Journal of Heredity Advance Access originally published online on October 26, 2005
Journal of Heredity 2005 96(6):627-634; doi:10.1093/jhered/esi115
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Genetic Structure Inside a Declining Red Oak Community in Old-Growth Forest
From the United States Department of Agriculture, Forest Service, North Central Research Station, Hardwood Tree Improvement and Regeneration Center, Purdue University Department of Forestry and Natural Resources, West Lafayette, IN 47907–2033 (Aldrich and Michler); Purdue University Department of Forestry and Natural Resources, West Lafayette, IN 47907–2033 (Parker and Rhodes); and Hardwood Tree Improvement and Regeneration Center, Purdue University Department of Forestry and Natural Resources, West Lafayette, IN 47907–2033 (Glaubitz)
Address correspondence to Preston R. Aldrich, Department of Biological Sciences, Birck Hall 341, 5700 College Road, Benedictine University, Lisle, IL 60532–0900, or e-mail: paldrich{at}ben.edu.
 |
Abstract |
|---|
 Top Abstract Materials and MethodsResultsDiscussionReferences |
|---|
Problems with oak regeneration have been documented in the last 50 years at numerous sites in the Midwestern United States. We applied nuclear microsatellites to examine the demographic and fine-scale spatial genetic structure of red oaks in two old-growth stands in Indiana. Oaks in one stand have declined in numbers over the past several decades whereas oaks in the other, smaller stand have increased. Large amounts of genetic variation were maintained within stands, and there was slight but significant differentiation among stands. There was significant but weak isolation by distance genetic structure within the large stand, likely reflecting family structure. No significant differences exist in allele frequencies or in levels of genetic diversity between cohorts that remain well represented within each stand, even between medium-sized adults and those antedating European settlement of the area. However, a virtual absence of smaller size classes in the forest interior of the large stand represents the early stages of a genetic bottleneck in what had been the core habitat of this stand. Whether future generations of this old-growth stand will retain the present genetic character depends on the oaks regenerating at the forest margins, absent any major changes in disturbance regimes. Similar demographic and genetic dynamics are likely occurring in a large number of remnant oak forests across the Midwest.
Despite the present widespread distribution of oaks in temperate zone forests, concerns have arisen from the past 50 years of research that oak regeneration is faltering in many forests (reviewed in Abrams 1992, 2003; Lorimer 1993). Increasingly, stands are comprising large oak trees with few seedlings or saplings in the understory, where more shade-tolerant species, such as maple (Acer spp.), maintain dense thickets of advanced regeneration. These patterns have been described in a range of forest types, from small woodlots in Indiana (Parker et al. 1985) to large expanses of the southern Appalachian Mountains (Lorimer 1993). The causes of the reproductive failure appear to be several (Lorimer 1993) and include changes in disturbance regimes, such as post–European settlement suppression of fire, which had served to keep both canopies and understories open and suitable for oak regeneration. Compounding these effects are elevated rates of herbivory and predation or ineffective dispersal of oak regeneration by deer and rodents (Frelich and Lorimer 1985; Goheen and Swihart 2003) and competition with invasive plant species (Huebner 2003).
It is unclear what effect these changes are having on oak genetic resources in the Midwestern United States, especially in the old-growth forests that have not been well studied genetically. This is despite the importance of the genus for timber and ecosystem function. Do the cohorts of the largest-size oaks in old-growth forest carry novel genetic variation that has not passed into the smaller size classes? Is the demographic structure of these stands likely to provide for the in situ maintenance of variation currently present in the old-growth stands?
A few studies have examined the internal organization of genetic variation in old-growth forests in other taxa, and several conclude that the abundance of contemporary regeneration is key to whether genetic variation is being lost. In some within-stand studies where abundant regeneration was present, no significant genetic differentiation was found between old and young trees (Acer saccharum: Fore et al. 1992; Simon et al. 1995; Pinus taeda: Roberds and Conkle 1984). In the absence of regeneration, partial harvest of old-growth can result in a loss of alleles (Buchert et al. 1997; Rajora et al. 2000), but stands that regenerate by natural means often show no significant reduction in genetic diversity relative to other old-growth stands (Gomory 1992; Neale 1985; Rajora 1999; Rajora and Pluhar 2003; Schmidtling and Hipkins 1998). Replanted stands can contain less genetic diversity than old-growth stands (Gomory 1992; Rajora 1999) but can also display no detectable difference (Rajora and Pluhar 2003).
