Systematic review of effects on biodiversity from oil palm production

Objective of the review

Search strategy

Study inclusion criteria

In collaboration with stakeholders, a set of inclusion criteria was developed. Studies that had data about relevant subject, exposure and outcome, together with a valid comparator were included if they fulfilled the quality criteria discussed in the section on study quality assessment.

Studies related to the primary study question were included according to the following criteria:

For the secondary study question “Is there a difference in the impact on biodiversity between industrial plantations and smallholder plantations per volume of fuel produced?”, location, subjects and outcome were the same, but the types of exposure and comparator were different:

For the secondary study question “Do different standards related to oil palm, jatropha, and soybean mitigate the negative impacts?” the following criteria were used:

Articles were assessed for relevance first by title, as well as keywords if these were available, then by abstract, and finally, by full text. If the inclusion of an article was in doubt in either of the first two stages, the article was included and the suitability determined at a later stage.

To assess the consistency in the use of inclusion criteria a kappa test was performed. Two reviewers applied the inclusion criteria to a random set of 108 articles at the abstract filter stage. The kappa statistic was calculated to measure the level of agreement between the reviewers. A score of 0.704 was achieved, which indicates substantial strength of agreement [14].

Potential effect modifiers and study quality assessment

Studies do not happen in a vacuum and hence, a number of variables that have the potential to affect study outcomes were recorded when available. The focus was on variables that can influence reliability and generalization of the findings. The following variables were recorded:

Data extraction and synthesis

Originally we planned to categorize the data for the analyses using the following five categories: Mammals, birds, amphibians and reptiles, invertebrates, and plants. However, as there were relatively few studies overall, the data were not categorized in this way for the analysis.

There were enough data on species richness (i.e. number of species) and abundance (i.e. overall number of individuals or occurrences) to perform meta-analysis. The purpose of meta-analysis is to quantitatively summarize the results of individual studies using specific statistical methods [16]. The concept at the heart of a meta-analysis is the effect size, which is a statistical measure that portrays the magnitude of which given effect is present in a sample. It makes it possible to determine whether the overall effect is greater than expected by chance [17]. There are several effect size estimates that measure the standardized mean difference between two samples and are thus suitable for species richness and abundance data. Hedges’ d was chosen because it corrects for a small sample size [18] (for the equations used in this section see the Additional file 2). The heterogeneity of the effect sizes was estimated using the Q-statistic. The I ² -statistic was used to describe the proportion of the observed variance that reflects real differences in effect sizes [19].

To perform a quantitative meta-analysis on species richness and abundance the estimates of mean species richness and abundance, the corresponding estimates of standard deviations, and sample sizes were tabulated. If the estimate of standard deviation was not provided it was calculated from the estimate of standard error and sample size. In some cases the estimates of mean and standard deviation or standard error were measured from the published figures. The measurements were made by one person, so any measurement error is expected to be consistent. In cases where the estimates of mean and standard deviation were not provided but a t-statistic was, this was used to calculate Hedges’ d by transforming the t-statistic first to Hedges’ g and the g then to Hedges’ d [18].

The effect sizes were analyzed using a random effects model. This was chosen because the subject groups and data collection methods varied between the studies and hence, there may be real differences among effect sizes of studies on different subjects [19, 20]. Different taxa and taxa that were collected using different methods within the same study were treated as independent samples. Also, data that had significant differences between sampling occasions [21, 22] were included as independent samples. Studies by different authors from the same location, regardless of the taxa studied, were treated as separate cases. Although originally we wanted to include explanatory variables into the model, this was not feasible owing to the small number of studies that met the inclusion criteria and hence, only the average effect sizes were estimated, along with 95% bias-corrected confidence intervals. The bias-corrected confidence intervals were chosen because of the relatively small sample sizes. The analyses were performed using MetaWin 2.1 release 5.10 [23].

One of the well-known problems associated with meta-analysis is that studies with higher effects are more likely to be published; relying only on results published in academic journals can potentially lead to misleading conclusions about the effect [19]. To address this problem, an extensive search was performed to uncover “grey” (variously defined, but here we mean conference papers, book chapters, reports that are no part of established Series, etc.) and unpublished literature. Another reported source of publication bias is that non-significant results may not be published at all. We did not test for publication bias for two reasons. First, a variety of responses are expected in ecological studies dealing with different taxa and we therefore did not expect suppression by Editors of studies of smaller effects or non-significant results. Secondly, existing statistical tests require reasonable numbers of cases and dispersion in sample sizes, two conditions which the meta-analyses we performed do not fully meet.

