In the study by Vianna et al. ( 2018), mean arterial pressure (MAP) was found to be unchanged up to 60 min after water ingestion.

Although the classic formula, MAP = DBP + 0.33 × PP (where DBP is the diastolic blood pressure, PP the pulse pressure and ⅓ = 0.33 the form factor), has been extensively used, it should be kept in mind that other formulae exist (i.e. the formula using a form factor of 0.412 instead of 0.33) [3].

Alternative calculation of MAP might yield superior associations with target organ damage [3] or more accurate estimations of MAP compared with direct intra-arterial recordings.

Furthermore, several automated oscillometric blood pressure devices provide MAP values using their own embedded algorithms.

Of course, given that the same calculation of MAP was used before and after water ingestion, it is unlikely that MAP measured using another formula or form factor would change this outcome.

However, it is important to know how exactly the MAP values are calculated, in order to be able to extrapolate or interpret the results in comparison to other studies.

Still, the pressure response to water ingestion is controversial, because previous studies have found the opposite results, i.e. a significant increase [4].


Finally, algorithms for BRS calculation used in the literature vary greatly in technical, computational and methodological perspectives.

It is known that the sequence method is characterized by strict threshold criteria, with no evidence about the optimal threshold values.

Altering these thresholds can have a great impact on the computed BRS values.

In this study, the R–R interval threshold was chosen as 1 ms, which is much lower than the widely used threshold of 4 ms.

Although there is no gold-standard R–R interval threshold, it should be kept in mind that altering these threshold values can lead to different BRS estimations.

For this reason, it could be suggested that BRS should be estimated by more than one method.

For example, using frequency domain algorithms, which may be more robust in specific circumstances, in addition to the time domain method that was followed in this study, might provide more robust results concerning BRS responses.


We are happy that our study [6] has received the attention of others and pleased to have the opportunity to respond and debate the merits of our approach.

In their Letter to the Editor, Papaioannou et al. [ 3] raise some interesting points regarding the methods of our study and how they relate to the estimation of cardiac baroreflex sensitivity, which we would like to address and provide further clarification.

We are aware and in agreement with the statement by Dr Papaioannou and colleagues that body posture is a critical factor when assessing neural cardiovascular function at rest and during perturbational conditions.

In this regard, our group has recently demonstrated that both cardiac and peripheral sympathetic outflow to postexercise ischemia (i.e. muscle metaboreflex activation) can be modulated by mobilization of central blood volume [1, 4].

Whether the arterial baroreflex responses to water drinking are dependent on the body posture is unknown.

However, this was not part of our study question.

As we have clearly stated in the Methods section, subjects were studied in a supine position, which is a standard position for human neural cardiovascular control studies and the majority of studies on water drinking.

It is important to clarify further that subjects ingested the 500 ml of water or saline in this position using a flexible straw; therefore, there was no positional change.

This approach also minimizes limb movement and muscle activation, which would jeopardize the muscle sympathetic nerve activity recordings.

In our study, mean arterial pressure remained unchanged after ingestion of either bottled water or saline.

Of note, this is a common finding in young healthy subjects [2].


With regard to mean arterial pressure calculations, Dr Papaioannou and colleagues commented on the importance of describing how mean arterial pressure was derived, because the use of different formulae might limit the extrapolation and interpretation of our findings.

With all due respect, we disagree, and we would like to provide the following points for consideration.

Firstly, blood pressure was measured on a beat-to-beat basis using a valid and reliable technique (i.e. finger photoplethysmography).

In this sense, mean arterial pressure was calculated by a time-weighted integral of the instantaneous pressures derived from the area under the curve of the pressure–time waveform of the entire cardiac cycle.

Secondly, our interpretation has emerged from a study where the subjects participated in both experimental (water drinking) and control (saline drinking) trials, and we used the same blood pressure measurement before, during and after each intervention.

Therefore, we are confident that our results and interpretations are valid and reliable and would stand regardless of the way in which mean arterial pressure is calculated.

In their letter, Dr Papaioannou and colleagues also pointed out the lack of standardization in the literature with regard to the use of the sequence technique for the estimation of cardiac baroreflex sensitivity.

We agree that there are no absolute or agreed upon ideal parameters for analysis (i.e. systolic pressure and R–R interval thresholds).

However, in terms of their concern regarding the R–R interval threshold used in our study, we re-analysed our data using a threshold of 4 ms, as suggested in their letter, and the results remained unchanged.

Furthermore, the assessment of agreement between 1 and 4 ms threshold provided a high and significant intraclass correlation coefficient (0.938; P < 0.05).


Lastly, Papaioannou et al. [ 3] advocate the use of frequency domain analyses to address the research question further.

It is important to mention that our hypothesis was focused on the sympathetic branch of arterial baroreflex function, for which we had direct muscle sympathetic nerve activity measurements.

Although we would welcome the use of frequency analyses to explore cardiac baroreflex sensitivity further, we are confident in our findings using the sequence technique.

In summary, our data provide new insights on the potential contribution of the sympathetic baroreflex in the maintenance of arterial blood pressure after water drinking in young healthy subjects.

Furthermore, independently of the mathematical approach, our findings indicate a minimal role of the cardiac baroreflex in the regulation of arterial blood pressure after water ingestion.

Nevertheless, we acknowledge there are no perfect analyses and always welcome debate on different ways to evaluate data, as provided by Dr Papaioannou and colleagues.


Regulation of microtubule (MT) 1 distribution is of critical importance for many cellular processes, including directed cell motility, cell division, and establishment of cell polar- ity.

In the developing nervous system and during nerve re- generation, axon growth depends on assembly of polarized MT arrays; however, axon guidance depends on the coor- dinated action of both MT assembly in the distal axon shaft and actomyosin-based lamellar motility in the neu- ronal growth cone (Lin et al., 1994; Tanaka and Sabry, 1995; Letourneau, 1996).

In fact, dynamic interactions be- tween MTs and the actin cytoskeleton appear to be a pre- requisite for directional cell motility in general.


Neuronal growth cones (GC) have two distinct domains created by the largely discrete localization of F-actin and MTs.

The central domain (C-domain) has a high density of MTs and organelles and is separated from the F-actin-rich peripheral domain (P-domain) by an interface referred to as the transition (T) zone.

F-actin-based motility in the P-domain has been shown to result from constitutive plus- end-directed actin assembly into networks and filopodia at the leading edge and the concurrent action of myosin motors capable of translocating actin networks away from the leading edge centripetally towards the central do- main-a process referred to as "retrograde F-actin flow" (Forscher and Smith, 1988; Mitchison and Kirschner, 1988; Cramer et al., 1994; Tanaka and Sabry, 1995; Lin et al., 1996; Mitchison and Cramer, 1996).


Several lines of evi- dence suggest that F-actin networks and retrograde flow pose a barrier to MT advance and MT-dependent or- ganelle transport into the P-domain.

For example, clear- 1034 ance of F-actin networks subsequent to cytochalasin expo- sure results in rapid MT and organelle advance into the P-domain (Forscher and Smith, 1988; Waterman-Storer and Salmon, 1997); furthermore, recent evidence suggests that retrograde F-actin flow can translocate MTs from pe- ripheral F-actin domains and decreases MT plus-end as- sembly rates in newt lung cells (Waterman-Storer and Salmon, 1997).

Finally, MT advance and retrograde flow are inversely correlated during GC interactions either with native target substrates (Lin and Forscher, 1995) or Ig CAM-coated bead substrates (Letourneau et al., 1987; Lin et al., 1996; Suter et al., 1998).


Abundant and long-standing evidence implicates pro- tein kinase C as a regulator of cytoskeletal organization and neurite outgrowth.

For example, treatment with acti- vators of PKC such as phorbol dibutyrate (PDBu) or 12- O -tetradecanoylphorbol-13-acetate (TPA) result in neurite extension in embryonic ganglia explants (Hsu et al., 1989), neuroblastoma cells (Fagerstrom et al., 1996), and NGF- treated PC12 cells (Hundle et al., 1995), as well as changes in filopodial and lamellipodial protrusions in rat cerebral neurons and affect MT distribution in SH-SY5Y neuro- blastoma growth cones (Rosner and Fischer, 1996).


Con- versely, PKC inhibition can result in reduced rates of neu- rite outgrowth as well as dramatic changes in growth cone structure, sometimes referred to as "GC collapse" (Bixby, 1989).

Given that several well-known PKC substrates (e.g., GAP-43 and MARCKS) interact with and affect F-actin, previous studies have typically invoked PKC regu- lation of F-actin structure and motility to explain these ef- fects (Meiri et al., 1988; Hartwig et al., 1992; He et al., 1997; Dent and Meiri, 1998).


Microtubule-associated pro- teins (MAPs) such as MAP1B and MAP2 and Tau (Gor- don-Weeks, 1993; Liu et al., 1999) are also abundant PKC substrates in axons, and phosphorylation by PKC tends to inhibit their MT assembly-promoting activity (Mori et al., 1991); however, the mechanism by which MAP or tau phosphorylation promotes increased neurite outgrowth appears to involve complex interactions between multiple signaling pathways (Goold et al., 1999) and is not well un- derstood.


In this report, we describe a novel mechanism by which PKC regulates MT advance by controlling assembly of a highly dynamic pool of MTs normally residing in the T zone.

PKC activation promotes MT invasion deep into the P-domain, where MTs are rarely found under control con- ditions by a process that increases the lifetime of MT growth events.


Primary culture of Aplysia bag cell neurons and video-enhanced differen- tial interference microscopy (VE-DIC) was performed as previously de- scribed (Forscher et al., 1987).

Appropriate stock solutions of cheleryth- rine chloride, calphostin C, bisindolylmaleimide 1, Gö-6976, Ro32-0432, PDBu, 4- ␣ -phorbol, 1-oleoyl-2-acetyl- sn -glycerol (OAG), nocodazole, taxol, vinblastine (Calbiochem) and other drugs were prepared in DMSO and stored in Ϫ 20 Њ C. Fresh dilutions were made before each experiment in artificial sea water containing 2-3 mg/ml BSA as an amphipathic vehi- cle to aid drug solubilization in the high salt medium.

PDBu was used rather than phorbol-12-myristate-13-acetate (PMA or TPA) since it is bet- ter characterized in Aplysia (Sossin and Schwartz, 1994) and there was no observable difference between the actions of PDBu and PMA.

We mea- sured the absorption profile of the various PKC activators and inhibitors (data not shown) and have found that most of these PKC-related drugs absorb light in the green range.

When VE-DIC was performed with white or green light, phototoxic effects were greater in the presence of these drugs.

Therefore, VE-DIC was performed with 650-750-nm light except for calphostin C, since this compound is actually activated by 450-650-nm light (Gopalakrishna et al., 1992).


