Cacao (Theobroma cacao L.) has traditionally been considered a crop that requires shade, and consequently it is implemented under agroforestry systems (AFs) in order to regulate the level of incident solar radiation. However, optimal shade levels for this tree crop may vary depending on the climate conditions of where it is grown. Here we analyzed the physiological performance of cacao under three different AFs in the Colombian Amazon that differed in solar radiation patterns: high (H_PAR), medium (M_PAR), or low (L_PAR) mean daily incident radiation. The physiological performance was characterized using photosynthetic variables in leaves such as light- and CO₂-response curves, chlorophyll a fluorescence parameters, and total chlorophyll and carotenoid contents, in conjunction with other leaf functional traits. Cacao trees exposed to H_PAR showed an improved physiological performance as compared to those from the other two AFs. Compared to M_PAR and L_PAR, cacao trees in H_PAR doubled the rate of net carbon assimilation and reached higher maximum rates of RuBisCO carboxylation and RuBP regeneration. Moreover, cacao trees in H_PAR presented photoprotection mechanisms that avoided photoinhibition, which was accompanied by a greater non-photochemical quenching coefficient and biochemical and morphological adjustments (low chlorophyll but higher carotenoid contents and low specific leaf area) compared to cacao trees from the other AFs. Overall, our results show that, due to the high cloud cover in the Colombian Amazon, cacao plantations under conditions of sparse shade maximized their carbon use, showing an improved physiological performance as a result of higher photosynthetic rates and energy dissipation mechanisms. If the crop were managed with sparse shade, the paradigm that favors the cultivation of cacao under shade would be called into question in the Colombian Amazon and other regions with similar climatic conditions.

Colombia's agriculture, forestry and other land use sector accounts for nearly half of its total greenhouse gas (GHG) emissions. The importance of smallholder deforestation is comparatively high in relation to its regional counterparts, and livestock agriculture represents the largest driver of primary forest depletion. Silvopastoral systems (SPSs) are presented as agroecological solutions that synergistically enhance livestock productivity, improve local farmers’ livelihoods and hold the potential to reduce pressure on forest conversion. The department of Caquetá represents Colombia’s most important deforestation hotspot. Targeting smallholder livestock farms through survey data, in this work we investigate the GHG mitigation potential of implementing SPSs for smallholder farms in this region. Specifically, we assess whether the carbon sequestration taking place in the soil and biomass of SPSs is sufficient to offset the per-hectare increase in livestock GHG emissions resulting from higher stocking rates. To address these questions we use data on livestock population characteristics and historic land cover changes reported from a survey covering 158 farms and model the carbon sequestration occurring in three different scenarios of progressively-increased SPS complexity using the CO₂ fix model. We find that, even with moderate tree planting densities, the implementation of SPSs can reduce GHG emissions by 2.6 Mg CO_2e ha⁻¹ yr⁻¹ in relation to current practices, while increasing agriculture productivity and contributing to the restoration of severely degraded landscapes.

The objective of this work was to evaluate the soil macrofauna and the bioindicator taxonomic groups associated with different land uses in the Colombian Amazon. Twelve agroforestry arrangements were studied and compared with to the native forest and pasture. For each land use, six monoliths were randomly selected and divided into four layers (litter, and 0-10, 10-20, and 20-30 cm soil depths). The variables considered in the analysis of land use effects were: individuals per square meter, order richness, Shannon’s diversity index, and Pielou’s evenness index. The greatest values for soil macrofauna density and diversity occurred in the forest, in contrast with the pasture. The principal component analysis distinguished land use according to macrofauna diversity, separating the native forest from the other land uses. The cluster analysis indicated the potential of some agroforestry systems to conserve the values of soil macrofauna density and diversity similar to those of the forest. According to the analysis of indicator value, five taxonomic groups (Diplura, Pseudoscorpionida, Araneae, Chilopoda, and Gastropoda), identified as bioindicators, are associated with preserved sites because of the sensitivity of their populations.

The evaluation of disease resistance is considered an important aspect of phenotyping for crop improvement. Identification of advanced lines of the common bean with disease resistance contributes to improved grain yields. This study aimed to determine the response of the photosynthetic apparatus to natural pathogen infection by using chlorophyll (Chl_a) fluorescence parameters and their relationship to the agronomic performance of 59 common bean lines and comparing the photosynthetic responses of naturally infected vs. healthy leaves. The study was conducted over two seasons under acid soil and high temperature conditions in the western Amazon region of Colombia. A disease susceptibility index (DSI) was developed and validated using chlorophyll a (Chl_a) fluorescence as a tool to identify Mesoamerican and Andean lines of common bean (Phaseolus vulgaris L.) that are resistant to pathogens. A negative effect on the functional status of the photosynthetic apparatus was found with the presence of pathogen infection, a situation that allowed the identification of four typologies based on the DSI values ((i) moderately resistant; (ii) moderately susceptible; (iii) susceptible; and (iv) highly susceptible). Moderately resistant lines, five of them from the Mesoamerican gene pool (ALB 350, SMC 200, BFS 10, SER 16, SMN 27) and one from the Andean gene pool (DAB 295), allocated a higher proportion of energy to photochemical processes, which increased the rate of electron transfer resulting in a lower sensitivity to disease stress. This photosynthetic response was associated with lower values of DSI, which translated into an increase in the accumulation of dry matter accumulation in different plant organs (leaves, stem, pods and roots). Thus, DSI values based on chlorophyll fluorescence response to pathogen infection could serve as a phenotyping tool for evaluating advanced common bean lines. Six common bean lines (ALB 350, BFS 10, DAB 295, SER 16, SMC 200 and SMN 27) were identified as less sensitive to disease stress under field conditions in the western Amazon region of Colombia, and these could serve as useful parents for improving the common bean for multiple stress resistance.

In this study, we measured diurnal patterns of sap flow (V_s) in cacao trees growing in three types of agroforestry systems (AFs) that differ in the incident solar radiation they receive. We modeled the relationship of V_s with several microclimatic characteristics of the AFs using mixed linear models. We characterized microclimatic variables that may have an effect on diurnal patterns of sap flow: air relative humidity, air temperature, photosynthetically active radiation and vapor pressure deficit. Overall, our model predicted the differences between cacao V_s in the three different AFs, with cacao plants with dense Musaceae plantation and high mean diurnal incident radiation (H_PAR) displaying the highest differences compared to the other agroforestry arrangements. The model was also able to predict situations such as nocturnal transpiration in H_PAR and inverse nocturnal sap flows indicative of hydraulic redistribution in the other AFs receiving less incident radiation. Overall, the model we present here can be a useful and cost-effective tool for predicting transpiration and water use in cacao trees, as well as for managing cacao agroforestry systems in the Amazon rainforest.