Isolated Hypoxic Hepatic Perfusion with Retrograde Outflow in Patients with Irresectable Liver Metastases; A New Simplified Technique in Isolated Hepatic Perfusion

Background Isolated hepatic perfusion with high-dose chemotherapy is a treatment option for patients with irresectable metastases confined to the liver. Prolonged local control and impact on survival have been claimed. Major drawbacks are magnitude and costs of the procedure. We developed an isolated hypoxic hepatic perfusion (IHHP) with retrograde outflow without the need for a heart-lung machine.
Approximately 50–60% of colorectal cancer patients will develop liver metastases during follow-up. In nearly a quarter of these patients the liver is the only site of disease.1 If hepatic metastases of colorectal cancer are resectable, 5-year survival rates are reported between 25% and 45% depending on several prognostic factors.2 Patients with irresectable hepatic metastases have a 0–2% 5-year survival rate and a median survival of 10 months without treatment.3 Therefore, aggressive, selective treatment of the liver seems justified since control of hepatic metastases translates into improved overall survival. Despite the increasing response rates with systemic chemotherapeutic agents such as oxaliplatin and irinotecan in combination with 5-FU and the promising results with the addition of angiogenesis inhibitors,4 overall survival remains poor.5,6 In order to improve responses and survival, locoregional chemotherapeutic regiments have been developed. These therapies include hepatic arterial embolization, intratumoral injections of ethanol, acetic acid, biological agents, stereotactic or intra-arterial radiotherapy, intralesional laser therapy, cryotherapy, radiofrequency ablation, and regional infusion or perfusion of chemotherapeutic drugs. The best approach for regional infusion of chemotherapeutics in the liver is unknown. Hepatic artery infusion (HAI), hepatic artery ligation with hepatic artery and portal vein infusion, or portal vein infusion have all been attempted. Of these modalities, HAI is the most widely applied form. A number of studies have been conducted comparing systemic chemotherapy with HAI, and a modest but significant improvement of survival was demonstrated by HAI in a meta-analysis.7–9
In a leakage-free perfusion setting, isolated hepatic perfusion (IHP) shields the systemic compartment to drug exposure, and in combination with a washout procedure it protects against systemic toxicity. Clinical studies using melphalan with or without tumor necrosis factor alpha (TNF) have shown promising results.10–17 However, IHP is a major, complex, expensive, and time-consuming operation. These features in combination with hepatic and systemic toxicity are major drawbacks toward wide clinical application. Our aim was to develop an IHP that is easy to perform, with limited morbidity or mortality, not time consuming, and with minimal costs of the operation without affecting the antitumor efficacy. We started an isolated hypoxic hepatic perfusion (IHHP) technique with percutaneously placed balloon catheters and retrograde outflow without a heart-lung machine and extracorporeal venovenous bypass in pigs.18 In a recent study, we demonstrated the feasibility of this technique (retrograde outflow of the liver) in a clinical setting.17 A major drawback of the technique was 38% systemic leakage rate. On the basis of these results, we modified the technique by applying an “open” surgical procedure; balloon catheters are replaced by clamps and all tributaries to the vena cava such as the adrenal, lumbar, and diaphragmatic veins are dissected and ligated. Here we present the results of the first 24 patients with irresectable liver metastases who underwent an IHHP with melphalan. The major difference between this new technique and the classic IHP is that there is no veno-veno bypass and heart-lung machine involved and the drainage of the liver is retrograde through the portal vein.
MATERIALS AND METHODS
Patient Selection Criteria
Inclusion criteria were as described previously.17 In all patients a radical resection of the primary tumor was performed prior to entering the study protocol except for one patient with hepatic metastasis of unknown primary. The liver metastases were considered irresectable, on the basis of multiple lesions in multiple segments of the liver and/or location near vascular structures. Tumor involvement had to be less than 50% of the total liver volume to prevent massive necrosis in case of a response. Absence of extra hepatic tumor growth was evaluated by computed tomography (CT) scan of thorax and abdomen. All patients had a Karnofsky performance score of at least 90, liver enzymes (ALAT, ASAT and AF) not higher than five times the normal values, and bilirubin not higher than two times the normal values. Exclusion criteria included: age younger than 18 or older than 70, portal hypertension, significant central nervous system disease, significant cardiovascular, pulmonary or renal disease, uncontrolled infections, presence of organ grafts, and chemotherapy or radiation therapy within 4 weeks prior to the IHHP. Routinely, an angiography was performed to exclude aberrant hepatic arteries or to visualize other anatomic anomalies. The study protocol was approved by the Medical Ethical Committee of the Erasmus University Medical Centre, and written informed consent was obtained from all patients.
Perfusion Circuit
Perfusion sets (PfM, GmbH, Cologne, Germany) consisted of a tubing set with a volume of 220 mL, containing a bubble trap. All IHHPs were performed with inflow via the hepatic artery and outflow via portal vein. In the perfusion circuit, flow was maintained by a roller pump and pressure was measured via a sideline.
Drugs
A dosage of 1 mg/kg melphalan (L-Pam, Alkeran, Wellcome Ltd. London, UK) was used in 20 of the 24 patients and infused through a sideline into the perfusion circuit. Two times 1.5 mg/kg melphalan and two times 2.0 mg/kg was used. In the first eight patients, a bolus infusion was used. In the last 16 patients, a 10-minute pump infusion was used. The total perfusion (10-minute infusion included) with melphalan was conducted for 20 to 30 minutes.
Surgical Procedure of the Retrograde Flow IHHP
A right subcostal incision was performed, and the liver was mobilized from its retroperitoneal and diaphragmatic attachments. A prophylactic cholecystectomy was not performed routinely. Tributaries to the vena cava such as the adrenal, lumbar, and diaphragmatic veins were dissected and ligated. The vena cava was isolated and clamped above and below the liver, respectively, to prevent venous leakage. The portal vein, proper hepatic artery, and gastroduodenal artery were dissected, and the hepatic artery cannulated via the gastroduodenal artery with an 8 F catheter for inflow of the perfusate. In two patients, an aberrant left hepatic artery, coming from the left gastric artery was cannulated together with the proper hepatic artery for inflow. The portal vein was cannulated with a 14 F catheter for outflow. Patients subsequently received 2 mg/kg heparin. The hepatic artery catheter and the portal vein catheter were connected to the perfusion circuit primed with 220 mL Haemaccel (Behring Pharma, Amsterdam, The Netherlands). After clamping of the caval vein superior and inferior of the liver, clamping of the aorta just beneath the diaphragm, clamping the portal vein just above the pancreas, clamping the proper hepatic artery just proximal of the gastroduodenal branch, and clamping of the common bile duct with its surrounding tissue, the retrograde isolated perfusion was performed. The retrograde perfusion setup is depicted in Fig. 1.
FIG. 1.The retrograde perfusion setup.
The perfusate was circulated by a constant flow. Stable perfusion was monitored by pressure measurement and the perfusate level in the bubble trap. Hereafter, melphalan was infused into the circuit and the perfusion was conducted for 20 to 30 minutes. Thereafter, a washout procedure was performed by 1 L of Haemaccel collecting the venous effluent. Total liver ischemia time never exceeded 60 minutes.
The isolation was terminated by relief of the clamps on the caval vein followed by the relief of the aortic clamp, controlling systemic blood pressure. The catheter in the hepatic artery could be removed and the gastroduodenal artery could be ligated followed by decanulation and closing the venotomy of the portal vein. In case of an aberrant left hepatic artery, this artery was ligated after removal of the catheter.
Leakage Monitoring
During IHHP, potential leakage of drugs was monitored using a radioactive tracer. A small calibration dose of human serum albumin radiolabeled with 131I was injected into the systemic circulation prior to the perfusion and 10-fold higher dose of the same isotope was injected into the isolated hepatic perfusion circuit. Continuous monitoring was performed with a precordial scintillation probe. Systemic leakage is expressed quantitatively as a percentage (100% leakage representing a homogeneous distribution of the isotope in the body).14
Blood Sampling
Before, during, and after the perfusion blood samples were taken and collected to study pharmacokinetics of melphalan and hematological, renal, hepatic, and gastrointestinal toxic side effects. Toxicity is graded according to the standardized WHO common toxicity criteria.19
Measurement of Melphalan Concentrations
Melphalan was measured in plasma by gas chromatography–mass spectrometry (GC-MS). P-[Bis(2-chloroethyl)amino]-phenylacetic acid methyl ester was used as an internal standard. Samples were extracted over trifunctional C18 silica columns. After elution with methanol and evaporation, the compounds were derivatized with trifluoroacetic anhydride and diazomethane in ether. The stable derivates were separated on a methyl phenyl siloxane GC capillary column and measured selectively by single ion monitoring GC-MS in the positive EI mode described earlier by Tjaden et al.20
Assessment of Tumor Response
This was done by comparing pre-perfusion CT and/or MRI scans of the liver with scans made at 8–10 weeks after IHHP. The tumor marker carcinoembryonic antigen (CEA) was monitored (when indicated) preoperatively and 8–10 weeks postperfusion, but was not used for response assessment. Clinical responses are assessed by standardized WHO criteria.19
RESULTS
Patient Characteristics (Table 1)
In a total of 24 consecutive patients, 13 males and 11 females with a median age of 57 years (range, 41–70) were included in the protocol. Eighteen patients had irresectable metastases of colorectal origin, four ocular melanomas, one sarcomas, and one unknown primary hepatic metastases.