After each pharmacological experiment, cells were fixed and stained for F-actin and microtubules as described (Forscher and Smith, 1988), with the following modifications.

F-actin was labeled with alexa 568 or 594 phalloidin.

For MTs, alexa 488-labeled secondary antibody was used.

The alexa dyes (Molecular Probes) were brighter, more photostable, and gave better separation of emission spectra relative to FITC and rhodamine.


Retrograde flow of F-actin in lamellipodia was measured using Con- A-coated or polyethylenimine-coated 500-nm silica beads (Bangs Labo- ratories) in the presence of 3 mg/ml BSA.

Verification of beads as F-actin markers in this system, ionizing radiation-laser trapping and measure- ment of bead displacement were as previously described (Lin and For- scher, 1995).


MT density in the P-domain was measured by counting the number of mi- crotubules spanning 75% of the P-domain as defined by distal and proxi- mal borders of F-actin bundle labeling (see Fig. 3).

Data was normalized between growth cones by GC area and expressed as the number of MT/ 100 m 2 ; i.e., MT density.


Handling of Aplysia, dissection of abdominal ganglion, Western blots, and quantification of immunoblots were as previously described (Nakhost et al., 1998).


In Aplysia, the pleural-pedal ganglia are symmetrically paired on either side of the animal.

In all experiments, the ganglion on one side of the animal was used as a control for the corresponding one on the other side.


The ganglia were desheathed to facilitate penetration of pharmaco- logical agents and transferred to resting medium (the same as dissecting medium, but with 460 mM NaCl, 11 mM CaCl 2 , 55 mM MgCl 2 ; as de- scribed by Sossin and Schwartz, 1994).

The ganglia were incubated in ei- ther 1 M 4 ␣ -PDBu (control) or 1 M 4 ␤ -PDBu (experimental) for 1 h at 15 Њ C (physiological temperature of Aplysia).


The ganglia were then washed twice with microtubule stabilization buffer (0.1 M MES, 1 mM EGTA, 0.5 mM MgCl 2 ) containing 1 mM GTP and 10% glycerol (RGG buffer) and homogenized in 120 l of RGG buffer containing protease in- hibitors (20 g/ml aprotinin, 5 mM benzamidine, and 0.1 mM leupeptin) and 1% Triton X-100.


The samples were centrifuged at 15 Њ C for 1 min at 800 g to remove any unhomogenized debris.

The resulting homogenates (100 l) were centrifuged at 100,000 g for 30 min.

Supernatants were iso- lated and added to 20 l of sample buffer.


Pellets were either resuspended in sample buffer or resuspended in 120 l RGG plus protease inhibitors and divided into two 50- l fractions.

Subsequently, one fraction from each of the experimental and control ganglia was incubated with 100 nM no- codazole (in RGG plus protease inhibitors), while the other fraction was incubated with vehicle.


The samples were incubated at 15 Њ C for 15 min, and then centrifuged at 15 Њ C for 30 min at 94,000 g .

The supernatants were removed and added to 12 l of sample buffer.

The pellets were resus- pended in 72 l of sample buffer.


The samples were loaded onto 9% SDS- polyacrylamide gels and analyzed by immunoblotting with antitubulin an- tibody (clone DM 1A; Sigma-Aldrich).


Microtubule dynamics were assessed using the recently described fluores- cent speckle microscopy (FSM) technique (described in Waterman- Storer, 1998; Waterman-Storer and Salmon, 1998).

Neurons were injected with ف 1 mg/ml rhodamine-labeled tubulin (Cytoskeleton Inc.) in injection buffer (100 mM Pipes, 1 mM MgCl 2 , 1 mM EGTA) and allowed to re- cover for ف 60 min in L15-artificial sea water medium (Forscher et al., 1987) supplemented with 3 mg/ml BSA.

Under these conditions, MT 1035 speckles could be clearly discerned in distal axonal regions and used as fi- duciary marks for assessment of MT growth, shrinkage, pause, and trans- location rates and lifetimes.


MT image sequences were obtained using a Nikon Eclipse TE300 microscope equipped with a Photometrics Quantix 57 back-illuminated frame transfer cooled CCD camera and filter wheels (Ludl Inc.) for changing both excitation and emission wavelengths and rapid switching between fluorescence and DIC imaging modes.

Meta- morph control software (Universal Imaging Corp.) was used for instru- ment control and image analysis.

Images were recorded every 10 s using 300-500-ms integration times for fluorescent MTs and 50-ms for DIC.


Contrast of the speckles was enhanced by processing the fluorescent im- ages sequentially with the following spatial filters: unsharp mask, low pass, laplace edge enhancement, and a final low pass.

For DIC-fluorescent overlays, a threshold look-up table was applied to MT images before com- bining with the DIC image to clear low level background noise.


Representative examples of microtubule dynamics and the structural re- sponse of the growth cone to PKC activation are viewable as Quicktime movies.

In the single-channel microtubules dynamics examples, the open arrow follows the distal MT end and the closed arrow is an internal refer- ence mark.

The other examples are dual channel DIC-microtubule movies with MTs pseudocolored in green.

All movies are labeled according to the corresponding figure except the example of MT buckling.

Online supple- mental materials can be found at http://www.jcb.org/cgi/ content/full/152/ 5/1033/DC1.


Fig. 1 illustrates the typical C-, P-, and T-domain struc- tures of a growth cone under control conditions (see For- scher and Smith, 1988), note the relatively low density of MTs penetrating into the P-domain.

Fig. 2 shows the ef- fects of PKC activation on growth cone structure and the underlying MT and actin cytoskeleton.


PKC activation with 1 M PDBu (Sossin and Schwartz, 1994) resulted in relatively minor acute ( ف 5 min) morphological effects at the level of VE-DIC imaging, with the exception of rapid attenuation of T zone ruffling (not shown).

After 30 min in PDBu (Fig. 2 B), C-domain organelles appeared to have advanced slightly (A and B, dotted line) and attenuation of ruffling persisted.


Visualization of F-actin (Fig. 2 C) af- ter 30 min in 1 M PDBu revealed an intact P-domain F-actin structure, including well-defined F-actin bundles; however, F-actin hotspots corresponding to ruffling in the T zone were notably absent (Fig. 2 C).

Surprisingly, immu- nofluorescent visualization of ␤ -tubulin revealed that a striking advance of MTs into the F-actin-rich P-domain had occurred during PDBu treatment (Fig. 2 D).


This ro- bust advance or "invasion" of the MTs into the P-domain was unexpected, occurred as early as 5 min after 1 M PDBu application, and with doses of PDBu as low as 10 nM for 30 min (data not shown).

Invading microtubules were mostly unbundled, straight, and, in many cases, ran along or near F-actin cables (Fig. 2, C and D, arrowheads; see also Fig. 4, C and D).


Treatment with 1 M 4- ␣ -phor- bol (Fig. 2, I-L), an inactive phorbol-ester analogue, had no observable effects on growth cone motility or structure (Fig. 2, E-H).


To determine whether these effects were due to PKC activation, we preincubated cells with 10 M bisindolyl- maleimide 1 (Bis 1), a specific PKC inhibitor that interacts with the ATP binding site, for 15 min, and then added 1 M PDBu and 10 M Bis 1 for an additional 30 min.

Es- sentially all the morphological (Fig. 2, I and J) and cyto- skeletal (K and L) changes observed during PDBu treat- ment were absent in the presence of Bis 1; note that only a few MTs invade the P-domain (Fig. 2 L) and actin-based ruffling in the T zone is still clearly present (J and K).

In 1036 addition, treatment with 10 M Bis 1 alone for 45 min had little or no effect on growth-cone motility or cytoskeletal structure (Fig. 2, M-P).

In summary, Bis 1 did not affect basal GC motility, morphology, or cytoskeletal structure, but completely inhibited PDBu-mediated changes in these attributes.


Microtubule invasion levels (shown in Fig. 3) were quantified by determining the density of MTs spanning 75% of the P-domain, the latter defined by F-actin label- ing (see Materials and Methods; Fig. 3, inset).

Under con- trol conditions, there were 0.9 Ϯ 0.2 MT/100 m 2 .

After 30 min of 1 M PDBu treatment, MT density increased to 6.7 Ϯ 1.2 MT/100 m 2 .

In addition, chronic activation of PKC with lower doses of PDBu (e.g., 40 nM for 16 h) had simi- lar effects on MT distribution (data not shown).


In con- trast, after inhibition of PKC with 10 M Bis 1 for 45 min, there were 0.7 Ϯ 0.1 MT/100 m 2 (Fig. 3); i.e., similar to control levels.

Importantly, PDBu did not increase MT density above control levels in the presence of 10 M Bis 1.

Treatment with 1 M 4- ␣ -phorbol for 30 min also had no effect on the number of MTs invading the growth cone.

Treatment with 10 M OAG resulted in a less robust but statistically significant advance of MTs (3.1 Ϯ 0.8 MT/100 m 2 crossed the 75% threshold), as expected from its lower potency relative to PDBu.


In summary, activation of PKC was found to significantly increase the density of MTs found in the distal P-domain.

This effect was not present with inactive phorbolester analogues and was completely prevented by specific PKC inhibitors such as Bis1 (Figs. 2 and 3) as well as 10 M Gö-6976 or 10 M Ro32-0432 (data not shown).


There is evidence that P-domain F-actin and the process of retrograde flow itself inhibits MT advance and plus-end assembly (Forscher and Smith, 1988; Waterman-Storer and Salmon, 1997).

Thus, a possible mechanism for PDBu- mediated MT advance was a change in retrograde F-actin flow.


Using a laser trap-assisted flow-coupled bead assay to quantitatively assess F-actin flow rates as previously de- scribed (Lin and Forscher, 1995), we found no evidence for a decrease in retrograde flow of F-actin in growth cones subsequent to PDBu treatment.


Fig. 4 (A and B) il- lustrates an example of a retrograde flow assay before and after treatment with 1 M PDBu for 30 min.

Note that flow actually increased slightly after 30 min in PDBu (6.2 Ϯ 1.9 m/min) compared with controls (4.9 Ϯ 1.5 m/min) in this experiment; however, this increase was not significant over all experiments done ( n ϭ 6; 7.9 Ϯ 7.0% increase in retrograde flow after PDBu).


The presence of intact F-actin structure as well as MT extension was verified by post- experiment fixation and MT immunofluorescence, note that MT advance often occurred along lines defined by F-actin cables (Fig. 4, C and D, arrowheads).

These results indicate that PKC-mediated MT extension is not due to at- tenuation of retrograde flow.


In addition, experiments to investigate changes in the gel exclusion properties of the P-domain using microinjected FITC-dextrans indicate that there is little change in the functional pore size of the P-domain after PDBu treatment, suggesting that simple al- teration of the physical properties of the cytomatrix are not likely to account for the observed effects (our unpub- lished observations, see Discussion).


