Open Access

Systematic review of effects on biodiversity from oil palm production

  • Sini Savilaakso1Email author,
  • Claude Garcia2, 5,
  • John Garcia-Ulloa2,
  • Jaboury Ghazoul2,
  • Martha Groom3, 4,
  • Manuel R Guariguata1,
  • Yves Laumonier1, 5,
  • Robert Nasi1,
  • Gillian Petrokofsky6,
  • Jake Snaddon6 and
  • Michal Zrust7
Environmental EvidenceThe official journal of the Collaboration for Environmental Evidence20143:4

DOI: 10.1186/2047-2382-3-4

Received: 12 September 2013

Accepted: 27 January 2014

Published: 25 February 2014

Abstract

Background

During the past decade there has been a growing interest in bioenergy, driven by concerns about global climate change, growing energy demand, and depleting fossil fuel reserves. The predicted rise in biofuel demand makes it important to understand the potential consequences of expanding biofuel cultivation.

A systematic review was conducted on the biodiversity impacts of three first-generation biofuel crops (oil palm, soybean, and jatropha) in the tropics. The study focused on the impacts on species richness, abundance (total number of individuals or occurrences), community composition, and ecosystem functions related to species richness and community composition.

Methods

Literature was searched using an a priori protocol. Owing to a lack of available studies of biodiversity impacts from soybean and jatropha that met the inclusion criteria set out in the systematic review protocol, all analyses focused on oil palm. The impacts of oil palm cultivation on species richness, abundance, and community similarity were summarized quantitatively; other results were summarized narratively.

Results

The searches returned 9143 articles after duplicate removal of which 25 met the published inclusion criteria and were therefore accepted for the final review. Twenty of them had been conducted in Malaysia and two thirds were on arthropods.

Overall, oil palm plantations had reduced species richness compared with primary and secondary forests, and the composition of species assemblages changed significantly after forest conversion to oil palm plantation. Abundance showed species-specific responses and hence, the overall abundance was not significantly different between plantations and forest areas. Only one study reported how different production systems (smallholdings vs. industrial estates) affect biodiversity. No studies that examined the effects on ecosystem functions of reduced species richness or changes in community composition met the inclusion criteria. Neither were there studies that reported how areas managed under different standards (e.g. different certification systems) affect biodiversity and ecosystem function.

Conclusions

Our review suggests 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. Effects of different production systems on biodiversity and ecosystem function are clear knowledge gaps that should be addressed in future research.

Trial registration

CEE10-013

Keywords

Land use change Mitigation Oil palm Species diversity Tropical forest

Background

Over the last decade there has been a growing interest in bioenergy, especially biofuels, that has been driven by concerns about global climate change, increasing energy demand, reducing dependence on fossil fuel [1]. Energy derived from plant material, such as sugarcane and oil palm, offers, at least in theory, a promising way to answer energy demand without increasing greenhouse gas (GHG) emissions. In addition, biofuel production can create additional income for the rural poor and advance economic development [2].

Nevertheless, biofuel based opportunities do not come without concerns. Direct or indirect land use change resulting from expansion of biofuel cultivation can cause deforestation and destroy natural habitats [3, 4], which in turn may lead to the loss of biodiversity [5, 6]. Reduced biodiversity may have further negative impacts on ecosystem functions [7].

To respond to the concerns about potential negative social and environmental impacts, several voluntary standards have emerged since the beginning of the millennium. The most prominent have emerged from the Roundtable on Sustainable Palm Oil (RSPO) [8], which was formally established in 2004, the Roundtable on Responsible Soy Association (RRSA) in 2006 [9], and the Roundtable on Sustainable Biofuels (RSB) [10] in 2007. There have also been legislative efforts (e.g. Directive 2009/28/EC of the European Parliament and of the Council) to ensure that the production of imported is considered sustainable. However, there have been concerns that the standards are not effective enough to reduce the threat biofuel production poses to tropical forest ecosystems [11].

Currently palm oil and soybean are produced mainly for food, and thus cultivation for biofuel production has contributed little to the land-use change patterns for these crops [1, 6]. Nevertheless, biofuel production has been predicted to grow [12] and it is important to know what the potential consequences of expanding biofuel cultivation are for biodiversity and biodiversity-related ecosystem functions, and to understand how well the standards in their current form might help to mitigate those impacts.

Objective of the review

The purpose of this review was to assess objectively the current state of knowledge of the impact of three first-generation biofuel crops (oil palm, soybean, and jatropha) on biodiversity in the tropics. The focus was on the direct impacts of forest conversion for crop plantations (resulting in forest fragmentation and deforestation) on species richness, abundance (i.e. overall number of individuals or occurrences) and community composition, and on ecosystem functions related to biodiversity (such as pollination, seed dispersal, biocontrol, nutrient cycling, soil fertility, decomposition). In addition to impacts, different standards related to oil palm, jatropha, and soybean were assessed for their potential to mitigate the impacts. The specific study questions were:
  • Does cultivation of oil palm, soybean, and jatropha in the tropics lead to the loss of biodiversity and ecosystem functions due to deforestation and fragmentation?