Here, we report on the genetic composition of red oaks in remnant old-growth forest in Indiana. We applied microsatellite markers to explore the internal (spatial and temporal) organization of the genetic diversity in two adjacent stands (20.6 ha and 2.6 ha in size) isolated during European settlement in the 1800s. Oaks are failing to regenerate in the large stand (Parker et al. 1985) but are rebounding in the small stand (Aldrich et al. 2005). We compare genetic diversity within and between stands, within and between size classes within a stand, and describe the fine-scale spatial genetic structure in the large stand.
|
Materials and Methods |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
Study Site and Sampling
The Davis-Purdue Research Forest (DPRF) is an old-growth deciduous hardwood forest located in east-central Indiana in Randolph County (SE 1/4 of section 23, Township 21N, Range 12E). Oaks had an importance value of 41.2% in the 1976 canopy, with roughly half of these red oaks (Parker and Leopold 1983; for site descriptions, see Parker et al. 1985). The establishment of agriculture on the property during the 1800s left four remnant stands, of which we studied the largest (20.6 ha, S20) and the smallest (2.3 ha, S2), separated by roughly 400 m. Purdue University acquired the property in 1917 and suppressed exogenous disturbances thereafter. Beginning in 1926, professor Burr N. Prentice (Purdue Department of Forestry) mapped, measured, and tagged all stems
4.0 inches (10.2 cm) diameter at breast height (dbh) in both stands (Prentice 1927). Later censuses included 1976 (large stand only), 1986–1987, 1992, and 1998. Aldrich et al. (2003b) revealed only limited genetic differentiation among the three red oak (Quercus sect. Lobatae) species present at the site—namely, Q. rubra L. (northern red oak), Q. shumardii Buckl. (Shumard oak), and Q. palustris Muench. (pin oak). This is explained by overlap in morphological traits used to identify species, recent speciation, and extensive hybridization. Hybridization is thought to be common in the red oak group (Jensen 1995), and all pairwise hybrids between these three species have been described based on morphology (Laughlin 1963, 1964; Morsink and Pratt 1984; Palmer and Steyermark 1935). Consequently, we have treated the red oak community collectively.
For genotyping, we selected adult trees haphazardly from the small 2.3 ha stand (n = 62, or 37% of total 168 stems in the whole patch) and at a comparable sampling density (n = 96) from a 9.5 ha sampling plot falling within the northern half of the large 20.6 ha stand with roughly half of its area in core interior habitat and half in edge habitat. We collected cambium tissue from the trunk of adult trees using a chisel and hammer, placed samples on ice in the field, and froze them at Purdue University until DNA extraction.
Molecular Genetics
For DNA extractions, we ground sample tissue under liquid nitrogen with a wood pulverizer (CertiPrep 6750 Freezer/Mill, Spex) and then with a metal bead in an agitating rotor (FastPrep Bio101, Savant); details are in Aldrich et al. (2002). We adjusted template concentrations to 5–10 ng/µl for polymerase chain reactions.
Red oak microsatellite markers are described in Aldrich et al. (2002, 2003a), including primer sequences and recommended annealing temperatures. We examined their linkage relationships in an open pollinated mapping population (unpublished data) and selected a set of twelve that appear to be unlinked: red oak markers: quru-GA-0A01, –0A03, –0C19, –0I21, –0M07, –1C06, –1C08, –1F02, –1G13, –1H14, and –2G07, along with the European white oak locus ssrQpZAG9 (Steinkellner et al. 1997).
We conducted polymerase chain reaction amplifications (25 µl volume) as follows: 1x Ex Taq Buffer (Panvera, proprietary except 2.0 mM MgCl2), 100 µM dNTP each, 72 nm each forward and reverse primer, 0.01 U/µl Takara Ex Taq Polymerase (Panvera), and 0.2–0.4 ng/µl DNA. Polymerase chain reaction profiles were 94 °C, 1 min; 40–50 cycles of 94°C, 30 sec; Ta, 45 sec; 72 °C, 1.5 min; 72 °C, 10 min. We analyzed fragment sizes on an eight-capillary CEQ2000XL genotyper (Beckman Coulter).
Data Analysis
For the 158 total red oak stems genotyped in the study, we examined their diameter distribution in the full data set and identified three categories with balanced sample sizes within and across stands (Table 1; S = small, 10 cm 
dbh < 28 cm; M = medium, 28 cm dbh < 81 cm; and L = large, dbh 81 cm). In the large stand, we further divided the large size class red oaks into the "relict" trees that already were large (LR, dbh 53 cm) by the 1926 census (and hence were likely to have been established prior to fragmentation) and those "nonrelict" trees that were smaller (LNR, 10 dbh < 53) in 1926.
|
Some of the red oak size classes were poorly stocked, with stems either entirely missing or rare (see Aldrich et al. 2005 for detailed demography of both stands). In the 9.5 ha plot of the large stand, no stems were in the juvenile class (dbh < 10 cm), and adult stems in the small size class (S20-S) were rare. In the small stand, only a few stems were in the large size class (S2-L). Although we did not directly determine the genetic composition of these groups, we discuss here the implications of their near absence for the future gene pool.