To address whether MT assembly was involved, PDBu ef- fects were assessed under conditions where MT dynamics were damped with low concentrations of nocodazole or taxol.

We specifically chose conditions previously shown to inhibit plus-end MT assembly without significantly re- ducing polymer mass (Bamburg et al., 1986; Tanaka et al., 1995; Rochlin et al., 1996) or, alternatively, to stabilize MTs (Letourneau et al., 1987; Jordan and Wilson, 1998b).


Fig. 5, A-D, illustrates the effects of exposure to 100 nM nocodazole on growth-cone structure and the cytoskele- ton.

Similar effects were observed after exposure to 1 M taxol (Fig. 5, E-H).


Note retraction of the C-domain (Fig. 5, A and B, E and F, dotted lines) and depletion of MTs from the T zone (D and H) observed after a 30-min expo- sure to either nocodazole or taxol.

Interestingly, despite essentially complete separation of C and P cytoplasmic do- mains and the underlying microtubule retraction, retro- grade F-actin flow continued unabated (data not shown) and P-domain F-actin remained relatively unperturbed in both cases.


These results suggest that dynamic MTs are not necessary for maintenance of retrograde F-actin flow, but are a prerequisite for MT advance out of the C-domain into more distal regions.

In agreement with these results, persistent growth-cone motility and absence of P-domain MTs were reported after treatment of Xenopus neurons with nanomolar levels of vinblastine (Tanaka et al., 1995).

Note also the relatively high level of diffuse tubulin labeling in nocodazole (Fig. 5 D) when compared with taxol-treated growth cones (Fig. 5 H), where diffuse tubulin labeling is low, as expected from the decrease in critical tubulin con- centration.


We then tested whether PDBu-mediated invasion re- quires dynamic MTs by treating growth cones with taxol or nocodazole at or below the levels illustrated above.

In the absence of PDBu, all of the MT drugs examined (including vinblastine and colchicine; data not shown) decreased the density of MTs in the T zones and P-domains (as in Fig. 5, A-H) in a dose-dependent manner.

The effects of nocoda- zole were examined quantitatively since this drug was found to be highly potent and its mode of action is re- ported to be somewhat less complex and more readily re- versible than the others (Jordan and Wilson, 1998b).


Cells were treated with 0, 10, 25, or 100 nM nocodazole Ϯ PDBu and P-domain MT density was assessed (Fig. 5 I).

In the absence of PDBu, distal axonal MT's (i.e., in the T zone and P-domain) were highly sensitive to nocodazole, as pre- viously reported (Bamburg et al., 1986), with inhibitory ef- fects at doses Ͼ 10 nM. In the presence of 1 M PDBu, clear and highly significant ( P Ͻ 0.001) inhibitory effects on MT extension were observed at nocodazole doses as low as 10 nM and inhibition of the PDBu response was es- sentially complete in 100 nM nocodazole.


The extreme no- codazole sensitivity observed after PDBu treatment sug- gests that MTs assembled subsequent to PKC activation may be highly dynamic (Jordan et al., 1992; Rochlin et al., 1996; Challacombe et al., 1997; Jordan and Wilson, 1998a).

Low doses of vinblastine or taxol (Fig. 5 I) also inhibited PDBu-mediated MT advance.

In summary, these results indicate that MT assembly is a necessary component of PDBu-mediated MT advance.


To assess PDBu effects on microtubule assembly using an independent methodology, biochemical experiments were performed on Aplysia central nervous system tissue.

De- tecting changes in soluble tubulin biochemically in the face of high baseline levels was not possible due to signal-to- noise problems.

However, given the apparent high sensitiv- ity of newly assembled MTs to nocodazole, we tested whether PDBu would increase the nocodazole-sensitive MT pool as an alternative approach.

Experiments were per- formed on paired nervous systems from the same animal treated with either 1 M PDBu or 1 M of the inactive iso- mer 4-␣ phorbol.

Ganglia were lysed in microtubule stabili- zation buffer, and free tubulin and microtubules were sepa- rated by sedimentation.


We found a small but significant increase in the percentage of tubulin found in the pellet af- ter PDBu treatment (Fig. 6, A-C).

To determine whether this increase was due to assembly of nocodazole-sensitive microtubules, we assessed the amount of tubulin released from pellets by 100 nM nocodazole.

Nocodazole induced a significant increase in the amount of tubulin released from pellets prepared from PDBu-treated ganglia (Fig. 6, D-F); furthermore, the amount of tubulin released by nocodazole approximately matched the increase in tubulin sedimented after PDBu (Fig. 6 C).

Paradoxically, treatment with low doses of nocodazole alone resulted in a small decrease in the amount of tubulin released from the Triton-insoluble pellet (Fig. 6, D and E).

Similar effects have been reported in Xenopus extract preparations (Canman and Bement, 1997); however, this effect is not well understood and more- over was not observed in the presence of PDBu.


Overall, these biochemical results are consistent with PDBu increas- ing assembly of a dynamic (i.e., nocodazole-sensitive) pool of microtubules and support our in vivo findings that PDBu results in nocodazole-sensitive MT advance.


To directly address the mechanism of the PKC effects de- scribed above, we assessed microtubule dynamics before and after treatment with PDBu using FSM.

This relatively new microtubule marking technique (Waterman-Storer et al., 1998; Waterman-Storer and Salmon, 1998) permits rapid assessment of the critical dynamic parameters of MT behavior, including assembly, disassembly, and transloca- tion (sliding) rates as well as MT lifetimes in each state.


Fig. 7 shows DIC-MT overlays illustrating the distribution of MTs before (A) and after (B) PDBu exposure with re- spect to growth-cone structure.

Fig. 7 C is another growth cone in PDBu illustrating extended undbundled MTs typi- cally observed after PDBu treatment.

Note the spatial overlap between MTs and actin cables that extend into filopodia (Fig. 7 C, arrowheads), as observed in fixed cells (compare Fig. 4, C and D).


Representative MT behavior under control conditions is illustrated in the time-lapse im- age montages shown in Fig. 7, D and E. MTs underwent stochastic bursts of growth and shortening (green arrow- heads indicate the penultimate plus-end speckle) superim- posed on relatively short MT translocations in both direc- tions, as indicated by speckles maintained within the body of MTs over time (red arrowheads).

Under control condi- tions, microtubule growth, shrinkage, and sliding activity occurred within the transition zone with only occasional MT excursions into the P-domain.


In contrast, after PDBu exposure, MTs often extended deep into the P-domain and occasionally reached the leading edge of the growth cone.

This extension resulted from an increase in MT growth lifetimes as shown in the MT growth lifetime histo- grams in Fig. 7, H and I, under control conditions and after PDBu treatment.

Note the presence of MT growth life- times in excess of 80 s in PDBu (Fig 7 I) and the nearly twofold increase in mean MT growth lifetime (Fig. 8 A).

An example of a prolonged MT growth lifetime in PDBu is shown in Fig. 7 F.


The increase in growth lifetimes in PDBu was accompanied by a 1.7-fold increase in the MT rescue frequency and an approximately twofold decrease in catastrophe frequency (Table I).

Rates of MT growth and shortening increased slightly after PDBu treatment (Table I), but these changes were not statistically signifi- cant.

Anterograde and retrograde translocation rates re- mained unchanged (Table I).


Interestingly, after PDBu treatment, MTs penetrating the P-domain sometimes underwent prolonged periods of retrograde translocation, apparently in conjunction with retrograde F-actin flow.

An example of this phenomenon is illustrated in Fig. 7 G, where a MT continuously translo- cates in the retrograde direction (red marks) while still growing at a rate that matched or exceeded the rate of ret- rograde transport.

This resulted in the distal tip of the MT maintaining its position near the leading edge despite the opposing retrograde F-actin flow.

To analyze the contribu- tion of MT translocation in the observed effects, the per- centage of time MTs spent moving in the anterograde or retrograde direction or in a nonmoving state was assessed under control conditions and after PDBu treatment.

We found MTs spent significantly more time undergoing ret- rograde movement after PDBu treatment and a propor- tional decrease in the amount of time MTs were not mov- ing (Fig. 8 B).

It should be emphasized that net MT extension occurred despite the increase in retrograde MT


The effects of PDBu on MTs appear to be specifically due to PKC-regulated events since multiple activators such as PDBu, TPA, or OAG had similar MT assembly-pro- moting effects that could be completely blocked by spe- cific PKC inhibitors and not observed with the inactive PDBu analogue, 4-␣-phorbol.

Although phorbol esters are known to cause activation of proteins other than PKC, such as chimaerin, Munc 13-1, Unc13, or Ras-GRP (Ron and Kazanietz, 1999), none of these proteins are kinases and therefore their activity should not be sensitive to ATP site-active PKC inhibitors such as Bis 1 used in this study.


In contrast to activation, inhibition of PKC with Bis or re- lated compounds was surprisingly without observable ef- fects.

This could indicate that a minimal level of basal PKC activity is required for the maintenance of GC structure under the conditions employed here.

This finding appar- ently contradicts the "growth-cone collapse" due to PKC inhibition after introduction of protein kinase C pseu- dosubstrate peptides reported earlier (Theodore et al., 1995).

Indeed, we observed effects similar to "growth- cone collapse" when we tested inhibitors such as chel- erythrine or calphostin C that interact with regions of PKC other than the C3 (ATP binding) domain (our unpub- lished observations).

Caution should be exercised, how- ever, in interpreting effects of these agents on growth cone structure, given that chelerythrine is reported to have di- rect effects on MT polymerization, and calphostin C has unpredictable phototoxic effects due to light-stimulated oxidative damage to PKC (Gopalakrishna et al., 1992; Wolff and Knipling, 1993).

It has also been suggested that the regulatory domain of PKC, especially the pseudosub- strate, the C1 domain, and part of the V3 region, may be necessary and sufficient for sustaining neurite outgrowth (Zeidman et al., 1999).

These observations are consistent with the aforementioned disruption of growth-cone struc- ture after introduction of excessive pseudosubstrate pep- tide into growth cones (Theodore et al., 1995).

The differ- ence in the effects of ATP- and pseudosubstrate-based inhibitors may lie in the fact that addition of pseudosub- strate may increase availability of the regulatory domain for interactions while inhibiting the ATP transfer function of the kinase, whereas ATP-based inhibitors will only in- hibit ATP transfer without affecting availability of the reg- ulatory domain.


It should be noted that our culture condi- tions (i.e., serum-free defined medium and poly-L-lysine substrate) minimize cross-talk between cell adhesion mol- ecule and growth factor signaling pathways, which could have a significant effect upon the ultimate response of the neurons to PKC activation.

These factors should be kept in mind when comparing the responses reported here to those observed in more complex systems.


