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Keywords:

  • Disturbance;
  • Forest regeneration;
  • Gas pipeline;
  • Habitat fragmentation;
  • Power line

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Question

Does the creation of linear canopy openings in a lowland Atlantic tropical forest cause edge effects on understorey treelets, saplings and shrubs?

Location

União Biological Reserve, Rio de Janeiro state, southeastern Brazil (22°25′30″S, 42°02′30″W).

Methods

We sampled shrub, sapling and treelet communities at forest edges adjacent to two linear canopy openings (gas pipeline and power line) and in forest interiors far from any edge. Rarefaction curves were plotted to assess differences in species richness among treatments. Variation partitioning was used to assess main drivers of species composition and abundance. Partial Mantel correlations were calculated to verify edge effects controlling for effect of space on the abundance of Euterpe edulis palm and two ecological groups. For this purpose, species were classified either as disturbance-tolerant or disturbance-sensitive.

Results

Edge effects of linear canopy openings affect understorey species composition, but not species richness. Disturbance-tolerant species were more abundant in edges than in forest interiors, while disturbance-sensitive species did not show differences among treatments. However, the late-successional palm Euterpe edulis, which is abundant in forest interiors, was significantly less common at edges. Response to edge effects was stronger among treelets than shrubs and saplings.

Conclusions

The creation of infrastructure-related linear canopy openings caused edge effects that significantly affected understorey communities in the studied lowland Atlantic forest remnant. Such effects however were clearly distinct from those found at typical edges of tropical forest fragments.


Nomenclature
APG III

2009

Abbreviations
DBH

diameter at breast height

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Edge effects may be described as changes in resource availability, species interactions and disturbance regimes that occur in the margins of habitat remnants due to the influence of adjacent human-modified habitats (Saunders et al. 1991; Ries et al. 2004; Tabarelli et al. 2004; Fischer & Lindenmayer 2007). In previously undisturbed tropical forests, late-successional tree communities near recently created edges suffer very high mortality due to increased wind damage and altered microclimate conditions, such as increased air temperature and decreased air and soil moisture (Laurance et al. 1998, 2006a). Such trees are not replaced with functionally similar recruits, because increased light availability, altered microclimate and biased seed rain near edges promote the recruitment of early-successional species, as well as the recruitment failure of late-successional ones (Kapos 1989; Laurance et al. 2006b; Melo et al. 2006). The net result is a profound alteration of tropical tree communities near forest edges, which are directed toward early-successional stages because of edge effects (Oliveira et al. 2004; Laurance et al. 2007; Michalski et al. 2007; Tabarelli et al. 2008). Fragmentation and edge effects may also promote the establishment of exotic species and generalist, disturbance-adapted native species (Tabarelli et al. 1999; Laurance et al. 2009). In the long term, these factors may lead to a biotic homogenization of severely disturbed and fragmented tropical forest landscapes, which become increasingly dominated by such disturbance-tolerant species (Lôbo et al. 2011; Tabarelli et al. 2012).

The Brazilian Atlantic Forest, which shelters some of the most species-rich tropical tree communities in the world (Peixoto & Gentry 1990; Martini et al. 2007a), has been reduced to 11.7% of its original cover, and about half the remaining area is <100 m from any edge (Ribeiro et al. 2009). Some edge effects, such as decreased air moisture, may penetrate 100 m inside tropical forest fragments, while others may reach as far as 400 m (e.g. increased wind disturbance; Laurance et al. 2002). Thus, it is expected that most Atlantic Forest remnants are greatly affected by edge effects, with highly deleterious consequences for both the survival and regeneration of late-successional tree species. In the heavily deforested and fragmented Atlantic forest, mean distance between remnants is high (Ribeiro et al. 2009), and thus most forest edges face large clearings; studies have addressed edge effects in such typical situations. On the other hand, forest borders adjacent to deforested corridors have been largely ignored. Tropical forests are especially vulnerable to this specific kind of edge-related disturbance because habitat-specialist, disturbance-sensitive species comprise most of its astonishing diversity (Laurance et al. 2009). Furthermore, linear canopy openings, such as gas pipelines and power lines, may act as large-scale field experiments from which inferences about edge effects can be obtained. Thus, understanding edge effects from linear canopy openings may considerably improve our knowledge on the effects of fragmentation on tropical forests.

