Environmental Management DOI 10.1007/s00267-015-0491-3
Assessing the Effects of Woody Plant Traits on Understory Herbaceous Cover in a Semiarid Rangeland Tamrat A. Belay1,2 • Stein R. Moe1
Received: 20 March 2014 / Accepted: 31 March 2015 Ó Springer Science+Business Media New York 2015
Abstract The ecological impact of woody plant encroachment in rangeland ecosystems has traditionally been evaluated based on correlation studies between densities of dissimilar woody plants and various ecosystem properties. However, ecosystem properties respond differently to woody plant encroachment because of variations in adaptation of co-occurring woody plants. The objective of this study is to predict the impact of woody plant encroachment on understory herbaceous cover based on analysis of key traits of woody plants. We conducted a vegetation survey in 4 savanna sites in southwestern Ethiopia and compared 9 different key traits of 19 co-occurring woody plants with understory herbaceous cover. Our results show that low understory herbaceous cover is associated with evergreen leaf phenology, shrubby growth form, smaller relative crown-base height and larger relative crown diameter. However, the N2-fixing ability and density of woody plants did not influence the understory herbaceous cover. This shows that traits of individual woody plants can predict the impact of woody plant encroachment on understory herbaceous cover better than density does. The finding improves our ability to accurately predict the impact of woody plant encroachment on various ecosystem properties in highly diverse savanna systems. This plant traitbased approach could be also used as an important management exercise to assess and predict the impact of encroaching woody species in several rangeland ecosystems. & Tamrat A. Belay [email protected] 1
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, ˚ s, Norway 1432 A
2
Hawassa University, P.O. Box 5, Hawassa, Ethiopia
Keywords Crown architecture Lower Omo region Rangeland degradation Ecosystem properties Ethiopia
Introduction Woody plant encroachment, a rapid proliferation of trees and shrubs into grazing areas, is a widespread global problem (Cabral et al. 2003; Knapp et al. 2008; Lunt et al. 2010; Moleele et al. 2002; Ward 2005). Although the underlying mechanisms are still debated, several hypotheses have postulated a link between global climate change and accelerated woody plant encroachment in rangelands. Some of the climate-related drivers include high rainfall variability, atmospheric warming, nitrogen deposition and elevated carbon dioxide concentration (Archer 2010; Baez and Collins 2008; Bond and Midgley 2000; Polley et al. 2003; Wigley et al. 2010). Moreover, woody plant encroachment could be exacerbated by several local drivers, including overgrazing (Walker and Noy-Meir 1982; Walter 1971), suppression of fire (Scheiter and Higgins 2009; Scholes and Archer 1997) and exclusion of wild browsers (Augustine and McNaughton 2004; Goheen et al. 2007). Woody plant encroachment has commonly been considered one of the several factors accelerating rangeland degradation because of its impact on the biophysical properties of the soil, the hydrology and the overall community structure (Hudak et al. 2003; Maestre et al. 2009a). A number of studies (e.g., Angassa 2005; Ratajczak et al. 2012; Zarovalli et al. 2007) have also shown a strong negative association between the level of woody plant encroachment and productivity of the herbaceous vegetation. Although herbaceous cover and productivity generally decrease with increasing woody plant cover, positive relationships have also been documented. Blaser et al.
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(2014), Gomez-Aparicio et al. (2005) and Maestre et al. (2009a), for example, have shown that herbaceous production could be improved under tree or shrub canopies because of amelioration of the micro-climate. Woody plants modify harsh environmental conditions (e.g., heat and water stress) by either altering substrate characteristics or increasing resource availability. Some C3 plants, for example, grow better under canopies of dicot trees because they benefit from improved microhabitat and soil conditions (Scholes and Archer 1997). In spite of mixed reports from different rangelands, more recent findings (e.g., Ratajczak et al. 2012) assert the notion that the effect of woody plant encroachment on herbaceous vegetation, i.e., whether it is negative, positive or neutral, is determined by several factors, including the extent of disturbances, plant species composition and rainfall regime in that particular area (Blaser et al. 2013). Improvement of herbaceous production under tree or shrub canopies, for example, is more apparent in drier regions that have rainfall below 400–500 mm; the level of enhancement, however, gradually declines with increasing moisture level (Belsky 1994). On the other hand, in wetter areas, where plant growth is more limited by light and soil nutrient availability than water, trees and shrubs would have a more detrimental effect on herbaceous vegetation by limiting the radiant energy and rainwater and competing for soil nutrients (Belsky 1994). Nevertheless, within a given rainfall regime the effect of woody plant encroachment could be determined by specific traits of individual woody plants (Belsky et al. 1989; Ratajczak et al. 2012). Woody plant traits, morphological and physiological characteristics that determine how an individual woody plant adapts to its environment and influence other ecosystem properties (Garnier and Navas 2011; Poorter et al. 2003), have recently been used to understand and predict various ecological phenomena (Ozinga et al. 2009; Schurr et al. 2005). Many studies (e.g., McIntyre et al. 2005; Noble 1989; Prinzing et al. 2002) used traits as a tool to predict the potential invasive behavior of individual plants by comparing characteristics of successful and unsuccessful invaders to the target ecosystem. Some authors (e.g., Eldridge et al. 2011; Maestre et al. 2009b) have also suggested the use of plant traits as a predictor for the impact of woody plant encroachment on various ecosystem properties in highly diverse rangeland communities. Even though different models were developed in the past to relate the relationships between woody plant traits and understory vegetation cover (e.g., Pyke and Zamora 1982; Schott and Pieper 1985), we are still not able to accurately predict which woody plant trait influences the understory herbaceous cover in mixed-species savanna communities.
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The objective of this study is to predict the impact of woody plant encroachment on understory herbaceous cover based on physiological, crown architectural and other morphological traits of individual woody plants in a semiarid savanna rangeland. We asked the following questions: (1) is there strong association between traits of individual woody plants (e.g., leaf-phenology, N2-fixing ability, growth form and crown architecture) and understory herbaceous cover? (2) Is the effect of woody plants on the understory herbaceous cover size asymmetric, i.e., do large trees and shrubs affect understory herbaceous cover differently than smaller trees or shrubs? (3) Is the association between plant traits and understory herbaceous cover influenced by the level of woody plant encroachment (i.e., density of woody plants) and site variation? We predicted that the net effect of woody plant encroachment on ecosystem properties is influenced by a set of morphological and functional traits of individual woody plants (Eldridge et al. 2011; Maestre et al. 2009b). Therefore, based on previous assumptions, we derived the following specific predictions: (1) Woody plants with smaller crown-base-height (CBH), larger crown diameter and crown length affect understory herbaceous cover more negatively, because the crown architecture of individual woody plant influences the allocation of resources, including light intensity and water availability to the understory vegetation (Treydte et al. 2009). (2) Understory herbaceous cover increases with tree or shrub size, because large isolated trees positively influence understory herbaceous cover by ameliorating the surrounding microclimate and improving soil properties (Treydte et al. 2009). (3) We expect a higher herbaceous cover under canopies of nitrogen-fixing woody plants compared to non-nitrogen-fixing neighbors because of the addition of nitrogen-rich litter to the soil. Herbaceous production in most arid and semiarid savannas is limited by nitrogen, in addition to water and phosphorus (Ludwig et al. 2004). (4) Higher herbaceous cover is expected under canopies of evergreen woody plants compared to deciduous neighbors because of their year-round shading effect that minimizes heat stress (Belsky et al. 1993).
