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Keywords:

  • agricultural biodiversity;
  • disturbance;
  • field boundary habitat;
  • land use intensification;
  • marginal land;
  • native plant species;
  • weed distribution

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Agroecosystems are increasingly recognized as both sources and sinks of non-native weedy plant species as well as of native plant species, thus management of these systems has important implications for the composition of plant communities and landscape diversity. We quantified the distribution and abundance of both native and non-native plant species along a habitat gradient representing four management zones: managed agroecosystem, the agroecosystem boundary, ecotone, and neighbouring native forest for two land uses: kiwifruit orchards and neighbouring grassland agroecosystems. Native plant species diversity was highest in forest zones, and declined significantly with increasing non-native plant diversity across all management zones. The negative relationship between native and non-native plant species richness and diversity across all management zones was surprising, and contrasts with most ecological literature. Further, non-native plant species that have the largest ecological or ecosystem impacts were most abundant in ecotones, but were largely absent from managed zones and their margins. Our results suggest that agroecosystems and neighbouring vegetation can harbour native species, but can also be a source of non-native invasive weeds. These results highlight that agricultural margins contain both native plant diversity and environmental weeds, and that management of these margins affects diversity both on and off the farm.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Agroecosystems are increasingly recognized as both sources and sinks of non-native weedy plant species as well as of native plant species. Management of these systems thus has important implications for the composition of plant communities and landscape diversity (Kleijn et al. 2006, 2009; Batáry et al. 2011). For example, agri-environment schemes are an important mechanism for improving biodiversity on farmland as well as surrounding landscapes (Weibull et al. 2003; Gibson et al. 2007; Whittingham 2007, 2011; Pywell et al. 2010). The relative abundance of both native and non-native species responds strongly, but differently, to changes in land use and management intensity along gradients from core agricultural areas to marginal or edge habitats (Boutin & Jobin 1998; Weibull et al. 2003; Sosnoskie et al. 2007; Ernoult & Alard 2011; Kenward et al. 2011). For example, ecological refuges in edge habitats are thought to be an important resource for farmland wildlife, including birds, mammals, invertebrates and plants (Kromp & Steinberger 1992; Le Coeur et al. 1997; Gillings & Fuller 1998; Vickery et al. 2009). Field margins may also provide buffering against weed invasion from surrounding lands into agroecosystems and vice versa, and thus maintain diversity both on and off agroecosystems (Moonen & Marshall 2001; Olson & Wackers 2007; Boutin et al. 2008). As a consequence, some countries have created incentives for farmers to set aside refuge areas; for example, farmers in Switzerland who set aside at least 7% of their farmland receive a financial subsidy for this activity (Gibson et al. 2007).

Native species may persist within agroecosystems or be retained in marginal lands outside of productive management areas. However, the influence of different land management on biodiversity in marginal lands is poorly understood (Bestelmeyer et al. 2003; Berendse et al. 2004; Quétier et al. 2007; Lee et al. 2008; Moller et al. 2008). Non-native or weedy plant species may also persist within, or invade into, both agroecosystems and neighbouring lands. However, the importance of managing weeds in semi-natural habitats that are adjacent to farm fields is unclear. Vegetation in agroecosystem margins may harbour pests or pathogens and may also serve as source populations for ongoing immigration of weeds into production areas (Romero et al. 2008). It is also possible, however, that margin vegetation provides habitat for organisms, such as bird species, that consume weed seeds or reduce the likelihood of pest or pathogen outbreak (MacLeod et al. 2008).

An unresolved issue in ecology is the relative importance of biological and anthropogenic factors in controlling the diversity of co-occurring native and non-native plant species. Biological traits often differ among co-occurring native and non-native plant species, with non-natives having functional traits associated with relatively rapid nutrient uptake, use and growth (Peltzer et al. 2009; van Kleunen et al. 2009; Kurokawa et al. 2010). However, anthropogenic factors such as increased propagule pressure or overcoming dispersal limitation can overwhelm biological traits that confer invasion success (Gravuer et al. 2008; Alexander et al. 2012; McGregor et al. 2012). For example, many environmental weeds arise from the naturalization of cultivated species, and this anthropogenic propagule pressure is a stronger driver of non-native plant species naturalization and abundance than the biological traits of species (Reichard & White 2001; Sax et al. 2007; Gravuer et al. 2008; Cordeau & Reboud 2010; McGregor et al. 2012). In New Zealand, about 80% of environmental weed species that are managed by government agencies arise from garden dumping in marginal habitats, or through the naturalization of economic plant species outside of cultivation (Sullivan et al. 2004, 2005; Williams & Cameron 2006; Pyšek et al. 2009). Furthermore, land use and management manipulate both disturbance regime and primary productivity, and these are common drivers controlling the relationship between native and non-native diversity (Sandel & Corbin 2010; Laliberté et al. 2013; Tomasetto et al. 2013).

Here we quantified the distribution and abundance of both native and non-native plant species along a management intensity gradient from agroecosystems managed either for kiwifruit production (Actinidia deliciosa (A.Chev.) C.F.Liang & A.R.Ferguson (1984), Actinidiaceae) or as pastoral grassland systems, to unmanaged marginal areas, and finally to neighbouring native forest habitats. We surveyed plant communities in managed agroecosystems, the agroecosystem boundary, ecotones, and neighbouring indigenous forest communities. We further provide a detailed assessment of weed risk in relation to habitat zone and agroecosystem management by assessing the distribution and abundance of low- versus high-impact (sensu Parker et al. 1999) weeds along these management intensity gradients. We used these data to determine if weed risk is higher for indigenous forest patches neighbouring kiwifruit orchards compared with grassland agroecosystems. In addition, we determined if weed species composition in the ecotone zones could be used as a sentinel (i.e. warning) system for monitoring weed risk in neighbouring forest systems and production areas (Fig. 1). This information will be used to assess the potential risks that weeds pose to plant biodiversity in neighbouring ecotone and forest systems and to optimize weed management efforts in the region, but the approach used here can be widely applied to a range of agroecosystems.

figure

Figure 1. Conceptual figure for assessing weed risk across land use types on kiwifruit and non-kiwifruit (pastoral grassland) agroecosystems. We predict that weed species richness and abundance will be highest in Boundary and Ecotone management zones, and that if kiwifruit orchard management promotes weed establishment from production or forest habitats compared with neighbouring pastoral grassland systems, then there should be an increased weed forcing in marginal habitats (vertical line).

