Grain-dependent responses of mammalian diversity to land-use and the implications for conservation set-aside
Yüklə 288,19 Kb.
|
- Bu səhifədəki naviqasiya:
- Figures Figure 1
- Appendices Appendix A: Detailed study site descriptions.
- Appendix B: Additional information on β-diversity quantification.
- Appendix C: Species accumulation curves.
- Appendix D: Additional results tables.
Figure Legends Figure 1. Sampling design across (a) old-growth forest, (b) oil palm and (c) logged forest used in this study, illustrating the three spatial grains within each land-use: individual sampling points, 1.75 ha rectangular plots (consisting of clusters of points) and blocks (consisting of clusters of plots). Blocks were arranged identically in old-growth forest and oil palm, and were arranged to coincide with future experimental forest fragments in logged forest. Separation between points, plots and blocks was nonetheless similar across land-uses. Shaded areas lie outside the Kalabakan Forest Reserve, consisting of a 2,200 ha Virgin Jungle Reserve (Brantian-Tatulit) to the south and an extensive (>1 million ha) area of logged forest to the north (Mount Louisa Forest Reserve and connecting reserves). Insets show the location within insular Southeast Asia and the spatial proximity of the three land-uses within southeast Sabah, Malaysian Borneo. Figure 2. Diversity partitions for all mammals, large mammals and small mammals across a gradient of land-uses, including observed values (± SD) at four spatial grains and estimated α- and γ-diversities (± 95% CI). Estimates of α-diversity (standardised to 90% sample coverage) are predictions from a mixed-effects model which accounted for the hierarchical nested sampling design. Estimates of γ-diversity were calculated using the Abundance-based Coverage Estimator (ACE). Observed β-diversity at a given spatial grain is the average richness at the given grain subtracted from that in the grain above (for example, βplot = αblock – αplot). Only data from sampling points which were both camera-trapped and live-trapped were used in this figure (see Supporting Information for full results). Figure 3. β-diversity differences from null models (± SE) with increasing spatial grain, for all mammals, large mammals and small mammals. Panels show results across a gradient of land-uses. The horizontal line at y=0 represents the case of no difference between observed β-diversity and expected β-diversity from null models. Dashed vertical lines show the three spatial grains of β-diversity sampling within each land-use (points, plots and blocks). Smoothed lines between data points are to aid interpretation. Overlapping data points have been spaced apart slightly. See Supporting Information for 95% CIs. Figure 4. Percentage of overall β-diversity generated by nestedness (variation in species richness without species composition changes) and species turnover (changes in species composition) across species groups and land-use types.
The Maliau Basin Conservation Area (1,054 km2 including the buffer zone), one of the last remaining examples of lowland undisturbed habitat in the region (Reynolds et al. 2011), represented our old-growth control site. The sampled area consisted mostly of pristine hill forest, dominated by dipeterocarps including Shorea johorensis, Dryobalanops lanceolata and Parashorea melaanonan. One-third of the sampled sites (lying within the buffer zone) were in a water catchment that had been subjected to low levels of ironwood (Eusideroxylon zwageri) extraction in the 1970s and 1990s; some old skid-trails were present in the area, though the structure and community composition of the canopy and understorey were comparable to the surrounding unlogged forest (Ewers et al. 2011). Part of the Kalabakan Forest Reserve (2,240 km2), the SAFE Project experimental area (94 km2 including a Virgin Jungle Reserve) represented our logged forest site. This was connected to a large (> 1 million ha) area of logged forest to the north and was otherwise surrounded by oil palm plantations. Similar to our old-growth forest site, the SAFE Project experimental area was composed of hill dipterocarp forest, but had been affected by multiple, intense rounds of extraction, beginning in 1978 (Chong et al. 2005). Logging ended as recently as 2008, by which time timber restrictions had been lifted in anticipation of future clearance, and a total of 179 m3 ha-1 had been removed from the area (Yayasan Sabah, unpublished data). This land-use history, in combination with topographical constraints on access, means there was substantial spatial variability in the intensity and timing of logging, as well as the methods used (tractor-based and cable yarding), creating a highly heterogeneous forest landscape. There were few old-growth trees remaining, and pioneer species such as Macaranga pearsonii, M. hypoleuca and Neolamarckia cadamba were dominant. Indeed, M. pearsonii alone formed ~10% of tree basal area (SAFE Project, unpublished data). In addition, logging created a network of regenerating skid trails, roads of varying width and heavily degraded log-landing areas, which means there were also some areas of grassland and low scrub, often containing non-native shrubs including Clidemia hirta and Chromolaena odorata. Our oil palm sites were spread across two neighbouring plantation estates: Selangan Batu estate (operated by Benta Wawasan Sendirian Berhad) and Mawang estate (operated by Sabah Softwoods Sendirian Berhad). Oil palms within the Selangan Batu estate were mostly planted in 2006 and were 1-4 m in height, forming a discontinuous canopy. Oil palms within the Mawang estate were mostly planted in 