Abstract Remote sensing is very important for monitoring the natural forests. In this study was estimated the aboveground biomass (AGB) and carbon (C) with remote sensing in the Santuario de Fauna y Flora Iguaque (SFFI) in Boyacá, Colombia. A total of 23 temporal sampling plots (TSP) of 250 m2 each were installed and all trees with diameter at breast height (dbh) ≥ 10 cm were measured. The real AGB was estimated using an allometric equations for species from high-Andean forests and was multiplied for 0,5 to estimate C. Only nine TSP fulfilled the criterion of a minimal tree density of 30 trees per plot, these were correlated with three vegetation indexes, Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index and Enhanced Vegetation Index (NDVI, SAVI and EVI) derived from two Landsat 8 images from dry and rainy season in 2016. A model to estimate AGB based on a vegetation index was developed in order to build carbon maps. The best model was based on NDVI in the dry season (adjusted R2 = 0.79 and root of mean square error of 17.1 Mg/ha). The forests in the SFFI stored a mean of 36.6 Mg C/ha in AGB. Also, was accumulated 163 Gg CO2e in the forests the SFFI that correspond emissions evited at the atmosphere. This case study was presented as the first exercise for estimated AGB and C with remote sensing tools for forest monitoring in protected areas of environmental importance and will serve as a reference for future investigations for the satellite monitoring of the region’s natural forests.

Resumen La Teledetección es clave para el monitoreo de bosques naturales. En este estudio, se estimó la biomasa aérea (AGB) y el carbono (C) con teledetección en bosques del Santuario de Fauna y Flora Iguaque (SFFI) en Boyacá, Colombia. Se establecieron 23 parcelas temporales de muestreo (PTM) de 250 m2 cada una y se midieron los árboles con diámetro a la altura del pecho (dap) ≥ 10 cm. La AGB real se estimó con una ecuación alométrica para especies alto-andinas y se multiplicó por 0,5 para estimar el C. Solo nueve PTM cumplieron con criterios de una densidad mínima de 30 árboles por parcela, estas se correlacionaron con tres índices de vegetación: el Índice de Vegetación de Diferencia Normalizada, el Índice de Vegetación Ajustado al Suelo y el Índice de Vegetación Mejorado (NDVI, SAVI y EVI) derivados de dos imágenes Landsat 8 OLI en época seca y lluviosa del 2016. Se desarrolló un modelo para estimar AGB con base en índices de vegetación para construir mapas de carbono. El mejor modelo estuvo basado en el NDVI de la época seca (R2 ajustado = 0,79 y error medio cuadrático = 17, 1 Mg/ha). Los bosques del SFFI almacenaron en promedio 36,6 Mg C/ha en AGB. Asimismo, acumularon 163 Gg CO2e traducidos en emisiones evitadas a la atmósfera por deforestación. Este estudio de caso presenta un primer ejercicio en la estimación de AGB y C con herramientas de Teledetección para el monitoreo de bosques en áreas protegidas de importancia regional y servirá como referente para futuras investigaciones que involucren el monitoreo satelital de bosques naturales de la región.

RESUMO A estimativa do carbono armazenado nos ecossistemas florestais requer ferramentas precisas para prever a biomassa. Objetivou-se nesse estudo determinar a biomassa aérea individual de Prosopis affinis e sua distribuição por componente; desenvolver modelos alométricos para prever a biomassa, e estimar os fatores de expansão da biomassa (FEB) em florestas nativas de Entre Ríos (Argentina). Foram medidas variáveis dasométricas em 30 indivíduos de diferentes classes de diâmetro e determinada a biomassa aérea total e por componente (tronco, ramos com mais de 5 cm de diámetro, e ramos menores que 5 cm + folhas, flores e frutos) pelo método destrutivo. A seleção dos modelos com melhor ajuste foi feita de acordo com o coeficiente de determinação ajustado (R2adj), o erro médio quadrático de predição, os Critérios de Informação de Akaike e Bayesiana e o Índice de Furnival. As variáveis área da copa, diâmetro à altura do peito e altura total são os melhores estimadores da biomassa aérea total e por componente de P. affinis. O modelo de variável única baseado no diâmetro basal tem uma capacidade preditiva elevada de biomassa aérea, resultando em uma ferramenta simples de grande praticidade. A FEB oscilou entre 2,28 e 4,90, sendo significativamente diferente entre as classes diamétricas. Os maiores valores corresponderam aos indivíduos com diâmetros de tronco maiores que 25 cm. Os modelos desenvolvidos neste trabalho apresentam elevada precisão (R2adj. ≥ 0,94) para a predição da biomassa aérea total de P. affinis, e podem ser aplicados na área de florestas nativas de Entre Ríos (Argentina).

