Regional patterns of local diversity of trees: associations with anthropogenic disturbance

Pores~~dogy Management ELSEVIER

Forest Ecology and Management 93 (1997) 33-44

Regional patterns of local diversity of trees: associations with anthropogenic disturbance Martin A. Stapanian a, David L. Cassell b, Steven P. Cline b** a US Bureau of Land Management, 200 SW 35th Aue., Coruallis, OR 97333, USA b US Environmental Protection Agency. 200 SW 35th Ape., Comallis, OR 97333, USA

Accepted 23 September 1996

Abstract We useda probability-basedsamplingschemeto survey the forestedlandsof 14 statesin five regionsin the US (California, Colorado,and parts of the Southeast,Mid-Atlantic, and Northeast)from 1990to 1993.Using a nationally consistent plot design, we evaluated the local diversity of trees over 2.5 cm in diameter at breast height (dbh) at 780 l/ 15ha plots nationwide by measuring the plot-level species richness (RI. Visually evident anthropogenic disturbances (e.g. artificial regeneration, logging, grazing by livestock, and prescribed burning), if any, were recorded on each plot. We classified plots with visually evident anthropogenic disturbance as ‘disturbed’ and the remaining plots as ‘undisturbed’. In each of the five geopolitical regions, we quantified the difference in mean R between disturbed and undisturbed plots. With the exception of Colorado (5%), between 34 and 55% of forested lands in each region had recorded anthropogenic disturbances. Mean R was significantly higher for undisturbed areas than for disturbed areas in the Northeast and Southeast, with the hugest differences occurring in the Southeast. Mean R was greater in undisturbed areas than in disturbed areas in most forest cover types for all regions. These differences were greatest in the loblolly pine (Pinus tuedu), oak (Quercus spp.)-hickory (Curya spp.), and oak-pine forest types of the Southeast. The only group for which mean R was significantly greater in disturbed areas was the mixed western hardwoods in California. As expected from previous studies, significant differences between regions in mean R were observed, in both disturbed and undisturbed areas. This study bridges an important gap between site-specific forest studies and remote-sensing studies of the forests of a region. We discuss (1) why combining site-specific studies is not appropriate in most cases for rigorous testing at the regional level and (2) how data for some important site-specific variables are not available from most remotely-sensed data sets. The widespread presence of anthropogenic disturbances in most regions, notably the cutting and planting of pine plantations in the Southeast, is associated with generally lower local species richness of trees. The results warrant further investigation at the regional level in light of recent empirical studies on diversity and ecosystem stability. 0 1997 Elsevier Science B.V. Keywords:

Species richness; Local; Regional; Trees; Disturbance; Silviculture: United States: Probability sampling

1. Introduction

* Corresponding author. Tel.: (541)754-4.599; fax: (54 I )7544338; e-mail: [email protected]. 0378-l 127/97/$17.00 Published by Elsevier Science B.V. PII SO3781 127(96)03944-S

The conservation of biotic diversity is a global concern. In particular, the effects of human activities (e.g. landscapemodification) on speciesdiversity is

an issue that has considerable ecological interest from both a theoretical and applied standpoint. Historically high extinction rates are associated with human activities (Wilson and Frances, 1988). Landscape modification, characterized by landscape simplification and habitat fragmentation, is a well-documented and cumulative effect of human activity (e.g. Wilcove et al., 1986; O’Neill et al., 1988: Saunders et al., 1991; Noss and Csuti, 1994). Over longer periods of time. accelerated rates of climate change could increase extinction rates, especially in fragmented and simplified landscapes (Peters and Darling, 1985). Empirical studies (Hurd et al.. 1971: McNaughton, 1977, 1985; Tilman, 1988: Frank and McNaughton, 1991; Ewe1 et al., 199 1: Tilman and Downing, 1994) support the biodiversity-stability hypothesis concerning ecosystem stability (McNaughton, 1977). Under this hypothesis, ecosystems with greater species diversity are more resilient to environmental disturbances. Diverse systems, it is argued, are likely to contain some species that can thrive during the perturbation. These species would, in effect, compensate for those members of the community that are reduced or eliminated by the disturbance (Pimm, 1984; Ehrlich and Wilson, 1991: Lawton and Brown, 1993). The effectiveness of conservation strategies cannot be assessed reliably without statistically sound. quantitative estimates and trends of diversity at the regional or national level. Such estimates are lacking for most taxa in the United States, and when made, are based on data compiled from numerous studies with unrelated objectives (Langer and Flather. 1994; LaRoe et al., 1995). Such compilations include inconsistencies and unquantified biases of unknown significance, since estimates of species diversity are strictly comparable only when based on the same sampling area and collection methods (Peet, 1974). In this paper. we use a probability-based sampling scheme to survey the forested lands of five geopolitical regions (each 1S-4.0 X 10’ km’) in the United States. Using a nationally-consistent plot design and field methods, we evaluate local diversity of trees on 780 plots of equal area. The design and sampling scheme enables us to estimate rigorous population parameters for each region. We quantify the proportion of forested lands in each region that has visually

