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Complexity within an oil palm monoculture: the effects of habitat variability and rainfall on adult dragonfly (Odonata) communities.

Complexity within an oil palm monoculture: the effects of habitat variability and rainfall on adult dragonfly (Odonata) communities.
Complexity within an oil palm monoculture: the effects of habitat variability and rainfall on adult dragonfly (Odonata) communities.
Recent expansion of oil palm agriculture has resulted in loss of forest habitat and forest-dependent species. However, large numbers of species – particularly insects – can persist within plantations. This study focuses on Odonata (dragonflies and damselflies): a charismatic indicator taxon, and a potentially valuable pest control agent. We surveyed adult Odonata populations biannually over three years within an industrial oil palm plantation in Sumatra, Indonesia. We assessed the effects of rainfall (including an El Niño Southern Oscillation-associated drought), the role of roadside ditches, and the importance of understory vegetation on Odonata populations. To assess the impacts of vegetation we took advantage of a long-term vegetation management experiment that is part of the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Programme. We found 41 Odonata species, and communities varied between plantation core and roadside edge microhabitats, and between seasons. Abundance was significantly related to rainfall levels four months before surveys, probably indicating the importance of high water levels in roadside ditches for successful larval development. We found no significant effect of the BEFTA understory vegetation treatments on Odonata abundance, and only limited effects on community composition, suggesting that local understory vegetation structure plays a relatively unimportant role in determining communities. Our findings highlight that there are large numbers of Odonata species present within oil palm plantations, and suggest that their abundance could potentially be increased by maintaining or establishing waterbodies. As Odonata are predators, this could bring pest control benefits, in addition to enhancing biodiversity within intensive agricultural landscapes., Site.—Fieldwork was conducted within oil palm plantations in Riau Province, central Sumatra, Indonesia. The plantations are owned and managed by PT Ivo Mas Tunggal (a subsidiary company of Golden Agri Resources, GAR), with technical input from Sinar Mas Agro Resources and Technology Research Institute (SMARTRI) (the research and development centre of GAR) (Fig. S1, full manuscript). The area is naturally mixed lowland dipterocarp forest, but was deforested ~30 years ago, and is currently heavily dominated by oil palm agriculture, with very little non-converted habitat remaining. The region has a tropical climate, with mean annual rainfall of 2350 mm, spread unevenly across the year, and is based on mineral soil (Tao et al. 2016). We surveyed sites that formed part of the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Programme (Foster et al. 2014; Luke et al. 2020). As part of this, the BEFTA Understory Vegetation Project tests the effects of understory vegetation complexity on the oil palm ecosystem, through varying levels of herbicide use and manual cutting of vegetation. BEFTA has established three understory vegetation treatments (see Luke et al. (2020) for full details): Reduced complexity: this involves spraying all understory vegetation with herbicides. Hereafter referred to as ‘Reduced’. Normal complexity: this is the standard practice used within the SMARTRI estates and involves an intermediate level of herbicide spraying, with harvest paths and 1.5 m circles around palms being sprayed and woody vegetation being manually removed, but other vegetation being allowed to regrow. Hereafter referred to as ‘Normal’. Enhanced complexity: this involves no spraying of herbicides and only limited hand-cutting of woody vegetation, and along harvesting paths and in palm circles. Hereafter referred to as ‘Enhanced’. The three treatments represent the range of different management strategies that occur within oil palm plantations. There are eighteen BEFTA Understory Vegetation Project plots, split across two estates (Ujung Tanjung and Kandista), and organized into six triplets, each at least 800m from the next (Fig. S1; Fig. S2; Table S1, full manuscript). Each triplet contains one 150 x 150 m plot of each treatment, with the order allocated randomly. The middle plot in each triplet is 155 m from each of the outer plots within the triplet. Each plot is located at the end of a plantation block of 900 x 300 m, so that it is adjacent to an access road, and therefore includes both core and edge plantation microhabitat (hereafter referred to as ‘Core’ and ‘Edge’). Edge sites were located alongside both a dirt road and a drainage ditch filled with standing water (Fig. S2, full manuscript). These Edge sites occur around each of the 900 x 300m planting blocks. Core sites were within the interior of oil palm planting blocks, at least 50m from the edge. This led to differences in shading, exposure, and water occurrence in the two microhabitats, with consequent impacts on vegetation structure and diversity. Specifically, Edge areas had significantly higher plant biomass and cover, plant species richness, and higher occurrence of Turnera ulmifolia (planted along roadsides to promote populations of beneficial insects) than Core areas, whilst Core areas had significantly higher percentage cover of frond heaps (stacks of chopped palm fronds) (Luke et al. 2019, 2020) (and also see assessments of habitat structure presented in the full manuscript). All plots are in flat areas of the plantation, 10-30 m asl, and are in areas that were mature palm (palms planted between 1988 and 1993) at the time of survey. The SMARTRI estates are criss-crossed by a network of small streams (Fig. S1, full manuscript), and two plots had small streams running through them. There were no natural ponds or lakes nearby. Plots were marked out in October 2012 and were all managed using the standard SMARTRI vegetation practices (Normal complexity) until treatments began in February 2014, after which plots were managed according to their allocated understory vegetation treatment. Refer to Luke et al. (2020), for more details. Odonata surveying.