Degradation of Root Community Traits as Indicator for Transformation of Tropical Lowland Rain Forests into Oil Palm and Rubber Plantations.

Conversion of tropical forests into intensely managed plantations is a threat to ecosystem functions. On Sumatra, Indonesia, oil palm (Elaeis guineensis) plantations are rapidly expanding, displacing rain forests and extensively used rubber (Hevea brasiliensis) agro-forests. Here, we tested the influence of land use systems on root traits including chemical traits (carbon, nitrogen, mineral nutrients, potentially toxic elements [aluminium, iron] and performance traits (root mass, vitality, mycorrhizal colonization). Traits were measured as root community-weighed traits (RCWTs) in lowland rain forests, in rubber agro-forests mixed with rain forest trees, in rubber and oil palm plantations in two landscapes (Bukit Duabelas and Harapan, Sumatra). We hypothesized that RCWTs vary with land use system indicating increasing transformation intensity and loss of ecosystem functions. The main factors found to be related to increasing transformation intensity were declining root vitality and root sulfur, nitrogen, carbon, manganese concentrations and increasing root aluminium and iron concentrations as well as increasing spore densities of arbuscular mycorrhizas. Mycorrhizal abundance was high for arbuscular and low for ectomycorrhizas and unrelated to changes in RCWTs. The decline in RCWTs showed significant correlations with soil nitrogen, soil pH and litter carbon. Thus, our study uncovered a relationship between deteriorating root community traits and loss of ecosystem functionality and showed that increasing transformation intensity resulted in decreasing root nutrition and health. Based on these results we suggest that land management that improves root vitality may enhance the ecological functions of intense tropical production systems.Oüpen-Access Publikationsfonds 201

Geographic location of the research plots in two landscapes and four forest types on Sumatra (Indonesia).

<p>O = oil palm plantation, R = rubber plantation, J = jungle rubber, F = secondary rain forest.</p><p>Geographic location of the research plots in two landscapes and four forest types on Sumatra (Indonesia).</p

Mean PC scores of the land use systems.

<p>Different letters in columns indicate significant differences at P < 0.05 determined with the HSD test. B = Bukit 12, H = Harapan, O = oil palm, R = rubber plantation, J = jungle rubber, F = forest.</p><p>Mean PC scores of the land use systems.</p

Performance parameters of roots in different land use systems.

<p>(A) Fine root mass to a depth of 0.2 m, (B) Fraction of distorted root tips (100% is the total number of inspected root tips), (C) Fraction of the inspected root lengths colonized with mycorrhizal hyphae (AMh), arbuscules (AMa), vesicles (AMv) and fraction of vital root tips colonized with ectomycorrhizas (EM), (D) Number of arbuscular mycorrhizal spores. Data indicate means (± SE). Different letters indicate significant differences at P < 0.05. B = Bukit 12, H = Harapan, O = oil palm, R = rubber plantation, J = jungle rubber, F = forest.</p

Chemical composition of roots in different land use systems.

<p>Carbon (A), nitrogen (B), phosphorus (C), sulfur (D), manganese (E), base cations (F), iron (G) and aluminium (H) determined as root community-weight traits. Data indicate means (± SE). Different letters indicate significant differences at P < 0.05. B = Bukit 12, H = Harapan, O = oil palm, R = rubber plantation, J = jungle rubber, F = forest.</p

Best general linear model for the relationship of PC1 with ecosystem properties.

<p>Best general linear model for the relationship of PC1 with ecosystem properties.</p

Maps of the province Jambi (A) with the landscapes Bukit 12 (B) and Harapan (C) on Sumatra (Indonesia).

<p>The locations of the research plots are indicated.</p

General linear mixed model for PC1 and PC2 as dependent variables and landscape and land use system (LUS) as categorical factors.

<p>Landscape was set as fixed and LUS as random factor nested in landscape.</p><p>General linear mixed model for PC1 and PC2 as dependent variables and landscape and land use system (LUS) as categorical factors.</p