Supplementary Information- Expanded Methodology
We used a stratified random sampling design within each catchment to ensure that sample data
provide a representative assessment of the overall environmental condition. Between eight and
twelve 300 m transects allocated to each catchment, depending on catchment size with an even
density of 1 transect per 400 ha, totalling 165 transects. To reduce the dependency between
transects within each catchment, transects were separated by a minimum distance of 1.5 km. All
landowners in each catchment were visited prior to any fieldwork to introduce the project and
secure permissions for surveys in private properties. Transects were within habitats and not
conducted on road surfaces.
Land-use classification was made using 2010 Landsat images and a decision tree classification
algorithm (Gardner et al., 2013). Land-use types were classified into six broad groups: primary forest:
the region’s original climax physiognomy that has never been clear-felled for agriculture (although
may have been extensively degraded by disturbance and human exploitation); secondary forests:
forests that developed after complete clearance (Putz and Redford, 2010); tree plantations – in this
case commercial plantations, typically of Eucalyptus sp., teak (Tectona grandis) or paricá
(Schizolobium parahyba var. amazonicum); cattle pasture; mechanised agriculture: typically soybean
fields or rice; and small-holder agriculture: farms typically smaller than 100 ha and consisting of
small-scale manioc plantations and/or fruit trees. Primary forest transects were further subclassified by disturbance type. These classifications were based on ground-truthed observations of
past disturbance events (Gardner et al., 2013), resulting in four types of primary forest:
‘undisturbed’ for which no evidence of recent human-induced degradation was apparent,
‘selectively logged’ for forest which have undergone detectable logging, ‘burnt’ for forests in which
fire scars were found on trees and charcoal deposits detected on the ground and logged & burnt for
those forest exposed to both of these stressors.
In each transect three point count (PC) stations were located at 0, 150 and 300 m. A total of 1083
PCs were conducted across both regions. We conducted two repetitions of three fixed width (75 m)
15-minute point counts per transect situated at 150 m intervals along a 300 m transect. All point
counts (PCs) were conducted by principal observers A. C. Lees., N. G. Moura, C. B. Andretti and B. J.
W. Davis with the exception of two transects carried out independently by E. V. Lopes in Catchment
236 (see Figure 1. in Lees et al. 2013. for numbering of study catchments). Surveys were not carried
out on days with persistent rain and/or strong winds. Any systematic effect of seasonality
(presence/absence of austral/boreal migrants and peaks and troughs in vocalization activity) was
minimized by systematically rotating surveys between catchments of varying total forest cover and
between PCs were recorded using solid state recorders and sound-recordings archived on the global
avian sound library Xeno-canto (www.xenocanto.org), for more details on survey methodology, full
species lists and links to digital vouchers see Lees et al. (2013).
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Figure 1 ESM
FIGURE 1, Variance partitioning indicates that roadless volume (RV) has 15% more explanatory
power than percentage forest cover (%FC) alone, i.e. the variance explained by RV (34) minus
variance explained by FC (19). Combining the two variables explains over 91% of variation in species
richness, with a residual (R) of just 9%.