Previous studies on the effects of nocodazole in cells have demonstrated that concentrations in the 4-400-nM range inhibit MT dynamics without resulting in significant loss of MT polymer mass (Rochlin et al., 1996; Jordan and Wil- son, 1998b; Jordan and Wilson, 1999).

In the current study, similar treatments with extremely low doses of nocodazole and other inhibitors that interfere with MT polymerization potently inhibited PDBu-stimulated MT extension (Fig. 5), indicating that MT assembly is necessary for the effects reported here.

Furthermore, our biochemical experiments showed an increase in MT polymer mass after PDBu treat- ment, and this MT polymer was also sensitive to depoly- merization by low doses of nocodazole (Fig. 6).

In support of the current findings in neurons, PDBu has also been re- ported to increase MT polymerization in macrophages (Robinson and Vandre, 1995).


To directly address the role of MT assembly, we mea- sured MT dynamics using the FSM MT marking tech- nique.

This is a powerful new technique pioneered by Waterman-Storer and Salmon (1998) for investigating cy- toskeletal protein dynamics in living cells, which enables independent assessment of the contribution of polymer as- 1042 sembly dynamics and polymer translocation events.


FSM analysis revealed that MT polymerization is indeed af- fected by PDBu treatment; specifically, the duration of typical MT assembly events were increased approximately twofold (Fig. 7, H and I).

This increase in MT growth life- times was accompanied by a 1.7-fold decrease in catastro- phe and approximately twofold increase in rescue fre- quencies (Table I).

It should be noted that control rescue frequencies may be underestimated due to the difficulty in detecting rescue events occurring in relatively short MTs near the C-T-domain interface, where MT density is high (see Tanaka and Kirschner, 1991).


To investigate this is- sue, a subpopulation of long MTs with ends already in the P-domain under control conditions were analyzed (Table I).

In this population, the catastrophe frequency still de- ceased 1.7-fold in PDBu relative to controls; however, the rescue frequencies increased only -3.1فfold.

This smaller PDBu effect on peripheral (i.e., long) versus total MTs might result from inefficient detection of rescue events when assessed in the total MT population; however, we cannot rule out differences in MT behavior in the transi- tion zone versus P-domain.

These fundamental domain- specific issues are currently under investigation.


Finally, actual rates of MT growth and shortening were not af- fected by PDBu (Table I), making changes in tubulin dimer concentration an unlikely mechanism for the ob- served MT advance.


Changes in rates of MT translocation are clearly not in- volved since retrograde and anterograde sliding rates were unaffected (Table I).

In fact, the proportion of time MTs spent undergoing translocation in the retrograde direction was actually increased in PDBu (36% vs. 49% for control vs. PDBu, respectively) despite net MT advance.

How can this paradox be resolved?


Retrograde F-actin flow appears to act as a barrier to MT advance (Forscher and Smith, 1988), and retrograde translocation of MTs in peripheral F-actin domains has been described in nonneuronal cells (Waterman-Storer and Salmon, 1997).


The current study supports these findings and suggests that when MTs extend into the P-domain, they do so predominantly by exhibiting prolonged bursts of assembly that exceed the rate of F-actin flow (e.g., Fig. 7 F).

After extension, a MT can maintain its position in the P-domain by assembling at a rate that matches retrograde flow (e.g., Fig. 7 G); however, if MT assembly stops or slows below the rate of retrograde flow, the MT will be translocated rearward out of the P-domain.


After PDBu treatment, the increased length of MTs within the P-domain promotes chances for MT-actin filament in- teractions, and this in turn may result in the increase in ret- rograde translocation events observed (Fig. 8 B).

This scenario is consistent with the effects observed after stabi- lizing MTs with taxol; specifically, MTs were cleared from both the peripheral domain and transition zone, presum- ably via interactions with retrograde flow (Fig. 5 H).


This explanation suggests a role for the actomyosin-based pro- cess (Lin et al., 1996) of retrograde F-actin flow in clearing MTs from the P-domain; however, it does not rule out par- ticipation of other molecular motors in the variety of MT translocation events observed (a detailed analysis of MT behavior in this system will be published separately).


Whether PDBu-stimulated MT advance results from di- rect effects on the MTs themselves, indirectly from alter- ation of F-actin structure, or from changes in MT-F-actin interactions remains to be determined.

PDBu treatment does in fact affect F-actin structure; for example, in the in- hibition of actin-based ruffling seen in Fig. 2 B. Several lines of evidence, however, suggest that the structure of the P-domain cytomatrix remains largely intact after PDBu treatment.

First, the large (100-150-nm diameter) organelles typical of the C-domain do not significantly ad- vance into the P-domain in PDBu.

This is in contrast to treatment with cytochalasin, which disrupts peripheral F-actin and results in organelle advance into the P-domain (Forscher and Smith, 1988).

Second, previous studies sug- gest that the P-domain pore size or gel exclusion limit is 70-100 nM (Popov and Poo, 1992), which is considerably larger than the -52فnm diameter of a single MT, indicat- ing that individual MTs would not be excluded from the P-domain simply on the basis of cross-sectional area alone.

In agreement with this, we found that 2,000,000 kD FITC- dextran (-06فnm stokes radius) gained diffusional access into the P-domain and, furthermore, the distribution of this probe did not appear to change with PDBu treatment (our unpublished observations).

Taken together, these ob- servations suggest that organelles are simply sterically ex- cluded from the peripheral domain by an F-actin-based barrier and the mechanism for MT exclusion from the P-domain is more complex.


What potential effector proteins might be involved?

Re- cent evidence suggests the four parameters of MT dynam- ics (growth, shortening, catastrophe frequency, and rescue frequency) can be altered independently of one another in vivo (Desai and Mitchison, 1997; Andersen, 2000), so the situation is potentially complex.

With that said, the current data does point to a mechanism involving modulation of the frequency of MT catastrophe and/or rescue events by PKC.


Potential candidates are proteins that regulate MT catastrophe frequency such as Op18/stathmin (Belmont and Mitchison, 1996; Di Paolo et al., 1997), kinesin family members KIN 1 (Desai et al., 1999) and XKCM1 (Wal- czak et al., 1996; Tournebize et al., 2000), or XMAP310, a MT rescue-promoting factor (Andersen and Karsenti, 1997).


On the other hand, phosphorylation of MAPs by PKC is well known to promote their dissociation from MTs, MT unbundling, and decreased MT stability (Mori et al., 1991; Gordon-Weeks, 1993; Goold et al., 1999), all of which are consistent with the results presented here.

These lines of inquiry deserve further attention.


Previous analysis of PKC's regulation of neurite out- growth have focused primarily on changes in F-actin struc- ture and actin polymerization dynamics.

Our findings sug- gest an additional mechanism for regulating the overall rate of axon growth through modulation of MT dynamics.

PKC activation results in a net increase in MT polymeriza- tion via a pronounced increase in MT growth lifetimes, thus promoting MT extension into the P-domain.

MT in- vasion of the P-domain could contribute to increased rates of neurite outgrowth we and many others have observed with chronic PKC activation (Hsu et al., 1989; Hundle et al., 1995; Fagerstrom et al., 1996).

Interestingly, recent evi- dence suggests that dynamic MTs are necessary for deliv- ery and incorporation of new membranes into the distal 1043 axon (Zakharenko and Popov, 1998).

Thus, PKC activa- tion, by promoting MT growth, could also facilitate tar- geted delivery of membrane components.


This work was supported by a National Institutes of Health (NIH) grant RO1-NS28695 to P. Forscher and a Postdoctoral NIH National Research Service Award (1F32NS11122) to A.W. Schaefer.


Interactions between microtubules (MTs) and filamentous actin (f-actin) are involved in directed cell locomotion, but are poorly understood.

To test the hypothesis that MTs and f-actin associate with one another and affect each other’s organization and dynamics, we performed time-lapse dual-wavelength spinning-disk confocal fluorescent speckle microscopy (FSM) of MTs and f-actin in migrating newt lung epithelial cells.

F-actin exhibited four zones of dynamic behavior: rapid retrograde flow in the lamellipodium, slow retrograde flow in the lamellum, anterograde flow in the cell body, and no movement in the convergence zone between the lamellum and cell body.

Speckle analysis showed that MTs moved at the same trajectory and velocity as f-actin in the cell body and lamellum, but not in the lamellipodium or convergence zone.

MTs grew along f-actin bundles, and quiescent MT ends moved in association with f-actin bundles.

These results show that the movement and organization of f-actin has a profound effect on the dynamic organization of MTs in migrating cells, and suggest that MTs and f-actin bind to one another in vivo.


The directed movement of cells is thought to result from complex and dynamic interactions between the microtubule (MT) and filamentous actin (f-actin) cytoskeletal systems [1].

Migrating cells have a polarized morphology, with a ruffling lamellipodium at the leading edge facing the direction of migration, followed by a flat lamellum, a tapering cell body, and a trailing tail.

This polarity results from highly polarized organization and assembly/disassembly dynamics of f-actin.

The lamellipodium contains a dense meshwork of actin filaments whose barbed ends continuously grow near the leading edge.

F-actin in both the lamellipodium and lamellum undergoes retrograde movement towards the cell center, which may mediate cellular traction [2][3][4].


In the cell body and tail, f-actin at the ventral cell surface forms bundles that may be contractile and mediate retraction of the cell rear [5].

MTs, like f-actin, exhibit polarized organization and dynamics in migrating cells [1].

MT plus ends grow out from the cell center primarily towards the leading edge where they undergo dynamic instability, i.e., stochastic switching between growth and shortening.

There is evidence that MT movements may mimic those of f-actin, undergoing retrograde flow in the lamellum and forward motion in the cell body and tail [6][7][8].


How MTs and actin interact to produce directed cell motility is unclear.

MTs may provide spatial cues to localize f-actin–based protrusion and contraction [1].

One way this could be achieved is by physical interaction between the two filament systems.

In this study, we tested the hypothesis that MTs and f-actin interact with one another in living, migrating cells to affect each other’s dynamic organization by using time-lapse dual-wavelength spinning-disk confocal fluorescent speckle microscopy (FSM) [9][10] to near simultaneously visualize f-actin and MT dynamic behaviors in migrating newt lung epithelial cells.

This analysis reveals for the first time that MTs exhibit interactions with f-actin bundles and meshworks that guide the movement and organization of MTs during cell motility.


Results and discussion


F-actin exhibits four distinct zones of dynamic behavior


We concentrated our analysis of migrating newt lung epithelial cells on the cytoskeleton at the ventral cell surface because the f-actin in this region likely mediates the traction forces of motility.

To support this notion, we generated deconvolved three-dimensional reconstructions of fixed cells labeled with fluorescent phalloidin.

