- Email: [email protected]
Paleoecology
P Paleoecology Thompson Webb, Brown University, RI, USA r 2013 Elsevier Inc. All rights reserved.
Glossary AMS dates Radiocarbon dates obtained by directly measuring the amount of carbon 14 in a sample by using an accelerator mass spectrometer. Bryophytes Mosses and liverworts; nonvascular plants. Cyperaceae Sedge family. Fagus grandifolia American beech trees. Late Quaternary The past 21,000 years since the last time of maximum glaciation.
Introduction Past ecosystems are a continuous creation of those who study them. What is mapped through time or reduced to time series depends on the data available and the training of those who interpret and display the data. Studies in paleoecology, therefore, are an exercise in perception and interpretation that depend, to some extent, on the sensitivity of the data in time, space, and taxonomy. The ultimate goal is to understand what occurred ecologically in the past, but this understanding can only be obtained if reliable records exist of past taxon distributions (or other components of ecosystems) that can be displayed and interpreted in informative ways. Simple time series are not enough because of the many spatial variations and processes that affect the temporal changes at a site. Geographic networks of temporally varying data are required to show how past and present taxa have varied in abundance, location, and association within and among their associated ecosystems. The focus here is on the rich data sets of Quaternary pollen and plant macrofossils that provide records of the major changes in vegetation at a variety of space and timescales. These data (see Neotoma Paleoecology Database – http:// www.neotomadb.org/) provide a valuable bridge between modern ecological data and the fossil evidence in the Paleobiology Database, which paleontologists are compiling. The Quaternary data sets yield a remotely sensed view of past vegetation, landscapes, taxon migrations, and invasions and illustrate various temporal changes in ecological assemblages and communities (Huntley and Birks, 1983; Williams et al., 2004; Binney et al., 2009) – all of which show changes and patterns in biodiversity. Direct measurement of the changing
Encyclopedia of Biodiversity, Volume 5
Palynology The study of pollen and spores. Pliocene The period of geological time from 3.5 to 1.8 Ma. Quaternary The past 1.8 My of geological time. Radiocarbon dates Dates of organic matter in geological samples using the radioactive decay of carbon 14, which has a half-life of 5750 years. Tracheophytes Vascular plants.
numbers of species through time, however, is not always possible with pollen data, even when supplemented by plant macrofossil data, although the extinction and arrival of some species are evident in records dating back to the Pliocene (Hoogheimstra and Ran, 1994). The focus with these paleoecological data, therefore, is on vegetation and its diverse changing patterns of composition and distribution through time and space and how environmental factors, such as climate, disease, fire, and human activities, have influenced these changes. Other types of data such as ground-penetrating radar records, sediment characteristics, diatoms, ostracodes, and various geochemical measures allow independent interpretations of past environmental changes and thus permit the pollen and plant macrofossil data to show the taxon-level and vegetational response to these past environmental changes (Shuman et al., 2002, 2004). The combinations of data sets illustrate the ecological and environmental setting within which modern patterns of biodiversity have arisen. They also demonstrate, as long claimed by Richard West and Margaret Davis, that the ‘‘present plant communities have no long history.’’
Data and Sensing System Just as satellite-derived vegetation data today can be displayed in time series of maps, the pollen and plant macrofossil data can be viewed as if they came from a video recorder from high in space with resolution in places of up to 10 m. The images that are retrieved can be of high or low resolution temporally, spatially, taxonomically, and numerically, and they can illustrate local to global changes in plant populations, vegetation,
http://dx.doi.org/10.1016/B978-0-12-384719-5.00102-7
645
646
Paleoecology
biodiversity, human activity, fire frequency, and plant diseases over decades to millions of years. Because each of these entities or phenomena varies spatially and temporally, records of data covering a breadth of scales in space and time are needed. To obtain the highest quality images of a specific phenomenon requires an understanding of the sensing system that accumulated the data. How does the paleoecological videorecording system work and what are the scaling characteristics of the images that it registers? These characteristics include breadth of coverage, sampling resolution, and sampling density in time, space, and taxonomy. Studies of pollen and plant macrofossil data covering a variety of temporal and spatial scales within the Quaternary have helped provide this understanding. Quaternary paleovegetation data pose several problems for interpretation. The main problem arises because pollen samples in sediments represent death assemblages of immature microgametophytes (i.e., pollen grains) that differ manifestly from the assemblages of sporophytes (i.e., plants) that produced the pollen. Studies of modern data from surface sediments have therefore focused on identifying the features of plant assemblages that appear in pollen records. This work parallels ground-truthing studies by scientists deciphering the remotely sensed data from satellites because pollen data are a form of remotely sensed data from plant populations and vegetation. Just as the current vegetation emits or reflects radiation that remote sensors on satellites intercept, so too does (and has) the current (and past) vegetation shed pollen that accumulates remotely (i.e., well away from the source) in lakes and bogs. Both types of remote sensors (satellite instruments and lake sediments) record data with certain sampling characteristics (e.g., spatial and temporal resolution), and their data need calibration and ground-truthing in terms of vegetation attributes such as composition (taxon abundances), structure (height and mixture of growth forms), and pattern (geographic gradients and mosaics and aspect of beta and gamma diversity). Studies of spatial arrays of modern data by Bradshaw, Prentice, Hicks, Calcote, and Jackson have provided this calibration and ground-truthing. Down-core studies of pollen bring time into the picture, and temporal resolution becomes one of the factors controlling what is recorded in the data. Pollen in annually laminated sediments can provide seasonally distinct samples as neatly shown by Peglar et al. (1984), but most samples integrate 10 or more years and can be independently dated back 40,000 years with an average precision of 7200 years for data from within the past 12,000 years. However, if vegetational and ecological phenomena are the target for study, then spatially distributed data are needed because vegetation and biodiversity are inherently spatial entities that vary on virtually all time and space scales. Recording their full dynamics requires time series of geographically distributed data that yield a zoom lens space–time perspective. The author focuses on how the different scaling characteristics of the data sets control what we see and on how data can be organized to yield such a zoom lens perspective. The author discusses each of the sampling characteristics in taxonomy, space, and time. The author then describes different ways to display and visualize the data and some of the vegetational dynamics that they have revealed.
Scaling Factors Most Quaternary palynologists obtain their data from sediments from lakes, mires, or estuaries where (1) sediments and pollen grains accumulate relatively continuously, (2) the sediments are organic enough for radiometric dating, and (3) the pollen data blow or wash in from the surrounding vegetation. In these sediments, pollen grains are morphologically distinct and numerous, and plant macrofossils are often found. (Pollen and plant macrofossil data are also available from deposits that are discontinuous in time but can be organized into time series; Baker et al., 2002; Betancourt et al., 1990). Once analyzed, the data exist as point estimates of the abundance for each taxon in time series of samples at a site (or at nearby sites and middens for some discontinuous records). These time series can be expanded to transects of time series in latitude–, longitude–, or elevation–time diagrams, to networks of samples from an area for mapping, or to networks of time series, which are also time series of maps, to form a space– time box for displaying the data (Figure 1). Each of these displays illustrates different views in different dimensions of the space–time variations in the data. A zoom lens perspective can then be achieved in space, time, or both simultaneously by moving from data at a single site for a short time interval to progressively longer time series for either that site or for data on maps from increasingly larger areas. In this way, records of local succession can be seen in the broader context of longterm migrations and global climate changes. Palynologists control the ability of their data to display selected patterns in vegetation and biodiversity (both in time and in space) by making choices about the numerical aspects of their data and by choosing the temporal, spatial, and taxonomic sampling characteristics of their data. These sampling characteristics have three elements – breadth of coverage, resolution of individual samples, and sampling density – which for a photograph are comparable to its frame of reference, grain size, and number of grains (or pixels) that are exposed, respectively. The temporal and spatial breadth of the data is the total time or area covered by a data set, and the taxonomic breadth is the total set of taxonomic groups (e.g., seed plants) included. The temporal and spatial resolution of each sample is defined in terms of how much time or area is represented in each individual sample within the data set, and taxonomic resolution depends on whether the data are lumped into groups or listed at their finest level of morphological distinction. The uncertainties of radiocarbon dates and age estimates also affect temporal resolution in correlations among sites. The number of samples in time and space defines the temporal and spatial sampling density. The total number of taxa listed in a data set defines the taxonomic sampling density. Choices about these characteristics can influence what types of changes in vegetation and biodiversity appear in paleoecological times series and map sequences (Figures 1–3).
Taxonomic and Numerical Characteristics In most studies of lakes and bog sediments, the potential taxonomic breadth is Tracheophytes and Bryophytes along
Paleoecology
300
Depth (cm)
400 500 600 700 800 900
1000 1100
1200
h
As h O ak
Bi rc
Sp r
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000
Cal yr B.P.
0 100 200
Pi ne
uc
e
Pr ai rie fo G rb ra s ss es
Kirchner Marsh, Minnesota
647
20 40 60 80
20 40
20 40
20
20 40 60
20
20 40
Percent of Total Pollen Spruce (%) Sites
55
Latitude
50
30 20 10
Ice
45 40
50
40
30 20
10
0 0−10 10−20
0
20−30 30−40 40−40 > 50
35 30 18 21
6 000 years before present
Spruce (Picea)
21 k Cal yr
18 k Cal yr
15 12 9 6 3 18 10 7 3 14 Age (thousands of years before present)
0 C-14 0 Cal
No data
0 to 5%
5 to 20%
20 to 40%
>40%
14 k Cal yr
10 k Cal yr
7 k Cal yr
3 k Cal yr
0 k Cal yr
Figure 1 Pollen data in time and space. Different views from time series for multiple taxa at a single site to a single taxon (spruce) displayed either for a transect of sites in a latitude–time diagram or for a network of sites in the time series of maps from 21 k Cal yr (thousands of calendar years ago) to present. The shading on the maps indicates pollen abundances of 1–5% (light gray) and 45% (black). The white area at the top of the maps for 21, 18, 14, and 10 ka is the Laurentide ice sheet. When stacked vertically, these maps form a space–time box in which the three-dimensional contours can show the four-dimensional distribution of spruce pollen percentages in space–time.
with certain algal remains (Pediastrum) and fungal spores. When nonwetland vegetation is a primary focus, spores, algal remains, and pollen and plant macrofossils from aquatic plants are excluded from detailed study. Careful study and morphological characteristics of pollen grains determine the taxonomic resolution in samples and permit identification of genera and some species, although some grains can only be determined to the family level (e.g., Poaceae and Cyperaceae). Regional restriction of a single species, otherwise morphologically identifiable pollen only at the genus level (e.g., Fagus grandifolia within the northeastern US), can allow designation
of plant species from pollen, but plant macrofossils, if present, allow species to be identified directly. Palynology is a direct beneficiary of the ubiquity and inefficiency of wind pollination. Millions of grains are produced for every successful pollination, and some of the abundant residual reaches the sediments of lakes and bogs where the pollen grains are well preserved. Entomophilous grains are abundant in honey and on the legs of bees, but too few insects perish in lakes and bogs to leave a record that can be discerned among the overwhelming numbers of anemophilous grains. From the point of view of the remote-sensing metaphor,
648
Paleoecology
Eastern No. Am.