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Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Data for New Zealand kiwifruit farms

This study focused on the agroecosystems in the Te Puke, Western Bay of Plenty region of New Zealand. Plant biodiversity surveys were undertaken on 18 properties managed either as kiwifruit orchards or as pastoral grassland systems. In all cases, properties were adjacent to native forest habitats located within neighbouring unmanaged gully systems. This study system allowed us to determine whether weed risk in forest systems was greater in areas bordering kiwifruit orchards than those adjacent to non-kiwifruit grassland properties or vice versa.

The distribution and abundance of native and non-native plant species was quantified on 12 kiwifruit orchards and six grassland (grazing or hay meadow) properties. Plant community composition surveys were carried out along transects located in each of four zones within each property: in managed production areas (either kiwifruit orchards or grasslands), edge or boundary habitat (shelterbelts or along fence lines), ecotone zones (transition areas between boundary areas and adjacent forest systems, thus ‘ecotones’ here are defined spatially as the transition from productive to conservation land uses) and, from the top to bottom of gully systems dominated by native forests. Transects were a maximum of 150 m long and either followed a linear feature (e.g. fence line or parallel or perpendicular to the forest gully top), or diagonally across a paddock or orchard block for the managed zone. Surveys of both production and non-production areas provide a context for interpreting ecotone zone results. For example, we aimed to determine whether properties having diverse weed communities within their production areas are more prone to weed invasions within the ecotone zones and forest systems (Fig. 1).

Our study utilized a ‘natural experiment’ of variation in land cover and use to determine the effects of land management on the distribution and abundance of both native and non-native plant species. These treatments represent a complex gradient from indigenous forest occurring on steep slopes, receiving no management, and having modest disturbance from windthrow and animal activities to managed production areas characterized by grazing from domestic animals, herbicide application, and fertilization. This shift from forest vegetation to more intensive land use thus represents a complex environmental gradient. This complexity makes identifying specific drivers of native and non-native plant diversity difficult, but our study provides information on emergent patterns in native and non-native plant communities among land uses and management that is generalizable.

All data were collected in the Austral summer of 2009/2010. Plant species identity, presence and abundance (cover) were quantified using standard approaches (Hurst & Allen 2007) in 2 × 2 m quadrats located at 25 m intervals along each transect (total of 466 survey quadrats). Plant names follow the Allan Herbarium (2000). All plant species were classified into one of six categories based on weed risk assessment criteria as follows: 1: Indigenous (native) plant species, and five classes of non-native plant species; 2: Common non-native and garden escapes, for example, cleavers (Galium aparine) or wild strawberry (Fragaria vesca); 3: Regional Surveillance and National Pest Plant Accord (NPPA) weeds, for example, jasmine (Jasminum polyanthum) or Japanese honeysuckle (Lonicera japonica); 4: Boundary Control weeds, for example, gorse (Ulex europaeus) or blackberry (Rubus fruticosa); 5: Progressive Control weeds, for example, wild ginger (Hedychium gardnerianum) or woolly nightshade (Solanum mauritianum); and 6: Total Control weeds, for example, wilding kiwifruit (Actinidia deliciosa). This classification of plant weed status is based on the regional government's (Bay of Plenty) Pest Management Strategy 2003–2008, the Ministry of Agriculture and Forestry (2008) for management of undesirable pest plant species, and standard weed risk assessment criteria (Pheloung et al. 1999). Here we distinguish amongst non-native plant species that are considered widespread but relatively low impact weeds (sensu Parker et al. 1999) from species that have large, negative impacts on native biodiversity or other ecosystem properties (e.g. Tradescantia fluminensis, Williams & West 2000; Williams et al. 2003; Standish et al. 2004). These categories represent a multinomial variable, ranking species desirability (i.e. highest for native species) and their perceived negative impact on native biodiversity or ecosystem properties.

Data analysis

Data exploration and summary, and calculation of species richness and diversity of both native and non-native plant species were conducted for individual plots using JMP (version 6.03, SAS Institute Inc 2007). Differences in species richness and diversity were assessed using nested anova; management zone (fixed effect) was nested with agroecosystem types (kiwifruit orchard or grassland). Transects were treated as random effects within zone × property treatment combinations using the GLM package in R version 2.12.2 (R Development Core Team 2010). GLMs were also used to determine the effects of non-native plants on native species abundance or diversity by including non-native plant species abundance or diversity as a covariate in the analyses. As with any survey of communities, we may have imperfect detection and unequal replication among land management zones; however, these issues do not undermine our statistical analyses or data interpretation. This is because our analyses compared species richness at the plot-level, and we do not make claims about total species richness or accumulation among treatments (i.e. between agroecosystem types or management zones). In addition, Bayesian analyses were applied to this dataset to resolve issues of weed species detectability and accumulation amongst the treatments considered; these analyses yielded results identical to those presented in the original (results not presented here).