In X–Z views, f-actin in the lamellipodium and distal lamella fills an area the same thickness or thinner than our confocal optical section thickness of 530 nm.

In the proximal lamella and cell body, f-actin is concentrated solely in cortical regions of similar thickness, with little detectable actin in the central cell body.

This indicates that our confocal images contain the full population of ventral f-actin, and that in the cell center there is likely little interaction between dorsal and ventral f-actin.


For confocal FSM imaging, we injected cells with 0.5 mg/ml of X-rhodamine actin.

Random incorporation of a few labeled and many endogenous unlabeled monomers during filament assembly gives f-actin structures a fluorescent speckled appearance in diffraction-limited images [9][11].

The speckles act as fiduciary marks on the filaments; their movement reports polymer movement, whereas their appearance/disappearance report polymer assembly/disassembly.


To relate speckle dynamics to the f-actin structures seen in phalloidin-stained cells, we collected confocal FSM images at 10-s intervals followed by perfusion of fixative and staining with Alexa-488 phalloidin.

This showed that areas with somewhat even distributions of fluorescent speckles in FSM images corresponded to f-actin meshworks or fine f-actin bundles.

Linear arrays of f-actin speckles that moved together coherently in time-lapse FSM corresponded to bundles of f-actin.

There was a minor subset of f-actin bundles in the phalloidin image that had no correspondence in the FSM image, indicating their lack of incorporation of labeled actin and thus high stability.


Analysis of time-lapse confocal actin FSM image series in 39 cells revealed a general pattern of four distinct zones of f-actin movements.

At the leading edge and throughout the lamellipodium, f-actin speckles continuously appeared and moved towards the cell center at 1.62 μm/min, as determined from kymograph analysis along the axis of motion [10].

As speckles approached the junction between the lamellipodium and lamellum they usually disappeared, suggesting a zone of f-actin disassembly [11].

To confirm this apparent gradient in actin density across the lamellipodium, cells were coinjected with X-rhodamine actin and FITC dextran (6 kD) as a volume marker.

Ratio imaging indicated a steep gradient in actin density from the front to the rear of the lamellipodium.


F-actin speckles underwent retrograde flow more slowly in the lamellum at 0.34 μm/min.

Speckles also appeared and disappeared throughout the lamellum, suggesting f-actin assembly/disassembly throughout this region.


F-actin in the cell body generally moved towards the leading edge at a rate of 0.44 μm/min.

Linear arrays of f-actin speckles in filament bundles moved coherently together generally towards the leading edge, though cell body bundles often approached the cell front at oblique angles.


Between the cell body, where the f-actin moved anterograde, and the lamellum, where f-actin moved retrograde, kymograph analysis along either the axis of migration or parallel to the leading edge failed to detect directed movement of f-actin speckles, but local movements and speckle disappearance was noted.

Although one might expect a buildup of filaments in this novel convergence zone where f-actin movements from the lamellum and cell body meet, ratio imaging with a volume marker revealed no increase in actin density.

Thus, like the base of the lamellipodium, the convergence zone must be a region of massive f-actin disassembly.

Interestingly, the direction of movement of f-actin on the ventral surface of newt lung cells correlates well with the direction of traction forces that other migrating cell types generate on the substrate [12][13].

This novel convergence zone is located where forward and rearward traction forces are likely to meet.

This strongly implicates local ventral f-actin movement in generation of traction force, and suggests that actin depolymerization may be a major regulatory step in cell body traction, as has been shown for lamellipodial protrusion [14].


MTs are coupled to f-actin movements


To test the hypothesis that the movements of f-actin and MTs are directly correlated during cell migration, we monitored the dynamics of f-actin and MTs in 39 cells using dual-wavelength confocal FSM to capture images of X-rhodamine f-actin and Cy-2 MTs in rapid succession every 10 s. In single confocal sections, we could easily differentiate between an MT end, whose fluorescence intensity terminated abruptly, and an MT extending out of the plane of focus, whose fluorescence gradually decreased towards a terminus.


We first analyzed in detail the behavior of individual MTs that were oriented primarily parallel to the leading edge.

Using dual-wavelength kymographs, we determined the percentage of total MT movement rates that matched within 2.5% the movement rates of the immediately adjacent f-actin speckles.

The precise coupling of f-actin and parallel MT movements occurred in all four zones of f-actin dynamic behavior: the lamellipodium, lamellum, convergence zone, and cell body.


We also analyzed individual MTs that were oriented perpendicular to the leading edge.

Kymographs showed that speckle marks on perpendicular MTs moved at the same velocity as the immediately adjacent f-actin in both the lamellum and in the cell body.

In contrast, in the lamellipodium and convergence zone, perpendicular MT movements were often uncoupled from actin movements.

In the lamellipodium, f-actin speckles moved rapidly past MT speckles, and the rearward velocity of the portion of the MT in the lamellipodium matched the slower rate of f-actin rearward flow from the leading edge in the lamellum.

MTs that were perpendicular to the leading edge and extended from the cell body across the convergence zone and into the lamellum were often uncoupled from the stationary actin in the convergence zone.

Sections of MT spanning this region buckled and bent extensively and moved at odd angles relative to the stationary f-actin speckles as portions of MT length moved into the convergence zone from adjacent cellular regions.


These results directly show that the acto-myosin–dependent movements of MTs reported previously [6][7][8] occur at the exact same rate as the f-actin in the immediate vicinity of the moving MT.

We suggest that the coordinated movement of f-actin and MTs is mediated by a specific crosslinking interaction between f-actin and MTs, as opposed to nonspecific trapping of MTs in the moving f-actin meshwork.

First, the coupling of MT and f-actin movements is regionally regulated, being least robust in the lamellipodium, where the f-actin density is the highest.

This strongly argues against the notion of nonspecific trapping of MTs by a dense f-actin meshwork.

Second, both MTs oriented parallel to the leading edge, which have a large cross-sectional area exposed to the force of f-actin flow, and MTs that are oriented perpendicular to the leading edge and which have a very small cross-sectional area exposed to the force of f-actin flow, move at the exact same rate as the immediately adjacent f-actin in the lamella and cell body.

However, our analysis suggests that nonspecific trapping could occur for parallel MTs, which continue to move at f-actin flow rates in areas of the cell where perpendicular MTs are uncoupled from flow.

Alternatively, MTs and actin could both be riding on the same as yet unidentified conveyor belt, although we consider this unlikely, as we have documented MT/f-actin crosslinking interactions in Xenopus egg extracts [15].


MTs interact with f-actin bundles


In the cell body and convergence zone, dual-wavelength movies revealed that dynamic MTs often aligned along f-actin bundles and moved with them along their anterograde/oblique paths.

In addition, dynamically unstable MTs associated with f-actin bundles that terminated in dense f-actin plaques.

Analysis of speckle fiduciary marks indicated that the f-actin bundle and associated MT were stationary with respect to one another, demonstrating that MTs grew and shortened, as opposed to translocated, along f-actin bundles towards the plaques.


We also observed a second type of interaction between MTs and f-actin bundles in the cell body.

Individual MT ends terminated on linear arrays of f-actin speckles, often joining the f-actin bundle at oblique angles.

Speckle tracking analysis showed that the MT end and speckles in the f-actin bundle moved in tandem, whereas the MT end moved past adjacent, nonbundle-associated f-actin speckles.

Thus, the MT end and the f-actin bundle were cotranslocating, as opposed to the MT moving along the f-actin bundle.

In addition, the distance between the MT end and a speckle along the MT shaft stayed constant over time, indicating that the MT end was neither growing nor shortening, but was capped.

However, we have no indication of whether these were MT plus or minus ends.


We suggest that the guidance of MTs along actin bundles and the cotransport of MTs and f-actin in the lamellipodium and cell body may be mediated by the same putative MTs/f-actin crosslinking factor.

This factor could be distributed along the MT or actin filament lattices and subject to regional regulation to allow local uncoupling of MTs from f-actin, i.e., in the lamellipodium or convergence zone.

Further, such a crosslinker may be fundamental to cell motility.

For example, MT crosslinking to focal adhesion-associated f-actin bundles is likely the mechanism of MT targeting to focal adhesions, which spatially regulates focal adhesion turnover [16].

Similar MT/f-actin crosslinking may also mediate guidance of MTs by f-actin bundles in neurons to determine MT distribution in growth cones that is critical to axonal guidance and branching [17][18][19][20].


In contrast, the interactions of capped MT ends with f-actin bundles likely is mediated by a separate molecular mechanism, in which a MT end–binding protein links to f-actin.

We suggest that MT end/f-actin interactions may be critical to functions that require establishment of cellular asymmetries.

For example, linking of MT ends to the f-actin–rich cortex is important for orienting mitotic spindles and the placement of the cytokinetic furrow during cell division [21][22][23].

Similarly, MT end/f-actin interactions could orient the centrosome forward of the nucleus and thus establish the polarity of migrating cells.

Indeed, recent evidence has shown that centrosome reorientation in migrating cells is dependent on the MT end–associated protein complex, cytoplasmic dynein [24][25].

There are several interesting candidates for linking MT to f-actin [26], and it will be interesting to test their involvement in MT-actin coupling with our dual-wavelength FSM assay.


We have used multimode fluorescent speckle microscopy (FSM) and correlative differential interference contrast imaging to investigate the actin–microtubule (MT) interactions and polymer dynamics known to play a fundamental role in growth cone guidance.

We report that MTs explore the peripheral domain (P-domain), exhibiting classical properties of dynamic instability.

MT extension occurs preferentially along filopodia, which function as MT polymerization guides.

Filopodial bundles undergo retrograde flow and also transport MTs.

Thus, distal MT position is determined by the rate of plus-end MT assembly minus the rate of retrograde F-actin flow.

Short MT displacements independent of flow are sometimes observed.

MTs loop, buckle, and break as they are transported into the T-zone by retrograde flow.

MT breakage results in exposure of new plus ends which can regrow, and minus ends which rapidly undergo catastrophes, resulting in efficient MT turnover.

We also report a previously undetected presence of F-actin arc structures, which exhibit persistent retrograde movement across the T-zone into the central domain (C-domain) at 1/4 the rate of P-domain flow.

Actin arcs interact with MTs and transport them into the C-domain.

Interestingly, although the MTs associated with arcs are less dynamic than P-domain MTs, they elongate efficiently as a result of markedly lower catastrophe frequencies.


In the neuronal growth cone, a sharp, yet highly dynamic interface exists between growing microtubules (MTs) in the axon shaft, and peripheral actin networks.

Mounting evidence suggests that directed axon guidance depends on coordinated interactions between MTs and actin filaments in growth cones [1].

During axon guidance, actin based motility is harnessed to promote MT growth and steering.

However, the fundamental details of how F-actin networks influence MT behavior, and vice versa, are not well understood.