In this article, we report levels of genetic diversity (mean values for the 12 loci) within each stand along with comparisons between size classes (cohorts) within each stand. Diversity measures included average number of alleles per locus (allelic richness, Ar), effective number of alleles per locus (Ae; Kimura and Crow 1964), observed heterozygosity (Ho), unbiased expected heterozygosity (He), and panmictic index (f; Weir and Cockerham 1984). We performed permutation tests (C++ program; Glaubitz et al. 2003) to test for significant differences in genetic diversity measures between pairs of size classes. All diversity measures were tested in this manner. Observed differences were tested against distributions derived from 10,000 random permutations of individual multilocus genotypes among the two samples. In addition, the program GDA (Genetic Data Analysis; Lewis and Zaykin 2001) was used to estimate 95% confidence limits for all three F statistics at the stand level, based on 10,000 bootstrap resamples of loci. Also, to more fully examine potential associations between tree ages and the retention of rare alleles, we tested for an association between the mean number of rare alleles (frequency < 0.05 in full study) per locus per stem and the diameter of the tree (dbh, cm).
We also examined differentiation in allele frequencies between the two stands as a whole and between size classes (cohorts) within and between stands. This was done using the program GENEPOP 1.2 (Raymond and Rousset 1995a), accepting default settings for burn-in length, number of batches, and number of iterations per batch. For each test, GENEPOP calculated a global P value for an overall departure from null hypothesis expectations across loci using Fisher's method (Raymond and Rousset 1995b).
We used the program SPAGeDi 1.1 (Hardy and Vekemens 2002) to estimate FST (i.e., 
; method of Weir and Cockerham 1984; Weir 1996, chap. 5) for each pairwise comparison, testing the significance of each FST estimate via permutation of multilocus genotypes among the two samples in question (one-tailed test based on 20,000 permutations). At the stand level, the significances of f and F were also tested: f by permuting genes among individuals within stands and F by permuting genes among individuals in the total population.
Finally, we examined fine-scale spatial genetic structure within the large stand only (x-y coordinates were not available for the small stand). We used SPAGeDi to estimate relatedness (Hamilton 1964a, b) according to Queller and Goodnight (1989) between all possible pairs of genotyped trees within the large stand. As a parameter, relatedness (r) measures the expected proportion of allele sharing between two individuals as a result of identity by descent such that r = 0.5 for full sibs and r = 0.25 for half sibs. For every 20 m pairwise distance class, SPAGeDi computed an average of the pairwise estimates of r and then obtained 95% confidence intervals for these averages based on 20,000 permutations of multilocus genotypes among locations (x-y coordinates).
|
Results |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
Levels of Genetic Diversity
The oak populations displayed high levels of genetic diversity overall (Table 1), in each case exhibiting heterozygosities > 0.75 regardless of the stand or size class (not including the poorly stocked size classes). Levels of diversity were comparable in the two stands. Total inbreeding in the study was low (F = 0.047) as was stand-level inbreeding (f = 0.034) and differentiation (
= 0.013) according the GDA analysis. Inbreeding at individual loci in the study ranged from f = – 0.053 to 0.172; null alleles may be present at the two loci where f > 0.1. There were no significant differences (P > .05) in levels of genetic diversity between the well-stocked size classes within a stand. This held for all comparisons (S20-M versus S20-L; S20- LNR versus S20- LR; S20-M versus S20- LR; S2-S versus S2-M). No association was found between the mean number of rare alleles (frequency < 0.05) per locus per stem and the stem dbh (r = 0.042).
Genetic Differentiation Between and Within Stands
We detected significant differences in allele frequencies between stands but not within stands (Table 2). All interstand comparisons of allele frequencies were significant for all of the size classes compared. There were no detectable differences in overall allele frequencies between well-stocked size classes within a stand according to the pairwise GENEPOP tests. This held even for the oldest cohort (the relict trees or S20-LR), which was not significantly differentiated from other well-stocked cohorts in the large stand. Identical results were obtained from analysis of pairwise FST.
|
Fine-Scale Spatial Genetic Structure Within the Large Stand
Average genetic relatedness was a decreasing function of distance class in the large stand (Figure 1). The average relatedness estimate, r (Queller and Goodnight 1989), was significantly greater than zero for distance classes
80 m. The highest average relatedness value (r = 0.079, with P = .0000) was found for the shortest distance class (0–20 m), indicating that pairs of individuals within 20 m of each other have, on average, a level of relatedness slightly higher than that expected of half cousins (Blouin 2003). At distances 240 m, stems were, on average, no more genetically similar than expected of a random assemblage. Overall, we can convincingly reject the null hypothesis that geographic position carried no information on genetic relatedness. However, the low maximum average r estimate of 0.079 for the 0–20 m distance class suggests that parent-offspring clusters are heavily diluted with more distantly related individuals.