A variety of different methods used for examining changes in species composition makes it difficult quantitatively to assess the effects of habitat modification on species composition. Hence, to have a standardized measure to assess changes in species composition, a simple averaging method following Nichols et al. [24] was used to calculate the mean change in the number of shared species between forest and oil palm habitats, standardized by the total number of species recorded in forest. In addition to the mean response, 95% confidence intervals were calculated. The value was considered significant when the confidence interval did not include one. Primary and secondary forest data were combined in the analysis. When both primary and secondary forests were sampled, only primary forest data were used. The analysis was performed using SPSS version 17.0 [25].

Review statistics

The searches returned 9143 articles after duplicate removal (Figure 1). Of these articles, approximately 13 per cent had a relevant title and keywords and were therefore examined further. At the abstract-assessment stage 9.8 per cent of articles satisfied the inclusion criteria and were read in full. Of those, 25 articles (21 per cent of those read in full) reported single studies with an appropriate comparator (Additional file 3). All of the selected studies belonged to category III (Table 2), which meant that none were excluded on the grounds of weak methodology.

Description of studies

Source

All 25 articles included in the review were published in peer-reviewed journals. Only three articles were published before 2000, and the majority of the articles were published after 2005 (Figure 2). The figure for 2012 is not fully representative of the whole year because the search was conducted on articles published by the bibliographic databases up to November 2012.

Context of the studies

Study location

Most of the studies were conducted in Asia: 20 of them in Malaysia. Of the studies conducted in Malaysia, 10 were from one State Sabah. There were only single studies from other tropical regions, Africa (Ghana), Oceania (Papua New Guinea), and Latin America (Dominican Republic).

Study comparator

Only studies of oil palm were retrieved using our search strategy. Typically, oil palm plantations were compared with forest, either primary (n = 20) or secondary forest (n = 14). All except one study were site comparisons. None of the studies were experimental. Only one of the studies examined outcomes before and after forest conversion.

Study outcomes

The 25 studies reported a total of 58 outcomes. All studies had examined faunal species richness/diversity (n = 25); almost all had examined abundance (n = 21), but only 12 had looked at species composition. Almost two thirds of them studied invertebrates (Figure 3).

The age and size of the plantations

The age of the plantations was reported in 15 studies; two additional studies mentioned that the plantation was ‘mature’. The age of the plantations varied from one year to more than 25 years. Nine studies collected data from plantations aged less than ten years, eight studies collected data from plantations aged ten years or more, including the study by Azhar et al. [26] that collected data from oil palm plantations of varying ages. Only ten studies mentioned plantation area, which ranged from 36 to 16000 hectares, with the majority of studies having studied plantations of several thousand hectares (Figure 4).

Quantitative synthesis

Species richness

We found 11 studies that provided suitable data for conducting meta-analysis to compare species richness in oil palm plantations and primary forest, and 8 whose data could be used for comparison between oil palm plantations and secondary forests. Owing to the limited amount of suitable data we focused on overall effects. Although examining only overall effects can mask differences in responses between taxa, it was done out of necessity to retain power in the analyses. As primary and secondary forests can be biologically very different environments, the analyses were done separately.

There was relatively uniform negative response as shown in the forest plots of differences in species richness between oil palm plantation and either primary or secondary forest (Figures 5 and 6). The estimated mean effect size was significantly different from zero (primary forest: E++ = -1.41, 95% bias-corrected CI -2.06 to -0.90; secondary forest: E++ = -3.02, 95% bias-corrected CI -4.42 to -1.84) indicating that oil palm plantations have fewer species than either primary or secondary forest. As the effect sizes got larger, the confidence intervals were also wider.

There was heterogeneity in the effects when the species richness of plantation was compared to that of primary forest (Q = 29.76, p = 0.02), but not when the comparison was between plantation and secondary forest (Q = 16.19, p = 0.24). The I ² index indicated that 43% of the variance considering the effects regarding plantations and primary forests reflects real differences in the effect sizes. Correlations between effect and sample sizes were not significant (Spearman’s rank correlation, p > 0.05) for either primary or secondary forest implying that larger effects in one direction were not reported more often than other effects, but at low samples sizes the power of the correlation is rather low [19].

