1
2
Geochemistry, Geophysics, Geosystems
3
Supporting Information for
4
Varying styles of magmatic strain accommodation in the East African Rift
5
James D. Muirhead1, Simon A. Kattenhorn1,2, Nicolas Le Corvec3
6
7
8
1. Department of Geological Sciences, University of Idaho, Moscow, Idaho 83844, USA
2. ConocoPhillips Company, Houston, Texas 77079, USA
3. Lunar and Planetary Institute, Houston, Texas 77058, USA
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Contents of the supporting material
25
26
27
28
29
Additional Supporting Information (Files uploaded separately)
30
Introduction
31
32
33
34
35
36
37
38
The supplementary text provides a detailed description of our methods for determining
cone lineaments, vent alignments and cone groupings, and a brief review of physical
processes driving local modifications of the remote stress field. We provide 4 supporting
figures illustrating our methods, 1 showing radial patterns in South Natron and Arusha
using a moving average analysis, and 2 figures of 2-D elastic models illustrating tectonomagmatic processes controlling local stress perturbations. The 4 tables provided
(additional supporting information) summarize all data used in this study. These tables
are available as Excel spreadsheets.
Text S1. Stress fields induced by pressurized magma chambers.
Text S2. Stress rotations induced by mechanical interactions between rift segments.
Text S3. Observational methods: deducing cone lineaments.
Text S4. Analytical methods: creation of vent alignments.
Text S5. Defining cone field boundaries in the North Tanzanian Divergence and
Kenya Rift.
Text S6. Cone fields in the North Tanzanian Divergence and Kenya Rift.
Figure S1. Two-dimensional elastic models of a pressurized hole in an elastic plate.
Figure S2. Moving average analyses of dike trends in the South Natron and Arusha
fields.
Figure S3. Two-dimensional elastic model of interacting rift segments.
Figure S4. Classification of cone morphologies used to determine cone lineaments.
Figure S5. Schematic demonstration of the criteria for defining vent alignments.
Figure S6. Cone groupings in the North Tanzanian Divergence.
Figure S7. Cone groupings in the North Tanzanian Divergence and Kenya Rift.
Table S1. Locations and lineament trends produced by volcanic cones in this study.
Table S2. Vent alignment locations and orientations.
Table S3. Fault locations, lengths and orientations.
Table S4. Focal mechanism data for the North Tanzanian Divergence.
1
39
Text S1. Stress fields induced by pressurized magma chambers
40
The stress conditions involved in the generation of radial dike patterns may be
41
modeled in two-dimensions as a pressurized hole in an elastic body subject to a biaxial
42
remote stress field [Muller and Pollard, 1977; Baer and Reches, 1991; Koenig and
43
Pollard, 1998]. Some modeling studies also include additional stress sources, such as
44
an overlying volcanic load [e.g., Pinel and Juapart, 2003; Hurwitz et al., 2009; Le Corvec
45
et al., 2015]. The presence of a pressurized hole, or magma chamber, perturbs the local
46
stress field (Fig. S1). This perturbation results in a radial stress pattern, where the
47
greatest compressive stress (σ1) rotates around the chamber such that the strike of σ 1
48
everywhere converges on the center of the chamber. The magnitude of this local stress
49
perturbation is dependent on magma chamber radius (R), internal magma pressure (P)
50
and the remote differential stress (σ11- σ22) (Fig. S1a). If R and P remain constant, the
51
magnitude of the stress perturbation decreases with increasing differential stress values
52
(Figure S1b-d).
53
This study describes a number of radial dike patterns in the East African Rift
54
(EAR), possibly reflecting these modeled effects. Figure S2 shows a moving average
55
analysis of the radial dike swarms in the North Tanzanian Divergence. Note the change
56
in the mean orientations in the NE, SE, SW and NW sectors around the Oldoinyo Lengai
57
and Meru volcanoes. Around Meru, dikes in the NE and SW sectors exhibit ~NE-SW
58
striking trends, whereas dikes in the NW and SE sectors exhibit ~NW-SE trends,
59
indicative of a radial pattern. This radial trend prevails for cone lineaments both near the
60
volcano (<25 km from the volcano summit), as well as those as far as 40 km from the
61
summit. Radial swarms may also be differentiated using the method of maximum
62
intersections (Ancochea et al. 2008), shown in Figures 6 and 7 of the main text.
