Successional processes in abandoned pastures in the Amazon region have been well-documented for the floristic component; however, soil succession has been poorly studied. This study assessed the physical, chemical and biological responses of soils in the Amazon region during the natural succession process in two main landscapes of the Colombian Amazon. Soil data on soil physico–chemical (bulk density, macroaggregates, pH and minerals) and biological (soil macrofauna) composition were evaluated along chronosequence with four successional stages: (i) degraded pastures, (ii) young (10–20-year-old), (iii) middle-age (25–40-year-old) and (iv) mature forests, in two different landscapes (hill and mountain). Individual soil variables and a synthetic indicator of soil quality (GISQ) were evaluated as tools for natural succession monitoring. The results corroborated the negative impact that cattle ranching has on Amazon soils. After 10 years of natural succession, the physico–chemical and biological soil components were widely restored. Less soil compaction and organic carbon occurred in older successional stages. Soil macrofauna richness and density increased along the chronosequence, with an evident association between the macrofauna composition and the macroaggregates in the soil. None of the individual soil properties or the GISQ indicator discriminated among natural succession stages; therefore, new soil quality indicators should be developed to monitor soil quality restoration in natural successions.

The efficiency of visible and near-infrared (VIS/NIR) sensors and predictive modeling for detecting and classifying South American Leaf Blight (SALB) (Pseudocercospora ulei) in rubber trees (Hevea brasiliensis) has been poorly explored. Furthermore, the performance of VIS/NIR analysis combined with machine learning (ML) algorithms for predicting photosynthetic alterations caused by SALB is unknown. Therefore, this study aimed to detect and classify the SALB levels, as well as to predict, for the first time, disease-induced photosynthetic changes in rubber trees. Leaf hyperspectral reflectance combined with five ML techniques (random forest (RF), boosted regression tree (BRT), bagged classification and regression trees (BCART), artificial neural network (ANN), and support vector machine (SVM)) were used. The RF, ANN, and BCART models achieved the best performance for classifying the SALB levels on the training dataset (accuracies of 98.0 to 99.8%), with 10-fold cross-validation repeated five times, and test dataset (accuracies of 97.1 to 100%). The ANN and RF models were better at predicting leaf gas exchange-related traits such as net CO₂ assimilation rate (A) and extrinsic water use efficiency (WUEe) in the training (R² ranged from 0.97 to 0.99) and testing (R² ranged from 0.96 to 0.99) phases. In comparison, lower performances (R² ranged from 0.24 to 0.52) were evidenced for the photochemical traits. This research provides a basis for future designs of a remote monitoring system based on early detection and accurate diagnosis of biotic stress caused by SALB, which is fundamental for more effective rubber crop protection.

The Amazon ecosystem plays a vital role in global climate regulation and biodiversity conservation but faces escalating threats from deforestation and degradation. The resulting secondary forests (SFs) provide a promising opportunity for Transformative Territorial Management, fostering restoration and enhancing conservation values. This study evaluated aboveground biomass (AGB), species diversity, forest structure, and soil properties in SFs of the Colombian Amazon along a chronosequence, from early to mature successional stages, in landscapes of mountains and of hills to identify key indicators for effective restoration management. The results show a consistent increase in AGB, species diversity, forest structure, and soil quality with forest age, though recovery patterns varied between both landscapes evaluated. Topographic differences influenced successional dynamics, with mountainous landscapes showing faster early recovery compared to the steadier, linear growth observed in hill areas. In hills, AGB at 10 years reached 12.65% of the biomass expected in a mature forest, increasing to nearly 42% by 40 years of abandonment, at a rate of 0.708 Mg C ha⁻¹ year⁻¹. In contrast, in the mountain landscape, AGB at 10 years reached approximately 8.35% of the carbon in a mature forest and increased to nearly 63.55% at 40 years. Forest age and soil properties emerged as primary drivers of AGB recovery, while diversity and forest structure played indirect but significant roles. In hill areas, soil conservation practices are critical for maintaining steady growth, whereas mountain regions benefit from assisted natural regeneration (ANR) to accelerate recovery. These findings highlight the importance of prioritizing the management of SFs as a central strategy for achieving restoration goals. Such practices are essential to enhance the ecological resilience of SFs and ensure their long-term sustainability, fostering their role as key contributors to restoration efforts and the provision of ecosystem services.

The rubber tree [Hevea brasiliensis (Willd. Ex Adr. de Juss.) Muell.-Arg] is the main source of natural rubber in the world. However, in the Amazon region, its production is reduced by biotic and abiotic limitations, which have prompted breeding programs in order to identify desirable agronomic and physiological indicators. The objective of this study was to analyze the temporal dynamics of photosynthetic responses based on the parameters of leaf gas exchange and chlorophyll a fluorescence in 10 rubber tree clones during the immature phase (pre-tapping) in three large-scale clone trials, during daily cycles and under two climatic periods (dry and rainy) in the Caquetá region (Colombian Amazon). The variables A, LT, Φ_PSII, ETR and qP were significantly higher in the dry period, where the highest values of PAR, AT and VPD were seen. In San Vicente del Caguán and Florencia, the highest averages were estimated for A, E and g_s, as compared with Belén de los Andaquíes. In Florencia, the highest fluorescence parameters of chlorophyll a were recorded. At 9:00 h and 12:00 h, the highest means of A, E, Φ_PSII and ETR were observed. The majority of the clones displayed the highest F_v/F_m mean (0.82–0.84) in the dry period. The clones FX 4098, FDR 4575, MDF 180, GU198 and FDR 5788 represent genotypes with the best photosynthetic performance (greater photosynthetic rates and better ability of the photosynthetic apparatus to capture, use and dissipate light energy). These desirable genotypes constitute a promising gene pool for expanding the genetic resource of rubber trees in the Colombian Amazon.