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The relative influence of fire and herbivory on savanna three-dimensional vegetation structure
Biological Conservation 142 (2009) 1693–1700
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The relative influence of fire and herbivory on savanna three-dimensional vegetation structure Shaun R. Levick *, Gregory P. Asner, Ty Kennedy-Bowdoin, David E. Knapp Department of Global Ecology, Carnegie Institution, 260 Panama Street, Stanford, CA 94305, USA
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Article history: Received 19 November 2008 Received in revised form 27 February 2009 Accepted 3 March 2009 Available online 3 April 2009 Keywords: Carnegie airborne observatory Conservation Heterogeneity LiDAR Management Thresholds of potential concern
a b s t r a c t The relative importance of fire and herbivory on vegetation structure has been the subject of much debate in savanna ecology. Fire regime and herbivore numbers are two key variables that managers of protected areas can manipulate to meet their conservation objectives. We deployed a new airborne remote sensing system (Carnegie Airborne Observatory) to the Kruger National Park (KNP), South Africa, to map a unique herbivore/fire exclusion experiment on basaltic soils. We collected high resolution (56 cm) three-dimensional (3-D) vegetation structural data over areas that have been protected from herbivores (34 yr) and/or fire (7 yr), as well as those exposed to both disturbance agents. Canopy height distribution, as well as the distribution of foliage within the vertical canopy profile, differed significantly between all treatments and between each treatment and the control area (Kolmogorov–Smirnov, p < 0.001). Herbivory exerted a greater influence on vegetation 3-D structure and heterogeneity than did fire. At the broad scale, total percentage woody cover was 36 times greater in areas protected from herbivores, compared to the control area. At a finer scale, areas protected from herbivores contained 5 times more tall tree canopy (>9 m) and up to 66 times more small tree canopy (3–6 m). Fire restricted growth of vegetation in the 0–3 m height range, both in the absence and presence of herbivores. Our findings highlight the active role that conservation managers can play in modifying vegetation structure and heterogeneity through herbivore and fire management, as well as the value of 3-D remote sensing for the assessment of conservation management outcomes. Ó 2009 Elsevier Ltd. All rights reserved.
1. Introduction Savannas are heterogeneous systems shaped by many drivers acting at multiple spatio-temporal scales (Belsky, 1995; Pickett et al., 2003; Scholes and Walker, 1993). At the regional level, maximum savanna vegetation cover is strongly influenced by rainfall and increases linearly with mean annual precipitation (MAP) up to about 650 mm yr1 (Sankaran et al., 2005). However, at landscape scales, vegetation pattern varies considerably with geologic substrate and topographic position (Belsky, 1995; Milne, 1935; Venter et al., 2003). Although these bottom-up drivers are key determinants of vegetation structure in savanna landscapes, large herbivores and fire are major mediators of vegetation properties, potentially acting at both regional and landscape scales (Bond, 2008; Bond and Keeley, 2005; Sankaran et al., 2008). Changes in herbivory and fire regimes are thought to be central contributors in the observed transformation of many African landscapes from woodland savanna to shrubland/grassland conditions (Barnes, 1985; Dublin et al., 1990; Laws, 1970; van de Vijver et al., 1999). A wide range of herbivores, from antelope to elephant, * Corresponding author. Tel.: +1 650 462 1047x243. E-mail address: [email protected] (S.R. Levick). 0006-3207/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2009.03.004
have the potential to markedly alter vegetation structure through their foraging and trampling activities (Birkett, 2002; Bond and Loffell, 2001; Laws, 1970). Similarly, fire is a major consumer of plant biomass (Bond and Keeley, 2005; Bond and van Wilgen, 1996), and is widely regarded as being a fundamental driver of savanna vegetation structure (Higgins et al., 2007, 2000; van Wilgen et al., 2003). The relative influence of fire and herbivory, however, has proven difficult to quantify, as feedbacks exist between them and they seldom occur in isolation of one another (Eckhardt et al., 2000; Roques et al., 2001; van Langevelde et al., 2003). Given the enormous yet still unclear role that fire and herbivory play in driving changes in savanna vegetation structure, and the role that land managers play in altering both fire and herbivore regimes (Biggs and Rogers, 2003), understanding the relative importance of these drivers in shaping savanna structure and biodiversity remains a key challenge. In the Kruger National Park (KNP), South Africa, where managers are tasked with ‘‘maintaining biodiversity in all its facets and fluxes” (Rogers, 2003), the relative effects of fire and herbivory need to be quantified to enable informed management decisions. For example, if large herbivores or fire management practices alter vegetation structure to the detriment of biodiversity and ecological functioning, then population control measures or alterations to the
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burning regime may need to be implemented. Such decisions cannot be made without quantifiable evidence of these effects. Achieving this goal requires both the long-term experimental manipulation of fire and herbivory, and a detailed analysis of vegetation structural responses to these manipulations. To develop such an opportunity, we mapped a long-term herbivore exclusion experiment (Makhohlola in the KNP), which incorporates a shorter-term fire exclusion treatment, using the Carnegie Airborne Observatory (CAO, http://cao.stanford.edu). The CAO is a new airborne remote sensing system that provides detailed three-dimensional (3-D) imaging of vegetation and ecosystems by integrating high-fidelity imaging spectrometers (HiFIS) with light detection and ranging (LiDAR) sensors (Asner et al., 2007). Kruger’s Makhohlola experiment was first established in 1974 on the southern basaltic soils of KNP, and provides a unique treatment of herbivore and fire manipulation effects on savanna vegetation. In April 2008, we mapped Makhohlola and the surrounding landscape with the CAO to gain deeper insight into the relative influence of fire and herbivory on savanna vegetation structure and heterogeneity.