  • Is there a difference in the impacts on biodiversity between industrial plantations and smallholder plantations per volume of fuel produced?

  • Do different standards related to oil palm, jatropha and soybean mitigate the negative impacts?

Methods

Search strategy

Design of review

An a priori protocol was established, peer reviewed and posted on the website of the Collaboration for Environmental Evidence (CEE) after acceptance by CEE [13]. The protocol was followed with one change: the secondary study question on standards was revised after publication of the protocol and is presented in this review in the form used.

Search sources

The original literature search was conducted between May and November 2011 and updated between October and November 2012 to retrieve articles published after November 2011. The search included academic literature databases, internet search engines, as well as websites of specialist organizations. In addition, bibliographies of articles included in the review and previously published reviews were checked for references. The following is the full list of sources searched:

Literature databases

  • Biofuels abstracts database by CAB

  • Directory of Open Access Journals

  • Web of Science

Internet search engines

Websites of specialist organizations

The internet search engines typically returned several thousand results. Therefore, the searches were restricted to the first fifty hits and links to potentially relevant material were followed only once from the original hit. At the websites of specialist organizations, the search was limited to the publications section of the website if there was one. At the website of the European Biofuels Technology Platform the search was restricted to sustainability articles.

Search terms and languages

Search strings were created using three categories (exposure, location, and outcome) with Boolean operators AND between categories and OR within categories (Table 1). No specific search terms were used for the study population, i.e. faunal and floral species, as they are inherent in the outcome category. A wildcard character, i.e. the asterisk, was used in the location category to include alternative word endings. When the search string could not be used in its complete form, combinations of the search terms were used so that one term from each three categories was included, e.g. oil palm AND tropic* AND species richness. Owing to the limitations of the search engine, two search strings were used for the Directory of Open Access Journals: (Oil palm OR jatropha OR soybean) AND tropic* and (Oil palm OR jatropha OR soybean) AND tropical. Similarly, only terms Oil palm OR jatropha OR soybean were used at the website of Forest Trends –organization owing to the limitation on number of words imposed by the search engine. The search terms were also translated into French, Spanish, German, Swedish, and Finnish (Additional file 1) and searches conducted using the same logic.
Table 1

Search terms in different categories

Exposure

Location

Outcome

Oil palm

 

Species diversity

Soybean

Tropic*

Species richness

Jatropha

 

Species abundance

  

Species similarity

  

Species composition

  

Community composition

  

Deforestation

  

Land use change

  

Fragmentation

  

Habitat loss

  

Connectivity

  

Functional diversity

  

Ecosystem

  

Displacement

*Denotes a wildcard character that was used to include alternative word endings.

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:

  • Geographical location: Study area within the tropics (23.438°S to 23.438°N).

  • Relevant subject(s): Faunal and floral species.

  • Type of exposure: Conversion of the land to cultivate oil palm, soybean, and jatropha for any purpose.

  • Type of comparator: Other land use or land cover (primary forest, logged-over forest, secondary forest (i.e. regrowth forest), scrubland, grassland, cropland). Both before-after and site comparison studies were accepted.

  • Types of outcome: Change in species richness, abundance (the overall number of individuals or occurrences), community composition, and ecosystem functions (pollination, seed dispersal, biocontrol, soil processes).

  • Types of study: Qualitative and quantitative primary studies as well as descriptive studies and reports.

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:

  • Type of exposure: Conversion of the land to industrial plantations for the cultivation of biofuel crops

  • Type of comparator: Smallholder plantations

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

  • Relevant subject(s): Faunal and floral species.

  • Types of exposure: Standard in place should mitigate the impact of crop cultivation on biodiversity.

  • Types of comparator: Standards were compared against each other to clarify how they mitigate the impact on biodiversity.

  • Types of outcome: Any reported change within and nearby production area.

  • Types of study: Standards related to oil palm, jatropha, and soybean, i.e. international legislation, industry standards, ISO management standards, NGO standards

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:

  • Temporal and spatial scale. The temporal and spatial aspects of sampling were recorded, as well as whether sampling effort was evaluated.

  • Comparator features: before/after or site comparison.

  • Methodology used to collect data.

  • Environmental features of the site: soil type, original vegetation, and the type of surrounding landscape

  • Variables related ecological interactions: competition and predation.

  • Variables related to plantation management: use of herbicides, insecticides, and fertilizers.

  • Plantation type (industrial vs. smallholder), age, size, and certification status.

To avoid misleading conclusions by including studies with inappropriate design, the studies were evaluated according to the hierarchy of quality of evidence (Table 2). Studies that fell into the category VI were excluded from analysis.
Table 2

Hierarchy of quality of evidence based on the information provided in the documents

Category

Quality of evidence presented

I.

Randomized controlled trials of adequate spatial and temporal scale for the study species.

II.

Controlled trials without randomization with adequate spatial and temporal scale for the study species.

III.

Comparisons of differences between sites with and without controls with adequate spatial and temporal scale for the study species.