2000, with some trees up to 10 m in height and forming a continuous canopy layer. Palms in both estates were planted with approximately 10 m separation. Understorey communities within the plantations consisted of various grasses, ferns, other herbs such as Ageratum conyzoides, and vines, including the highly invasive Mikania cordata (T. Döbert, personal communication). Herbicide use in the plantations meant that the area directly around each palm was bare in most cases, but there was otherwise substantial variation in the extent of understorey growth. In the older plantations, where the canopy was unbroken, much of the ground was bare except for the oil palm fronds which are cut during harvesting and stacked between the rows of palms. Some small areas within the younger plantations had been planted with seedlings of subsistence crops, or had been burned in anticipation of doing so. Small riparian buffers of degraded logged forest existed in the broader landscape, as well as a 45 km2 block of logged forest (managed by the Sabah Forestry Department) immediately to the west of the sampling points. Interviews with the estate managers indicated that there were no active rodent control programmes operating in the plantations (W. Lojinin, personal communication; R. Hussein, personal communication), with no recent use of rodenticide or biocontrol by barn owls (Tyto alba javanica). Appendix B: Additional information on β-diversity quantification. β-diversity patterns remain poorly characterised at least in part because of uncertainty surrounding how to define β-diversity (Tuomisto 2010) and how best to measure it (Jost 2007; Baselga 2010a; Chao et al. 2012; Legendre & De Cáceres 2013). β-diversity may be separated into those components which vary due to sampling effects, including the effects of sampling extent (Soininen et al. 2007b), grain (Mac Nally & Fleishman 2004; Steinbauer et al. 2012; Olivier & Aarde 2014), replication (Crist & Veech 2006; Chao et al. 2012) and sample completeness (Cardoso et al. 2009; Beck et al. 2013), and those components which vary depending on the assembly of communities, including patterns of species abundance, occupancy, co-occurrence and intraspecific aggregation (Veech et al. 2003; Veech 2005). It is these latter components that are typically of interest to researchers. In the context of diversity partitioning, there is the additional problem that β-diversity is calculated using values for α- and γ-diversity, and as a result there has been a recurring debate about whether β-diversity calculated in this way is truly independent (Jost 2007, 2010; Baselga 2010b; Ricotta 2010; Veech & Crist 2010a, 2010b). Chao et al. (2012) recently synthesised this debate, showing conclusively that neither additive β-diversity (= γ-α) nor multiplicative β-diversity (= γ/α) are free of this dependence, and recommended a normalisation to overcome this. However, it remains unclear whether sampling effects on α- and γ-diversity are completely controlled for using this normalisation. The effects of the sampling process, as well as the size of regional species pools (Lessard et al. 2012), can be accounted for by comparing observations with a null model which specifically includes these details (Crist et al. 2003; Kraft et al. 2011). Any differences between observations and the null model which remain are taken to be indicative of non-random processes that were excluded from the null model, for example community assembly processes. This is the approach we chose to use here (see Methods for more details). β-diversity sensu lato includes community variance due both to the turnover of species and due to variation in species richness independent of turnover, i.e. the nestedness of communities. Baselga (2007, 2010a) and others (for a review see Legendre, 2014) have argued for a separation of turnover and nestedness and for β-diversity sensu stricto to be measured independently of the effects of nestedness. The predominance of turnover or nestedness in communities is related to the assembly processes at work. For example, niche assembly and random community drift will often be responsible for patterns of turnover at local scales, whilst differential dispersal capacities and selective extinction are more likely to create nested communities across space. The distinction between turnover and nestedness is particularly important in the context of conservation set-aside; if β-diversity is driven by species turnover, a distributed network of set-aside patches would be required to ensure representation of all species, whilst if β-diversity is completely driven by nestedness patterns, the optimal solution would simply be to prioritise the conservation of the most diverse forest patches. Following the approach of (Baselga 2010a), we therefore separated observed β-diversity into its turnover and nestedness components (more details on this approach are given in Methods).
Figure C1. Sample-based species accumulation curves across land-use types, based on a Bernoulli product model (Colwell et al. 2012). Only data from sampling points which were both camera-trapped and live-trapped were used. Solid lines show interpolated values, whilst dashed lines show extrapolated values. Filled circles show the observed γ-diversities. 
Appendix D: Additional results tables. Table D1. Observed α-diversity and model estimates of standardised α-diversity across land-use types.
Table D2. Observed and estimated γ-diversity across land-use types.
Table D3. β-diversity differences from null models across land-use types and spatial grains.
Yüklə 288,19 Kb. Dostları ilə paylaş:
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
