduction of the rock strengths, e.g., presence of evaporites, hydration, serpentinization of mantle rocks,and intensive fluid circulation [e.g., Hensen et al., 2015].

Figure 11. Decision on preferred plate scenario: 2platesmodels versus comparable 3platesmodels (for 3plates, vbcAL, andTAUMAX are fixed to 3.5mm/yr and 5.0 × 1012 Nm�1, respectively; see Table 3). This analysis is restricted to SEGAL2013velocity model and to scoring in RoI (see sections 8.3 and 9.1).



9.2. Preferred Model

The preferredmodel was determined as the one having the lowest combinedmisfit (m) within the whole finalrun of experiments, for scoring evaluation restricted to the RoI. It corresponds to the 3plates-SEGAL2013setting, with FFRIC= 0.225, vbcAL= 3.5mm/yr, and TAUMAX=5.0 × 1012 Nm�1.

The output results are represented in Figures 13a (long-term predictions for the horizontal velocity field), 13b(fault heave rates), 13c (nonelastic scalar strain rates), and 14a (most compressive principal stress directions).In Table 5 we list the maximum heave rates predicted for each modeled fault and the respective kinematics(thrust, normal, or strike slip). Note that the assigned fault dip does not determine the modeled fault kine-matics. The triplet of fictitious point forces exerted in AL plate is shown in Figure 14b. For comparison withFigure 13a, we show in supporting information Figure S3 the velocity fields predicted by the best modelsfound for the three alternative geodynamic scenarios.9.2.1. Quantitative Comparison With Previous Neotectonic ModelsThe two latest neotectonic models produced for the study region were Cunha et al. [2012] and Carafa et al.[2015a] (see section 3.2). To compare our preferred model with preferred models of these previous studies,we evaluated their performance using the same OrbScore2 code and the same scoring data set used here.We scored these models in regions that correspond (within some slight differences, due to distinct grid out-lines) to our total model area ALL and to our RoI (Table 4). Figure 12 plots these results for the RoI scoring. Thiscomparison reveals that our work improves the modeling of stress directions, geodetic velocities, and seismicstrain rates observed in the studied region. Therefore, results from our preferred model can be used for esti-mation of the deformation ongoing on this singular region of the Earth. In particular, fault slip rates and con-tinuum strain rates can be used for hazard studies, and the modeled velocity and stress fields can be used forstudies on Africa-Iberia geodynamics.

Figure 12. Comparison of our preferredmodel scoring results versus scoring of Carafa et al. [2015a] and Cunha et al. [2012]preferred models (only for scoring in RoI).

Table 4. Scoring Evaluation of Carafa et al. [2015a] and Cunha et al. [2012] Best Modelsa

Reference Scored Region gps (mm/yr) SHmax (deg) seismi m

Carafa et al. [2015a] RoI 1.151 28.37 0.4389 2.4290Cunha et al. [2012] RoI 0.934 18.33 0.3844 1.8740This work, preferred model RoI 0.911 12.22 0.3180 1.5241

Carafa et al. [2015a] ALL 1.007 31.93 0.3697 2.2822Cunha et al. [2012] ALL 0.830 18.95 0.4105 1.8621This work, preferred model ALL 0.790 13.51 0.3776 1.5914

aFor these models, ALL and RoI are best approximations to ALL and RoI used for scoring our models. The same scoringdata sets and OrbScore2 code used in this work.



9.2.2. Completeness and Correctness of the Input Fault NetworkBefore considering the output fault slip rates, both completeness and correctness of the input fault networkneed to be addressed. It is noteworthy that the assumed fault geometries affect the results in terms of sliprates and kinematics; similarly, the lacking of a fault (i.e., the incompleteness of the fault database) perturbsthe model results, at least locally. Although this incompleteness issue affects all deformation models andactive fault databases, SHELLS proved to be much more robust in case of an incorrect description of faults,due to the similar rheological description of continuum and faults, which allows the model to recover thedeformation of a potentially missing fault somewhere in the nearby continuum (see, e.g., Puysegur trenchdeforming zone in Liu and Bird [2002], Himalaya in Bird et al. [2008], and Southern Alps in Kastelic andCarafa [2012]). On the other hand, in other different modeling approaches (like rigid block modeling; e.g.,McCaffrey [2002]), the choice of modeled faults becomes much more important, because the continuum isassumed as rigid and/or purely elastic; therefore, in those cases, the deformation pattern of the final modelis fully governed by the inserted faults.