Materials and Methods Study Area The study was conducted at the western plains of Hamer district (4.92°–5.33° N and 36.17°–36.37° E) in the lower Omo region of southwestern Ethiopia. The entire Omo river basin, which extends approximately 500 km from the highlands of central Ethiopia to Lake Turkana in Northern Kenya, is an important home for wild animals and many
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pastoral communities. The altitude ranges between 398 and 552 m above mean sea level, with gentle slopes to the west and southwest. It has a semiarid climate with moderate but highly variable rainfall (mean annual precipitation = 581 mm; interannual variability = 33.7 % CV). The main rainy season is between March and May, followed by a long dry season characterized by warm temperature (mean monthly maximum temperature = 34 °C). The soil has predominantly silt to clayey silt texture (Carr 1998). The vegetation is predominantly savanna; the dominant canopy plants include species of Acacia, Commiphora, Boswellia, Maerua and Ormocarpum, whereas the understory vegetation is dominated by annual and perennial grasses, including Aristida adscensionsis, Bothriochloa insculpta, Tetrapogon teneullus, Panicum maximum, Cenchrus ciliaris and Cynodon dactylon. The entire study area has been designated as a conservation site since mid-1970s, and serves as a sanctuary for wild animals migrating from the neighboring Mago National Park. Settlement, fire and other human activities are restricted, although livestock often graze during the wet season of the year. However, recently, the degree of grazing has been relatively reduced because of diminution of grass cover from prolonged drought and the phenomenon of woody plant encroachment in the region. Belay and Moe (2012) and Belay et al. (2013a) provide a more detailed description of the study area, including the map. Site Selection and Vegetation Sampling In 2009, we selected four grazing sites in the vicinity of the Murule controlled hunting area (CHA) that have relatively similar grazing history, landform, elevation, rainfall pattern, and soil texture and fertility (Table 1). Site 1 (Murule) was located adjacent to the Murule CHA headquarter, whereas site 2 (Gudre), site 3 (Zewgella) and site 4 (Lochuba) were located approximately 15 km south, 20 km north and 30 km southeast of the Murule CHA Table 1 Comparison of mean elevation, soil organic matter and density of woody plants between the four study sites in the lower Omo region of southwestern Ethiopia
headquarters, respectively. To verify the similarity of soil characteristics, we randomly sampled the top soil (0–10 cm depth), 24–35 samples from each site, and analyzed them for the percent organic matter using the loss on ignition (LOI) technique (Schulte and Hopkins 1996). The soil organic matter, which is the ultimate source of carbon and nitrogen in the savanna, did not show significant variation between sites (F = 0.42, P = 0.74). To check for the similarity of rainfall between sites, we extracted the mean annual rainfall data from the world climate database (www. worldclim.org) using the DIVA-GIS program (Hijmans et al. 2004) and found no significant variation between sites. To sample the cross section of the vegetation structure, we randomly placed two 6–8-km-long parallel transects, 1 km apart, along the elevation gradient of each site. Following each transect, we systematically placed 20 9 20-m plots (i.e., 24 at site 1, 29 at site 2, 35 at site 3 and 26 at site 4) every 400 m. In each plot, we recorded the number of all woody plants by species type and age category, i.e., seedling (\1.0 m height), sapling (\2.5 cm dbh and [1.0 m height) and adult ([2.5 cm dbh), and measured the height of the median size tree or shrub, which was later used to standardize the density of woody plants using tree equivalent (TE) units (Dalle et al. 2006). Following the density measurement, we selected the largest adult tree or shrub from each species, a total of 472 individuals, and measured the height (i.e., the vertical distance between the ground surface to the tip of the stem), crown base height (i.e., the distance from the ground to the base of the crown), crown length (i.e., the distance from the base to the tip of the crown) and crown diameter (i.e., the average of the widest horizontal crown projection and the one perpendicular to it) to the nearest centimeter using calibrated poles. The diameter at breast height (dbh) was also measured to the nearest millimeter using a vernier caliper. We followed Gschwantner et al. (2009) for the standard definition of tree measurements. Moreover, we visually estimated the percentage cover of the understory herbaceous vegetation, i.e., the area covered by
Site
Name
Number of plots (n)
Elevation (m.a.s.l.)
Soil OM (%)
Woody density (TE ha-1)
Site 1
Murule
24
398.0 (0.0)*
1.6 (0.1)*
Site 2
Gudre
29
453.0 (6.1)
1.6 (0.1)
801.3 (89.8)
Site 3
Zewgella
35
478.7 (12.2)
1.6 (0.1)
2475.0 (205.0)
Site 4
Lochuba
26
552.1 (9.09)
1.3 (0.1)
2827.0 (276.0)
Mean
471.9 (6.7)
1.5 (0.1)
1731.2 (130.0)
F-score p
43.75 \0.05
0.42 0.74
583.2 (79.3)*
Summary 35.96 \0.05
*Values in the brackets are standard errors of the mean
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all grasses and other non-woody plants, as viewed from the canopy, relative to the entire area of the vertical crown projection of the focal tree or shrub. Because the crown diameter of the adult trees and shrubs in the study area was too small (average = 9.0 m2), we did not use quadrats or plots for sampling. Even though variations in the crown projection area (i.e., our sampling unit) may affect measurements of certain vegetation attributes, such as species richness and diversity, the percent herbaceous cover, i.e. proportion of the crown area covered by herbaceous vegetation, is not affected to a greater extent. To avoid any bias in the visual estimation, two people were consistently involved in all the measurements and their estimates averaged. A voucher specimen of each plant species was collected and identified at the National Herbarium at Addis Ababa University. Statistical Analyses In order to compare the density of woody plants between plots and sites, we standardized all individual trees or shrubs into TE units. A TE, which is given by a tree or shrub with 1.5 m height, has been widely used to assess the level of woody plant encroachment in mixed-species and mixed-age plant communities (Dalle et al. 2006; Richter et al. 2001; Roques et al. 2001). For example, 3.0- and 15.0-m-tall trees are standardized to 2.0 TE (i.e., 3.0/1.5) and 10.0 TE (i.e., 15.0/1.5), respectively. Moreover, because most of the stem and crown measurements (i.e., height, dbh, crown length and crown diameter) were intercorrelated, we derived the following noncorrelated indices: relative crown diameter (RCD) (= crown diameter/ height), relative crown length (RCL) (= crown length/ height), relative crown-base-height (RCBH) (= CBH/ height) and slenderness (= crown length/crown diameter), which are also important adaptive traits specific to individual tree or shrub species (Gratzer et al. 2004). To estimate the size of a tree or shrub and examine its association with understory herbaceous cover, we used a simplified formula given by: p (0.25 9 dbh)2 9 height. This index has been widely used as surrogate for the biomass or size of a tree or shrub (Clark et al. 2001). To predict the association between understory herbaceous cover and traits of the canopy tree or shrub, we used stepwise regression analysis. Our response variable, understory herbaceous cover, was modeled as a combination of traits of woody plants, namely, plant size, CBH, RCL, RCD, RCBH, slenderness, growth form (tree vs. shrub), leaf phenology (deciduous vs. evergreen) and N2-fixing ability (no vs. yes). Densities of woody plants, summarized at plot level, and sites were also included as explanatory variables. Density of woody plants and plant size were transformed into logarithmic scale to normalize the
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covariance structure and error distribution. In stepwise regression, all the variables were included in the initial model, and those variables with the highest P value from the F-test were sequentially removed until all the remaining variables were significant at 0.05 level (Crawley 2007). After performing the analysis, we employed the standard model adequacy checking for the final model. All statistical analyses were performed using R-statistical software (R Development Core Team 2010).