evident anthropogenic disturbance of v arious types (‘disturbed’). For each region we test the significance of (I) the difference in tree species richness between disturbed and ‘undisturbed’ forested lands. and (2) the difference in tree species richness hetween disturbed and undisturbed areas for the major forest types. Tree species richness is only one cl+ ment of forest biodiversity. Howevet, trees are ;L logical starting point, given their ecological domnance (Packham and Harding. 1982). influencr on the forest environment and other organisms (Hunter. 19901, and economic importance (Smith. 1986). Further, species richness is considered by \ome biolo. gists to be the simplest. most practical. and most objective measure of species diversity (e.g. Poorc. 1962; Whittaker. 1965. 1972: Greig-Smith, IV7 I : Hurlbert, 1971: Peet. 1974; Debinski and Brussard. 1991). 2. Methods 2.1. Surnpling design artd plot layout The Forest Health Monitoring (FHM) program. a large-scale synoptic forest survey system. was the source of our data. FHM is an inter-agency government project which comprehensively samples the forested area of each participating state (Alexander and Barnard, 1993). FHM’s objectives include the monitoring and statistical estimation of trends, changes, and current status in indicators of the condition of the country’s forest resources. on a regional and national scale (Palmer et al., 199 I). Tree species diversity is just one of those indicators. The basis of the FHM sampling design (Cassell, 1993; Schreuder and Czaplewski, 1993) is the Environmental Monitoring and Assessment Program (EMAP) design (Stevens, 1994; Stehman and Overton. 19941, which uses an equal-area triangular grid with points approximately 27 km apart. This design permits statistical estimation using traditional sampling theory: Horvitz-Thompson estimation with Yates-Grundy variance estimates (Cochran, 1977). The target sampling density of the forested area in each participating state is achieved after 4 years of sampling, using a rotating panel design (Cassell, 1993). Population parameters can be estimated after a minimum of one season of sampling.

M.A. Stapanian

et al. / Forest Ecology

Each forested ground plot located from the FHM sampling system is a circle of 1 ha, within which are four fixed-radius subplots of radius 7.32 m (24 ft) (Scott, 1993). The combined area of the four subplots is l/1.5 ha. Measurements for trees having diameter at breast height (dbh) of over 12.7 cm are taken on these subplots. Within each subplot is a circular microplot of radius 2.1 m (6.8 ft), from which data for trees with dbh between 2.54 and 12.7 cm are collected. Only trees of over 2.54 cm dbh are considered in this study. Statistical evaluations of the FHM plot design (Riitters et al., 1991; Lewis and Conkling, 1994) have demonstrated using sampling theory formulae (Cochran, 1977; Cassell, 1992) that the multi-tiered plot layout is well suited to the variety of current FHM indicators. 2.2. Field methods and descriptions