—Within each plot, adult Odonata were surveyed along transects in the Core and Edge of the plot. Core transects followed the edge of a central 50 x 50 m sampling area within each plot and so were 200 m long, whilst Edge transects followed the roadside edge of the plot and so were 150 m long (Fig. S2, full manuscript). Recorders walked at a steady pace along each transect and identified and counted the dragonflies seen within a 5 m sided cube of space in front of them. Survey duration was not fixed because the time required to complete a survey depended on the number of dragonflies present. When a species was not immediately identifiable by sight, they were caught using a hand-net and photographed, allowing later identification by an experienced taxonomist (Rory A. Dow) and using identification guides (Orr 2003; Tang et al. 2010). Surveys were conducted at each plot during two ‘Seasons’: February-April, and September, hereafter referred to as ‘March’ and ‘September’. Both seasons were surveyed in 2013, 2014, and 2015. Two repeat surveys of each plot were conducted within each season. Surveys conducted in March 2014 fell partly during the BEFTA Understory Vegetation Project pre-treatment (hereafter referred to as ‘pre-treatment’), and partly during the BEFTA Understory Vegetation Project post-treatment (hereafter referred to as ‘post-treatment’) time period, and were categorised accordingly in analyses. Surveys were conducted between 9am and 5pm. Vegetation measurements.—Vegetation measurements were taken every 10 m along each of the transects, once in March-April 2013 (pre-treatment), and again in September 2014 (post-treatment). Vegetation percentage cover (of ferns, palm fronds, bare ground, empty fruit bunch (EFB – used husks of harvested palm fruits, applied by industry as a mulch), and the non-native shrub Turnera ulmifolia (planted by industry along roadways to promote pest control)) was assessed by eye within a 5 x 5 m area at each point. Vegetation height was measured with a metre rule. At each measurement point, the metre rule was held in a vertical position, with its base resting on the ground, and an A4 clipboard lightly rested on the vegetation (to push down any single tall stems) and the height measured accordingly. Canopy openness was measured using a densiometer (Lemmon 1956), averaging four measurements taken North, South, East and West at each point. Rainfall measurements.—We recorded daily rainfall (mm) using rain gauges that each had a 100 cm2 collecting area. Rainfall values from all rain gauges within each estate (three in Ujung Tanjung, and two in Kandista) were averaged to calculate a monthly rainfall value for each estate. In analyses, we used the estate rainfall value that was applicable to each plot. We used rainfall measures from March of the relevant year as the ‘monthly rainfall’ value for surveys conducted during February to April, and rainfall measures from September for September surveys. In addition to ‘monthly rainfall’, we also used the value of rainfall for the calendar month that was four months before (‘rainfall four months before’) the March and September dragonfly surveys in analyses. This is because dragonflies have an aquatic larval stage, and therefore presence of adults at a site is dependent on sufficient water for larval development before the survey date. Although different dragonfly species exhibit a range of reproductive strategies, the majority of tropical species are multivoltine (Corbet 1980). The development time for many tropical dragonfly larvae is between 60 and 200 days (Corbet 1980), the mean of which is 130 days (4.3 months). Using this lagged rainfall value in analyses allowed us to consider the influence of rainfall on egg laying, egg survival, and larval development stages of the dragonfly lifecycle, in addition to assessing impacts of rainfall on adult presence. Statistical analyses.—We conducted analyses using R statistical program version 3.5.1 (R Core Team 2018), and the program R Studio (R Studio Team 2016). To compare 200 m-long Core transects and 150 m-long Edge transects, we standardised all abundance data to predicted values for 150 m-long transects by multiplying Core abundance values by 0.75. We included data for an unidentified teneral individual (‘Unknown teneral’) within overall abundance models, but excluded this data point from species richness curves and family level analyses, as its species and family were unknown.
DRYAD
Luke, Sarah H.
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Rambe, T. Dzulfikar S.
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Luke, Sarah H.
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Wahyuningsih, Resti
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Widodo, Rudy Harto
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Caliman, Jean-Pierre
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Snaddon, Jake L.
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Foster, William A.
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Turner, Edgar C.
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Luke, Sarah H., Dow, Rory A., Eycott, Amy E., Naim, Mohammad, Purnomo, Dedi, Slade, Eleanor M., Ps, Sudharto, Suhardi, Suhardi, Wahyuningsih, Resti, Caliman, Jean-Pierre, Foster, William A. and Turner, Edgar C. (2020) Complexity within an oil palm monoculture: the effects of habitat variability and rainfall on adult dragonfly (Odonata) communities. DRYAD doi:10.5061/dryad.c59zw3r3v [Dataset]