63
64
Text S2. Stress rotations induced by mechanical interactions between rift
65
segments
66
Field, analog, and numerical modeling studies show that the lateral growth of en-
67
echelon structural segments, whether joints, faults, dikes or rifts, is accompanied by
68
stress interactions between adjacent segments [Pollard and Aydin, 1984]. In some
69
instances, these stress interactions may cause the lateral ends of segments to rotate,
70
forming two interlocking hooks (Pollard et al., 1982; Olson and Pollard, 1991; Thomas
71
and Pollard, 1993; Tentler, 2003; Koehn et al., 2008). The interaction zone where these
72
rotations occur is located in the area between segment ends (Fig. S3b and c) [Pollard
2
73
and Aydin, 1984]. This behavior is inferred to be scale-invariant, occurring in brittle
74
material over at least 11 orders of magnitude in length scale, from micro-cracks to mid-
75
ocean ridge or continental rift segments [Pollard and Aydin, 1984; Tentler, 2003; Koehn
76
et al., 2010]. The size of these interaction zones thus scales with the size of the
77
interacting structural segments.
78
these interaction zones will be on the order of 10-1 to 100 m2 [Pollard et al., 1982; Pollard
79
and Aydin, 1984]. For continental rift basins 100s of km in length, such as the EAR,
80
these interaction zones, commonly termed transfer zones, may occupy areas of 102 to
81
103 km2 [Ebinger, 1989; Koenh et al., 2010; Corti, 2012].
For macro-scale fractures tens of meters in length,
82
En echelon structural segments in extensional settings may be modeled in two-
83
dimensions as two offset slits (mode I fractures) in an elastic medium subject to remote
84
tensile stresses acting normal to the slit walls [Pollard and Aydin, 1984; Gudmundsson,
85
1995] (Fig. S3a). Early-stage continental rift segments have been modeled previously
86
as underlapping segments [Pollard and Aydin, 1984] (Fig. S3a and b), as would be
87
appropriate for the Natron and Pangani basins shown in Figure S3c. High stress
88
concentrations form at the tips of mode I fractures subjected to an external tensile stress
89
field [Olson and Pollard, 1989]. In the case of two offset fracture or rift segments, stress
90
fields generated at the respective segment tips interact and locally reorient the principal
91
stress directions [Pollard and Aydin, 1984;
92
reorientation causes fracture segments to divert from their original propagation paths,
93
and in some instances form the characteristic interlocking hook shapes between
94
segment ends [Pollard et al., 1982; Tentler, 2003]. For the two underlapping, left-
95
stepping segments modeled in Fig. S3b, the interaction between segments results in a
96
counter-clockwise rotation of the horizontal principal stresses. The dike and fault
97
orientations observed in the interaction zone (transfer zone) between the left-stepping
98
Natron and Pangani rift segments (Fig. S3c) are consistent with this modeled interaction
99
and resulting stress rotation. A similar counter-clockwise stress rotation is inferred for the
100
Rwenzori transfer zone between the left-stepping Lake Albert and Lake Edward rift
101
basins of the EAR, based on fault kinematic and numerical modeling data [Koehn et al.,
102
2008, 2010]. This type of stress modification in the interaction zone between segments
103
has been described in a number of studies as a “mechanical interaction” between
104
rift/fracture segments [Pollard et al., 1982; Pollard and Aydin, 1984; Olsen and Pollard,
105
1991; Crider and Pollard, 1998]; hence, we adopt the same terminology in this work.