of regions

We sampled 780 plots from five regions of the United States. The Northeast region consistedof the forested areasof Maine, Vermont, New Hampshire, Rhode Island, Connecticut, and Massachusetts.The plots were in the Northeastern Highlands and Northeastern Coastal Zone ecoregions (Omernik, 1987, 19951. The Mid-Atlantic region consisted of the forested areas of Virginia, Maryland, New Jersey, and Delaware. The plots were located predominantly in the Northern Piedmont, Central Appalachian, and SoutheasternPlains ecoregions.The Southeastregion consisted of the forested areas of Georgia and Alabama, which were predominantly in the Southeastern Plains and Southwestern Appalachian ecoregions. Plots in Colorado were predominantly in the Southern Rockies and the Colorado Plateau ecoregions. Plots in California were mainly in the Sierra Nevada, Southern and Central California PIains and Hills, and Coast Range ecoregions. Data were collected during the summersof 1990 through 1993, including 4 years in the eastern regions and 2 years in Colorado and California. Data were recorded for only that portion of each plot in which land use was classified in the field asforested, according to standard protocols used by the US Forest Service (Tallent-Halsell, 1994). The list of speciesthat are consideredtrees in FHM may also be found in Tallent-Halsell (1994). Forest cover type(s) (e.g. oak (Quercus spp.)-hickory (Caya spp.) for-

and Management

93 f 1997) 33-44

35

est) in each plot was (were) determined in the field, based on tree composition, according to standard protocols from the US Forest Service (TallentHalsell, 1994), and the classification schemeby Eyre (1980). Nomenclature of tree specieswas according to Harlow and Harrar (1969) and Harlow et al. (1991). On each plot, up to three types of visually evident disturbance were recorded per forested condition class (Scott and Bechtold, 1995; Tallent-Halsell, 1994). This was done in accordancewith the definition of White and Pickett (1985, p. 7) of disturbance as “any relatively discrete event in time that disrupts ecosystem, community, or population structure and changesresources,substrateavailability, or the physical environment”. Consequently, disturbance provides no a priori inference about the condition or health of ecosystemproperties. We used disturbance information to classify each plot as either ‘undisturbed’ (no disturbance recorded) or ‘disturbed’ (at least one disturbancerecorded). Disturbed plots were further divided into ‘anthropogenically disturbed’ and ‘naturally disturbed’. Types of ‘anthropogenic’ disturbancesincluded artificial regeneration, harvesting, cutting, thinning, prescribed burning, application of fertilizer or herbicide, grazing by domestic livestock, and construction. Types of ‘natural’ disturbances included alterations by weather, disease,insects. and wildfire, as well as natural reversion to forest from unforested plots. Natural disturbances were recorded on too few plots (n = 42, or 5.4% of the total number of plots) to be analyzed separately. The 42 plots with natural disturbances were reclassified rather than omitted from the analysis. Consequently, in subsequentanalyses ‘disturbed’ plots are anthropogenically disturbed. Since ten naturally-disturbed plots also had at least one anthropogenic disturbance, they were assignedto the ‘disturbed’ category. The remaining 32 plots were assignedto the ‘undisturbed’ category. We found no evidence (t-tests, P > 0.49 for all regions) that the small number of plots with natural disturbances had any impact on our study conclusions for (1) all plots, (2) the subsetof undisturbed plots, and (3) the subset of anthropogenically disturbed plots. Values of local speciesrichnessare strictly comparable only when basedon the samesampling area

using the same sampling protocol. Not all FHM plots are 100% forested, due to land use differences and physical restrictions. Therefore, a transformation of species counts was necessary. We define local (plotlevel) species richness R as R = S/Z, where S is the number of tree species on the study plot, and Z is the proportion of the sampling area that was in forested conditions. We restricted our analyses to those plots in which Z 2 0.5. Although the relationship between species count and area is often nonlinear and dependent upon habitat heterogeneity and isolation (e.g. MacArthur and Wilson. 1963, 1967; Simpson, 1964; Cook, 1969; Brown, 1971), previous FHM research (Alexander et al., 1994) indicates that the linear model is an excellent first-order approximation for tree species on these plots when Z 2 0.5. In this study, 84.5% of the plots were fully forested, so R = S in the vast majority of cases. Typically, FHM and EMAP use cumulative distribution functions (CDFS) of the sample data to describe distributional features and to analyze the data (e.g. Forest Health Monitoring, 1994; Larsen et al.. 1994). While CDFs are more useful than sample means in visualizing the behavior of the entire distribution and in evaluating the tail behaviors, they are less widely used than tests of means by forest ecologists. Since the CDF analyses of these data yielded the same statistical results as the analyses of variance (ANOVAS) performed in this paper. we did not present analyses of CDFs.