Results We identified 19 different woody plants in the entire study area, of which Acacia nilotica, Maerua crassifolia, Ormocarpum trichocarpum, Grewia villosa, Grewia tenax and Acacia brevispica were among the dominant woody species, in their order of abundance (Table 2). The mean height, crown length, crown diameter and CBH of adult woody plants were 3.25 (SE 0.08), 1.80 (SE 0.05), 2.96 (SE 0.08) and 1.47 (SE 0.05) m, respectively. The mean understory herbaceous cover was 57.24 % (SE 1.20); the lowest cover was recorded under the crown perimeter of Lannea triphylla and Acacia mellifera (Table 2). Pearson’s correlation analysis showed that some of the plant traits, such as plant size, were strongly correlated with crown length (r = 0.53) and CBH (r = 0.66), whereas crown length was strongly correlated with crown diameter (r = 0.69) and CBH (r = 0.44). Nevertheless, none of the traits were influenced by the density of woody plants (Table 3). As explained by the best final model (Table 4), understory herbaceous cover increased with increasing RCBH and with decreasing RCD (Fig. 1). It was also associated with leaf phenology (evergreen vs. deciduous), growth form (tree vs. shrub) and plant size. Woody plants with tree growth form have a more positive influence on understory herbaceous cover than shrubs. Similarly, understory herbaceous cover was more negatively associated with evergreen woody plants (P = 0.05) than with deciduous woody plants (Table 4; Fig. 1). As opposed to our expectation, understory herbaceous cover was not positively associated with size of individual woody plants. However, when the plant size interacted with growth form, it showed a more positive effect; largesized trees tend to improve understory herbaceous cover more than large-sized shrubs. Similarly, understory herbaceous cover was not positively associated with the N2-fixing ability of the canopy tree or shrub. However, when the N2-fixing ability interacts with plant size, it has a significantly positive effect on understory herbaceous cover; large-sized N2-fixing woody plants tend to improve the understory herbaceous cover compared to small-sized N2-fixing woody plants.
9
Acacia senegal
5
39
26
12
28
88
19
23 12
15
23
Grewia bicolor
Grewia tenax
Grewia villosa
Lannea triphylla
Lycium shawii
Maerua crassifolia
Maerua oblongifolia
Ormocarpum trichocarpum Premna resinosa
Salvadora persica
Teclea nobilis
Tree
Tree
Tree Tree
Shrub
Tree
Tree
Tree
Shrub
Shrub
Shrub
Shrub
Tree
Shrub
Tree
Tree
Tree
Shrub
Tree
Growth form
EG
EG
DD EG
EG
EG
DD
DD
DD
DD
DD
DD
DD
EG
EG
DD
DD
DD
DD
Leaf phenology
No
No
Yes No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
N2_fixation
3.25
2.19
3.11
3.65 2.66
2.27
3.63
2.25
3.64
2.43
2.34
3.34
2.58
2.44
2.13
2.94
4.25
5.31
2.88
2.89
Height (m)
6.97
4.20
8.21
7.13 4.36
3.56
8.32
5.46
11.80
2.90
3.26
3.60
4.35
2.41
2.44
10.98
9.56
13.40
4.27
6.17
DBH (cm)
1.80
1.06
1.89
1.96 1.51
1.27
2.02
1.36
2.26
1.28
1.32
1.82
1.36
1.20
1.21
1.65
2.04
2.90
1.78
1.58
Crown length (m)
2.96
1.51
3.56
2.54 2.00
1.95
2.91
2.05
4.47
2.01
2.53
3.16
2.43
1.66
1.77
2.57
2.95
4.59
3.31
4.35
Crown diameter (m)
1.47
1.13
1.22
1.69 1.15
0.99
1.61
0.89
1.39
1.15
1.02
1.52
1.22
1.24
0.91
1.29
2.21
2.52
1.10
1.32
CBH (m)
0.56
0.49
0.64
0.53 0.56
0.57
0.56
0.60
0.62
0.53
0.56
0.54
0.54
0.47
0.56
0.56
0.49
0.55
0.60
0.54
RCL
0.94
0.70
1.15
0.71 0.75
0.94
0.84
0.90
1.18
0.82
1.13
1.06
0.92
0.84
0.86
0.88
0.76
0.91
1.14
1.44
RCD
0.45
0.51
0.36
0.47 0.44
0.43
0.44
0.40
0.38
0.47
0.44
0.46
0.46
0.53
0.44
0.44
0.51
0.46
0.40
0.46
RCBH
0.69
0.77
0.64
0.80 0.79
0.80
1.52
0.78
0.74
0.72
0.61
0.58
0.68
0.80
0.72
0.72
1.30
0.76
0.58
0.46
Slender-ness
57.24
58.91
50.93
53.91 47.50
56.58
58.82
51.64
38.50
63.46
57.18
62.00
64.33
55.00
60.06
63.41
76.67
62.19
42.53
49.60
Herb. cover (%)
N implies the number of woody plants sampled, DBH diameter at breast height, CBH crown-base-height, RCL relative crown length, RCD relative crown diameter, RCBH relative crown-baseheight; slenderness = crown length/diameter
For leaf phenology, DD is deciduous, EG is evergreen. The 19 species contribute about 96 % of woody plants in the entire study area. Less frequent species (\5 % relative frequency) are not included
Mean
15
7
Cordia monoica
Combretum paniculatum
16
69
Acacia nilotica
Cadaba farinosa
19
Acacia mellifera
22
25
Acacia brevispica
Balanites rotundifolia
N
Species name
Table 2 Mean measurements for traits of woody plants and understory herbaceous cover in the lower Omo region of southwestern Ethiopia
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Plant size
Crown length
Crown diameter
CBH
RCL
RCD
RCBH
Slenderness
Growth form (tree)
N2fixing (yes)
Plant size
-0.04
Crown length (m)
0.53
Crown diameter (m) CBH (m)
0.45
0.69
0.07 -0.03 -0.01
0.66
0.44
0.42
RCL
-0.06
0.43
0.17
-0.46
RCD
-0.06
0.00
0.58
-0.21
0.19
0.05 -0.10
RCBH
0.11
-0.35
-0.13
0.54
-0.96
-0.18
Slenderness
0.03
0.17
-0.39
-0.05
0.30
-0.66
-0.30
Growth form (trees)
0.17
0.22
0.16
0.24
-0.04
-0.12
0.05
0.03
N2_fixing (yes) leaf phenology (evergreen)
Woody density (TE ha-1)
-0.06 0.02 0.04
0.17
0.31
0.39
0.31
-0.04
0.10
0.06
-0.07
0.27
-0.07
-0.09
-0.20
-0.14
0.07
-0.15
-0.08
0.10
0.33
0.03 -0.37
0.05
Correlation coefficients in bold letters are significant at P = 0.05 level CBH, RCL, RCD and RCBH are for crown-base-height, relative crown length, relative crown diameter and relative crown-base-height, respectively a
Values averaged at plot level (n = 114) were used while testing the correlations between traits and density of woody plants
Table 4 The best model (multiple linear regressions) explaining the association between understory herbaceous cover and traits of individual woody plants
Coefficients
Estimate
(Intercept) RCD
t value
p
0.25
0.35
0.72
0.47
-0.07
0.03
-2.40
0.02
RCBH Phenology (evergreen vs. deciduous)
SE
0.20
0.09
2.28
0.02
-0.07
0.03
-1.99
0.05 \0.01
Growth form (tree vs. shrub)
0.29
0.10
2.92
-0.04
0.02
-2.37
0.02
0.01
0.05
0.19
0.85
Site 2
0.47
0.41
1.14
0.25
Site 3
0.48
0.47
1.03
0.30
1.69 0.04
0.51 0.02
3.29 2.60
\0.01 0.01
Plant sizea Woody densitya Site 1 versus
Site 4 Plant size: growth form (tree vs. shrub) Plant size: N2 fix (yes vs. no)
0.01
0.01
2.06
0.04
Woody density: site 2
-0.04
0.06
-0.70
0.48
Woody density: site 3
-0.07
0.07
-0.97
0.33
Woody density: site 4
-0.21
0.07
-2.89
\0.01
RCD is the relative crown diameter, whereas RCBH is for relative crown-base-height. Other variables including the density of woody plants, growth form and crown length were not selected in the model R2 = 0.175, F-score = 6.90, P \ 0.01 Plant size and woody density are log transformed
a
