Corridor Forest Structure
Riparian forests (RF) around Alta Floresta were highly heterogenous both in terms of their patch metrics and preservation status whether we considered unnested comparisons or nested ANOVAs in which the 222 PC stations were nested within the 37 RF sites (Table 1). Stand basal area was significantly different among the 3 types of RF sites (one-way ANOVA; F= 38.2, df = 31, p < 0.001). Remnant connected corridors retained a significantly higher structural integrity in terms of their width, basal area, canopy structure, and height (estimated by vertical pixel counts) compared with those that had lost connectivity to source patches. Corridor height differed significantly between the taller and more structurally uniform connected corridors and the lower-stature and more degraded unconnected corridors (ANOVA; F= 9.6, df = 31, p < 0.004). Across the 32 corridors, mean width was positively correlated with spectral forest quality (r= 0.592, p < 0.001), corridor height (r= 0.425, p= 0.015), nonpalm tree basal area (r= 0.317, p= 0.077), and canopy cover (r= 0.473, p= 0.006). Cattle intrusion occurred in 70% and 89% of all connected and unconnected corridor plots, respectively, although wire fences were only erected in 16% and 2% of connected and unconnected corridor plots, respectively. Cattle intrusion, however, may have been suppressed or restricted in some plots by dense stands of bamboo (Guadua sp.), which occurred in 24% of connected corridor plots, 40% of unconnected corridor plots, and 33% of control plots. Mauritia palms occurred in 42% of connected corridor plots, 90% of unconnected corridor plots, and 16% of control plots.
We recorded 17,999 detections of 365 bird species during 444 point counts. Mean corridor width was a significant predictor of bird species richness per corridor (R2= 0.393, p < 0.001, n= 32). There was a critical width threshold of ∼400 m beyond which species accumulation did not increase significantly (Fig. 2). Other highly significant predictors included spectral forest quality (R2= 0.473, p < 0.001) and the distance from the nearest of the 2 major urban centers (Alta Floresta or Carlinda) (R2= 0.372, p < 0.001). Less important but still significant determinants of bird species richness included nonpalm basal area (R2= 0.242, p= 0.002), mean corridor height (R2= 0.111, p= 0.035), and canopy cover (R2= 0.157, p= 0.014).
Figure 2. Relationships between vertebrate species richness and mean corridor width and forest quality for riparian forest corridors that are either connected (shaded circles) or unconnected (open triangles) to large forest patches and control sites within continuous forest patches (CF, dark-shaded squares): (a, b) birds and (c, d) mammals.
Download figure to PowerPoint
Bird species were widely variable in their persistence in the 3 types of riparian forests. Some taxa (e.g., Red-bellied Macaw [Orthopsittaca manilata] and other psittacids) were nearly ubiquitous across all sites and were more abundant in unconnected corridors because of the higher abundance of Mauritia palms, one of their key food plants. Likewise, some riverine specialist passerines (e.g., Silvered Antbird [Sclateria naevia]) were frequently encountered in all 3 riparian forest types and were only absent in the most degraded sites. Levels of species richness in control sites were far higher than in either corridor types, and more species occurred in connected than in unconnected corridors. Some species conspicuously absent from unconnected corridors were common in connected corridors (e.g., Black-tailed Trogon [Trogon melanurus]), whereas others were common in control sites and rare or absent in both corridor types (e.g., Cinereous Antshrike [Thamnomanes caesius]).
Bird species richness was affected by different patch and landscape characteristics in connected and unconnected corridors and control sites, but responses were highly species-specific. The most significant positive predictors of the number of primary forest-sensitive species (classes 1–2) retained in riparian corridors were (in order of importance) corridor width, size of source patch, and forest basal area (Table 2; Fig. 3), whereas Mauritia palm abundance and cattle intrusion had a negative effect. Conversely the less-sensitive species (classes 3–4) were negatively affected by forest canopy cover, but positively affected by Mauritia palm abundance and source patch size. Forest-sensitive species responded to bamboo abundance and corridor height and width, whereas less-sensitive species were more likely to occur in sites of low forest quality, which contained a more heterogeneous vertical profile. For the riparian sites within large forest patches, canopy cover was the only significant variable retained for the most sensitive species, and there were more less-sensitive species in low-quality patches.
