A statistical test for correlation between crater formation rate and mass extinctions

Transcription

1 Mon. Not. R. Astron. Soc. 282, (1996) A statistical test for correlation between crater formation rate and mass extinctions Maki Matsumoto * t and Hirota Kubotani* t Department of Physics, Ochanomizu University, Bunkyo, Tokyo 112, Japan Accepted 1996 June 18. Received 1996 April 23; in original fonn 1995 December 11 1 NTRODUCTON Fossil records show that most biological species have not always evolved monotonously; they have also experienced extinctions. Furthermore, mass extinctions, i.e. events in which numerous species in different regions on the arth disappeared simultaneously at certain horizons in the geological records, are observed. For example, we can find bones of dinosaurs and fossils of ammonites up to just below the Cretaceous-Tertiary (KT) boundary, which was formed 65 million years ago (Ma), but not above it. t is also well known that a lot of marine animal families and genera died out at the end of the Permian (250 Ma), which corresponds to the Permian-Triassic (PfTr) boundary. The cause of the KT boundary extinction has been researched most widely and verified most frequently. Alvarez et al. (1980) claimed that the mass extinction at the KT boundary was brought about catastrophically by the giant impact of an asteroid. They based their argument on world-wide iridiumrich layers found in the K!f boundary clay, which might be the vapourized remnant of the crash. t is called an iridium anomaly, since iridium had been depleted in the crust and mantle and concentrated in the core of the arth. For the K/ *Present address: Asahi-Kasei Microsystems, Atsugi 243, Japan (MM); Department of Mathematics, Nara University of ducation, Takabatake, Nara 630, Japan (HK). ' t-mail: maki@akm-dc.atsugi.asahi-kasei.co.jp (MM), kubotani@phys.ocha.ac.jp (HK) ABSTRACT Previous works have analysed the stationary periodicities of terrestrial crater formation rate and mass extinctions, and have compared the periods to discuss their causality. However, the coincidence of the periods does not necessarily mean that the two are correlated. Thus, in order to estimate the correlation directly, we test the null hypothesis that extinctions occurred independently of peaks in the crater formation rate. This hypothesis is rejected with a low significance level ( per cent), even if the uncertainty in dating the craters is taken into account. Therefore, the rhythm of the mass extinctions with the time-scale of 30 Myr is highly correlated with that of the giant impacts. Key words: methods: statistical - comets: general - arth - meteors, meteoroids. T boundary, the discovery of an iridium anomaly and other recent analyses consistently supports the extraterrestrial scenario of the extinction (van den Bergh 1994; Rampino & Haggerty 1995). n 1984, Raup & Sepkoski (1984) counted extinctions of marine animals over the past 250 million years (Myr) and identified 12 significant mass extinction events. They found out that the mass extinctions occurred with a 26-Myr period. Their conclusion evoked controversy, since it had been implicitly believed that mass extinctions were random events driven by miscellaneous factors, but the observed periodicity indicated the existence of a dominant unique reason. After their work, some astronomers elaborately analysed the ages of terrestrial impact craters in order to seek evidence of bombardments with a period of the order of 30 Myr, which might be followed by mass extinctions just as in the KT boundary. They also proposed causes for the periodicity. According to various scenarios, the Oort cloud is perturbed by a large interstellar cloud (Rampino & Stothers 1984) and by gravitational tidal force (Bailery, Clube & Napier 1990; Matese et al. 1995) which the Solar system encounters periodically through the perpendicular motion in our Galactic disc or through the influence of Nemesis (Whitmire & Jackson 1984; Davis, Hut & Muller 1984), which is an unseen companion star of the Sun. As a result, a significant number of comets were driven into the orbit arriving at the planetary region. The bombardment in a discrete shower called a 'comet shower', continued for 1-3 Myr (Hut et al. 1987). During each comet shower, several comets were expected to collide with the arth and change 1996 RAS