2. Materials and methods 2.1. Experimental design and study location The Makhohlola experimental site is situated in the south-eastern corner of the Kruger National Park, South Africa (Fig. 1) and was originally constructed in 1974. The 2.4 ha fenced area excluded all mammalian herbivores larger than a hare (5 kg). In 1992 the fence was breached and herbivores would have had some access to the site until 2004 when the fencing was fixed. The area inside the exclosure was burnt in 1974, 1988, 1989 (partial), 1990, 1992 (partial) and 2001. Over the same period, the surrounding landscape was exposed to both herbivory and fire (with burns in 1974, 1979, 1985, 1988, 1991 and 2001). In 2004 a new experiment was put in place and one-half (1.2 ha) of the original exclosure is now protected from fire and the other half is burnt in conjunction with the surrounding landscape (last burnt in 2006). In addition, a new 1.2 ha plot was established adjacent to the exclosure and is protected from fire (not burnt since 2001) while being accessible to herbivores. The Makhohlola design therefore currently enables long-term (34 yr) exploration of the effects of reduced herbivory on woody vegetation three-dimensional structure in areas exposed to fire, and short-term (7 yr) exploration of the effects of fire suppression in areas with and without herbivores. The entire study area is underlain by dark clay soils of basaltic origin, and the three treatment plots are situated on the crest of a gentle hillslope. The area receives approximately 525 mm of precipitation per year. Dominant woody vegetation species include Sclerocarya birrea subsp. caffra, Lannea schweinfurthii var. stuhlmannii, Acacia nigrescens and Gymnosporia senegalensis. 2.2. Airborne mapping In April 2008, we operated the CAO over the Makhohlola experimental site. The CAO HiFIS sub-system provides spectroscopic images of the land surface. The CAO Alpha system uses a pushbroom imaging array with 1500 cross-track pixels, and sampling across the 367–1058 nm range at up to 2.4 nm spectral resolutions (Asner et al., 2007). The spectrometer sub-system is fully integrated with a waveform LiDAR sub-system having an adjustable laser pulse repetition rate of up to 100 kHz. The CAO LiDAR subsystem provides 3-D structural information on vegetation canopies and the underlying terrain surface. The GPS-IMU sub-system pro-
vides 3-D position and orientation data for the CAO sensors, allowing for highly precise and accurate projection of HiFIS and LiDAR observations on the ground. For this study, the CAO data were collected from 1000 m above ground level, providing combined HiFIS and LiDAR measurements at 56 cm spatial resolution. The flight was conducted within 2.5 h of solar noon. HiFIS, LiDAR and GPS-IMU data were processed together to identify woody, herbaceous and bare soil based on their unique spectral and structural properties. The same airborne data were then used to develop maps of canopy height and 3-D structure using data fusion algorithms (Asner et al., 2007). The large number of LiDAR points collected at high pulse rates enabled the analysis of vegetation vertical structure through the rendering of pseudo-waveform profiles (Weishampel et al., 2000). The vertical distribution of LiDAR points was represented by binning them into volumetric pixels (voxels) of 2 2 m spatial resolution, and 1 m vertical resolution. The LiDAR derived ground elevation was used to standardize the vertical datum of each voxel. The height of each voxel within the vegetation canopy was defined relative to the ground at the horizontal center of that voxel. The number of LiDAR points in each voxel was divided by the total number of LiDAR points in that column, yielding the percentage of LiDAR points that occurred in each voxel. For each treatment and control area, the mean and standard deviation of the LiDAR returns per voxel were calculated to represent the three-dimensional structure of the vegetation layer. 2.3. Ground validation We conducted a field study during the flight campaign to assess the accuracy of the vegetation height estimates from the CAO in KNP. We collected 350 randomly selected field points for woody canopies ranging from approximately 1–20 m in height, and including a wide range of the common plant species found in the park. The data were collected with an extendable, graduated range pole or a handheld laser range finder (Impulse200, Laser Technologies Inc., Denver, CO, USA). The geographic coordinate of each point was logged on a survey-grade Global Positioning System (GPS) receiver (GeoXT, Trimble Inc., Sunnyvale, CA, USA) and later differentially corrected to sub-meter accuracy using local GPS base stations (http://www.trignet.co.za/). The individual crowns of the field measured trees were digitized as polygons from the LiDAR derived canopy height model. The maximum canopy height for each crown polygon was then calculated and regressed against the field data for that particular tree. 2.4. Analytical approach The distribution of these height data values, for both top of canopy and for the vertical profiles derived from the LiDAR data, were compared between different treatments and against the control areas by means of the Kolmogorov–Smirnov test, which is sensitive to differences in both the location and shape of the empirical cumulative distribution functions (Sokal and Rohlf, 1995). Differences in canopy vertical heterogeneity were determined by applying the Shannon–Weiner diversity index (SWDI) to the vertical profile data. The Shannon–Weiner diversity index stems from information theory (Shannon and Weaver, 1962) and is widely used to characterize species diversity within a community and accounts for both abundance and evenness of the species present (Magurran, 1988, 2004). The index is calculated according to the following equation:
H¼
s X i¼1
pi ln pi
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Fig. 1. Location and layout of the Makhohlola treatments within the Kruger National Park, South Africa. Inset image displays canopy cover of woody vegetation in dark green.
whereby pi is the proportion of individuals found in the ith species, s is the total number of species found in the community, and ln is the natural logarithm. The principle of this index is transferable to structural data in categorical format, and it is a commonly used metric of landscape spatial pattern (O’Neill et al., 1988; Turner, 1990). Here, we applied the index to the proportional distribution of foliage within the vertical profile of vegetation canopies.
3. Results 3.1. Validation of airborne mapping Linear regression indicated a strong positive relationship between field measured and remotely sensed vegetation height, with r2 = 0.92, p < 0.01 and a standard error of the estimate of 1.17 m (Fig. 2). Our ground-validation exercise therefore showed that a high level of confidence could be placed in the accuracy of vegetation height data obtained from the CAO.
3.2. Vegetation three-dimensional structure The reduction of different combinations of herbivory and fire at the treatment sites caused substantial differences in woody vegetation structure compared to the control area. For example, a cross-sectional view of the LiDAR returns clearly showed greater woody cover and taller woody canopy across all treatments plots, particularly in those protected from herbivory (Fig. 3). These structural differences were best quantified in terms of the frequency of occurrence (per given area) of vegetation canopy height across the study site (Fig. 4). Through area-normalization by hectare, these frequency distributions represent both the height and cover components of vegetation structure. The control area exposed to both fire and herbivory was sparsely vegetated (0.6% cover), and the majority of the cover occurred in height classes of less than 3 m (Fig. 4a). The treatment that was exposed to herbivores over the long-term but was recently protected from fire had greater vegetation cover (2.6%), but it was largely contained in height intervals of less than 4 m above ground level (Fig. 4b). This pattern showed
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tion of foliage within the canopy (Fig. 5). The Shannon–Weiner diversity index (SWDI) was lowest in the control area, where the small amount of foliage present was evenly distributed within the vertical profile (Fig. 5a). The SWDI was highest in the plots protected from herbivores (Fig. 5c and d), where foliage was more diversely distributed within the vertical profile, particularly in the plot that was also recently protected from fire (Fig. 5d). Although the long-term herbivore effect was the most prominent, recent fire suppression rapidly altered the distribution of foliage in the 0–3 m height intervals (Fig. 5a and c vs. b and d). The vertical distribution of foliage reflected the large differences in tree to shrub ratios across the treatments. In the control area, we only found one laser return from a tree canopy (>3 m) for every 19 returned from shrub canopy (<3 m). The ratio increased to 1:6 in the treatment recently protected from fire but not herbivores, and to more than 1:2 in the treatments protected from herbivores. Therefore, different height classes of vegetation responded differentially to fire and herbivore disturbances, in terms of both canopy height and vertical profile. 3.4. Responses by height class
Fig. 2. Field validation of woody canopy height from 350 randomly selected points during the mapping campaign in April 2008.