Gudmundsson 1995]. This stress
106
3
107
Text S3. Observational methods: deducing cone lineaments
108
Monogenetic volcanic cones were mapped using aerial photography (0.5 m
109
resolution) and Google Earth satellite imagery (1-2 m resolution), supplemented by
110
published maps [Roberts, 2002; Dawson, 2008; Wauthier, 2011; Smets et al., 2014] (see
111
Table S1). Following Paulsen and Wilson [2010], the idealized shapes (circular to
112
elliptical) of cones and craters were determined and each cone was classified as a cone,
113
cleft cone, linear fissure, or crater (Fig. S4). As the resolution of the imagery (0.5-2.0 m)
114
is an order of magnitude greater than the typical dimensions of the monogenetic cones
115
(30-1000 m radii), the reliability of the cone morphology is not affected by image
116
resolution. The reliability of the shape of each cone was nonetheless ranked (1 =
117
probable; 2 = likely; 3 = unknown) depending on the degree of observable erosion and
118
the likelihood that the cone morphology was affected by wind direction rather than a
119
possible dike-feeder. The cone was considered to produce a lineament if it had a
120
reliability ranking of 1 or 2 and a cone or crater axial ratio (long axis to short axis) >1.2,
121
which is the minimum ratio required to define lineaments from Paulsen and Wilson
122
[2010]. If these criteria were met, the trend of the long axis of the cone was recorded and
123
interpreted to mimic the dike that fed the cone [Tibaldi, 1995; Korme et al., 1997; Bonali
124
et al., 2011]. If both the cone base and cone crater exhibited an axial ratio >1.2, the long
125
axis direction of the crater was used in the analysis. In addition to using cone and crater
126
elongations, the breaching direction (Fig. 4 of main text) was used as a direct indicator of
127
feeder dike orientation [i.e., Tibaldi, 1995], as well as the strike of volcanic fissures (Fig.
128
S4). Throughout this paper these features are described as cone lineaments, and are
129
inferred to reflect the strike of the dike that fed the volcanic cone (Fig. S4).
130
131
Text S4. Analytical methods: creation of vent alignments
132
In addition to identifying cone lineaments, alignment analyses were performed on
133
groups of 3 cones using the linear regression algorithm and MATLAB script of Le Corvec
134
et al. [2013]. For these analyses, each alignment must satisfy a certain “width” and
135
“length” tolerance (Fig. S5). For our analyses, a width tolerance of 50 m was used, which
136
is within the width tolerance for “A grade” alignments of Paulsen and Wilson [2010] (125
137
m). The length tolerance of the alignment depended on the observed distribution of
138
cones within each field, where the mean distance between cones within the alignment
139
had to be less than the expected mean distance between cones from a Poisson
140
distribution (Table 1).
4
141
Following Paulsen and Wilson [2010], the reliability of each alignment was then
142
verified by assessing cone lineaments produced by cones present within each alignment
143
(Fig. S5). In this case, there must be a cone present within the alignment that has a cone
144
lineament trend within 15˚ of the alignment trend for the alignment to be considered for
145
our analysis. As such, each vent alignment satisfied the reliability criteria for vent
146
alignments defined by Paulsen and Wilson [2010]. In our study, if these criteria were
147
met, the trend of the alignment was recorded, and any cones present within the
148
alignment that did not exhibit a cone lineament trend (i.e. have an axial ratio <1.2 and/or
149
a reliability rating of 3) were ascribed a cone lineament trend that matched the
150
alignment. Alignments analyzed in each field are outlined in Supplementary Table S2.
151
Throughout this paper, these features are described as vent alignments and are distinct
152
from cone lineaments, as they represent a structural alignment between 3 points [e.g.,
153
Le Corvec et al., 2013] rather than the orientation of a feeder dike below a single cone
154
[e.g., Bonalli et al., 2011].
155
156
Text S5. Defining cone field boundaries in the North Tanzanian Divergence and
157
Kenya Rift
158
Boundaries delineating cone fields analyzed in the North Tanzanian Divergence
159
and Kenya Rift in this study have not been previously specified, in part due to an
160
incomplete catalog of geochemical data and ages for most cones. Similar problems
161
occur in the EAR as a result of sparse geochemical sampling [e.g., Main Ethiopian Rift:
162
Mazzarini, 2007], as well as in cone fields elsewhere [e,g., Baja California, Mexico:
163
Germa et al., 2013]. Monogenetic fields are, therefore, often grouped using statistical
164
methods, such as agglomerative hierarchical clustering [Mazzarini, 2004; Mazzarini et
165
al., 2013] or kernel density estimations [Connor and Connor, 2009; Germa et al., 2013].