In this study, we addressed the question of whether the creation of linear canopy openings causes edge effects on species richness and species composition of Atlantic Forest understorey woody plants. For this, we sampled shrub, sapling and treelet communities at forest edges adjacent to two linear canopy openings (gas pipeline and power line) and in forest interiors far from any edge.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Study area

The study was conducted at the União Biological Reserve (União), located in the state of Rio de Janeiro, southeastern Brazil (22°25′30″S, 42°02′30″W). The reserve was created in 1998 to protect lowland Atlantic Forest remnants and the endangered Golden Lion Tamarin (Leontopithecus rosalia L.). União covers an area of 2548 ha, and the relief is comprised of alluvial plains, small rounded hills and mountain ranges with a maximum height of 376 m a.s.l. The climate is tropical wet. Mean annual precipitation is 1690 mm, with a moderate dry season between April and September (Oliveira 2002), and the mean annual temperature is 22 °C. The vegetation is comprised of lowland Atlantic rain forest (sensu Oliveira-Filho & Fontes 2000). During the last century, before the creation of the reserve, valuable native timbers were harvested from the forests of the formerly called União Farm, and some areas were covered with plantations of Corymbia citriodora (Hook) Hill & Johnson (formerly Eucalyptus citriodora). However, Rodrigues (2004) found that some forest stretches of the reserve have a high basal area and a very high richness of late-successional tree species, both of which are indicative of old-growth forests (Clark 1996).

The reserve is crossed by a gas pipeline and an electrical power line that pass through two distinct linear canopy openings within the forest (Fig. 1). The gas pipeline opening was created in the early 1980s, thus being ca. 25 yrs old by the time sampling was conducted (see 'Introduction' below), and is ca. 25-m wide. This opening is covered by grassy, relatively homogenous vegetation, which rarely exceeds 1 m in height. Vegetation management through manual clear-cutting is done along this canopy opening at least once every year, to prevent the establishment of deeply rooting woody species that would damage the buried gas pipeline. The power line opening was created in the early 1960s, thus being ca. 45 yrs old when sampled. This opening is ca. 100-m wide, and is covered by dense secondary vegetation composed of shrubs and scattered pioneer trees, mainly Cecropia sp. The weedy fern Pteridium arachnoideum (Kaulf.) Maxon forms dense, fairly homogenous, ca. 1.5-m high stands in many parts of the opening. This opening was subjected to annual clear-cutting until the year 2000, to avoid damage to the electricity towers. Furthermore, fire events were reported, as supported by the occurrence of dense stands of P. arachnoideum, an indicator species of fire-disturbed habitats (Martini et al. 2007b). Since 2000, vegetation was allowed to regenerate in some stretches of this canopy opening because the electricity towers there are high enough (e.g. on hilltops) to prevent forest regrowth reaching the wires. This caused the managed area within the canopy opening to decrease by some 40%, from 44.2 to 26.5 ha. Thus, linear canopy openings of the gas pipeline and power line differ in terms of age (25 vs 45 yrs), width (25 vs 100 m) and vegetation cover (grassy vs shrubby).

image

Figure 1. Map of União Biological Reserve. Stars, power line forest edge plots; triangles, gas pipeline forest edge plots; and squares, forest interior plots.

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Sampling

We sampled sapling, shrub and treelet communities in forest edges adjacent to the two linear canopy openings and in forest interiors far from any edge (Fig. 1). We selected 12 sites of mid-slope forest with no evidence of natural or human disturbance. Four of these sites were immediately adjacent to the gas pipeline canopy opening; four close to the power line; and the remaining four were located in forest interior areas at least 400 m distant from any edge (Fig. 1). In each of these sites, a 20 m × 50 m permanent sample plot was established. Gas pipeline and power line plots were placed completely within the forest, with one side close (1–5 m) to an imaginary line between closed-canopy and open areas. While allocating sampling units, we tried as much as possible to standardize the topographic position and forest physiognomy of the sampled areas. The sampling criteria constrained available sites for placing edge plots, in such a way that most plots belonging to the same edge type tended to be clustered in the landscape. Nevertheless, the minimum distance between any two plots was 100 m. All sampled forest edges had a similar, southeast-facing orientation.