2 1408 M. Matsumoto and H. Kubotani the terrestrial ecosystem abruptly and drastically, through, for example, the nuclear winter effect, the greenhouse effect and/or acid rain. Alternatively, the impact might induce global volcanism (Rampino 1987) or produce a geomagnetic reversal (Muller & Morris 1986). The extraterrestrial scenario that sudden changes in the environment resulting from giant impacts from outer space periodically extinguished a great number of species through some process has been suggested as a plausible one. To verify the proposed causes of the periodicity, previous works in this field have tried to estimate the correlation between mass extinctions and (variously) peaks of the differential crater formation rate (Alvarez & Muller 1984), magnetic reversal events (Raup 1985) or the Sun's oscillation about the Galactic plane (Rampino & Stothers 1984; Schwartz & James 1984). These papers analysed cyclicity in the event proposed as a cause of the extinction, assuming that it had stationary periodicity, and compared the results with those of Raup & Sepkoski. Then, on the grounds that the periods of the two time series were nearly the same and the last events happened almost at the same time, it was concluded that the mass extinctions were certainly correlated with the suggested causes. However, this method of estimating correlations is unsatisfactory in principle. The cyclicity found in the adopted procedure simply means that the successive events tend to be centred around an ideal sequence predicted from a period and a phase position. Consider the case in which each of two time series has a large drift from the ideal events used as referential markers. f they may drift contrary to each other, we will scarcely recognize a correlation between them. Therefore, the correspondence in the period and the phase do not necessarily signify a strong correlation between them. Practically, it is not clear what we mean by the difference of the periods derived from the stationary periodicity analysis, which picks up only the time-scale of the rhythm of a series of events. For mass extinctions, Raup & Sepkoski (1986) suggested a 26-Myr periodicity. On the other hand, Alvarez & Muller found a dominant cyclicity of 28 Myr in the observed age distribution of impact craters. The difference of the periods, 2 Myr, appears to show a marked discrepancy between the time series, since 200 Myr later the total value of the delay will accumulate to one entire cycle interval, even if the initial events coincide with each other. s this argument justified? n this paper, we re-examine whether mass extinctions and crater formation rate have any correlation by using a proper statistical method. We concentrate on this particular correlation since it is the most fundamental one in the extraterrestrial scenarios. Considering that we have not yet been able to specify the cause event for the KT boundary, which has been researched most widely, it is reasonable and still significant to estimate the statistical correlation. We use the method developed by rtel (1994) to test the correlation between the point time series, since traditional methods of checking correlations between two time series do not apply to them (Stothers 1994). This paper is organized as follows. n Section 2, we explain the statistical method used to analyse the correlation between the two time series. Next, the data sets of the ages of the observed craters and the mass extinctions, which are used for our analysis, are introduced. Section 4 is devoted to reporting our results. Finally, we discuss the implications. 2 MTHOD n this section, we review the method used to analyse the correlation between two point series, {X' X 2, X 3,,x m } and {Y' Y2, Y3,,Yn}, following rtel (1994). n using this method, we must note that it does not matter which time series fits the cause or result; what is important is the number of points in each of them. The time series which contains the smaller number of points fits {xj. Therefore, when the method is applied to our work, the time series {xj and {Yj} will correspond to the mass extinctions and the peaks of the crater formation rate, respectively. We first compute D; (i = 1, 2, 3,, m), the distance of each X; from the nearest Yr Then we calculate Q; (i = 1, 2, 3,,m): D, Q=1-2 - l Dmax' (2.1) where Dmax is the maximum value of D;, that is, the half of the interval between Yj and Yj + (yj _ ) which contains x;, The values of Q; range from -1 (maximum possible distance between X; and y) to + 1 (minimum possible distance, i.e. D; = zero). The mean Q is then obtained using Q - i=1 =-. (2.2) m Recall here that m is the number of points of the series {x;}. A large value for Q means that the two series are correlated. or example, when the series {xj and {) coincide, Q = + 1. On the other hand, if the value of Q is - 1, the series {x;} avoids the series {Yj}' Q = 0 simply means that the two series have no correlation. To check the significance of the value of Q, we must estimate the probability that the observed Q can be obtained by chance. We make randomized sequences {y) by using the following replacement technique. The real time series is randomized by scrambling the intervals between Yj and Yj + ; the first and last are used as fixed endpoints and all intervals in between are rearranged using standard Monte Carlo techniques. Most properties of the randomized series are the same as those of the original one, but each {y) is located at an unexpected point because of the differences between the intervals. We repeat randomizing the series of {Yj} many times, and calculate Q every time. Those Q fo! the randomized series that equal or surpass the value of Q for the original series are indications that the original series are not correlated, in the sense that the null hypothesis that the series {xj happens with no correlation to the series {y) is not rejected. The number of these Qs, expressed in percentage, represents the 'chance' probability P. t points out how often a random series outperforms the original series in matching the observed {x;}. 