Record type: Dataset

Abstract

Recent expansion of oil palm agriculture has resulted in loss of forest habitat and forest-dependent species. However, large numbers of species – particularly insects – can persist within plantations. This study focuses on Odonata (dragonflies and damselflies): a charismatic indicator taxon, and a potentially valuable pest control agent. We surveyed adult Odonata populations biannually over three years within an industrial oil palm plantation in Sumatra, Indonesia. We assessed the effects of rainfall (including an El Niño Southern Oscillation-associated drought), the role of roadside ditches, and the importance of understory vegetation on Odonata populations. To assess the impacts of vegetation we took advantage of a long-term vegetation management experiment that is part of the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Programme. We found 41 Odonata species, and communities varied between plantation core and roadside edge microhabitats, and between seasons. Abundance was significantly related to rainfall levels four months before surveys, probably indicating the importance of high water levels in roadside ditches for successful larval development. We found no significant effect of the BEFTA understory vegetation treatments on Odonata abundance, and only limited effects on community composition, suggesting that local understory vegetation structure plays a relatively unimportant role in determining communities. Our findings highlight that there are large numbers of Odonata species present within oil palm plantations, and suggest that their abundance could potentially be increased by maintaining or establishing waterbodies. As Odonata are predators, this could bring pest control benefits, in addition to enhancing biodiversity within intensive agricultural landscapes., Site.—Fieldwork was conducted within oil palm plantations in Riau Province, central Sumatra, Indonesia. The plantations are owned and managed by PT Ivo Mas Tunggal (a subsidiary company of Golden Agri Resources, GAR), with technical input from Sinar Mas Agro Resources and Technology Research Institute (SMARTRI) (the research and development centre of GAR) (Fig. S1, full manuscript). The area is naturally mixed lowland dipterocarp forest, but was deforested ~30 years ago, and is currently heavily dominated by oil palm agriculture, with very little non-converted habitat remaining. The region has a tropical climate, with mean annual rainfall of 2350 mm, spread unevenly across the year, and is based on mineral soil (Tao et al. 2016). We surveyed sites that formed part of the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Programme (Foster et al. 2014; Luke et al. 2020). As part of this, the BEFTA Understory Vegetation Project tests the effects of understory vegetation complexity on the oil palm ecosystem, through varying levels of herbicide use and manual cutting of vegetation. BEFTA has established three understory vegetation treatments (see Luke et al. (2020) for full details): Reduced complexity: this involves spraying all understory vegetation with herbicides. Hereafter referred to as ‘Reduced’. Normal complexity: this is the standard practice used within the SMARTRI estates and involves an intermediate level of herbicide spraying, with harvest paths and 1.5 m circles around palms being sprayed and woody vegetation being manually removed, but other vegetation being allowed to regrow. Hereafter referred to as ‘Normal’. Enhanced complexity: this involves no spraying of herbicides and only limited hand-cutting of woody vegetation, and along harvesting paths and in palm circles. Hereafter referred to as ‘Enhanced’. The three treatments represent the range of different management strategies that occur within oil palm plantations. There are eighteen BEFTA Understory Vegetation Project plots, split across two estates (Ujung Tanjung and Kandista), and organized into six triplets, each at least 800m from the next (Fig. S1; Fig. S2; Table S1, full manuscript). Each triplet contains one 150 x 150 m plot of each treatment, with the order allocated randomly. The middle plot in each triplet is 155 m from each of the outer plots within the triplet. Each plot is located at the end of a plantation block of 900 x 300 m, so that it is adjacent to an access road, and therefore includes both core and edge plantation microhabitat (hereafter referred to as ‘Core’ and ‘Edge’). Edge sites were located alongside both a dirt road and a drainage ditch filled with standing water (Fig. S2, full manuscript). These Edge sites occur around each of the 900 x 300m planting blocks. Core sites were within the interior of oil palm planting blocks, at least 50m from the edge. This led to differences in shading, exposure, and water occurrence in the two microhabitats, with consequent impacts on vegetation structure and diversity. Specifically, Edge areas had significantly higher plant biomass and cover, plant species richness, and higher occurrence of Turnera ulmifolia (planted along roadsides to promote populations of beneficial insects) than Core areas, whilst Core areas had significantly higher percentage cover of frond heaps (stacks of chopped palm fronds) (Luke et al. 2019, 2020) (and also see assessments of habitat structure presented in the full manuscript). All plots are in flat areas of the plantation, 10-30 m asl, and are in areas that were mature palm (palms planted between 1988 and 1993) at the time of survey. The SMARTRI estates are criss-crossed by a network of small streams (Fig. S1, full manuscript), and two plots had small streams running through them. There were no natural ponds or lakes nearby. Plots were marked out in October 2012 and were all managed using the standard SMARTRI vegetation practices (Normal complexity) until treatments began in February 2014, after which plots were managed according to their allocated understory vegetation treatment. Refer to Luke et al. (2020), for more details. Odonata surveying.