that although woody cover and height may rapidly increase with decreased exposure to fire, they are still constrained below a 4 m threshold by herbivores. In the absence of herbivores, there was 17.2% woody cover in the plot exposed to fire (Fig. 4c) and 18.5% cover in the plot that was recently protected from fire (Fig. 4d). Vegetation frequently occurred in height classes of greater than 4 m in both of these cases. The long-term exclusion of herbivores therefore markedly influenced vegetation height at intervals greater than 4 m, while the influence of fire in limiting vegetation was apparent in the 0–3 m intervals (Fig. 4a and c vs. b and d). 3.3. Structural heterogeneity Long-term protection from herbivory greatly impacted vegetation structural heterogeneity, defined here as the vertical distribu-
To differentiate height class specific responses, we examined the percentage difference in canopy area between control and treatment sites for different vegetation height classes (Fig. 6). Compared to the control, canopy area was greater in the area recently protected from fire for shrub (0–3 m) and small tree (3–6 m) height classes, but did not differ in medium tree (6–9 m) and tall tree (9– 12 m) height classes. The two long-term herbivore exclusion sites contained more canopy area in the shrub and tall tree height classes than did the control, but the exclusion plot recently protected from fire contained more canopy area in both the shrub and tall tree size classes. Compared to the control, the areal extent of small tree canopies was considerably greater in both long-term herbivore exclusion plots (42 times and 66 times), with the largest difference observed in the exclusion plot that was also recently protected from fire. Interestingly, the area of medium tree canopy was 38 times greater than the control in the exclusion plot exposed to fire, but was only 18 times greater than the control in the exclusion plot recently protected from fire. Therefore, while the small tree height class
Fig. 3. Cross-profile comparisons of the herbivore and fire experimental treatments and the control landscape. Profiles display the LiDAR point cloud of both ground surface and vegetation canopy returns. Solid redline marks the boundary between control and treatment sites.
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Fig. 4. Distribution of vegetation height values across: (a) control area exposed to long-term herbivory and fire; (b) area exposed to long-term herbivory but recently protected from fire (7 yr); (c) area protected from herbivory over the long-term (34 yr) but exposed to fire; and (d) area protected from herbivory over the long-term (34 yr) and recently protected from fire (7 yr). Histograms represent the frequency of canopy height values (as determined from LiDAR) per hectare. Height distribution differed significantly between all three treatments, and all three treatments were significantly different to the control (Kolmogorov–Smirnov, p < 0.001).
showed a linear response to the removal of disturbance agents, the medium tree height class displayed a more complex relationship. 4. Discussion and conclusions 4.1. Relative influence of fire and herbivory on savanna structure The relative influence of fire and herbivory has been difficult to elucidate in savanna ecology (Dublin et al., 1990; Trollope et al., 1998; van Langevelde et al., 2003). Previous studies of vegetation structure and dynamics in KNP have hypothesized that both fire and large herbivores (such as elephant) are responsible for the observed reduction in tree cover on the basaltic soils over the last few decades (Eckhardt et al., 2000; Trollope et al., 1998). The structural patterns that we uncovered at Makhohlola suggest that herbivores bear greater responsibility for limiting woody vegetation height, cover and structural heterogeneity on the southern basalts of KNP. Moreover, many of these 3-D structural differences can only be attributed to mega-herbivores (Owen-Smith, 1988) such as elephant (Loxodonta africana) and giraffe (Giraffa camelopardalis), by virtue of their height and feeding behaviors, as the most pronounced structural differences occurred above a 4 m height threshold. The experimental manipulation of fire occurrence and herbivore access to the study site revealed heterogeneous responses of
different height classes of vegetation to the removal of one or both of the disturbance agents. The heterogeneous nature of disturbance effects has been well documented (Levick and Rogers, 2008; Pickett and White, 1985; Turner, 1989), but has primarily been considered from a two-dimensional landscape patch-mosaic point of view. Our study was confined to one landscape (upland basalts), but we found heterogeneous responses to disturbance agents within different height classes of vegetation canopy. These findings would not have been possible without the use of 3-D remote sensing, which enabled the detailed exploration of vegetation structure at multiple height class intervals. Our results showed that fire rapidly affects vegetation canopies in the 0–3 m height interval above ground level, a zone often referred to as ‘the fire trap’ (Bond and Keeley, 2005) and a height class that would be expected to be influenced by fire. Interestingly, however, reduced fire occurrence was associated with less vegetation canopy in the medium tree size class (6–9 m) in the absence of herbivory. The different patterns in small and medium tree height classes between the two herbivore exclusion plots suggest a possible feedback with plant competition. By restricting plant growth in the ‘fire trap’, growth in the medium height class might be promoted by greater resource availability, although the timeframe under consideration may have been too short for such feedbacks to have occurred. Nonetheless, it is likely that the effects of fire in the initial 3 m will have cascading effects through the rest of the vegetation profile
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Fig. 5. Vertical diversity of foliage distribution within the canopy across: (a) control area exposed to long-term herbivory and fire; (b) area exposed to long-term herbivory but recently protected from fire (7 yr); (c) area protected from herbivory over the long-term (34 yr) but exposed to fire; and (d) area protected from herbivory over the longterm (34 yr) and recently protected from fire (7 yr). Foliage distribution differed significantly between all three treatments, and all three treatments were significantly different to the control (Kolmogorov–Smirnov, p < 0.001). SWDI = Shannon–Weiner diversity index (relative).