Variation in the abundance of plant weed classes among agroecosystem types and management zones was assessed using logistic regression in the GLM package of R; these analyses were restricted to weed Classes 2–5 because Class 1 represents native plants rather than weeds, and Class 6 weeds were observed in only two instances (i.e. naturalized kiwifruit plants were observed at two forest locations only). Plant community compositional shifts were determined by summarizing species compositional data as ordination axes using Non-Metric multi-Dimensional Scaling (NMDS), and then comparing changes in these axes to agroecosystem and zone-type using redundancy analyses (RDA) and permutational procedures of ADONIS in the VEGAN package of R version 2.12.2 (R Development Core Team 2010).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Native species

About 40% of the plant species observed in the study region were native (96 of the 239 plant species observed). Native plant species were observed in all management zones, with the highest species richness and Shannon diversity in forest (Table 1). Native plant abundance (cover for all and individual species) was lowest in the managed zone compared with other zones (Table 2; Fig. 2).

figure

Figure 2. Mean cover (%) of individual species within 4 m2 plots for native versus non-native plant species in Managed, Boundary, Ecotone, and Forest management zones. Zones represent a gradient of management intensity from the centre of managed agroecosystems to adjacent unmanaged native forest vegetation. Data are shown across agroecosystem-types because the interaction between habitat and plant status (native vs. non-native status in New Zealand) was significant whereas interactions involving land use and other factors were not (see Results section). Total covers of native and weed species are presented in Table 2. Results for individual species are in Appendix S3.

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Table 1. Summary of mean species richness (S) and diversity (H′) for non-native (weeds) and native plant species observed within 2 × 2 m plots established in combinations of four habitat-types or management zones: Managed (paddock), Boundary (farm edge), Ecotone (transition zone), and Forest (native bush) and in each of two land uses: kiwifruit orchards or pastoral grassland
Management ZoneManaged Boundary Ecotone Forest 
Land useKiwifruitGrasslandKiwifruitGrasslandKiwifruitGrasslandKiwifruitGrassland
  1. N plots’ is the total sample size across Management Zone and Land use treatment combinations. s.e.m., standard error of the mean.

N plots894610451199849354
Mean S natives0.491.390.911.452.001.137.427.17
s.e.m.0.080.090.090.130.240.200.290.31
H′ natives0.080.350.190.340.440.251.451.41
s.e.m.0.010.010.020.030.050.050.040.05
S weeds10.848.1210.139.764.234.970.480.51
s.e.m.0.430.440.300.490.350.340.150.19
H′ weeds1.701.441.651.560.831.060.070.09
s.e.m.0.040.050.040.060.060.070.020.04
Table 2. Summary of mean total cover (%) (1 s.e.m.) across all plant species assigned to different plant functional groups or classes (see Methods for details): native species (Class 1) and non-native plant species (Classes 2–6) observed in combinations of four habitat-types or management zones: Managed (paddock), Boundary (farm edge), Ecotone (transition zone), and Forest (native bush) and two land uses: kiwifruit orchards or pastoral grassland
Management ZoneManagedBoundaryEcotoneForest
Land useKiwifruitGrasslandKiwifruitGrasslandKiwifruitGrasslandKiwifruitGrassland
  1. Total cover can exceed 100% because of overlapping vertical tiers of vegetation. N plots is the total sample size across Management Zone and Land use treatment combinations. s.e.m., standard error of the mean.

N plots894610451199849354
Native species (1)22.56.255.4211.542.044.296.584.2
(7.22)(3.75)(1.65)(3.67)(6.39)(8.89)(4.59)(5.0)
Minor weeds (2)167192137.3191.861.592.311.149.29
(10.3)(11.7)(6.54)(11.0)(5.95)(8.64)(4.55)(3.77)
Moderate weeds (3)18.8023.6043.744.311.535.6
(7.2)(0)(6.59)(0)(4.93)(7.34)(3.67)(11.5)
Major weeds (4)02.5018.840.022.148.3310.0
(0)(0)(0)(16.3)(5.61)(6.03)(5.83)(7.5)
Containment weeds (5)000013.817.52.50
(0)(0)(0)(0)(3.75)(0)(0)(0)
Eradication weeds (6)0000002.50
(0)(0)(0)(0)(0)(0)(0)(0)

Native plant diversity was significantly lower in kiwifruit orchards compared with grassland systems for managed and boundary zones, but not for ecotones or forests (Fig. 3, Table 1; GLM on native H′: Zone effect: F3,458 = 245.6, P < 0.001, Kiwifruit effect: F1,458 = 18.2, P < 0.001, Zone × Kiwifruit interaction: F3,458 = 28.9, P < 0.001). Means contrasts revealed that native species diversity was much higher in neighbouring forest compared with all other zone and agroecosystem combinations, and that both managed and boundary zones of kiwifruit orchards had significantly lower diversity than all other combinations. Similarly, native plant diversity in ecotones was significantly lower in grassland than kiwifruit agroecosystems. However, native plant diversity was intermediate in ecotone and boundary and lowest in managed zones for kiwifruit orchards whereas it was intermediate for boundary and managed and lowest in ecotone zones for grassland systems.

figure

Figure 3. Relationships between native and non-native plant diversity in Managed, Boundary, Ecotone, and Forest management zones. These zones represent a gradient of management intensity from the centre of managed agroecosystems to adjacent unmanaged native forest vegetation. In all cases, native plant diversity declined with increasing non-native plant diversity, albeit modestly in Managed and Boundary zones. Native plant diversity was highest in Forests, intermediate in Ecotones, and lowest in managed zones. A significant interaction between weed diversity and management zone was caused by the relatively strong negative association between native and non-native plant diversity in Ecotones (see Results section).