TABLE 1.Characteristics of 24 patients with irresectable liver metastases treated by IHHP with retrograde outflow via portal vein with melphalanPTTumor primaryProgressive on chemotherapyToxicityResponse after perfusionTime to progr. (months)StatusMonths after perfusionHepatoBloodRenal1CRCNo100CR10Alive462CRCNo100PR24Dead383CRCYes140SD12Dead424CRCNo100PR6Dead295CRCNo130PR20Dead326EMNo100PR5Dead97SARCNo130PR13Dead178CRCNo200PR9Dead99CRCYes100SD12Dead3710CRCYes100PD2Dead1011CRCNo100PR9Dead2912CRCNo100PD9Dead1813CRCNo100PD2Dead814CRCYes100PR4Dead1815EMNo100PR5Dead616CRCNo120PR9Alive2917UPYes130PD2Dead518EMNo100PR9Dead2019CRCNo220PR4Dead620CRCNo101PR5Dead521EMNo120PR13Dead1522CRCYes100PD4Dead623CRCYes100SD5Dead624CRCYes100PD9Alive11PT, patient number; CRC, colorectal cancer; CR, complete response; SARC, sarcoma; PR, partial response; EM, eye melanoma; SD, stable disease; UP, unknown primary; PD, progressive disease.
Operation Characteristics
Median operation time was 240 minutes (150–300 minutes), including perfusion time. Median blood and fluid loss was 900 mL (300–3200 mL). In the first eight patients, melphalan was administered as a bolus into the isolated liver circuit. The last 16 patients received a 10-minute pump infusion of melphalan. The perfusion (10-minute infusion included) with melphalan was conducted for 20 to 30 minutes. Perioperative mortality (<90 days) was 0%. Median hospital stay was 9 days (5–29 days).
Leakage Control
All IHHPs were leakage free during the perfusion except in one patient, where 2% systemic leakage was measured. When this perfusion was finished, it appeared that in this patient there was an insufficient clamping of the suprahepatic caval vein. After washout of the isolated circuit with Haemaccell, a median of 7% (4–10%) leakage into the systemic circuit was demonstrated by continued monitoring until the end of the operation.
Toxicity Study (Table 1)
Hepatic toxicity consisted mainly of a transient rise of liver enzymes during the first week after IHHP. WHO grade I occurred in 92% of the patients (22 of 24) and WHO grade II in 8% of the patients (2 of 24). Three patients experienced bile duct necrosis (discussed in detail in the section “Complications”). No other hepatic toxicities occurred (no coagulopathy was observed). Systemic toxicity was mainly leucopenia, WHO grade I–III in 25% (6 of 24), and severe grade IV leucopenia in one patient (4%) after perfusion. Two of these patients received G-CSF (Neupogen, Amgen B.V., Breda, The Netherlands). One patient received prophylactic G-CSF. Eighteen patients (71%) did not develop leucopenia. No renal (except for one patient grade 1) or gastrointestinal toxicity was observed.
Melphalan Pharmacokinetics
Figure 2 shows a drug concentration vs time curve in the isolated circuit in a patient with a pump infusion. The area under the concentration versus time curve (AUC) calculation showed a regional concentration of 2382 (μg × min/mL) versus undetectable systemic that makes the ratio AUC regional/systemic infinite (Fig. II). The median peak regional melphalan concentration was 68.04 μg/mL (range, 42.3–256.99) and negligibly low to undetectable systemic concentrations. After washout and subsequent releasing of the clamps, median peak systemic 4.2 μg/mL (range, 3.00–18.33) melphalan concentrations were observed. The AUC calculation showed a systemic concentration of 275 μg × min/mL after washout. Thus, intrahepatic melphalan concentrations during the IHHP are >9 fold higher than the post-IHHP systemic melphalan concentrations.
FIG. 2.Drug-concentration versus time curve.
Complications
In three patients, bile duct necrosis occurred (Fig. 3). One of these patients was asymptomatic, and bile duct necrosis was found on routine CT scan during follow-up. Two of the patients with bile duct necrosis developed fever. No other explanation could be found for the fever, besides the intrahepatic “bilomas,” and therefore one patient was treated with percutaneous drainage and endoscopic stent placement in ductus choledochus. The other patient with fever received antibiotics. Both patients recovered, and slight elevations of bilirubin persisted, without complaints. In the first eight patients melphalan was administered as a bolus into the isolated liver circuit. After four patients melphalan dose was increased to 1.5 mg/kg in two patients and to 2 mg/kg melphalan in another two patients. Three of these patients (37.5%) developed bile duct necrosis, which is why the other 16 patients were treated with 1 mg/kg melphalan using a 10-minute pump infusion into the circuit. Bile duct necrosis did not occur in these patients. Postoperative chemical cholecystitis was not demonstrated.
FIG. 3.Intra-hepatic bile duct necrosis after IHHP
Tumor Response and Patient Survival (Table 1)
In one patient a complete response was observed (4%). Partial response (PR) was seen in 14 patients (58%), and stable disease (SD) was demonstrated in three patients (13%). Overall, a clinical response rate of 62% and a clinical benefit of nonprogression in 75% were observed. Six patients developed progressive disease (25%). Progressive disease occurred with median interval after IHHP of 9 months (range 2–24 months). Sixteen patients had progression of the liver tumors during follow-up. Fourteen patients developed extrahepatic disease during follow-up. To analyze the response rates and survival, it may be more opportune to include only the 18 patients with colorectal liver metastases. Median follow-up was 18 months. Median patient survival for patients with colorectal liver metastases (n = 18) was 18 months (range, 5–46 months). Median time to progression was 9 months (2–16 months). Seven of these 18 patients experienced failures of systemic chemotherapy. Two patients (PtNo 3 and 23) were progressive on the combination of 5-fluorouracil (5FU) and oxaliplatin (FOLFOX) (10 and 6 cycles, respectively), two patients (PtNo 9 and 10) were progressive on 5-FU and leucovorine (22 and 16 cycles, respectively), one patient (PtNo 14) was progressive after Xeloda (four cycles) and irinotecan (four cycles), one patient (PtNo 24) after six cycles of FOLFOX and four cycles of irinotecan, and one patient (PtNo 22) was progressive after Xeloda (six cycles), irinotecan (six cycles), and combination of Xeloda and oxaliplatin (XELOX) (eight cycles). Median survival for patients with colorectal liver metastases, not treated with chemotherapy before IHP (n = 11), was 29 months (range, 5–46 months).
DISCUSSION
Isolated liver perfusions are only performed by a few centers worldwide, demonstrating promising antitumor effects; however, the technique is a major, complex, expensive, and time-consuming operation. In the present study we describe an alternative technique using a retrograde hepatic flow in an isolated hypoxic hepatic perfusion (IHHP) system. The technique was performed in 24 patients and demonstrated to be safe, with minimal morbidity and no morbidity. Overall response rate was 62% with no progression in 75%, and median time to progression of disease was 9 months.
The magnitude of the standard isolated liver perfusion technique is well demonstrated in two recently published series by the centers with the largest experience in IHP (NCI, Bethesda, MD, USA, and LUMC, Leiden, The Netherlands, respectively).11,15 Median IHP operation time was reported to be more than 8 hours (range, 5.8–14.7 hours). In the study of Bartlett et al.11 the estimated blood loss was 2.2 L (range, 0.8–4.5 L), and Rothbarth et al.15 reported a range of 0.9–10 L (median not given, older series mean of 4.4 L). Mortality (<30 days) occurred in both series with 5.6% in the Leiden series (n = 71) and 4% in the NCI series (n = 124). Classical IHP uses a venovenous bypass and a heart-lung machine, which is a time-consuming procedure necessitating a specialized perfusion team. In the present study a modification was developed, allowing a safe perfusion in a shorter operation time (median duration, 4 hour), with less blood loss (median, 900 cc), reducing morbidity and without mortality, without the need of a heart-lung machine or venovenous bypass.