3 DATA n this section, we present the data regarding mass extinctions and the formation ages of terrestrial craters. For the 1996 RAS, MNRAS 282,

3 ages of craters, we mainly use the data set of Grieve & Shoemaker (1995), which consists of 139 craters. For some craters, only an upper or lower limit is given for their ages. We exclude these ambiguous segments from the present analysis. f one divides the craters according to their ages, 68 have ages ::;; 300 Myr. This means that younger craters are better preserved than the older ones. Therefore, we restrict our attention to the events during the last 300 Myr. However, we exclude the most recent 5 Myr, since the interval has a much stronger bias towards retaining craters than the previous part. Furthermore, we also disregard those craters that have an age determination error ;?: 20 Myr in order to concentrate on the time-scale discussed by the previous works in relation to the periodicity (Section 1). n consequence, 35 craters are available for our analysis. Nowadays, several craters are recognized every year as remnants of giant impacts, and the ages of some of the craters have been re-analysed. We replace the old data with the new. The age of the Manson Crater, which was thought to be a candidate for the cause of the K!f boundary (65 Ma), has been re-estimated recently by zett et al. (1993) using the radio isotope 4 Arr Ar method. We adopt the larger age, 73.8 ± 0.15 Ma (Alvarez, Claeys & Kieffer 1995). Further, for Aragunainha Crater, we adopt the new data which were determined by Hammerschmidt & Von ngelhardt (1995) using the same method (245.5 ± 1.75 Ma). Raup & Sepkoski (1986) made a data set of extinctions of marine animal families during the past 250 Myr, and classified them by the stratigraphical stages. They judged eight of the extinction peaks in the time sequence to be significant mass extinction events and four peaks to be doubtful ones. We adopt the mass extinctions that were identified by them as being significant (Table 1). 4 RSULTS n this section, we estimate the correlation between terrestrial crater formation rate and mass extinction events, fol- Table 1. The data set of the mass extinctions adopted from Raup & Sepkoski (1984,1986). This data set shows the significant peaks of the percentage of the extinction of the marine animal families. The geological time-scale of Harland et al. (1990) is used. System and stage nd of interval ( 10 6 years ago = Ma) Tertiary, middle Miocene 10.4 Thrtiary, late ocene 35.4 Crater formation rate and mass extinctions 1409 lowing the statistical method introduced in Section 2. At first, we ignore the uncertainty of the age determination of craters. Fig. 1 shows a probability distribution of the ages of the observed impact structures during the last 300 Myr. n order for the variance of crater formation rate of the order of 10 Myr to stand out, the probability distribution has been smoothed out by a Gaussian window function whose dispersion (1' is 3.0, 4.0 or 5.0 Myr, which is ofthe same order as the duration of a comet shower.! We identify the local maxima of Fig. 1 as peaks ofthe crater formation rate; we find 15, 11 and 10 peaks in Figs l(a), (b) and (c), respectively. Following the procedure given in Section 2, the values of Q, 0.577, and 0.606, are obtained for (1'=3.0, 4.0 and 5.0 cases, respectively. The calculation of Q for randomized series is performed. The distribution of Q for (1' = 4.0, which approximates to the Gaussian distribution whose standard deviation is 0.240, is given in Fig. 2. These Qs are greater than or equal to the original Q for 24, 5 and 45 cases out of randomizations in the case of (1' = 3.0, 4.0 and 5.0 Myr, respectively. The results indicate the low probability of a chance association between the peaks of the crater formation rate and the mass extinctions; P is equal to 0.24, 0.05 or 0.45 per cent for each case. n other words, their correlation is significant. This result does not depend upon the width of the window function. We have calculated Q for the randomized series times. The Monte Carlo simulation was performed until the standard deviation of the distribution of these values converged to a single value. For (1'=4.0 