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Across both kiwifruit and grassland systems, native plant species richness was highest in forests > ecotones > boundaries = managed zones. Further, kiwifruit orchards had similar level of native species richness in forests and ecotones, but relatively low native plant species richness in managed and boundary zones compared with grassland systems (Table 1; GLM on native S: Zone effect: F3,458 = 395.6, P < 0.001, Kiwifruit effect: F1,458 = 0.275, P = 0.610, Zone × Kiwifruit interaction: F3,458 = 6.84, P < 0.001).

The total cumulative cover of native species increased from 1 to 2% in managed and boundary zones to about 27% in ecotones and 90% in forest; although there was a tendency for kiwifruit orchards to have higher total native plant cover than grassland systems, the shift in dominance toward native species did not differ between agroecosystem types (Table 2; GLM for native species cover: Zone effect: F3,458 = 222.5, P < 0.001, Kiwifruit effect: F1,458 = 3.47, P = 0.063, Zone × Kiwifruit interaction: F3,458 = 1.02, P = 0.384). In summary, all management zones contained native plant species, and further, agroecosystem-type and management zone interacted to influence the abundance and diversity of native plant species in this system.

Weed species

Almost two-thirds, or 143 of the 239 plant species observed, were non-native naturalized species. Non-native plant diversity was higher in kiwifruit orchards compared with grassland systems for managed and boundary zones, but lower in ecotones or forests (Table 1, Fig. 3; GLM on non-native H′: Zone effect: F3,458 = 397.5, P < 0.001, Kiwifruit effect: F1,458 = 0.577, P = 0.448, Zone × Kiwifruit interaction: F3,458 = 8.26, P < 0.001). Managed and boundary zones had about twice the weed diversity of ecotones, and about 20-fold higher weed diversity than forests irrespective of land use.

Non-native plant species richness was about 9–10 per plot in managed and boundary zones, about half of this in ecotones, and only 0.49 in forests (Table 1). Across zones, kiwifruit orchards had, on average, about one more non-native plant species per plot compared with grassland systems. A significant interaction between kiwifruit production and zone was driven by managed and boundary zones having about one more non-native species in kiwifruit orchards, but about 0.42 species less in ecotones and forests compared with grassland systems (Table 1; GLM on weed S: Zone effect: F3,458 = 279.9, P < 0.001, Kiwifruit effect: F1,458 = 4.71, P = 0.030, Zone × Kiwifruit interaction: F3,458 = 7.92, P < 0.001).

Surprisingly, native plant species richness and diversity both declined significantly with increasing non-native richness or diversity; this result was robust across and within all management zones (Fig. 3; GLM of native H′: Non-native species H′ effect: F3,450 = 58.8, P < 0.001, Zone effect: F3,450 = 10.2, P < 0.001, Kiwifruit effect: F1,450 = 1.95, P = 0.163, Zone × Kiwifruit interaction: F3,450 = 4.06, P = 0.007, Weed H′ × Zone effect: F3,450 = 10.2, P ≤ 0.001, other interactions were not significant). However, this negative association between native and non-native plant diversity was relatively weak in managed and boundary zones (Fig. 3).

Non-native plant species were further categorized into six classes, based on expert opinion on their ability to invade and have negative impacts in systems (see Methods; Class 2 represents the lowest impact weeds). Class 2 weeds dominated managed and boundary zones, had about half this abundance in ecotones, and were nearly absent in forests (Table 2). Class 3 weeds were most abundant (44% cover) in the ecotones of kiwifruit orchards and grassland systems, but were much less common in all other zones. Classes 4 and 5 weeds were much more common in ecotones (about 31% and 15% cover) than all other zones (which had much less than 10% cover) irrespective of agroecosystem type. Non-native plant species thought to have the largest effects (i.e. Class 6 weeds) were very uncommon and their abundance did not differ with zone or agroecosystem. Considered simultaneously, weed abundance varied with all factors considered (GLM/logistic regression of weed classes: Zone effect: L-R χ215d.f, = 3087, P < 0.001, Kiwifruit effect: L-R χ25d.f. = 20.5, P = 0.001, Zone × Kiwifruit: L-R χ215d.f. = 28.3, P = 0.020). These effects were caused by Kiwifruit orchards having fewer Class 2 weeds, more Class 3 weeds, but similar abundance of other weed classes compared with grassland properties. Similarly, managed and boundary zones had relatively greater abundance of Classes 2 and 3 (minor) weeds, but much fewer Classes 4 or 5 weeds than did ecotone or forest zones (Table 2). Wild kiwifruit, the only Class 6 weed species encountered, was observed twice in forests, once in on each of two kiwifruit properties.

Community compositional shifts

Dominant species shifted in a predictable way from kiwifruit orchards or grassland paddocks through to ecotones and forests across native and non-native species. Managed and boundary zones were dominated by small native herbs (e.g. Hydrocotyle moschata, Euchiton involucratus, Cardamine hirsuta, Geniostoma rupestre) and larger European grasses and herbs (e.g. Ranunculus repens, Lolium spp., Bromus diandrus, Paspallum spp., Plantago lanceolata, Mycelis muralis, Trifolium repens, Holcus lanatus). Ecotone zones shifted to dominance by native ferns, shrubs and juvenile tree species (e.g. Blechnum chambersii, Muehlenbeckia australis, Cyathea medullaris, Pneumatopteris pennigera, Brachyglottis repanda, Knightia excelsa, Pteridium esculentum, Melicytus ramiflorus) whereas the non-native species were a mix of shrubs and large grasses (Ulex spp., Rubus phoenicolasius, Bromus diandrus, Lonicera japonica, Rubus fruticosus, Anthoxanthum odoratum) with the exception to this being the rhizomatous herb Tradescantia fluminensis. In forests, native species were dominated by ferns and short-statured trees (e.g. Cyathea dealbata, Blechnum novae-zelandiae, Melicytus ramiflorus, Hedycarya arborea, Knightia excelsa) whereas non-natives were dominated by shrubs (Lonicera japonica, Ligustrum lucidum, Solanum nigrum, Actinidia spp., Berberis glaucocarpa) and Tradescantia.