3. Results Regional spatial coverage of local tree species richness is broader in the three eastern regions than in the two western regions (Figs. 1 and 2). This is because (1) data for four seasons had been collected in the eastern regions versus data for two seasons in the western regions and (2) a large proportion of the areas of Colorado and California is nonforested lands. In Colorado, the nonforested areas correspond mainly with the Western High Plains or Southwestern Table Lands ecoregions (Omemik, 1987, 1995). In California, these areas correspond mainly with the Northern Basin and Range, Southern Basin and Range, and Central California Valley ecoregions.

Fig. I. Species regions.

richness

of trees in sample

plots in three eastern

When the entire data set is considered, significant (ANOVA; d.f. = 4. 775; P < 0.01) differences among regions in mean local speciesrichness(mean R) were observed (Table 1). This result is consistent with a visual inspection of Figs. 1 and 2. and is expected. Values of mean R were significantly different for all pairwise comparisonsof regions (Table 1, Scheffe’s test, P < 0.05) except between the Southeast and Northeast and between Colorado and California. The pooled number of species found in each region (regional speciesrichness)(Table I ) exhibited the following geographic patterns: (1) an increase from the Southeast to the Northeast, (2) the eastern regions contained more species than the western regions, and (3) California contained more species than Colorado. Qualitatively, these are the same as patterns found by Currie (1991) and Currie and Paquin (1987) for speciesrichness of trees in North

M.A. Stapanian

et al. / Forest

Ecology

and Management Table 1 Summary the US

31

93 (1997133-44

statistics

for species richness

of trees in five regions

Region

Pooled no. species

n

Mean

Northeast Mid-Atlantic Southeast Colorado California

60 79 94 17 42

215 126 275 65 99

6.46 7.70 6.07 2.76 2.86

R (s) (2SO)b (3.02)a (3.63)b (1.24)~ (1.77)~

of

R,,, 14.0 14.0 17.5 6.0 10.4

n, number of plots; R, local species richness; s, standard deviation; R,,, , the maximal value of local species richness. Values of mean R followed by the same letter were not significantly different ( P > 0.05, Scheffe’s test).

-bw0 Spmci a,

RI chnert

\

n w n 0

Fig. 2. Species California.

richness

> 10 > I .sd <- TO > 1 .“d <- 7 > t .D# 4- 1 <- f

of trees in sample plots in Colorado

and

America. This geographicpattern was not evident for values of mean R (Table 1). The proportions of forested area in each region in which types of disturbance occurred are shown in Table 2. Some plots had more than one type of disturbance. Therefore, the sum of the proportions of area in Table 2 may not equal the proportion of disturbed plots in each region. Colorado’s forested area had by far the smallest proportion that was anthropogenically disturbed (approximately 5%) of all regions (Tables 2 and 3). For the remaining regions, the percentage area disturbed ranged from approximately 34 to 55% (Tables 2 and 3). The Southeast had the highest proportion of area impacted by silvicultural practices, including artificial regeneration.Theseareaswere dominated by loblolly pine (Pinus tueda) and shortleaf pine (Pinus echinata). Pine plantations accounted for all but one of the planted stands.In artificially regeneratedplots, R was typically less than or equal to 3. California had approximately the sameproportion of area disturbed

as the Southeast.However, California had the highest proportion of forested area impacted by grazing. Mean R was significantly greater in the undisturbed plots than in the disturbed plots in the Northeast (ANOVA, F = 4.84, P = 0.029) and Southeast (ANOVA, F = 63.85, P < 0.01) (Table 3). In the remaining regions, mean R was also greater in undisturbed plots, but not significantly so. With the exception of Colorado, the total number of species recorded in each region was greater for the subsetof undisturbed plots than for the subset of disturbed plots (Table 3, values of T* ). In the undisturbed