Oak tree percentages
Menominee Co.
Wisconsin
0
Oak pollen percentages
500 km
0
500 km
0 50
0 50
km
km
0 10
0 10
km
km
>80%
40−60%
10−20%
60−80%
20−40%
<10%
Figure 2 Zoom lens view of the mapped distributions of oak tree and pollen percentages at the scales of a subcontinent (107 km2), state (105 km2), and county (103 km2). These maps show how well pollen percentages can reflect the distribution of tree percentages. Data used in contouring at the subcontinental scale were also used in contouring at the state scale, but a different data set was used at the county scale. Modified from Solomon and Webb (1985).
wind-pollinated plants are bright lights on the landscape and little or no signal comes from the other plants. As a result of this bias, the focus is on using pollen data to record the vegetation rather than species lists. For temperate to boreal forests in which the diversity of wind-pollinated trees is greatest globally, pollen records provide a fairly direct representation of the vegetation; however, in tropical regions and deserts, the pollen records yield a much more indirect representation of the vegetation because so many species are insect-pollinated. In arid lands of southwestern North America, where lakes are rare, packrats create middens with embedded plant macrofossils that can be radiocarbon dated and identified to the species level for those plants collected (Betancourt, 2004). These records provide valuable information about arid vegetation and environments including studies of Holocene plant migration and biogeography (Lyford et al., 2004; Gray et al., 2006).
In most studies of Quaternary pollen, taxon percentages are used. Three hundred to five hundred grains are typically counted in a sample, and the counts for each taxon are divided by the total count. Because counts for individual taxa can be thought of as being binomially distributed (i.e., each grain is either taxon x or not taxon x), the percentages for multiple taxa are multinomially distributed, thus permitting direct calculation of confidence intervals. Pollen concentrations (grains cm 3 or grains g 1) are seldom used because of their dependence on sedimentation rates. When radiocarbon or stratigraphic dates allow estimation of sedimentation rates, pollen accumulation rates (grains cm–2 year–1) can be calculated, and procedures exist for calculating and potentially minimizing the confidence intervals for both pollen concentrations and accumulation rates. Pollen accumulation rates, first introduced by Margaret Davis, have proven valuable for checking the ambiguity of
Paleoecology
649
Tundra Northern Coniferous Forest Temperate Deciduous and Rain Forest Temperate Grassland
Local
Globe
Chaparral Desert Tropical Rain Forest Tropical Deciduous Forest
100 m
Tropical Scrub Forest Tropical Grassland and Savanna Mountains
35,000 km
Tundra
Oak Openings and Barrens Oak
Boreal Forest
Continent
Landscape
Prairie
Mixed Forest Deciduous Forest Prairie
Aspen-Oak
S. Coniferous Forest
15 km 4000 km
Pine Elm-Ash
Region
Northern Hardwoods Spruce-Fir Forest Prairie Oak-Hickory Forest Prairie Transition Oak-Hickory
Maple-Basswood Oak-Blackgum-Cypress Oak-Pine Beech-Maple
1000 km Figure 3 Zoom lens view of the vegetation from the scale of single site (where pollen accumulates) up to the global scale. No one view or interpretation of the vegetation is possible because the composition and gradients vary with scale and reflect climate gradients at the global and continental scales, a mixture of soil and climate gradients at the regional scale, and difference in soils and disturbance history at the landscape and local scales. Modified from Kutzbach and Webb (1991).
certain changes in pollen percentages. However, pollen accumulation rates are unsuitable when large sets of comparably sampled pollen data are required for mapping. These rates are highly sensitive to sedimentation differences within and between lakes as shown by Pennington and Davis and thus vary dramatically for nonvegetational reasons. Percentages of pollen taxa, which serve to cancel out these variations, are therefore best used in mapping studies (Figures 1–3). Many studies show that the percentages for pollen taxa represent well the relative abundance of plants on the landscape. The relationships vary with spatial scale and pollen type, and the uncertainties of these relationships add to the number of uncertainties for the pollen data when estimates of the vegetation are attempted. Finding reliable quantitative measures for plant macrofossils is much more difficult than for pollen data. Most data
are recorded in presence/absence terms or categorically, but sometimes percentages or concentrations are calculated. Local biases can make the data difficult to interpret because, for example, 1000 needles may all come from the same nearby tree.
Spatial Characteristics The breadth of coverage for sets of pollen data can be broad or fine and thus match the different scales for mapping the vegetation (Figure 3). Continental and global data sets exist (Prentice et al., 2000) along with those at regional (1000–300,000 km2) and local (10 3 km2) scales, and an embedded series of these data sets can provide a zoom lens view of past vegetation change if the sample resolution and sampling density are appropriate.
650
Paleoecology
The potential spatial resolution of individual pollen samples varies among pollen taxa depending on the dispersibility of their pollen. Pollen from taxa with large grains is dispersed less far than that with small grains. Individual pollen samples are therefore variable-area samples, with the area of vegetation contributing pollen depending on which pollen type is studied; the percentages for pine pollen, for example, represent a larger area than those for beech or maple. Such differences in sampling area among pollen types can be important for studies of local or even regional vegetation but are less important for networks of data in which the distance between samples is much larger than the average dispersal distances for the different taxa. The potential spatial resolution also depends on the basin characteristics. Key factors include the presence or absence of a canopy over the basin, the size of the water or wetland surface accumulating airborne pollen, the presence or absence of horizontal mixing of sediments within the basin, and the watershed area that supplies additional waterborne pollen to lakes. Samples from within a forest canopy accumulate most of their pollen from plants growing with 10–100 m of the coring site, and data from samples that preserve pollen are comparable spatially to vegetation data from large permanent plots in forests. In contrast, samples from lakes accumulate their pollen from distances of 100 m to 30 km. The within-canopy data have enough spatial resolution to illustrate succession within forests (Figure 4), whereas pollen data from lakes integrate across the mosaic of vegetation on landscapes and are sensitive to succession only if it is occurring across much of the pollen-source area. Bogs, mires, and shallow wetlands accumulate pollen at both regional (1 to 410 km) and local (10 m) scales because many plants grow on these wetlands. In samples within mires, pollen from local taxa can vary systematically and abruptly, whereas the pollen from regional taxa remains reasonably uniform. (This behavior of pollen percentages for regional taxa led von Post to develop pollen analysis as a method in 1916.) The spatial resolution of pollen samples, therefore, varies with pollen type within certain basin types, but selection of samples by pollen type and basin type can help keep the spatial resolution reasonably uniform. Such choices are key to seeing well with the observations afforded by sets of pollen samples. For plant macrofossils, Dunwiddie and Jackson have shown that needles and seeds in lake sediments have a spatial sampling resolution of 10–20 m, which is much finer than the distance sampled by most pollen in lakes or open wetlands. Plant macrofossils can therefore help resolve local changes at or near a site and fine-scale elevation differences (Jackson and Whitehead, 1991). Sampling schemes can use a mixture of open and canopy-covered basins, mire and lake sediments, local and regional pollen types, and plant macrofossils in order to represent different scales of spatial pattern in the vegetation. Such mixtures of data sets can show vegetation differences that reflect specific soil and elevation differences within a broader geographic data set. Mapping of plant macrofossils can also show the range of species and of haplotypes and add precision to what maps of pollen data show (Jackson et al., 1997; Binney et al., 2009; Magri et al., 2006).
The geographical sampling density for pollen data varies. To illustrate the variations in recent pollen within a basin or a forest, some studies include samples at 10 m or finer intervals along 500 m or longer transects through a basin or forest. For selected taxa, these studies show high sensitivity in the pollen data to local variations in vegetation cover and biodiversity. The variations are also evident in sets of time series from closely spaced cores in a basin (Simmons, 1993). For studies whose breadth of coverage is regions to continents (Figure 3), sets of modern data exist with average densities of 1/14 km2 in 1000 km2, 1/500 km2 in 100,000 km2, and 1/5000 km2 in 107 km2. These densities are sufficient for the contour patterns of oak pollen percentages to match the corresponding patterns of oak tree percentages at each spatial scale (Figure 2). Sets of fossil data provide less dense geographic coverage and vary in density from 1/50 km2 for the Adirondacks to 1/6000 km2 for the northern Midwest and 1/40,000 km2 for eastern North America and Europe (Gaudreau et al., 1989; Williams et al., 2004). These data sets have been used to illustrate how well pollen data represent or remotely sense spatial vegetational features such as range boundaries, ecotones, and abundance gradients (Figures 2 and 3) (Williams et al., 2004; http://www.ncdc. noaa.gov/paleo/pollen/viewer/webviewer.html). Detecting the range boundary with pollen can be difficult because of pollen transport and relatively high counting uncertainties at low pollen percentages, but Davis et al. (1991) used a data set from the Midwest with a sampling density of one sample per 1000 km2 to show that the past species limit for beech and hemlock can be identified within an area 20 km wide. For widely dispersed taxa such as oak and pine, such fine-scale resolution may not be possible, but the abundance gradients for these taxa can be used to locate ecotones at scales of 10–100 km (Figure 2).