Plant species composition shifted strongly and predictably from managed zones to neighbouring forest zones, and also differed between kiwifruit orchards or grassland systems (Fig. 4) (GLM on RDA axis 1: Zone effect: F3,458 = 481.7, P < 0.001, Kiwifruit effect: F1,458 = 1.89, P = 0.170, Zone × Kiwifruit interaction: F3,458 = 2.22, P = 0.085; RDA axis 2: Zone effect: F3,458 = 48.8, P < 0.001, Kiwifruit effect: F1,458 = 143.8, P < 0.001, Zone × Kiwifruit interaction: F3,458 = 9.13, P < 0.001; results from ADONIS permutational tests were identical). The compositional shift represented by RDA axis 2 is from low-statured light-demanding weedy species such as Pteridium esculutum, Daucus carota, Digitalis purpurea, Hieracium pilosella (all high positive loadings) to dominance by ferns common in forest understory including Blechnum discolor, Polystichum richardii, Asplenium spp. and shade-tolerant native tree species (see also Appendices S1–S3). The significant effects of kiwifruit production and interaction with zone are because of relatively high abundance of more shade-tolerant species, particularly in managed zones for kiwifruit orchards compared with grassland systems.

figure

Figure 4. Community compositional shifts for vascular plant species observed in Managed, Boundary, Ecotone, and Forest zones in each of two land uses: kiwifruit production or grassland agroecosystems. These zones represent a gradient of management intensity from managed agroecosystems to adjacent unmanaged native forest vegetation. The first two axes of a redundancy analysis are shown: Managed and Boundary zones were distinguished from Ecotone and Forest zones, but kiwifruit and grassland agroecosystem land uses were not (see also Appendices S1,S2 for further details). RDA, redundancy analyses.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Our results suggest that agroecosystems and associated marginal habitats contain both native plant species and potential environmental weeds; this highlights the balancing act that land managers face trying to ensure that management has positive effects on native diversity, while minimizing the risk of negative effects via promotion of weeds. Our main finding is that more native plant species, but fewer weed species, were observed in the ecotone between kiwifruit orchards and neighbouring native forest vegetation than were observed in the ecotones of co-occurring grassland agroecosystems (Table 1). Thus, for the spatial scale considered in our study (i.e. the 2 × 2 m plot level), there was no support for the view that kiwifruit orchards have greater weed forcing in ecotones (or forests) compared with nearby pastoral grassland systems (Fig. 1).

Changes in native and non-native species along the management gradient

Indigenous plant species comprised about a third of the species recorded in the study region, and the total abundance of these species increased by an order of magnitude from managed to ecotones or adjacent native forest (Table 2; see also Appendix S3). The plant community composition shifted in predictable ways from managed and boundary to ecotone and forest zones. For native species, this shift was from dominance by short-statured herbaceous species to dominance by ferns, shrubs and trees. Native species observed in managed and boundary zones were typically small-statured native herbs such as Hydrocotyle moschata, Euchiton involucratus and Cardamine hirsuta that persist in short-statured vegetation characterized by frequent disturbance. In ecotones, native species were dominated by a greater functional diversity of plant species including ferns (e.g. Blechnum chambersii, Cyathea medullaris, Pteridium esculentum), shrubs (Muehlenbeckia australis, Brachyglottis repanda) and juvenile individuals of tree species (e.g. Knightia excelsa, Melicytus ramiflorus). These native species are relatively widespread in New Zealand and do not represent rare or endangered taxa (Allan Herbarium 2000), however, they commonly dominate forest succession and thus play an important role in driving vegetation change (Wardle 1991).

The community shift for non-native species from managed to boundary zones was from widespread European pasture grasses and herbs to shrubs (see ordination results above). Many of these species are both widespread and abundant in New Zealand, and form the basis of many pastoral systems (e.g. the grasses Anthoxanthum odoratum, Dactylis glomerata, Holcus lanatus, and the N-fixing forb Trifolium repens). However, a few non-native species that are known to have large, negative impacts on native biodiversity or other ecosystem properties were present. For example, the clonal herb Tradescantia fluminensis was present in kiwifruit orchard boundaries, and has well documented negative impacts on litter-dwelling invertebrates, and the regeneration of indigenous tree species (Williams & West 2000; Williams et al. 2003; Standish et al. 2004). Similarly, native forests and ecotones are an important habitat for non-native weed species. For example, the shade-tolerant and high-impact invasive shrubs Lonicera japonica, Ligustrum lucidum, Solanum nigrum and Berberis glaucocarpa were observed only in forest and ecotone zones; although each of these species was observed in <10 plots (Appendix S3), all can persist in forest understories and are managed as environmental weeds. These and other non-native species are managed as environmental weeds to mitigate their negative impacts on indigenous biodiversity or alter ecosystem processes and services (Howell 2008; Peltzer et al. 2009, 2010).

There were few shared species between managed zones and those outside of management (i.e. ecotones and forests) for both native and non-native species. As a consequence, almost no weed species found within the managed zone were shared with unmanaged habitats (Appendix S3). An important exception to this was naturalized kiwifruit that was observed in two forest plots, suggesting kiwifruit production per se may not be a major source of new weeds into indigenous habitats. However, this observation may be because of successful weed control by regional government in order to prevent the spread of these weeds (Sullivan & Hutchison 2010), because time as naturalization has not been sufficiently long for these weeds to be abundant (Lockwood et al. 2005; Daehler 2009; Pyšek et al. 2009), or because there is an interaction between kiwifruit naturalization and dispersal agents like birds such that fruit size must first be sufficiently small in order to be eaten and dispersed (Logan & Xu 2006; J.J. Sullivan, 2011, pers. comm.). In general, kiwifruit orchards are not currently associated with increased numbers of invasive weed species at the spatial scale of our study (Tables 1, 2, Fig. 2; see also Pelosi & Goulard 2010).