Table 2 Proportions of forested areas in which disturbances (including artificial regeneration) occurred. Individual plots may have more than one type of disturbance. Values are expressed as the proportion of the total forested area in the region Disturbance

type

Harvesting/cutting Prescribed burning Planting b Other e Grazing Disease/insects r Weather/wildfire r

Region * NE

MA

SE

CO

CA

0.248 0.004 0.022 c 0.018 0.000 0.004 0.004

0.127 0.000 0.109 0.036 0.030 0.018 0.091

0.295 0.048 0.190 0.052 0.032 0.000 0.008

0.000 0.000 o.ooo 0.000 0.016 0.033 0.000

0.226 0.000 0.050 d 0.026 0.161 0.000 0.133

a NE, Northeast; MA, Mid-Atlantic; SE, Southeast; CO, Colorado; CA, California. b Artificial regeneration. ’ Stand origin was not recorded for two plots. d Stand origin was not recorded for one plot. ’ Other silvicultural practices (e.g. herbicide application). f Not considered anthropogenic disturbances.

areas, the values of mean R in the Mid-Atlantic and the Southeast were significantly greater than the values of mean R in the other regions (Scheffe’s test, P < 0.05, Table 3). The Northeast had a significantly greater value of mean R than either Colorado or California. Significant differences between regions were also observed in the disturbed areas (Table 3). Mean R for disturbed areas was greatest in the Mid-Atlantic. followed by the Northeast. Mean R was significantly greater in the Southeast than in either Colorado or California. For the major forest cover types in each region, there were substantial differences in f I ) the proportion of total forested area disturbed, and (2) the difference in species richness between disturbed and undisturbed areas (Table 4). A major forest type had to contribute more than 5% of the total forested area of a region in order to be considered in Table 4. Individual plots often contained more than one forest type. Table 4 shows only the results for plots in which one forest type comprised at least 50% of the area of the plot. In the Northeast, the maple ( Acrr spp.)-beech (Fugus spp.)-birch (Betula spp.) type had the greatest proportion of that region’s total forested area. in both the disturbed and undisturbed subsets of plots (Table 4). The forested area in the Mid-Atlantic region was dominated by the oak-hickory forest type. Only three other forest cover types contributed over 5% of the total forested area in the Mid-Atlantic. The remaining regions had five or six types. The loblolly-shortleaf pine and oak-pine forest cover

types had the largest proportions of the forested area of the Southeast in disturbed plots and in the entirc population. When considering only the undisturbed plots. however. the oak-hickory and oak-pine forest cover types dominated the total forested area of the Southeast. The forested areas of California and Colorado were dominated by western hardwoods and major pine ( Pizzas spp.) types. Disturbed areas of the following forest cover types comprised at least 10% of the total forested area in their respective regions (Table 4): maple-beech-hirch and eastern spruce-fir (Northeast); oak-hickory (Mid-Atlantic); loblolly-shortleaf pine. oak-pine, and longleaf ( Pints /~utust~i.~)-slash pine ( Pirni.\ dliottii) (Southeast): and western hardwoods :md major pine (California). Disturbed areas of the loblolly-shortleaf pine forest type made up 2 I .7% OJ’ the total forested area of the Southeast. This was the largest proportion of the total forested area that was disturbed for any forest type in any region. ‘This forest type comprised approximately 39.5% of the disturbed forested area in the Southeast. The largest values of mean species richness were observed for the oak-pine. oak-hickory. and oak-gum t N\..F.sLIspp.)--cypress (Tarodiunr spp.) types in the eastern regions (Table -1). In Colorado and California, the Douglas fir ( Pseuhtsugcr mrnrirsii ). mixed conifer, and major pine types had the highest values of mean R. Mean R was statistically significantly greater in undisturbed plots than in disturbed plots in the Southeast in (1) the loblolly-shortleaf pine type ( F,.,, = 8.32. P = 0.005) and (2) the oah (QUCYCMS spp.)-hickory (Cut-y spp.) type ( E-,,, i =

Table 3 Summary statistics for local species richness of trees in plots which had detectable disturbance by humans (“disturbed“) did not (“undisturbed”). The total number of species in each region for these two subsets are given in the respective Region

Northeast Mid-Atlantic Southeast Colorado California

Undisturbed

plots

II

T

Mean

138

55

87

74 X6 17 36

(?.43)b (2.95)a 7.94 (3.40)a 2.77 (1.26)e

I I-4 61 53

Disturbed R(s)

6.73 7.93

9.86

(1.79)e

For explanation of abbreviations see Table 1. Values of mean R followed by the same letter were not significantly

plots

Rm.. .