Moreover, the variation in understory herbaceous cover was not explained by the density of woody plants. However, density has a more negative association with understory herbaceous cover in site 4 (highly encroached site) compared to site 1 (Table 4, Fig. 2).
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Discussion Our study shows that understory herbaceous cover is influenced by a set of traits of individual woody plants. It declines with increasing RCD and decreasing RCBH of
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herbaceous cover (%)
A
B 80
80
60
60
40
40
20
Evergreen Deciduous
20
0
0 0
1
2
3
4
0.0
C
0.5
1.0
Relative Crown-Base-Height (RCBH)
Relative Crown Diameter (RCD)
herbaceous cover (%)
Evergreen Deciduous
D 80
80
60
60
40
40
20
Shrubs Trees
20
Non N2_fixing N2_fixing
0
0 0.0
0.5
1.0
1.5
2.0
Plant size
0.0
0.5
1.0
1.5
2.0
Plant size
Fig. 1 Association between understory herbaceous cover and various traits of woody plants based on predicted values of the best final model. The association between understory herbaceous cover and a relative crown diameter and b relative crown-base height is influenced by leaf phenology. Evergreen plants influence more negatively than Deciduous woody plants. c Association between understory herbaceous cover and woody plant size as influenced by
growth form. Larger shrubs have a negative effect on herbaceous cover, whereas larger trees have a positive influence. d Association between understory herbaceous cover and woody plant size as influenced by N2-fixing ability. Non-N2-fixing woody plants influence the understory herbaceous cover more negatively compared to N2fixing woody plants
trees and shrubs. Bushy woody plants with larger RCD and smaller RCBH usually have intact canopies that prevent solar radiation and rainwater infiltration to the understory vegetation. For example, A. mellifera was found to reduce understory radiation by approximately 53–65 % (Belsky et al. 1993). It can also intercept up to 50 % of rainwater with its leaves and branches in order to maximize the infiltration around the stem (Donaldson 1969). Similarly, woody plants with crown projection closer to the ground, i.e., those with smaller CBH, shade the understory vegetation more hours of day than those that are high above the ground (Belsky et al. 1993). Previous studies have shown that large woody plants may positively influence understory herbaceous cover either directly by manipulating soil properties or indirectly by attracting diverse groups of birds, mammals and other animals by supplying nest sites, shade and food resources (Treydte et al. 2009). Accumulation of fallen nest materials, defecations and food remains by animals under large woody plant canopies increase the level of soil nutrients, thereby improving the understory herbaceous growth (Dean et al. 1999). Moreover, large woody plants serve as
an ‘‘island of fertility’’ by trapping eroded nutrients and debris around their stem (Dean et al. 1999; Ludwig et al. 2004). However, in our study we found a contrasting result by which the understory herbaceous cover declined with increasing woody plant size. This is because of different responses by the herbaceous cover to the two growth forms (i.e., trees and shrubs) (Table 4). As compared to trees, large shrubs have an intact crown architecture, characterized by smaller CBH (P \ 0.01) and larger crown diameter (P \ 0.01), which negatively affects the understory herbaceous cover by limiting the intensity of light and rainwater reaching the ground (Belsky et al. 1993). On the other hand, large trees have a more positive effect (Table 4). Thus, the positive effect of large-sized trees on understory vegetation was most likely overplayed by the strong negative effect of large-sized shrubs. Because a low nitrogen level is a growth-limiting factor in most arid and semiarid savannas (Wang et al. 2009), we expected improvement of herbaceous cover under N2-fixing woody plants (e.g., Eldridge et al. 2011). However, we did not see any significant association between understory herbaceous cover and N2-fixing ability of the canopy
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Environmental Management Site 1
Site 2
100
herbaceous cover (%)
Fig. 2 Association between mean understory herbaceous cover and density of woody plants recorded at plot level. Density has a more pronounced negative effect in highly encroached site (site 4)
2
R = 0.30% F = 0.070 p = 0.801
80
80
60
60
40
40
20
20
0
0 0
500
1000
1500
2000
2500
Site 3
herbaceous cover (%)
0
500
1000
1500
2000
2500
Site 4
100
R2= 1.8% F = 0.520 p = 0.478
80
100
R2= 20.9% F = 5.560 p =
Assessing the Effects of Woody Plant Traits on Understory Herbaceous Cover in a Semiarid Rangeland Tamrat A. Belay1,2 • Stein R. Moe1
Received: 20 March 2014 / Accepted: 31 March 2015 Ó Springer Science+Business Media New York 2015
Abstract The ecological impact of woody plant encroachment in rangeland ecosystems has traditionally been evaluated based on correlation studies between densities of dissimilar woody plants and various ecosystem properties. However, ecosystem properties respond differently to woody plant encroachment because of variations in adaptation of co-occurring woody plants. The objective of this study is to predict the impact of woody plant encroachment on understory herbaceous cover based on analysis of key traits of woody plants. We conducted a vegetation survey in 4 savanna sites in southwestern Ethiopia and compared 9 different key traits of 19 co-occurring woody plants with understory herbaceous cover. Our results show that low understory herbaceous cover is associated with evergreen leaf phenology, shrubby growth form, smaller relative crown-base height and larger relative crown diameter. However, the N2-fixing ability and density of woody plants did not influence the understory herbaceous cover. This shows that traits of individual woody plants can predict the impact of woody plant encroachment on understory herbaceous cover better than density does. The finding improves our ability to accurately predict the impact of woody plant encroachment on various ecosystem properties in highly diverse savanna systems. This plant traitbased approach could be also used as an important management exercise to assess and predict the impact of encroaching woody species in several rangeland ecosystems. & Tamrat A. Belay [email protected] 1
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, ˚ s, Norway 1432 A
2
Hawassa University, P.O. Box 5, Hawassa, Ethiopia
Keywords Crown architecture Lower Omo region Rangeland degradation Ecosystem properties Ethiopia