If the land use of neighbouring properties is changed from grassland systems to farm forests, we would expect there to be a migration of woody weeds from forests into these systems. Although we did not determine the source of weed populations in forest gully systems, anecdotal evidence suggests that dumping of garden waste and seed dispersal by birds have both created nascent foci for non-native species. Similarly, Sullivan et al. (2004, 2005) found that the richness and abundance of environmental weeds is strongly associated with garden dumping and close proximity to urban areas. On the other hand, weed species in agroecosystems rarely also occurred in neighbouring ecotone or forest habitats, even though some weeds such as the grasses Holcus lanatus and Bromus diandrus, and the shrub Ulex europeaus persist at much lower abundance in forest canopy gaps (M. Perry, 2011, pers. comm.). In summary, our findings demonstrate that there are distinct communities of both native and non-native plant species between managed and unmanaged habitats. We also suggest that a two-way flow of species between managed and unmanaged systems is unlikely because of the coincident shift from grassland (managed) to forest (unmanaged) vegetation in this system.

In contrast to previous studies (Stohlgren et al. 2006; Fridley et al. 2007), native plant diversity was negatively associated with non-native plant diversity across all habitats for both kiwifruit and grassland systems. This negative association held across changes in plant growth-form and species composition associated with shifts from herbaceous and grass-dominated managed systems, to shrub-dominated ecotones, to tree-dominated native forests (ordination results for changes in plant community composition above; see also Appendices S1,S2). The negative relationship between native and non-native plant species richness and diversity across all management zones was surprising, and highly robust given the distinct native and non-native plant communities observed in managed and unmanaged habitats here. The cause and effect of this relationship cannot be determined using our community compositional data, but could be disentangled using appropriate manipulative field experiments or more complex spatial analyses (Peltzer et al. 2009; see also Pelosi & Goulard 2010; Ernoult & Alard 2011).