We conducted the sampling of understorey communities in 2006. We sampled all treelets with DBH ≥ 5 cm and <10 cm within plots. Saplings and shrubs with DBH ≥ 1 cm and <5 cm were sampled in ten 5 m × 5 m subplots distributed within each plot. For this purpose, each plot was divided into 10 columns of four 5 m × 5 m subplots. In each column, one subplot was randomly assigned. Thus, the total sampled area for treelets (DBH 5–10 cm) was 1.2 ha, and for saplings and shrubs (DBH 1–5 cm) was 0.3 ha. Each individual had its DBH measured and was identified to species level whenever possible.

Statistical analysis

To evaluate whether the sites showed differences in species richness irrespective of differences in plant density (Gotelli & Colwell 2001), we plotted a rarefaction curve of the observed number of species in each treatment (i.e. either gas pipeline, power line or forest interior) as a function of the number of individuals sampled using the software EstimateS (Colwell 2006). Curves and respective 95% confidence intervals were plotted for each size class separately. We checked for significant differences in observed species richness between treatments by comparing the 95% confidence intervals.

Partial redundancy analysis (pRDA; Legendre & Legendre 1998) was used to decompose the variation associated with treelet and sapling/shrub abundance data into two and three sets of explanatory variables, respectively. Sapling/shrub and treelet abundance data were normalized prior to analysis (see Legendre & Gallagher 2001). When saplings/shrubs were the response data set, the variation was partitioned into three sources: treelets (T), space (S) and edge effect (E). When treelets were the response data set, space and edge effect were used as explanatory data sets.

Edge effect, a qualitative vector with three states (gas pipeline, power line and forest interior), was coded as a dummy variable (Legendre & Legendre 1998), and the resulting matrix was used as an explanatory data set (see Borcard et al. 2011). The spatial coordinates x and y were expanded to comprise nine terms (x, y, x2, xy, y2, x3, x2y, xy2, y3) in order to capture more complex structures (Borcard et al. 1992). Only species that occurred in at least eight sampling units for the sapling/shrub (only response) data set and five sampling units for the treelet (explanatory or response) data set were used in the analyses in order to ensure more robust estimation of regression parameters. This difference was set because the number of variables in the response data set must be lower than N–1 (in our case, 12–1 = 11 sampling units), and lower than the number of variables in the explanatory data sets (see Legendre & Legendre 1998). We applied a forward model selection with the ordistep function in R to select explanatory variables maximally related to each response data set (R Foundation for Statistical Computing, Vienna, AT). The general algorithm proposed by Økland (2003) was used to decompose sapling/shrub or treelet abundance data into three and two sources, respectively.

For saplings/shrubs as response data set, there were 7 = 23−1 components. The analysis began by calculating the total variation explained (TVE) by all sets of explanatory variables, i.e. V(S∪E∪T). Then, we calculated the partial terms. First, we calculated the first-order partial terms: V((T)|S∪E), sapling/shrub variation unique to treelets, i.e. constrained ordination between normalized sapling/shrub abundance data and normalized treelet abundance controlling for the combined effect of space and edge; V((S)|T∪E), variation unique to space, controlling for the combined effect of treelets and edge effect; V((E)|S∪T) variation unique to edge effect, controlling for the combined effect of space and treelets. Then, we calculated the second-order partial unions for each combination of two data sets: V((T∪S)|E), V((E∪S)|T), V((T∪E)|S). The shared variation was assessed by subtracting the combined variation from the sum of the unique terms. For the shared variation between treelets and space, the calculation was V((T∩S)|E) = V((T∪S)|E)−V((T)|S∪E) + V((S)|T∪E); for shared variation between edge effect and space was V((E∪S)|T)−V((E)|S∪T) + V((S)|T∪E); and for the shared variation between treelets and edge effect was V((T∪E)|S)−V((T)|S∪E) + V((E)|T∪S). The unexplained variation (UV) was calculated as 1−TVE. Finally, the shared variation by all sets of explanatory variables was calculated by subtracting from TVE the sum of first- and second-order partial intersections.

For treelets as response data set, there were 3 = 22−1 components. TVE was calculated as V(S∪E). First-order partial terms were calculated as the variation unique to edge effect V(E|S), and the variation unique to space V(S|E). In order to calculate the shared variation, the sum of these unique terms variation was subtracted from TVE. Unexplained variation was calculated as 1−TVE.