Introduction Woody plant encroachment, a rapid proliferation of trees and shrubs into grazing areas, is a widespread global problem (Cabral et al. 2003; Knapp et al. 2008; Lunt et al. 2010; Moleele et al. 2002; Ward 2005). Although the underlying mechanisms are still debated, several hypotheses have postulated a link between global climate change and accelerated woody plant encroachment in rangelands. Some of the climate-related drivers include high rainfall variability, atmospheric warming, nitrogen deposition and elevated carbon dioxide concentration (Archer 2010; Baez and Collins 2008; Bond and Midgley 2000; Polley et al. 2003; Wigley et al. 2010). Moreover, woody plant encroachment could be exacerbated by several local drivers, including overgrazing (Walker and Noy-Meir 1982; Walter 1971), suppression of fire (Scheiter and Higgins 2009; Scholes and Archer 1997) and exclusion of wild browsers (Augustine and McNaughton 2004; Goheen et al. 2007). Woody plant encroachment has commonly been considered one of the several factors accelerating rangeland degradation because of its impact on the biophysical properties of the soil, the hydrology and the overall community structure (Hudak et al. 2003; Maestre et al. 2009a). A number of studies (e.g., Angassa 2005; Ratajczak et al. 2012; Zarovalli et al. 2007) have also shown a strong negative association between the level of woody plant encroachment and productivity of the herbaceous vegetation. Although herbaceous cover and productivity generally decrease with increasing woody plant cover, positive relationships have also been documented. Blaser et al.
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(2014), Gomez-Aparicio et al. (2005) and Maestre et al. (2009a), for example, have shown that herbaceous production could be improved under tree or shrub canopies because of amelioration of the micro-climate. Woody plants modify harsh environmental conditions (e.g., heat and water stress) by either altering substrate characteristics or increasing resource availability. Some C3 plants, for example, grow better under canopies of dicot trees because they benefit from improved microhabitat and soil conditions (Scholes and Archer 1997). In spite of mixed reports from different rangelands, more recent findings (e.g., Ratajczak et al. 2012) assert the notion that the effect of woody plant encroachment on herbaceous vegetation, i.e., whether it is negative, positive or neutral, is determined by several factors, including the extent of disturbances, plant species composition and rainfall regime in that particular area (Blaser et al. 2013). Improvement of herbaceous production under tree or shrub canopies, for example, is more apparent in drier regions that have rainfall below 400–500 mm; the level of enhancement, however, gradually declines with increasing moisture level (Belsky 1994). On the other hand, in wetter areas, where plant growth is more limited by light and soil nutrient availability than water, trees and shrubs would have a more detrimental effect on herbaceous vegetation by limiting the radiant energy and rainwater and competing for soil nutrients (Belsky 1994). Nevertheless, within a given rainfall regime the effect of woody plant encroachment could be determined by specific traits of individual woody plants (Belsky et al. 1989; Ratajczak et al. 2012). Woody plant traits, morphological and physiological characteristics that determine how an individual woody plant adapts to its environment and influence other ecosystem properties (Garnier and Navas 2011; Poorter et al. 2003), have recently been used to understand and predict various ecological phenomena (Ozinga et al. 2009; Schurr et al. 2005). Many studies (e.g., McIntyre et al. 2005; Noble 1989; Prinzing et al. 2002) used traits as a tool to predict the potential invasive behavior of individual plants by comparing characteristics of successful and unsuccessful invaders to the target ecosystem. Some authors (e.g., Eldridge et al. 2011; Maestre et al. 2009b) have also suggested the use of plant traits as a predictor for the impact of woody plant encroachment on various ecosystem properties in highly diverse rangeland communities. Even though different models were developed in the past to relate the relationships between woody plant traits and understory vegetation cover (e.g., Pyke and Zamora 1982; Schott and Pieper 1985), we are still not able to accurately predict which woody plant trait influences the understory herbaceous cover in mixed-species savanna communities.
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The objective of this study is to predict the impact of woody plant encroachment on understory herbaceous cover based on physiological, crown architectural and other morphological traits of individual woody plants in a semiarid savanna rangeland. We asked the following questions: (1) is there strong association between traits of individual woody plants (e.g., leaf-phenology, N2-fixing ability, growth form and crown architecture) and understory herbaceous cover? (2) Is the effect of woody plants on the understory herbaceous cover size asymmetric, i.e., do large trees and shrubs affect understory herbaceous cover differently than smaller trees or shrubs? (3) Is the association between plant traits and understory herbaceous cover influenced by the level of woody plant encroachment (i.e., density of woody plants) and site variation? We predicted that the net effect of woody plant encroachment on ecosystem properties is influenced by a set of morphological and functional traits of individual woody plants (Eldridge et al. 2011; Maestre et al. 2009b). Therefore, based on previous assumptions, we derived the following specific predictions: (1) Woody plants with smaller crown-base-height (CBH), larger crown diameter and crown length affect understory herbaceous cover more negatively, because the crown architecture of individual woody plant influences the allocation of resources, including light intensity and water availability to the understory vegetation (Treydte et al. 2009). (2) Understory herbaceous cover increases with tree or shrub size, because large isolated trees positively influence understory herbaceous cover by ameliorating the surrounding microclimate and improving soil properties (Treydte et al. 2009). (3) We expect a higher herbaceous cover under canopies of nitrogen-fixing woody plants compared to non-nitrogen-fixing neighbors because of the addition of nitrogen-rich litter to the soil. Herbaceous production in most arid and semiarid savannas is limited by nitrogen, in addition to water and phosphorus (Ludwig et al. 2004). (4) Higher herbaceous cover is expected under canopies of evergreen woody plants compared to deciduous neighbors because of their year-round shading effect that minimizes heat stress (Belsky et al. 1993).