MT behavior in growth cones was initially characterized by Tanaka and Kirschner [2] (also Sabry et al., 1991).

They found that individual unbundled MTs invaded the actin-rich peripheral domain (P-domain) and appeared to display properties of dynamic instability; however, because it was not possible to make fiducial marks on MTs, the respective contributions of polymerization and translocation to MT advance could not be assessed.

Damping MT dynamics with vinblastine (without net depolymerization) disrupted the normal cycle of MT bundling and splaying, but actin-based motility was essentially unimpaired.

Interestingly, vinblastine-treated growth cones tended to wander, suggesting that MT dynamics are necessary for converting actin-based motility into directed, persistent growth [3].

Subsequent reports confirmed that dampening MT dynamics also inhibited growth cone turning in response to guidance cues [2, 4, 5].


Hints that actin motility is an early step in axon guidance responses emerged from studies where F-actin accumulated in growth cone filopodia before turning [6].

In particular, there has been much speculation about the function of filopodia.

Evidence suggests that filopodia can play a structural role, exert mechanical tension, selectively adhere to target substrates, and are involved in signal transduction [7, 8].

EM and immunofluorescence studies have also noted striking coalignment of filopodial F-actin bundles with MTs in growth cones [9, 10, 11].

These observations led to the notion that capture or stabilization of dynamic MT ends via interactions with filopodial actin bundles may be an early step in growth cone turning [10, 11, 12, 13, 14].

It is also well known that growth cones use actomyosin-based motility to exert steering forces on substrates [15, 16].

Not surprisingly, cytochalasin treatments resulted in loss of axon and MT guidance capabilities [17], although axonal MTs can still extend randomly in the absence of actin assembly [18].

MTs were also observed to rapidly extend to the leading edge of growth cones treated with cytochalasin after clearance of P-domain F-actin [19], again suggesting intimate MT–actin interactions.


In complimentary experiments, damping MT dynamics (with taxol or low doses of MT assembly inhibitors) did not markedly affect retrograde F-actin flow; however, MTs were cleared from the P-domain [20, 21, 22, 23], suggesting retrograde actin flow may regulate MT positioning.

Indeed, recent studies in motile cells have demonstrated that retrograde F-actin flow affects MT translocation, assembly, and catastrophe rates [24].

All of these observations point to the importance of MT–actin filament interactions; however, a clear description of how these two cytoskeletal polymers influence each other’s behavior in growth cones has not emerged.


Recent advances in cooled CCD-based imaging techniques, including multimode fluorescent speckle microscopy (FSM), make it possible to directly measure actin and tubulin polymer dynamics in living cells, and correlate them with cell motility [25, 26].

In the current study we have used FSM to determine the relative contribution of MT assembly dynamics versus MT translocation in establishing the steady-state MT distribution in growth cones, and to address how F-actin dynamics influence MT behavior.

This data provides a quantitative framework for interpreting the complex effects of signaling pathways on the cytoskeletal motility machinery during axon growth and guidance [27].

We focus on three findings: (1) filopodia are assembly guides for a highly dynamic population of MTs that efficiently explore the P-domain; (2) actin filament arc structures in the T-zone are associated with a population of MTs with distinctly different kinetic parameters than those in the P-domain; and (3) filopodia and arcs both transport MTs.


Although elephants (Loxodonta africana Blumenbach, 1797) have less stringent habitat requirements than many other smaller mammals (Laws, 1970), they do not use habitats randomly (e.g. Leuthold, 1977; Western & Lindsay, 1984; Viljoen, 1989; Verlinden & Gavor, 1998).

This is especially true in the dry season when resources are less abundant and occur in hot spots (Ntumi et al., 2005).

Stokke & Du Toit (2000) argue that investi- gations into sex- and age-related differences in elephant feeding patterns and habitat use, coupled with surveys of elephant population structure, would be logical precursors to meaningful quantifications of the impacts of elephant populations on savanna vegetation.

In this paper, we investigate sexual segregation in space and resource use between mixed herds and bull groups in Kruger National Park (KNP), South Africa.


Various studies have shown that larger herbivores can tolerate a wider range of forage quality than smaller herbivores can (e.g. Bell, 1971; Geist, 1974; Jarman, 1974; Du Toit & Owen-Smith, 1989; Illius & Gordon, 1992; Wilmshurst et al., 2000).

This phenomena is mostly ascribed to the absolute metabolic needs and retention time increasing with body size, and mass-specific metabolic rates decreasing, with gut capacity as fraction of body mass remaining almost constant.

This means that larger herbivores can satisfy their nutritional requirements even when ingesting forage of lower quality, because the cell walls are better digested as a result of increased ingesta retention time (Demment & van der Soest, 1985).

Therefore, critical forage quality thresholds are higher for small Diversity and Distributions, 13, 225-236, Journal compilation © 2007 Blackwell Publishing Ltd than large animals and critical forage quantity thresholds are higher for large animals than small animals.


In the context of the present study, the theory of allometric scaling of dietary tolerance therefore implies that female and juvenile elephants will have higher nutritional requirements per unit body size than male elephants because of their smaller body size (Du Toit & Owen-Smith, 1989; Du Toit & Cumming, 1999).

Considering this, together with the increased reproductive demands on cows (pregnancy and lacta- tion), we can expect bulls to be less selective and more tolerant of lower-quality food than cows and juveniles (Stokke, 1999; Stokke & Du Toit, 2000).

This would result in a wider use of habitats and thus a wider spatial distribution of bull groups compared to mixed herds.

This forms the first hypothesis we addressed in this paper.


Although bulls have greater total water requirements (Young, 1970), cows and juveniles have higher relative rates of water turn- over because of their higher rates of evaporative and respiratory water loss (Gordon, 1977; Beuchat, 1990).

Furthermore, mixed herds with juveniles and neonates are less mobile than bull groups.

As a consequence, mixed herds will have to drink more often and minimize their distance to the closest water source.

The second hypothesis we tested is that mixed herds occur closer to surface water sources than bull groups.

This hypothesis has also been proposed by Stokke & Du Toit (2002).


In this paper, we examined dry season sexual segregation in the KNP elephant population at the landscape scale.

In particular, we considered differences between mixed herds and bull groups with regard to (1) spatial distribution, (2) forage and habitat selection (tree cover and herbaceous biomass), and (3) ranging distance from rivers and artificial waterholes.

We expect bull groups to (1) have a wider spatial distribution, (2) be less specific in their forage and habitat requirements, and (3) occur farther from surface water than mixed herds.


This study was conducted on a landscape scale and included the whole of KNP.

The park covers a total area of nearly 20,000 km 2 in the eastern Lowveld region of South Africa, adjoining the Mozambique border in the east and Zimbabwe in the north.

Elevations range from 260 to 839 m a.s.l. and mean annual rainfall varies from around 750 mm in the south to around 440 mm in the north, but with large variations between years (Gertenbach, 1980; Venter et al., 2003).

The west of the park is dominated by granites and their erosion products, whereas the east is domi- nated by basalts.

The Lebombo Mountains, primarily rhyolite, run from north to south on the eastern boundary.


Four major vegetation types dominate the KNP landscape (Eckhardt et al., 2000).

The south-west are well-wooded, with accumulation of low-quality grazing because of the nutrient- poor granitic soils underlying this area.

Important trees include the red bushwillow (Combretum apiculatum Sond.), knobthorn (Acacia nigrescens Oliv.), tamboti (Spirostachys africana Sonder) and marula (Sclerocarya birrea [A. Rich.] Hochst.).


In the south-east, on the basalts, the grasses are more palatable and tend to be more heavily grazed.

Important trees include knobthorn, leadwood (Combretum imberbe Wawra) and marula.


The north-west granites are dominated by mopane (Colophospermum mopane [Kirk ex benth.] Kirk ex J. Leonard) and red bushwillow and are poorly grassed.


The north-east basalts are dominated by homogeneous 1-2 m high, multi-stemmed mopane shrubs, with more grass cover than the north-west granites.


Six perennial rivers cross the park from west to east.

Further- more, more than 300 boreholes were drilled between the 1930s and the 1980s as part of the water provision programme to ensure a reliable year-round network of surface water throughout the park (Gaylard et al., 2003).


In more recent years, the desirability of such a high density of surface water, minimizing the influence of temporal variability in rainfall, has been questioned (e.g. Walker et al., 1987; Owen-Smith, 1996; Harrington et al., 1999; Owen-Smith & Mills, 2006).


Consequently, the water provision policy was revised, resulting in the closure of more than half the artificial waterholes (Pienaar et al., 1997).

The history of the water provision programme and the revision thereof is described in detail, respectively, by Pienaar (1985) and Pienaar et al. ( 1997).


A common spatial framework to which all the Geographical Information System (GIS) and satellite data layers could be summarized had to be enforced.

This is a common approach in ecological studies faced with data from different sources and with different underlying spatial resolutions (e.g. Tognelli & Kelt, 2004).

Considering the spatial resolution of the different data sets, it was decided to summarize all variables to a common 1-km grid.

This resulted in 19,269 grid cells covering the whole of the park.

As could be expected, some cells on the boundaries were smaller than 1 km 2 , and as a result all the different data layers were summarized to the reference grid by averaging within the grid, rather than by adding within the grid (i.e. standardizing by area).


Two KNP elephant distribution data sets were used.

Data from the annual mega-herbivore census (a helicopter count of ele- phants, buffaloes and rhinos) were used for testing whether the elephant sexes exhibit spatial and resource segregation.

These data were also used for calibrating the multivariate autologistic regression models that identify significant predictors of elephant distribution.

The second data set came from the annual ecologi- cal aerial survey (EAS), which used a fixed-wing aeroplane to count all the large herbivores in the park.

The EAS data set was used only for verifying the predictions of the autologistic models.


A helicopter was flown at an average height of 150 m and at a speed of 100 knots, with four observers on board, counting and noting all elephants, buffaloes and rhinos.

These annual censuses were conducted over the whole park in the late dry season (August), using a total count on a pattern that follows all of the Sexual segregation of elephants © 2007 The Authors Diversity and Distributions, 13, 225-236, Journal compilation © 2007 Blackwell Publishing Ltd 227 drainage lines (Whyte, 2001a).

When a big elephant herd was sighted, the helicopter would circle lower until the observers reached consensus on the herd size.

The number and location was plotted on a 1 : 100,000 map for later digitization.

For each sighting, it was noted whether it was a mixed herd or a bull group.

Mixed herds were defined to include breeding herds with a matriarch and other adult females with their offspring, as well as family units attended by adult males.

Bull groups comprised of adult males only, occurring independently from family units.

Individual elephant bulls were included in the bull group category.


We used data from 1985 to 1996 in this study, with census totals ranging from 6887 to 8371 individuals over this period.