11

T

Mean

13.0

43

17.5 6.0

77 39 Ihl -l

56 74

8.0

36

il

5.96 7.20 3.74 2.50 2.85

I-t.0

different

and m plots which coh.tmna labeled ?

I7

( P > 0.05. Scheffe’s

test)

R (s)

R- .

(2.56)~

14.0

(3.15fab

12.0 16.0 4.0 IO.4

(3.19)d

1 l.OOk (I .76k

--.

---

M.A. Stapaniarr

93 f 1997) 33-44

39

Table 4 Summary statistics for the forest types constituting at least 5% of each region’s forested area. An ANOVA R for disturbed versus undisturbed piots for each forest type in all regions except Colorado. Abbreviation: forested area of a region comprised of the forest type

was performed on the values of Prop. = proportion of the total

Region/type

Northeast Maple-beech Eastern spruce-fir White pine Oak-pine Oak-hickory

All forested

areas

n

R

91 64 21 10 10

Mid-Atlantic Oak-hickory Loblolly-shortleaf Oak-pine Maple-beech

pine

Southeut Loblolly-shortleaf Oak-pine

pine

Mean

6.857 5.969 6.265 7.403 9.45 I

et al. /Forest

Ecology

and Management

Undisturbed

areas

s

Prop.

n

R

2.63 1 2.270 2.558 2.474 2.362

0.423 0.310 0.121 0.048 0.045

51 42 18 8 7

Mean

Disturbed

areas

s

Prop.

II

Mean

7.156 6.270 6.667 7.470 9.714

2.346 2.199 2.569 2.799 1.976

0.241 0.205 0.039 0.032

40 22 9 2 3

2.790 2.924 4.97 I 2.345

0.448 0.096 0.093 0.040

* * 3.129 + 2.721

*

R

s

Prop.

6.475 5.394 5.460 7.133 8.838

2.94 1 2.342 2.480 0.188 3.459

0.182 0.105 0.039 0.009 0.013

19 7 4

8.972 6.429 9.524 4.000

3.090 3.823 1.433

0.136 0.06 I 0.035 0.009

0.083 0.122

57 31

4.616 7.652 +

3.047 4.293

0.217 0.115

3.771 2.485 2.559

0.121 0.024 0.063

20 30 15

7.580 4.438 8.456

4.012 3.127 3.616

0.07’ 0.110 0.052

1.414

0.029 0.000 0.000 0.028 0.000

70 18 16 6

9.024 6.498 10.098 5.661

2.852 3.193 4.318 2.25 I

0.583 0.157 0.128 0.049

51 II 12 5

9.043 6.542 10.298 6.000

80 62

5.241 8.541

3.207 3.615

0.301 0.237

23 31

6.790 9.431

53 37 33

9.332 4.716 8.940

4.066 3.041 3.066

0.192 0.134 0.1 15

33 18

10.395 5.905 9.343

Colorado Major pine Western hardwoods Western spruce-fir Western softwoods Douglas fir

20 19 13 8 4

3.451 1.961 3.252 2.082 3.850

1.510 0.868 1.000 0.667 1.090

0.32 1 0.296 0.188 0.120 0.057

18 19 13 6 4

3.508 1.961 3.252 1.930 3.850

I .550 0.868 1.000 0.63 1 1.090

0.292 0.296 0.188 0.093 0.057

3.000 2.537 -

California Western hardwoods Major pine Mixed western conifers Western softwoods Western spruce-fir Douglas fir

33 22 14 11 12 6

2.51 I 3.206 5.543 1.273 2.248 4.278

1.307 1.694 3.111 0.786 1.546 2.886

0.327 0.219 0.127 0.124 0.120 0.062

2.013 * 3.000 4.670 1.500 2.225 5.167

1.231 1.633 1.917 0.837 1.718 2.560

0.153 0.107 0.091 0.067 0.090 0.039

2.925 * 3.378 7.115 1.000 2.317 2.500

‘.

