Long-Term Studies of Vertebrate Communities

Predation in Vertebrate Communities
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mail.skylinenw.com/birthdays-for-the-dead.php How many copies would you like to buy? Cody , Jeffrey A. Add to Cart Add to Cart. Add to Wishlist Add to Wishlist. This unique book synthesizes the ongoing long-term community ecology studies of fish, amphibians, reptiles, birds, and mammals. We also reconstructed diversity patterns using an alternative, and recently proposed 30 , maximum-likelihood-based richness estimator, TRiPS.

For regional unstandardized samples of palaeogeographic spread, TRiPS recovers a pattern very similar to that observed for raw richness, although confidence intervals reveal high levels of uncertainty for many richness estimates Fig. Bonferroni corrections for multiple comparisons modify our threshold for statistical significance to 0.

However, this correction is not conservative in the context of our analyses, which test the hypothesis that diversity changed little through the Mesozoic. Furthermore, corrections for multiple comparisons are now widely disfavoured because they reduce statistical power 58 , and we do not consider them to be appropriate. The distribution of pooled Mesozoic samples Fig.

Very few diversity estimates are available from lower- and higher-latitude fossil localities 59 , as also appears to be the case for the Phanerozoic marine invertebrate record The situation is even more acute when latitudinal patterns of diversity are assessed for single time slices, because only a few intervals Tr1, Tr4, K7 and K8 provide diversity estimates from more than one palaeolatitude. These data points provide weak evidence for slightly lower diversity at higher latitudes compared to low latitudes.

Higher diversity at lower latitudes has been reported for Triassic pseudosuchians the total-group of Crocodylia Relationship between absolute palaeolatitude and species richness or sampling intensity for Mesozoic-early Palaeogene non-marine, non-flying tetrapods, estimated from spatially standardized samples of fossil localities. Thick error bars represent palaeolatitudinal interquartile range of spatial subsample; thin lines represent total latitudinal range. Dotted blue lines connect regions within time intervals. Data points associated with fewer than 20 references shown in grey.

Colours distinguish continental regions, which are defined in Supplementary Table 1. The apparent temperate-latitude peak in Mesozoic tetrapod diversity reported by ref. These patterns strongly support bounded diversification in the Mesozoic, followed by explosive diversification after the mass extinction, during which terrestrial tetrapod diversity increased rapidly to a new and substantially higher equilibrium level consistent with the notion of a time-varying equilibrial diversity value 14 , 15 , Results are implicitly presented as estimates of gamma diversity either global, continental or regional-scale , but in fact represent arbitrary points on a species-area curve, and may fall substantially below the desired spatial scale.

This approach will yield reliable estimates of gamma diversity only when spatial sampling is uniformly high, or when it closely tracks changes in habitable area which may vary due to Earth system processes, most notably continental flooding induced by sea-level change. Sample-standardization tools such as SQS and TRiPS cannot correct for systematic differences in the geographic scope of the sampling universe introduced by such unequal comparisons.

Standardizing the palaeogeographic spread of fossil localities before estimating taxon richness reduces the confounding effect of variable spatial sampling through time and between geographic regions. However, they do represent approximately comparable points on the species-area curve, thus permitting fair comparisons of species richness, and how it varies through time and space. Our analyses were performed on a global fossil occurrence data set.

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The woodlands are important to a number of threatened ground cover species including the Yass daisy. Standardizing palaeogeographic spread Geographic sampling in fossil occurrence data sets has been quantified in a variety of ways. The author of this summary is the project coordinator, who is responsible for the content of this summary. Average Review. Due to the occurrence-level structure of the PaleoDB, we used occurrence-based subsampling, which defines singletons as taxa found only in one collection. The kowari: Saving a central Australian micro-predator Wed, 05 Jun Cody Editor , Jeffrey A.

Nevertheless, our geographic standardization procedure provides diversity estimates at regional sub-continental scales, which are more appropriate than global scales for studying phenomena such as diversity-dependence. Although regional and global diversities must be linked, regional diversities may sum to global diversities differently as continents fragment over geological time, as occurred in the Mesozoic Our evidence for essentially flat regional diversity patterns does not therefore preclude an overall increase in global diversity through time.

Here, and elsewhere 8 , we find a strong correlation between the geographic spread of fossil localities and both raw and subsampled estimates of tetrapod species richness. This closely mirrors patterns documented for marine invertebrates 25 , 32 , Temporal variability in spatial sampling may prove to be intimately linked to macrostratigraphic biases such as the area or volume of rock available for sampling, which have long been suspected to control raw taxon counts observed in the fossil record 25 , 50 , 51 , 63 , Raw genus diversity for all terrestrial organisms correlates strongly with terrestrial outcrop area through the Phanerozoic 6 , and outcrop area strongly predicts taxon counts, as well as counts of both fossil collections and geological formations Some of these observations were originally made by Raup 25 in pioneering research into biases on fossil record estimates of biodiversity through time.