|
|
Discussion |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
These remnant old-growth red oak populations have retained high levels of genetic variation despite the genetic bottlenecks that seem to have accompanied European settlement of the area. For example, 87% of Indiana was forested in 1816 (Petty and Jackson 1966) whereas today much of northern Indiana is used for agriculture with occasional, spatially isolated second-growth and less frequent old-growth stands (Spetich et al. 1997). In addition to the bottleneck in numbers resulting from the initial harvests, the process of removing the biggest and best trees (i.e., high-grading) from the forest remnants continues (McGuire et al. 1999; Nyland 1992), potentially further depleting the gene pool of important variation. Although we cannot speak to any genetic diversity already purged from the DPRF stands, the remaining trees are highly diverse genetically, and the younger cohorts that are well stocked are still genetically representative of trees that had existed during settlement of the area. Because nonindustrial private forest owners control almost 60% of the forested land in the United States (Smith et al. 2001), wise management of these remnant woodlots should be included in a stewardship plan for the red oak gene pool.
The small observed genetic differentiation between the two stands can be explained by genetic structure that existed before fragmentation of the forest in the 1800s. Interstand genetic differentiation ( = 0.013), though statistically significant, was low, and it fell within other interstand estimates published for Q. rubra (Gst = 0.009, Schwarzmann and Gerhold 1991; FST = 0.092, Sork et al. 1993). The presettlement forest may have been composed of genetic patches of familial substructure that, upon fragmentation, were transformed into significant though slight genetic differences among stands.
It is unlikely that postfragmentation genetic drift associated with small effective breeding populations has played a prominent role in the differentiation of the stands. Life expectancy of red oaks is about 100 to 150 years with peak reproduction occurring sometime between 25 and 50 years (Burns and Honkala 1990). Given the average diameter growth rate for red oaks at the DPRF (0.444 cm/year), the average-size red oak that we genotyped (small stand, mean 31.7 cm; large stand, 81.5 cm) established over 70 and 180 years ago in the small and large stands, respectively. Thus, only one or two generations have accrued in the large stand since the European settlers fragmented this landscape and only slightly more generations in the small stand, providing little opportunity for the erosion of genetic diversity by random drift.
Compared to the oaks in nine other published studies (Table 3), the red oaks in the large DPRF stand displayed typical patterns of fine-scale spatial genetic structure. Oak populations usually exhibit weak genetic correlations between near-neighbor stems, typically within 50 m (< 80 m at the DPRF), though reports ranged from 0 to 160 m. Spatial genetic structure is negligible and at times negative beyond these distances. These patterns are consistent with the isolation by distance (IBD) genetic structure predicted by Wright (1943, 1946) to accrue in a continuous population with limited dispersal of progeny from parents, though several other factors can generate and erode spatial genetic structure in oak populations and thus deserve consideration.
|
Additional factors beyond limited primary dispersal from parents may have contributed to the fine-scale IBD genetic structure at the DPRF. First, the constituent species of a hybrid swarm could contribute to spatial genetic correlations within a stand if the species are distributed nonrandomly, though we detected only a weak association between genetic relatedness and species identity (Mantel test, p = 0.1556). Second, differential survivorship of genotypes across habitats can produce spatial genetic correlations within a stand (Epperson 1990b), and it is known that Q. palustris is tolerant of wet soils, whereas Q. rubra prefers well-drained soils (Burns and Honkala 1990). Third, some oaks exhibit clonal genetic structure (Berg and Hamrick 1994), though the oak species at the DPRF are not known for this, despite their ability to resprout from stumps (Burns and Honkala 1990).
Fourth, episodic recruitment following disturbance could introduce spatial genetic structure if several progeny of relatively few trees recruit into a canopy opening or if stands are replanted using few acorn sources. Stands whose oaks are not regenerating will gradually loose their spatial aggregation (Aldrich et al. 2003c) and should lose their IBD genetic structure through random attrition (Hamrick et al. 1993). Our literature review (Table 3) confirmed these expectations, that oaks in old-growth stands generally exhibit less pronounced IBD genetic structure than that found in naturally regenerated or replanted stands.