No accurate locations were recorded for the sightings prior to 1985.

In 1997, the water provision policy in the park was revised and many artificial waterholes were closed (Pienaar et al., 1997).

This caused a change in the resource distribution and hence data from post 1996 were excluded from the present analysis.


In order to get a better idea of elephant distribution, all sight- ings over the 12-year period were combined into a single GIS data layer.

This approach of combining snap-shot data from various periods is common in ecological studies (e.g. Osborne et al., 2001; Lichstein et al., 2002; Silva et al., 2002; Tognelli & Kelt, 2004; Olivera-Gomez & Mellink, 2005).

The data were then transformed into absence/presence data for each 1-km grid cell.


The fixed-wing EAS were used as an independent data set for validating the model predications.

The EAS was conducted annually over most of the park in the dry season (May-August), using a total area count on 800-m wide strip transects (Viljoen, 1996).

A fixed-wing aircraft was flown at a height of 65-70 m at a speed of 95-100 knots, with four observers on board.

The location and herd size of the key herbivore species were recorded.

Most of the park was covered from 1981 to 1993, after which the methodology was changed and only sections or specific transects in the park were flown.

We used data from 1985 to 1996, covering the same period as the mega-herbivore census data used in this study.

Again, all the sightings were combined into a single GIS layer and transformed into absence/presence data for each 1-km grid cell.


The annual counting of elephants in both the mega-herbivore census and EAS may appear like duplication in effort.

It is known that the EAS data contain an under-count bias (Redfern et al., 2002) and because mega-herbivores (elephant, buffalo and rhino) are of particular concern for managers of confined conservation areas, like the KNP, the helicopter census was designed to provide better estimates and distributions of these heavy, bulk feeders (Joubert, 1983).

The greater manoeuvrability of the helicopter compared to the fixed-wing aeroplane improves data collection, resulting in better-quality data.

However, even though the EAS data represent an under-count of the elephant population, it still provides independent and spatially accurate distribution data suitable for validating the regression models.


Table 1 lists the resource variables included in the study.


There is a trend of decreasing annual rainfall from south to north, except in the extreme north-west and south-east, where topography influences rainfall (Venter et al., 2003; Redfern et al., 2005).

The northing Universal Transverse Mercator (UTM) coordinate will therefore give a crude estimate of the rainfall gradient.

The rainfall gradient is related to forage quantity, with more vegetative biomass in the south.


Every May since 1989, herbaceous biomass has been estimated at more than 500 field sites scattered throughout the park.

These sites were selected to be proportionally representative of the different landscapes in the park (Trollope et al., 1989).

Field measurements were taken with a disc pasture meter at these sites and the herbaceous biomass calculated from a simple regression equation calibrated for Kruger.

The method is fully described in Trollope & Potgieter (1986).


Variograms of the average herba- ceous biomass at each site revealed that the sites exhibited strong spatial structure, suggesting that geostatistical techniques may be useful for interpolation across the park.

Co-kriging is one such geostatistical interpolation technique that minimizes the variance of the estimation error by exploiting the cross-correlation between the variable to be interpolated and another variable (Isaaks & Srivistava, 1989; Webster & Oliver, 2002).

We established that advanced very high-resolution radiometer (AVHRR) derived normalized difference vegetation index (NDVI) metrics had a reasonable cross-correlation with biomass and therefore we used it as a secondary variable in the co-kriging.

Various other studies have also shown that annual metrics derived from remote sensing can be useful for estimating vegetation cover (e.g. Hansen et al., 2002a; Schwarz & Zimmerman, 2005).

We found that co-kriging, using the satellite-derived data described previously as secondary variable, gave better interpolation results than ordinary kriging without the satellite data.

The data and method are fully described in Smit et al. ( in preparation).

The interpolation was carried out on a 500-m grid, before being averaged to the 1-km reference grid.


These data were derived from the moderate resolution imaging spectroradiometer (MODIS).

The product we used is referred to as MOD44B (vegetation continuous fields) and can be found on the internet (http://glcf.umiacs.umd.edu/data/modis/vcf/ description.shtml).

This product estimates for each 500 m pixel, the percentage of the pixel covered by (1) trees (2) bare soil and (3) herbaceous layer.


The dependent data were derived by classifying high-resolution imagery and then aggregating it to the coarser MODIS scale.

The independent data were derived from multitemporal metrics based on a full year of coarse resolution MODIS data.

A regression tree algorithm was then used to predict the dependent variable of tree cover based on signatures from the multi-temporal metrics.


The method is fully described in Hansen et al. ( 2002a) and verified for an African woodland in Hansen et al. ( 2002b).


We included tree canopy cover in our analysis, averaging it to the 1-km reference grid.


The distance from the centroid of each 1-km grid cell to the closest main river was calculated using standard GIS procedures.

Rivers were classified as 'main' rivers if they were perennial or seasonal with reliable pools.


The period studied was during the height of the water stabilization programme, with more than 300 artificial waterholes providing surface water for animals throughout the park (Gaylard et al., 2003).

The distance from the centroid of each 1-km grid cell to the closest artificial waterhole was calculated.


As a first step to establish whether bulls have a wider occurrence in the park, we simply compared the proportion of the total number of cells within which bulls were observed to the proportion of cells within which mixed herds were observed.

The McNemar test (McNemar, 1947) was used to test if the probability is the same to detect a bull group or a mixed herd in any given cell.


Figure 2 illustrates the  results.

Note that both distance to closest artificial waterhole and distance to closest river were nor- malized by the square-root transform.

Northing was relatively uniformly distributed and could not be transformed to a normal distribution using the transformations usually employed, so care should be taken when interpreting the northing results.


To explore the multivariate significance of each resource variable in explaining the presence of mixed herds and bull groups, respectively, logistic regression models were used.

However, con- ventional logistic regression ignores spatial autocorrelation in the residuals.

This often inappropriately inflates the statistical importance of variables (Lichstein et al., 2002; Knapp et al., 2003).


To overcome this, we adopted the approach proposed by Augus- tine et al. ( 1996), by incorporating an autologistic term in the models.

The autologistic term was calculated as the probability of occurrence based on kernel density in a neighbourhood around the cell of interest.


This means that cells with many herds in close proximity will have bigger autologistic values (higher probabilities) than cells with no herds in close proximity (lower probabilities), using a Gaussian distance decay function.


After investigating the indicator variograms (Isaaks & Srivastava, 1989) for mixed herds and bull groups, it was decided to define the neighbourhood as 15 km, representing the range of the spatial dependence.


Although calculated slightly differently, this approach of using a distance decay function is similar with that used in other studies (Augustine et al., 1996; Osborne et al., 2001; Lichstein et al., 2002; Tognelli & Kelt, 2004).


To select among multivariate model terms, backward selection procedures were used.

The full model was run with all explana- tory variables and the term with the highest P value was removed Sexual segregation of elephants running the model.

Terms were removed until the biggest P value was less than 0.05.


The predicted surfaces from the regression models were cross- validated using the elephant distribution data collected in an independent survey (EAS).

We compared if elephants indeed occurred more frequently in cells with higher predicted probabil- ities using a different data set than the one used for calibrating the models.


Statistical analyses were conducted using  (version 14) and all GIS analyses were conducted using  (version 3.2).


Over the 12-year period of this study, bulls were observed in significantly more grid cells (24.89%) than the mixed herds (17.50%) (McNemar χ 2 = 354.8164, d.f. = 1, P < 0.001).


Additionally, 25.08% of the cells within which bulls were observed occurred more than 2 km from the nearest cell within which a mixed herd was recorded, whereas only 3.96% of mixed herd cells were farther than 2 km from the nearest cells where bulls were observed.

Figure 1 confirms this visually.

Note the wide distribution of bulls and the exclusive bull areas as well as the apparent lack of such exclusive areas for mixed herds.


Cells within which only bulls were observed were more north than cells within any of the other categories (Fig. 2a: F = 31.28, d.f. = 3, P < 0.001).

The cells with no elephants were, however, more north than both the cells within which mixed herds and bull groups occurred concurrently, as well as the cells within which only mixed herds occurred.

However, the northing of the cells within which mixed herds and bulls occurred simultane- ously were not significantly different from the northing of cells occupied exclusively by mixed herds.


The categories differed concerning herbaceous biomass (Fig. 2b: F = 41.30, d.f. = 3, P < 0.001).

Bull groups occurred, on average, in cells with more herbaceous biomass than cells within which no elephants were encountered.

Furthermore, cells within which no elephants were observed had more herbaceous biomass © 2007 The Authors Diversity and Distributions, 13, 225-236, Journal compilation © 2007 Blackwell Publishing Ltd 231 than cells within which both mixed herds and bull groups occurred simultaneously.

The latter did not differ significantly from cells within which only mixed herds occurred.


The tree cover was highest in the cells where mixed herds occurred and lowest in cells within which only bulls were encountered (Fig. 2c: F = 63.7, d.f. = 3, P < 0.001).


The cells where elephants occurred were closer to the rivers than cells within which no elephants were observed (Fig. 2d: F = 112.27, d.f. = 3, P < 0.001).

Cells within which both mixed herds and bull groups were observed were closest to the rivers, but this was not significantly closer to rivers than cells where only mixed herds occurred.

Cells within which bull groups occurred exclusively were farther from the rivers than cells where mixed herds occurred exclusively, but it was still closer than cells where no elephants were observed.


The categories differed concerning distance to the closest arti- ficial waterhole (Fig. 2e: F = 37.75, d.f. = 3, P < 0.001).

The mul- tiple comparison test showed that cells within which bull groups occurred were significantly closer to the artificial waterholes than cells within which no elephants were observed.

However, cells within which both mixed herds and bull groups occurred as well as cells within which mixed herds occurred exclusively were farther from the waterholes.


Collinearity between predictor variables may confound their independent effects.

Therefore, prior to logistic regression ana- lysis, we calculated the Pearson correlation coefficients (r) for all pairwise combinations of the independent variables.

The corre- lations between the resource variables were moderate to low (| r | < 0.3) and therefore we did not consider collinearity to be of major concern (Berry & Feldman, 1985).

Table 2 summarizes the variables that were included in the models after backward selection.

Note that both mixed herds and bull groups are attracted to rivers.

Additionally, mixed herds prefer areas with higher tree coverage.

Bull groups seem to be significantly associated with waterholes and although they occur throughout the park, their distribution is biased towards the north.


The autologistic models performed better than a random model in predicting mixed-herd and bull-group dry season distribution of an independently collected data set (Fig. 3).

The cells were sorted from small to large predicted probabilities and based on this, divided into four classes with equal number of cells within each category (i.e. quartiles).

The percentages of the total Fig. 3(a-b), respectively.