Table 2. Minimum, generalized linear mixed models (GLMMs) of bird and mammal species richness in 24 connected and 8 unconnected corridors, accounting for point-count (PC) sites nested within clusters (corridors).a
|all (358 species)||primary-forest specialists (207 species)||edge and second-growth tolerant (151 species)||all (18 species)||large (13 species)||primates (5 species)|
|Corridor width (m)||1.623||0.020||13.944||<0.001||−1.575||0.524||1.599||0.012||0.945||0.086|| |
|Patch size (ha)b||0.113||0.059||1.497||0.019||0.251||0.519||0.188||0.048||0.203||0.030|| |
|Spectral forest quality|| ||0.546||0.352||−0.671||0.158|| ||0.070||0.221|
|Tree basal area (m/ha)|| ||0.087||0.060|| ||0.022||0.041||0.026||0.004|| |
|Understory density|| ||0.037||0.104|
|Canopy cover (%)|| ||0.026||0.198||−0.036||0.021|| |
|Bamboo abundance||1.099||0.092||0.641||0.207|| ||0.277||0.014||0.330||<0.001|| |
|Mauritia palms||−1.129||0.109||−1.239||0.024|| |
|Cattle intrusion||−1.460||0.415||−0.622||0.650|| ||−0.597||0.063||−0.380||0.149||−0.216||0.169|
|Hunting score|| ||0.117||0.201|
Figure 3. Relationships between species richness and corridor width for 4 functional groups of bird species with varying degrees of habitat sensitivity (sensitivity classes; S1, all strict forest understory and midstory species; S2, all remaining species dependent on primary forest; S3, forest species able to tolerate secondary or highly degraded forest; S4, primarily nonforest species including scrub and open-habitat countryside species). Open triangles, gray circles, and black squares indicate unconnected corridors, connected corridors, and control riparian sites, respectively.
Download figure to PowerPoint
In connected corridors only, a higher fraction of the species richness in adjacent source patches was lost with increasing distance from these patches (p= 0.020), but ΔS was also significantly depressed at narrow corridor sites (p < 0.001), which contained lower canopy cover (p= 0.002) and a spectral index of poorer quality (p= 0.042), particularly where cattle intrusion had regularly taken place (p= 0.016). This species decay along corridors was very pronounced within 50 m of the patch node, but was more gradual with increasing distance from the source patch (Fig. 4).
Figure 4. Changes in species richness (ΔS) for (a) birds and (b) mammals along connected corridors as a function of distance from their respective source-forest patch nodes.
Download figure to PowerPoint
According to the BIO-ENV analysis, the most important grouping of variables predicting community structure among all 37 sites were corridor width, spectral forest quality, Mauritia palm abundance, and cattle intrusion (R= 0.544). Excluding the 5 control sites, spectral forest quality and bamboo and Mauritia abundance were the most important combination of variables (R= 0.402). Unconnected corridors and narrow connected corridors retained far fewer species than wide, connected corridors and control riparian areas, and MDS scores indicated they were more dissimilar from one another in assemblage composition (Fig. 5). Similarly, community composition differed significantly among all riparian sites (overall ANOSIM R= 0.501, p < 0.05) and between the 3 riparian types (overall ANOSIM R= 0.319, p < 0.05).
Figure 5. Vertebrate assemblage composition as a function of forest corridor width for patch size for (a) birds (stress = 0.15) and (b) mammals (stress = 0.2). Open triangles, gray circles, and black squares indicate unconnected corridors, connected corridors, and control riparian sites, respectively. Circle size is proportional to forest corridor width and control patch size, which was the significant predictor of the variation in multidimensional scaling (MDS).
Download figure to PowerPoint
We detected 794 tracks of 22 species of non primate mammals and 226 sightings of 5 primate species. Corridor width was a significant predictor of mammal species richness (all species combined: R2= 0.192, p < 0.012, n= 32; large terrestrial mammals: R2= 0.147, p < 0.017), but not of primates alone (R2= 0.076, p < 0.127). The quality of the forest habitat was also a significant predictor of mammal species richness (R2= 0.312, p= 0.001). Less important, but still significant, determinants included mean corridor height (R2= 0.132, p= 0.023) and canopy cover (R2= 0.161, p= 0.013).
As with birds, responses to corridors were highly species-specific (Table 2). Some species (e.g., small armadillos, Dasypus spp.) were ubiquitous, whereas others (e.g., Capybara [Hydrochoerus hydrochaeris]) were encountered more frequently in corridors than in control sites. Nevertheless, encounter rates for most species were lower in corridors than in control sites. Some species were common in control sites and connected corridors but rarer in unconnected corridors (e.g., paca [Agouti paca]), whereas others were conspicuously absent from both corridor types (e.g., spider monkey [Ateles sp.]).
Mammal species richness was affected by different predictor variables across the 3 types of sites. In connected corridors, source patch size was the most important predictor, followed by corridor width, corridor height, canopy cover, bamboo abundance, and hunting pressure. In unconnected corridors, the only 2 variables retained in the GLMs were Mauritia palm abundance and SD of corridor height. Few variables had a strong effect on the control sites, but those retained in the GLMs included nonpalm basal area and understory density (Table 2).
For the BIO-ENV analyses, the most important grouping of variables predicting mammal community composition across all 37 sites were patch size, spectral forest quality, distance to the nearest urban center, bamboo abundance, and presence of cattle (R= 0.368). Excluding the 5 control sites, patch size, distance to urban center, understory density, bamboo abundance, and spectral forest quality were the most important combination of variables (R= 0.343). The MDS scores showed a more diffuse scatter of control sites, although the same broad trend of increasing similarity in assemblage composition of large patches and control sites was apparent (Fig. 5). Community composition did not differ significantly among all riparian sites (overall ANOSIM R= 0.115, p= 0.28) but was significantly different among the 3 sampled riparian types (overall ANOSIM R= 0.509, p < 0.001).