Dynamic Stand Model for Eucalyptus globulus (L.) in Uruguay

Los modelos dinámicos a nivel de rodal son ampliamente usados en el ámbito forestal. Para su ajuste se emplean datos empíricos que se integran en un conjunto de ecuaciones que describen las relaciones entre diferentes variables. Las metodologías clásicas para desarrollar ecuaciones de transición invariantes con respecto al intervalo de simulación (path invariance) e invariantes respecto a la edad de referencia empleadas son algebraic difference approach (ADA) y generalized algebraic difference approach (GADA). El objetivo de este trabajo fue desarrollar un modelo dinámico de rodal para Eucalyptus globulus, empleando ecuaciones de transición para área basal, altura media dominante y mortalidad, utilizando enfoque de variables dummy. Los datos utilizados provienen de 168 parcelas permanentes. Las ecuaciones evaluadas individualmente fueron luego ajustadas simultáneamente mediante seemingly unrelated regression (SUR). En base al análisis de bondad de ajuste y de la capacidad predictiva, se seleccionó el modelo propuesto por Korf, modificado por Cieszewski (2004), para la altura media dominante; el modelo de Levakovic (Zeide, 1993), para el área basal y el modelo de Pienaar y Shiver (1981) para la mortalidad. El modelo de simulación desarrollado es más flexible y permite levantar algunas de las limitantes del modelo utilizado anteriormente. Su integración a sistemas de apoyo a la toma de decisiones constituirá una herramienta de gran utilidad para la planificación y toma de decisiones en el sector forestal.Stand level dynamic models are widely used in forestry. Fitting empirical data that is integrated into a set of equations is used to describe the relationships between different variables The classic methodologies to develop equations invariant with respect to transition simulation interval (path invariance) and invariant respect to the reference age are employed algebraic difference approach (ADA) and generalized algebraic difference approach (GADA). The aim of this study was to develop a dynamic model for Eucalyptus globulus stand using transition equations for basal area, dominant average height and mortality, using tle dummy variables approach. The data used are from 168 permanent plots. The equations evaluated individually were then adjusted simultaneously by seemingly unrelated regression (SUR). Based on the analysis of goodness of fit and predictive ability, the model proposed by Korf, as amended by Cieszewski (2004), for the dominant average height was selected; Levakovic model (Zeide, 1993) for the basal area and the model Pienaar and Shiver (1981) for mortality. The simulation model developed is more flexible and can lift some of the limitations of the model used previously. Its integration into a decision support system (DSS), constitute a useful tool for planning and decision making in the forestry sector.S

Aplicación de imágenes de satélites y datos LiDAR en la modelización e inventario de Eucalyptus spp en Uruguay