Materials and Methods Study Area The study was conducted at the western plains of Hamer district (4.92°–5.33° N and 36.17°–36.37° E) in the lower Omo region of southwestern Ethiopia. The entire Omo river basin, which extends approximately 500 km from the highlands of central Ethiopia to Lake Turkana in Northern Kenya, is an important home for wild animals and many
Environmental Management
pastoral communities. The altitude ranges between 398 and 552 m above mean sea level, with gentle slopes to the west and southwest. It has a semiarid climate with moderate but highly variable rainfall (mean annual precipitation = 581 mm; interannual variability = 33.7 % CV). The main rainy season is between March and May, followed by a long dry season characterized by warm temperature (mean monthly maximum temperature = 34 °C). The soil has predominantly silt to clayey silt texture (Carr 1998). The vegetation is predominantly savanna; the dominant canopy plants include species of Acacia, Commiphora, Boswellia, Maerua and Ormocarpum, whereas the understory vegetation is dominated by annual and perennial grasses, including Aristida adscensionsis, Bothriochloa insculpta, Tetrapogon teneullus, Panicum maximum, Cenchrus ciliaris and Cynodon dactylon. The entire study area has been designated as a conservation site since mid-1970s, and serves as a sanctuary for wild animals migrating from the neighboring Mago National Park. Settlement, fire and other human activities are restricted, although livestock often graze during the wet season of the year. However, recently, the degree of grazing has been relatively reduced because of diminution of grass cover from prolonged drought and the phenomenon of woody plant encroachment in the region. Belay and Moe (2012) and Belay et al. (2013a) provide a more detailed description of the study area, including the map. Site Selection and Vegetation Sampling In 2009, we selected four grazing sites in the vicinity of the Murule controlled hunting area (CHA) that have relatively similar grazing history, landform, elevation, rainfall pattern, and soil texture and fertility (Table 1). Site 1 (Murule) was located adjacent to the Murule CHA headquarter, whereas site 2 (Gudre), site 3 (Zewgella) and site 4 (Lochuba) were located approximately 15 km south, 20 km north and 30 km southeast of the Murule CHA Table 1 Comparison of mean elevation, soil organic matter and density of woody plants between the four study sites in the lower Omo region of southwestern Ethiopia
headquarters, respectively. To verify the similarity of soil characteristics, we randomly sampled the top soil (0–10 cm depth), 24–35 samples from each site, and analyzed them for the percent organic matter using the loss on ignition (LOI) technique (Schulte and Hopkins 1996). The soil organic matter, which is the ultimate source of carbon and nitrogen in the savanna, did not show significant variation between sites (F = 0.42, P = 0.74). To check for the similarity of rainfall between sites, we extracted the mean annual rainfall data from the world climate database (www. worldclim.org) using the DIVA-GIS program (Hijmans et al. 2004) and found no significant variation between sites. To sample the cross section of the vegetation structure, we randomly placed two 6–8-km-long parallel transects, 1 km apart, along the elevation gradient of each site. Following each transect, we systematically placed 20 9 20-m plots (i.e., 24 at site 1, 29 at site 2, 35 at site 3 and 26 at site 4) every 400 m. In each plot, we recorded the number of all woody plants by species type and age category, i.e., seedling (\1.0 m height), sapling (\2.5 cm dbh and [1.0 m height) and adult ([2.5 cm dbh), and measured the height of the median size tree or shrub, which was later used to standardize the density of woody plants using tree equivalent (TE) units (Dalle et al. 2006). Following the density measurement, we selected the largest adult tree or shrub from each species, a total of 472 individuals, and measured the height (i.e., the vertical distance between the ground surface to the tip of the stem), crown base height (i.e., the distance from the ground to the base of the crown), crown length (i.e., the distance from the base to the tip of the crown) and crown diameter (i.e., the average of the widest horizontal crown projection and the one perpendicular to it) to the nearest centimeter using calibrated poles. The diameter at breast height (dbh) was also measured to the nearest millimeter using a vernier caliper. We followed Gschwantner et al. (2009) for the standard definition of tree measurements. Moreover, we visually estimated the percentage cover of the understory herbaceous vegetation, i.e., the area covered by
Site
Name
Number of plots (n)
Elevation (m.a.s.l.)
Soil OM (%)
Woody density (TE ha-1)
Site 1
Murule
24
398.0 (0.0)*
1.6 (0.1)*
Site 2
Gudre
29
453.0 (6.1)
1.6 (0.1)
801.3 (89.8)
Site 3
Zewgella
35
478.7 (12.2)
1.6 (0.1)
2475.0 (205.0)
Site 4
Lochuba
26
552.1 (9.09)
1.3 (0.1)
2827.0 (276.0)
Mean
471.9 (6.7)
1.5 (0.1)
1731.2 (130.0)
F-score p
43.75 \0.05
0.42 0.74
583.2 (79.3)*
Summary 35.96 \0.05
*Values in the brackets are standard errors of the mean
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all grasses and other non-woody plants, as viewed from the canopy, relative to the entire area of the vertical crown projection of the focal tree or shrub. Because the crown diameter of the adult trees and shrubs in the study area was too small (average = 9.0 m2), we did not use quadrats or plots for sampling. Even though variations in the crown projection area (i.e., our sampling unit) may affect measurements of certain vegetation attributes, such as species richness and diversity, the percent herbaceous cover, i.e. proportion of the crown area covered by herbaceous vegetation, is not affected to a greater extent. To avoid any bias in the visual estimation, two people were consistently involved in all the measurements and their estimates averaged. A voucher specimen of each plant species was collected and identified at the National Herbarium at Addis Ababa University. Statistical Analyses In order to compare the density of woody plants between plots and sites, we standardized all individual trees or shrubs into TE units. A TE, which is given by a tree or shrub with 1.5 m height, has been widely used to assess the level of woody plant encroachment in mixed-species and mixed-age plant communities (Dalle et al. 2006; Richter et al. 2001; Roques et al. 2001). For example, 3.0- and 15.0-m-tall trees are standardized to 2.0 TE (i.e., 3.0/1.5) and 10.0 TE (i.e., 15.0/1.5), respectively. Moreover, because most of the stem and crown measurements (i.e., height, dbh, crown length and crown diameter) were intercorrelated, we derived the following noncorrelated indices: relative crown diameter (RCD) (= crown diameter/ height), relative crown length (RCL) (= crown length/ height), relative crown-base-height (RCBH) (= CBH/ height) and slenderness (= crown length/crown diameter), which are also important adaptive traits specific to individual tree or shrub species (Gratzer et al. 2004). To estimate the size of a tree or shrub and examine its association with understory herbaceous cover, we used a simplified formula given by: p (0.25 9 dbh)2 9 height. This index has been widely used as surrogate for the biomass or size of a tree or shrub (Clark et al. 2001). To predict the association between understory herbaceous cover and traits of the canopy tree or shrub, we used stepwise regression analysis. Our response variable, understory herbaceous cover, was modeled as a combination of traits of woody plants, namely, plant size, CBH, RCL, RCD, RCBH, slenderness, growth form (tree vs. shrub), leaf phenology (deciduous vs. evergreen) and N2-fixing ability (no vs. yes). Densities of woody plants, summarized at plot level, and sites were also included as explanatory variables. Density of woody plants and plant size were transformed into logarithmic scale to normalize the
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covariance structure and error distribution. In stepwise regression, all the variables were included in the initial model, and those variables with the highest P value from the F-test were sequentially removed until all the remaining variables were significant at 0.05 level (Crawley 2007). After performing the analysis, we employed the standard model adequacy checking for the final model. All statistical analyses were performed using R-statistical software (R Development Core Team 2010).