We classified all sampled species into two groups according to their conservation importance. Species were classified either as (1) disturbance-tolerant, i.e. native pioneer or generalist species and exotic species; or (2) disturbance-sensitive, which includes native late-successional and habitat specialist species. This classification was based on data from published ecological, floristic and phytosociological studies; on information from herbarium records; and on our previous field experience within the Atlantic Forest (see Sansevero et al. 2011). Then simple and partial Mantel tests were used to relate abundance of disturbance-tolerant, disturbance-sensitive and Euterpe edulis palm to edge effect (after dummy variable coding) and space (x and y coordinates). Significance of correlations was tested by means of bootstrapping with 999 permutations.

Constrained ordinations and Mantel tests were run in the R environment with packages VEGAN and STATS. For Mantel tests, Euclidean distance was used as distance measure for all data, except for edge effect, for which distances were calculated using the binary method in function dist from the package Stats. We adopted a P-value of 0.1 in all analysis to avoid type II errors, as proposed in Mesquita et al. (1999).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Observed species richness did not differ between treatments in both size classes, as 95% confidence intervals of rarefaction curves were strongly overlapping (Fig. 2).

image

Figure 2. Rarefaction curves of understorey species richness as a function of the number of individuals sampled. Error bars denote confidence intervals. (a) Treelets, DBH 5–10 cm. (b) Saplings and shrubs, DBH 1–5 cm. Note that scale of the x-axis differs between size classes.

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The results show that edge effects acts primarily upon treelet composition and that treelets have a huge effect over sapling/shrub composition. Treelet composition was responsible for the largest fraction of variation on sapling/shrub composition (64%), while space and edge effect had a minor contribution (Fig. 3). For treelets, edge effect alone explained about 24% (P = 0.154) of the variation in this response data set. Space variation alone (9%) or shared with edge effect (3%) contributed less and not significantly to sapling/shrub variation.

image

Figure 3. Top, Venn diagram for the partitioning of sapling/shrub abundance data related to edge effect (E), treelet abundance (T) and spatial coordinates (S) as explanatory data sets. Total variation explained (E∪T∪S), 0.882 (88%; P = 0.015); unexplained variation, 0.118 (12%). Bottom, partition of treelet abundance data into two sources: edge effect and space. Total variation explained, (E∪S), 0.362 (36%; P = 0.075); unexplained variation, 0.638 (64%).∪, combined variation. ∩, shared variation. See Økland (2003) for a detailed formulation of the variation partitioning procedures. Negative fractions should be interpreted as zeroes (Legendre 2008). See text for details.

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Edge effect controlling for spatial effects was a significant predictor of the abundance of both Euterpe edulis palm and disturbance-tolerant species, although the correlation was weaker and less significant for saplings and shrubs (Table 1, Appendix S1). On the other hand, abundance of disturbance-sensitive species was not affected by edges.

Table 1. Effects of space and edges on the abundance of Euterpe edulis palm, disturbance-tolerant and disturbance-sensitive species. Simple Mantel and partial Mantel tests (controlling for spatial effects) are shown in the first column, followed by their respective Pearson coefficients and probabilities. See text for details
Mantel testCorrelation P
Euterpe edulis
Space0.280.043
Edge0.310.024
Edge|Space0.270.004
Disturbance-tolerant saplings and shrubs
Space0.100.156
Edge0.140.056
Edge|Space0.120.099
Disturbance-tolerant treelets
Space0.020.307
Edge0.270.008
Edge|Space0.280.004
Disturbance-sensitive saplings and shrubs
Space−0.020.392
Edge0.040.302
Edge|Space0.040.298
Disturbance-sensitive treelets
Space−0.030.429
Edge−0.080.817
Edge|Space−0.070.754

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We found evidence that the creation of linear canopy openings affects species composition, but not species richness, of understorey communities because of edge effects. We also verified that edges of linear canopy openings had a higher abundance of native pioneer, generalist and exotic species than did forest interior areas.