—Within each plot, adult Odonata were surveyed along transects in the Core and Edge of the plot. Core transects followed the edge of a central 50 x 50 m sampling area within each plot and so were 200 m long, whilst Edge transects followed the roadside edge of the plot and so were 150 m long (Fig. S2, full manuscript). Recorders walked at a steady pace along each transect and identified and counted the dragonflies seen within a 5 m sided cube of space in front of them. Survey duration was not fixed because the time required to complete a survey depended on the number of dragonflies present. When a species was not immediately identifiable by sight, they were caught using a hand-net and photographed, allowing later identification by an experienced taxonomist (Rory A. Dow) and using identification guides (Orr 2003; Tang et al. 2010). Surveys were conducted at each plot during two ‘Seasons’: February-April, and September, hereafter referred to as ‘March’ and ‘September’. Both seasons were surveyed in 2013, 2014, and 2015. Two repeat surveys of each plot were conducted within each season. Surveys conducted in March 2014 fell partly during the BEFTA Understory Vegetation Project pre-treatment (hereafter referred to as ‘pre-treatment’), and partly during the BEFTA Understory Vegetation Project post-treatment (hereafter referred to as ‘post-treatment’) time period, and were categorised accordingly in analyses. Surveys were conducted between 9am and 5pm. Vegetation measurements.—Vegetation measurements were taken every 10 m along each of the transects, once in March-April 2013 (pre-treatment), and again in September 2014 (post-treatment). Vegetation percentage cover (of ferns, palm fronds, bare ground, empty fruit bunch (EFB – used husks of harvested palm fruits, applied by industry as a mulch), and the non-native shrub Turnera ulmifolia (planted by industry along roadways to promote pest control)) was assessed by eye within a 5 x 5 m area at each point. Vegetation height was measured with a metre rule. At each measurement point, the metre rule was held in a vertical position, with its base resting on the ground, and an A4 clipboard lightly rested on the vegetation (to push down any single tall stems) and the height measured accordingly. Canopy openness was measured using a densiometer (Lemmon 1956), averaging four measurements taken North, South, East and West at each point. Rainfall measurements.—We recorded daily rainfall (mm) using rain gauges that each had a 100 cm2 collecting area. Rainfall values from all rain gauges within each estate (three in Ujung Tanjung, and two in Kandista) were averaged to calculate a monthly rainfall value for each estate. In analyses, we used the estate rainfall value that was applicable to each plot. We used rainfall measures from March of the relevant year as the ‘monthly rainfall’ value for surveys conducted during February to April, and rainfall measures from September for September surveys. In addition to ‘monthly rainfall’, we also used the value of rainfall for the calendar month that was four months before (‘rainfall four months before’) the March and September dragonfly surveys in analyses. This is because dragonflies have an aquatic larval stage, and therefore presence of adults at a site is dependent on sufficient water for larval development before the survey date. Although different dragonfly species exhibit a range of reproductive strategies, the majority of tropical species are multivoltine (Corbet 1980). The development time for many tropical dragonfly larvae is between 60 and 200 days (Corbet 1980), the mean of which is 130 days (4.3 months). Using this lagged rainfall value in analyses allowed us to consider the influence of rainfall on egg laying, egg survival, and larval development stages of the dragonfly lifecycle, in addition to assessing impacts of rainfall on adult presence. Statistical analyses.—We conducted analyses using R statistical program version 3.5.1 (R Core Team 2018), and the program R Studio (R Studio Team 2016). To compare 200 m-long Core transects and 150 m-long Edge transects, we standardised all abundance data to predicted values for 150 m-long transects by multiplying Core abundance values by 0.75. We included data for an unidentified teneral individual (‘Unknown teneral’) within overall abundance models, but excluded this data point from species richness curves and family level analyses, as its species and family were unknown.