Temporal Characteristics The time range for records from individual cores can vary from 50 years to millions of years ago (Figure 4), with the bulk of the late Quaternary cores covering 14,000 years and fewer extending back 21,000 years, the last glacial maximum. Temporal density generally correlates with time range because short cores are often taken to study short-term changes and may contain 10–20 samples for 500 years, which yields one sample per 25–50 years, whereas 200 samples in a 2-millionyear (My) record can only yield one sample per 20,000 years. Twenty to 40 samples for 10,000 years yield one sample per 250–500 years, which is typical for most cores in the data sets from eastern North American and European (Huntley and Webb, 1988). At a high level of temporal density are records from millimeter-scale sampling of peats that have yielded 1- to 5-year sampling for 50–200 years for selected times in the past, as reviewed by Turner and Peglar (1988) and Simmons (1993). One of the longest continuous records for the Quaternary is from Sabana de Bogota in Colombia and covers 1.5 My (Figure 4). This study is remarkable in having relatively high sampling density of one sample per 1000 years and shows the appearance from North America of Alnus and Quercus at 1.3
0
0
Oak
Massachusetts
Wisconsin
California
Colombia Alder
Oak 0
0
4
4
Oak
Pine 0.0
Pine
Hemlock
Chestnut
Beech
0.000
25
Age (103 yr before present)
0.5 0.075
50
500
1.0
75 10
10 100
0.150 1.5
1000 125
14
14
0.225 2.0
150
175
1500 20 40 60
19 20 40 60 80
19 20 40 60
2.5 20 40 20 40 60 Percent of total pollen
0.300 20 40 60
20 40 60
20 40 60 80 20 40 60
Paleoecology
Figure 4 Zoom lens view of pollen data in time from a 1.5-My record down to a 300-year record. Different ecological processes are evident on different timescales. Temporal coverage, resolution, and density all vary appropriately for the Colombian lake record of alder pollen to show (a) alder’s arrival at the site long after North and South America joined and (b) its response to orbitally driven climate changes (Hoogheimstra and Ran, 1994). The California lake record of oak pollen shows its response to orbitally driven climate variations over 130,000 years and the transition from glacial to interglacial climate over 16,000 years. In Wisconsin, pollen data from a lake that is free from bottom-organism mixing are sufficiently high in resolution to record how oak and pine populations responded to climate and regional disturbance events (e.g., fire) over 11,000 and 2500 years, respectively. Local succession is evident in the pollen data from a 300-year record from a small hollow within the forest canopy in Massachusetts (Foster and Zebryk, 1993). Gray indicates a portion of a time series that is expanded in the graph on the right.
651
652
Paleoecology
million and 250,000 years ago, respectively. Other long cores with records of 50,000 years or longer exist on all continents but Antarctica; however, only in Europe are these long cores numerous enough to allow some mapping of vegetation from previous glacial and interglacial periods. At the other extreme in terms of temporal coverage are (1) short cores of the upper sediments of lakes or bogs and (2) cores from forest soils that preserve pollen. The former provide records of human impact on the vegetation and of recent changes, whereas the latter show combined fine-scale sampling in both time and space and provide the view most closely approximating scale within which succession into forest gaps occurs. One of the ironies of paleoecological research is how seldom the data reveal succession as the dominant dynamic in the vegetation even though much ecological research has focused on succession. These short-term records are often analyzed in high temporal density, for example, one sample per 50 years or even one per decade. The short cores (50 cm to 2 m) from lakes give coverage in high detail for 100–500 years or more in transects or in networks of relatively high spatial density (one sample per 1000 km2) from states or regions (Russell et al., 1993; Foster and Aber, 2006). Dating can be fairly accurate and precise because historical dates can be assigned to events in cores, and the date for the core top is usually known. Highresolution mapping in 50-year intervals is possible.
Temporal Resolution A key metaphor for thinking about temporal resolution within individual samples and cores is to consider stratigraphic sections of lake sediments as strip charts along which pollen data have accumulated to form palygraphs. The sediment accumulation rate (which varies but averages 0.7 mm per year in most Holocene lakes) measures the drum speed (as on a thermograph) that drives the strip chart past the recorder, and the mixing of sediments between one and a few cm of the sediment surface after burial measures the degree to which the pen recording the data wiggles up and down vertically in time while registering horizontally the changing abundances of pollen. Within this sediment mixing zone, older sediments are moved both up from below (2–6 cm) and in from other parts of the basin by reworking. Such processes can make for tricky pen work on the palygraph. If the paper in the imagined palygraph were to absorb the ink slowly such that the scatter of tracings in the upper mixed zone is reduced to a single tracing of the abundances below this zone, then our metaphorical instrument would yield what is finally observed downcore. This image of the palygraph helps by indicating the separate components controlling temporal resolution in a core. The mixing depth and sedimentation rate largely control postdepositional time averaging, which regulates the time interval (i.e., temporal resolution) represented by pollen in a sample, whereas the temporal density of samples recorded and the accuracy and precision of assigning dates to each of many cores (strip charts) control analytical time averaging, which determines the temporal resolution among a set of cores used for mapping.
Dating Uncertainties The dating uncertainty of an arbitrary pollen sample at some depth in a core depends on the uncertainties of the dating method, what is dated, the uncertainties of the age model, and variations in the sediment accumulation rate. The most accurate and precise dates are from lakes with annually laminated sediments, whose annual layers can be counted. These dates are in calendar years and accurate, with dating errors of only 1% or 2% at most. Unfortunately, lakes with such precision are too sparsely distributed for detailed mapping work. For lakes without varves, the dating near the tops of cores is more accurate and precise than that lower in the core because historical dates can be assigned to events in the core. These dates have uncertainties of 50 years or less and can be pinpointed in the core to 1 or 2 cm. In studies of Late Quaternary data, most cores have been dated by conventional radiocarbon dates of bulk sediments. The bulk dates give the dates for the sediment matrix (i.e., strip chart material) and not for the pollen embedded within the sediments (i.e., what the pen records). The bulk dates have counting uncertainties of 20–400 years, with most approximately 100 years. These average errors give 7200 years as the 95% confidence interval for each date. The dates can also be derived from 2 to 10 cm of sediment and therefore may average sediments covering 20–1000 years in age depending on the sediment accumulation rate. When dates for synchronous pollen events are averaged, such as the elm decline in Europe and the hemlock decline in eastern North America, standard deviations of ca. 300 years result. This uncertainty incorporates both the depth and the counting uncertainties. As Olsson (1986) observed, ‘‘There is y no point in determining the radiocarbon age with an uncertainty of 750 years if the relevant pollenanalytical level has an uncertainty of 7200 years.’’ Olsson (1986) and Grimm et al. (2009) also note the problems with contamination, old carbon, and sampling depths. Old carbon can lead to systematic errors of 2000 or more years and requires correction. Dates on wood and accelerator mass spectrometer (AMS) dates on macrofossils in cores are helping to reduce these errors, and AMS radiocarbon dates are allowing depth intervals of 1 cm or less to be dated. Pilcher (1993) concludes that standard errors for radiocarbon dates from sediments are potentially 7200 years but not more than 7225 years. Recent work using many AMS radiocarbon dates on selected macrofossils and wiggle matching can lower this uncertainty however, and holds much promise for studying century-scale phenomena (see Hormes et al., 2009).
Age Models and Mapping Intervals Most pollen samples (30–50 per core) are not dated directly by a radiocarbon date (3–6 per core). Rather, their age is estimated by an age model based on linear interpretation, regression, or some other curve-fitting method. For cores with continuous sedimentation, the age model estimates the drum speed for the strip chart on the palygraph. The uncertainties for all data plotted on the map for 12,000 years ago give an estimate for the amount of time before and after 12,000 years ago that the pollen data may cover on the
Paleoecology
map. The uncertainties are likely to be between 300 and 500 years. This dating uncertainty for the data mapped matches the average temporal sampling density of one sample per 300–500 years in Late Quaternary pollen studies. Given such large uncertainties, maps to-date are best restricted to 1000-year intervals. Attempts to map at finer intervals will only produce maps whose data are not independently observed from the data in the maps for the next earlier and later dates. As more studies get done at higher temporal resolution and with greater sampling interval, mapping can be attempted at finer time intervals. For sets of short cores in which historical dates yield a precision of 50 years or less, age models back to 500 years can yield dating sufficiently precise for maps in 100to 50-year intervals. For regions over which stratigraphic markers such as volcanic ash represent synchronous layers in cores, some fine-scale mapping intervals are possible for the distant past, but even the dating of tephras has uncertainties of a century or more. Pollen-assemblage zones are sometimes used chronostratigraphically and can yield temporal resolution to 50 years or less among nearby cores, but synchroneity must be assumed for processes (e.g., abundances changes for individual taxa) that are ultimately time transgressive, especially at scales of 200 km or more. The geographic area for maps at a fine time resolution is therefore relatively small, but may be enlarged as more studies like that by Hormes et al. (2009) are completed.