(Bond, 2008). Indeed, many studies of herbivory and/or fire effects on savanna vegetation have yielded complex and even contrasting results (Sankaran et al., 2008), but further exploration of fire and herbivory effects from an explicit 3-D perspective of vegetation is likely to advance our understanding of these complexities. 4.2. Limitations It is important to acknowledge three limitations of the experimental design at Makhohlola. First, the experiment was restricted to one un-replicated site on nutrient-rich basaltic soils. We would expect the relative influence of fire and herbivory to differ on nutri-
ent-poor granitic substrates, which offer lower forage quality to herbivores (Grant and Scholes, 2006). Second, the design allowed for the testing of fire suppression over the short-term, but not longer-term fire return interval, fire intensity, or season of burning, all of which have been shown to be important determinants of fire impact in savanna systems (Higgins et al., 2007; van Wilgen et al., 2003). Third, while this study explored structural patterns that have arisen from 34 yr of reduced herbivory, and 7 yr of fire suppression, these periods may be too brief to observe even longerterm vegetation responses to herbivore and fire manipulation. Although fire predominantly appeared to restrict woody canopy development in the initial 3 m above ground level, fire in this shrub
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bivore and fire management policies consider a 3-D perspective of vegetation structure. Vegetation TPCs need to be defined in a height-specific manner, as we have shown that different height classes respond differently to herbivory and fire. Our LiDAR analyses provided detail on the 3-D structural responses of ecosystems to management actions, but their full potential to inform management decisions cannot be realized until the linkages between 3-D structure, biodiversity and ecological functioning are explicitly clarified. We know that taller trees promote both biodiversity (Cumming et al., 1997; Fenton et al., 1998) and ecological functioning (Belsky and Canham, 1994; Bond, 2008; Treydte et al., 2007; van de Koppel et al., 2002), but we lack an understanding of which height classes, and which proportions of their occurrence, are most important. Three-dimensional remote sensing has opened the door to tackling these issues, but the most effective use of remotely sensed data is through their fusion with appropriate field investigations (Chambers et al., 2007). Defining meaningful TPCs for vegetation in savannas requires intensive investigation of the relationship between 3-D structure, biodiversity and ecological functioning. Although 3-D TPCs are yet to be defined for KNP ecosystems, our study provides managers with insight into the continuum of savanna vegetation structure and heterogeneity on basaltic substrates. While no official TPC was triggered, herbivores (mega-herbivores in particular) and fire have reduced/limited vegetation growth to a degree that likely holds negative consequences for biodiversity and ecological functioning. We consider the extent of the structural differences to be of major conservation concern. Fig. 6. Height class specific differences in the area of canopy cover between the three treatments and the control.
layer may prevent the recruitment of taller trees, causing longerterm consequences for the vegetation 3-D structure and diversity. 4.3. Implications for the conservation and management of savanna landscapes Changes to herbivore access and fire regime markedly altered vegetation 3-D structure and heterogeneity at the Makhohlola experimental site. The structural differences found here have important implications for the conservation and management of savanna landscapes, as modification of herbivore numbers and fire regime impact not only the structure of vegetation, but also the organisms that depend upon those structures (Cumming et al., 1997). Our findings highlight the active role that conservation managers can play in modifying vegetation structure through herbivore and fire management, and suggest that managers have the potential to directly influence biodiversity and ecological functioning through their actions or inactions. In KNP, managers use monitoring endpoints, known as thresholds of potential concern (TPCs), as an integral part of their strategic adaptive management approach to conservation (Biggs and Rogers, 2003). The TPCs are a set of operational goals that define the upper and lower limits along a continuum of change in selected ecological indicators for which ecosystems are managed (Rogers and Biggs, 1999). The TPCs act as early warning systems to help managers decide when intervention is necessary. A key challenge to managers in KNP, and other savanna parks, is defining the upper and lower limits of ‘acceptable’ change in woody structure. Meaningful thought has been given to defining these limits for woody cover (Gillson and Duffin, 2007), but a 3-D consideration of these limits is lacking. Since we have illustrated the extent to which herbivores and fire can modify the 3-D structure and heterogeneity of savanna vegetation, it is essential that the operational goals in her-
Acknowledgements We thank Izak Smit and the entire SANParks staff for their outstanding logistical and scientific support. We greatly appreciate the help of Navashni Govender in tracing the history of the experimental site. We commend the SANParks managers of the time for their foresight in establishing the Makhohlola exclosure. We thank Ruth Emerson, James Jacobson, Matt Colgan and Robin Martin for assistance with field work and image analysis. This research was funded by the Andrew Mellon Foundation. The Carnegie Airborne Observatory is supported by the W.M. Keck Foundation and William Hearst III.
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Rogers, K.H., Biggs, H.C., 1999. Integrating indicators, endpoints and value systems in strategic management of the rivers of the Kruger National Park. Freshwater Biology 41, 439–451. Roques, K.G., O’Connor, T.G., Watkinson, A.R., 2001. Dynamics of shrub encroachment in an African savanna: relative influences of fire, herbivory, rainfall and density dependence. Journal of Applied Ecology 38, 268–280. Sankaran, M., Hanan, N.P., Scholes, R.J., Ratnam, J., Augustine, D.J., Cade, B.S., Gignoux, J., Higgins, S.I., Roux, X.L., Ludwig, F., Ardo, J., Banyikwa, F., Bronn, A., Bucini, G., Caylor, K.K., Coughenour, M.B., Diouf, A., Ekaya, W., Feral, C.J., February, E.C., Frost, P.G.H., Hiernaux, P., Hrabar, H., Metzger, K.L., Prins, H.H.T., Ringrose, S., Sea, W., Tews, J., Worden, J., Zambatis, N., 2005. Determinants of woody cover in African savannas. Nature 438, 846–849. Sankaran, M., Ratnam, J., Hanan, N.P., 2008. Woody cover in African savannas: the role of resources, fire and herbivory. Global Ecology & Biogeography 17, 236– 245. Scholes, R.J., Walker, B.H., 1993. An African savanna: Synthesis of the Nylsvley Study. Cambridge University Press. Shannon, C.E., Weaver, W., 1962. The Mathematical Theory of Communication. University of Illinois Press. Sokal, R., Rohlf, F., 1995. Biometry: The Principles and Practice of Statistics in Biological Research, third ed. WH Freeman, New York, USA. 887 pp. Treydte, A., Heitkönig, I., Prins, H., Ludwig, F., 2007. Trees improve grass quality for herbivores in African savannas. Perspectives in Plant Ecology, Evolution and Systematics 8, 197–205. Trollope, W.S.W., Trollope, L.A., Biggs, H.C., Pienaar, D., Potgieter, A.L.F., 1998. Longterm changes in the woody vegetation of the Kruger National Park, with special reference to the effects of elephants and fire. Koedoe 41, 103–112. Turner, M.G., 1989. Landscape ecology: the effect of pattern on process. Annual Review of Ecology and Systematics 20, 171–197. Turner, M.G., 1990. Spatial and