Abundance

There was more dispersion in the direction of effect sizes of abundances (i.e. the overall number of individuals or occurrences) than of species richness and the mean effect size was not significantly different from zero for the comparison of an oil palm plantation to either primary forest (E++ = -0.92, 95% bias-corrected CI -2.03 to 0.01) (Figure 7) or secondary forest (E++ = -0.21, 95% bias-corrected CI -1.58 to 0.75) (Figure 8). However, it is important to note that the results for the secondary forests were based on only four independent studies, and that owing to the limitations in data available, we aggregated all taxa in these analyses. As with species richness, larger effect sizes had larger confidence intervals.

There was heterogeneity in the effect sizes when the abundance of plantations was compared with primary forest (Q = 31.88, p = 0.02) as well as with a secondary forest (Q = 19.35, p = 0.01). The I ² index indicated that 47% of the variance considering the effects regarding plantations and primary forests reflects real differences in the effect sizes. The figure was 59% when faunal abundance of secondary forests and plantations are compared. Correlations between effect and sample sizes were not significant for either primary or secondary forest (Spearman’s rank correlation, p > 0.05).

Species composition

The similarity of species composition was statistically assessed in 12 of the original studies while a further 11 studies provided some information about species composition (Tables 4 and 5). Species composition differed between forest and oil palm plantation areas in all except one of the 23 studies. In most of the studies that had statistically assessed the difference, the similarity between plantation and forest areas was either low or zero. However, the statistical methods used differed between the studies and results are therefore not directly comparable.