166
Volcanic cone groupings in the North Tanzanian Divergence in this study did not depend
167
solely on density estimations (Figs. S6 and S7). This is because the distribution of cones
168
appears to be affected by large volcanic edifices (composite volcanoes) and areas of
169
high sediment input, possibly creating artificial clusters. For example, a distinct scarcity
170
of cones was observed in the 1.2 Ma Engaruka (sub-)basin (Fig. S6a); cones erupted
171
into this depression are likely buried by rapidly accumulating sediments in the subsiding
172
basin. Dikes intersecting volcanic edifices are also more likely to erupt on the lower
173
flanks rather than the volcano summit and, in these instances, cones may form clusters
5
174
on the lower flanks of volcanoes [Pinel et al., 2004; Gaffney and Damjanac, 2006;
175
Kervyn et al., 2009] (Fig. S7a).
176
As our analysis addressed the variability in cone lineament and vent alignment
177
data across different structural locations in the North Tanzanian Divergence and Kenya
178
Rift, we chose to approximate boundaries based on general rift structure and the spatial
179
distribution of vents (Figs. S6 and S7). Cones within the defined groups exhibit distinct
180
trends that align locally with fault structures (Fig. 5 of main text), and we therefore
181
consider that dividing up vent groups based on basin structure is appropriate for our
182
analyses.
183
184
Text S6. Cone fields in the North Tanzanian Divergence and Kenya Rift
185
The sections of the North Tanzanian Divergence and Kenya Rift analyzed in our study
186
were divided into 6 cone fields: Naivasha-Nakuru, Natron-Magadi, South Natron,
187
Arusha, Ngorongoro Volcanic Highlands, and Kilimanjaro (Figs. S6 and S7; Fig. 5 of
188
main text). The Natron-Magadi field was delineated based on a distinct lack (n=19) of
189
monogenetic cones over a ~130 km-long section from Gelai volcano in the south to
190
Suswa volcano in the north (Fig. S7a). North of the Natron-Magadi field are volcanic
191
cones of the Naivasha-Nakuru field. The Naivasha-Nakuru basin represents a distinct
192
magmatic-tectonic province (Kenya peralkaline province) of the Kenya Rift [MacDonald
193
and Baginski, 2009], comprising a series of actively deforming composite volcanoes and
194
silicic centers (e.g., Suswa, Longonot, Menegai) [Biggs et al., 2009]. The transition from
195
the Natron-Magadi field north into the Naivasha-Nakuru field is marked by an increase in
196
the number of cones (n=118) north of Suswa volcano, which exhibit significant clustering
197
in the center of the field (Fig. S7b). The South Natron field (cluster 1 in Fig. S6b) has a
198
greater number of cones (n=267) and extends rift-parallel across the southernmost ~40
199
km of the Natron Basin into the northernmost ~10 km of the Ngorongoro-Kilimanjaro
200
Volcanic Belt.
201
orientations (029° and 011° mean strike, respectively), and also align sub-parallel with
202
the orientation of the 2007 Natron dike (027° strike: Calais et al., 2008). It also contains
203
a unique group of cones with a mean ESE-WNW trend that, on closer inspection, forms
204
a sub-radial pattern (section 4.2 of main text). A small group of cones (n=15) ~50 km
205
southwest of the South Natron field exhibit a NE-SW cone lineament trend, and form the
206
Ngorongoro Volcanic Highlands field (cluster 2 in Fig. S6b). East of this field are three
207
clusters of cones (clusters 3, 4 and 5 in Fig. S6b), all of which exhibit a NW-SE trend
Here, cone lineaments and faults exhibit primarily spreading-normal
6
208
and are surrounded by NW-SE trending faults. Based on the similar structural trends
209
observed in these clusters, they have been grouped into a single cone field, called the
210
Arusha field. The final cone field delineated in this study is the Kilimanjaro field (clusters
211
6 and 7 in Fig. S6b). This field consists of cones on or around the flanks of Kilimanjaro
212
volcano. These cones exhibit a NW-SE cone lineament trend. Unlike the Arusha field, no
213
faults are identifiable in Google Earth imagery in the Kilimanjaro field.