temporal analysis of landscape patterns. Landscape Ecology 4, 21–30. van de Koppel, J., Rietkerk, M., van Langevelde, F., Kumar, L., Klausmeier, C.A., Fryxell, J.M., van Andel, J., de Ridder, N., Skidmore, A., 2002. Spatial heterogeneity and irreversible vegetation change in semiarid grazing systems. The American Naturalist 159, 209–218. van de Vijver, C.A.D.M., Foley, C.A., Olff, H., 1999. Changes in the woody component of an east African savanna during 25 years. Journal of Tropical Ecology 15, 545– 564. van Langevelde, F., van De Vijver, C., Kumar, L., van De Koppel, J., de Ridder, N., van Andel, J., Skidmore, A.K., Hearne, J.W., Stroosnijder, L., Bond, W.J., 2003. Effects of fire and herbivory on the stability of savanna ecosystems. Ecology 84, 337– 350. van Wilgen, B.W., Trollope, W.S.W., Biggs, H.C., Potgieter, A.L.F., Brockett, B.H., 2003. In: du Toit, J.T., Biggs, H.C., Rogers, K.H. (Eds.), Fire as a Driver of Ecosystem Variability. Island Press, Washington, DC, pp. 149–170. Venter, F.J., Scholes, R.J., Eckhardt, H.C., 2003. The abiotic template and its associated vegetation pattern. In: du Toit, J.T., Biggs, H.C., Rogers, K.H. (Eds.), The Kruger Experience: Ecology and Management of Savanna Heterogeneity. Island Press, Washington, DC, pp. 83–129. Weishampel, J.F., Blair, J.B., Knox, R.G., Dubayah, R., Clark, D.B., 2000. Volumetric lidar return patterns from an old-growth tropical rainforest canopy. International Journal of Remote Sensing 21, 409–415.
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The relative influence of fire and herbivory on savanna three-dimensional vegetation structure Shaun R. Levick *, Gregory P. Asner, Ty Kennedy-Bowdoin, David E. Knapp Department of Global Ecology, Carnegie Institution, 260 Panama Street, Stanford, CA 94305, USA
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Article history: Received 19 November 2008 Received in revised form 27 February 2009 Accepted 3 March 2009 Available online 3 April 2009 Keywords: Carnegie airborne observatory Conservation Heterogeneity LiDAR Management Thresholds of potential concern
a b s t r a c t The relative importance of fire and herbivory on vegetation structure has been the subject of much debate in savanna ecology. Fire regime and herbivore numbers are two key variables that managers of protected areas can manipulate to meet their conservation objectives. We deployed a new airborne remote sensing system (Carnegie Airborne Observatory) to the Kruger National Park (KNP), South Africa, to map a unique herbivore/fire exclusion experiment on basaltic soils. We collected high resolution (56 cm) three-dimensional (3-D) vegetation structural data over areas that have been protected from herbivores (34 yr) and/or fire (7 yr), as well as those exposed to both disturbance agents. Canopy height distribution, as well as the distribution of foliage within the vertical canopy profile, differed significantly between all treatments and between each treatment and the control area (Kolmogorov–Smirnov, p < 0.001). Herbivory exerted a greater influence on vegetation 3-D structure and heterogeneity than did fire. At the broad scale, total percentage woody cover was 36 times greater in areas protected from herbivores, compared to the control area. At a finer scale, areas protected from herbivores contained 5 times more tall tree canopy (>9 m) and up to 66 times more small tree canopy (3–6 m). Fire restricted growth of vegetation in the 0–3 m height range, both in the absence and presence of herbivores. Our findings highlight the active role that conservation managers can play in modifying vegetation structure and heterogeneity through herbivore and fire management, as well as the value of 3-D remote sensing for the assessment of conservation management outcomes. Ó 2009 Elsevier Ltd. All rights reserved.
1. Introduction Savannas are heterogeneous systems shaped by many drivers acting at multiple spatio-temporal scales (Belsky, 1995; Pickett et al., 2003; Scholes and Walker, 1993). At the regional level, maximum savanna vegetation cover is strongly influenced by rainfall and increases linearly with mean annual precipitation (MAP) up to about 650 mm yr1 (Sankaran et al., 2005). However, at landscape scales, vegetation pattern varies considerably with geologic substrate and topographic position (Belsky, 1995; Milne, 1935; Venter et al., 2003). Although these bottom-up drivers are key determinants of vegetation structure in savanna landscapes, large herbivores and fire are major mediators of vegetation properties, potentially acting at both regional and landscape scales (Bond, 2008; Bond and Keeley, 2005; Sankaran et al., 2008). Changes in herbivory and fire regimes are thought to be central contributors in the observed transformation of many African landscapes from woodland savanna to shrubland/grassland conditions (Barnes, 1985; Dublin et al., 1990; Laws, 1970; van de Vijver et al., 1999). A wide range of herbivores, from antelope to elephant, * Corresponding author. Tel.: +1 650 462 1047x243. E-mail address: [email protected] (S.R. Levick). 0006-3207/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2009.03.004
have the potential to markedly alter vegetation structure through their foraging and trampling activities (Birkett, 2002; Bond and Loffell, 2001; Laws, 1970). Similarly, fire is a major consumer of plant biomass (Bond and Keeley, 2005; Bond and van Wilgen, 1996), and is widely regarded as being a fundamental driver of savanna vegetation structure (Higgins et al., 2007, 2000; van Wilgen et al., 2003). The relative influence of fire and herbivory, however, has proven difficult to quantify, as feedbacks exist between them and they seldom occur in isolation of one another (Eckhardt et al., 2000; Roques et al., 2001; van Langevelde et al., 2003). Given the enormous yet still unclear role that fire and herbivory play in driving changes in savanna vegetation structure, and the role that land managers play in altering both fire and herbivore regimes (Biggs and Rogers, 2003), understanding the relative importance of these drivers in shaping savanna structure and biodiversity remains a key challenge. In the Kruger National Park (KNP), South Africa, where managers are tasked with ‘‘maintaining biodiversity in all its facets and fluxes” (Rogers, 2003), the relative effects of fire and herbivory need to be quantified to enable informed management decisions. For example, if large herbivores or fire management practices alter vegetation structure to the detriment of biodiversity and ecological functioning, then population control measures or alterations to the
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burning regime may need to be implemented. Such decisions cannot be made without quantifiable evidence of these effects. Achieving this goal requires both the long-term experimental manipulation of fire and herbivory, and a detailed analysis of vegetation structural responses to these manipulations. To develop such an opportunity, we mapped a long-term herbivore exclusion experiment (Makhohlola in the KNP), which incorporates a shorter-term fire exclusion treatment, using the Carnegie Airborne Observatory (CAO, http://cao.stanford.edu). The CAO is a new airborne remote sensing system that provides detailed three-dimensional (3-D) imaging of vegetation and ecosystems by integrating high-fidelity imaging spectrometers (HiFIS) with light detection and ranging (LiDAR) sensors (Asner et al., 2007). Kruger’s Makhohlola experiment was first established in 1974 on the southern basaltic soils of KNP, and provides a unique treatment of herbivore and fire manipulation effects on savanna vegetation. In April 2008, we mapped Makhohlola and the surrounding landscape with the CAO to gain deeper insight into the relative influence of fire and herbivory on savanna vegetation structure and heterogeneity.