Myr, these are 0.243, and for 1000, 5000 and times, respectively. Therefore, a 10 OOO-times simulation is enough for our analysis. Next we incorporate the effect of errors. The mean value of the uncertainty of the age determination in our data set is ± 3.6 Myr. t is assumed that the uncertainty has a Gaussian distribution, the deviation of which has the same value as the error. For each crater that has an age determination error, an error that is randomized (for each crater) is added to the centre age. specially for two pairs of craters (i.e. Kara and Ust-Kara), which are placed very close together and are thus believed to have been created simultaneously, the same scale of errors is added. This operation is reiterated times. The distribution of the obtained values of Q and the 'chance' probability P are shown in Figs 3 and 4, respectively. These results mean that we can still recognize the correlation between the two series with a low significance level, although the consideration. of the determination error of crater ages raises the value of the significance level; the expectation value of P, (P), is 2.97, 3.86 or 7.06 per cent for (1'=3, 4 or 5 Myr, respectively. Here we note that we have quantified the effect of determination errors of the ages; this effect cannot be conjectured from the error of Cretaceous, Maestrichtian 65.0 Cretaceous, Cenomanian 90.4 Jurasric, Tithonian Jurasric, Pliensbachian 'Triasric, Norian Permian, Dzulfian f comets in a shower crash on the arth, their ages are correlated with each other. To estimate the correlation with extinctions properly, the correlation between the comet-origin craters in a shower must be excluded. The smoothing of the cratering rate absorbs the correlation. We note that the procedure never does erase the random component in the cratering rate (e.g. asteroids), although the information regarding age is lost a little. To estimate the validity of the smoothing, we must check its dependence on the width of the window function RAS, MNRAS 282,

4 1410 M Matsumoto and H. Kubotani 0.5 "';:: 0.4 CD..c :::> CD 0.3 f!.;::; '".! 0.1 f! u c :::> 0.3 f!.g 0.2 '". 0.1 CD CJ 0 (a) 0=3.0 'V V V )V V 'V vvi v v v: v l v v: v '-1' :---.-!!...._- - - t- _._- -- H _t _ H. - : ;; L age(myr) v v j vv V i V!! :,, r ;.....-l-. ;! (b) ' t.---- _l ! :-- -- o o age(myr) (e) 0=5.0 O. 5,-r-"'T""">..,.--r1,-.-+-r-r-r-r-Tr.,,-r-.,..%,,-J-r-TL,-:-,..:."'T""">-, "';:: :::> 0.3, i '11 '1 - H. N ' M N.,,_ : : f :;; 0.1 CJ o _Uu o so age(myr) Figure 1. Smoothed-out probability distribution of the ages of the observed terrestrial impact structures during the last 300 Myr, derived from the ages presented in Grieve & Shoemaker (1995). The probability distributions (a), (b) and (c) have been smoothed out by Gaussian window functions with 3-, 4- and 5-Myr dispersions, respectively. The triangles and the arrows mark the peaks, which we identify as the peak of the crater formation rate, and the mass extinctions (Table 1), respectively. ' i the periodicity analysis. This is the result of the adoption of our method. Yabushita (1991) showed that the periodicity of crater ages depends on their diameters. He found that the small craters (D < 10 km), in contrast to the larger ones, satisfied a period ranging from 30 to 50 Myr. Prior to this Shoea.. 1.S --randomized data Gaussian distribution._-'- _.- _.- -,,- _. o L--L o 0.5 Q Figure 2. Distribution of the value of Q (solid line), which is compared with a Gaussian distribution whose dispersion is ( dashed line) o.;::; il 2.;:: 'ii is 1.5 c;; -;::; is r-,..,,..,,,,--, ,--,--'--'--'--'--'--'--'--'--' --sigma= sigma=4.0 _. _. - sigma= ; : -7-', :"., ". o 4_-A o Q Figure 3. Distribution of the value of Q for the crater age data {Yi} to which the randomized correction are added. For each crater, the correction is given to be a Gaussian random variable whose dispersion is the standard deviation of the age.. --sigma= _.!._...._ sigma=4.0 _. _. - sigma=5.0 o.;::; il 60.;: C is c;; 40 -;::; 20 is o Q1 0.1 p Figure 4. Distribution of P which corresponds to Q shown in Fig RAS, MNRAS 282,

5 maker, Wolfe & Shoemaker (1990) suggested that large craters tend to originate from the crash of comets rather than asteroids. According to the comet shower scenario, craters are necessarily composed of recursive comet showers, and asteroids may contribute to random components of the crater formation. Therefore, Yabushita's claim is worth consideration. From the point of view of our analysis, it is also significant to discuss which types of impacting bodies are more closely correlated with mass extinction events. To make this problem tractable, we investigate the dependence of the correlation on the diameter of craters, since the identification of the type of impacting bodies is still ambiguous for a considerable number of craters [see table 4 in Grieve & Shoemaker (1995)]. First, we use