Results We identified 19 different woody plants in the entire study area, of which Acacia nilotica, Maerua crassifolia, Ormocarpum trichocarpum, Grewia villosa, Grewia tenax and Acacia brevispica were among the dominant woody species, in their order of abundance (Table 2). The mean height, crown length, crown diameter and CBH of adult woody plants were 3.25 (SE 0.08), 1.80 (SE 0.05), 2.96 (SE 0.08) and 1.47 (SE 0.05) m, respectively. The mean understory herbaceous cover was 57.24 % (SE 1.20); the lowest cover was recorded under the crown perimeter of Lannea triphylla and Acacia mellifera (Table 2). Pearson’s correlation analysis showed that some of the plant traits, such as plant size, were strongly correlated with crown length (r = 0.53) and CBH (r = 0.66), whereas crown length was strongly correlated with crown diameter (r = 0.69) and CBH (r = 0.44). Nevertheless, none of the traits were influenced by the density of woody plants (Table 3). As explained by the best final model (Table 4), understory herbaceous cover increased with increasing RCBH and with decreasing RCD (Fig. 1). It was also associated with leaf phenology (evergreen vs. deciduous), growth form (tree vs. shrub) and plant size. Woody plants with tree growth form have a more positive influence on understory herbaceous cover than shrubs. Similarly, understory herbaceous cover was more negatively associated with evergreen woody plants (P = 0.05) than with deciduous woody plants (Table 4; Fig. 1). As opposed to our expectation, understory herbaceous cover was not positively associated with size of individual woody plants. However, when the plant size interacted with growth form, it showed a more positive effect; largesized trees tend to improve understory herbaceous cover more than large-sized shrubs. Similarly, understory herbaceous cover was not positively associated with the N2-fixing ability of the canopy tree or shrub. However, when the N2-fixing ability interacts with plant size, it has a significantly positive effect on understory herbaceous cover; large-sized N2-fixing woody plants tend to improve the understory herbaceous cover compared to small-sized N2-fixing woody plants.
9
Acacia senegal
5
39
26
12
28
88
19
23 12
15
23
Grewia bicolor
Grewia tenax
Grewia villosa
Lannea triphylla
Lycium shawii
Maerua crassifolia
Maerua oblongifolia
Ormocarpum trichocarpum Premna resinosa
Salvadora persica
Teclea nobilis
Tree
Tree
Tree Tree
Shrub
Tree
Tree
Tree
Shrub
Shrub
Shrub
Shrub
Tree
Shrub
Tree
Tree
Tree
Shrub
Tree
Growth form
EG
EG
DD EG
EG
EG
DD
DD
DD
DD
DD
DD
DD
EG
EG
DD
DD
DD
DD
Leaf phenology
No
No
Yes No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
N2_fixation
3.25
2.19
3.11
3.65 2.66
2.27
3.63
2.25
3.64
2.43
2.34
3.34
2.58
2.44
2.13
2.94
4.25
5.31
2.88
2.89
Height (m)
6.97
4.20
8.21
7.13 4.36
3.56
8.32
5.46
11.80
2.90
3.26
3.60
4.35
2.41
2.44
10.98
9.56
13.40
4.27
6.17
DBH (cm)
1.80
1.06
1.89
1.96 1.51
1.27
2.02
1.36
2.26
1.28
1.32
1.82
1.36
1.20
1.21
1.65
2.04
2.90
1.78
1.58
Crown length (m)
2.96
1.51
3.56
2.54 2.00
1.95
2.91
2.05
4.47
2.01
2.53
3.16
2.43
1.66
1.77
2.57
2.95
4.59
3.31
4.35
Crown diameter (m)
1.47
1.13
1.22
1.69 1.15
0.99
1.61
0.89
1.39
1.15
1.02
1.52
1.22
1.24
0.91
1.29
2.21
2.52
1.10
1.32
CBH (m)
0.56
0.49
0.64
0.53 0.56
0.57
0.56
0.60
0.62
0.53
0.56
0.54
0.54
0.47
0.56
0.56
0.49
0.55
0.60
0.54
RCL
0.94
0.70
1.15
0.71 0.75
0.94
0.84
0.90
1.18
0.82
1.13
1.06
0.92
0.84
0.86
0.88
0.76
0.91
1.14
1.44
RCD
0.45
0.51
0.36
0.47 0.44
0.43
0.44
0.40
0.38
0.47
0.44
0.46
0.46
0.53
0.44
0.44
0.51
0.46
0.40
0.46
RCBH
0.69
0.77
0.64
0.80 0.79
0.80
1.52
0.78
0.74
0.72
0.61
0.58
0.68
0.80
0.72
0.72
1.30
0.76
0.58
0.46
Slender-ness
57.24
58.91
50.93
53.91 47.50
56.58
58.82
51.64
38.50
63.46
57.18
62.00
64.33
55.00
60.06
63.41
76.67
62.19
42.53
49.60
Herb. cover (%)
N implies the number of woody plants sampled, DBH diameter at breast height, CBH crown-base-height, RCL relative crown length, RCD relative crown diameter, RCBH relative crown-baseheight; slenderness = crown length/diameter
For leaf phenology, DD is deciduous, EG is evergreen. The 19 species contribute about 96 % of woody plants in the entire study area. Less frequent species (\5 % relative frequency) are not included
Mean
15
7
Cordia monoica
Combretum paniculatum
16
69
Acacia nilotica
Cadaba farinosa
19
Acacia mellifera
22
25
Acacia brevispica
Balanites rotundifolia
N
Species name
Table 2 Mean measurements for traits of woody plants and understory herbaceous cover in the lower Omo region of southwestern Ethiopia
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Environmental Management Table 3 Correlation (Pearson’s r) between different plant traits and density of woody plants in the lower Omo region of southwestern Ethiopia Traitsa
Plant size
Crown length
Crown diameter
CBH
RCL
RCD
RCBH
Slenderness
Growth form (tree)
N2fixing (yes)
Plant size
-0.04
Crown length (m)
0.53
Crown diameter (m) CBH (m)
0.45
0.69
0.07 -0.03 -0.01
0.66
0.44
0.42
RCL
-0.06
0.43
0.17
-0.46
RCD
-0.06
0.00
0.58
-0.21
0.19
0.05 -0.10
RCBH
0.11
-0.35
-0.13
0.54
-0.96
-0.18
Slenderness
0.03
0.17
-0.39
-0.05
0.30
-0.66
-0.30
Growth form (trees)
0.17
0.22
0.16
0.24
-0.04
-0.12
0.05
0.03
N2_fixing (yes) leaf phenology (evergreen)
Woody density (TE ha-1)
-0.06 0.02 0.04
0.17
0.31
0.39
0.31
-0.04
0.10
0.06
-0.07
0.27
-0.07
-0.09
-0.20
-0.14
0.07
-0.15
-0.08
0.10
0.33
0.03 -0.37
0.05
Correlation coefficients in bold letters are significant at P = 0.05 level CBH, RCL, RCD and RCBH are for crown-base-height, relative crown length, relative crown diameter and relative crown-base-height, respectively a