La integración de información de inventarios de campo, con datos procedentes de sensores remotos y su alta correlación con la estructura de la vegetación, permite ajustar modelos precisos para la estimación de la producción forestal. Esto impacta reduciendo costos, tiempos y sesgos, generando productos que son insumos para procesos como la segmentación y la optimización de la cosecha. En este trabajo se presenta una alternativa a los inventarios forestales y al procesamiento de datos, mediante el uso de sensores LiDAR e imágenes multiespectrales. El objetivo general fue evaluar el uso de LiDAR y datos multiespectrales, en plantaciones de Eucalyptus grandis y Eucalyptus dunnii en Uruguay; para mejorar la calidad y la cantidad de información brindada para optimizar los procesos de gestión forestal con respecto a los sistemas de inventario tradicionales. Los resultados obtenidos demuestran la mejora en la precisión y en la calidad de los datos frente a los inventarios tradicionales. Se proporcionan herramientas que permiten mejorar la precisión en cuatro aspectos para la cuantificación y el manejo de la producción forestal: i) el uso de modelos compatibles y aditivos; ii) el modelado de las variables del rodal a gran escala empleando datos de teledetección; iii) la delimitación de zonas homogéneas dentro del rodal basada en una evaluación no supervisada; y iv) un método de programación lineal que optimiza los planes de corta basado en la disponibilidad de madera, el secuestro de carbono y el Valor Actual Neto. Se concluye que la aplicación de herramientas de geomática en el sector forestal supone un cambio fundamental en las prácticas de inventarios, desde su planificación, ejecución y resolución, así como de la capacidad para generar modelos predictivos y de algoritmos de segmentación con mayor precisión. Se comprobó que el uso de datos procedentes de sensores activos y pasivos incrementa las posibilidades de automatización de inventarios forestales, aumentando la resolución espacial y la temporal de la cartografía forestal. Esto, junto con el uso de técnicas estadísticas paramétricas y no paramétricas, constituyen un avance en el campo del manejo forestal en Uruguay.The integration of information from field inventories, with data from remote sensors, and its high correlation with the structure of the vegetation, allows to adjust precise models for the estimation of forest production. This allows for a reduction in costs, time and bias, producing valuable inputs for processes such as segmentation and optimizing the harvest. Here we present an alternative to forest inventories and data processing through the use of LiDAR and multispectral images. The main objective was to evaluate the use of LiDAR information and high-resolution multispectral data in Eucalyptus plantations in Uruguay, to improve the quality and quantity of information provided to optimize forest management processes with respect to traditional inventory systems. The results obtained demonstrate the improvement in precision and quality of the data compared to traditional inventories. Tools that improve precision in four fundamental aspects for the quantification and management of forest production are provided: i) the use of compatible and additives models; ii) modeling of stand variables on a large scale using remote sensing data; iii) delimitation of homogeneous areas within the stand based on an unsupervised assessment; and iv) a method for optimizing felling plans based on timber availability, carbon prices, and harvest age. The main conclusion is that the application of geomatic tools in the forestry sector represent a fundamental change in inventory practices, from planning, execution and resolution, as well as the ability to generate predictive models and segmentation algorithms with greater precision than those obtained with field inventories. Throughout the thesis, it is shown that the use of data from different active and passive sensors increases the possibilities for automating forest inventories, increasing the spatial and temporal resolution of forest cartography. This, together with the use of parametric and non-parametric statistical techniques, constitutes an advance in the field of forest management in Uruguay

Desarrollo de un modelo dinámico de rodal para Eucalyptus globulus L. en Uruguay

Programa de Posgrad

Use of Optimization Modeling to Assess the Effect of Timber and Carbon Pricing on Harvest Scheduling, Carbon Sequestration, and Net Present Value of Eucalyptus Plantations

Quantifying the impact of carbon (C) and timber prices on harvest scheduling and economic returns is essential to define strategies for the sustainable management of short-rotation plantations so that they can provide timber products and contribute to C sequestration. In this paper, we present a mixed-integer linear programming model that optimizes harvest scheduling at the forest level, C sequestration, and Net Present Value (NPV) over a planning period of up to 15 years. The model included revenue from the sale of timber (pulplogs) and credits from the net C sequestered during the life of the stands. In addition, plantation establishment, management, harvesting, and transportation costs were included in the analysis. The study area comprised 88 Eucalyptus grandis W. Hill and Eucalyptus dunnii Maiden stands located in Uruguay, totaling a forest area of nearly 1,882 ha. The study investigated the impact of C and timber prices on NPV, harvest schedules, stands’ harvest age, timber flows to customers, and C sequestered per period. The maximum NPV among all the scenarios evaluated (USD 7.53 M) was calculated for a C price of 30 USD t−1, an interest rate of 6%, and a timber price of 75 USD m−3. This was USD 2.14 M higher than the scenario with the same parameters but that included only revenue from timber. C prices also impacted stands’ harvest age, C sequestration, and timber flows delivered to end customers. On average, in scenarios that included C prices, timber flows and C sequestration increased by 15.4 and 12.1%, respectively, when C price increased from 5 to 30 USD t−1. These results demonstrate that harvest scheduling, harvest age, and NPV are very sensitive to C and timber, and that the best economic returns are obtained when the stands are managed to maximize timber production and C sequestration

Patterns in flight phenologies of bark beetles (Coleoptera: Scolytinae) in commercial pine tree plantations in Uruguay