Authors	Year published	Taxonomic group	Similarity between primary forest and plantation	Similarity between secondary forest and plantation	Statistics used	Changes in communities between forest and plantation	Notes on similarity	Causes
Invertebrates
Brühl & Eltz [36]	2010	Ground-dwelling ants	-	-	-	Yes	Communities of plantations dominated by a small number of, partly invasive, non-forest taxa. Highly impoverished in regard to forest taxa.	Absence of leaf litter. Hot and dry conditions possibly prevent colony establishment and reduce survival.
Chang et al. [27]	1997	Mosquitoes	100%	-	-	No	Lower abundances but same species composition.	na
Chey [31]	2006	Moths	0.278		Preston’s coefficient of faunal resemblance	Yes	Noctuid and arctiid species dominated the assemblages.	Low floristic diversity. Lichens and other host plants. Open habitat (many noctuid and arctiid species favor open habitat).
Chey [31]	2006	Moths	0.228
Chey [31]	2006	Moths	0.970
Chung et al. [21]	2000	Subterra-nean, understorey and arboreal beetles	-	-	Detrended Correspondence Analysis and Canonical Correspondence Analysis	Yes	Species composition significantly different between sites (primary forest, secondary forest and oil palm). A few species dominated the assemblage at the plantation site.	The amount of litter, tree and sapling densities, and plant species richness.
Davis & Philips [22]	2005	Dung beetles	22.5%	-	Steinhaus similarity coefficient; Persentage disagreement distance measure; Cluster analysis and ordination	Yes	Similarity between both forest types and plantation.	Physiognomic differences.
Fayle et al. [42]	2010	Ants (canopy)	S: 0.191, C: 0.301	-	Sørenson’s classic similarity index; Chao’s incidence-based measure with a correction for unseen species	Yes	Only a small proportion of forest ant species were present in oil palm plantation. Non-native species were much more widespread.	Temperature nearly significant factor ( P = 0.073). Simplification of the canopy structure. Competitive interactions.
Fayle et al. [42]	2010	Ants (ferns)	S: 0.056, C: 0.070	-	Sørenson’s classic similarity index; Chao’s incidence-based measure with a correction for unseen species	Yes	Only a small proportion of forest ant species were present in oil palm plantation. Non-native species were much more widespread.	Competitive interactions.
Fayle et al. [42]	2010	Ants (leaf-litter)	S: 0.213, C: 0.555	-	Sørenson’s classic similarity index; Chao’s incidence-based measure with a correction for unseen species	Yes	Only a small proportion of forest ant species were present in oil palm plantation. Non-native species were much more widespread.	Temperature. Hotter and drier environment. Competitive interactions.
Hashim et al. [41]	2010	Ants	-	-	-	Yes	Four species found in the plantation were absent from mangrove forest and two species found in the mangrove were absent from the plantation.	na
Hassall et al. [35]	2006	Terrestrial isopods	-	-	-	Yes		na
Liow et al. [43]	2001	Bees	-	-	Cluster analysis and canonical correspondence analysis	Yes	Families Halictidae and Anthophoridae were more commonly caught in oil palm plantation.	The occurence of families Halictidae and Anthophoridae were correlated with higher temperatures and light intensity, lower humidity levels and greater flowering intensities.
Lucey & Hill [32]	2012	Ants	-	-	Non-metric multidimensional scaling	Yes	NMDS differentiated between the habitats.	Air and soil temperature.
Lucey & Hill [32]	2012	Butterflies	-	-	Non-metric multidimensional scaling	Yes	Two distinct clusters, one for forest and one for plantation.	Air and soil temperature.
Room	1975	Ground foraging ants	25.0%	-	Percentage similarity expressed as 100 × [(2 × number of occurences common to both)/(sum of occurences present in each)]	Yes	Only a small proportion of forest ant species were present in oil palm plantation. Non-native species were much more widespread.	na
Vaessen et al. [33]	2011	Termites	-	-	-	Yes	The assemblage dominated by Schedorhinotermes.	Decrease in the amount of dead wood.
Vertebrates
Aratrakorn et al. [45]	2006	Birds	-	-	-	Yes	Plantations dominated by few species. 60% of the species recorded only in the forest, 3% only in the oil palm plantation. Species recorded only in the forest had significantly smaller ranges. Species that were recorded in both forest and plantations had smaller body size than species recorded only in forest.	na
Bernard et al. [34]	2009	Non-volant small mammals	12.0%	-	Proportional difference calculated following a formula by Thiollay (1992); a hierarchical cluster analysis	Yes	Both forest types (primary and secondary) combined. Oil palm plantations may act as an effective barrier to the dispersal of small mammals.	na
Danielsen & Heegaard	1995	Birds	38.7%	-	Proportional difference calculated following a formula by Thiollay (1992)	Yes	Widespread, generalist, and common species much more abundant in plantations than in the primary forest.	Plantation age, proximity to forest, microhabitat structure, and level of human disturbance.
Danielsen & Heegaard	1995	Primates	0.0%	-	Proportional difference	Yes		na
Danielsen & Heegaard	1995	Squirrels and tree-shrews	0.0%	-	Proportional difference	Yes	No squirrels or tree-shrews observed in the plantation.	na
Danielsen & Heegaard	1995	Bats	13.0%	-	Proportional difference	Yes	Insectivorous bats appear to be more susceptible to conversion than frugivores/nectarivors.	na
Edwards et al.	2010	Birds	10.0%		Analysis of Similarity	Yes		na
Fukuda et al. [48]	2009	Bats	-	-	-	Yes	Certain species absent in the oil palm plantation: Two frugivorous species were not recorded at all, only two insectivorous species recorded.	The absent frugivorous species rarely use agricultural lands for feeding.
Gillespie et al. [39]	2012	Amphibians	0.592 (p = 0.0002)	-	Analysis of Similarity between all forest transects and plantation and non-forest transects combined.	Yes	The assemblages reflect the strong affinities of certain species with particular habitat types. Plantation assemblages dominated by terrestrial, non-endemic, generalist species.	Absence of suitable microhabitats. The simple structure and open canopy of plantations results in greater temperature flux between day and night, increased evaporation rates and lower humidity.
Glor et al.	2001	Lizards	-	-	-	Yes		Microhabitat availability in regard to, at least, two species (grass-bush anole and Cochran's dwarf gecko). Oil palm plantation lacks the perch availability and understory microhabitat of natural forest.
Peh et al.	2005, 2006	Birds	-	-	Multiresponse permutation procedure	Yes	Forest species constituted only 26% of the total individuals observed in plantation. Nearby primary forest may act as a source habitat.	Simplification of the vertical vegetational structure.
Juliani	2010	Bats	-	-	-	Yes	Almost all species that were found in the oil palm plantation can be classified as common species in disturbed areas.	na
Sheldon et al. [37]	2010	Birds	-	-	-	Yes	Most species in oil palm plantation were open country and scrub species that are common throughout Borneo.	Simple botanical structure.

*The causes marked bold were statistically significant.