7
214
Spporting figure captions
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
Figure S1. Two-dimensional elastic models of a pressurized hole (magma chamber) in
an elastic plate, modified from Koenig and Pollard [1998]. A: Idealization of the model
setup. Pink circle represents the pressurized hole (magma chamber) with radius, R, and
internal pressure, P. The hole is subject to remote biaxial loading from a least (σ 22) and
greatest (σ11) compressive stress. θ and r indicate the polar coordinate system, the
origin of which is located at the center of the hole. B-D: Calculated stress trajectories
resulting from a pressurized magma chamber. Black ticks at each grid point represent
the local orientation of σ1. In each example, internal magma pressure (100 MPa) and
chamber diameter (normalized to 1) are held constant, while the remote stress
difference is varied from 2 to 10 to 20 MPa in B, C and D, respectively. Analytical
solutions for these models are provided in Koenig and Pollard [1998].
Figure S2. Moving average analyses of dike trends in the South Natron and Arusha
fields. The analysis was performed in ArcGIS v. 10.3 and involves non-overlapping
neighborhoods (2.5 x 2.5 km in size) and a search radius of 6 km. Neighborhoods
colored blue contain cone lineaments with mean strike values in NE and SW quadrants
(i.e., 000-090° and 180-270°, respectively). Neighborhoods colored red contain cone
lineaments with mean strike values in SE and NW quadrants (i.e., 090-180° and 270360°, respectively). A: Moving average analysis of cone lineaments in the Arusha field
for neighborhoods within 40 km of the summit of Meru volcano. B: Same analysis as in
A, except that only neighborhoods within 25 km of the summit are presented. C: Analysis
of mean strike values of cones in the South Natron field for neighborhoods within 22 km
of the summit of Oldoinyo Lengai. Note that in each analysis the mean orientations of
cone lineaments varies depending on the position around the volcano. Cones in NE and
SW quadrants also show ca. NE-SW striking lineaments. Those in SE and NW
quadrants exhibit ca. SE-NW striking lineaments. These geometries are consistent with
a radial pattern.
Figure S3. Two-dimensional elastic model of interacting rift segments, modified from
Pollard and Aydin [1984]. A: Geometry and boundary conditions for two rift segments
subject to orthogonal extension. The model considers rift segment length (2b), segment
spacing (2k) and segment separation (2s). The remote tectonic stress (tensile) normal to
the rift is σr11 and α represents the angle between the rift segment ends with respect to
the strike of the rift. B: Contour map of maximum shear stress ((σ1 – σ2)/2) and stress
orientations (black ticks represent the orientation of the greatest compressive stress) for
left-stepping, underlapping rift segments (α = 45°) subject to far-field tension. Stress
magnitudes are normalized to the ambient shear stress. The highest stress occurs near
the segment tips and within the interaction zone between the rift segments (dashed box),
where the orientations of the principal stresses are locally rotated in a counter-clockwise
sense. Analytical solutions applied in this model are provided in Pollard and Aydin
[1984]. C: Example of underlapping, left-stepping rift segments in the North Tanzanian
Divergence. Dike (grey rose plots) and fault data (black rose plot) are from this study.
8
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
These data show a counter-clockwise rotation of the principal stresses away from the
regional stress field, consistent with the model results in B.
Figure S4. Example images from Google Earth representing the classification of cone
morphologies used to determine cone lineaments from the Virunga Province (A and D),
Boset segment (B), and South Natron (C). Double-sided arrows show the orientation of
the cone lineaments for each cone based on fissure orientation (A), crater elongation (B
& C), and breaching direction (D).
Figure S5. Schematic demonstration of the criteria for defining vent alignments,
modified from Le Corvec et al. [2013]. The alignment represented by the black line (i) is
accepted for analysis because it contains a cone with a lineament trend that has an
angular deviation <15˚ from the trend of the alignment. The red alignments are rejected
on the basis that they have no cone with a reliable lineament (ii) or, alternatively, have a
cone with a lineament that is >15˚ to the trend of the vent alignment (iii).
Figure S6. A: Distribution of monogenetic cones in the North Tanzanian Divergence
shown on an Aster DEM hillshade map. Note how the cones are largely absent near the
summits of stratovolcanoes (transparent purple) and in the Engaruka Basin (transparent
brown). B: Kernel density plots of North Tanzanian Divergence cones performed in Arc
GIS v.10 using a 15 km search radius. Rose plots are of fault segment and cone
lineament trends in the 7 computed clusters. NVH corresponds to Ngorongoro Volcanic
Highlands.