the data from 26 large craters, with diameters greater than or equal to 10 km. We would not perform the statistical test for the six small craters, since they are hard to preserve and their ages are confined to the last 120 Myr in our data, and we can use only three extinction events in Table 1 to evaluate Q. The values of Q and the 'chance' probability P for the large craters are and 0.20 per cent, respectively. When the uncertainty of the age of the crater is considered, the 'chance' probability P is expected to be 6.98 per cent. Here we use 0"=4.0 Myr. At least the large craters (D10 km) contribute to the strong correlation with the mass extinction. Next, we divide the crater data by the threshold of 23 km in diameter. The values of Q, P and <P) are 0.356, 9.9 and 19.0 per cent, respectively, for 17 large craters. For 18 small ones, these are 0.211, 11.5 and 18.6 per cent respectively. Here we again use 0" =4.0 Myr. No difference is found between the large and the small craters, although the degree -4-2 o 2 4 time delay a (Myr) Figure 5. The values of Q for the time series {Yj} and {Xi + a}, where a is the delay interval. Here, {Yj} and {x,} are the peaks of the crater formation rate and the mass extinction events, respectively. They are calculated to check the correlation where the incubation period is taken into account. The origin of the horizontal axis is the time when the cause of the extinction can be expected to occur. Q measures the correlation between these events and the peaks of the crater formaton rate. Crater formation rate and mass extinctions 1411 of correlation is worse than in the total data because of the smaller data set available for each of these cases. We now examine whether the mass extinctions coincide with the peaks of crater formation rate, or if they occurred some million years later. To find this out, we determined that the mass extinctions lag relative to the peak of the crater formation rate in increments of 0.1 Myr, for a total of 5 Myr. f a mass extinction tends to occur a Myr after a peak, the value of Q will be maximized when the lag is a Myr. Fig. 5 seems to indicate that the mass extinction event is delayed about 1.2 Myr from the peak of the crater formation. However, if we pay attention to the age-determination errors, the peak of the line fluctuates around the mean lag, 0.72 Myr, with a dispersion of 1.83 Myr. t shows that the effect of the impact of large bodies on mass extinctions is not delayed. f the width of this peak were narrower, then a mass extinction would have a correlation with only the peak of the crater formaton rate. This means that no body that crashes before or after the peak of the cratering rate will have an effect on the mass extinctions. This would not allow the 'comet shower' picture, in which the bombardment continues for several Myr. 5 DSCUSSON We have verified that giant impacts are indeed correlated with mass extinctions by using the statistical method of rtel (1994). t was found that these two series were correlated. Our results are not changed by the uncertainty of the crater ages. The correlation has no dependence on the diameters of the craters. n addition, we have checked the possibility of a time lag between the two series, and the result indicates that the extinctions occurred with no delay after the peaks of crater formation rate. We have used Q as a measure of the correlation between two discrete series, i.e. the peaks of the cratering rate and the mass extinction events, where one series is assumed to be the cause of the other. Whether the former series happens before or after the latter one does not reflect on the measure. ndeed, when we seek to discover which impact caused a mass extinction, the order is important. However, our statistical approach is focused on whether the eight mass extinctions were always accompanied by impacts. Therefore, we do not require a measure that is sensitive to whether a mass extinction event happened before or after the peak point of the cratering rate. There is no unique way to make a randomized time series for the purpose of comparison with the original one put to the statistical test. Stothers (1994) recommended a Poisson process for the time series which corresponds to peaks of the crater formation rate. n our case, however, previous works reported that the series {xj and {y) have almost the same periodicity. Hence, if the series {y) is assumed to be a Poisson process, the Monte Carlo simulation will reduce only to the analysis of the periodicity of this series. This is why we have used the method of randomization adopted by rtel (1994). rrors in the determination of the ages of craters are critical when analysing the uniform periodicity of giant impacts. Grieve et al. (1985) showed that the possible period ranged from 10 to 35 Myr, when dating errors were included in their analysis. The results of the analysis are very 1996 RAS, MNRAS 282,

