Geology Reference
In-Depth Information
lithologies. Recovering all the rocks from such areas has
been suggested and even tested, but as the number density
of terrestrial rock increases, the scale of such an effort
becomes impractical, even absurd. For example, in 1997
and 1998 ANSMET marked off a 100 × 100 m region of
the informally named Mare Meteoriticus icefield in the
Foggy Bottom region of the Walcott Névé (the major
source of QUE specimens), an area subjectively consid-
ered representative of the average numerical surface
density of rocks. One hundred twenty-five rocks were
recovered during this exercise, but no meteorites. This
same exercise, if scaled up to the entire Mare Meteoriticus
icefield, would require the collection of more than 500
million rocks in the <4-g range alone, of which roughly
one in 250,000 would probably be a meteorite. Sorting
meteorites from terrestrial rocks in some fashion must
inevitably be considered more effective.
A number of technologically sophisticated sorting
tools have been suggested and tested by ANSMET,
including everything from simple metal detectors to a
meteorite-hunting robot (NOMAD) equipped with mul-
tiple sensors and intelligent processing algorithms [e.g.,
Apostolopoulos et al.
, 2001]. In our experience, such tech-
nological sensors have inevitably proven both slow and
prone to unintentional sorting. For example, while well-
calibrated metal detectors can efficiently sort iron, stony
iron, and ordinary chondrite meteorites from terrestrial
rock due to the presence of metal in the former, many of
the most scientifically valuable Antarctic meteorites con-
tain little or no metal and are effectively indistinguishable
from common Antarctic igneous rocks. Equally impor-
tant is that operation of such detectors divides the opera-
tor's attention between their eyes and the signals from the
detection device; all too often, the latter takes precedence
because it seems less subjective and involves conscious
recognition of a signal. In fact, it
is
simpler, but primarily
because it is a less data-rich detection technique, focused
on the ferromagnetic properties of a rock and ignoring
other key variables such as size, shape, texture, patina,
and color. Second, while the speed of modern computer
processors and robotic systems is growing exponentially,
it has not yet come close to the human mind's ability to
integrate a scene and pick out key elements. Our experi-
ments with NOMAD suggest that a trained individual
with innate positioning, path-choosing, and visual syn-
thesis skills may be several hundred times more efficient
than a robot (at least from that era) [
Harvey
, 2003].
Finally, there is ample indication that the human visual
system is effective even in confusing environments. Of the
5,900 specimens recovered from meteorite stranding sur-
faces in the Walcott Névé region (LEW, QUE, and MAC
specimens), all but a few hundred were recovered from
regions rich in terrestrial rock. These specimens include
many notable samples easily confused with terrestrial
rocks, including two martian specimens, five lunar speci-
mens, and several rare igneous specimens such as angrites
and brachinites. Certainly some proportion of meteorites
were not recovered, particularly those lacking diagnostic
fusion crust; but the overall success of meteorite recovery
in such confusing environments suggests losses are not
high enough to warrant dramatic changes to our current
operational procedures.
Another proposed sorting strategy is “high-grading”:
purposefully targeting recoveries on achondrites or large
specimens that are of the most interest to science and
ignoring more mundane discoveries such as small ordi-
nary chondrites [
Harvey
, 2003]. Some amount of this
does in fact take place during reconnaissance searches,
when unique specimens are encountered by sheer chance,
time is limited, and any recoveries that do take place must
be prioritized, given the risk that a site might not be revis-
ited. Unfortunately, the potential loss of interesting spec-
imens during high-grading is very high. As noted earlier,
rare specimens are not always easily recognized from
among other meteorites; the differences in their lithol-
ogies may be subtle at the hand-specimen level of exami-
nation, and fusion crust typically hides their interior.
Many unique specimens in the existing Antarctic collec-
tions were not recognized as such while in the field
(Figure 2.3). It is also not clear that searching specifi-
cally for rare specimens would significantly reduce the
amount of time it takes to find them, given that the
geographical distribution of meteorites on each icefield
shows no distinction among meteorite types. Getting
to the meteorite concentration site for even the most
cursory examination is the major logistical cost faced
by ANSMET, and with actual collection times that are
short, the value of high-grading decreases. ANSMET
field searches take the opposite approach, choosing to
recover everything that is clearly a meteorite or has the
potential to be a meteorite. By doing so, we accept some
level of false positives but increase the likelihood that
unusual specimens will not be overlooked.
2.4.2. Recognizing Meteorites
Many of the meteorite stranding surfaces explored by
ANSMET are far enough inland of the Transantarctic
Mountains that they are devoid of terrestrial rocks; any
rock found at such sites almost certainly fell from the sky,
essentially making recognition of them as meteorites a
trivial pursuit. At the remaining sites, however, meteor-
ites are often mixed with terrestrial rocks, either blown
out onto the ice by the katabatic winds or carried in by
glacial movement to form moraines. Recognizing meteor-
ites in such settings is thus a crucial task for ANSMET
field parties. The capability of the human visual system
as an innate and not-entirely-conscious tool for meteorite