IV.

Evidence obtained from multiple time series or from dramatic results in uncontrolled experiments.

V.

Opinions of respected authorities based on qualitative field evidence, descriptive studies or reports of expert committees.

VI.

Evidence inadequate owing to problems of methodology e.g. sample size, spatial or temporal scale.

Modified after [15].

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].

Results

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.
https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig1_HTML.jpg
Figure 1

The number of articles at different assessment stages.

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.
https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig2_HTML.jpg
Figure 2

Number of articles published in different years. The articles shown are limited to those included in this systematic review. For articles published before 2000 only those years in which an article was published are shown. Arrows indicate the years when standards from Roundtable on Sustainable Palm Oil (RSPO) and Roundtable on Sustainable Biofuels (RSB) were first published.

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).
https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig3_HTML.jpg
Figure 3

Taxonomic groups studied in the 25 studies on biodiversity included in the review. Some of the studies studied several taxonomic groups.

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).
https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig4_HTML.jpg
Figure 4

The size of plantations studied. The bars represent individual studies and the labels refer to the study numbers in Additional file 3.

Study designs and methodology

All studies included in the review used quantitative methods. All except one study were site comparisons between oil palm plantation and primary or secondary forest or both. In the one before-and-after study Chang et al. [27] studied changes in abundance of mosquitoes induced by land use change during the development of an oil palm plantation.

All site comparison studies selected sites that could be paired and, except for Koh and Wilcove [28], collected data from the sites during same time period. Koh and Wilcove [28] used butterfly data collected from primary and logged forest in two earlier studies [29, 30] and compared with the data they collected from an oil palm plantation. The exact method for site selection or pairing was described in only four studies [26, 3133]. It was impossible to assess the robustness of the selection in the other studies. Similarly, the selection of sub-sites within the studied habitats was unclear in most of the studies as even the studies that selected sub-sites randomly did not explain the exact method for randomization.

Half of the studies reported distance between the sites and only ten studies discussed leakage effects from or to adjacent areas. One of these [32] was specifically focused on spillover of butterflies and ants from forest to oil palm plantations and found that although vagrant forest butterflies were found in the plantations, recapture data did not reveal dispersal of butterflies across the forest-plantation ecotone. No spillover of ant species was reported. In addition, it was reported that leakage from adjacent areas was unlikely owing to behavioral characteristics [34] to dispersal capabilities [27, 35] or ecological conditions [36]. In three studies on birds it was reported that nearby primary forest areas either ‘probably’ [37] or ‘certainly’ [26, 38] contributed to the species richness in oil palm landscapes. Similarly, Gillespie et al. [39] suggested that it is possible that the occurrence of arboreal amphibian species (tree frogs), specifically Rhacophorus appendiculatus, Rhacophorus dulitensis and Rhacophorus pardalis, in the plantation resulted from local dispersal from nearby forest habitats. Juliani et al. [40] suspected that the lack of shelter or roosting sites in areas adjacent to the oil palm plantation studied could have contributed to the high abundance of bats in the plantation.

The species studied in the faunal studies varied considerably, and therefore the data collection methods also differed (Table 3). Sampling effort was statistically evaluated in almost two thirds of the studies (58%) and in addition one more study [41] reported that it was ‘low’. The most frequently reported method of evaluating sampling effort was by use of species accumulation curves; comparisons between observed and predicted species richness were used in three studies [22, 26, 36]. Generally, the studies that had statistically evaluated the sampling effort deemed it to be satisfactory to show the differences (or lack of differences) between the sites, and 11 of the 14 studies specifically discussed that point.
Table 3

Summary of methods used in the studies included in the review

Study

Taxonomic group

Collected data

Sampling method

Methodology

Invertebrates

    

Brühl & Eltz [36]

Ground-dwelling ants

Species richness

Tuna baits

Baits along 105 transects of various lengths (10-100 m)

Chey [31]

Moths

Species richness, abundance and composition

Light traps

One light-trap at each site for 3 consecutive nights.

Chang et al. [27]

Mosquitoes

Species richness and abundance

Human baits

All-night human landing collections on 5 consecutive nights each year.

Chung et al. [21]

Subterranean beetles

Species richness, abundance and composition

Winkler sampling

Ten 1 m2 samples of leaf litter and soil at each site.

 

Understorey beetles

Species richness, abundance and composition

Flight-interception-trapping

3 traps per site. Two weeks of sampling. Only samples from alternate days used.

 

Arboreal beetles

Species richness, abundance and composition

Mist-blowing

10 trees at least 10 m apart

Davis & Philips [22]

Dung beetles

Species richness and abundance

Pitfall traps

4 sites per habitat, 3 traps per site at least 10 m apart, two 24-hour periods

Fayle et al. [42]

Canopy ants

Species richness, abundance and composition

Fogging

20 transects per habitat

 

Ants in the ferns

Species richness, abundance and composition

Entire ferns collected, litter and core fragments processed.