Figure S7. A: Distribution of monogenetic cones in the North Tanzanian Divergence and
Kenya Rift shown on an Aster DEM hillshade map. B: Kernel density plots performed in
Arc GIS v.10 using a 15 km search radius. Rose plots are of fault segment and cone
lineament trends in each field.
9
285
References
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
Ancochea, E., J. L. Brandle, M. J. Huertas, F. Hernan, and R. Herrera (2008), Dikeswarms, key to the reconstruction of major volcanic edifices: The basic dikes of
La Gomera (Canary Islands), Journal of Volcanology and Geothermal Research,
173, 207-216.
Baer, G., and Z. Reches (1991), Mechanics of emplacement and tectonic implications of
the Ramon dike systems, Israel, Journal of Geophysical Research-Solid Earth
and Planets, 96(B7), 11895-11910.
Bonali, F. L., C. Corazzato, and A. Tibaldi (2011), Identifying rift zones on volcanoes: an
example from La Reunion island, Indian Ocean, Bulletin of Volcanology, 73(3),
347-366.
Connor, C. B., and L. J. Connor (2009), Estimating spatial density with kernel methods,
in Volcanic and tectonic hazard assessment for nuclear facilities, edited by C. B.
Connor, N. A. Chapman and L. J. Connor, pp. 387-412, Cambridge University
Press, Cambridge.
Corti, G. (2012), Evolution and characteristics of continental rifting: Analog modelinginspired view and comparison with examples from the East African Rift System,
Tectonophysics, 522, 1-33.
Crider, J. G., and D. D. Pollard (1998), Fault Linkage: Three-dimensional mechanical
interaction between echelon normal faults, Journal of Geophysical ResearchSolid Earth, 103(B10), 24373-24391.
Dawson, J. B. (2008), The Gregory Rift Valley and Neogene-Recent Volcanoes of
Northern Tanzania Introduction, Gregory Rift Valley and Neogene-Recent
Volcanoes of Northern Tanzania, 33, 1-2.
Ebinger, C. J. (1989), Geometric and kinematic development of border faults and
accommodation zones, Kivu-Rusizi Rift, Africa, Tectonics, 8, 117-133.
Gaffney, E. S., and B. Damjanac (2006), Localization of volcanic activity: Topographic
effects on dike propagation, eruption and conduit formation, Geophysical
Research Letters, 33(14), doi: 10.1029/2006gl026852.
Germa, A., L. J. Connor, E. Canon-Tapia, and N. Le Corvec (2013), Tectonic and
magmatic controls on the location of post-subduction monogenetic volcanoes in
Baja California, Mexico, revealed through spatial analysis of eruptive vents,
Bulletin of Volcanology, 75(12), doi: 10.1007/s00445-013-0782-6
Gudmundsson, A. (1995), Stress fields associated with oceanic transform faults, Earth
and Planetary Science Letters, 136(3-4), 603-614.
Hurwitz, D. M., S. M. Long, and E. B. Grosfils (2009), The characteristics of magma
reservoir failure beneath a volcanic edifice, Journal of Volcanology and
Geothermal Research, 188, 379-394.
Kervyn, M., G. G. J. Ernst, B. V. de Vries, L. Mathieu, and P. Jacobs (2009), Volcano
load control on dyke propagation and vent distribution: Insights from analogue
modeling, Journal of Geophysical Research-Solid Earth, 114,
10.1029/2008jb005653
10
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
Koehn, D., K. Aanyu, S. Haines, and T. Sachau (2008), Rift nucleation, rift propagation
and the creation of basement micro-plates within active rifts, Tectonophysics,
458(1-4), 105-116.
Koehn, D., M. Lindenfeld, G. Rumpker, K. Aanyu, S. Haines, C. W. Passchier, and T.
Sachau (2010), Active transsection faults in rift transfer zones: evidence for
complex stress fields and implications for crustal fragmentation processes in the
western branch of the East African Rift, International Journal of Earth Sciences,
99(7), 1633-1642.