The absence of mortality (<90 days) in the present study can be explained by the smaller number of patients and/or patient selection. However, it may well be related to the smaller magnitude of the operation and the corresponding decreased operation time and blood loss. Median hospital stay was 9 days (range, 5–29), which was also shorter than the 12 and 11 days in the aforementioned studies.11,15
Hepatic toxicity is remarkably low in the present series except for three patients who developed bile duct necrosis (Table 1). High peak concentrations of melphalan in the isolated circuit might explain the bile duct necrosis that was observed in patients who were perfused with higher melphalan concentrations. In a preclinical study, the occurrence of severe cholangiofibrosis was strongly dependent on the melphalan concentration.21 The study also demonstrated that tumor response was not affected by melphalan peak concentration, but by the total dose of melphalan. Therefore, to prevent high peak concentrations keeping the same concentration of melphalan, bolus infusions were replaced by a 10-minute pump infusion. This resulted in the absence of bile duct necrosis in the last 16 perfused patients.
The maximum period of 60-minute hypoxia did not seem to result in extrahepatic and/or systemic toxicity. Moreover, clamping of the aorta just underneath the diaphragm for a maximum of 60 minutes did not lead to renal and/or gastrointestinal morbidity.
To overcome the use of a venovenous bypass and heart-lung machine, we performed a hypoxic perfusion. The use of hypoxia might also enhance the antitumor effect. Hypoxia renders tumor cells more sensitive to cytostatic agents in general and enhances the antitumor effects of drugs such as melphalan.22,23 Changing the perfusion direction may reduce liver toxicity, without affecting the antitumor efficacy as described by Rothbarth et al.24 An animal study demonstrated an unaffected tumor uptake and a reduced liver uptake by 80% in an IHP model with arterial inflow and retrograde portal outflow.25 This may explain our remarkably low hepatic toxicity in the present series using retrograde outflow in a clinical setting.
In the large IHP series of patients with colorectal liver metastasis, response rates of 74% and 59%,11,15 respectively, are reported, which is in line with the response rate in the present study. The median time to progression in these IHP studies was 14.5 and 7.7 months, respectively. The time to tumor progression of 9 months after IHHP seems to be comparable to these numbers. Alexander et al. published their results in patients with progressive disease after irinotecan-based therapies, and still a response rate of 60% was obtained after IHP with melphalan.16 The 2-year survival was 28% with a 12-month median survival. Although interpretation and comparison of the results from these different studies are difficult, the results of the retrograde IHHP technique described here are similar. In the past 10 years, new anticancer agents (oxaliplatin and irinotecan) have increased the response and survival rates. The addition of targeted therapies (cetuximab and bevacuzimab) may increase the response rates more than 70%. Especially in this era of exciting developments, tailored treatment to increase individual survival rates while keeping the toxic effects to a minimum is challenging. The role of IHP in colorectal liver metastases has been discussed in recent reviews.24,26,27 The promising results of the IHP studies in the past years cannot be disregarded. It is conceivable to combine IHP with adjuvant treatment strategies to reduce the recurrence rate, which is the major determinant of the survival rate after IHP. Continuing locoregional treatment by HAI after an IHP procedure is technically feasible and appears to prolong the duration of the response and survival in patients with colorectal hepatic metastases.11 Of the 18 patients with colorectal liver metastases in the present series, 10 developed extrahepatic disease, suggesting the need for additional systemic treatment. Duration of tumor control needs to be improved. To achieve this, the addition of vasoactive drugs, identified in our laboratory to have synergistic activity in combination with melphalan by significantly increasing drug uptake in the metastases, will be explored in further studies.28,29 At this time, IHHP should be reserved for those patients who are progressive on standard chemotherapy protocols. When responses in future trials are improved, this technique might be optional for patients who prefer a single procedure, which could potentially lead to similar results as multiple courses of systemic or intra-arterial chemotherapy. Leaving behind at the end of the IHHP a port-a-cath system for subsequent HAI in case of (re)progression should also be considered as a strategy to further improve prolonged locoregional tumor control.
In ocular melanoma, the liver is the only organ site involved in 70–80% of patients and is usually responsible for death.30,31 The prognosis of a patient with hepatic metastases from uveal melanoma is extremely poor, with a median survival between 2 and 5 months.32 Partial liver resection is seldom possible. The therapeutic options are not very effective with systemic chemotherapy, providing 9% partial responses and no survival benefit.33,34 There is limited experience with IHP for hepatic metastases from uveal melanoma, but the response rates are promising.35–37 Despite the fact that the experience with hepatic metastases from uveal melanoma is small in the present study (n = 4), IHP seems to be an effective treatment. All four patients died because of progressive tumor growth and consequent liver failure after 6, 9, 15, and 20 months. Therefore, especially in this group of patients, local tumor control is likely to result in a survival benefit.
CONCLUSIONS
Isolated hypoxic hepatic perfusion with retrograde outflow via portal vein is a promising technique that is a relatively simple procedure with reduced blood loss, no mortality, very limited toxicity, and response rates comparable to classic, extensive IHP. The operation time is reduced to 4 hours, without the need of a heart-lung machine and perfusionists, which reduces the costs.

hypoxic
retrograde outflow
isolated hepatic perfusion
melphalan
metastasis


When pharmacotherapeutic recommendations may lead to the reverse effect on physician decision-making

For long the medical literature has shown that patients do not always receive appropriate care, including pharmacotherapeutic treatment. To achieve improved patient care, a number of physician-oriented interventions are being delivered internationally in an attempt to implement evidence based medicine in routine daily practice of medical practitioners. The pharmacy profession has taken an active role in the delivery of intervention strategies aimed at promoting evidence based prescribing and improved quality and safety of medicine use. However, the medical literature also supports the notion that valid clinical care recommendations do not always have the desired impact on physician behaviour. We argue that the well-established theory of psychological reactance might at least partially explain instances when physicians do not act upon such recommendations. Reactance theory suggests that when recommended to take a certain action, a motivational state compels us to react in a way that affirms our freedom to choose. Often we choose to do the opposite of what the recommendation is proposing that we do or we just become entrenched in our initial position. The basic concepts of psychological reactance are universal and likely to be applicable to the provision of recommendations to physicians. Making recommendations regarding clinical care, including pharmacotherapy, may carry with it implied threats, as it can be perceived as an attempt to restrict one’s freedom of choice potentially generating reactance and efforts to avoid them. By identifying and taking into account factors likely to promote reactance, physician-oriented interventions could become more effective.
It is well known that the use of medicines often results in avoidable complications or adverse events. In the United States a study showed that approximately 60% of iatrogenically related admissions to intensive care units were drug related and 75% were preventable [1]. In Australia, adverse medicine events are responsible for 1.6% of all hospital admissions [2].
To achieve improved quality and safety of medicine use, a number of physician-oriented interventions are being delivered internationally in an attempt to improve evidence based prescribing in routine daily practice of medical practitioners—e.g., distribution of educational materials, decision support systems, outreach visits, medication reviews, etc.
The pharmacy profession has taken an active role in the delivery of intervention strategies related to pharmacotherapy. For example, in medication review programmes, pharmacists interview patients, conduct assessments of information gathered on patients’ use of medicines and prepare reports for physicians, which may contain pharmacotherapeutic recommendations [3]. Pharmacists also are typically involved in educational outreach programmes. In such programmes it is common for pharmacists to take up the role of educator, visiting physicians in their office to provide educational interventions on specific pharmacotherapeutic topics. As pharmacists and physicians share expertise in pharmacotherapy, their involvement in intervention strategies aimed at promoting quality and safety of medicine use makes sense. Indeed, the literature has reported positive results on patient health outcomes arising from such interventions [4, 5].
However, despite the delivery of interventions designed to foster quality and safety of medicine use, the literature provides support for the notion that, at times, despite physicians agreeing to the value of evidence based clinical recommendations, intervention strategies do not always have an impact on physician behaviour. For example, in a study in which both physicians and community pharmacists had negotiated actions based on medication reviews, the researchers were only able to document a rate of implementation of 42% of the proposed actions [6]. These findings are supported by our own experience working with community pharmacists involved in medication management programmes in Australia. Some of these pharmacists report that sometimes their recommendations have the desired impact on physician choice of pharmacotherapy, but at times they have no impact at all and in some instances they even cause physicians to respond negatively.
As expected, failure to change physician behaviour is not restricted to the prescribing area. Indeed, non-compliance to evidence based recommendation is a consistent finding in clinical care research [7]. For example, Grol and Grimshaw [7] note that hospital-acquired infections affect one in every 11 patients with 13% mortality rate and that 15–30% of infections are considered to be preventable by handwashing [8]. Still, compliance with handwashing by health care providers, in particular medical practitioners, is known to be poor [7]. Indeed, with surprising frequency, and to the considerable dismay of interventionists, physician-oriented interventions often fail to improve handwashing behaviour [7, 9]. Without a doubt while there are certainly circumstances that may lead physicians to justifiably question clinical care recommendations, in general non-compliance to evidence based recommendations proves costly to patients and society alike.