Zoom Lens Perspective Time series and mapped networks of pollen and plant macrofossils record Late Quaternary vegetation patterns at the scale of local vegetation, landscapes, regions, and continents (Figures 1–4). A hierarchy of nested data sets can reveal vegetation patterns at a variety of scales and provide information from general to detailed about the spatial vegetation patterns (Figures 2 and 3). Such hierarchies can link local changes to global events by recording each simultaneously (Kutzbach and Webb, 1991). A paleoecological zoom lens can then be used to examine the vegetation patterns that dominate different spatial scales for areas of 100–107 km2 with a spatial resolution of 10–2–104 km over timescales covering 10–104 years (with time series to 106 years) with resolution from 1 to 500 years (Figure 4). From a global perspective over thousands of years with a relatively coarse grid of temporally and spatially averaged samples, investigators can zoom in ultimately to the locally small but statistically significant short-term changes in species abundances within one wetland or forest stand. A zoom lens perspective is possible for eastern North America and Europe and is becoming possible in western North America and other regions. Two examples using current data illustrate this zoom lens view. The first holds time relatively constant and focuses up spatially from local to continental (Figures 1–3), and the second zooms in from a 1-My timescale down to successional changes during the past 300 years (Figure 4). The first example covers the past 21,000 years since the last glacial maximum in the northern Midwest and focuses up from a local to a continental perspective. It shows how the local changes in a wetland during the past 12,000 years in central Minnesota are
653
part of regional climate changes that ultimately reflect the global climate changes during deglaciation and the current interglacial period. At the local scale of the sampling basin, plant macrofossils, aquatic pollen, and diatoms at Kirchner Marsh in east-central Minnesota illustrate that 3000 years after the Laurentide ice sheet retreated from the sites ca. 19,000 years ago, a buried ice block melted to form the kettle basin and its associated lake (Kutzbach and Webb, 1991). Water levels were high until approximately 11,000 years ago when the seeds of damp ground and weedy annuals began appearing in the core (Watts and Winter, 1966). These appeared when the mixture of oak and herb pollen data show the first evidence of oak savanna conditions within the landscape and region near the site (Figure 1). When the herb pollen values increased sufficiently to indicate prairie vegetation near the site, large fluctuations in aquatic seeds indicated intermittent droughts that continued until a marsh developed at the site 2000 years ago. This history of local wetland development is closely linked to the vegetation and climate changes indicated at the landscape, regional, and continental levels (Figures 1–3). Here, there is a shift from the time series view provided by local pollen and macrofossils to the continental view that the maps of pollen data provide. These show how 15,000 years ago spruce trees grew initially in a parkland that became populated with deciduous trees, first ash and then birch and oak, from 14,500 to 12,000 years ago as forests began to develop near the site for the first time (Figure 1). This early vegetation was unlike any growing today and illustrates the major compositional changes in vegetation that accompanied the major changes in climate (Williams and Jackson, 2007). The sudden decrease in spruce abundance near Kirchner Marsh 12,500 years ago reflects the general northward movement and decrease in regional and continental spruce populations as climate warmed and the ice sheet retreated. Pine populations were then invading from the east to replace the birch trees that briefly grew abundantly near the site and in the northern Midwest generally. Oak and elm populations then increased to replace the pines as the climate warmed. The regional addition of herb pollen after 11,000 years ago signals the development of savanna conditions as the climate dried and the ice sheet retreated further north. The savanna grew until prairie vegetation developed approximately 8000 years ago as the grasslands spread from the west across Minnesota and the northern Midwest. By then, the ice sheet had almost disappeared and spruce populations were beginning to grow abundantly in eastern and central Canada where the boreal forest has developed today. With the retreat westward of the prairie–forest ecotone after 6000 years ago, open oak forests began growing near the lake that with further growth in aquatic vegetation became a marsh after 2000 years ago. Oak populations then decreased regionally as part of a general retreat of oak in the north as conifer populations increased and spruce populations increased south from Canada into the northern Midwest and New England. The broad-scale regional and continental maps show how the local and landscape changes in vegetation fit within the broader context of changes. The second example is a zoom lens perspective in time (Figure 4) and shows time series for taxa reflecting the long-
654
Paleoecology
term temporal beat in climate at long time scales (1.5 My to 16,000 years) but then shifting to reflect fires, disease, and other disturbances at shorter timescales, especially when the pollen data are derived from within a forested hollow. Within the latter, the pollen reflects local changes in trees next to the site. This arrangement and description of the data allow paleoecologists to zoom in or out in space–time to observe different aspects of vegetation dynamics and patterns of biodiversity from long-term changes on several spatial scales (from continental to inside the forest canopy) to competitive interactions after disturbance within communities. With such an ordering of data and images, the interconnected roles and impacts of climate change, disturbance, disease, succession, soil development, competition, and evolution can all be observed and potentially distinguished from one another in studies of past biodiversity. To this end, recent studies of sediment records are including data on charcoal, sediments, biomarkers, isotopes, biogeochemistry, and plankton that provide evidence for environmental changes from fires to climate that can be used to help interpret the changes in the vegetation (Whitlock et al., 2003; Webb et al., 2003). Mapping and studying pollen and plant macrofossil data in space–time have been convincing of the potential for resolving many different views of the past. No single fixed picture is possible because there is no preferred viewing scale or perspective, nor is there any one way to describe the vegetation and biodiversity. Many conventional displays and perspectives are used, but some, such as traditional pollen diagrams, may not be optimal for interpreting key variations in the vegetation. A zoom lens perspective in space and time is required to help explore all the possibilities and to allow for diverse narratives and explanations. Succession and patch dynamics are evident with data scaled to meters and decades, whereas climatically induced migrations and abundance changes appear best over thousands of kilometers and years. To zoom out from a local to a global view, the paleoecological data need to be organized so that highly resolved images of species near a site give way to more generalized averages of data values whose patterns will stand out sharply when viewed across continents or the world. Appropriate study of assembled databases should allow ecologists to resolve and perceive a variety of phenomena, such as ecotones, disturbance horizons, species distributions, and migration patterns, that are important for biodiversity.
See also: Biodiversity, Evolution and. Fossil Record. Remote Sensing and Image Processing
References Baker RG, Bettis III EA, Denniston RF, Gonzalez LA, Strickland LE, and Krieg JR (2002) Holocene paleoenvironments in southeastern Minnesota – Chasing the prairie–forest ecotone. Palaeogeography Palaeoclimatology Palaeoecology 177: 103–122. Betancourt JL (2004) Arid lands paleobiogeography: The fossil rodent midden record in the Americas. In: Lomolino MV and Heaney LR (eds.) Frontiers in Biogeography: New Directions in the Geography of Nature, pp. 27–46. Sunderland, MA: Sinauer Associates Inc.
Betancourt JL, Van Devender TR, and Martin PS (eds.) (1990) Packrat Middens: The Last 40,000 Years of Biotic Change. Tucson: University of Arizona Press. Binney HA, Willis KJ, Edwards ME, et al. (2009) The distribution of late Quaternary woody taxa in northern Eurasia: Evidence from a new macrofossil database. Quaternary Science Reviews 28: 2445–2464. Davis MB, Schwartz MW, and Woods K (1991) Detecting a species limit from pollen in sediments. Journal of Biogeography 18: 653–668. Foster DR and Aber JD (eds.) (2006) Forests in Time: The Environmental Consequences of 1,000 Years of Change in New England. New Haven, CT: Yale University Press. Foster DR and Zebryk TM (1993) Long-term vegetation dynamic and disturbance history of a Tsuga-dominated forest in New England. Ecology 74: 982–998. Gaudreau DC, Jackson ST, and Webb III T (1989) The use of pollen data to record vegetational patterns in regions of moderate to high relief. Acta Botanica Nederlandica 38: 369–390. Gray ST, Betancourt JL, Jackson ST, and Eddy RG (2006) Role of multidecadal climatic variability in a range extension of pinyon pine. Ecology 87: 1124–1130. Grimm EC, Maher Jr. LJ, and Nelson DM (2009) The magnitude of error in bulk-sediment radiocarbon dates from central North America. Quaternary Research 72: 301–308. Hoogheimstra H and Ran ETH (1994) Late Pliocene–Pleistocene high resolution pollen sequence of Colombia: An overview of climatic change. Quaternary International 21: 63–80. Hormes A, Blaauw M, Dahl SO, Nesje A, and Possnert G (2009) Radiocarbon wiggle-match dating of proglacial lake sediments – implications for the 8.2 ka event. Quaternary Geochronology 4: 267–277. Huntley B and Birks HJB (1983) An Atlas of Past and Present Pollen Maps for Europe: 0–13000 Years Ago. Cambridge: Cambridge University Press. Huntley B and Webb III T (eds.) (1988) Vegetation History. Dordrecht: Kluwer. Jackson ST and Whitehead DR (1991) Holocene vegetation patterns in the Adirondack Mountains. Ecology 72: 641–653. Jackson ST, Overpeck JT, Webb III T, Keattch S, and Anderson KH (1997) Mapped plant macrofossil and pollen records of late-Quaternary vegetation change in eastern North America. Quaternary Science Review 15: 1–71. Kutzbach JE and Webb III T (1991) Late Quaternary climatic and vegetational change in eastern North America: Concepts, models, and dates. In: Shane LCK and Cushing EJ (eds.) Quaternary Landscapes, pp. 175–217. Minneapolis: University of Minnesota Press. Lyford ME, Jackson ST, Gray ST, and Eddy RJ (2004) Validating the use of woodrat (Neotoma) middens for documenting natural invasions. Journal of Biogeography 31: 333–342. Magri D, Vendramin GG, Comps B, et al. (2006) A new scenario for the Quaternary history of European beech populations: Palaeobotanical evidence and genetic consequences. Journal of Biogeography 171: 199–221. Olsson IU (1986) Radiometric dating. In: Berglund BE (ed.) Handbook of Holocene Palaeoecology and Palaeohydrology, pp. 110–120. Chichester, UK: Wiley. Paleobiology Database. http://paleodb.org/cgi-bin/bridge.pl Peglar SM, Fritz SC, Alapieti A, Saarnisto M, and Birks HJB (1984) Composition and formation of laminated sediments in Diss Mere, Norfolk, England. Boreas 13: 13–28. Pilcher JR (1993) Radiocarbon dating and the palynologist: A realistic approach to precision and accuracy. In: Chambers FM (ed.) Climate Change and Human Impact on the Landscape, pp. 23–32. London: Chapman & Hall. Prentice IC, Jolly D and BIOME 6000 participants (2000) Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa. Journal of Biography 27: 507–519. http://www.neotomads.org Russell E, Davis RB, Anderson RS, Rhodes TE, and Anderson DS (1993) Recent centuries of vegetational change in the glaciated north-eastern United States. Journal of Ecology 81: 647–664. Shuman BN, Bartlein PJ, Logar N, Newby P, and Webb III T (2002) Parallel vegetation and climate responses to the Early-Holocene collapse of the Laurentide Ice Sheet. Quaternary Science Reviews 21: 1793–1805. Shuman BN, Newby P, Huang Y, and Webb III T (2004) Evidence for the close climatic control of New England vegetation history. Ecology 85: 1297–1310. Simmons IG (1993) Vegetation change during the Mesolithic in the British Isles: Some amplifications. In: Chambers FM (ed.) Climate Change and Human Impact on the Landscape, pp. 109–118. London: Chapman & Hall. Turner J and Peglar SM (1988) Temporally precise studies of vegetation history. In: Huntley B and Webb III T (eds.) Vegetation History, pp. 753–777. Dordrecht: Kluwer.
Paleoecology
Watts WA and Winter TC (1966) Plant macrofossils from Kirchner Marsh, Minnesota – a paleoecological study. Bulletin Geological Society of America 77: 1339–1360. Webb III T, Shuman BN, and Williams JW (2003) Climatically-forced vegetation dynamics in North America during the late-Quaternary. In: Gillespie A, Porter SC, and Atwater BF (eds.) The Quaternary Period in the United States, pp. 459–478. New York: Elsevier. Williams JW and Jackson ST (2007) Novel climates, no-analog communities, and ecological surprises. Frontiers in Ecology and the Environment 5: 475–482.
655
Williams JW, Shuman BN, Webb III T, Bartlein PJ, and Leduc PL (2004) Late Quaternary vegetation dynamics in North America: Scaling from taxa to biomes. Ecological Monographs 74: 309–334. Whitlock C, Shafer SL, and Marlon J (2003) The role of climate and vegetation change in shaping past and future fire regimes in the northwestern US and the implications for ecosystem management. Forest Ecology and Management 178: 5–21.