2. Materials and methods 2.1. Experimental design and study location The Makhohlola experimental site is situated in the south-eastern corner of the Kruger National Park, South Africa (Fig. 1) and was originally constructed in 1974. The 2.4 ha fenced area excluded all mammalian herbivores larger than a hare (5 kg). In 1992 the fence was breached and herbivores would have had some access to the site until 2004 when the fencing was fixed. The area inside the exclosure was burnt in 1974, 1988, 1989 (partial), 1990, 1992 (partial) and 2001. Over the same period, the surrounding landscape was exposed to both herbivory and fire (with burns in 1974, 1979, 1985, 1988, 1991 and 2001). In 2004 a new experiment was put in place and one-half (1.2 ha) of the original exclosure is now protected from fire and the other half is burnt in conjunction with the surrounding landscape (last burnt in 2006). In addition, a new 1.2 ha plot was established adjacent to the exclosure and is protected from fire (not burnt since 2001) while being accessible to herbivores. The Makhohlola design therefore currently enables long-term (34 yr) exploration of the effects of reduced herbivory on woody vegetation three-dimensional structure in areas exposed to fire, and short-term (7 yr) exploration of the effects of fire suppression in areas with and without herbivores. The entire study area is underlain by dark clay soils of basaltic origin, and the three treatment plots are situated on the crest of a gentle hillslope. The area receives approximately 525 mm of precipitation per year. Dominant woody vegetation species include Sclerocarya birrea subsp. caffra, Lannea schweinfurthii var. stuhlmannii, Acacia nigrescens and Gymnosporia senegalensis. 2.2. Airborne mapping In April 2008, we operated the CAO over the Makhohlola experimental site. The CAO HiFIS sub-system provides spectroscopic images of the land surface. The CAO Alpha system uses a pushbroom imaging array with 1500 cross-track pixels, and sampling across the 367–1058 nm range at up to 2.4 nm spectral resolutions (Asner et al., 2007). The spectrometer sub-system is fully integrated with a waveform LiDAR sub-system having an adjustable laser pulse repetition rate of up to 100 kHz. The CAO LiDAR subsystem provides 3-D structural information on vegetation canopies and the underlying terrain surface. The GPS-IMU sub-system pro-
vides 3-D position and orientation data for the CAO sensors, allowing for highly precise and accurate projection of HiFIS and LiDAR observations on the ground. For this study, the CAO data were collected from 1000 m above ground level, providing combined HiFIS and LiDAR measurements at 56 cm spatial resolution. The flight was conducted within 2.5 h of solar noon. HiFIS, LiDAR and GPS-IMU data were processed together to identify woody, herbaceous and bare soil based on their unique spectral and structural properties. The same airborne data were then used to develop maps of canopy height and 3-D structure using data fusion algorithms (Asner et al., 2007). The large number of LiDAR points collected at high pulse rates enabled the analysis of vegetation vertical structure through the rendering of pseudo-waveform profiles (Weishampel et al., 2000). The vertical distribution of LiDAR points was represented by binning them into volumetric pixels (voxels) of 2 2 m spatial resolution, and 1 m vertical resolution. The LiDAR derived ground elevation was used to standardize the vertical datum of each voxel. The height of each voxel within the vegetation canopy was defined relative to the ground at the horizontal center of that voxel. The number of LiDAR points in each voxel was divided by the total number of LiDAR points in that column, yielding the percentage of LiDAR points that occurred in each voxel. For each treatment and control area, the mean and standard deviation of the LiDAR returns per voxel were calculated to represent the three-dimensional structure of the vegetation layer. 2.3. Ground validation We conducted a field study during the flight campaign to assess the accuracy of the vegetation height estimates from the CAO in KNP. We collected 350 randomly selected field points for woody canopies ranging from approximately 1–20 m in height, and including a wide range of the common plant species found in the park. The data were collected with an extendable, graduated range pole or a handheld laser range finder (Impulse200, Laser Technologies Inc., Denver, CO, USA). The geographic coordinate of each point was logged on a survey-grade Global Positioning System (GPS) receiver (GeoXT, Trimble Inc., Sunnyvale, CA, USA) and later differentially corrected to sub-meter accuracy using local GPS base stations (http://www.trignet.co.za/). The individual crowns of the field measured trees were digitized as polygons from the LiDAR derived canopy height model. The maximum canopy height for each crown polygon was then calculated and regressed against the field data for that particular tree. 2.4. Analytical approach The distribution of these height data values, for both top of canopy and for the vertical profiles derived from the LiDAR data, were compared between different treatments and against the control areas by means of the Kolmogorov–Smirnov test, which is sensitive to differences in both the location and shape of the empirical cumulative distribution functions (Sokal and Rohlf, 1995). Differences in canopy vertical heterogeneity were determined by applying the Shannon–Weiner diversity index (SWDI) to the vertical profile data. The Shannon–Weiner diversity index stems from information theory (Shannon and Weaver, 1962) and is widely used to characterize species diversity within a community and accounts for both abundance and evenness of the species present (Magurran, 1988, 2004). The index is calculated according to the following equation:
H¼
s X i¼1
pi ln pi
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Fig. 1. Location and layout of the Makhohlola treatments within the Kruger National Park, South Africa. Inset image displays canopy cover of woody vegetation in dark green.
whereby pi is the proportion of individuals found in the ith species, s is the total number of species found in the community, and ln is the natural logarithm. The principle of this index is transferable to structural data in categorical format, and it is a commonly used metric of landscape spatial pattern (O’Neill et al., 1988; Turner, 1990). Here, we applied the index to the proportional distribution of foliage within the vertical profile of vegetation canopies.