20 transects per habitat

 

Leaf litter ants

Species richness, abundance and composition

Litter samples

20 transects per habitat

Hashim et al. [41]

Ants

Species richness

Hand-collecting and pitfall traps

3 randomly-distributed 0.25 m2 subplots within each of three 10 m × 10 m plots and 5 pitfall traps per habitat.

Hassall et al. [35]

Terrestrial isopods

Species richness and abundance

Quadrats

Plots sampled on a stratified random basis.

Koh & Wilcove [28]

Butterflies

Species richness

Banana-baited traps

98 trapping sites with total of 48 hours of trapping

Liow et al. [43]

Bees

Species richness, abundance and composition

Honey-baited traps in transects

Non-randomly selected 1-3 transects per site. On average 12.85 hours surveyed per transect

Lucey & Hill [32]

Ground-dwelling ants

Species richness, abundance, and composition

Pitfall traps

2000 m transects, f1ve traps per trap station, six trap stations in forest and in oil palm plantations, 100 m between trap stations. Sampled twice for 12 consecutive days.

 

Butterflies

Species richness, abundance, and composition

Fruit-bated traps

Two 2000 m transects, 10 trap stations in forest and in oil palm plantation, 100 m between trap stations. Sampled twice for 12 consecutive days at both occasions.

Room [44]

Ground foraging ants

Species richness, abundance and composition

Quadrats

30 samples per habitat.

Vaessen et al. [33]

Termites

Species richness, abundance and composition

Transects

One transect established randomly at each site.

Vertebrates

    

Aratrakorn et al. [45]

Birds

Species richness and relative abundance

Timed Species Counts

30 oil palm plantations selected from aerial photographs. The number of sites based on preliminary counts. Two counts of 20 min divided into five 4-minute blocks.

Azhar et al. [26]

Birds

Species richness, abundance and composition

Transect counts

470 various-length transects: 418 in plantation estates, 52 in smallholdings and 20 in peat swamp forest.

Bernard et al. [34]

Non-volant small mammals

Species richness, abundance and composition

Live cage traps with baits

50 traps per trapping site arranged into 5 200 m long trap lines.

Danielsen & Heegaard [46]

Birds, primates, tree-shrews, and squirrels

Species richness, abundance, and composition

Variable-distance line-transect

2000 m straight line; surveyed for 40 hours in forest areas and for 20 hours in oil palm.

 

Bats

Species richness, abundance, and composition

Mist nets

15-20 nets (totaling 150-250 m).

Edwards et al. [47]

Birds

Species richness and abundance

Timed point-counts along transects

5 sites per habitat, 12 sampling points at 250 m intervals at each site.

Fukuda et al. [48]

Bats

Species richness and abundance

Mist nets and harp traps

2-4 mist nets per night, 3-6 census points per habitat.

Gillespie et al. [39]

Amphibians

Species richness and composition

Transects

400 m transects; 6 in wet forest, 5 in dry forest, and 3 in oil palm plantation. Each sampled 3-4 times.

Glor et al. [49]

Lizards

Species richness and abundance

Glue traps

Non-randomly selected 10 x 10 m trapping grids with 20 traps each, 3 plots in oil palm, 4 in mogote.

Juliani [40]

Bats

Species richness and abundance

Mist nets

10 mist nets randomly placed in each habitat type.

Peh et al. [38, 50]

Birds

Species richness and abundance

Point counts

240 point counts arbitrary chosen. At least 200 m from each other. 127 sites in the oil palm.

Sheldon et al. [37]

Birds

Species richness, abundance and composition

Point counts

20 three-minute point counts at 50 m intervals along the transects.

Nine of the studies explicitly reported efforts aimed at minimizing or controlling for the effect of extrinsic variables. For example, sampling at the same time of the day, or only in fine weather conditions, collecting samples away from the edges of the habitat, and sampling birds at a limited spatial scale to ensure visibility.

Temporal and spatial scale of the studies

Temporal and spatial scales are important in several contexts. Although the spatial scale of data collection can influence the results of faunal studies [51], this was rarely discussed in the studies. Only two studies [32, 35] discussed the results in the context of spatial scale, specifically in relation to the dispersal abilities of the species in question.

None of the studies collected long-term data and hence, the studies are based on a rather limited time scale. In addition, only two studies assessed the effects of seasonality. Fukuda et al. [48] conducted censuses on bats four times within 17 months and did not detect any significant differences between the seasons. Lucey and Hill [32] compared similarity of species assemblages between first and second sampling occasion and concluded that for butterfly species temporal turnover contributed substantially to overall diversity. For ant species the similarity of species assemblages was higher for both forest and oil palm habitats and thus, temporal turnover had less impact on the diversity of ants than butterflies.

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.
https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig5_HTML.jpg
Figure 5

Forest plot of effect sizes for species richness (mean standardized difference between primary forest and oil palm plantation). The grand mean is the summary effect of all the individual effect sizes. The error bars represent 95% confidence intervals. The numbers after the taxa refer to the study number in Additional file 3.

https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig6_HTML.jpg
Figure 6

Forest plot of effect sizes for species richness (mean standardized difference between secondary forest and oil palm plantation). The grand mean is the summary effect of all the individual effect sizes. The error bars represent 95% confidence intervals. The numbers after the taxa refer to the study number in Additional file 3.