Glossary AMS dates Radiocarbon dates obtained by directly measuring the amount of carbon 14 in a sample by using an accelerator mass spectrometer. Bryophytes Mosses and liverworts; nonvascular plants. Cyperaceae Sedge family. Fagus grandifolia American beech trees. Late Quaternary The past 21,000 years since the last time of maximum glaciation.
Introduction Past ecosystems are a continuous creation of those who study them. What is mapped through time or reduced to time series depends on the data available and the training of those who interpret and display the data. Studies in paleoecology, therefore, are an exercise in perception and interpretation that depend, to some extent, on the sensitivity of the data in time, space, and taxonomy. The ultimate goal is to understand what occurred ecologically in the past, but this understanding can only be obtained if reliable records exist of past taxon distributions (or other components of ecosystems) that can be displayed and interpreted in informative ways. Simple time series are not enough because of the many spatial variations and processes that affect the temporal changes at a site. Geographic networks of temporally varying data are required to show how past and present taxa have varied in abundance, location, and association within and among their associated ecosystems. The focus here is on the rich data sets of Quaternary pollen and plant macrofossils that provide records of the major changes in vegetation at a variety of space and timescales. These data (see Neotoma Paleoecology Database – http:// www.neotomadb.org/) provide a valuable bridge between modern ecological data and the fossil evidence in the Paleobiology Database, which paleontologists are compiling. The Quaternary data sets yield a remotely sensed view of past vegetation, landscapes, taxon migrations, and invasions and illustrate various temporal changes in ecological assemblages and communities (Huntley and Birks, 1983; Williams et al., 2004; Binney et al., 2009) – all of which show changes and patterns in biodiversity. Direct measurement of the changing
Encyclopedia of Biodiversity, Volume 5
Palynology The study of pollen and spores. Pliocene The period of geological time from 3.5 to 1.8 Ma. Quaternary The past 1.8 My of geological time. Radiocarbon dates Dates of organic matter in geological samples using the radioactive decay of carbon 14, which has a half-life of 5750 years. Tracheophytes Vascular plants.
numbers of species through time, however, is not always possible with pollen data, even when supplemented by plant macrofossil data, although the extinction and arrival of some species are evident in records dating back to the Pliocene (Hoogheimstra and Ran, 1994). The focus with these paleoecological data, therefore, is on vegetation and its diverse changing patterns of composition and distribution through time and space and how environmental factors, such as climate, disease, fire, and human activities, have influenced these changes. Other types of data such as ground-penetrating radar records, sediment characteristics, diatoms, ostracodes, and various geochemical measures allow independent interpretations of past environmental changes and thus permit the pollen and plant macrofossil data to show the taxon-level and vegetational response to these past environmental changes (Shuman et al., 2002, 2004). The combinations of data sets illustrate the ecological and environmental setting within which modern patterns of biodiversity have arisen. They also demonstrate, as long claimed by Richard West and Margaret Davis, that the ‘‘present plant communities have no long history.’’
Data and Sensing System Just as satellite-derived vegetation data today can be displayed in time series of maps, the pollen and plant macrofossil data can be viewed as if they came from a video recorder from high in space with resolution in places of up to 10 m. The images that are retrieved can be of high or low resolution temporally, spatially, taxonomically, and numerically, and they can illustrate local to global changes in plant populations, vegetation,
http://dx.doi.org/10.1016/B978-0-12-384719-5.00102-7
645
646
Paleoecology
biodiversity, human activity, fire frequency, and plant diseases over decades to millions of years. Because each of these entities or phenomena varies spatially and temporally, records of data covering a breadth of scales in space and time are needed. To obtain the highest quality images of a specific phenomenon requires an understanding of the sensing system that accumulated the data. How does the paleoecological videorecording system work and what are the scaling characteristics of the images that it registers? These characteristics include breadth of coverage, sampling resolution, and sampling density in time, space, and taxonomy. Studies of pollen and plant macrofossil data covering a variety of temporal and spatial scales within the Quaternary have helped provide this understanding. Quaternary paleovegetation data pose several problems for interpretation. The main problem arises because pollen samples in sediments represent death assemblages of immature microgametophytes (i.e., pollen grains) that differ manifestly from the assemblages of sporophytes (i.e., plants) that produced the pollen. Studies of modern data from surface sediments have therefore focused on identifying the features of plant assemblages that appear in pollen records. This work parallels ground-truthing studies by scientists deciphering the remotely sensed data from satellites because pollen data are a form of remotely sensed data from plant populations and vegetation. Just as the current vegetation emits or reflects radiation that remote sensors on satellites intercept, so too does (and has) the current (and past) vegetation shed pollen that accumulates remotely (i.e., well away from the source) in lakes and bogs. Both types of remote sensors (satellite instruments and lake sediments) record data with certain sampling characteristics (e.g., spatial and temporal resolution), and their data need calibration and ground-truthing in terms of vegetation attributes such as composition (taxon abundances), structure (height and mixture of growth forms), and pattern (geographic gradients and mosaics and aspect of beta and gamma diversity). Studies of spatial arrays of modern data by Bradshaw, Prentice, Hicks, Calcote, and Jackson have provided this calibration and ground-truthing. Down-core studies of pollen bring time into the picture, and temporal resolution becomes one of the factors controlling what is recorded in the data. Pollen in annually laminated sediments can provide seasonally distinct samples as neatly shown by Peglar et al. (1984), but most samples integrate 10 or more years and can be independently dated back 40,000 years with an average precision of 7200 years for data from within the past 12,000 years. However, if vegetational and ecological phenomena are the target for study, then spatially distributed data are needed because vegetation and biodiversity are inherently spatial entities that vary on virtually all time and space scales. Recording their full dynamics requires time series of geographically distributed data that yield a zoom lens space–time perspective. The author focuses on how the different scaling characteristics of the data sets control what we see and on how data can be organized to yield such a zoom lens perspective. The author discusses each of the sampling characteristics in taxonomy, space, and time. The author then describes different ways to display and visualize the data and some of the vegetational dynamics that they have revealed.
Scaling Factors Most Quaternary palynologists obtain their data from sediments from lakes, mires, or estuaries where (1) sediments and pollen grains accumulate relatively continuously, (2) the sediments are organic enough for radiometric dating, and (3) the pollen data blow or wash in from the surrounding vegetation. In these sediments, pollen grains are morphologically distinct and numerous, and plant macrofossils are often found. (Pollen and plant macrofossil data are also available from deposits that are discontinuous in time but can be organized into time series; Baker et al., 2002; Betancourt et al., 1990). Once analyzed, the data exist as point estimates of the abundance for each taxon in time series of samples at a site (or at nearby sites and middens for some discontinuous records). These time series can be expanded to transects of time series in latitude–, longitude–, or elevation–time diagrams, to networks of samples from an area for mapping, or to networks of time series, which are also time series of maps, to form a space– time box for displaying the data (Figure 1). Each of these displays illustrates different views in different dimensions of the space–time variations in the data. A zoom lens perspective can then be achieved in space, time, or both simultaneously by moving from data at a single site for a short time interval to progressively longer time series for either that site or for data on maps from increasingly larger areas. In this way, records of local succession can be seen in the broader context of longterm migrations and global climate changes. Palynologists control the ability of their data to display selected patterns in vegetation and biodiversity (both in time and in space) by making choices about the numerical aspects of their data and by choosing the temporal, spatial, and taxonomic sampling characteristics of their data. These sampling characteristics have three elements – breadth of coverage, resolution of individual samples, and sampling density – which for a photograph are comparable to its frame of reference, grain size, and number of grains (or pixels) that are exposed, respectively. The temporal and spatial breadth of the data is the total time or area covered by a data set, and the taxonomic breadth is the total set of taxonomic groups (e.g., seed plants) included. The temporal and spatial resolution of each sample is defined in terms of how much time or area is represented in each individual sample within the data set, and taxonomic resolution depends on whether the data are lumped into groups or listed at their finest level of morphological distinction. The uncertainties of radiocarbon dates and age estimates also affect temporal resolution in correlations among sites. The number of samples in time and space defines the temporal and spatial sampling density. The total number of taxa listed in a data set defines the taxonomic sampling density. Choices about these characteristics can influence what types of changes in vegetation and biodiversity appear in paleoecological times series and map sequences (Figures 1–3).
Taxonomic and Numerical Characteristics In most studies of lakes and bog sediments, the potential taxonomic breadth is Tracheophytes and Bryophytes along
Paleoecology
300
Depth (cm)
400 500 600 700 800 900
1000 1100
1200
h
As h O ak
Bi rc
Sp r
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000
Cal yr B.P.
0 100 200
Pi ne
uc
e
Pr ai rie fo G rb ra s ss es
Kirchner Marsh, Minnesota
647
20 40 60 80
20 40
20 40
20
20 40 60
20
20 40
Percent of Total Pollen Spruce (%) Sites
55
Latitude
50
30 20 10
Ice
45 40
50
40
30 20
10
0 0−10 10−20
0
20−30 30−40 40−40 > 50
35 30 18 21
6 000 years before present
Spruce (Picea)
21 k Cal yr
18 k Cal yr
15 12 9 6 3 18 10 7 3 14 Age (thousands of years before present)
0 C-14 0 Cal
No data
0 to 5%
5 to 20%
20 to 40%
>40%
14 k Cal yr
10 k Cal yr
7 k Cal yr
3 k Cal yr
0 k Cal yr
Figure 1 Pollen data in time and space. Different views from time series for multiple taxa at a single site to a single taxon (spruce) displayed either for a transect of sites in a latitude–time diagram or for a network of sites in the time series of maps from 21 k Cal yr (thousands of calendar years ago) to present. The shading on the maps indicates pollen abundances of 1–5% (light gray) and 45% (black). The white area at the top of the maps for 21, 18, 14, and 10 ka is the Laurentide ice sheet. When stacked vertically, these maps form a space–time box in which the three-dimensional contours can show the four-dimensional distribution of spruce pollen percentages in space–time.
with certain algal remains (Pediastrum) and fungal spores. When nonwetland vegetation is a primary focus, spores, algal remains, and pollen and plant macrofossils from aquatic plants are excluded from detailed study. Careful study and morphological characteristics of pollen grains determine the taxonomic resolution in samples and permit identification of genera and some species, although some grains can only be determined to the family level (e.g., Poaceae and Cyperaceae). Regional restriction of a single species, otherwise morphologically identifiable pollen only at the genus level (e.g., Fagus grandifolia within the northeastern US), can allow designation
of plant species from pollen, but plant macrofossils, if present, allow species to be identified directly. Palynology is a direct beneficiary of the ubiquity and inefficiency of wind pollination. Millions of grains are produced for every successful pollination, and some of the abundant residual reaches the sediments of lakes and bogs where the pollen grains are well preserved. Entomophilous grains are abundant in honey and on the legs of bees, but too few insects perish in lakes and bogs to leave a record that can be discerned among the overwhelming numbers of anemophilous grains. From the point of view of the remote-sensing metaphor,
648
Paleoecology
Eastern No. Am.
