Relative importance of environmental variables in explaining total avian species richness (A) and forest-associated bird richness (B).

<p>Signs indicate the direction of the effect of each variable. The explanatory variables include distance to the forest border (border), tree species richness, forest cover (% of primary forest cover) and biomass of trees (biomass).</p

Circular phylograms illustrating avian community composition in a) primary forests b) cattle pasture and c) oil palm plantations, families with more than eight species are labelled.

<p>Bold lines indicate species presences in the given land-use type whereas pale lines denote species absences from that land-use type which were found in one or more other land-uses.</p

The top-ranked 15 bird species in each land-use type which contributed to the dissimilarity of species composition between oil palm plantations, cattle pastures, secondary forests and primary forests.

<p>The top-ranked 15 bird species in each land-use type which contributed to the dissimilarity of species composition between oil palm plantations, cattle pastures, secondary forests and primary forests.</p

Linear regressions between richness of forest bird species and a) tree biomass and b) distance to the nearest primary forest border.

<p>Linear regressions between richness of forest bird species and a) tree biomass and b) distance to the nearest primary forest border.</p

NMDS plots of community structure of the avian community in Moju (polygons with heavy black borders) and Paragominas (narrow borders), primary forest transects are represented by dark green squares, secondary forests by light green squares, orange circles are cattle pastures, grey circles are mechanised agriculture and triangles are oil palm plantations (dark red = 15–20 years old, lighter red 0–6 years old).

<p>NMDS plots of community structure of the avian community in Moju (polygons with heavy black borders) and Paragominas (narrow borders), primary forest transects are represented by dark green squares, secondary forests by light green squares, orange circles are cattle pastures, grey circles are mechanised agriculture and triangles are oil palm plantations (dark red = 15–20 years old, lighter red 0–6 years old).</p

Box plots comparing avian species richness between land-use types, using the entire avian assemblage (A) and just forest-associated birds (B).

<p>Non-significant pairwise differences between land-use types are indicated by the presence of the same letter (according to a Tukey test 95%).</p

Number of sampled plots (0.25ha) in each study region.

<p>Number of sampled plots (0.25ha) in each study region.</p

The costs and errors of simplifying carbon sampling protocols.

<p>Relationship between the average error of different estimates of carbon stored in large live stems and the costs of sampling a 1-ha plot. Results are separated into three hypothetical scenarios of carbon stock assessments in human-modified tropical forests: A) No <i>a priori</i> information of forest class; B) Primary forests only—includes undisturbed and disturbed primary forests; and C) Secondary forests only. Filled symbols indicate estimates of carbon stocks present in all stems ≥10cm DBH, whereas open symbols represent carbon estimates of subsets of large live stems. The dotted lines indicate the average error of both the IPCC and FAO estimates.</p

Recommended sampling approaches to assess carbon stocks in human-modified tropical forests.

<p>Recommendations are based on the results of this study, following the IPCC three- tiers system for forest carbon assessments.</p

Financial costs and time spent sampling different components of the total carbon stocks.

<p>S = Soil 0-30cm, SSI = Small stems (2–9.9cm DBH) identified to species level, LSI = Large stems (≥10cm DBH) identified to species level, SSN = Small stems without species identification, LSN = Large stems without species identification, CWD = Coarse woody debris, FWD = Fine woody debris, L = Leaf litter. As live and dead stems were sampled together, it is impossible to disentangle their specific costs in this analysis.</p