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.
https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig7_HTML.jpg
Figure 7

Forest plot of effect sizes for abundance of individuals (mean standardized difference between primary forest and oil palm plantation). The grand mean is the summary effect of all the individual effect sizes. The error bars represent 95% confidence intervals. The numbers after the taxa refer to the study number in Additional file 3.

https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig8_HTML.jpg
Figure 8

Forest plot of effect sizes for abundance of individuals (mean standardized difference between secondary forest and oil palm plantation). The grand mean is the summary effect of all the individual effect sizes. The error bars represent 95% confidence intervals. The numbers after the taxa refer to the study number in Additional file 3.

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.
Table 4

Summary of information on species composition provided in the reviewed studies*

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.

Table 5

Summary of information on species composition between logged peat forest and smallholder plantations*

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.
Table 6

Total species richness in forests and plantations, the number of shared species, and the proportion of species remaining

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

https://static-content.springer.com/image/art%3A10.1186%2F2047-2382-3-4/MediaObjects/13750_2013_Article_37_Fig9_HTML.jpg
Figure 9

Mean proportion of shared species between oil palm plantation and forest with 95% confidence intervals. Data were standardized by the total number of species recorded in forest (the number of forest species = 1).

Narrative synthesis

Biodiversity in industrial versus smallholder plantations

Only one study [26] addressed differences in species richness and community composition between smallholder and industrial plantations. The results showed that, on average, smallholdings with mixed-age stands supported higher bird species richness than industrial plantation estates that had uniform age structure (range from <6 years old to >25 years old). The average dissimilarity of bird assemblages between the plantation estates and smallholdings was 47.6%. However, since yields were not taken into account in the analyses, it is not known whether the impact is similar when compared for equivalent amounts of fuel produced under different management systems.

Explanatory factors for differences in species richness and community composition

Only four studies had statistically analyzed the causes of differences in either species richness or community composition. For birds, the statistical analyses showed that increased ground vegetation and undergrowth height, as well as decreased canopy cover, were all correlated with higher species richness [26]. In addition, increased proximity to a forest patch, cumulative area of natural forest patches, and decreased isolation distance positively influenced bird species richness [26]. The role of food resources was speculated about in the discussion but not tested.

In the case of invertebrates, the hotter and drier conditions in oil palm plantations were the main cause of changes in community compositions (ants [42]; beetles [21]; bees [43]). Soil pH was a significant factor for isopods [35], whereas the amount of leaf litter, tree and sapling densities, and plant species richness were significant factors for primary forest beetle species [21].

Ecosystem function

None of the studies had specifically looked at biodiversity-related ecosystem functions, such as pest control, pollination and soil processes that might have included supporting data. However, we found some discussions about concern for the continuity of pollination processes after expansion of oil palm habitats, and the changed communities between primary forest and other areas [40, 43]. In summary, these postulated that there would be negative consequences for forest regeneration if remaining forest areas cannot support large enough pollinator populations and pollinators are also absent in the surrounding oil palm matrix.

Biofuel-related standards

There were no studies that had tried to assess the impact of the standards on biodiversity. In fact, only a few of the studies reported whether the oil palm plantations studied were complying with standards. None of these had been structured to compare impacts before and after standards were applied (for a qualitative assessment of the standards see Additional file 4).

Discussion

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.

Conclusions

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:

  • Landscape level studies that would contribute better knowledge of the impacts at larger scale beyond simple habitat comparisons.

  • Research on how reduced species richness or changes in community composition affect ecosystem functions. The lack of knowledge about this topic was also a conclusion of a recent review by Foster et al.[53].

  • Research on differences in biodiversity and ecosystem function in response to different production systems, (smallholdings vs industrial estates) and different management practices (certified and non-certified plantations).

  • Studies on jatropha and soybean and oil palm beyond Malaysia.

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.

Author’s contributions

SS carried out the literature survey and assessment, extracted data, designed and carried out the statistical analysis. She drafted the systematic review and revised it following reviewers’ comments. RN had the idea for the study. SS, MRG, RN, and YL contributed to the design and focus of the study. SS, MG, and MZ assessed the standards. SS, CG, JUG, JG, MG, GP, JS, MZ participated in the workshop where the first draft of the review was discussed and subsequently improved. All authors participated in the revisions of the manuscript. GP and MG edited the language. All authors read and approved the final manuscript.

Declarations

Acknowledgements

We thank all the authors who responded to our queries and provided additional information. We acknowledge our superb librarian, Wiwit Siswarini, for her help in finding articles and other information resources. We are thankful for Bruno Locatelli for his guidance on statistical issues but note that he bears no responsibility for any of our decisions regarding the statistics. We thank Ankara M. Chen for her help in organizing the superb workshop in Zürich that provided the push to finalize the review. We acknowledge Wen Zhou for her support. Three anonymous reviewers provided useful suggestions to improve the protocol to conduct this systematic review. We thank Andrew Pullin and two anonymous reviewers for their comments that made the final review more focused and improved its quality. The review was supported by the Center for International Forestry Research, the Government of Finland, ETH Zürich, and CIRAD.