+ 0.05
Oak-hickory Longleaf-slash Oak-gum-cypress

PiO.01:

pine

P
6.61, P = 0.013) (Table 4). Mean R was marginally significantly (F, 60 = 3.80, P = 0.056) greater in undisturbed plots’in the oak-pine type in the Southeast. In California, disturbed plots had a significantly (Ft.,, = 4.41, P = 0.043) larger mean R than undisturbed plots in the mixed western hardwoods forest type. For the remaining forest cover types within each region, the difference in mean R between

=

0.759

1.251 I.797 4.393 0.707 1.155 3.536

0.171 0.1 I2 0.035 0.056 0.030 0.022

disturbed and undisturbed plots was not statistically significant (Table 4, ANOVA, P > 0.10 in all cases).

4. Discussion

and conclusions

Recent efforts to summarize the status and trends of biodiversity in the USA (Langer and Flather,

1994; LaRoe et al., 1995) suggest that quantitative estimates of regional population parameters are lacking. This study is the first of which we are aware that quantifies with known confidence (1) local species richness of trees in any region, (2) differences in local tree species richness for anthropogenically disturbed and undisturbed areas at the regional level, (3) differences in local tree species richness for disturbed and undisturbed areas of individual forest types in each region, and (4) proportions of total forested area in each region that are disturbed and undisturbed for each forest type. Although we could not calculate appropriate confidence intervals, this study is the also the first of which we are aware that estimates the difference in the regional tree species richness between disturbed and undisturbed areas. Therefore, this study bridges an important gap between site-specific forest studies and remote-sensing studies of the forests of a region. As discussed below, combining site-specific studies is not appropriate for rigorous testing at the regional level in most cases. Conversely, many site-specific data (e.g. disturbance types and local species richness) are not available from most remote1 y-sensed data sets. When collected over regular time periods, data from studies such as this can be used for rigorously monitoring species richness at the regional level. Concerns of widespread threats to biodiversity (e.g. United States Environmental Protection Agency, 1990; Raven and Wilson, 1992) underscore the importance of monitoring and quantifying species richness at the regional scale. The design and scope of FHM enables one to make regional conclusions about forests in the US because (1) it uses a probability-based sampling scheme, (2) the number of primary sampling units is large. (3) sampling effort is the same at each site, reducing problems associated with species areacurves and (4) data are collected by the same techniques at all sites. reducing measurement error. Further, the statistical design enables one to estimate population parameters with known confidence. There is a vast literature on the pattern and process of response of local plant diversity to anthropogenic disturbance in forests (e.g. Grime, 1979; Oliver, 1981: Hunter, 1990). These studies suggest a wide array of positive and negative responses of local diversity to disturbance under various conditions.

However, they cannot be used individually or collectively to estimate population parameters at a regional level because they (1) are based on non-probability samples, (2) have insufficient sample sizes from a regional perspective, and (3) are site- or landscapespecific. The differences in mean local species richness among regions are not surprising. Further, the values of regional species richness found in this study were considerably less than those found by Currie (1991) and Currie and Paquin (1987). This result was also expected. Fewer species are considered ‘trees’ in FHM than by Little (197 1). which Currie and Paquin ( 1987) used to produce their geographic isoclines of species richness. In particular, some mid-canopy and multiple-stemmed species (e.g. Kulmiu Iat(fdi?lirr and Rhododtwdum spp.) were listed as ‘trees’ by Little (1971) but not by FHM. Further. Currie and Paquin’s (Currie and Paquin, 1987) isoclines were derived from literature values of the ranges of individual species.covering all possiblehabitats. and including uncommon species.In contrast. our data were from surveys of plots of l/15 ha. in which land use was strictly forested. and was not designed to find rarr species(Scott and Bechtold, 1995). However. our data for regional speciesrichness exhibited qualitatively the same geographic patterns as Currir and Paquin ( 1987) and Currie ( 1991). In order for local disturbancesto translate rnto a regional pattern, disturbance must be widespread regionally and the association between disturbance and diversity must be consistent locally. We found abundant and widespreadevidence of anthropogenic disturbance (34-55% of the total forested area in all regions except Colorado) in a large, probability-based sampleof forested land in the USA. Anthropogenic disturbance was associatedwith statistically signitlcantly lower mean local species richness in the Southeast and Northeast. Harvesting and artificial regeneration occurred on 3 larger proportion of the forested area in the Southeast than in any other region. Further. the Southeasthad the largest difference of any region between the values of mean local species richness of its disturbed and undisturbed plots even when examining single forest cover types. These differences were most obvious in the loblolly-shortleaf pine, oak-pine, and oak-hickory forest cover types in the Southeast.