The upward trend in both Fig. 3(a-b) indicates that the models are useful in predicting the distribution of mixed herds and bull groups, with more elephant herds occurring in cells with higher predicted probabilities.

Note, however, that there are still considerable sightings in the lower probability classes.

Consider- ing (1) that the models were based on aggregating snapshot data from different years (2) the inherent inaccuracies associated with data collection and recording (3) that elephants may have been recorded as they moved across non-preferred habitat between feeding hot spots (Bayley et al., 1998) (4) the uncertainty associ- ated with interpolation techniques (herbaceous biomass), (5) the inaccuracies associated with remote sensing data (tree cover), and (6) the fact that the various data layers were collected on different spatial scales, the models performed reasonably well.

However, these models are probably more valuable in an explor- atory way, indicating which variables drive the landscape scale and sexually distinct dry season distribution patterns of elephants, rather than being accurate models for predicting fine-scale localized patterns.


This study indicates differences between the elephant dry season distribution patterns of mixed herds and bull groups in the KNP.

Compared to mixed herds, elephant bull groups had a wider scatter across the park.

This provides support for the hypothesis that elephant bull groups have less specific habitat and food requirements (Stokke, 1999; Stokke & Du Toit, 2002), and there- fore they can roam more extensively across a wider range of habitats than mixed herds.

This can be expected because the larger- bodied bulls can tolerate a wider range of forage quality, are more mobile to move between feeding hot spots, and because of smaller group sizes, have lower collective feeding requirements than the bigger mixed herds.

This also agrees with work carried out in Mozambique that found bulls' home range to be larger than that of females (Ntumi et al., 2005).


As resources are more widely available during the wet season, niche differentiation may be weaker during the abundant season when competition is less intense.

For example, Gordon & Illius (1989) and Voeten & Prins (1999) have shown that the distributions of herbivores overlap more during the abundant season than during the lean season.

Ntumi et al. ( 2005) also found that elephants occur in hot spots during the dry season when resources are less abundant.

Therefore, although it seems as if the bull areas remain intact during the wet season (I Whyte, pers.

obs.), the sexual segregation boundaries may become softer during the rainy season because of a wider availability of resources, and musth bulls seeking more mating opportunities.


Over and above the wider distribution of bull groups com- pared to mixed herds, our results demonstrate inter-sexual differences between the resources in the grid cells frequented by the mixed herds and bull groups, respectively.

The univariate non-spatial analysis suggests that the average of resources in grid cells where mixed herds occurred exclusively differed significantly from the average of resources in grid cells where bull groups roamed exclusively.

In addition, it was of particular significance that the resources in the cells within which both mixed herds and bull groups occurred concurrently were more similar to the resources in the cells within which only mixed herds occurred than the cells within which only bulls occurred.

This illustrates that the bulls' distribution and resource use overlaps with that of mixed herds, but not vice versa.


One possible reason is that bulls can utilize resources that the mixed herds utilize, but mixed herds cannot utilize resources/areas that the bulls use (i.e. bull areas).

Furthermore, the bulls' distribution may overlap with mixed herds, as a result of musth bulls associating with the family units for mating opportunities.

However, the time of the surveys (dry season) is when very few females are in oestrus (Smuts, 1975) and mating possibilities would be limited.

It is also likely that the overlap is the result of young males that have left their natal herd, but still occur in the vicinity (Moss, 1988).

We will leave this as an untested hypothesis because no data on size, age and social relationships of the bulls were collected.


Note, however, that this hypothesis of young bulls leaving their natal herd and staying in the area close to the herd is in line with the principle of allometric scaling.

Because elephants grow for their entire lifetime (Laws, 1966; Hanks, 1972), the young mature bulls leaving the mixed herds will be smaller than old bulls and may therefore have habitat and forage requirements similar to that of the smaller individuals in mixed herds (hence the observed resource overlap).

However, as the bulls grow older and bigger, they can move out of these mixed herd areas into bull areas, exploiting resources that will not meet the requirements of the smaller cows, calves and new-generation young bulls.


Mixed herds were expected to occur closer to surface water sources than the bull groups because of higher rates of water turnover (Gordon, 1977; Beuchat, 1990) and lower mobility.

This was indeed observed around the rivers (Fig. 2d), with mixed herds occurring closer to the rivers than the bull groups.

Stokke & Du Toit (2002) observed the same pattern in Chobe, Bot- swana, with bull groups roaming farther from the rivers than the mixed herds during the dry season.

Laws (1970) also noted that bulls could survive for longer periods away from water.


A point of interest in Kruger, however, concerns the pattern around the artificial waterholes, with bull groups occurring closer and mixed herds being neutral to these artificial water sources (Table 2).

We hypothesize that this preference for rivers by the mixed herds is because rivers not only act as water sources, but additionally as a habitat hot spot with shade and higher-quality browse.

Many of the waterholes, especially in the north of the park, are located farther from the main rivers, sometimes in open, grassy areas with little tree cover.

As seen in this paper, this is suboptimal dry season habitat for the mixed herds.

Therefore, surface water availability did not seem to provide a strong enough incentive to lure large numbers of mixed herds away from the rivers and the areas with a denser tree canopy where nutritional, water and shade requirements could be met.

However, our results suggest that waterholes may be more important for bulls.

Visual inspec- tion of Fig. 1 seems to further support this notion.


However, it must be remembered that because of the data collection method, the results of this paper show that mixed herds are not aggregat- ing around the waterholes at the time of the survey and do not Sexual segregation of elephants © 2007 The Authors Diversity and Distributions, 13, 225-236, Journal compilation © 2007 Blackwell Publishing Ltd 233 necessarily imply that the mixed herds do not utilize the water- holes from time to time, at night, during other seasons or when moving across otherwise waterless areas.


The multivariate spatial analysis suggests that tree cover and distance to rivers are significant predictors for mixed herds' dis- tribution, with mixed herds preferring areas close to rivers and with higher tree coverage.

This agrees with the work of Ntumi et al. ( 2005) in Mozambique who found that elephants prefer habitat types with a relatively closed canopy as well as riverine thickets.

This may be expected, as the mixed herds, with their requirements for shade (Laws & Parker, 1968; Laws, 1970; Barnes, 1993) and higher-quality forage (Miquelle et al., 1992; Du Toit, 1985; Weckerley, 1993; Stokke, 1999) will select areas with adequate tree cover.

Furthermore, many studies in Africa have proven that elephants prefer to browse rather than graze during the dry season, providing further support for the impor- tance of trees (Laws, 1970; Beekman & Prins, 1989; Kabigumila, 1993).

The bark and roots of trees also form important high- quality resources utilized by elephants.


Both distance to rivers and distance to waterholes, as well as UTM northing, significantly predict the bull's distribution (Table 2).

It therefore seems as if it is primarily water resources, and not forage (tree or herbaceous cover) determining bull dry season distribution.

This also agrees with our hypothesis that bulls, because of their size, can utilize a wider range of low-quality forage.

Stokke (1999) found similar results in a study conducted at a feeding patch scale.

It was found that family units discriminated between patches in their surroundings and selected patches offer- ing the highest density of palatable species, whereas males were apparently less influenced by the distribution of resources in their environment and browsed in patches containing the same amount and combination of species as surrounding areas.

In Kruger, bulls are often seen during the aerial censuses to stand fully exposed on grassy plains or under the few large trees on grassy plains, whereas it is extremely uncommon to see mixed herds in these open areas.

We propose that bulls can occur on the open grassy plains in the dry season because of their wider tolerance for low-quality food, with grass being less nutritious than browse in the dry season.

Also, individual or small groups of bulls need fewer trees to satisfy their shade and browse requirements (com- pared to the larger mixed herds, which need more shade, cover and browse, especially if young elephants are present).


Considering all the grid cells, the average distance to the closest artificial waterhole and closest main river were 4.4 km and 6.1 km, respectively, for the study period.

This is relatively short distances that should not pose major difficulty for elephants to cross.

There- fore, very little of the park was really significantly far from surface water and hence we expect that a full expression of how elephants relate to surface water could not be expressed in the Kruger context.

Only if many or all the waterholes are closed or rivers dry up, may elephants alter their distribution with regard to surface water.


The elephant population of the Kruger National Park (KNP) increased at a mean intrinsic rate of 7.5% per year between 1967 and 2000 (Whyte et al., 2003).

The culling of elephants from 1966 to 1994 kept the population between 7000 and 8500 indi- viduals.

However, after 1994, a moratorium was placed on cull- ing (Whyte et al., 1999) and the elephant population increased to 12,467 (0.66/km 2 ) in 2005 (Whyte, 2005).

Cumming et al. ( 1997) stated that an elephant density of 0.5/km 2 could convert a savanna woodland to a shrubland.

Various other studies have also proven that high densities of elephants modify and change animal and plant communities (e.g. Western & Gichohi, 1989; Moolman & Cowling, 1994; Johnson et al., 1999; Lombard et al., 2001; Western & Maitumo, 2004) and homogenize habitats.

The core mission of the KNP is the preservation of biodiversity (Mabunda et al., 2003), and a loss of biodiversity as a result of the effects of a large elephant population is therefore unacceptable.

However, whether Kruger has long reached, are about to reach or will ever reach an elephant population density that will cause structural homogenization or cause a loss of biodiversity, are highly debated topics (Anon, 2004) and hence elephant manage- ment, or the lack thereof, remains controversial (Whyte et al., 1998; Whyte, 2001a,b; Gillson & Lindsay, 2003; Skinner, 2005; Whyte & Fayrer-Hosken, in press).


But not only is the need for elephant management in Kruger, and indeed many southern African countries, controversial, but also the options available to managers.

Culling, immuno-contraception, translocations and metapopulations with movement corridors are some of the options often considered (Whyte, 2001b; Anon, 2004).

Another non-intrusive management tool that has been proposed is the management of artificial water sources (Owen-Smith, 1996; Gillson & Lindsay, 2003).


Considering (1) the results presented here (preference of mixed herds for areas close to rivers as opposed to areas close to artificial waterholes during the dry season) (2) the fact that the population growth rate did not decrease post-1997 when more than half of the waterholes in Kruger were permanently closed (Pienaar et al., 1997; Whyte, 2005) (3) the abundance of natural surface water in Kruger (Redfern et al., 2005), and (4) the abundance of elephants in parks with no or little artificial water provision (Barnes et al., 1999), it is unlikely that closure of artificial waterholes will affect the elephant population in the KNP significantly.


In fact, smaller less mobile species with more specific habitat requirements will possibly be more affected if waterholes are closed within their home range (Smit et al., in press).


It is important to distinguish between resource use by elephant bulls and mixed herds because their impact on the habitat may differ.

In this study, we compared the dry season distribution of bull groups and mixed herds, highlighting spatial and resource segregation between them in the Kruger National Park (KNP), South Africa.