Authors’ Affiliations

(1)
Center for International Forestry Research
(2)
Department of Environmental Systems Science, ETH Zurich
(3)
Interdisciplinary Arts & Sciences, University of Washington
(4)
Program on the Environment, University of Washington
(5)
CIRAD, Research Unit Goods and Services of Tropical Forest Ecosystems, Avenue Agropolis
(6)
Biodiversity Institute, Department of Zoology, University of Oxford
(7)
Zoological Society of London, Indonesia Programme

References

  1. Rajagopal D, Zilberman D: Review of environmental, economic and policy aspects of biofuels. Washington DC, USA: World Bank Policy Research Working Paper; 2007:4341.View ArticleGoogle Scholar
  2. Feintrenie L, Chong WK, Levang P: Why do Farmers Prefer Oil Palm? Lessons Learnt from Bungo District, Indonesia. Small-scale Forestry 2010, 9: 379–396. 10.1007/s11842-010-9122-2View ArticleGoogle Scholar
  3. Koh LP, Ghazoul J: Biofuels, biodiversity, and people: understanding the conflicts and finding opportunities. Biol Conserv 2008, 141: 2450–2460. 10.1016/j.biocon.2008.08.005View ArticleGoogle Scholar
  4. Lewandowski I, Faaij APC: Steps towards the development of a certification system for sustainable bio-energy trade. Biomass Bioenergy 2006, 30: 83–104. 10.1016/j.biombioe.2005.11.003View ArticleGoogle Scholar
  5. Danielsen F, Beukema H, Burgess ND, Parish F, Bruhl CA, Donald PF, Murdiyarso D, Phalan B, Reijnders L, Struebig M, Fitzherbert EB: Biofuel plantations on forested lands: double jeopardy for biodiversity and climate. Conserv Biol 2009, 23: 348–358. 10.1111/j.1523-1739.2008.01096.xView ArticleGoogle Scholar
  6. Phalan B: The social and environmental impacts of biofuels in Asia: an overview. Appl Energy 2009,86(Supplement 1):S21-S29.View ArticleGoogle Scholar
  7. Aerts R, Honnay O: Forest restoration, biodiversity and ecosystem functioning. BMC Ecol 2011, 11: 29. 10.1186/1472-6785-11-29View ArticleGoogle Scholar
  8. Roundtable on Sustainable Palm Oil. http://www.rspo.org/
  9. Round Table on Responsible Soy Association. http://www.responsiblesoy.org/
  10. Roundtable on Sustainable Biomaterials. http://rsb.org/
  11. Laurance WF, Koh LP, Butler R, Sodhi NS, Bradshaw CJA, Neidel JD, Consunji H, Mateo Vega J: Improving the performance of the roundtable on sustainable palm oil for nature conservation. Conserv Biol 2010, 24: 377–381. 10.1111/j.1523-1739.2010.01448.xView ArticleGoogle Scholar
  12. FAO: Forests and Energy. In FAO Forestry Paper 154. Rome, Italy: FAO; 2008.Google Scholar
  13. Savilaakso S, Laumonier Y, Guariguata MR, Nasi R: Does production of oil palm, soybean, or jatropha change biodiversity and ecosystem functions in tropical forests? Environmental Evidence 2013, 2: 17. 10.1186/2047-2382-2-17View ArticleGoogle Scholar
  14. Edwards P, Clarke M, DiGuiseppi C, Pratap S, Roberts I, Wentz R: Identification of randomized controlled trials in systematic reviews: accuracy and reliability of screening records. Stat Med 2002, 21: 1635–1640. 10.1002/sim.1190View ArticleGoogle Scholar
  15. Pullin AS, Knight TM: Support for decision making in conservation practice: an evidence-based approach. J Nat Conserv 2003, 11: 83–90. 10.1078/1617-1381-00040View ArticleGoogle Scholar
  16. Arnqvist G, Wooster D: Meta-analysis: synthesizing research findings in ecology and evolution. Trends Ecol Evol 1995, 10: 236–240. 10.1016/S0169-5347(00)89073-4View ArticleGoogle Scholar
  17. Rosethal R: Parametric measures of effect size. In The handbook of research synthesis. Edited by: Cooper H, Hedges LV. New York, USA: Russell Sage Foundation; 1994:232–244.Google Scholar
  18. Rosenberg MS, Adams DC, Gurevitch J: MetaWin: Statistical software for meta-analysis. Version 2.0. Sunderland, Massachusetts: Sinauer Associates; 1999.Google Scholar
  19. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR: Introduction to meta-analysis. John Wiley & Sons Ltd: United Kingdom; 2009.View ArticleGoogle Scholar
  20. Cooper H, Hedges LV: The Handbook of Research Synthesis. New York, USA: Russell Sage Foundation; 1994.Google Scholar