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Published date: 1 January 2020

Identifiers

Local EPrints ID: 449109
URI: http://eprints.soton.ac.uk/id/eprint/449109
PURE UUID: 84366151-0d90-4f4f-a0d4-60c5234e8b2b
ORCID for Jake L. Snaddon: ORCID iD orcid.org/0000-0003-3549-5472

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Date deposited: 17 May 2021 16:33
Last modified: 18 May 2021 01:47

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Contributors

Creator: Sarah H. Luke
Contributor: Andreas Dwi Advento
Creator: Rory A. Dow
Contributor: Anak Agung Ketut Aryawan
Contributor: Holly Barclay
Creator: Amy E. Eycott
Contributor: Julie K. Hinsch
Contributor: Candra Kurniawan
Creator: Mohammad Naim
Contributor: Darren J. Mann
Contributor: Pujianto Pujianto
Creator: Dedi Purnomo
Contributor: T. Dzulfikar S. Rambe
Creator: Eleanor M. Slade
Contributor: Soeprapto Soeprapto
Creator: Sudharto Ps
Creator: Suhardi Suhardi
Contributor: Ribka Sionita Tarigan
Creator: Resti Wahyuningsih
Contributor: Rudy Harto Widodo
Creator: Jean-Pierre Caliman
Contributor: Jake L. Snaddon ORCID iD
Creator: William A. Foster
Creator: Edgar C. Turner

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