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They suggest that changes in rock volume or outcrop area from each time interval could be driving changes in observed diversity, biasing the fossil record, and obscuring actual patterns of ancient biodiversity. It is unlikely that the relationship between outcrop area and fossil taxon counts result from a common cause mechanism on land. However, fluctuations in spatial sampling do not track trends in actual habitable area.

This was demonstrated by Wall et al. Our data also shows no correlation between the palaeogeographic spread of fossil localities and original landmass area Fig. Both results favour a record bias explanation, and underscore the need to directly account for variable spatial sampling when reconstructing diversity patterns in the fossil record contra refs 4 , Our equal-spread subsampled diversity estimates demonstrate that correcting for spatial biases can yield flatter diversity trajectories relative to uncorrected data.

However, we anticipate that studies of diversity in deep time will increasingly focus on quantifying species-area relationships 32 , 36 , 37 , 38 , 39 , 67 —which encode information about patterns of alpha, beta and gamma diversity—and how they vary through time and space. This approach will provide rich new insights about the history of biodiversity on our planet. Relationship between regional-level palaeogeographic spread all data points as quantified by summed MST length and continental land area through time.

Continental land-area values derived from ref. To enable direct comparison with earlier work, we used the Triassic—early Palaeogene Ypresian tetrapod fossil occurrence data analysed by Benson et al. Carrano, J. Alroy, R. Butler, P. Mannion, R. Benson, A. Rees, W. Kiessling, M. Clapham, F. Fursich, M. Aberhan and M. Data preparation and analysis were performed in R 3. Data were cleaned by removing the following: occurrences that were generically indeterminate; wastebasket taxa; marine tetrapods; and both oo- and ichnotaxa eggs and footprints.

Occurrences with soft-tissue preservation were excluded, as spatiotemporally restricted modes of preservation can bias coverage-based subsampling methods Flying taxa pterosaurs, birds and bats were likewise excluded, as their fossil records are dominated by these exceptional modes of preservation 68 , We restricted our analyses to occurrences dating from the start of the Triassic to the end of the Ypresian, an interval for which records of non-marine, non-flying tetrapods in the PaleoDB were recently and comprehensively vetted 8. There is no significant trend in-bin durations Supplementary Fig.

Bins Tr2, Tr5, J2—J5 and K2—K6 were excluded from the equal-spread analyses as regional-level, variable-spread subsampled diversity estimates could not be obtained for these intervals. The ubiquity of sampling biases in the fossil record largely prohibits literal interpretation of raw in-bin taxon counts.

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Sampling standardization is therefore necessary to correct for uneven sampling intensity. In contrast to classical rarefaction, which draws equal but not necessarily fair subsamples of each sampling pool, and is known to flatten diversity curves by underestimating the diversity in richer pools, SQS subsamples fairly, by drawing occurrences that represent a fixed portion or coverage sum of proportional frequencies of taxa in each sample of the underlying species-abundance distribution, determined by the quorum level.

SQS is a non-parametric approach that makes fewer assumptions about sampling distributions than TRiPs, a recent parametric approach that calculates maximum-likelihood estimates of underlying richness by modelling fossil sampling as a Poisson process For comparative purposes, however, results were also calculated using TRiPS, both for variable and equal levels of palaeogeographic spread. Due to the occurrence-level structure of the PaleoDB, we used occurrence-based subsampling, which defines singletons as taxa found only in one collection.

In each subsampling trial, all occurrences within each collection were drawn.

Only occurrences falling entirely within a bin were used to calculate subsampled diversity for that bin. A quorum level of 0. Geographic sampling in fossil occurrence data sets has been quantified in a variety of ways. Commonly used metrics include the total area enclosed by a convex hull defined by the outermost spatial points for example by refs 32 , 36 , 37 , 67 , 72 , maximum great-circle distance the standard metric for studies that seek to estimate geographic range-sizes for taxa from fossil occurrence data; for example, by refs 73 , 74 , 75 , mean or median pairwise great-circle distances 29 , 72 and counts of grid cells from which fossil occurrences have been found for example, refs 23 , 29 , 33 , 74 , 75 , 76 , 77 , To the best of our knowledge, no study has rigorously evaluated differences in the behaviour or performance of these different metrics and, with certain exceptions for example, ref.

Fossil localities consist of point-pattern data that are aggregated, to varying degrees, over a wide range of spatial scales.