6 1412 M Matsumoto and H Kubotani sensitive to errors. Further, it has also been emphasized that a large uncertainty makes it impossible to distinguish genuine periodic events from apparent ones, and that in order to fix a period, the time series analysis needs an error of less than 10 per cent of the observed period (Grieve et al. 1987; Heisler & Tremaine 1989). However, we are only concerned with the correlation of craters and another time series. The uncertainty affects the detection of correlation less severely than it affects the detection of uniform periodicity, since as far as the correlation is concerned, the degree of relative neighbourhood (D;) rather than the age itself is of vital importance. Further, recently, the 4()ArrAr isotope method has been developed (York, Hall & Hanes 1981), and as a result we can routinely determine the age of a very small amount of sample (;51 mg) with low systematic error. The use of the more recent data has also reduced the ambiguity of the results of our analysis. Therefore, we could apply the correlation analysis to the impact crater data in question. Finally, we would like to remark that we can use only 35 crater ages due to the uncertainty of the crater age determination, although more than 150 craters had been discovered by 1994 (Hodge 1994). Therefore, the re-analysis of the ages of the craters, evaluated by the isotope agedetermination method, will be important. From a statistical point of view, the peaks of the cratering rate are well correlated with the mass extinctions. However, there remain some problems about details of the extinction process. For instance, the Chicxulub Crater, which was found a few years ago, is regarded as one of the reasons for the KT boundary (van den Bergh 1994). As for the P{T boundary, terrestrial explanations are generally accepted (rwin 1993), but Aragunainha Crater was made almost at the same time (Hammerschmidt & van ngelhardt 1995). ntensive further research is required on the direct relationship between impacts and geological boundaries. ACKNOWLDGMNTS We would like to thank Professor M. Morikawa for continuous encouragement. We also would like to thank Dr M. Abmady for his careful reading of this manuscript. HK is indebted to the Japan Society for Promotion for financial aid. This work was partly supported by Grants-in-Aid for the ncouragement of Young Scientists. RFRNCS Alvarez W., Muller R A, 1984, Nat, 308, 718 Alvarez L. W., Alvarez W., Asaro F., Michel H. V., 1980, Science, 208, 1095 Alvarez W., Claeys P., Kieffer S. W., 1995, Science, 269, 930 Bailey M.., Clube S. V. M., Napier W. M., 1990, The Origin of Comets. Pergamon Press, Oxford Davis M., Hut P., Muller R A, 1984, Nat, 308, 715 rtel S., 1994, Naturwissenschaften, 81, 308 rwin D. H., 1993, The Great Paleozoic Crisis: life and death in the Permian. Columbia Univ. Press, New York Grieve R A F., Sharpton V. L., Goodacre A K, Garvin J. B., 1985, arth Planet. Sci. Lett., 76, 1 Grieve R A F., Sharpton V. L., Goodacre A K, Rupert J. D., 1987, in Ryder G., ed., Proc. 18th Lunar and Planetary Science Conf. Cambridge Univ. Press, Cambridge, and the Lunar and Planetary nstitute, Houston, p.375 Grieve R A F., Shoemaker. W., 1995, in Gehrels T., ed., Hazards Due to Comets and Asteroids. Univ. of Arizona Press, Arizona, p. 417 Hammerschmidt K, Von ngelhardt W., 1995, Meteoritics, 30, 227 Harland W. B., Armstrong R L., Cox A V., Craig L. W., Smith A G., Smith D., 1990, A geologic time scale. Cambridge Univ. Press, Cambridge Heisler J., Tremaine S., 1989, carus, 77, 213 Hodge P., 1994, Meteorite craters and impact structures of the arth. Cambridge Univ. Press, Cambbridge Hut P., Alvarez W., lder W. P., Hansen T., Kauffman. G., Keller G., Shoemaker. M., Weissman P. R, 1987, Nat, 329, 118 zett G. A, Cobban W. A, Obradovich J. D., Kunk M. J., 1993, Science, 262, 729 Matese J. J., Whitman P. G., nnanen K A, Valtonen M. J., 1995, carus, 116, 255 Muller R A, Morris D.., 1986, Geophys. Res. Lett., 13, 1177 Rampino M. R, 1987, Nat, 327, 468 Rampino M. R, Haggerty B. M., 1995, in Gehrels T., ed., Hazards Due to Comets and Asteroids. Univ. of Arizona Press, Arizona,p.827 Rampino M. R, Stothers R B., 1984, Nat, 308, 709 Raup D. M., 1985, Nat, 314, 341 Raup D. M., Sepkoski J. J., 1984, Proc. Natl. Acad. Sci. USA, 81, 801 Raup D. M., Sepkoski J. J., 1986, Science, 231, 833 Schwartz R. D., James P. B., 1984, Nat, 308, 712 Shoemaker. M., Wolfe R F., Shoemaker C. S., 1990, in Sharpton V. L., Ward P. D., eds, Geological Soc. of America Special Paper 247, Global Catastrophes in the arth History. Geol. Soc. Am., Boulder, CO Swisher C. C. et a., 1992, Science, 257, 954 van den Bergh S., 1994, PASP, 106, 689 Whitmire D. P., Jackson A A, 1984, Nat, 308, 713 Yubashita S., 1991, MNRAS, 250, 481 York D., Hall C. M., Hanes J. A, 1981, Geophys. Res. Lett., 8, RAS, MNRAS 282,