Author	Year published	Taxonomic group	Similarity between logged peat forest and plantation	Similarity between logged peat forest and smallholdings	Statistics used	Changes in communities between forest and plantation	Notes on similarity	Causes
Azhar et al. [26]	2011	Birds	21.40%	19.10%	Analysis of similarity, Similarity percentage procedure	Yes	Oil palm management regimes had a similar species composition but both differed from the forest. The bird community in oil palm consisted of non-forest resident, forest-dependent, migratory, and wetland species.	Extensive canopy cover which in turn may suppress ground layer vegetation that can provide refuge from predators and provide food sources.

*The causes marked bold were statistically significant.

To have comparable results, a mean of shared species between oil palm plantation and forest was assessed. There were 10 studies on invertebrates and 9 studies on vertebrates that provided suitable data for the comparison. On average only 29% of the invertebrate species and 22% of the vertebrate species were shared between oil palm plantation and forest after the values were standardized (Table 6, Figure 9). This represents significant change in community composition for both invertebrates and vertebrates.

Authors	Year published	Taxonomic group	Forest species	Plantation species	Number of shared species	Proportion of species remaining
Invertebrates
Brühl	2001	Ground-dwelling ants	31	23	14	0.45
Chang et al. [27]	1997	Mosquitoes	6	6	6	1.00
Chey [31]	2006	Moths	75	85	28	0.37
Chey [31]	2006	Moths	133	73	28	0.21
Chey [31]	2006	Moths	78	90	11	0.14
Davis & Philips [22]	2005	Dung beetles	25	20	8	0.32
Fayle et al. [42]	2010	Ants (canopy)	120	58	17	0.14
Fayle et al. [42]	2010	Ants (ferns)	36	35	2	0.06
Fayle et al. [42]	2010	Ants (leaf-litter)	216	56	29	0.13
Hashim et al. [41]	2010	Ants	5	7	3	0.60
Hassall et al. [35]	2006	Terrestrial isopods	12	4	0	0.00
Koh & Wilcove [28]	2008	Butterflies	69	15	12	0.17
Room	1975	Ground foraging ants	49	29	11	0.22
Vaessen et al. [33]	2011	Termites	11	6	2	0.18
Mean						0.29
SD						0.26
n						14
95% CI						0.14
Vertebrates
Aratrakorn et al. [45]	2006	Birds	108	41	21	0.19
Bernard et al. [34]	2009	Non-volant small mammals	6	1	0	0.00
Danielsen & Heegaard	1995	Primates	5	1	0	0.00
Danielsen & Heegaard	1995	Bats	8	1	1	0.13
Fukuda et al. [48]	2009	Bats	19	5	4	0.21
Gillespie et al. [39]	2012	Amphibians	21	12	10	0.48
Glor et al.	2001	Lizards	11	5	4	0.36
Juliani	2010	Bats	9	7	3	0.33
Peh et al.	2005, 2006	Birds	159	40	36	0.23
Azhar et al. [26]	2011	Birds	194	55	49	0.25
Mean						0.22
SD						0.15
n						10
95% CI						0.09

Narrative synthesis

Evidence of impact

Although the number of studies that met the inclusion criteria was small relative to the amount of literature broadly related to the review topic, the evidence on species richness and community similarity from the included studies showed clearly that oil palm plantations have reduced species richness compared with primary and secondary forests, and the composition of species assemblage changes significantly after forest conversion to oil palm plantation. Species-specific responses would be expected to vary, but based on the studies included in the review, regardless of the taxa, forest specialists do not, in general, succeed in oil palm plantations. The findings are consistent with previous reviews that have addressed similar questions [5, 28, 52, 53].

With respect to abundance, responses appear to vary depending on species and there is no clear overall effect in one direction. When the abundance results are considered in the light of the results on species richness and similarity, it appears that certain invertebrate species, e.g. generalist species, increase in abundance after forest conversion whereas others decline. However, it is possible that the responses may differ for vertebrates, as none of the studies in the meta-analysis looked at abundance of vertebrate taxa in forest compared with plantation.

Reasons for variation in impact

The variation in effect sizes observed in the meta-analysis most likely reflects different ecological requirements of different taxa and different species within these taxa. Part of the variance in the effect sizes was due to real differences between taxa rather than general heterogeneity, but the small number of studies included in the analyses did not warrant further exploration, mainly because the cases could not be categorized based on a taxon.

Both temporal and spatial aspects of sampling can create variation in effect sizes, which is why the importance of scale has been emphasized in biodiversity studies [51]. As none of the studies addressed biodiversity changes at landscape level, scale-dependent variation in effect sizes could not be evaluated. Variation in impacts due to seasonality could not be evaluated because the available evidence was based on short term data collection.