Oak tree percentages
Menominee Co.
Wisconsin
0
Oak pollen percentages
500 km
0
500 km
0 50
0 50
km
km
0 10
0 10
km
km
>80%
40−60%
10−20%
60−80%
20−40%
<10%
Figure 2 Zoom lens view of the mapped distributions of oak tree and pollen percentages at the scales of a subcontinent (107 km2), state (105 km2), and county (103 km2). These maps show how well pollen percentages can reflect the distribution of tree percentages. Data used in contouring at the subcontinental scale were also used in contouring at the state scale, but a different data set was used at the county scale. Modified from Solomon and Webb (1985).
wind-pollinated plants are bright lights on the landscape and little or no signal comes from the other plants. As a result of this bias, the focus is on using pollen data to record the vegetation rather than species lists. For temperate to boreal forests in which the diversity of wind-pollinated trees is greatest globally, pollen records provide a fairly direct representation of the vegetation; however, in tropical regions and deserts, the pollen records yield a much more indirect representation of the vegetation because so many species are insect-pollinated. In arid lands of southwestern North America, where lakes are rare, packrats create middens with embedded plant macrofossils that can be radiocarbon dated and identified to the species level for those plants collected (Betancourt, 2004). These records provide valuable information about arid vegetation and environments including studies of Holocene plant migration and biogeography (Lyford et al., 2004; Gray et al., 2006).
In most studies of Quaternary pollen, taxon percentages are used. Three hundred to five hundred grains are typically counted in a sample, and the counts for each taxon are divided by the total count. Because counts for individual taxa can be thought of as being binomially distributed (i.e., each grain is either taxon x or not taxon x), the percentages for multiple taxa are multinomially distributed, thus permitting direct calculation of confidence intervals. Pollen concentrations (grains cm 3 or grains g 1) are seldom used because of their dependence on sedimentation rates. When radiocarbon or stratigraphic dates allow estimation of sedimentation rates, pollen accumulation rates (grains cm–2 year–1) can be calculated, and procedures exist for calculating and potentially minimizing the confidence intervals for both pollen concentrations and accumulation rates. Pollen accumulation rates, first introduced by Margaret Davis, have proven valuable for checking the ambiguity of
Paleoecology
649
Tundra Northern Coniferous Forest Temperate Deciduous and Rain Forest Temperate Grassland
Local
Globe
Chaparral Desert Tropical Rain Forest Tropical Deciduous Forest
100 m
Tropical Scrub Forest Tropical Grassland and Savanna Mountains
35,000 km
Tundra
Oak Openings and Barrens Oak
Boreal Forest
Continent
Landscape
Prairie
Mixed Forest Deciduous Forest Prairie
Aspen-Oak
S. Coniferous Forest
15 km 4000 km
Pine Elm-Ash
Region
Northern Hardwoods Spruce-Fir Forest Prairie Oak-Hickory Forest Prairie Transition Oak-Hickory
Maple-Basswood Oak-Blackgum-Cypress Oak-Pine Beech-Maple
1000 km Figure 3 Zoom lens view of the vegetation from the scale of single site (where pollen accumulates) up to the global scale. No one view or interpretation of the vegetation is possible because the composition and gradients vary with scale and reflect climate gradients at the global and continental scales, a mixture of soil and climate gradients at the regional scale, and difference in soils and disturbance history at the landscape and local scales. Modified from Kutzbach and Webb (1991).
certain changes in pollen percentages. However, pollen accumulation rates are unsuitable when large sets of comparably sampled pollen data are required for mapping. These rates are highly sensitive to sedimentation differences within and between lakes as shown by Pennington and Davis and thus vary dramatically for nonvegetational reasons. Percentages of pollen taxa, which serve to cancel out these variations, are therefore best used in mapping studies (Figures 1–3). Many studies show that the percentages for pollen taxa represent well the relative abundance of plants on the landscape. The relationships vary with spatial scale and pollen type, and the uncertainties of these relationships add to the number of uncertainties for the pollen data when estimates of the vegetation are attempted. Finding reliable quantitative measures for plant macrofossils is much more difficult than for pollen data. Most data
are recorded in presence/absence terms or categorically, but sometimes percentages or concentrations are calculated. Local biases can make the data difficult to interpret because, for example, 1000 needles may all come from the same nearby tree.
Spatial Characteristics The breadth of coverage for sets of pollen data can be broad or fine and thus match the different scales for mapping the vegetation (Figure 3). Continental and global data sets exist (Prentice et al., 2000) along with those at regional (1000–300,000 km2) and local (10 3 km2) scales, and an embedded series of these data sets can provide a zoom lens view of past vegetation change if the sample resolution and sampling density are appropriate.
650
Paleoecology
The potential spatial resolution of individual pollen samples varies among pollen taxa depending on the dispersibility of their pollen. Pollen from taxa with large grains is dispersed less far than that with small grains. Individual pollen samples are therefore variable-area samples, with the area of vegetation contributing pollen depending on which pollen type is studied; the percentages for pine pollen, for example, represent a larger area than those for beech or maple. Such differences in sampling area among pollen types can be important for studies of local or even regional vegetation but are less important for networks of data in which the distance between samples is much larger than the average dispersal distances for the different taxa. The potential spatial resolution also depends on the basin characteristics. Key factors include the presence or absence of a canopy over the basin, the size of the water or wetland surface accumulating airborne pollen, the presence or absence of horizontal mixing of sediments within the basin, and the watershed area that supplies additional waterborne pollen to lakes. Samples from within a forest canopy accumulate most of their pollen from plants growing with 10–100 m of the coring site, and data from samples that preserve pollen are comparable spatially to vegetation data from large permanent plots in forests. In contrast, samples from lakes accumulate their pollen from distances of 100 m to 30 km. The within-canopy data have enough spatial resolution to illustrate succession within forests (Figure 4), whereas pollen data from lakes integrate across the mosaic of vegetation on landscapes and are sensitive to succession only if it is occurring across much of the pollen-source area. Bogs, mires, and shallow wetlands accumulate pollen at both regional (1 to 410 km) and local (10 m) scales because many plants grow on these wetlands. In samples within mires, pollen from local taxa can vary systematically and abruptly, whereas the pollen from regional taxa remains reasonably uniform. (This behavior of pollen percentages for regional taxa led von Post to develop pollen analysis as a method in 1916.) The spatial resolution of pollen samples, therefore, varies with pollen type within certain basin types, but selection of samples by pollen type and basin type can help keep the spatial resolution reasonably uniform. Such choices are key to seeing well with the observations afforded by sets of pollen samples. For plant macrofossils, Dunwiddie and Jackson have shown that needles and seeds in lake sediments have a spatial sampling resolution of 10–20 m, which is much finer than the distance sampled by most pollen in lakes or open wetlands. Plant macrofossils can therefore help resolve local changes at or near a site and fine-scale elevation differences (Jackson and Whitehead, 1991). Sampling schemes can use a mixture of open and canopy-covered basins, mire and lake sediments, local and regional pollen types, and plant macrofossils in order to represent different scales of spatial pattern in the vegetation. Such mixtures of data sets can show vegetation differences that reflect specific soil and elevation differences within a broader geographic data set. Mapping of plant macrofossils can also show the range of species and of haplotypes and add precision to what maps of pollen data show (Jackson et al., 1997; Binney et al., 2009; Magri et al., 2006).
The geographical sampling density for pollen data varies. To illustrate the variations in recent pollen within a basin or a forest, some studies include samples at 10 m or finer intervals along 500 m or longer transects through a basin or forest. For selected taxa, these studies show high sensitivity in the pollen data to local variations in vegetation cover and biodiversity. The variations are also evident in sets of time series from closely spaced cores in a basin (Simmons, 1993). For studies whose breadth of coverage is regions to continents (Figure 3), sets of modern data exist with average densities of 1/14 km2 in 1000 km2, 1/500 km2 in 100,000 km2, and 1/5000 km2 in 107 km2. These densities are sufficient for the contour patterns of oak pollen percentages to match the corresponding patterns of oak tree percentages at each spatial scale (Figure 2). Sets of fossil data provide less dense geographic coverage and vary in density from 1/50 km2 for the Adirondacks to 1/6000 km2 for the northern Midwest and 1/40,000 km2 for eastern North America and Europe (Gaudreau et al., 1989; Williams et al., 2004). These data sets have been used to illustrate how well pollen data represent or remotely sense spatial vegetational features such as range boundaries, ecotones, and abundance gradients (Figures 2 and 3) (Williams et al., 2004; http://www.ncdc. noaa.gov/paleo/pollen/viewer/webviewer.html). Detecting the range boundary with pollen can be difficult because of pollen transport and relatively high counting uncertainties at low pollen percentages, but Davis et al. (1991) used a data set from the Midwest with a sampling density of one sample per 1000 km2 to show that the past species limit for beech and hemlock can be identified within an area 20 km wide. For widely dispersed taxa such as oak and pine, such fine-scale resolution may not be possible, but the abundance gradients for these taxa can be used to locate ecotones at scales of 10–100 km (Figure 2).