Table 5. Fault Heave Rates as Predicted by the Preferred Model: Maximum Heave Rate (as Indicated in Figure 13b), Range of Heave Rate Variation Across Elementsof the Same Fault, and Respective Kinematicsa

Preferred Model

Fault Maximum Heave Rate (mm/yr) Range Modeled Kinematics SHARE

Southwest Iberia Gloria 3.2 2.0–3.2 dextral ---Horseshoe 1.0 0.7–1.0 thrust 0.35–0.37SWIM1 0.82 0.6–0.82 dextral 0.2–1.5Gorringe 0.77 0.6–0.77 thrust 0.5–2.5

São Vicente 0.77 0.4–0.77 thrust ---Cadiz 0.46 0.3–0.46 thrust ---SWIM2 0.43 0.24–0.43 dextral 0.2–1.5

Coral Patch Ridge 0.34 0.2–0.34 thrust 0.5–2.5Portimão Bank 0.24 0.12–0.24 dextral 0.5–2.5

Marquês de Pombal 0.18 0.12–0.18 thrust 0.5–2.5SWIM3 0.12 0.10–0.12 dextral / thrust ---

Tagus Abissal Plain 0.10 0.05–0.1 thrust ---Pereira de Sousa 0.07 0.07 thrust ---Portimão Fault 0.06 0.06 sinistral 0.0001–0.1

Estremadura Spur 0.08 0.02–0.08 thrust / dextral ---Rif-Alboran-Betics Betics 1.9 1.0–1.9 dextral / thrust ---

Carboneras 1.7 1.3–1.7 sinistral 1.1–1.5Rif 0.9 0.5–0.9 thrust 0.9–1.9

Nekor 0.73 0.5–0.73 sinistral 0.5–1Alboran Ridge 0.55 0.34–0.55 thrust 0.02–0.9

Yussuf 0.49 0.26–0.49 dextral 0.5–1Crevillente/Bajo Segura 0.40 0.15–0.4 thrust 0.01–0.35

Jumilla 0.21 0.1–0.21 thrust 0.01–0.2Al Hoceima 0.14 0.07–0.14 sinistral 0.5–1Las Moreras 0.08 0.04–0.08 thrust 0.01–0.4Tofiño Bank 0.06 0.06 thrust ---

Portugal Lower Tagus Valley 0.07 0.03–0.07 thrust 0.01–0.3Régua-Verin 0.06 0.03–0.06 sinistral 0.05–0.5

Ponsul 0.06 0.03–0.06 thrust 0.01–0.04Vilariça-Bragança 0.05 0.03–0.05 sinistral 0.05–0.4

Seia-Lousã 0.02 0.02 thrust 0.07–0.21North Africa Tell Front 3.2 1.4–3.8 thrust 0.26–1.87

North Algeria offshore thrust 2.5 1.5–2.5 thrust 0.9–1.7El Asnam 1.4 1.0–1.4 thrust 0.26–1.87Djurdjura 1.1 0.8–1.1 thrust 0.26–1.87

Saharan Atlas west 0.80 0.4–0.8 thrust 0.1–1High Atlas 0.76 0.6–0.76 thrust 0.1–1

North Algeria onshore 0.25 0.2–0.25 dextral 0.5–1Saharan Atlas east 0.12 0.03–0.12 thrust 0.1–1

aFor comparison are listed the slip rates estimated by SHARE project (http://diss.rm.ingv.it/share-edsf/SHARE_WP3.2_Database.html). For the location of faultssee Figure 1.



http://diss.rm.ingv.it/share-edsf/SHARE_WP3.2_Database.html

Figure 13. Preferred model. (a) Long-term horizontal velocity field. (b) predicted long-term fault heave rates (see Table 5).(c) scalar strain rates. Per construction, these are predicted long-term permanent strain rates (nonelastic), equivalent to thenonrotational portions of the velocity gradients. Symbols indicate the predicted type and orientation of conjugatemicrofaults, with area proportional to strain rates.