Currently, there is a lack of theoretical framework for understanding instances when valid recommendations do not lead to the desired impact on physician behaviour. The key question is: What are the barriers that impede physician acceptance of valid recommendations? We argue that the theory of psychological reactance [10] might at least partially explain instances when evidence based recommendations fail to impact on physician behaviour.
Psychological reactance
Psychological reactance is a tendency to resist perceived attempts by others to control the individual’s behaviour [10]. Most of us like to perceive ourselves as being in control; we value our sense of freedom and autonomy and like to project an image of being in control [11]. In general, when we perceive that our freedom of choice is being restricted by the action of others, we react in a way that affirms our ability to choose. Often we choose to do the opposite of what the recommendation is proposing that we do or we just become entrenched in our initial position. This phenomenon is called psychological reactance [10]. Reactance is directed towards reattaining the restricted freedom; a motivational state compels us to reassert that freedom [10]. In many circumstances, reactance results in an increase in the attractiveness of the constrained behaviour and an increased sense of confidence in the ultimate decision made [10]. Particular noteworthy is the finding that reactance appears to be a biological tendency, an inherent human characteristic. At the very least, it can be said that reactance manifests itself at a very young age [12].
For the last four decades the theory of psychological reactance has been widely tested and applied with reactance being widely recognised as a powerful determinant of behaviour. To date, studies across a vast array of behaviours have consistently demonstrated that recommending that individuals take a certain course of action often produces the opposite effect, consistent with this tendency to resist perceived attempts by others to restrict freedom of choice. For example: in the marketing area research indicates that expert recommendations are desirable as long as they are consistent with the choice tendency of individuals. When expert recommendations contradict the consumer’s choice tendencies, a reactant state is activated on the part of the decision maker leading to a behavioral “backlash” that results not only in consumers ignoring the recommendations but in intentionally contradicting them [13]. Not only there is an increase in choice of the non-recommended option, but also a significant increase in confidence in the non-recommended option [13].
In the healthcare literature, psychological reactance has been primarily used to explain patient non-compliance, i.e., why some patients refuse to cooperate with medical treatment [14, 15]. Fogarty and Young [15] conducted research that indicates that individual variability in compliance to a medication regimen is related to individual variability in reactance as a personality trait [15]. Psychological reactance has also for long been observed in the natural setting in response to perceived attempts to restrict one’s freedom of choice. A classic example of psychological reactance in the everyday life took place when a city in the United States banned the possession and use of laundry detergents containing phosphates for environmental reasons. It was found that residents stockpiled an enormous quantity of detergents containing phosphates before the ban went into effect. Others organised carpools to neighbouring counties to purchase detergents containing phosphates [16, 17]. As a result of the ban, the perceived value of the prohibited products was increased; compared with residents in neighbouring counties, who were free to choose whatever detergent they liked, residents subjected to the ban rated phosphate detergents as gentler, easier to pour, better whiteners and stain removers, and more effective in cold water. It is noted that phosphates have no impact whatsoever on the cleaning effectiveness of detergents.
Psychological reactance and physician-oriented interventions
The long history of successful support for reactance theory in diverse settings and areas of behaviour may also have implications for physician-oriented interventions in which evidence based clinical recommendations are provided, as health care providers may not be immune to the phenomenon of psychological reactance. It is true that the basic concepts of psychological reactance are universal and likely also to be applicable to the provision of evidence based clinical recommendations to physicians.
In the context of physician-oriented interventions, the theory and research on psychological reactance would predict that at times when opposing recommendations are provided, physicians’ perceptions of threats to their freedom to select an appropriate course of action could produce the opposite reaction leading them to become more likely to ignore the recommendation or to choose the non-recommended option. This would be the case even in circumstances where physicians may agree, in essence, to the value of the recommendation....to the extent that it is perceived by the individual that the communicator is trying to make him change, his freedom to decide for himself will be threatened and he will experience reactance... Information and arguments can be quite helpful to the individual and may result in positive influence, but the perception that the communicator is attempting to influence will tend to be seen as a threat to one’s freedom to decide for oneself ([10], p. 94 cited in [14]).Indeed, making recommendations regarding clinical care, including pharmacotherapy, may carry with it implied threats, as it can be perceived as an attempt to restrict one’s freedom of choice generating reactance and efforts to avoid them. Furthermore, the inherent “veto” power that physicians have over the treatment regimen may facilitate manifestation of reactant-style responses making non-compliance to evidence based recommendations more likely to occur.
It is also important to recognise that even in circumstances where physicians agree to participate in interventions, they may not necessarily expect their practice to be challenged. For example, there are several possible reasons for a physicians agreeing to a medication review. In some cases, physicians may wish to monitor the individual patient’s self-medication habits or they may be concerned about possible patient non-compliance with the medication regimen.
It is also true that physicians have for long subscribed to a body of ethical rules created above all for the benefit of the patient [18]. Professional behaviour of medical practitioners is guided by these ethical rules, which dictate what is morally approved and disapproved conduct specifying what ought to be done [18]. It is reasonable to expect medical ethics to have a considerable impact on physician decision-making in situations that involve potential harm to the patient. For example, the use of a non-steroidal anti-inflammatory drug (NSAID) in a patient taking the anticoagulant warfarin puts the patient at an increased risk of bleeding. In such situations, which involve potential harm to the patient, recommendations arising from intervention strategies most certainly will be recognised by the physician as an injunctive professional norm (a norm of “what ought to be done”) and most certainly will be implemented. However, it is possible that providing physicians with valid opposing clinical care recommendations that do not involve potential harm to the patient may at times be counterproductive. For example, in a patient with low gastrointestinal and cardiovascular risk, recommendation to use a non-selective NSAID if the patient is responding well to a COX-2 selective NSAID, may be perceived as an unwarranted attempt to restrict one’s action, increasing the likelihood of a reactant-style response.
Although no study appears to have specifically addressed reactance from a health care providers’ perspective, a recent qualitative study has provided some indication that reactance might play a role in physician decision-making in response to pharmacotherapeutic recommendations [19]. This study investigated determinants of successful collaboration between community pharmacists and physicians in medication review. Participating pharmacists discussed the need to be diplomatic in their recommendations, as they believed physicians’ misperception that they were “telling them what to do” could induce dismissal of their recommendations.
Possible determinants of reactance
It is possible that reactant responses may be more likely to occur in situations where the physician has not requested the information/recommendation. Experiments outside the medicines area have demonstrated that unsolicited information can evoke psychological reactance even when recommendations provide a substantial amount of information beyond what the decision maker knows [20]. Interestingly enough, in situations where the recommended action went contrary to the individual’s choice tendency, this reactance to unsolicited information was significantly more likely to occur when recommendations came from a source perceived to be an expert [20]. The authors suggest that unsolicited recommendations may be perceived as more of a threat or an intrusion when they come from credible sources. It is noted that although unsolicited information is typically provided to physicians through written materials and computerised decision support systems, in some programmes medicines use review can be initiated by the pharmacist and report sent to the patient’s physician in an unsolicited fashion [21].
It is also possible that the perception that the particular interventionist is directing recommendations specifically to the particular physician, as opposed to the treatment of the patient’s condition in general, also could make reactance more likely to occur. Brehm [10] demonstrated that reactant responses are more likely to occur when individuals perceive the constraint as being specifically directed at them as opposed to when it is perceived to be impersonal [10]. If indeed, this is found also to apply to physician-oriented interventions, it may have implications for how pharmacists and other health care professionals provide recommendations to physicians.
Sense of medical professionalism might also be implicated in reactant responses. We do value our sense of freedom and autonomy and we like to project an image of being in control [11]. Indeed, physicians are trained to make sound decisions with regard to treatment regimen and it is reasonable to expect them to believe that they are in control and have the knowledge and skills required to make the best possible decisions. The acceptance of a contrary recommendation to what is being used to treat the patient’s illness could undermine the physician’s own sense of competence, reducing the cognitive basis of professionalism. On the other hand, dismissal of the recommended option could have the opposite effect reinforcing physician’s ability to choose the most appropriate treatment.
We also know that once aroused, reactance may heighten individual’s sensitisation to additional threats to freedom of control [22]. It is also reasonable to believe that at a time when governments are encouraging greater involvement of allied healthcare professionals in patient care, issues related to professional territoriality may sensitise physicians to reactance in response to recommendations from allied healthcare professionals, including the pharmacist. Although the literature reports positive medical profession’s attitudes to pharmacists and their clinical role, some sentiments of encroachment are supported by studies that found that not all physicians view favourably greater involvement of pharmacists in patient care [23–25]. Thus, the physician-pharmacist interaction in the intervention process could be burdened with social and personal pressures, which can increase the possibility of a reactant response. Indeed, psychological reactance may offer a theoretical framework that could enhance our understanding of the, at times, difficult relationship between pharmacists and physicians.