Temporal Characteristics The time range for records from individual cores can vary from 50 years to millions of years ago (Figure 4), with the bulk of the late Quaternary cores covering 14,000 years and fewer extending back 21,000 years, the last glacial maximum. Temporal density generally correlates with time range because short cores are often taken to study short-term changes and may contain 10–20 samples for 500 years, which yields one sample per 25–50 years, whereas 200 samples in a 2-millionyear (My) record can only yield one sample per 20,000 years. Twenty to 40 samples for 10,000 years yield one sample per 250–500 years, which is typical for most cores in the data sets from eastern North American and European (Huntley and Webb, 1988). At a high level of temporal density are records from millimeter-scale sampling of peats that have yielded 1- to 5-year sampling for 50–200 years for selected times in the past, as reviewed by Turner and Peglar (1988) and Simmons (1993). One of the longest continuous records for the Quaternary is from Sabana de Bogota in Colombia and covers 1.5 My (Figure 4). This study is remarkable in having relatively high sampling density of one sample per 1000 years and shows the appearance from North America of Alnus and Quercus at 1.3
0
0
Oak
Massachusetts
Wisconsin
California
Colombia Alder
Oak 0
0
4
4
Oak
Pine 0.0
Pine
Hemlock
Chestnut
Beech
0.000
25
Age (103 yr before present)
0.5 0.075
50
500
1.0
75 10
10 100
0.150 1.5
1000 125
14
14
0.225 2.0
150
175
1500 20 40 60
19 20 40 60 80
19 20 40 60
2.5 20 40 20 40 60 Percent of total pollen
0.300 20 40 60
20 40 60
20 40 60 80 20 40 60
Paleoecology
Figure 4 Zoom lens view of pollen data in time from a 1.5-My record down to a 300-year record. Different ecological processes are evident on different timescales. Temporal coverage, resolution, and density all vary appropriately for the Colombian lake record of alder pollen to show (a) alder’s arrival at the site long after North and South America joined and (b) its response to orbitally driven climate changes (Hoogheimstra and Ran, 1994). The California lake record of oak pollen shows its response to orbitally driven climate variations over 130,000 years and the transition from glacial to interglacial climate over 16,000 years. In Wisconsin, pollen data from a lake that is free from bottom-organism mixing are sufficiently high in resolution to record how oak and pine populations responded to climate and regional disturbance events (e.g., fire) over 11,000 and 2500 years, respectively. Local succession is evident in the pollen data from a 300-year record from a small hollow within the forest canopy in Massachusetts (Foster and Zebryk, 1993). Gray indicates a portion of a time series that is expanded in the graph on the right.
651
652
Paleoecology
million and 250,000 years ago, respectively. Other long cores with records of 50,000 years or longer exist on all continents but Antarctica; however, only in Europe are these long cores numerous enough to allow some mapping of vegetation from previous glacial and interglacial periods. At the other extreme in terms of temporal coverage are (1) short cores of the upper sediments of lakes or bogs and (2) cores from forest soils that preserve pollen. The former provide records of human impact on the vegetation and of recent changes, whereas the latter show combined fine-scale sampling in both time and space and provide the view most closely approximating scale within which succession into forest gaps occurs. One of the ironies of paleoecological research is how seldom the data reveal succession as the dominant dynamic in the vegetation even though much ecological research has focused on succession. These short-term records are often analyzed in high temporal density, for example, one sample per 50 years or even one per decade. The short cores (50 cm to 2 m) from lakes give coverage in high detail for 100–500 years or more in transects or in networks of relatively high spatial density (one sample per 1000 km2) from states or regions (Russell et al., 1993; Foster and Aber, 2006). Dating can be fairly accurate and precise because historical dates can be assigned to events in cores, and the date for the core top is usually known. Highresolution mapping in 50-year intervals is possible.
Temporal Resolution A key metaphor for thinking about temporal resolution within individual samples and cores is to consider stratigraphic sections of lake sediments as strip charts along which pollen data have accumulated to form palygraphs. The sediment accumulation rate (which varies but averages 0.7 mm per year in most Holocene lakes) measures the drum speed (as on a thermograph) that drives the strip chart past the recorder, and the mixing of sediments between one and a few cm of the sediment surface after burial measures the degree to which the pen recording the data wiggles up and down vertically in time while registering horizontally the changing abundances of pollen. Within this sediment mixing zone, older sediments are moved both up from below (2–6 cm) and in from other parts of the basin by reworking. Such processes can make for tricky pen work on the palygraph. If the paper in the imagined palygraph were to absorb the ink slowly such that the scatter of tracings in the upper mixed zone is reduced to a single tracing of the abundances below this zone, then our metaphorical instrument would yield what is finally observed downcore. This image of the palygraph helps by indicating the separate components controlling temporal resolution in a core. The mixing depth and sedimentation rate largely control postdepositional time averaging, which regulates the time interval (i.e., temporal resolution) represented by pollen in a sample, whereas the temporal density of samples recorded and the accuracy and precision of assigning dates to each of many cores (strip charts) control analytical time averaging, which determines the temporal resolution among a set of cores used for mapping.
Dating Uncertainties The dating uncertainty of an arbitrary pollen sample at some depth in a core depends on the uncertainties of the dating method, what is dated, the uncertainties of the age model, and variations in the sediment accumulation rate. The most accurate and precise dates are from lakes with annually laminated sediments, whose annual layers can be counted. These dates are in calendar years and accurate, with dating errors of only 1% or 2% at most. Unfortunately, lakes with such precision are too sparsely distributed for detailed mapping work. For lakes without varves, the dating near the tops of cores is more accurate and precise than that lower in the core because historical dates can be assigned to events in the core. These dates have uncertainties of 50 years or less and can be pinpointed in the core to 1 or 2 cm. In studies of Late Quaternary data, most cores have been dated by conventional radiocarbon dates of bulk sediments. The bulk dates give the dates for the sediment matrix (i.e., strip chart material) and not for the pollen embedded within the sediments (i.e., what the pen records). The bulk dates have counting uncertainties of 20–400 years, with most approximately 100 years. These average errors give 7200 years as the 95% confidence interval for each date. The dates can also be derived from 2 to 10 cm of sediment and therefore may average sediments covering 20–1000 years in age depending on the sediment accumulation rate. When dates for synchronous pollen events are averaged, such as the elm decline in Europe and the hemlock decline in eastern North America, standard deviations of ca. 300 years result. This uncertainty incorporates both the depth and the counting uncertainties. As Olsson (1986) observed, ‘‘There is y no point in determining the radiocarbon age with an uncertainty of 750 years if the relevant pollenanalytical level has an uncertainty of 7200 years.’’ Olsson (1986) and Grimm et al. (2009) also note the problems with contamination, old carbon, and sampling depths. Old carbon can lead to systematic errors of 2000 or more years and requires correction. Dates on wood and accelerator mass spectrometer (AMS) dates on macrofossils in cores are helping to reduce these errors, and AMS radiocarbon dates are allowing depth intervals of 1 cm or less to be dated. Pilcher (1993) concludes that standard errors for radiocarbon dates from sediments are potentially 7200 years but not more than 7225 years. Recent work using many AMS radiocarbon dates on selected macrofossils and wiggle matching can lower this uncertainty however, and holds much promise for studying century-scale phenomena (see Hormes et al., 2009).
Age Models and Mapping Intervals Most pollen samples (30–50 per core) are not dated directly by a radiocarbon date (3–6 per core). Rather, their age is estimated by an age model based on linear interpretation, regression, or some other curve-fitting method. For cores with continuous sedimentation, the age model estimates the drum speed for the strip chart on the palygraph. The uncertainties for all data plotted on the map for 12,000 years ago give an estimate for the amount of time before and after 12,000 years ago that the pollen data may cover on the
Paleoecology
map. The uncertainties are likely to be between 300 and 500 years. This dating uncertainty for the data mapped matches the average temporal sampling density of one sample per 300–500 years in Late Quaternary pollen studies. Given such large uncertainties, maps to-date are best restricted to 1000-year intervals. Attempts to map at finer intervals will only produce maps whose data are not independently observed from the data in the maps for the next earlier and later dates. As more studies get done at higher temporal resolution and with greater sampling interval, mapping can be attempted at finer time intervals. For sets of short cores in which historical dates yield a precision of 50 years or less, age models back to 500 years can yield dating sufficiently precise for maps in 100to 50-year intervals. For regions over which stratigraphic markers such as volcanic ash represent synchronous layers in cores, some fine-scale mapping intervals are possible for the distant past, but even the dating of tephras has uncertainties of a century or more. Pollen-assemblage zones are sometimes used chronostratigraphically and can yield temporal resolution to 50 years or less among nearby cores, but synchroneity must be assumed for processes (e.g., abundances changes for individual taxa) that are ultimately time transgressive, especially at scales of 200 km or more. The geographic area for maps at a fine time resolution is therefore relatively small, but may be enlarged as more studies like that by Hormes et al. (2009) are completed.