Koenig, E., and D. D. Pollard (1998), Mapping and modeling of radial fracture patterns
on Venus, Journal of Geophysical Research-Solid Earth, 103(B7), 15183-15202.
Korme, T., J. Chorowicz, B. Collet, and F. F. Bonavia (1997), Volcanic vents rooted on
extension fractures and their geodynamic implications in the Ethiopian Rift,
Journal of Volcanology and Geothermal Research, 79(3-4), 205-222.
Le Corvec, N., B. K. Spörli, J. V. Rowland, and J. Lindsay (2013), Spatial distribution and
alignments of volcanic centers: Clues to the formation of monogenetic volcanic
fields Earth Science Reviews, 124, 96-114.
Le Corvec, N., P. J. McGovern, E. B. Grosfils, and G. Galgana (in press), Effects of
crustal-scale mechanical layering on magma chamber failure and magma,
Journal of Geophysical Research, doi: 10.1002/2015JE004814.
Mazzarini, F. (2004), Volcanic vent self-similar clustering and crustal thickness in the
northern Main Ethiopian Rift, Geophysical Research Letters, 31,
doi:10.1029/2003GL018574.
Mazzarini, F. (2007), Vent distribution and crustal thickness in stretched continental
crust: The case of the Afar Depression (Ethiopia), Geosphere, 3(3), 152-162.
Mazzarini, F., T. O. Rooney, and I. Isola (2013), The intimate relationship between strain
and magmatism: A numerical treatment of clustered monogenetic fields in the
Main Ethiopian Rift, Tectonics, 32(1), 49-64.
Muller, O. H., and D. D. Pollard (1977), The stress state near Spanish Peaks, Colorado
determined from a dike pattern, Pure and Applied Geophysics, 115, 69-86.
Olson, J., and D. D. Pollard (1989), Inferring paleostress from natural fracture patterns: a
new method, Geology, 17, 345-348.
Olson, J. E., and D. D. Pollard (1991), The initiation and growth of en echelon veins,
Journal of Structural Geology, 595-608.
Paulsen, T. S., and T. J. Wilson (2010), New criteria for systematic mapping and
reliability assessment of monogenetic volcanic vent alignments and elongate
volcanic vents for crustal stress analyses, Tectonophysics, 482(1-4), 16-28.
Pollard, D. D., P. Segall, and P. T. Delaney (1982), Formation and interpretation of
dilatant echelon cracks, Geological Society of America Bulletin, 93, 1291-1303.
Pollard, D. D., and A. Aydin (1984), Propagation and linkage of ocean ridge segments,
Journal of Geophysical Research, 89, 17-28.
Pinel, V., and C. Jaupart (2003), Magma chamber behavior beneath a volcanic edifice,
Journal of Geophysical Research-Solid Earth, 108, doi: 10.1029/2002jb001751.
Pinel, V., and C. Jaupart (2004), Magma storage and horizontal dyke injection beneath a
volcanic edifice, Earth and Planetary Science Letters, 221(1-4), 245-262.
11
371
372
373
374
375
376
377
378
379
380
381
382
383
384
Roberts, M. A. (2002), The geochemical and volcanological evolution of the Mt. Meru
region, northern Tanzania, 264 pp, University of Cambridge.
Smets, B., et al. (2014), Detailed multidisciplinary monitoring reveals pre- and coeruptive signals at Nyamulagira volcano (North Kivu, Democratic Republic of
Congo), Bulletin of Volcanology, 76(1), 10.1007/s00445-013-0787-1
Tentler, T. (2003), Analogue modeling of overlapping spreading centers: insights into
their propagation and coalescence, Tectonophysics, 376(1-2), 99-115.
Thomas, A. L., and D. D. Pollard (1993), The geometry of echelon fractures in rock implications from laboratory and numerical experiments, Journal of Structural
Geology, 15(3-5), 323-334.
Tibaldi, A. (1995), Morphology of pyroclastic cones and tectonics, Journal of
Geophysical Research-Solid Earth, 100(B12), 24521-24535.
Wauthier, C. (2011), InSAR applied to the study of active volcanic and seismic areas in
Africa, 209 pp, University of Liege.
12