It is also possible that the nature of the physician relationship with the allied healthcare professional is also a determinant of reactance. For example, it has been argued that the most successful pharmacist interventions have been those in which the pharmacist works in close liaison with the physician [26]. Indeed, in the United States much of the evidence supporting pharmacist involvement in collaborative drug therapy management is derived from the ambulatory care setting [27] where routine contact with physicians may allow for the development of the trusting relationship needed for interprofessional collaboration [28].
Finally, another factor that may determine reactant responses to recommendations include individual differences, as some people are more likely to have a reactant response in general to any perceived constraint [29]. Individual variations in susceptibility to reactance can explain why identical situations may lead to markedly different perceptions of threat and magnitudes of reactant responses in different persons. Indeed, scales developed to measure reactance as a trait demonstrate that individual reactance levels lie along a continuum from very low to very high [29]. Naturally, in the context of physician-oriented interventions, the nature and intensity of the reactant response is also likely to be a function of how much the particular physician values his/her freedom to select the treatment option him/herself. Again, a recent qualitative study provides some support to the notion that some physicians are more prone to psychological reactance than others [19]. In this study, personality of medical practitioners was discussed as a factor influencing the outcome of medication review. Participating pharmacists distinguished between physicians who they thought were amenable to discussing their prescribing decisions and those who were not. These results indicate that interventionists do assess the reactance potential of the individual physician although it is unlikely that they label the assessment as such. It is noteworthy that when interventionists sense reactance in their interaction with the physician, they may be faced with a difficult dilemma, as they are aware of the possibility that the provision of evidence based clinical recommendation may trigger the opposite response. What can the interventionist do in such situation?
Dealing with reactance
A phenomenon like psychological reactance, which is likely to impede the desired outcome of physician-oriented interventions, needs to be adequately addressed when training healthcare professionals to deliver such interventions. We must be mindful that the process of delivering physician-oriented interventions can be difficult as psychological reactance is not a reasonable or rational response; it can cause people to become highly emotional and motivated to defend their behaviour.
Prior research on reactance suggests that individuals’ ability to exercise some choice (freedom) in relation to recommendations may impact on compliance to the advice provided. That is, maximising the individual’s perception of free choice can minimise reactance [22]. It is possible that the degree to which the physician is incorporated in the selection of evidence based clinical care practices may affect the extent to which the intervention will induce reactance. Indeed, it is possible that intervention strategies which give physicians the impression they have little or no say on their own clinical practices will be less likely to be effective, as they are perceived as more threatening, compared to those where physicians perceive themselves as exercising some choice.
We are now training pharmacists on how to deal with psychological reaction in the context of medication review. We also expect such training to enhance commitment to the pharmacy lead intervention from the interventionist’s perspective, as after being equipped with tools for dealing with reactance, pharmacists may experience a greater sense of self-efficacy in dealing with all types of physicians, including those who are highly reactant. In addition, awareness of reactant responses and its causes may assist pharmacists and other healthcare professionals in altering their emotional response to reactant behaviour avoiding a decreased sense of self-efficacy.
Concluding remarks
The current paper addressed an intrinsic human characteristic, psychological reactance, as a factor that may influence the outcome of physician-oriented intervention strategies, including those typically delivered by pharmacists. Although psychological reactance has not been tested from a healthcare provider’s perspective, there is enough research to suggest the basic cognitive process represented is universal and also valid in the context of clinical care recommendations in the healthcare setting. Indeed, reactance theory fits well as it offers some explanation of why at times valid recommendations fail to have the desired impact on physician behaviour.
It is possible that as human beings, even healthcare professionals are subjected to the same human emotions and weaknesses as humans in general. However, a role for reactance in clinical care recommendations needs to be investigated empirically. If this role is established, factors likely to increase the potential for reactance may need to be taken into account when implementing intervention strategies that attempt to influence physician behaviour.
It also is acknowledged that physician non-compliance to valid recommendations is more likely to be a complex, multi-faceted phenomenon. Physicians may not adhere to evidence based recommendations for a number of reasons unique to the individual patient, and the circumstance. It is most likely that reactance, although a powerful determinant of behaviour in general, is only one of the many factors that influence decision-making in relation to clinical care/pharmacotherapeutic recommendations.

physician
interventions
psychological reactance
decision support systems
medication review
pharmacist
professional behavior change
continuing medical education
health psychology


Impacts of savanna trees on forage quality for a large African herbivore

Recently, cover of large trees in African savannas has rapidly declined due to elephant pressure, frequent fires and charcoal production. The reduction in large trees could have consequences for large herbivores through a change in forage quality. In Tarangire National Park, in Northern Tanzania, we studied the impact of large savanna trees on forage quality for wildebeest by collecting samples of dominant grass species in open grassland and under and around large Acacia tortilis trees. Grasses growing under trees had a much higher forage quality than grasses from the open field indicated by a more favourable leaf/stem ratio and higher protein and lower fibre concentrations. Analysing the grass leaf data with a linear programming model indicated that large savanna trees could be essential for the survival of wildebeest, the dominant herbivore in Tarangire. Due to the high fibre content and low nutrient and protein concentrations of grasses from the open field, maximum fibre intake is reached before nutrient requirements are satisfied. All requirements can only be satisfied by combining forage from open grassland with either forage from under or around tree canopies. Forage quality was also higher around dead trees than in the open field. So forage quality does not reduce immediately after trees die which explains why negative effects of reduced tree numbers probably go initially unnoticed. In conclusion our results suggest that continued destruction of large trees could affect future numbers of large herbivores in African savannas and better protection of large trees is probably necessary to sustain high animal densities in these ecosystems.
Introduction
Savanna ecosystems are characterized by a continuous grass layer interspersed with trees and shrubs. The density and diversity of large herbivores is very high in African savannas and many pastoral communities depend on semi-natural savannas through livestock grazing (Prins and Olff 1998; Olff et al. 2002). The effects savanna trees have on understorey grass productivity have been a focus of research for decades, and both negative and positive effects have been described (Belsky et al. 1989; 1993; Mordelet and Menaut 1995; Ludwig et al. 2001; 2004a). Trees reduce grass growth by competing with grasses for water, light and nutrients (Scholes and Archer 1997; Anderson et al. 2001; Ludwig et al. 2001, 2004b), but trees can also improve grass production through hydraulic lift (Caldwell et al. 1998; Ludwig et al. 2003), reduced evapotranspiration (Amundson et al. 1995: Ludwig et al. 2001) and increased nutrient availability (Scholes and Archer 1997; Ludwig et al. 2004a). Although total plant production affects animal biomass, forage quality is of much more importance for understanding herbivore performance and food limitation (Van Soest 1994) and the interplay between forage quality and quantity determines to a large extent the composition of the herbivore assemblage (Prins and Olff 1998; Olff et al. 2002). Two previous studies which compared forage quality under trees and in the open field both report higher forage quality under Acacia (Belsky 1992) and Eucalyptus (Jacskon and Ash 1998) trees. Increased forage quality is probably caused by higher soil nutrient concentrations under tree canopies (Kellman 1979; Belsky et al. 1989; Scholes and Archer 1997). Also water competition and shade could increase forage quality because nutrients taken up by grasses are less diluted due to a lower biomass production.
Currently, large tree cover is decreasing in several African savannas due to high elephant pressure and frequent fires (Eckhardt et al. 2000). In Tarangire National Park (NP) (northern Tanzania) the cover of large trees declined from 20% in 1970, to only 5% in 1996 (Van de Vijver et al. 1999). A recent study in Namibia showed that the number of large trees was reduced by 50% over the last 36 years while the extent of shrubland dramatically increased (Mosugelo et al. 2002). Also in Kruger NP (South Africa) and in the Serengeti-Masai Mara ecosystem (Tanzania and Kenya) the number of large trees in savannas has decreased over the last decades (Ruess and Halter 1990; Eckhardt et al. 2000). Outside protected areas the situation is often even more dramatic, with most of the large trees being removed by local people for production of charcoal (Kituyi et al. 2001; Luoga et al. 2002). Reductions in tree cover could have serious consequences if trees have a positive effect on herbivore food quality and availability.
The objective of this study was to investigate the impact of trees on forage quality and how a reduction in the number of large trees could affect herbivore populations in African savannas. Specifically, we focussed on the impact of the dominant East African savanna tree, Acacia tortilis, on nutrient concentrations, protein content and digestibility of grasses. We included small, large and dead trees in our study to be able to determine how large tree destruction affects forage quality through time. A linear programming model was used to test the hypothesis that forage growing under trees is necessary for the long-term survival of wildebeest, the dominant large herbivore in East African savannas.