The increasing forested area in Uruguay facilitates the establishment of exotic bark and ambrosia beetles. In 2009, the first infestation of bark beetles was officially recorded. The outbreak included Hylurgus ligniperda, Cyrtogenius luteus and Orthotomicus erosus. The objective of this study was to describe and compare the seasonal flight activity and development time of bark beetles in Pinus taeda commercial stands. Flight activity was monitored by placing interception traps from July 2012 to July 2013. Every 15 days, beetles were collected. Development time was assessed with sets of trap logs from June 2013 to June 2014 during every season. A fortnight after the presence of colonization signs was verified, trap logs were taken to the lab to be incubated. Among the three species of bark beetles captured, H. ligniperda was the most abundant, representing 57 % of the total captures,followed by O. erosus (30 %) and C. luteus 12 %). Hylurgus ligniperda was captured throughout the monitoring period, showing flight peaks during fall and winter. On the other hand, captures of O. erosus were recorded mostly during spring and summer. Cyrtogenius luteus was captured exclusively during high temperature periods. For all species recorded, log colonization date varied through seasons matching the flight period. Incubation time was strongly influenced by temperature, with shorter generations in high temperature periods. Correspondingly, differences in the duration of the subcortical phase were observed for the three species. Our study provided valuable information that can be used to adjust pruning and thinning schedules by forestry companies

Stand Characterization of Eucalyptus spp. Plantations in Uruguay Using Airborne Lidar Scanner Technology

Airborne lidar scanner (ALS) technology is used in a variety of applications, including forestry. ALS has enormous potential for the estimation of relevant biometric parameters in forest plantations. This study investigates the use of an object-oriented semi-automated segmentation algorithm for stands delineation, based on modeling ALS data, in plantations of Eucalyptus grandis and E. dunnii in Uruguay. The results show that non-parametric methods delivered more accurate and less biased results for total volume (TV) with R2 0.93, RMSE 20.04 m3 h−1 for E. grandis and R2 0.93, RMSE 18.43 m3 h−1 for E.dunnii; and above ground biomass (AGB) with R2 0.95, RMSE 70.2 kg h−1 for E. grandis and R2 0.96, RMSE: 71.2 Kg h−1 for E. dunnii. Parametric methods performed better for dominant height (Ho) with R2 0.98, RMSE 0.67 m and R2: 0.96, RMSE: 0.8 m for E. grandis and E. dunnii, respectively. The most informative ALS metrics for the estimation of AGB and TV were metrics related to the elevation in parametric models (Elev.70 and Elev.75), while for the non-parametric models (k-NN) they were Elev.75 and canopy density. For Ho, the ALS metrics selected were also related to elevation both in the parametric (Elev.90 and Elev.99) and random forest models (Elev.max and Elev.75). The segmentation methodology proposed here matched closely the segments delineated by human operators, and provides a low-cost, cost-effective, easy to apply and update model aimed at generating AGB or TV maps for harvest tasks, based on rasters derived from ALS metrics. The present research shows the capacity of ALS metrics to improve extensive strategic inventories; validating and promoting the adoption of ALS technology for inventory forest stands of Eucalyptus spp. in Uruguay

What Factors Control the Crude Protein Content Variation of a Basaltic “Campos” Native Grassland of South America?

Native grasslands are the main source of food for livestock in the Campos region of South America. These forage resources are heterogeneous in species composition, grazing management, and soil fertility within a context of variable climate, all of which are factors that affect forage crude protein content over time and space. Despite the importance of protein in livestock nutrition, there is a gap in the knowledge of how fertilisation, sward height, and soil water availability influence the crude protein content of these grasslands. We used data from a long-term fertilisation experiment to construct a structural model aiming to identify the main factors influencing forage crude protein content of a basaltic native grassland in northern Uruguay. The structural model revealed that both fertilisation and the increase in soil water availability (through the improvement of the nitrogen content of green leaves) are the main pathways by which forage crude protein content increases. This new approach (which identifies and quantifies the main factors that drive forage crude protein content of native grasslands) could be used to support prediction models for forage protein content in order to improve grazing livestock nutrition of Campos native grasslands.EEA Concepción del UruguayFil: Núñez, Laura. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; UruguayFil: Hirigoyen, Andrés. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Forestal; UruguayFil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; ArgentinaFil: Durante, Martin. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; UruguayFil: Arroyo, José María. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA La Estanzuela. Programa Pasturas y Forrajes; UruguayFil: Cazzuli, Fiorella. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; UruguayFil: Bremm, Carolina. Universidade Federal de Rio Grande do Sul.Faculdade de Agronomia. Departamento de Plantas Forrageiras e Agrometeorologia. Programa de Pós-Graduação em Zootecnia; BrasilFil: Jaurena, Martín. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; Urugua