3. Results 3.1. Validation of airborne mapping Linear regression indicated a strong positive relationship between field measured and remotely sensed vegetation height, with r2 = 0.92, p < 0.01 and a standard error of the estimate of 1.17 m (Fig. 2). Our ground-validation exercise therefore showed that a high level of confidence could be placed in the accuracy of vegetation height data obtained from the CAO.
3.2. Vegetation three-dimensional structure The reduction of different combinations of herbivory and fire at the treatment sites caused substantial differences in woody vegetation structure compared to the control area. For example, a cross-sectional view of the LiDAR returns clearly showed greater woody cover and taller woody canopy across all treatments plots, particularly in those protected from herbivory (Fig. 3). These structural differences were best quantified in terms of the frequency of occurrence (per given area) of vegetation canopy height across the study site (Fig. 4). Through area-normalization by hectare, these frequency distributions represent both the height and cover components of vegetation structure. The control area exposed to both fire and herbivory was sparsely vegetated (0.6% cover), and the majority of the cover occurred in height classes of less than 3 m (Fig. 4a). The treatment that was exposed to herbivores over the long-term but was recently protected from fire had greater vegetation cover (2.6%), but it was largely contained in height intervals of less than 4 m above ground level (Fig. 4b). This pattern showed
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tion of foliage within the canopy (Fig. 5). The Shannon–Weiner diversity index (SWDI) was lowest in the control area, where the small amount of foliage present was evenly distributed within the vertical profile (Fig. 5a). The SWDI was highest in the plots protected from herbivores (Fig. 5c and d), where foliage was more diversely distributed within the vertical profile, particularly in the plot that was also recently protected from fire (Fig. 5d). Although the long-term herbivore effect was the most prominent, recent fire suppression rapidly altered the distribution of foliage in the 0–3 m height intervals (Fig. 5a and c vs. b and d). The vertical distribution of foliage reflected the large differences in tree to shrub ratios across the treatments. In the control area, we only found one laser return from a tree canopy (>3 m) for every 19 returned from shrub canopy (<3 m). The ratio increased to 1:6 in the treatment recently protected from fire but not herbivores, and to more than 1:2 in the treatments protected from herbivores. Therefore, different height classes of vegetation responded differentially to fire and herbivore disturbances, in terms of both canopy height and vertical profile. 3.4. Responses by height class
Fig. 2. Field validation of woody canopy height from 350 randomly selected points during the mapping campaign in April 2008.
that although woody cover and height may rapidly increase with decreased exposure to fire, they are still constrained below a 4 m threshold by herbivores. In the absence of herbivores, there was 17.2% woody cover in the plot exposed to fire (Fig. 4c) and 18.5% cover in the plot that was recently protected from fire (Fig. 4d). Vegetation frequently occurred in height classes of greater than 4 m in both of these cases. The long-term exclusion of herbivores therefore markedly influenced vegetation height at intervals greater than 4 m, while the influence of fire in limiting vegetation was apparent in the 0–3 m intervals (Fig. 4a and c vs. b and d). 3.3. Structural heterogeneity Long-term protection from herbivory greatly impacted vegetation structural heterogeneity, defined here as the vertical distribu-
To differentiate height class specific responses, we examined the percentage difference in canopy area between control and treatment sites for different vegetation height classes (Fig. 6). Compared to the control, canopy area was greater in the area recently protected from fire for shrub (0–3 m) and small tree (3–6 m) height classes, but did not differ in medium tree (6–9 m) and tall tree (9– 12 m) height classes. The two long-term herbivore exclusion sites contained more canopy area in the shrub and tall tree height classes than did the control, but the exclusion plot recently protected from fire contained more canopy area in both the shrub and tall tree size classes. Compared to the control, the areal extent of small tree canopies was considerably greater in both long-term herbivore exclusion plots (42 times and 66 times), with the largest difference observed in the exclusion plot that was also recently protected from fire. Interestingly, the area of medium tree canopy was 38 times greater than the control in the exclusion plot exposed to fire, but was only 18 times greater than the control in the exclusion plot recently protected from fire. Therefore, while the small tree height class
Fig. 3. Cross-profile comparisons of the herbivore and fire experimental treatments and the control landscape. Profiles display the LiDAR point cloud of both ground surface and vegetation canopy returns. Solid redline marks the boundary between control and treatment sites.
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Fig. 4. Distribution of vegetation height values across: (a) control area exposed to long-term herbivory and fire; (b) area exposed to long-term herbivory but recently protected from fire (7 yr); (c) area protected from herbivory over the long-term (34 yr) but exposed to fire; and (d) area protected from herbivory over the long-term (34 yr) and recently protected from fire (7 yr). Histograms represent the frequency of canopy height values (as determined from LiDAR) per hectare. Height distribution differed significantly between all three treatments, and all three treatments were significantly different to the control (Kolmogorov–Smirnov, p < 0.001).