Materials and methods
Site description
Data were collected in Tarangire NP (4°S, 37°E, 1,200 m above sea level) which is located at the eastern side of the Great Rift Valley in northern Tanzania and encompasses an area of about 2,600 km2. Mean rainfall is 650 mm/year (Van de Vijver 1999). The wet season is from November until May with most of the rain typically falling during March and April. The Tarangire River runs through the park, and in the dry season this river is the main permanent fresh water supply within the entire 35,000 km2 Masai ecosystem (Prins 1987).
Northern Tarangire NP is in the dry season range of large migratory herds of Burchell’s zebra (Equus burchelli) and wildebeest (Connochaetes taurinus) and to a lesser extent Cape buffalo (Syncerus caffer). Towards the end of the dry season Northern Tarangire has one of the highest concentrations of large herbivores in the world. At the beginning of the wet season wildebeest and zebra leave Tarangire NP to graze on the Simanjiro Plains. During most years both species give birth and lactate on the Simanjiro plains and return to Tarangire NP in the dry season (Voeten and Prins 1999). The park is also famous for its large herds of elephants (Loxodontaafricana) which primarily reside in the park during the dry season and sometimes disperse to surrounding areas in the wet season. The number of large elephants has increased sharply over the last 20 years due to destruction of habitat outside the park which forced more elephants into Tarangire NP.
Two wooded savanna types dominate the park: Acacia savanna, which can be found in the riverine area with lacustrine soils in which A. tortilis is the dominant tree species, and the deciduous savanna, which is concentrated on the ridges and upper slopes on Precambrian well drained red loamy soils (see Van de Vijver et al. 1999). Here, the dominating trees are Combretum and Commiphora species. Most of the herbivores concentrate in the Acacia savanna (Tarangire Conservation Project 1997, Voeten 1999), presumably because of the higher forage quality, so we focused our work on this savanna type. As A. tortilis accounts for 90% of the large trees in this savanna type (Van de Vijver et al. 1999) we focused our study on grass vegetation growing under and around this tree species. Total woody cover, including bushes, is about 20%, and especially the cover of large trees has declined over the last 30 years (Van de Vijver et al. 1999).
Grass sample collection and chemical analyses
A study site of 2 × 2 km was selected with a vegetation which was representative of the Acacia savanna in Tarangire NP. The study site was located between the main entrance of the Tarangire NP and the park headquarters. For this study the same four large trees were used as described in Ludwig et al. (2004a). Trees were selected on the basis that they were separated from other large trees by at least 100 m and 50 m from any bushes or small trees. Trees close to termite hills were avoided. Measurements and calculations by Prins and Van der Jeugd (1993) suggest that these trees are ca. 100 years old. Trees have a canopy diameter between 15 and 25 m. A previous study showed that around large trees, three different vegetation zones of the herbaceous layer can be distinguished, namely: (1) under large tree canopies, (2) just outside tree canopy projections (called “around tree canopies”), and (3) in open patches more than 50 m from any tree (Ludwig et al. 2004a).
Species composition was recorded at peak standing biomass during the early dry season in June 2000 in 20 different 2 × 2-m plots in each of the three different communities. For each plot the cover of all grass species was visually estimated. Nomenclature followed Clayton and Renvoize (1982). Under tree canopies, plots were located in between the tree stem and canopy edge. Plots around tree canopies were selected at twice the distance from the stem, as the edge of the tree crown. For example, if the canopy edge was at 10 m from the trunk the centre of the plot under the canopy was located at 5 m from the trunk and the plot “around canopies” at 20 m from the trunk. Open grassland plots were at least 50 m from any tree.
To analyse grass nutrient concentration, grass samples were collected in the early dry season in June 2000, because this is the time of year when migratory herds of wildebeest and zebra return to Tarangire NP and start grazing at the study site. At each of the three different vegetation zones around large trees, samples of the most abundant grass species were collected. Different species were sampled in the three zones because of differences in species compositions. See Table 1 for species sampled in each zone. Three Cynodon species, Cynodon dactylon, Cynodon nlemfluensis and Cynodon plectostachius, were treated as one group because they are very similar, rarely flower and it is very hard to distinguish between the species without uprooting them and when they are not flowering (see Clayton and Renvoize 1982).
Table 1Average (SD in parentheses, n = 4) vegetation cover, live and dead stems and leaves and leaf/stem ratio of grass species growing under and around canopies of large Acacia tortilis trees and in open grassland patchesLocationSpeciesCover of vegetation at specific zone (%)Live stem (%)Live leaf (%)Dead stem (%)Dead leaf (%)Leaf/stem ratioDataUnder tree canopyPanicum maximum933.1 (5)51.1 (13)4.5 (6)11.3 (4)1.81 (0.73)Cynodon spp.6247.4 (7)42.0 (8)4.4 (2)6.2 (3)0.95 (0.24)Cenchrus ciliaris940.8 (15)28.3 (9)6.8 (3)24.0 (13)1.22 (0.54)Around tree canopyCynodon spp.750.4 (6)25.4 (3)5.4 (3)18.8 (7)0.80 (0.14)Cenchrus ciliaris640.9 (19)27.2 (3)15.4 (10)16.5 (10)0.83 (0.37)Digitaria macroblephera1439.0 (15)25.2 (8)7.9 (15)27.8 (3)0.70 (0.24)Chloris virgata943.7 (7)30.7 (8)9.0 (6)16.6 (6)1.14 (0.12)Urochloa mosambicencis2152.4 (3)34.7 (11)4.9 (5)8.0 (10)0.91 (0.20)Heteropogon contortis1743.8 (6)27.2 (9)15.9 (4)13.1 (3)0.77 (0.25)Open grasslandH. contortis3848.3 (4)32.9 (7)8.4 (5)10.4 (5)0.77 (0.11)Sehima nervosum3650.1 (12)29.2 (9)12.0 (7)8.7 (14)0.62 (0.16)StatisticsadfLocationF2 ,381.766.57**1.861.848.60***Tree (block)F3, 38 1.600.421.180.081.15** P < 0.01, *** P < 0.001aVariance of data was analysed with a general linear model (GLM) with grass species and location (open grassland and under and around canopies) as fixed factors
Grass samples were collected following the “hand plucking method” (Wallis de Vries 1995). Samples were plucked between thumb and backward-bent index finger to simulate large herbivore grazing as closely as possible. One sample of every species was collected within each zone. One sample consisted of between 15 and 25 pickings collected in small mono-specific stands at different spots within the same zone. Samples were dried in the sun and sorted into leaves and stems and live and dead material.
After drying at 70°C for at least 48 hours, live leaves were analysed for total N, P, K, Ca, Mg and N using a modified Kjeldahl procedure with Se as a catalyst (Novozamski et al. 1983). After digestion, N and P concentrations were measured colorimetrically with a continuous flow analyser (Skalar SA-4000; The Netherlands) and K, Ca, Mg and Na were analysed with an atomic absorption spectrophotometer (Varian Spectra AA-600; The Netherlands). Neutral detergent fibre (NDF) was determined according to Goering and Van Soest (1970) and digestibility of organic matter (DOM) according to Tilley and Terry (1963). Crude protein was calculated as 6.25 × total N concentration. DOM, NDF and protein concentration of the vegetation per zone were calculated by multiplying the nutrient concentration in a specific species by its relative abundance within the vegetation.
Dead and smaller trees have a different effect on the understorey vegetation than large trees or open grassland (Ludwig et al. 2004a). To study how large-tree removal affects forage quality through time, grass samples were also collected around dead and smaller A. tortilis trees. Samples of the dominant grass species were collected under bushes, small trees and around dead trees. Well-developed “bushes” of A. tortilis were ca. 4 m high and had no signs of tree or umbrella shape development. “Small trees” had a clear tree form and were about 10 m tall and had started to form an umbrella shape. “Dead trees” were large trees which had died 4–8 years ago. For detailed description of tree stages see Ludwig et al. (2004a). Samples were collected as described above and analysed for protein, NDF and DOM.
Linear model
The problem of having to comply with several different requirements can be analysed with a linear programming model (Belovsky 1978; Voeten 1999). This is an optimization model in which one variable is maximized or minimized, while subjected to different constraints. Here, it is used to study whether herbivores can meet all their nutritional and energy requirements by selecting either food from under or around trees or from open grassland or a combination of food sources. As a basis the model described by Voeten (1999) is used. We used wildebeest as model species because it is the most abundant herbivore in Tarangire NP (Tarangire Conservation Project 1997) and nutrient and energy constraints of this species have partly been described by Murray (1993, 1995). It would be ideal to include more herbivore species but only data for wildebeest are available. Each constraint was formulated as a general linear equation: where C is a constraint value which stands for either nutrient, energy or fibre intake. We formulated minimum requirements for nutrient, protein and energy intake, and a maximum value for fibre intake. Iiis the amount of food consumed by class i; in this study grass leaves from under or around tree canopies or open grassland. The parameter ciconverts Ii into the same unit as C and is based on the nutrient, energy and fibre content measured in the grass leaves of the different zones.