M.A. Stapanian

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Clearcutting and subsequent artificial regeneration of pine plantations is practiced widely in the Southeast and is expected to expand in the future (USDA Forest Service, 1988; Alig et al., 1990; Boyce and Martin, 1993). Millions of acres of hardwood forests in the Southeast have been converted to agriculture and pine plantations since the 1930s particularly in the oak-pine uplands and the mixed hardwood bottom lands in major river valleys (Smith and Linnartz, 1980 and references therein). Most of these plantations are loblolly pine. Competing woody vegetation is typically suppressed in the established plantation by controlled burning (Richter et al., 1982; Binkley et al., 19921, application of synthetic hormones (Walker, 19801, and other techniques (Swindel et al., 1984). As the planted pines become more dominant, diversity trends in maturing plantations “are expected to be less ecologically favorable” (Swindel et al., 1984, p. 19). Other studies suggest that when mixed-species forests are cleared and replaced by pine plantations, the result is a locally-impoverished flora and fauna relative to the ‘original’ forest (Atkeson and Johnson, 1979; Repenning and Labisky, 1985; Childers et al., 1986; Felix et al., 1986; Skeen et al., 1993). In contrast to the Southeast, there was an inconsistent association between mean species richness and disturbance among the forest types in California. Mean R was significantly greater in disturbed than in undisturbed plots in one forest type (mixed westem hardwoods) in California. California had approximately the same proportion of area disturbed by human activity as the Southeast. California had a higher proportion of forested areas used for grazing livestock than any other region. Further study is needed in order to quantify the regional effects of specific disturbances in a widespread probability sample. At the local level, structurally simple forests and forests with few species have been shown to be less tolerant of biotic stresses such as disease and insect attacks (e.g. Schmidt. 1978; Knight and Heikkenen, 1980). Other studies (e.g. Willson, 1974; Harper, 1977; Deuser and Shugart, 1978; August, 1983; Bersier and Meyer, 1995) suggest that simple forest systems, such as even-aged monocultures or systems in which certain species are removed, provide ‘quality’ habitat for fewer wildlife species than do more

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complex stands. However, the impacts of silviculture and artificial regeneration are numerous and complex. Simplification of the system may not be the only, or even most important cause of increased local instability (Pimm, 1984). The interactions between diversity and stability at the regional level are poorly known. Although this study considered only data for trees, the extent of anthropogenic disturbance and associated decrease in species richness in US forests warrant further investigation from a regional biodiversity-stability standpoint.

Acknowledgements We thank D.J. Currie and C.C. Smith for comments and suggestions on two earlier versions of this paper. Comments on earlier drafts were also provided by D. Bradford, T. Lather, B. McCune, S. Franson, K. Killingbeck, P. Owsten, J. Tappeiner, A. Liston, R. Alverts, D. White, F. Andersson, and three anonymous reviewers. This study was funded by the Forest Health Monitoring Program (FHM). an interagency program. Participating agencies include the USDA Forest Service, US Environmental Protection Agency, and the USDI Bureau of Land Management. The research described in this paper has been subjected to review by some of the agencies participating in FHM. However, it does not necessarily reflect the views of any of the agencies. No official endorsement should be inferred.

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