Land use comprises a suite of management activities, and these differ considerable between kiwifruit and grassland land uses. For example, grassland systems are seasonally grazed by domestic stock and receive relatively low inputs of fertilizer and or herbicide use whereas kiwifuit orchards are typically ungrazed and have moderate herbicide application (Steven & Benge 2007; Macleod et al. 2012). Similarly, although disturbance regimes increase in magnitude and frequency in managed systems, forests are not undisturbed, but rather have a history of canopy disturbance through windthrow, soil erosion (because of their location in gullies), introduced pest animals, and fire (Wardle 1991). Our results above thus demonstrate that the different subsets of native and weed species observed across habitat-types are driven by a complex set of mechanisms associated with different land uses (see also Macleod & Moller 2006; Lee et al. 2008). This further highlights the issue that land use and intensification comprises a complex suite of inputs and management activities. More generally, managed systems alter species composition, resource availability and disturbance regime, which interact to determine the balance between native and non-native species (Sandel & Corbin 2010; Laliberté et al. 2013; Tomasetto et al. 2013). The effects of land use and management per se on native and non-native plant species require additional information on resource manipulations and disturbance.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We thank Jacinda Woolly, Sean Brill, Mike Perry, Chris Mckay, Bill Kent, Sara Brill, Walter Stahel, Bob Mankelow, Rob Fraser and Ines Schönberger for field data collection or assisting with plant identification. We also thank Henrik Moller, Alistair Mowat, John Mather and Jayson Benge for helpful discussion or providing logistic support, and two anonymous referees for thorough and helpful comments on this manuscript. We warmly acknowledge financial support from Zespri Group Limited, the Environment Bay of Plenty and by Core funding for Crown Research Institutes from the New Zealand Ministry of Business, Innovation and Employment's Science and Innovation Group.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • Alexander H. M., Foster B. L., Ballantyne F. IV, Collins C. D., Antonovics J. & Holt R. D. (2012) Metapopulations and metacommunities: combining spatial and temporal perspectives in plant ecology. J. Ecol. 100, 88103.
  • Allan Herbarium (2000) Ngā Tipu o Aotearoa – New Zealand Plant Names Database. Landcare Research, New Zealand. [Cited 9 December 2012.] Available from URL: http://nzflora.landcareresearch.co.nz/
  • Batáry P., Báldi A., Kleijn D. & Tscharntke T. (2011) Landscape-mediated biodiversity effects of agri-environmental management – a meta-analysis. Proc. Roy. Soc. B, Biological Sciences 278, 18941902. doi: 10.1098/rspb.2010.1923.
  • Berendse F., Chamberlain D., Kleijn D. & Schekkerman H. (2004) Declining biodiversity in agricultural landscapes and the effectiveness of agri-environment schemes. Ambio 8, 499502.
  • Bestelmeyer B. T., Miller J. R. & Wiens J. A. (2003) Applying species diversity theory to land management. Ecol. Applic. 13, 17501761.
  • Boutin C., Baril A. & Martin P. A. (2008) Plant diversity in crop fields and woody hedgerows of organic and conventional farms in contrasting landscapes. Agric. Ecosyst. Environ. 123, 185193.
  • Boutin C. & Jobin B. (1998) Intensity of agricultural practices and effects on adjacent habitats. Ecol. Applic. 8, 544557.
  • Cordeau S. & Reboud X. (2010) Relative importance of farming practices and landscape context on the weed flora of sown grass strips. Agric. Ecosyst. Environ. 139, 595602.
  • Daehler C. C. (2009) Short lag times for invasive tropical plants: evidence from experimental plantings in Hawai'i. PloS ONE 4, e4462. doi:10.1371/journal.pone.0004462.
  • Ernoult A. & Alard D. (2011) Species richness of hedgerow habitats in changing agricultural landscapes: are α and γ diversity shaped by the same factors? Landsc. Ecol. 26, 683696.
  • Fridley J. D., Stachowicz J. J., Naeem S. et al. (2007) The invasion paradox: reconciling pattern and process in species invasions. Ecology 88, 317.
  • Gibson R. H., Pearce S., Morris R. J., Symondson W. O. C. & Memmott J. (2007) Plant diversity and land use under organic and conventional agriculture: a whole-farm approach. J. Appl. Ecol. 44, 792803.
  • Gillings S. & Fuller R. J. (1998) Changes in bird populations in sample lowland English farms in relation to loss of hedgerow and other non-crop habitats. Oecologia 116, 120127.
  • Gravuer K., Sullivan J. J., Williams P. A. & Duncan R. P. (2008) Strong human association with plant invasion success for Trifolium introductions to New Zealand. Proc. Natl acad. Sci. USA 105, 63446349.
  • Howell C. (2008) Consolidated List of Environmental Weeds in New Zealand. DRDS292. Department of Conservation, Wellington. ISBN 978-0-478-14413-0.
  • Hurst J. M. & Allen R. B. (2007) A permanent plot method for monitoring indigenous forests- expanded manual, version 4. Landcare Research Contract report LC0708/028.
  • Kenward R. E., Whittingham M. J., Arampatzis S. et al. (2011) Identifying governance strategies for the effective conservation of biodiversity. Proc. Natl acad. Sci. USA 108, 53085312.
  • Kleijn D., Baquero R. A., Clough Y. et al. (2006) Mixed biodiversity benefits of agri-environment schemes in five European countries. Ecol. Lett. 9, 243254.
  • Kleijn D., Kohler F., Báldi A. et al. (2009) On the relationship between land-use intensity and farmland biodiversity in Europe. Proc. Roy. Soc. B, Biological Sciences 276, 903909.
  • Kromp B. & Steinberger K. H. (1992) Grassy field margins and arthropod diversity: a case study on ground beetles and spiders in eastern Austria (Coleoptera: Carabidae; Arachnida: Aranei, Opiliones). Agric. Ecosyst. Environ. 40, 7193.
  • Kurokawa H., Peltzer D. A. & Wardle D. A. (2010) Plant ecophysiological traits, leaf palatability and litter decomposability of co-occurring native and invasive N-fixing species in a shrub community of New Zealand. Funct. Ecol. 24, 513523.
  • Laliberté E., Norton D. A. & Scott D. (2013) Contrasting effects of productivity and disturbance on plant functional diversity at local and metacommunity scales. J. Veg. Sci. 23, DOI: 10.1111/jvs.12044.
  • Le Coeur D., Baudry J. & Burel F. (1997) Field margins plant assemblages: variation partitioning between local and landscape factors. Land. Urb. Plan 37, 5771.
  • Lee W. G., Meurk C. D. & Clarkson B. D. (2008) Agricultural intensification: whither indigenous biodiversity? NZ J. Agric. Res. 51, 457460.
  • Lockwood J. L., Cassey P. & Blackburn T. (2005) The role of propagule pressure in explaining species invasions. TREE 20, 223228.
  • Logan D. P. & Xu X. (2006) Germination of kiwifruit, Actinidia chinensis, after passage through Silvereyes, Zosterops lateralis. NZ J. Ecol. 30, 407411.
  • McGregor K. F., Watt M. S., Hulme P. E. & Duncan R. P. (2012) What determines pine naturalization: species traits, climate suitability or forestry use? Divers. Distrib. 18, 10131023.