Murray (1995) calculated, from a feeding trial in the Serengeti, northern Tanzania, that wildebeest need an energy intake of 22.32 MJ/day for maintenance. This was based on an average body mass of 143 kg. The metabolic energy of grasses equals the digestible energy multiplied by 0.82 (Van Soest 1994). The digestible energy can be calculated from the DOM multiplied by the gross energy of grass. The energy content of grasses averages 19 MJ/kg DOM (Crampton and Harris 1969), and this number was used for all grass species. Thus the constraint equation for energy intake is: where DOM is the digestibility of organic matter as determined in vegetation. I is the intake rate [kg dry weight (DW)/day] and i stands for the foraging zone.
Digestible protein (DP) requirements at maintenance for ruminants can be calculated as (Voeten 1999): where W stands for metabolic weight (kg). We used an average weight of wildebeest of 143 kg (Murray 1993) which means they need 130 g DP per day for maintenance. DP for tropical grasses can be calculated from crude protein using a formula proposed by Prins (1987):
The second constraint equation used in the model is: For ruminants the daily intake rates are often constrained by rate of digestion and passage through the rumen (Voeten 1999). The digestibility rate of food is often correlated with the cell wall content, measured in the vegetation as NDF (Van Soest 1994). Reid et al. (1988) calculated from a feeding trial of cattle on a C4 grass diet that maximum daily NDF intake can be calculated as:
For wildebeest of 143 kg, the maximum intake is thus 2.76 kg NDF so the third constraint equation is:
In addition, two equations were defined based on requirements of the two most important nutrients for wildebeest as determined by Murray (1995). The constraint equation for maintenance levels of Ca and P are: where P and Ca are the concentrations measured in the vegetation.
Na is not considered in this model because wildebeest can satisfy their daily requirements through drinking water from the Tarangire River (Voeten 1999). The different constraints were used to calculate whether wildebeest can meet all nutritional and energy requirements for maintenance (to maintain a stable body weight) by selecting forage from different foraging zones. As an input value for each of the three zones a weighted average, depending on plant cover, of the dominant grass species was used. Plant cover instead of biomass was used because only plant cover data were available.
Statistical analysis
Percentages of dead and live leaves and stems, nutrient concentrations, NDF and DOM of grass samples were analysed with a general linear model (GLM) with vegetation zone (under and around tree canopies, and open grassland) as fixed factors and trees as a random factor. Differences in NDF, DOM and protein concentrations of grasses from different tree stages (open grassland, bushes and small, large and dead trees) were analysed with a GLM with tree stage as a fixed factor. All data were statistically analysed with SPSS 11.0.
Results
Cynodon species covered 62% of the vegetation under tree canopies (Table 1). The other two abundant species under trees were Panicum maximum and Cenchrus ciliaris. The remaining 20% was covered mainly by herb species. Around tree canopies the vegetation was more species rich with six more or less abundant grass species (see Table 1). In open grassland, the vegetation consisted almost exclusively of the grass species Heteropogon contortis and Sehima nervosum. Percentage of live and dead stem and dead leaves was similar under and outside trees. Percentage of live leaves, however, was higher under trees compared to around trees and open grassland.
Forage quality was much higher under large tree canopies than in open grassland. This was indicated by higher leaf/stem ratios, higher concentrations of protein and DOM and lower NDF concentrations (Table 2, Fig. 1). For example, digestibility of green leaf organic matter (DOM) was highest in Cynodon grasses growing under the canopy where 70% of green leaves was digestible (Table 1) and DOM was lowest in H. contortis growing in open grassland. For NDF a reversed pattern was observed with the lowest values for Cynodon spp. and highest for H. contortis and S. nervosum. Protein contents of grasses were highest under tree canopies and Cynodon spp. and Cenchrus ciliaris showed a higher protein content under than around tree canopies. Forage quality of grasses growing around tree canopies was also higher than in grasses from open field but lower than under canopies. Leaf/stem ratios, protein concentration and DOM were all higher around trees canopies than in open field. P concentrations showed a different pattern: concentrations were higher in grasses growing around canopies than under canopies and in open grassland (Table 1).
Table 2Average (SD in parentheses) of digestibility of organic matter (DOM), neutral detergent fibre (NDF), protein and nutrient concentrations of grass species growing under and around canopies of large A. tortilis trees and in open grassland patchesLocationSpeciesDOM (%)NDF (%)Protein (mg/g)P (mg/g)K (mg/g)Ca (mg/g)Mg (mg/g)DataUnder tree canopyP. maximum65.7 (6.5)70.6 (3.3)141 (19.7)1.77 (0.17)40.6 (2.2)4.12 (0.26)3.25 (0.79)Cynodon spp.70.3 (7.2)61.5 (4.9)165 (8.4)1.80 (0.32)38.4 (2.4)6.91 (0.71)2.44 (0.57)Cenchrus ciliaris59.8 (3.2)70.1 (5.0)137 (5.0)1.74 (0.18)44.8 (3.8)4.34 (2.19)1.95 (0.43)Around tree canopyCynodon spp.65.1 (12.4)66.5 (8.6)127 (26.2)2.38 (0.42)36.1 (11.2)6.70 (2.18)2.58 (0.38)Cenchrus ciliaris58.0 (9.0)71.5 (6.1)106 (15.4)2.43 (0.07)41.9 (7.0)3.30 (0.65)1.87 (0.38)D. macroblephera62.6 (8.0)72.9 (6.2)75 (13.5)2.85 (0.52)38.6 (1.5)3.75 (0.76)2.26 (0.55)Chloris virgata66.8 (5.9)70.4 (4.1)105 (5.0)2.59 (0.61)37.6 (1.8)4.91 (0.30)3.03 (0.45)U. mosambicencis69.1 (5.4)64.8 (3.5)104 (10.3)3.59 (0.78)44.3 (3.9)5.28 (0.56)4.00 (0.40)H. contortis57.0 (4.8)70.2 (3.0)82 (11.8)1.46 (0.13)17.2 (0.5)3.30 (0.3)1.64 (0.18)Open grasslandH. contortis51.7 (2.2)74.0 (2.2)68 (9.3)1.65 (0.19)15.1 (0.7)3.31 (0.31)1.22 (0.15)S. nervosum54.7 (1.0)74.6 (1.0)61 (9.7)1.46 (0.13)12.0 (0.8)4.67 (0.36)1.47 (0.06)StatisticsaLocationF10.4***5.55**49.9***11.7***28.2***1.347.77**Tree (block)F7.08***5.45***1.361.071.360.640.71 ** P < 0.01, *** P < 0.001aVariance of data was analysed with a GLM with grass species and location (open grassland and under and around canopies) as fixed factorsFig. 1Indicators of forage quality of grasses growing under different sized Acacia tortilis trees, dead trees and in open grassland. Mean (+SD) protein, digestibility of organic matter and neutral detergent fibre (NDF) concentrations of green grass leaves. Bars with the same letter are not significantly different (LSD test, P > 0.05)
Protein concentration, NDF and DOM differed significantly between different tree stages (P < 0.05). Protein concentrations were highest under large trees and lowest in open grassland (Fig. 1). Smaller Acacia (bushes and small trees) showed intermediate values. Under dead trees grass protein concentrations were higher than in open grassland but lower than under large trees. DOM percentages showed a similar trend to protein concentrations; under small Acacia trees and bushes DOM of grasses was higher than in open grassland but lower than under large trees. NDF values showed the opposite trend with lowest values under large trees and highest values in open grassland (Fig. 1). NDF values of grasses growing under bushes and small and dead trees were lower than in open grassland but not significantly different from those of grasses growing under large trees. In general, these patterns show that forage quality increased with tree age and size. Under dead trees forage quality was higher than in open grassland but lower than under large trees.
Results from the linear programming model show that by selecting forage from under large tree canopies wildebeest can meet all their energy, nutrient and protein requirements before reaching their maximum intake determined by the grass fibre concentration (Fig. 2). Wildebeest can also satisfy their requirements for nutrients, protein and energy by selecting grass around tree canopies. However, the results of the linear programming model indicate they cannot do so by selecting food exclusively from open grassland. Due to the relatively high fibre content in forage from open grassland the maximum intake for wildebeest is about 3,700 g/day. Due to the low nutrient and protein concentrations in grasses from the open field, this amount is not enough to satisfy all the dietary requirements for wildebeest. All requirements can be satisfied by combining forage from open grassland with either forage from under or around tree canopies. Especially if forage from open grassland is combined with grass from under large tree canopies only a relatively small amount (10–20%) of forage is required from under trees and the rest of the forage can be selected from open grassland (Fig. 2).