Finally, secondary dispersal by animals deserves additional consideration as a source of IBD genetic structure. Secondary dispersal might diminish family structure unless seeds are transported together in a fruit or to a cache or larder. Darley-Hill and Johnson (1981) reported that blue jays (Cyanositta cristata) moved 54% of pin oak (Q. palustris) acorns over a kilometer on average, which should dissipate IBD genetic structure except that acorns were moved in groups of one to five (mean of 2.2) per foraging bout. Squirrels are another important agent of oak dispersal. The North American red squirrel (Tamiasciurus hudsonicus) is replacing the native gray squirrel (Sciurus carolinensis) in many parts of its range. Differences in their foraging (described by Goheen and Swihart 2003) will likely become manifest as differences in red oak genetic structure. Gray squirrels are scatter-hoarders, dispersing few acorns to each of many sites, which should reduce the amount of IBD genetic structure in a stand. Red squirrels are larder-hoarders, dispersing numerous acorns to each of few sites. The codispersal of sibs would tend to increase IBD genetic structure.
As for pollination, evidence suggests that the DPRF breeding populations of red oaks have remained large, judged here indirectly and only for the well-stocked classes. We found little evidence of elevated inbreeding (positive f) that might arise through biased fecundity distributions or consanguineous matings (Q. rubra is considered an obligate outcrosser; Schwarzmann and Gerhold 1991). We did not observe the pattern of decreasing heterozygote deficit (decreasing f) with age that would be expected had there been selection over time against inbred individuals (Mitton et al. 1997). Inbreeding as measured by heterozygote deficit was slightly greater in the large stand (f = 0.047) than in the small stand (f = 0.014) but, according to bootstrap tests, was not significantly different from zero overall. Ecological evidence also suggests a large breeding population, as the stands still contain numerous large red oaks, many of which regularly produce acorns in great numbers (Aldrich, personal observation).
Lack of genetic differentiation among size classes within a stand indicates that much of the genetic variation present in the oldest red oaks has passed successfully between generations. Studies of old-growth pine (Pinus) and maple (Acer) have found similarly (Pinus ponderosa: Linhart et al. 1981; Pinus taeda: Roberds and Conkle 1984; Acer saccharum: Fore et al. 1992; Simon et al. 1995). If oaks on adjacent farms have contributed heavily to the smaller DPRF size classes, then they must have essentially the same genetic composition as the large DPRF red oaks.
One aspect that distinguishes our findings from these studies of pine and maple is the reproductive failure of the oaks and the ensuing implications for the genetic variation. For example, maples are shade tolerant and generally able to thrive following canopy closure arising from cessation of forest disturbances. In fact, the intrusion of maples into the subcanopy and eventually the canopy of the DPRF appears to be a primary factor in the decline of the oaks, which are less tolerant of shade (Aldrich et al. 2003c, 2005; Parker et al. 1985). Aldrich et al. (2005) surveyed red oaks in the center of the large stand in 2001 and found none smaller than 10 cm diameter, even though the nearby small stand contained 98 stems (42.4 stems/ha) in this size class. Combined with the rarity of small adults (dbh < 28 cm), red oaks in the core of the large stand are experiencing the incipient stages of a severe genetic bottleneck.
There is little evidence of the demographic failure abating in the core habitat of the large stand (Aldrich et al. 2005). Although the genetic diversity in the old-growth oaks has been passed on to the medium-size trees in the same stand, the local breeding pool may become depleted once the currently medium- and large-size trees senesce. In the absence of natural disturbance or management intervention, the genetic erosion currently evident in the juvenile and small adult size classes is likely to propagate into the canopy classes. And while it is known that oak pollen can move large distances (Streiff et al. 1999), recent improvements in estimation of pollen dispersal (Austerlitz and Smouse 2001a,b; Smouse et al. 2001) show that the local breeding pool is often dominated by relatively few oaks, on the order of four or five individuals (Sork et al. 2002), suggesting that random drift may be more important in oak populations than previously thought. Further reductions in pollen donor density at the DPRF could lower acorn production, as was seen in blue oak (Q. douglasii; Knapp et al. 2001), which would compound the problems already evident from low survivorship of small stems in the shaded core habitat.
Moreover, the core habitat gene pool composition is increasingly dependent on input from oaks in other habitats, reminiscent of a source-sink (Pulliam 1988). These sites differ in genetic composition to a lesser (small DPRF stand) or greater degree (presumably other, more distal woodlots), and high rates of gene flow into the core may eventually displace the relict variation currently maintained in the canopy classes. The DPRF sites that would likely serve as a genetic source for the core habitat are mostly edge habitat—namely, the extreme margins of the large stand and the small stand, which is itself mostly edge habitat. Forest edges often experience greater environmental stochasticity and lower adult survivorship rates (reviewed in Murcia 1995); note the rarity of large red oaks in the small DPRF stand. Thus, the core habitat is likely to be supported by a shifting genetic base, and it is unlikely that future generations of DPRF oaks will retain the present genetic character. The same scenario (increasing dependence on volatile edge habitat) is likely being played out in numerous remnant oak stands throughout the Midwest.