ABSTRACT Estimation of carbon stored in forest ecosystems requires accurate biomass prediction tools. The objective of this study was to determine the individual aerial biomass of Prosopis affinis and its distribution by component, to develop allometric models for the estimation of biomass and to estimate biomass expansion factors (BEF) in native forests of Entre Ríos (Argentina). Dendrometric variables on 30 individuals of different diameter classes were measured. Values of total aerial biomass and component biomass (trunk, branches larger than 5 cm in diameter and branches smaller than 5 cm + leaves, flowers and fruits) were determined using the destructive method. Different models were developed, and the best models were selected according to the adjusted coefficient of determination (R2adj), mean squared prediction error, the Akaike information and Bayesian information criteria and the Furnival index. The variables crown area, diameter at breast height and total height were the best estimators of total aerial biomass and component biomass of P. affinis. The single-variable model based on the basal diameter has a very good predictive capacity for total aerial biomass, resulting in a simple model of great practicality. The BEF was significantly different among diameter classes, with mean values between 2.28 and 4.90. The highest values corresponded to individuals with trunk diameters larger than 25 cm. The models developed in this work present high precision (R2adj. ≥ 0.94) for the prediction of total aerial biomass of P. affinis and can be applied in the native forest area of the province of Entre Ríos (Argentina).

Resumen El bosque seco tropical esta amenazado por una fuerte estacionalidad y presiones antropogénicas, lo cual puede afectar su estructura y composición. El objetivo del estudio fue estimar el impacto de dos matrices agropecuarias (arrozales y pasturas) en la composición florística y el almacenamiento de carbono en bosques riparios. Se establecieron cinco parcelas de muestreo (10 x 10 m cada una) en el interior y borde de los bosques en las dos matrices en julio 2013. Se midieron todos los individuos con un diámetro a la altura del pecho (dap) ≥ 5 cm. La biomasa arriba del suelo fue estimada con un modelo alométrico general, recomendado para estos bosques. El índice de valor de importancia (IVI), la riqueza de especies y los índices de diversidad alfa fueron estimados. Fueron realizados análisis de varianza y pruebas de comparación de medias de Fisher LSD. Se registró un total de 32 familias, 21 géneros y 45 especies (29 y 33 especies para pasturas y arrozales, respectivamente) de árboles en 0.2 ha. Las especies más abundantes y más importantes ecológicamente fueron: Oxandra espintana y Calliandra sp. (520 y 241 individuos/ha y 72 y 48 % de IVI, respectivamente). Estos bosques presentaron una dominancia media de 33.9 m2/ha sin efecto estadístico (P< 0.05) de la posición del bosque ni de la matriz. La matriz del paisaje no afectó (P> 0.05) los índices de la diversidad alfa. Los árboles más grandes y el mayor carbono fueron encontrados en la matriz de pasturas en comparación con la de arrozales (14.6 vs 13.4 cm de dap y 72.9 vs 45.6 t C/ha, respectivamente). Esta investigación provee un entendimiento de la riqueza y composición arbórea y almacenamiento de carbono de bosques ribereños en dos matrices agropecuarias, lo cual podría servir para el establecimiento de sistemas silvopastoriles con especies nativas.

Abstract The tropical dry forest is a typical lowland ecosystem that is threatened by a strong seasonality and anthropogenic pressures, which can affect the forest composition and structure. The objective of this study was to estimate the impact of two agricultural matrices on the floristic composition and carbon storage in riparian forests. For this, five permanent plots (10 x 10 m each) were established and sampled in the forest interior and at the edge of two agricultural matrices (rice fields and pasture lands), in July 2013. All individuals with a diameter at breast height (dbh) ≥ 5 cm were recorded and measured, and the aboveground biomass was estimated with a general allometric model. Additionally, the importance value index (IVI), species richness and Alpha´s diversity indexes were estimated; an analysis of variance and means comparison tests of Fisher LSD were also carried out. A total of 32 families, 21 genera and 45 species (29 and 33 species in pasture lands and rice fields, respectively) of trees in 0.2 ha were recorded. The most abundant and most ecologically important species were Oxandra espintana and Calliandra sp. (520 and 241 individuals/ha and 72 and 48 % of IVI, respectively). These forests presented a mean dominance of 33.9 m2/ha with no effect (P< 0.05) of forest location or agricultural matrix. The matrix of the landscape did not affect (P> 0.05) the Alpha diversity indexes. The biggest trees and greatest carbon storage were found in forests with pasture matrices when compared to rice fields (14.6 vs 13.4 cm of dbh and 72.9 vs 45.6 t C/ha, respectively). This research provides an understanding of the tree richness and composition and carbon storage of riparian forests in two agricultural matrices, which could be a basis for the establishment of silvopastoral systems with native species.