Fig. 2Results of a linear programming model, predicting whether wildebeest can meet their daily requirements for energy, nutrients and protein by selecting forage from under tree canopies, around tree canopies, or in open grassland patches. Within this model the minimum daily amount of energy, protein, P and Ca needed by wildebeest is defined. The lines indicate the minimum food intake needed to meet these requirements for a combination of two of the three food sources available. For fibre the maximum food intake is shown. The maximum and minimum intakes rates are calculated using Eqs. 2, 5, 7, 8 and 9. The shaded part indicates all possible combinations of food sources which meet nutrient, energy and protein requirements without exceeding maximum intake rates determined by the fibre content. DW Dry weight
Discussion
Our results show that the forage quality of the herbaceous layer is much higher under trees than in open grassland. Grasses growing under tree canopies contained a lower fibre content and the highest concentrations of protein and Ca and had a higher digestible organic matter content. The higher forage quality under trees is partly caused by the different species which dominate the vegetation under large trees. However, Cynodon spp. growing under trees also had higher protein concentrations and DOM contents than the same species growing around tree canopies. This shows that a higher below-crown forage quality it is not only a species effect but also due to a different environment under trees.
The positive effect of trees on forage quality did not stop at the canopy edge. Grasses around tree canopies still had higher nutrient concentrations and leaf/stem ratios and a higher DOM than the two species dominating open grassland. The grasses we sampled around tree canopies were growing about 7–10 m from the canopy edge. So one mature Acacia tree with a canopy diameter of 15 m can potentially increase forage quality over an area of more than 600 m2.
Our results could have been affected by the fact that we only sampled once. However plant samples taken in 2 previous years during different periods within the season show much higher nutrient concentration in grasses under trees compared to open grassland (Ludwig et al. 2001, 2004a). So it is likely that forage quality is higher under trees throughout the season.
Increased forage quality under savanna trees can be caused by a range of different effects because savanna trees influence the availability of all major resources used by grasses. Trees reduce light availability through shade, often increase soil nutrient concentrations, and compete with grasses for belowground resources, especially water (Belsky 1994; Scholes and Archer 1997; Anderson et al. 2001). Shade alone can already increase forage quality (Cruz et al.1999). For example, two independent studies showed that N concentrations were increased in P. maximum growing under artificial shade (Deinum et al.1996; Durr and Rangel 2000). However, probably most important is the higher soil nutrient availability under savanna trees. In a previous study, under the same Acacia trees, we found that concentrations of all major nutrients were higher under trees compared to open grassland (Ludwig et al. 2004a). Higher soil nutrient concentrations increase plant nutrient concentrations which improve the forage quality. Higher soil nutrient concentrations usually also increase grass productivity which would result in reduced plant nutrient concentrations due to dilution. However, grass productivity under these Acacia trees is mainly limited by water. Previous studies showed that soils under Acacia trees had lower soil moisture contents and soil water potentials than soils beyond the edge of canopies (Ludwig et al. 2003, 2004a). Higher forage quality under these savanna trees is probably caused by a combination of reduced soil moisture and increased nutrient availability.
The results of the linear model show the importance of the higher forage quality from under and around trees for large herbivores. When wildebeest forage only in open grassland, they cannot satisfy all their nutritional and energy requirements to maintain a stable body weight. The grass species growing in open grassland have a high fibre content which limits the maximum daily intake. Due to this limited intake insufficient amounts of protein and P can be extracted. Most of the available data on energy and nutrient requirements originate from agricultural studies and still few data are available for wild herbivores. For our model, we adjusted daily intake requirement for wildebeest from agricultural data in combination with experimental work on wildebeest (Murray 1993). These adjustments could have resulted in some errors in the model. For example the maximum NDF intake used originated from cattle and could be different for wildebeest. Also only one standard value for energy contents of grasses was used because no other data were available. Due to the large differences in forage quality of grasses from under trees compared to the open field, it is unlikely that a small change in model parameters or input values will significantly affect the conclusion that wildebeest need at least some forage from under trees. For example, wildebeest would have to increase their fibre intake by more than 35% to satisfy their protein needs in open grassland, and only if their protein needs were 30% less than assumed in our model could wildebeest satisfy their needs without grazing under or around trees. Another indication that large herbivores would need to forage under trees is that the crude protein concentration is below 7% in grasses from open grassland. At these protein concentrations the digestion rate is severely limited for all herbivores (Van Soest 1994) which suggests that large herbivores cannot survive when foraging from open grassland only. These results show the importance of trees for the functioning of savanna ecosystems and many large grazers probably depend indirectly on large trees for their long-term survival.
Trees are not the only source of spatial heterogeneity in forage quality. For example also termite hills, faeces concentrations and rivers can increase nutrient availability and thus improve forage quality (Grant and Scholes 2006). So in the absence of trees, large herbivores could forage in these “hot spots” to satisfy their nutrient requirements. However, trees cover a much larger part of the landscape than other sources of spatial heterogeneity and are thus particularly important in improving forage quality. In the absence of trees, herbivores can increase forage quality through positive feedbacks of grazing (Augustine and McNaughton 2006). For example through the formation of grazing lawns (McNaughton 1985) However, these positive feedbacks are mainly observed in nutrient-rich savannas and grasslands such as the Serengeti (Grant and Scholes 2006).
Forage quality of grasses growing around dead trees was lower than under large trees but still higher than in open grassland. Grass protein concentrations, for example, were almost twice as high around dead trees as in open grassland. So, forage quality does not dramatically decline immediately after trees die. This might explain why negative effects of tree removal have largely been ignored. In a previous study, we also showed that grass biomass production is higher around dead trees than in open grassland and under large trees due to the lingering positive effect of trees (increased soil nutrient availability persists for some years), combined with the removal of negative effects such as shade and competition for water (Ludwig et al.2004a). Thus, the first impression after trees are cut down/killed is that trees were suppressing grass production.
When the positive effect of higher soil nutrient concentrations around dead trees has disappeared, grass forage quality and productivity will be as currently found in open grassland, where both productivity and quality are lower than under trees that died recently. So only after a time lag of at least 8 years (Ludwig et al. 2004a), when the effect of trees on forage quality has disappeared, does it become clear that tree felling only temporarily increases grass biomass and ultimately reduces forage quality, thereby jeopardising animal productivity. Large trees killed by elephants or human pressure can be replaced by regenerating small trees or bushes; however, their impact on grass quality and availability is different from that of large trees. Bushes tend to reduce grass production (Ludwig et al. 2004a) and have a smaller positive effect on forage quality than large trees. Grass forage quality under the small trees was also still significantly lower than under large trees. The small trees we used for our study were about 20 years old so it will take more than two decades before forage quality will be as good as before clearing. Another problem is that the contradictory effects of different sized trees on grass quality and production can encourage bush-clearing. Increased grass production after large tree removal suggests that trees negatively affect grass production. After clearing the large trees, regenerating bushes start to repress grass production which again encourages removal of all woody species. Bush-clearing is, however, ultimately counterproductive because it will result in savannas with few or no large trees and thus a much lower forage quality.
Over the last 20 years, numbers of elephants have increased in several NPs in Africa (Van de Vijver et al.1999; Eckhardt et al.2000; Skarpe et al.2004). This increase can have serious effects on other large herbivores. For example, the increase in the number of African elephants in Kruger NP which took place over the last 50 years, and the consequent reduction in the number of large trees (Eckhardt et al.2000) could have caused the demise of rare selective antelopes such as the roan. Roan largely depend on forage from P. maximum (Heitkonig 1994), a grass species which dominates the vegetation under trees in southern African savannas (Ruess and Halter 1990; Scholes and Walker 1993; Scholes and Archer 1997; Eckhardt et al.2000). As the effects of tree removal only become clear years after trees die, impacts of increased elephant pressure might not be clear at the moment but could become a serious problem in the near future.
In conclusion, our results presented here show that savanna trees have an important role in affecting the quality of forage available for wildebeest in Tarangire NP. Some recent work shows that forage quality is also higher under trees in other African savannas and more future work should show how general our results are (Treydte et al.2007). As trees increase food quality for herbivores the reduction in the number of large trees observed in savannas across Africa (Van de Vijver et al.1999; Eckhardt et al.2000; Mosugelo et al.2002) can have serious consequences for the survival of large herbivores. These negative effects of tree removal are probably usually not recognised because forage quality only slowly reduces after trees die. However, better protection of large trees in savanna ecosystems could be necessary to sustain current numbers of large herbivores.

wildebeest
acacia tortilis
nutrients
plant–animal interactions
tree–grass interactions