|
Acknowledgments |
|---|
This work was supported by the United States Department of Agriculture Forest Service, North Central Research Station, and the Purdue University Department of Forestry and Natural Resources. K. Woeste, V. Busov, and two anonymous reviewers offered constructive comments on the manuscript. We also thank M. Jagtap, J. Romero-Severson, and W. Sun for logistical support.
|
Footnotes |
|---|
Corresponding Editor: John Burke
Received February 22, 2005
Accepted July 29, 2005
|
References |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
-
Abrams MD, 1992. Fire and the development of oak forests. Bioscience 42:346–353.[CrossRef]
Abrams MD, 2003. Where has all the white oak gone? Bioscience 53:927–939.[CrossRef]
Aldrich PR, Jagtap M, Michler CH, and Romero-Severson J, 2003a. Amplification of North American red oak microsatellite markers in European white oaks and Chinese chestnut. Silvae Genet 52:176–179.
Aldrich PR, Michler CH, Sun W, and Romero-Severson J, 2002. Microsatellite markers for northern red oak (Fagaceae: Quercus rubra). Mol Ecol Notes 2:472–474.[CrossRef]
Aldrich PR, Parker GR, Michler CH, and Romero-Severson J, 2003b. Whole-tree silvic identifications and the microsatellite genetic structure of a red oak species complex in Indiana old-growth forest. Can J Forest Res 33:2228–2237.[CrossRef]
Aldrich PR, Parker GR, Romero-Severson J, and Michler CH, 2005. Confirmation of oak recruitment failure in Indiana old-growth forest: 75 years of data. Forest Science 51:406–416.
Aldrich PR, Parker GR, Ward JS, and Michler CH, 2003c. Spatial dispersion of trees in an old-growth temperate hardwood forest over 60 years of succession. Forest Ecol Manag 180:475–491.[CrossRef]
Austerlitz F and Smouse PE, 2001a. Two-generation analysis of pollen flow across a landscape. II. Relation between fft, pollen dispersal, and inter-female distance. Genetics 157:851–857.
Austerlitz F and Smouse PE, 2001b. Two-generation analysis of pollen flow across a landscape. III. Impact of within-population structure. Genetical Research 78:271–280.[Web of Science][Medline]
Bacilieri R, Labbe T, and Kremer A, 1994. Intraspecific genetic structure in a mixed population of Quercus petraea (Matt.) Leibl and Q. robur L. Heredity 73:130–141.
Berg EE and Hamrick JL, 1994. Spatial and genetic structure of two sandhills oaks: Quercus laevis and Quercus margaretta (Fagaceae). Am J Bot 81:7–14.
Blouin MS, 2003. DNA-based methods for pedigree reconstruction and kinship analysis in natural populations. Trends Ecol Evol 18:503–511.[CrossRef]
Buchert GP, Rajora OP, Hood JV, and Dancik BP, 1997. Effects of harvesting on genetic diversity in old-growth eastern white pine in Ontario, Canada. Conserv Biol 11:747–758.[CrossRef]
Burns RM and Honkala BH, 1990. Silvics of North America. USDA Forest Service, agriculture handbook 654. Washington, DC: United States Department of Agriculture.
Chung MY and Chung MG, 2002. Fine-scale genetic structure in populations of Quercus variabilis (Fagaceae) from southern Korea. Can J For Res 80:1034–1041.
Chung MY, Nason J, Chung MG, Kim K-J, Park C-W, Sun B-Y, and Pak J-H, 2002. Landscape-level spatial genetic structure in Quercus acutissima (Fagaceae). Amer J Bot 89:1229–1236.
Cottrell JE, Munro RC, Tabbener HE, Milner AD, Forrest, GI, and Lowe AJ, 2003. Comparison of fine-scale genetic structure using nuclear microsatellites within two British oakwoods differing in population history. Forest Ecol Manag 176:287–303.[CrossRef]
Darley-Hill S and Johnson WC, 1981. Acorn dispersal by the blue jay (Cyanositta cristata). Oecologia 50:231–232.[CrossRef]
Epperson BK, 1990b. Spatial autocorrelation of genotypes under directional selection. Genetics 124:757–771.[Abstract]
Fore SA, Hickey RJ, Vankat JL, Guttman SI, and Schaefer RL, 1992. Genetic structure after forest fragmentation: a landscape ecology perspective on Acer saccharum. Can J Bot 70:1659–1668.