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Summarizing information about their distribution using single univariate metrics is therefore challenging: should we be principally concerned with the total extent, dispersion, density or completeness of coverage, or clustering of points? Commonly used spatial sampling metrics each emphasize different components of the distribution of fossil localities; some emphasize ranges, others dispersion or density of coverage, and differ in their sensitivity to outliers and sampling intensity see Supplementary Methods for more detailed discussion.

In fact, it is not possible to summarize all desirable information about geographic coverage using a single univariate statistic; nor is it usually possible to standardize spatial samples over all distributional aspects simultaneously. For this reason, we chose to use an alternative measure of palaeogeographic spread that represents a good compromise between commonly used metrics 8 , 29 : summed MST length. MSTs the minimum length of segments that can connect a set of points have been used for decades to cluster various types of data based on pairwise distances Summed MST length was first proposed by ref.

This is important, as our metric should be an informative proxy for the size of the geographic sampling universe, which plays a major role in dictating the size of the underlying taxon pool available for estimating diversity in deep time. A closely related metric, the minimum total path-length between point localities, has also been applied to point-source ecological census data in a macroecological context Supplementary Fig. Summed MST length thus represents a good compromise between other metrics, which captures a combined signal of spatial coverage, dispersion and total extent.

MSTs are also algorithmically advantageous for constructing spatial samples using point data. The measure of geographic spread obtained from an MST may be partly sensitive to the number of sites sampled. To a certain extent, this is desirable, as it captures a signal of the coverage of localities within the study region and accounts for the closer correlation with counts of occupied grid cells. Although grid cells formed by equidistant lines of latitude and longitude do not result in perfectly uniform cell areas along latitudinal gradients although often used; for example, refs 20 , 23 , 29 , 76 , 77 , the vast majority of collections lie at palaeotemperate latitudes, and thus the procedure has a very limited impact on our results compared to the absolute total length of each MST.

To obtain standardized spatial samples of fossil localities, long branches representing intercontinental and interregional connections were removed from the global MST by 1 iteratively removing the longest branch, 2 calculating the individual summed MST lengths of the remaining subtrees and 3 dropping any subtrees smaller than the size specified for equal-spread subsampling. Any remaining branches that crossed biogeographic barriers were manually removed and subtrees below the target size dropped.

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From each of these subtrees, we drew 20 replicate subsamples of fossil localities, each having approximately equal summed MST length. This was achieved by progressively growing each spatial sample from a random starting locality until the target MST length had been achieved. The MST length chosen for standardizing spread must be large enough that each spatial sample contains sufficient occurrences to enable SQS subsampling at acceptable quorum levels.

However, larger spreads tend to be more spatially uneven with respect to the distribution of localities within samples for example, aggregation or discontinuities , and many important fossil-bearing regions have palaeogeographic spreads that may not meet larger target sizes.

Other sizes did not always return subsampled diversity estimates for all informative regions within Tr4, J6 and Pg1. Because of the nature of fossil locality data, which consists of discrete, often unevenly distributed spatial points, it is not possible to achieve perfectly uniform spatial subsamples. Our objective was not to achieve perfectly uniform subsamples, but reduce the variance of palaeogeographic spread among regions and time intervals.

In this regard, we succeeded not only according to the summed MST length metric, but also according to alternative metrics Supplementary Fig. The greatest reduction in variance is for summed MST length over a six-fold reduction in the coefficient of variation , but convex-hull area and maximum GCD also see a threefold reduction in variance. For comparative purposes, we also calculated subsampled diversity estimates for unstandardized spatial samples representing five separate continental regions North America, South America, Europe, Asia and Africa; regions defined in Supplementary Table 1.

Poisson regressions GLMs using a log-link function of diversity as a function of time were performed for the Mesozoic bins Tr1-K8. Because our models use the canonical log-link function appropriate for count data with a Poisson error distribution , these are log-linear regressions that model the relationship between diversity and time as an exponential function, the slope of which is an estimate of the net diversification rate inverted because time counts down towards the present.

We did not explicitly fit logistic models to the data because these are only appropriate for higher-resolution time-series data in which multiple data points provide evidence of both the increasing phase of diversity, and its subsequent static or equilibrial phase. However, because diversity-dependent models imply an initial rising phase followed by essentially static diversity, models were also run for the Mesozoic excluding bins Tr1—3.

Richness estimates are only reported for data points associated with more than 20 references, which establishes a minimum threshold for worker effort or sampling intensity in an interval or region. How to cite this article: Close, R. Controlling for the species-area effect supports constrained long-term Mesozoic terrestrial vertebrate diversification. Benton, M.

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This unique book synthesizes the ongoing long-term community ecology studies of fish, amphibians, reptiles, birds, and mammals. The studies have been. dynipalo.tk: Long-Term Studies of Vertebrate Communities: Martin L. Cody, Jeffrey A. Smallwood.

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