Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)

Abstract:

Background: Since the 1990’s, afforestation programs in the páramo have been implemented to offset carbon emissions through carbon sequestration, mainly using pine plantations. However, several studies have indicated that after the establishment of pine plantations in grasslands, there is an alteration of carbon pools including a decrease of the soil organic carbon (SOC) pool. The aim of this study is to investigate the impact of the establishment of pine plantations on the carbon stocks in different altitudes of the páramo ecosystem of South Ecuador. Results: At seven locations within an elevational gradient from 2780 to 3760 m a.s.l., we measured and compared carbon stocks of three types of land use: natural grassland, grazed páramo, and Pinus patula Schlltdl. & Cham. plantation sites. For a more accurate estimation of pine tree carbon, we developed our own allometric equations. There were significant (p < 0.05) differences between the amounts of carbon stored in the carbon pools aboveground and belowground for the three types of land use. In most of the locations, pine plantations revealed the highest amounts of aboveground and belowground carbon (55.4 and 6.9 tC/ha) followed by natural grassland (23.1 and 2.7 tC/ha) and grazed páramo sites (9.1 and 1.5 tC/ha). Concerning the SOC pools, most of the locations revealed significant lower values of plantations’ SOC in comparison to natural grassland and grazed páramo sites. Higher elevation was associated with lower amounts of pines’ biomass. Conclusions: Even though plantations store high amounts of carbon, natural páramo grassland can also store substantial amounts above and belowground, without negatively affecting the soils and putting other páramo ecosystem services at risk. Consequently, plans for afforestation in the páramo should be assessed case by case, considering not only the limiting factor of elevation, but also the site quality especially affected by the type of previous land use.

Abstract:

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individualbased model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Abstract:

Tropical montane forests are commonly limited by N or co-limited by N and P. Projected increases in N deposition in tropical montane regions are thought to be insufficient for vegetation demand and are not therefore expected to affect soil N availability and N2O emissions. We established a factorial Nand P-addition experiment (i.e., N, P, N ? P, and control) across an elevation gradient of montane forests in Ecuador to test these hypotheses: (1) moderate rates of N and P additions are able to stimulate soil-N cycling rates and N2O fluxes, and (2) the magnitude and timing of soil N2O-flux responses depend on the initial nutrient status of the forest soils. Moderate rates of nutrients were added: 50 kg N ha-1 year-1 (in the form of urea) and 10 kg P ha-1 year-1 (in the form of NaH2PO4 . 2H2O) split in two equal applications. We tested the hypotheses by measuring changes in net rates of soil–N cycling and N2O fluxes during the first 2 years (2008??2009) of nutrient manipulation in an oldgrowth premontane forest at 1,000 m, growing on a Cambisol soil with no organic layer, in an old-growth lower montane forest at 2,000 m, growing on a Cambisol soil with an organic layer, and an oldgrowth upper montane rainforest at 3,000 m, growing on a Histosol soil with a thick organic layer. Among the control plots, net nitrification rates were largest at the 1,000-m site whereas net nitrification was not detectable at the 2,000and 3,000-m sites. The already large net nitrification at the 1,000-m site was not affected by nutrient additions, but net nitrification became detectable at the 2,000and 3000-m sites after the second year of N and N + P additions. N2O emissions increased rapidly following N and N ? P additions at the 1,000-m site whereas only smaller increases occurred at the 2,000and 3,000-m sites during the second year of N and N + P additions. Addition of P alone had no effect on net rates of soil N cycling and N2O fluxes at any elevation. Our results showed that the initial soil N status, which may also be influenced by presence or absence of organic layer, soil moisture and temperature as encompassed by the elevation gradient, is a good indicator of how soil N cycling and N2O fluxes may respond to future increases in nutrient additions.

Abstract:

The dependence of aboveground biomass and productivity of tropical forests on soil fertility is not fully understood, since previous studies yielded contrasting results. Here, we quantify aboveground biomass (AGB) and stem wood production, and examine the impact of soil chemistry on these parameters in mature tropical forest stands of the equatorial Andes in Ecuador. In 80 plots of 0.04 ha at four elevation levels (500, 1,000, 1,500 and 2,000 m a.s.l., total sample area = 3.2 ha), we measured ten important soil chemical parameters, inventoried all trees ¸10 cm dbh and monitored stem diameter growth with dendrometer tapes in 32 plots. Top canopy height and stem density signiWcantly decreased from 500 to 2,000 m, while tree basal area increased and AGB remained invariant (344 § 17 Mg DM ha¡1, mean § SE) with elevation. Wood speciWc gravity (WSG) showed a signiWcant, but small, decrease. Stem wood production decreased from 4.5 to 3.2 Mg DM ha¡1 year¡1 along the transect, indicating a higher biomass turnover at lower elevations. The only soil variable that covaried with AGB was exchangeable K in the topsoil. WSG increased with decreases in N mineralisation rate, soil pH and extractable Ca and P concentrations. Structural equation modelling (SEM) revealed that nitrogen availability acts on stem wood production only indirectly through a negative relation between N mineralisation rate and WSG, and a positive eVect of a lowered WSG on stem growth. The SEM analysis showed neither direct nor indirect eVects of resin-extractable P on wood production, but a negative P inXuence on AGB. We conclude that nitrogen availability signiWcantly inXuences productivity in these Andean forests, but both N and P are aVecting wood production mainly indirectly through alterations in WSG and stem density; the growth-promoting eVect of N is apparently larger than that of P.