Zoom Lens Perspective Time series and mapped networks of pollen and plant macrofossils record Late Quaternary vegetation patterns at the scale of local vegetation, landscapes, regions, and continents (Figures 1–4). A hierarchy of nested data sets can reveal vegetation patterns at a variety of scales and provide information from general to detailed about the spatial vegetation patterns (Figures 2 and 3). Such hierarchies can link local changes to global events by recording each simultaneously (Kutzbach and Webb, 1991). A paleoecological zoom lens can then be used to examine the vegetation patterns that dominate different spatial scales for areas of 100–107 km2 with a spatial resolution of 10–2–104 km over timescales covering 10–104 years (with time series to 106 years) with resolution from 1 to 500 years (Figure 4). From a global perspective over thousands of years with a relatively coarse grid of temporally and spatially averaged samples, investigators can zoom in ultimately to the locally small but statistically significant short-term changes in species abundances within one wetland or forest stand. A zoom lens perspective is possible for eastern North America and Europe and is becoming possible in western North America and other regions. Two examples using current data illustrate this zoom lens view. The first holds time relatively constant and focuses up spatially from local to continental (Figures 1–3), and the second zooms in from a 1-My timescale down to successional changes during the past 300 years (Figure 4). The first example covers the past 21,000 years since the last glacial maximum in the northern Midwest and focuses up from a local to a continental perspective. It shows how the local changes in a wetland during the past 12,000 years in central Minnesota are
653
part of regional climate changes that ultimately reflect the global climate changes during deglaciation and the current interglacial period. At the local scale of the sampling basin, plant macrofossils, aquatic pollen, and diatoms at Kirchner Marsh in east-central Minnesota illustrate that 3000 years after the Laurentide ice sheet retreated from the sites ca. 19,000 years ago, a buried ice block melted to form the kettle basin and its associated lake (Kutzbach and Webb, 1991). Water levels were high until approximately 11,000 years ago when the seeds of damp ground and weedy annuals began appearing in the core (Watts and Winter, 1966). These appeared when the mixture of oak and herb pollen data show the first evidence of oak savanna conditions within the landscape and region near the site (Figure 1). When the herb pollen values increased sufficiently to indicate prairie vegetation near the site, large fluctuations in aquatic seeds indicated intermittent droughts that continued until a marsh developed at the site 2000 years ago. This history of local wetland development is closely linked to the vegetation and climate changes indicated at the landscape, regional, and continental levels (Figures 1–3). Here, there is a shift from the time series view provided by local pollen and macrofossils to the continental view that the maps of pollen data provide. These show how 15,000 years ago spruce trees grew initially in a parkland that became populated with deciduous trees, first ash and then birch and oak, from 14,500 to 12,000 years ago as forests began to develop near the site for the first time (Figure 1). This early vegetation was unlike any growing today and illustrates the major compositional changes in vegetation that accompanied the major changes in climate (Williams and Jackson, 2007). The sudden decrease in spruce abundance near Kirchner Marsh 12,500 years ago reflects the general northward movement and decrease in regional and continental spruce populations as climate warmed and the ice sheet retreated. Pine populations were then invading from the east to replace the birch trees that briefly grew abundantly near the site and in the northern Midwest generally. Oak and elm populations then increased to replace the pines as the climate warmed. The regional addition of herb pollen after 11,000 years ago signals the development of savanna conditions as the climate dried and the ice sheet retreated further north. The savanna grew until prairie vegetation developed approximately 8000 years ago as the grasslands spread from the west across Minnesota and the northern Midwest. By then, the ice sheet had almost disappeared and spruce populations were beginning to grow abundantly in eastern and central Canada where the boreal forest has developed today. With the retreat westward of the prairie–forest ecotone after 6000 years ago, open oak forests began growing near the lake that with further growth in aquatic vegetation became a marsh after 2000 years ago. Oak populations then decreased regionally as part of a general retreat of oak in the north as conifer populations increased and spruce populations increased south from Canada into the northern Midwest and New England. The broad-scale regional and continental maps show how the local and landscape changes in vegetation fit within the broader context of changes. The second example is a zoom lens perspective in time (Figure 4) and shows time series for taxa reflecting the long-
654
Paleoecology
term temporal beat in climate at long time scales (1.5 My to 16,000 years) but then shifting to reflect fires, disease, and other disturbances at shorter timescales, especially when the pollen data are derived from within a forested hollow. Within the latter, the pollen reflects local changes in trees next to the site. This arrangement and description of the data allow paleoecologists to zoom in or out in space–time to observe different aspects of vegetation dynamics and patterns of biodiversity from long-term changes on several spatial scales (from continental to inside the forest canopy) to competitive interactions after disturbance within communities. With such an ordering of data and images, the interconnected roles and impacts of climate change, disturbance, disease, succession, soil development, competition, and evolution can all be observed and potentially distinguished from one another in studies of past biodiversity. To this end, recent studies of sediment records are including data on charcoal, sediments, biomarkers, isotopes, biogeochemistry, and plankton that provide evidence for environmental changes from fires to climate that can be used to help interpret the changes in the vegetation (Whitlock et al., 2003; Webb et al., 2003). Mapping and studying pollen and plant macrofossil data in space–time have been convincing of the potential for resolving many different views of the past. No single fixed picture is possible because there is no preferred viewing scale or perspective, nor is there any one way to describe the vegetation and biodiversity. Many conventional displays and perspectives are used, but some, such as traditional pollen diagrams, may not be optimal for interpreting key variations in the vegetation. A zoom lens perspective in space and time is required to help explore all the possibilities and to allow for diverse narratives and explanations. Succession and patch dynamics are evident with data scaled to meters and decades, whereas climatically induced migrations and abundance changes appear best over thousands of kilometers and years. To zoom out from a local to a global view, the paleoecological data need to be organized so that highly resolved images of species near a site give way to more generalized averages of data values whose patterns will stand out sharply when viewed across continents or the world. Appropriate study of assembled databases should allow ecologists to resolve and perceive a variety of phenomena, such as ecotones, disturbance horizons, species distributions, and migration patterns, that are important for biodiversity.
See also: Biodiversity, Evolution and. Fossil Record. Remote Sensing and Image Processing
References Baker RG, Bettis III EA, Denniston RF, Gonzalez LA, Strickland LE, and Krieg JR (2002) Holocene paleoenvironments in southeastern Minnesota – Chasing the prairie–forest ecotone. Palaeogeography Palaeoclimatology Palaeoecology 177: 103–122. Betancourt JL (2004) Arid lands paleobiogeography: The fossil rodent midden record in the Americas. In: Lomolino MV and Heaney LR (eds.) Frontiers in Biogeography: New Directions in the Geography of Nature, pp. 27–46. Sunderland, MA: Sinauer Associates Inc.
Betancourt JL, Van Devender TR, and Martin PS (eds.) (1990) Packrat Middens: The Last 40,000 Years of Biotic Change. Tucson: University of Arizona Press. Binney HA, Willis KJ, Edwards ME, et al. (2009) The distribution of late Quaternary woody taxa in northern Eurasia: Evidence from a new macrofossil database. Quaternary Science Reviews 28: 2445–2464. Davis MB, Schwartz MW, and Woods K (1991) Detecting a species limit from pollen in sediments. Journal of Biogeography 18: 653–668. Foster DR and Aber JD (eds.) (2006) Forests in Time: The Environmental Consequences of 1,000 Years of Change in New England. New Haven, CT: Yale University Press. Foster DR and Zebryk TM (1993) Long-term vegetation dynamic and disturbance history of a Tsuga-dominated forest in New England. Ecology 74: 982–998. Gaudreau DC, Jackson ST, and Webb III T (1989) The use of pollen data to record vegetational patterns in regions of moderate to high relief. Acta Botanica Nederlandica 38: 369–390. Gray ST, Betancourt JL, Jackson ST, and Eddy RG (2006) Role of multidecadal climatic variability in a range extension of pinyon pine. Ecology 87: 1124–1130. Grimm EC, Maher Jr. LJ, and Nelson DM (2009) The magnitude of error in bulk-sediment radiocarbon dates from central North America. Quaternary Research 72: 301–308. Hoogheimstra H and Ran ETH (1994) Late Pliocene–Pleistocene high resolution pollen sequence of Colombia: An overview of climatic change. Quaternary International 21: 63–80. Hormes A, Blaauw M, Dahl SO, Nesje A, and Possnert G (2009) Radiocarbon wiggle-match dating of proglacial lake sediments – implications for the 8.2 ka event. Quaternary Geochronology 4: 267–277. Huntley B and Birks HJB (1983) An Atlas of Past and Present Pollen Maps for Europe: 0–13000 Years Ago. Cambridge: Cambridge University Press. Huntley B and Webb III T (eds.) (1988) Vegetation History. Dordrecht: Kluwer. Jackson ST and Whitehead DR (1991) Holocene vegetation patterns in the Adirondack Mountains. Ecology 72: 641–653. Jackson ST, Overpeck JT, Webb III T, Keattch S, and Anderson KH (1997) Mapped plant macrofossil and pollen records of late-Quaternary vegetation change in eastern North America. Quaternary Science Review 15: 1–71. Kutzbach JE and Webb III T (1991) Late Quaternary climatic and vegetational change in eastern North America: Concepts, models, and dates. In: Shane LCK and Cushing EJ (eds.) Quaternary Landscapes, pp. 175–217. Minneapolis: University of Minnesota Press. Lyford ME, Jackson ST, Gray ST, and Eddy RJ (2004) Validating the use of woodrat (Neotoma) middens for documenting natural invasions. Journal of Biogeography 31: 333–342. Magri D, Vendramin GG, Comps B, et al. (2006) A new scenario for the Quaternary history of European beech populations: Palaeobotanical evidence and genetic consequences. Journal of Biogeography 171: 199–221. Olsson IU (1986) Radiometric dating. In: Berglund BE (ed.) Handbook of Holocene Palaeoecology and Palaeohydrology, pp. 110–120. Chichester, UK: Wiley. Paleobiology Database. http://paleodb.org/cgi-bin/bridge.pl Peglar SM, Fritz SC, Alapieti A, Saarnisto M, and Birks HJB (1984) Composition and formation of laminated sediments in Diss Mere, Norfolk, England. Boreas 13: 13–28. Pilcher JR (1993) Radiocarbon dating and the palynologist: A realistic approach to precision and accuracy. In: Chambers FM (ed.) Climate Change and Human Impact on the Landscape, pp. 23–32. London: Chapman & Hall. Prentice IC, Jolly D and BIOME 6000 participants (2000) Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa. Journal of Biography 27: 507–519. http://www.neotomads.org Russell E, Davis RB, Anderson RS, Rhodes TE, and Anderson DS (1993) Recent centuries of vegetational change in the glaciated north-eastern United States. Journal of Ecology 81: 647–664. Shuman BN, Bartlein PJ, Logar N, Newby P, and Webb III T (2002) Parallel vegetation and climate responses to the Early-Holocene collapse of the Laurentide Ice Sheet. Quaternary Science Reviews 21: 1793–1805. Shuman BN, Newby P, Huang Y, and Webb III T (2004) Evidence for the close climatic control of New England vegetation history. Ecology 85: 1297–1310. Simmons IG (1993) Vegetation change during the Mesolithic in the British Isles: Some amplifications. In: Chambers FM (ed.) Climate Change and Human Impact on the Landscape, pp. 109–118. London: Chapman & Hall. Turner J and Peglar SM (1988) Temporally precise studies of vegetation history. In: Huntley B and Webb III T (eds.) Vegetation History, pp. 753–777. Dordrecht: Kluwer.
Paleoecology
Watts WA and Winter TC (1966) Plant macrofossils from Kirchner Marsh, Minnesota – a paleoecological study. Bulletin Geological Society of America 77: 1339–1360. Webb III T, Shuman BN, and Williams JW (2003) Climatically-forced vegetation dynamics in North America during the late-Quaternary. In: Gillespie A, Porter SC, and Atwater BF (eds.) The Quaternary Period in the United States, pp. 459–478. New York: Elsevier. Williams JW and Jackson ST (2007) Novel climates, no-analog communities, and ecological surprises. Frontiers in Ecology and the Environment 5: 475–482.
655
Williams JW, Shuman BN, Webb III T, Bartlein PJ, and Leduc PL (2004) Late Quaternary vegetation dynamics in North America: Scaling from taxa to biomes. Ecological Monographs 74: 309–334. Whitlock C, Shafer SL, and Marlon J (2003) The role of climate and vegetation change in shaping past and future fire regimes in the northwestern US and the implications for ecosystem management. Forest Ecology and Management 178: 5–21.