Tempe Terra is a structurally complex region situated at the northeast edge of the Tharsis Rise volcano-tectonic province (Figure 1). Crustal stresses associated with the development of the Tharsis Rise resulted in the formation of radial extensional features and concentric shortening features surrounding Tharsis (Figure 1) (Anderson et al., 2001). Despite decades of research into various aspects of the Tharsis Rise (e.g.,
Numerous graben features transect the Tempe Terra plateau in the northeastern Tharsis Rise, making it one of the most heavily structured regions of Tharsis. The origin of the complex fault geometries, generated over three distinct stages of tectonic activity, is still poorly understood. This work distinguishes between locally-sourced and regionally-sourced structures within Tempe Terra, to isolate regional deformation patterns related to the general development of the Tharsis Rise from the effects of local mechanisms. Comparison of structural observations to predicted deformation patterns from different sources of graben formation in the Martian crust demonstrates the important role of magmatic activity at a variety of scales in driving tectonism in Tempe Terra. Noachian (Stage 1) faulting was the result of local magmatic underplating and associated heating and uplift, which formed part of an incipient stage of widespread Tharsis volcanism that predated development of the main Tharsis Rise. Early Hesperian (Stage 2) faults reflect the interaction of regional stresses from growth of the Tharsis Rise with magmatic activity highly localised along the Tharsis Montes Axial Trend – a linear volcanotectonic trendline including the alignment of the Tharsis Montes volcanoes. Early–Late Hesperian (Stage 3) faulting resulted from a series of dyke swarms from a Tharsis-centred plume, which propagated in a regional stress field generated by growth of the Tharsis Rise. As only Stage 2 NNE faults and Stage 3 ENE faults are linked to regional, Tharsis-related stresses, other observed Tempe Terra fault trends can be excluded when evaluating models of Tharsis’s tectonic evolution.
<p><strong>Introduction</strong></p> <p>The structurally complex region of Tempe Terra, at the north-eastern edge of the Tharsis Rise, is of substantial interest for understanding the tectonic history of Tharsis, and Mars more broadly. Tempe Terra is a plateau consisting largely of Noachian to Hesperian volcanic and highland units [1], and it preserves evidence of tectonic activity across the lifespan of the Tharsis complex, from faulting of ancient Noachian crust to volcanic and tectonic activity through the Amazonian [2]. Fundamental work on the structural evolution of Tempe Terra [e.g. 2&#8211;5] was done with Viking Orbiter imagery and the 1986 geological map of Scott and Tanaka [6]. But in light of revised geological unit ages [1] and the higher-resolution image data now available, that structural evolution requires revisiting.</p> <p>We present an updated inventory of structures in the Tempe Terra region, based on interpretation of recent, high resolution data. We utilised a detailed mapping approach at a regional scale to capture the area&#8217;s full tectonic complexity. Our work includes qualitative analysis of the regional structural trends, revised groupings and chronologies of constituent tectonic structures, and statistical characterisation of the fault populations present. First analysis shows that the total population of fault lengths is best described by a lognormal distribution, potentially indicating the impact of geological layering on development of the system. This work will lead to a revised structural history and assessment of stress regime evolution for Tempe Terra.</p> <p><strong>Methods</strong></p> <p>We undertook photogeological mapping at a scale of 1:300,000 across a study area 2.3&#160;million&#160;km<sup>2</sup> in extent (Fig.&#160;1), primarily using High Resolution Stereo Camera (HRSC) images (of resolution 12&#8211;25&#160;m/pixel, Mars Express). Thermal Emission Imaging System (THEMIS) image mosaics (at 100&#160;m/pixel, Mars Odyssey) were used to aid mapping interpretation in areas of poor HRSC data quality. The focus of the mapping was normal faults, although other features including pit crater chains, wrinkle ridges, and chasms were also identified (but are not further discussed here). We mapped faults in a direction consistent with the right-hand rule for fault dip (i.e. 45&#176; strike for a SE-dipping fault, 225&#176; strike for a NW-dipping fault). Faults were grouped into sets, taking into consideration their orientation, morphology, crosscutting relations, absolute model age from associated geological units, and genetic relations (e.g. circumferential faults around volcanic centres). Erosional processes have affected existing structures at the plateau edges to the north and south, making some landforms ambiguous and their interpretation challenging.</p> <p>Each mapped fault was assigned values for strike, length, and inferred dip direction (taken as 90&#176; to the right of the fault strike), to help quantitatively characterise each fault set. We also assessed fault scaling properties by comparing functions for the cumulative frequency distribution of fault lengths with the Maximum Likelihood Estimators (MLE) function of the FracPaQ toolkit in MATLAB [7, 8]. Such analyses can help establish the mechanical properties of faulted rock, with power-law (fractal) distributions of fault lengths commonly described for deeply penetrating structures, and exponential distributions for faults in a brittle layer of restricted thickness [9].</p> <p><img src="data:image/jpeg;base64, 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
Tempe Terra is a structurally complex region situated at the northeast edge of the Tharsis Rise volcano-tectonic province (Figure 1). Crustal stresses associated with the development of the Tharsis Rise resulted in the formation of radial extensional features and concentric shortening features surrounding Tharsis (Figure 1) (Anderson et al., 2001). Despite decades of research into various aspects of the Tharsis Rise (e.g.,
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