showed a linear response to the removal of disturbance agents, the medium tree height class displayed a more complex relationship. 4. Discussion and conclusions 4.1. Relative influence of fire and herbivory on savanna structure The relative influence of fire and herbivory has been difficult to elucidate in savanna ecology (Dublin et al., 1990; Trollope et al., 1998; van Langevelde et al., 2003). Previous studies of vegetation structure and dynamics in KNP have hypothesized that both fire and large herbivores (such as elephant) are responsible for the observed reduction in tree cover on the basaltic soils over the last few decades (Eckhardt et al., 2000; Trollope et al., 1998). The structural patterns that we uncovered at Makhohlola suggest that herbivores bear greater responsibility for limiting woody vegetation height, cover and structural heterogeneity on the southern basalts of KNP. Moreover, many of these 3-D structural differences can only be attributed to mega-herbivores (Owen-Smith, 1988) such as elephant (Loxodonta africana) and giraffe (Giraffa camelopardalis), by virtue of their height and feeding behaviors, as the most pronounced structural differences occurred above a 4 m height threshold. The experimental manipulation of fire occurrence and herbivore access to the study site revealed heterogeneous responses of
different height classes of vegetation to the removal of one or both of the disturbance agents. The heterogeneous nature of disturbance effects has been well documented (Levick and Rogers, 2008; Pickett and White, 1985; Turner, 1989), but has primarily been considered from a two-dimensional landscape patch-mosaic point of view. Our study was confined to one landscape (upland basalts), but we found heterogeneous responses to disturbance agents within different height classes of vegetation canopy. These findings would not have been possible without the use of 3-D remote sensing, which enabled the detailed exploration of vegetation structure at multiple height class intervals. Our results showed that fire rapidly affects vegetation canopies in the 0–3 m height interval above ground level, a zone often referred to as ‘the fire trap’ (Bond and Keeley, 2005) and a height class that would be expected to be influenced by fire. Interestingly, however, reduced fire occurrence was associated with less vegetation canopy in the medium tree size class (6–9 m) in the absence of herbivory. The different patterns in small and medium tree height classes between the two herbivore exclusion plots suggest a possible feedback with plant competition. By restricting plant growth in the ‘fire trap’, growth in the medium height class might be promoted by greater resource availability, although the timeframe under consideration may have been too short for such feedbacks to have occurred. Nonetheless, it is likely that the effects of fire in the initial 3 m will have cascading effects through the rest of the vegetation profile
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Fig. 5. Vertical diversity of foliage distribution within the canopy across: (a) control area exposed to long-term herbivory and fire; (b) area exposed to long-term herbivory but recently protected from fire (7 yr); (c) area protected from herbivory over the long-term (34 yr) but exposed to fire; and (d) area protected from herbivory over the longterm (34 yr) and recently protected from fire (7 yr). Foliage distribution differed significantly between all three treatments, and all three treatments were significantly different to the control (Kolmogorov–Smirnov, p < 0.001). SWDI = Shannon–Weiner diversity index (relative).
(Bond, 2008). Indeed, many studies of herbivory and/or fire effects on savanna vegetation have yielded complex and even contrasting results (Sankaran et al., 2008), but further exploration of fire and herbivory effects from an explicit 3-D perspective of vegetation is likely to advance our understanding of these complexities. 4.2. Limitations It is important to acknowledge three limitations of the experimental design at Makhohlola. First, the experiment was restricted to one un-replicated site on nutrient-rich basaltic soils. We would expect the relative influence of fire and herbivory to differ on nutri-
ent-poor granitic substrates, which offer lower forage quality to herbivores (Grant and Scholes, 2006). Second, the design allowed for the testing of fire suppression over the short-term, but not longer-term fire return interval, fire intensity, or season of burning, all of which have been shown to be important determinants of fire impact in savanna systems (Higgins et al., 2007; van Wilgen et al., 2003). Third, while this study explored structural patterns that have arisen from 34 yr of reduced herbivory, and 7 yr of fire suppression, these periods may be too brief to observe even longerterm vegetation responses to herbivore and fire manipulation. Although fire predominantly appeared to restrict woody canopy development in the initial 3 m above ground level, fire in this shrub
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bivore and fire management policies consider a 3-D perspective of vegetation structure. Vegetation TPCs need to be defined in a height-specific manner, as we have shown that different height classes respond differently to herbivory and fire. Our LiDAR analyses provided detail on the 3-D structural responses of ecosystems to management actions, but their full potential to inform management decisions cannot be realized until the linkages between 3-D structure, biodiversity and ecological functioning are explicitly clarified. We know that taller trees promote both biodiversity (Cumming et al., 1997; Fenton et al., 1998) and ecological functioning (Belsky and Canham, 1994; Bond, 2008; Treydte et al., 2007; van de Koppel et al., 2002), but we lack an understanding of which height classes, and which proportions of their occurrence, are most important. Three-dimensional remote sensing has opened the door to tackling these issues, but the most effective use of remotely sensed data is through their fusion with appropriate field investigations (Chambers et al., 2007). Defining meaningful TPCs for vegetation in savannas requires intensive investigation of the relationship between 3-D structure, biodiversity and ecological functioning. Although 3-D TPCs are yet to be defined for KNP ecosystems, our study provides managers with insight into the continuum of savanna vegetation structure and heterogeneity on basaltic substrates. While no official TPC was triggered, herbivores (mega-herbivores in particular) and fire have reduced/limited vegetation growth to a degree that likely holds negative consequences for biodiversity and ecological functioning. We consider the extent of the structural differences to be of major conservation concern. Fig. 6. Height class specific differences in the area of canopy cover between the three treatments and the control.
layer may prevent the recruitment of taller trees, causing longerterm consequences for the vegetation 3-D structure and diversity. 4.3. Implications for the conservation and management of savanna landscapes Changes to herbivore access and fire regime markedly altered vegetation 3-D structure and heterogeneity at the Makhohlola experimental site. The structural differences found here have important implications for the conservation and management of savanna landscapes, as modification of herbivore numbers and fire regime impact not only the structure of vegetation, but also the organisms that depend upon those structures (Cumming et al., 1997). Our findings highlight the active role that conservation managers can play in modifying vegetation structure through herbivore and fire management, and suggest that managers have the potential to directly influence biodiversity and ecological functioning through their actions or inactions. In KNP, managers use monitoring endpoints, known as thresholds of potential concern (TPCs), as an integral part of their strategic adaptive management approach to conservation (Biggs and Rogers, 2003). The TPCs are a set of operational goals that define the upper and lower limits along a continuum of change in selected ecological indicators for which ecosystems are managed (Rogers and Biggs, 1999). The TPCs act as early warning systems to help managers decide when intervention is necessary. A key challenge to managers in KNP, and other savanna parks, is defining the upper and lower limits of ‘acceptable’ change in woody structure. Meaningful thought has been given to defining these limits for woody cover (Gillson and Duffin, 2007), but a 3-D consideration of these limits is lacking. Since we have illustrated the extent to which herbivores and fire can modify the 3-D structure and heterogeneity of savanna vegetation, it is essential that the operational goals in her-
Acknowledgements We thank Izak Smit and the entire SANParks staff for their outstanding logistical and scientific support. We greatly appreciate the help of Navashni Govender in tracing the history of the experimental site. We commend the SANParks managers of the time for their foresight in establishing the Makhohlola exclosure. We thank Ruth Emerson, James Jacobson, Matt Colgan and Robin Martin for assistance with field work and image analysis. This research was funded by the Andrew Mellon Foundation. The Carnegie Airborne Observatory is supported by the W.M. Keck Foundation and William Hearst III.
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