  21. Chung AY, Eggleton P, Speight MR, Hammond PM, Chey VK: The diversity of beetle assemblages in different habitat types in Sabah, Malaysia. Bull Entomol Res 2000, 90: 475–496.View ArticleGoogle Scholar
  22. Davis ALV, Philips TK: Effect of deforestation on a southwest Ghana dung beetle assemblage (Coleoptera : Scarabaeidae) at the periphery of Ankasa conservation area. Environ Entomol 2005, 34: 1081–1088. 10.1603/0046-225X(2005)034[1081:EODOAS]2.0.CO;2View ArticleGoogle Scholar
  23. Rosenberg MS, Adams DC, Gurevitch J: MetaWin: Statistical software for meta-analysis. Version 2.1. Sunderland, Massachusetts: Sinauer Associates; 2007.Google Scholar
  24. Nichols E, Larsen T, Spector S, Davis AL, Escobar F, Favila M, Vulinec K: Global dung beetle response to tropical forest modification and fragmentation: a quantitative literature review and meta-analysis. Biol Conserv 2007, 137: 1–19. 10.1016/j.biocon.2007.01.023View ArticleGoogle Scholar
  25. Inc SPSS: SPSS Statistics for Windows, Version 17.0. Chicago: SPSS Inc.; 2008.Google Scholar
  26. Azhar B, Lindenmayer DB, Wood J, Fischer J, Manning A, McElhinny C, Zakaria M: The conservation value of oil palm plantation estates, smallholdings and logged peat swamp forest for birds. For Ecol Manage 2011, 262: 2306–2315. 10.1016/j.foreco.2011.08.026View ArticleGoogle Scholar
  27. Chang MS, Hii J, Buttner P, Mansoor F: Changes in abundance and behaviour of vector mosquitoes induced by land use during the development of an oil palm plantation in Sarawak. Trans R Soc Trop Med Hyg 1997, 91: 382–386. 10.1016/S0035-9203(97)90248-0View ArticleGoogle Scholar
  28. Koh LP, Wilcove DS: Is oil palm agriculture really destroying tropical biodiversity? Conserv Lett 2008, 1: 60–64. 10.1111/j.1755-263X.2008.00011.xView ArticleGoogle Scholar
  29. Dumbrell AJ, Hill JK: Impacts of selective logging on canopy and ground assemblages of tropical forest butterflies: implications for sampling. Biol Conserv 2005, 125: 123–131. 10.1016/j.biocon.2005.02.016View ArticleGoogle Scholar
  30. Hamer KC, Hill JK, Benedick S, Mustaffa N, Sherratt TN, Maryati M, Chey VK: Ecology of butterflies in natural and selectively logged forests of northern Borneo: the importance of habitat heterogeneity. J Appl Ecol 2003, 40: 150–162. 10.1046/j.1365-2664.2003.00783.xView ArticleGoogle Scholar
  31. Chey V: Impacts of Forest Conversion on Biodiversity as Indicated by Moths. Malay Nat J 2006, 57: 383–418.Google Scholar
  32. Lucey JM, Hill JK: Spillover of insects from rain forest into adjacent oil palm plantations. Biotropica 2012, 44: 368–377. 10.1111/j.1744-7429.2011.00824.xView ArticleGoogle Scholar
  33. Vaessen T, Verwer C, Demies M, Kaliang H, Van Der Meer PJ: Comparison of termite assemblages along a landuse gradient on peat areas in Sarawak, Malaysia. J Trop For Sci 2011, 23: 196–203.Google Scholar
  34. Bernard H, Fjeldså J, Mohamed M: A case study on the effects of disturbance and conversion of tropical lowland rain forest on the non-volant small mammals in North Borneo: management implications. Mammal Study 2009, 34: 85–96. 10.3106/041.034.0204View ArticleGoogle Scholar
  35. Hassall M, Jones DT, Taiti S, Latipi Z, Sutton SL, Mohammed M: Biodiversity and abundance of terrestrial isopods along a gradient of disturbance in Sabah, East Malaysia. Eur J Soil Biol 2006,42(Supplement 1):S197-S207.View ArticleGoogle Scholar
  36. Brühl CA, Eltz T: Fuelling the biodiversity crisis: species loss of ground-dwelling forest ants in oil palm plantations in Sabah, Malaysia (Borneo). Biodivers Conserv 2010, 19: 519–529. 10.1007/s10531-009-9596-4View ArticleGoogle Scholar
  37. Sheldon FH, Styring A, Hosner PA: Bird species richness in a Bornean exotic tree plantation: a long-term perspective. Biol Conserv 2010, 143: 399–407. 10.1016/j.biocon.2009.11.004View ArticleGoogle Scholar
  38. Peh K, Sodhi N, de Jong J, Sekercioglu C, Yap C, Lim S: Conservation value of degraded habitats for forest birds in southern Peninsular Malaysia. Divers Distrib 2006, 12: 572–581. 10.1111/j.1366-9516.2006.00257.xView ArticleGoogle Scholar