Frelich LE and Lorimer CG, 1985. Current and predicted long-term effects of deer browsing in hemlock forests in Michigan, USA. Biol Conserv 34:99–120.[CrossRef]
Geburek T and Tripp-Knowles P, 1994. Genetic architecture in bur oak, Quercus macrocarpa (Fagaceae), inferred by means of spatial autocorrelation analysis. Pl Syst Evol 189:63–74.[CrossRef]
Glaubitz JC, Murrell JC, and Moran GF, 2003. Effects of native forest regeneration practices on genetic diversity in Eucalyptus consideniana. Theor Appl Genet 107:422–431.[CrossRef][Web of Science][Medline]
Goheen JR and Swihart RK, 2003. Food-hoarding behavior of gray squirrels and North American red squirrels in the central hardwoods region: implications for forest regeneration. Can J Zool 81:1636–1639.[CrossRef]
Gomory D, 1992. Effect of stand origin on the genetic diversity of Norway spruce (Picea abies Karst.) populations. Forest Ecol Manag 54:215–223.[CrossRef]
Hamilton WD, 1964a. The genetical evolution of social behavior. J Theor Biol 7:1–16.[CrossRef][Web of Science][Medline]
Hamilton WD, 1964b. The genetical evolution of social behavior, II. J Theor Biol 7:17–52.[CrossRef][Web of Science][Medline]
Hamrick JL, Murawski DA, and Nason JD, 1993. The influence of seed dispersal mechanisms on the genetic structure of tropical tree populations. Vegetatio 107/108:281–297.
Hardy O and Vekemans X, 2002. SPAGeDi: a versatile computer program to analyze spatial genetic structure at the individual or population levels. Mol Ecol Notes 2:618–620.[CrossRef][Web of Science]
Huebner CD, 2003. Vulnerability of oak-dominated forests in West Virginia to invasive exotic plants: temporal and spatial patterns of nine exotic species using herbarium records and land classification data. Castanea 68:1–14.
Jensen RJ, 1995. Identifying oaks: the hybrid problem. J Int Oak Soc 6:47–54.
Kimura M, Crow J, 1964. The number of alleles that can be maintained in a finite population. Genetics 49:725–738.
Knapp EE, Goedde MA, and Rice KJ, 2001. Pollen-limited reproduction in blue oak: implications for wind pollination in fragmented populations. Oecologia 128:48–55.[CrossRef]
Laughlin K, 1963. Quercus x riparia Laughlin Kansas City oak. Phytologia 9:101–107.
Laughlin K, 1964. Quercus x columnaris Laughlin Caldwell oak. Phytologia 9:488–495.
Lewis PO and Zaykin D, 2001. Genetic Data Analysis: computer program for the analysis of allelic data. Version 1.0 (d16c). http://lewis.eeb.uconn.edu/lewishome/software.html (visited Jan 7, 2002).
Linhart YB, Mitton JB, Sturgeon KB, and Davis ML, 1981. Genetic variation in space and time in a population of ponderosa pine. Heredity 46:407–426.
Lorimer CG, 1993. Causes of the oak regeneration problem. USDA For Serv Gen Tech Rep SE-84. Washington, DC: United States Department of Agriculture; 25 p.
McGuire M, Stevens J, and Potter-Witter K, 1999. Assessing scarcity of the north central veneer log resource. North J Appl For 16:160–166.
Mitton JB, Latta RG, and Rehfeldt GE, 1997. The pattern of inbreeding in Washoe pine and survival of inbred progeny under optimal environmental conditions. Silvae Genet 46:215–219.
Montalvo AM, Conard SG, Conkle MT, and Hodgskiss PD, 1997. Population structure, genetic diversity, and clone formation in Quercus chrysolepis (Fagaceae). Amer J Bot 84:1553–1564.[Abstract]
Morsink WAG and Pratt PD, 1984. Shumard Oak, Quercus shumardii, in Essex County, Ontario. Can Field Nat 98:470–478.
Murcia C, 1995. Edge effects in fragmented forests: implications for conservation. Trends Ecol Evol 10:58–62.
Neale DB, 1985. Genetic implications of shelterwood regeneration of Douglas-fir in southwest Oregon. Forest Sci 31:995–1005.
Nyland RD, 1992. Exploitation and greed in eastern hardwood forests. J Forest, 90:33–37.
Palmer EJ and Steyermark JA, 1935. Quercus x mutabilis Palmer & Steyerm. Ann Mo Bot Gard 22:521.
Parker GR and Leopold DJ, 1983. Replacement of Ulmus americana L. in a mature east-central Indiana woods. B Torrey Bot Club 110:482–488.[CrossRef]
Parker GR, Leopold DJ, and Eichenberger JK, 1985. Tree dynamics in an old-growth, deciduous forest. Forest Ecol Manag 11:31–57.