9.2.3. Predicted Long-Term Deformation and Fault ActivityEarth Scientists cannot rely on geological analogues to infer the geodynamics of the Gulf of Cadiz and its con-sequences for earthquake and tsunami hazard assessment. In fact, nowhere in the globe is found such a largeand structurally complex convergent domain, with spread distribution of the deformation [e.g., Sartori et al.,1994; Terrinha et al., 2009]; coexistence of oceanic, transitional, and thinned continental-type lithosphere[Sallares et al., 2011]; and earthquake ruptures down to a depth of 60 km in regions where there is no linkto a subduction plane [Monna et al., 2015]. An important contribution of our work is the estimation oflong-term (and permanent) strain rates for continuum elements and slip rates for the modeled faults.

Figure 14. Preferred model. (a) predicted stress azimuths (SHmax), assumed to be parallel to the most compressivehorizontal strain rates. (b) triplet of fictitious point forces equivalent to lithostatic pressure, basal strength, and sidestrength torques acting on AL plate. In the representation described in Bird et al. [2008], the triplet should be placed at39.53°E/58.48°N, but for simplicity of representation we show it at the center of AL plate.



These results will then be useful for further hazard studies [Bird and Liu, 2007; Carafa et al., 2015a], e.g., forestimation of earthquake recurrence rates.

Figure 13b plots and Table 5 lists the predicted fault kinematics and heave rates (horizontal component ofslip rates). In Table 5 we also list for comparison the slip rates assigned in the European Database forSeismogenic Faults (SHARE project; http://diss.rm.ingv.it/share-edsf/index.html). Note that the velocitychange across faults in Figure 13 corresponds to the faults heaves rates (Figure 13b), and the velocity changein the continuum to computed strain rates (Figure 13c).

For the Gloria transform fault, the preferred model predicts heave rates between 3.2mm/yr (where the platemotion is purely transcurrent and the total convergence rate is accommodated as fault slip) and 2.0mm/yr (whereconvergence is oblique and some compressional strain rate is transferred to nearby continuum elements). To theeast of the Gloria fault, where its linear trend vanishes to give place to the diffuse boundary in the SW Iberianmargin, stresses and strain are distributed over various mapped structures and over the continuum off the faults.The highest slip rates (from 0.8 to 1.0mm/yr) are predicted for the SWIM1 strike-slip fault and for the NE-SW strik-ing Horseshoe, Gorringe, and São Vicente thrust faults, which are part of the SW Iberian margin thrust system.

In the easternmost part of the Gulf of Cadiz, strike-slip SWIM2 and the Cadiz and Coral Patch thrusts have pre-dicted heave rates around 0.4mm/yr. The Portimão Bank, acting as strike slip, and the Marquês de Pombal thrusthave predicted heave of around 0.2mm/yr. The remaining faults have predicted slips of about 0.1mm/yr or less,apparently due to their less favorable orientation (e.g., the N-S Portimão and Pereira de Sousa faults) or to theirdistance from the plate boundary zone (e.g., the Tagus Abyssal Plain fault and the Estremadura Spur thrust).