Values averaged at plot level (n = 114) were used while testing the correlations between traits and density of woody plants
Table 4 The best model (multiple linear regressions) explaining the association between understory herbaceous cover and traits of individual woody plants
Coefficients
Estimate
(Intercept) RCD
t value
p
0.25
0.35
0.72
0.47
-0.07
0.03
-2.40
0.02
RCBH Phenology (evergreen vs. deciduous)
SE
0.20
0.09
2.28
0.02
-0.07
0.03
-1.99
0.05 \0.01
Growth form (tree vs. shrub)
0.29
0.10
2.92
-0.04
0.02
-2.37
0.02
0.01
0.05
0.19
0.85
Site 2
0.47
0.41
1.14
0.25
Site 3
0.48
0.47
1.03
0.30
1.69 0.04
0.51 0.02
3.29 2.60
\0.01 0.01
Plant sizea Woody densitya Site 1 versus
Site 4 Plant size: growth form (tree vs. shrub) Plant size: N2 fix (yes vs. no)
0.01
0.01
2.06
0.04
Woody density: site 2
-0.04
0.06
-0.70
0.48
Woody density: site 3
-0.07
0.07
-0.97
0.33
Woody density: site 4
-0.21
0.07
-2.89
\0.01
RCD is the relative crown diameter, whereas RCBH is for relative crown-base-height. Other variables including the density of woody plants, growth form and crown length were not selected in the model R2 = 0.175, F-score = 6.90, P \ 0.01 Plant size and woody density are log transformed
a
Moreover, the variation in understory herbaceous cover was not explained by the density of woody plants. However, density has a more negative association with understory herbaceous cover in site 4 (highly encroached site) compared to site 1 (Table 4, Fig. 2).
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Discussion Our study shows that understory herbaceous cover is influenced by a set of traits of individual woody plants. It declines with increasing RCD and decreasing RCBH of
Environmental Management
herbaceous cover (%)
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B 80
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Fig. 1 Association between understory herbaceous cover and various traits of woody plants based on predicted values of the best final model. The association between understory herbaceous cover and a relative crown diameter and b relative crown-base height is influenced by leaf phenology. Evergreen plants influence more negatively than Deciduous woody plants. c Association between understory herbaceous cover and woody plant size as influenced by
growth form. Larger shrubs have a negative effect on herbaceous cover, whereas larger trees have a positive influence. d Association between understory herbaceous cover and woody plant size as influenced by N2-fixing ability. Non-N2-fixing woody plants influence the understory herbaceous cover more negatively compared to N2fixing woody plants
trees and shrubs. Bushy woody plants with larger RCD and smaller RCBH usually have intact canopies that prevent solar radiation and rainwater infiltration to the understory vegetation. For example, A. mellifera was found to reduce understory radiation by approximately 53–65 % (Belsky et al. 1993). It can also intercept up to 50 % of rainwater with its leaves and branches in order to maximize the infiltration around the stem (Donaldson 1969). Similarly, woody plants with crown projection closer to the ground, i.e., those with smaller CBH, shade the understory vegetation more hours of day than those that are high above the ground (Belsky et al. 1993). Previous studies have shown that large woody plants may positively influence understory herbaceous cover either directly by manipulating soil properties or indirectly by attracting diverse groups of birds, mammals and other animals by supplying nest sites, shade and food resources (Treydte et al. 2009). Accumulation of fallen nest materials, defecations and food remains by animals under large woody plant canopies increase the level of soil nutrients, thereby improving the understory herbaceous growth (Dean et al. 1999). Moreover, large woody plants serve as
an ‘‘island of fertility’’ by trapping eroded nutrients and debris around their stem (Dean et al. 1999; Ludwig et al. 2004). However, in our study we found a contrasting result by which the understory herbaceous cover declined with increasing woody plant size. This is because of different responses by the herbaceous cover to the two growth forms (i.e., trees and shrubs) (Table 4). As compared to trees, large shrubs have an intact crown architecture, characterized by smaller CBH (P \ 0.01) and larger crown diameter (P \ 0.01), which negatively affects the understory herbaceous cover by limiting the intensity of light and rainwater reaching the ground (Belsky et al. 1993). On the other hand, large trees have a more positive effect (Table 4). Thus, the positive effect of large-sized trees on understory vegetation was most likely overplayed by the strong negative effect of large-sized shrubs. Because a low nitrogen level is a growth-limiting factor in most arid and semiarid savannas (Wang et al. 2009), we expected improvement of herbaceous cover under N2-fixing woody plants (e.g., Eldridge et al. 2011). However, we did not see any significant association between understory herbaceous cover and N2-fixing ability of the canopy
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Environmental Management Site 1
Site 2
100
herbaceous cover (%)
Fig. 2 Association between mean understory herbaceous cover and density of woody plants recorded at plot level. Density has a more pronounced negative effect in highly encroached site (site 4)
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R = 0.30% F = 0.070 p = 0.801
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R2= 1.8% F = 0.520 p = 0.478
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R2= 20.9% F = 5.560 p =