Petty RO and Jackson MT, 1966. Plant communities. In: Natural features of Indiana (Lindsey AA, ed). Indianapolis: Indiana Academy of Science; 264–296.
Prentice B, 1927. Forest survey no. 1: Herbert Davis Forestry Farm. Unpublished report to the Department of Forestry and Conservation, Purdue University, West Lafayette, IN.
Pulliam HR, 1988. Sources, sinks and population regulation. Am Nat 132:652–661.[CrossRef]
Queller DC and Goodnight KF, 1989. Estimating relatedness using genetic markers. Evolution 43:258–275.[CrossRef][Web of Science]
Rajora OP, 1999. Genetic biodiversity impacts of silvicultural practices and phenotypic selection in white spruce. Theor Appl Genet 99:954–961.[CrossRef]
Rajora OP and Pluhar SA, 2003. Genetic diversity impacts of forest fires, forest harvesting, and alternative reforestation practices in black spruce (Picea mariana). Theor Appl Genet 106:1203–1212.[Web of Science][Medline]
Rajora OP, Rahman MH, Buchert GP, and Dancik BP, 2000. Microsatellite DNA analysis of genetic effects of harvesting in old-growth eastern white pine (Pinus strobes) in Ontario, Canada. Mol Ecol 9:339–348.[CrossRef][Medline]
Raymond M and Rousset F, 1995a. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J Hered 86:248–249.
Raymond M and Rousset F, 1995b. An exact test for population differentiation. Evolution 49:1280–1283.[CrossRef][Web of Science]
Roberds JH and Conkle MT, 1984. Genetic structure in loblolly pine stands: allozyme variation in parents and progeny. Forest Sci 30:319–329.
Schmidtling RC and Hipkins V, 1998. Genetic diversity in longleaf pine (Pinus palustris): influence of historical and prehistorical events. Can J For Res 28:1135–1145.[CrossRef]
Schwarzmann JF and Gerhold HD, 1991. Genetic structure and mating system of northern red oak (Quercus rubra L.) in Pennsylvania. Forest Sci 37:1376–1389.
Simon JP, Payette Y, and Longpre MH, 1995. Comparative analysis of the genetic composition of canopy and juvenile sugar maple individuals (Acer saccharum) in an old-growth forest in southern Quebec as related to anthropogenic disturbance. Can J For Res 25:743–752.
Smith WB, Vissage JS, Darr DR, and Sheffield RM, 2001. Forest resources of the United States, 1997. Gen Tech Rept NC-219. St. Paul, MN: United States Department of Agriculture, Forest Service, North Central Research Station; 190 pp.
Smouse PE, Dyer RJ, Westfall RD, and Sork VL, 2001. Two-generation analysis of pollen flow across a landscape. I. Male gamete heterogeneity among females. Evolution 55:260–271.[CrossRef][Web of Science][Medline]
Sork VL, Davis FW, Smouse PE, Apsit VJ, Dyer RJ, Fernandez-M J, and Kuhn B, 2002. Pollen movement in declining populations of California Valley Oak, Quercus lobata: Where have all the fathers gone? Molecular Ecology 11:1657–1668.[CrossRef][Medline]
Sork VL, Huang S, and Wiener E, 1993. Macrogeographic and fine-scale genetic structure in a North American oak species, Quercus rubra L. Ann Sci For 50(suppl.):261–270.
Spetich M, Parker G, and Gustafson E, 1997. Spatial and temporal relationships of old-growth and secondary forests in Indiana. Natural Areas Journal 17:118–130.
Steinkellner H, Fluch S, Turetschek E, Lexer C, Streiff R, Kremer A, Burg K, and Glossl J, 1997. Identification and characterization of (GA/CT)n—microsatellite loci from Quercus petraea. Plant Mol Biol 33:1093–1096.[CrossRef][Web of Science][Medline]
Streiff R, Ducousso A, Lexer C, Steinkellner H, Gloessl J, and Kremer A, 1999. Pollen dispersal inferred from paternity analysis in a mixed oak stand of Quercus robur L. and Q. petraea (Matt.) Liebl. Molec Ecol 8:831–841.[CrossRef]
Streiff R, Labbe T, Bacilieri R, Steinkellner H, Glossl J, and Kremer A, 1998. Within-population genetic structure in Quercus robur L. and Quercus petraea (Matt.) Liebl. assessed with isozymes and microsatellites. Molec Ecol 7:317–328.[CrossRef]
Weir BS, 1996. Genetic Data Analysis II. Sunderland, MA: Sinauer.
Weir BS and Cockerham CC, 1984. Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370.[CrossRef][Web of Science]
Wright S, 1943. Isolation by distance. Genetics 28:114–138.
Wright S, 1946. Isolation by distance under diverse systems of mating. Genetics 31:39–59.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||