For the Alboran plate, our preferred model predicts the highest strain rates along its borders, with relativetranspression being accommodated by dextral strike slip with rates up to 1.9mm/yr in the Betics. To the west,thrust with rates up to 0.9mm/yr are modeled in the Rif. In the NE margin of the Alboran domain, the modelpredicts high strain rates and a high activity of the Carboneras fault, with left-lateral strike-slip component upto 1.7mm/yr. This result agrees with the minimum strike-slip rate of 1.3mm/yr determined by Moreno et al.[2015] to its onshore segment La Serrata through geomorphological and geochronological analyses and con-firms this fault as important for hazard assessment. The fault zones to the northeast of the Betics (Jumilla,Crevillente, and Bajo Segura) accommodate total heave rates of about 0.6mm/yr. SE of AL, the sinistralNekor and Al Hoceima faults have predicted heave rates of 0.73 and 0.14mm/yr, respectively, although theymay interchange some of the slip. The Al Hoceima region is known for destructive seismic events in historicaland instrumental catalogs [El Mrabet, 2005; Peláez et al., 2007] with three recent strong events of Mw 6.0 in1994 [e.g., El Alami et al., 1998], 6.4 in 2004 [e.g., Stich et al., 2005b], and the most recent 6.1 on 25 January2016. The Nekor fault has been identified as the surface expression of undergoing tearing of the Alboran westdipping slab [Mancilla et al., 2015]. Tearing may thus be one more possible slab-related mechanism drivingAlboran westward and provoking this seismicity cluster in the Alboran basin/margin.

Along the Atlas mountain ranges, the model predicts slip rates up to 0.8mm/yr in the High Atlas and impor-tant compression rates along the Middle Atlas up to the south Rif; we acknowledge that some of the MiddleAtlas stresses can actually be released also as slip on some faults not included in the model. For the SaharanAtlas, the model predicts up to 0.8mm/yr at its eastern sector. To the east, total convergence rates up to5mm/yr are mostly distributed through the north Algeria offshore thrust (up to 2.5mm/yr), in the Kabyliesthrusts, in particular in El Asnam and Djurdjura zones (up to 1.4mm/yr), and in the Tell Front (more than3mm/yr). These results are in agreement with the observed seismicity in north Algeria, which spreads fromthe Tell front up to the northern offshore margin.

In Portugal, intraplate faults with the highest slip rates are the Lower Tagus Valley (which acts as a thrust) andthe Serra da Estrela pop-up, each system accommodating up to 0.07mm/yr. The two northern large faultsRégua-Verin and Vilariça-Bragança are both modeled as sinistral strike slips with rates up to 0.06mm/yr. Insouth Portugal and Spain, strain rate is also predicted, possibly generating some weak seismicity. In thePyrenees, where no fault was modeled, significant extensional strain rates are predicted; we acknowledgethat some of these strain rates may be expressing the lack of slip rate on some missing faults.

Comparing our preferred model maximum slip rates with SHARE slip rates suggests that the estimation oflong-term fault slip depends on the geodynamic assumptions. Thus, the effect of plate convergence ratesand direction and their influence on faults activities in terms of both slip rates and kinematics must be studied



http://diss.rm.ingv.it/share-edsf/index.html

and accounted for. Otherwise, active-fault databases risk to include only local and better studied faults and tomiss the long-term complexity of the study area.9.2.4. Alboran Driving MechanismsFigure 14b shows the side strength, basal strength, and lithostatic pressure torques acting on the AL plate inthe preferred model. The basal strength force appears as the main driving force, thus claiming for somemechanism, external to the lithosphere, being exerted at AL. Basal shear traction is SW directed, slightlyoblique to the plate motion and toward the location where the slab is still attached, according to tomography[e.g., Spakman and Wortel, 2004; Levander et al., 2014]. We recall that imposed velocities in the Rif region(parameter vbcAL) are west directed, mimicking observed GPS velocities [e.g., Koulali et al., 2011; Palanoet al., 2015]. The fact that basal traction is SW directed supports the hypothesis of the Alboran domain beingdriven by a slab-related mechanism.

A subducted slab sinking in the upper mantle, either delaminated or not, induces mantle flow and affects thelithospheric plate motion. The mechanisms and effects of slab-induced mantle flow on plate motion anddeformation have been discussed by numerical and analogue modeling studies [e.g., Duarte et al., 2013a;Faccenda and Capitanio, 2013; Schellart and Moresi, 2013; Sternai et al., 2014; Chen et al., 2015, 2016;Menant et al., 2016]. Mantle flow can drive the plates from below and can be expressed as shear tractionsdistributed at the base of the lithosphere [e.g., Bird et al., 2008].