  39. Gillespie GR, Ahmad E, Elahan B, Evans A, Ancrenaz M, Goossens B, Scroggie MP: Conservation of amphibians in Borneo: relative value of secondary tropical forest and non-forest habitats. Biol Conserv 2012, 152: 136–144.View ArticleGoogle Scholar
  40. Juliani NS, Anuar MSS, Salmi ALN, Munira AN, Liyana KN: Diversity pattern of bats at two contrastinng habitat types along Kerian River, Perak, Malaysia. Trop Life Sci Res 2011, 22: 13–22.Google Scholar
  41. Hashim NR, Jusoh WFAW, Nasir MNSM: Ant diversity in a Peninsular Malaysian mangrove forest and oil palm plantation. Asian Myrmecology 2010, 3: 5–8.Google Scholar
  42. Fayle TM, Turner EC, Snaddon JL, Chey VK, Chung AYC, Eggleton P, Foster WA: Oil palm expansion into rain forest greatly reduces ant biodiversity in canopy, epiphytes and leaf-litter. Basic Appl Ecol 2010, 11: 337–345. 10.1016/j.baae.2009.12.009View ArticleGoogle Scholar
  43. Liow LH, Sodhi NS, Elmqvist T: Bee diversity along a disturbance gradient in tropical lowland forests of south-east Asia. J Appl Ecol 2001, 38: 180–192. 10.1046/j.1365-2664.2001.00582.xView ArticleGoogle Scholar
  44. Room PM: Diversity and organization of the ground foraging ant faunas of forest, grassland and tree crops in Papua New Guinea. Australian Journal of Zoology 1975, 23: 71–89. 10.1071/ZO9750071View ArticleGoogle Scholar
  45. Aratrakorn S, Thunhikorn S, Donald PF: Changes in bird communities following conversion of lowland forest to oil palm and rubber plantations in southern Thailand. Bird Conserv Int 2006, 16: 71–82. 10.1017/S0959270906000062View ArticleGoogle Scholar
  46. Danielsen F, Heegaard M: Impact of logging and plantation development on species diversity: a case study from Sumatra. In Management of tropical forests: towards an integrated perspective. Edited by: Sandbukt O. Oslo: Centre for Development and the Environment. University of Oslo; 1995.Google Scholar
  47. Edwards DP, Hodgson JA, Hamer KC, Mitchell SL, Ahmad AH, Cornell SJ, Wilcove DS: Wildlife-friendly oil palm plantations fail to protect biodiversity effectively. Conserv Lett 2010, 3: 236–242. 10.1111/j.1755-263X.2010.00107.xView ArticleGoogle Scholar
  48. Fukuda D, Tisen OB, Momose K, Sakai S: Bat diversity in the vegetation mosaic around a lowland dipterocarp forest of Borneo. Raffles Bull Zool 2009, 57: 213–221.Google Scholar
  49. Glor R, Flecker A, Benard M, Power A: Lizard diversity and agricultural disturbance in a Caribbean forest landscape. Biodiversity & Conservation 2001, 10: 711–723. 10.1023/A:1016665011087View ArticleGoogle Scholar
  50. Peh KSH, Jong J, Sodhi NS, Lim SLH, Yap CAM: Lowland rainforest avifauna and human disturbance: persistence of primary forest birds in selectively logged forests and mixed-rural habitats of southern Peninsular Malaysia. Biol Conserv 2005, 123: 489–505. 10.1016/j.biocon.2005.01.010View ArticleGoogle Scholar
  51. Hamer KC, Hill JK: Scale-dependent effects of habitat disturbance on species richness in tropical forests. Conserv Biol 2000, 14: 1435–1440. 10.1046/j.1523-1739.2000.99417.xView ArticleGoogle Scholar
  52. Fitzherbert EB, Struebig MJ, Morel A, Danielsen F, Brühl CA, Donald PF, Phalan B: How will oil palm expansion affect biodiversity? Trends Ecol Evol 2008, 23: 538–545. 10.1016/j.tree.2008.06.012View ArticleGoogle Scholar
  53. Foster WA, Snaddon JL, Turner EC, Fayle TM, Cockerill TD, Ellwood MD, Broad GR, Chung AY, Eggleton P, Khen CV, Yusah KM: Establishing the evidence base for maintaining biodiversity and ecosystem function in the oil palm landscapes of South East Asia. Philos Trans R Soc Lond B Biol Sci 2011, 366: 3277–3291. 10.1098/rstb.2011.0041View ArticleGoogle Scholar
  54. Ramage BS, Sheil D, Salim HM, Fletcher C, Mustafa NZ, Luruthusamay JC, Harrison RD, Butod E, Dzulkiply AD, Kassim AR, Potts MD: Pseudoreplication in tropical forests and the resulting effects on biodiversity conservation. Conserv Biol 2013, 27: 364–372. 10.1111/cobi.12004View ArticleGoogle Scholar
  55. iSpot. http://www.ispotnature.org/

Copyright

© Savilaakso et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.