  • MacLeod C. J., Blackwell G. & Benge J. (2012) Reduced pesticide toxicity and increased woody vegetation cover on organic kiwifruit orchards enhances native bird densities. J. Appl. Ecol. 49, 652666. DOI: 10.1111/j.1365-2664.2012.02135.x.
  • MacLeod C. J., Blackwell G., Moller H., Innes J. & Powlesland R. (2008) The forgotten 60%: bird ecology and management in New Zealand's agricultural landscape. NZ J. Ecol. 32, 240255.
  • MacLeod C. J. & Moller H. (2006) Intensification and diversification of New Zealand agriculture since 1960: an evaluation of current indicators of land use change. Agric. Ecosyst. Environ. 115, 201218.
  • Ministry of Agriculture and Forestry (2008) National Plant Pest Accord Manual. MAF Biosecurity, Wellington.
  • Moller H., MacLeod C. J., Haggerty J. et al. (2008) Intensification of New Zealand agriculture: implications for biodiversity. NZ J. Agric. Res. 51, 253263.
  • Moonen A. C. & Marshall E. J. P. (2001) The influence of sown margin strips, management and boundary structure on herbaceous field margin vegetation in two neighbouring farms in southern England. Agric. Ecosyst. Environ. 86, 187202.
  • Olson D. M. & Wackers F. L. (2007) Management of field margins to maximize multiple ecological services. J. Appl. Ecol. 44, 1321.
  • Parker I. M., Simberloff D., Lonsdale W. M. et al. (1999) Impact: toward a framework for understanding the ecological effects of invaders. Biol. Invasions 1, 319.
  • Pelosi C. & Goulard M. (2010) The spatial scale mismatch between ecological processes and agricultural management: do difficulties come from underlying theoretical frameworks? Agric. Ecosyst. Environ. 139, 455462.
  • Peltzer D. A., Allen R. B., Lovett G. M., Whitehead D. & Wardle D. A. (2010) Effects of biological invasions on forest carbon sequestration. Global Change Biol. 16, 732746.
  • Peltzer D. A., Bellingham P. J., Kurokawa H., Walker L. R., Wardle D. A. & Yeates G. W. (2009) Punching above their weight: low-biomass non-native plant species alter soil properties during primary succession. Oikos 118, 10011014.
  • Pheloung P. C., Williams P. A. & Halloy S. R. (1999) A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. J. Environ. Manage. 57, 239251.
  • Pyšek P., Křivánek M. & Jarošík V. (2009) Planting intensity, residence time, and species traits determine invasion success of alien woody species. Ecology 90, 27342744.
  • Pywell R. F., Meek W. R. & Loxton R. G. (2010) Ecological restoration on farmland can drive beneficial functional responses in plant and invertebrate communities. Agric. Ecosyst. Environ. 140, 6267.
  • Quétier Q., Lavorel S., Thuiller W. & Davies I. (2007) Plant-trait-based modeling assessment of ecosystem-service sensitivity to land-use change. Ecol. Applic. 17, 23772386.
  • R Development Core Team (2010) R: A Language and Environment for Statistical Computing. Version 2.12.1. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0, [Cited 26 May 2011.] Available from URL: http://www.R-project.org/
  • Reichard S. H. & White P. (2001) Horticulture as a pathway of invasive plant introductions in the United States. Bioscience 51, 103113.
  • Romero A., Chamorro L. & Sans F. X. (2008) Weed diversity in crop edges and inner fields of organic and conventional dryland winter cereal crops in NE Spain. Agric. Ecosyst. Environ. 124, 97104.
  • Sandel B. & Corbin J. D. (2010) Scale, disturbance and productivity control the native-exotic richness relationship. Oikos 119, 12811290.
  • SAS Institute Inc (2007) JMP, Version 6. SAS Institute Inc., Cary, 1989–2007.
  • Sax D. F., Stachowicz J. J., Brown J. H. et al. (2007) Ecological and evolutionary insights from species invasions. TREE 22, 465471.
  • Sosnoskie L. M., Luschei E. C. & Fanning M. A. (2007) Field margin weed-species diversity in relation to landscape attributes and adjacent land use. Weed Sci. 55, 129136.
  • Standish R. J., Williams P. A., Robertson A. W., Scott N. A. & Hedderley D. I. (2004) Invasion by a perennial herb increases decomposition rate and alters nutrient availability in warm temperate lowland forest remnants. Biol. Invasions 6, 7181.
  • Steven D. & Benge J. (2007) Sprays on New Zealand kiwifruit – use patterns and outcomes. Proceedings of the Sixth International Symposium on kiwifruit. Volume 2. Acta Hortic. 735, 711717.
  • Stohlgren T., Flather C., Fuller P., Peterjohn B., Kartesz J. & Master L. (2006) Species richness and patterns of invasion in plants, birds, and fishes in the United States. Biol. Invasions 8, 427447.
  • Sullivan J. J. & Hutchison M. (2010) Cost-benefit analysis and impact assessment for the proposed Bay of Plenty Regional Pest Management Strategy. Preliminary assessment of pests of special concern: boundary control weeds. Bio-Protection Research Centre, Lincoln University, Lincoln, Canterbury.
  • Sullivan J. J., Timmins S. M. & Williams P. A. (2005) Movement of non-native plants into coastal native forests from gardens in northern New Zealand. NZ J. Ecol. 29, 110.
  • Sullivan J. J., Williams P. A., Cameron E. K. & Timmins S. M. (2004) People and time explain the distribution of naturalized plants in New Zealand. Weed Technol. 18, 13301333.
  • Tomasetto F., Duncan R. P. & Hulme P. E. (2013) Environmental gradients shift the direction of the relationship between native and alien plant species richness. Divers. Distrib. 19, 4959.
  • Van Kleunen M., Weber E. & Fischer M. (2009) A meta-analysis of trait differences between invasive and non-invasive plant species. Ecol. Lett. 13, 235245.
  • Vickery J. A., Feber R. E. & Fuller R. J. (2009) Arable field margins managed for biodiversity conservation: a review of food resource provision for farmland birds. Agric. Ecosyst. Environ. 133, 113.
  • Wardle P. (1991) Vegetation of New Zealand. Cambridge University Press, Cambridge.
  • Weibull A. C., Ostman O. & Granqvist A. (2003) Species richness in agroecosystems: the effect of landscape, habitat and farm management. Biodivers. Conserv. 12, 13351355.
  • Whittingham M. J. (2007) Will agri-environment schemes deliver substantial biodiversity gain, and if not why not? J. Appl. Ecol. 44, 15.
  • Whittingham M. J. (2011) The future of agri-environment schemes: biodiversity gains and ecosystem service delivery? J. Appl. Ecol. 48, 509513.
  • Williams J. A. & West C. J. (2000) Environmental weeds in Australia and New Zealand: issues and approaches to management. Austral Ecol. 25, 425444.
  • Williams P. A. & Cameron E. (2006) Creating gardens: the diversity and progression of European plant introductions. In: Biological Invasions in New Zealand. Ecological Studies, Vol. 186. (eds R. B. Allen & W. G. Lee ) pp. 3347. Springer, Berlin.
  • Williams P. A., Winks C. & Rijkse W. (2003) Forest processes in the presence of wild ginger (Hedychium gardnerianum). NZ J. Ecol. 27, 4554.

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
aec12043-sup-0001-si.docx1156K

Appendix S1. Plant species observed.

Appendix S2. Mean NMDS scores derived from plant species cover in each zone.

aec12043-sup-0002-si.xlsx28K

Appendix S3. Cover of each plant species in each zone.

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.