Bird et al. [2008] concluded that large plates are driven by deep mantle convection through slab pull and dis-tributed basal shear tractions. In our case, we suggest that the small Alboran block is mainly driven by localslab-inducedmantle flow and, eventually, slab suction. Deflection of mantle flow around the Alboran slab hasbeen revealed by interpretation of mantle anisotropic properties [e.g., Bonnin et al., 2014; Díaz et al., 2015].

10. Conclusions

Here follow the main conclusions of this work:

1. Scoringmisfits from the neotectonic modeling developed in this work are considerably lowwithin most ofthe tested parameter space. This suggests a good accuracy in the reproduction of the observed velocity,stress, and seismic strain patterns.

2. The continuum strain rates and the fault slip rates estimated by our preferred model can be used in theestimation of long-term deformation and in the earthquake and tsunami hazard studies (as done, forexample, by Carafa et al. [2015a]) for the East Mediterranean region.

3. The angular velocity model that best describes the Africa-Eurasia dynamics (either for velocity field, stressfield, or seismic strain reproduction) is the geodetically determined SEGAL2013 pole, rather than thegeological-scale MORVEL pole.

4. The plate configuration that includes an independent Alboran plate (3plates) leads to amore accurate repro-duction of the observed geodesy, stress directions, and seismicity than a simple Africa-Eurasia configuration(2plates). This claims for the presence of an active driving mechanism external to the simple Africa (Nubia)-Eurasia lithospheric convergence applied on the Alboran domain, i.e. a mantle driving mechanism.

5. The basal shear traction necessary to drive Alboran is SW directed, in the direction of the attachedGibraltar slab, suggesting that the Alboran domain is being driven by slab-related mechanisms, likely slabsuction and/or slab-induced mantle flow.

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AcknowledgmentsThe research leading to these resultshas received funding from theEuropean Union’s Seventh FrameworkProgramme (FP7/2007-2013) undergrant agreement 603839 (ProjectASTARTE-Assessment, Strategy and RiskReduction for Tsunamis in Europe).Publication is supported by project FCTUID/GEO/50019/2013-Instituto DomLuiz. M.N. acknowledges support by thePortuguese National ScienceFoundation (fellowship SFRH/BPD/96829/2013). M.M.C.C.’s research wassupported by project MIUR-FIRB“Abruzzo” (code: RBAP10ZC8K_001 andRBAP10ZC8K_003). J.C.D. was sup-ported by a DECRA fellowship(DF150100326) from the AustralianResearch Council. We thank the EditorMartha Savage, the Associate EditorMark D. Behn, and two anonymousreviewers for helpful and constructivecomments and suggestions.Provenance of the input lithosphericand scoring data and respectivemodifications, when applicable, aredescribed along the text. We provide, assupporting information, the finiteelement grid (containing final values oftopography, heat flow, crustal thickness,upper mantle thickness, densityanomaly, and geotherm curvature), thefault database, the plate model, the snxfiles of calculated geodetic velocities,and the SHmax databases.

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http://dx.doi.org/10.1029/2001JB000743


http://dx.doi.org/10.1111/j.1365-246X.1975.tb06206.x

http://dx.doi.org/10.1111/j.1365-246X.1975.tb06206.x


http://dx.doi.org/10.1029/2011TC002989



http://dx.doi.org/10.1130/0091-7613(1994)022%3c0555:esotag%3e2.3.co;2




http://dx.doi.org/10.1002/jgrb.50173

http://dx.doi.org/10.1029/2005JB003856

http://dx.doi.org/10.1029/2005GC001056


http://dx.doi.org/10.1029/2005GL023098

http://dx.doi.org/10.1029/2004JB003366




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Lithospheric deformation in the Africa-Iberia plate boundary:...

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