Edge effects are a main driver of tree species loss in tropical forest fragments (Benítez-Malvido & Martínez-Ramos 2003; Oliveira et al. 2004). Thus, it is surprising that understorey species richness was not affected by edge effects in our study system. This result is clearly related to the persistence of disturbance-sensitive species at edges, which is contrary to our initial expectations, and suggests that edge effects from linear canopy openings may not be as severe as observed in typical edges of forest fragments. Indeed, Pohlman et al. (2007) found that microclimatic alterations in tropical forest edges near power lines and highways are less intense than those found in edges of fragments. Nevertheless, the diminished abundance of the palm Euterpe edulis at edges shows that some species typical of old-growth forests are putatively affected. On the other hand, abundance of disturbance-tolerant species was significantly higher at edges, mainly among treelets. Thus, recruitment of pioneer, generalist and exotic species at edges is not necessarily coupled to a decrease in the abundance of disturbance-sensitive species, in such a way that edges of linear canopy openings may be able to keep both groups of species. However, we cannot confirm this will be the case in the long term, because species loss may be a slow process in forest edges (Williams-Linera et al. 1998).

Changes in species composition due to edge effects occurred only among treelets, and are related to an increased abundance of disturbance-tolerant species. Saplings and shrubs, on the other hand, did not respond significantly to edges in terms of species composition, even though they were strongly influenced by treelets. The increase in disturbance-tolerant species was also less marked among shrubs and saplings. Why did treelets show a stronger response to edges than did saplings and shrubs? We can argue that this may be due to a buffering effect caused by vegetation development at forest edges (e.g. Mesquita et al. 1999). If this is the case, we could expect that understorey composition at edges would become increasingly similar to that of forest interior areas, as disturbance-tolerant species are progressively inhibited. This hypothesis relies on the premise that treelet and canopy communities will remain relatively stable over time. However, the higher abundance at edges of disturbance-tolerant species, including short-lived pioneers, may affect gap regimes and prevent buffering. It is necessary to monitor vegetation dynamics along edges of linear canopy openings to verify temporal changes in species composition and abundance of distinct ecological groups.

Many investigators have found that arborescent palms act as biological filters, determining to a large extent the plant community structure under their crowns, because of over-shading (Denslow et al. 1991; Harms et al. 2004; Wang & Augspuger 2006), physical damage caused by their falling fronds (Peters et al. 2004) and the depth of their litter (Farris-López et al. 2004). Thus, diminished abundance of E. edulis may strongly influence seedling community dynamics in Atlantic Forest edges. This may be the case in other tropical forests, because palm species commonly exhibit negative responses to forest fragmentation and edge effects (Scariot 1999; Baez & Balslev 2006; Schedlbauer et al. 2007). Interestingly, Aguiar & Tabarelli (2010) found that the occurrence of dense clusters of the disturbance-adapted palm Attalea oleifera in Atlantic Forest edges sharply reduces seedling density and richness. Thus, we propose that altered abundance of palms at edges may be an important factor driving seedling dynamics and tree regeneration in fragmented tropical forest landscapes.

Our results clearly differ from patterns of edge effects verified in tropical forest fragments (e.g. Laurance et al. 2006b; Michalski et al. 2007; Oliveira et al. 2008). In such studies, authors found that the loss of disturbance-sensitive, late-successional canopy species leads to a sharp decrease in tree richness. Unlike edges of linear canopy openings, forest fragments are exposed to a wide variety of matrix effects that determine, to a great extent, the magnitude of edge effects (Mesquita et al. 1999; Kupfer et al. 2006; Laurance et al. 2007). The limited width of linear canopy openings may constrain more drastic changes in forest edge communities, even if such corridors are covered by very contrasting, grassy vegetation, such as the gas pipeline studied here. Nevertheless, the consequences of edge effects from linear canopy openings must not be disregarded. Unfortunately, few studies have addressed edge effects from linear canopy openings. We argue that these ‘large field experiments’ may provide important cues on how to manage fragmented forest landscapes in order to conserve diversity and function.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We thank three anonymous referees for valuable suggestions that significantly improved the manuscript; Felipe Sodré for building the map; Mark Leithead for linguistic advice; Marcelo Nascimento for collaborating in the sampling design; ICMBio for logistic support; and CNPq for granting a master's degree fellowship to Pablo V. Prieto. We are very grateful to Adilson Pintor and Antonio Tavares for their tireless support during fieldwork. Financial support was provided by the Fundação Flora and PETROBRAS (research grant number 6000.0023998.06.02 to Programa Mata Atlântica/Pablo J. F. P. Rodrigues).

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  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
avsc12043-sup-0001-AppendixS1.pdfapplication/PDF82KAppendix S1. Relative abundance of dominant species in the understorey of gas pipeline forest edges, power line forest edges and forest interiors, União Biological Reserve, southeastern Brazil.

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