The small number of studies did not allow us to conduct quantitative examination of the importance of environmental variables, or variables related to plantation management, such as clearing of ground vegetation or type of plantation ownership (smallholdings versus industrial estates). However, there was an indication that both types of variables had some effect [21, 26, 35, 42, 43, 45] and probably contribute to variation in the effect sizes, as they are most unlikely to be constant from one area to another, or even constant temporally within the same area (for example, because management practices can differ between plantations).

There are also natural processes such as competition and predation that can influence the results and create variation. Competitive interactions were mentioned, though not analysed, in one of the studies [42] but in general the influence of competition and predation were not reported.

Review limitations

This review was based on only one crop, oil palm, with the majority of studies conducted in Malaysia and almost half of the studies in one Malaysian State. We would therefore not want to generalize our findings outside South East Asia.

When biodiversity is compared across natural and human-modified landscapes, there are many factors that can limit the generality of conclusions. Variability is an inherent component of biological systems, and human actions in the studied area as well as in the surrounding landscape can add further variability. One way to account for the variability is to include replication in the study design. Unfortunately, the majority of the studies included in the review included insufficient reporting of study conditions and details, or were poorly replicated or pseudo-replicated, which is common for biodiversity studies [54]. Although it is assumed that site comparison studies pair sites that share common attributes, this is not necessarily the case in practice. For example, only a few studies reported on the type of surrounding landscape or on the original vegetation. A number of unreported factors could therefore have contributed to the true effect sizes.

One significant limitation of the review is the lack of landscape level comparisons. Although comparing production areas with forest provides information of the extent of losses at the management unit level, it does not provide information about whether there is a loss in biodiversity at the landscape level. A landscape level approach would be required to incorporate differences between different landscape mosaics as well as their historical backgrounds, into the analysis.

The 25 papers identified in this review compared oil palm plantations with forest. However for us to understand the differences between management systems and the link between management practices and biodiversity, we also need studies that make further comparisons between differently-managed areas. In this review such stratification was not possible because of the dearth of information. To move beyond comparing forest ecosystem with oil palm plantation, there is a need to conduct a robust impact evaluation of differently-managed areas.

The lack of information also prevented analysis of species or taxa-specific responses which is a limitation of the current review. We combined different taxa in the analyses out of necessity, but can recognized that this can mask responses that are specific to certain groups or taxa. As metrics of biodiversity, species richness and abundance suffer from a similar kind of blindness as they consider all the species and individuals to be equal. The inclusion of community similarity in the review alleviates this limitation to some extent.

Publication bias cannot be wholly discounted, even though there are grounds to assume that it is not a significant problem for this body of literature. Grey and unpublished literature was extensively searched in several languages. Correlations between sample sizes and effects were not significant. Finally, considering the nature of the subject, non-significant findings have the same value as significant ones.

Potential implications for biodiversity conservation, policy, and plantation management

The available evidence suggests that oil palm plantations support lower species richness than primary or secondary forest. Also, forest conversion to oil palm plantation leads to significant changes in community composition, which indicates that oil palm plantations are not suitable habitats for the majority of forest species. Unfortunately, very little information was available about the impacts of smallholder plantations or different standards, which makes it difficult to evaluate their usefulness.

Potential implications for research

The review identified several knowledge gaps about the impacts of biofuel crop cultivation on biodiversity and ecosystem function:

To provide a sound evidence base for land-use management decisions, future studies should pay careful attention to study designs, for example by defining the sampling population of land-uses and then using stratified randomization to select study sites, as well as ensuring that seasonality effects are taken into account, and that there are enough replicates. Methodologies should be shared across plantations, users and experiments to identify groups for future monitoring and to make use of crowdsourced identification (e.g. Ispot [55]).

Finally, there are a number of recommendations for authors and publishers that relate to the reporting of biodiversity studies. First, descriptions of methods should be more detailed, including exact explanations for site selection, and descriptions of plantation sizes, ages and management histories. Failure to include such basic information precludes subsequent analysis, and lowers the value of such studies for guiding policy. Second, details of management practices are needed, particularly whether the plantation is certified, and details about which standards are adhered to within the plantation. Finally, crop yields in plantations under different management regimes should be reported to facilitate comparisons that can support policy- and decision-making.