Antibiotic resistance of Staphylococcus aureus associated with subclinical and clinical mastitis in Uruguay during an eight-year period

Records of in vitro susceptibility tests performed between 2008 and 2015 were retrospectively reviewed in order to evaluate the dynamic profiles of possible changes in antimicrobial resistance of Staphylococcus aureus isolated from milk samples of cows with subclinical mastitis from 12 different Uruguayan Provinces. The results of 1,631 isolates tested by disk diffusion techniquefor susceptibility to penicillin and erythromycin were analysed. The possible tendency or changes in the behaviour of this pathogen against penicillin and erythromycin in the 8 year period was evaluated using the chi-square tests for trend and the homogeneity. The highest rate of resistance was observed for penicillin (36.9% in 2010), while erythromycin showed a resistance rate significantly lower (5.7% in 2015). The test for trend showed a significant trend towards decreased resistance to penicillin, whereas for erythromycin an increased resistance trend was observed. The determination of the scope of the problem is essential for the formulation and monitoring of effective response to anti-microbial resistance (AMR). Antibiotic assessment in Uruguay is now being reviewed with the objective of limiting antibiotics prescription to professionals trained to select a successful therapy, choosing the appropriated drug and treatment duration according each situation. To generate knowledge on the magnitude and tendency of the AMR problem using country-specific information must be a priority

Site index estimation using airborne laser scanner data in Eucalyptus dunnii maide stands in Uruguay

Intensive silviculture demands new inventory tools for better forest management and planning. Airborne laser scanning (ALS) was shown to be one of the best alternatives for high-precision inventories applied to productive plantations. The aim of this study was to generate multiple stand-scale maps of the site index (SI) using ALS data in the intensive silviculture of Eucalyptus dunnii Maide plantations in Uruguay. Forty-three plots (314.16 m3) were established in intensive E. dunnii plantations in the departments of Río Negro and Paysandú (Uruguay). ALS data were obtained for an area of 1995 ha. Linear and Random Forest models were fitted to estimate the height and site index, and OrpheoToolBox (OTB) software was used for stand segmentation. Linear models for dominant height (DH) estimation had a better fit (R2 = 0.84, RMSE = 0.94 m, MAPE = 0.04, Bias = 0.002) than the Random Forest (R2 = 0.85, RMSE = 1.27 m, MAPE = 7.20, Bias=−0.173) model when including only the 99th percentile metric. The coefficient between RMSE values of the cross-validation and RMSE of the model had a higher value for the linear model (0.93) than the Random Forest (0.75). The SI was estimated by applying the RF model, which included the ALS metrics corresponding to the 99th height percentile and the 80th height bicentile (R2 = 0.65; RMSE = 1.62 m). OTB segmentation made it possible to define a minimum segment size of 2.03 ha (spatial radius = 30, range radius = 1 and minimum region size = 64). This study provides a new tool for better forest management and promotes the need for further progress in the application of ALS data in the intensive silviculture of Eucalyptus spp. plantations in Uruguay

Selection of local and general hypsometric models for Eucalyptus globulus in stands of the southeast of Buenos Aires province, Argentina

El objetivo de este trabajo fue seleccionar modelos hipsométricos locales y generales para estimar alturas totales (h; m) de Eucalyptus globulus Labill. en macizos del sudeste de Buenos Aires, Argentina. Del conjunto inicial de 53 modelos candidatos, fueron seleccionados 14 para su validación. Se emplearon 236 árboles apeados para el ajuste y la validación cruzada, efectuando posteriormente una validación independiente con 743 árboles, cuyos datos de altura y diámetro a la altura del pecho (d) se obtuvieron en un inventario no destructivo. Las ecuaciones locales tuvieron en general la menor calidad de ajuste y precisión. Los mejores resultados con ecuaciones generales se lograron incorporando variables de rodal como el diámetro medio cuadrático (dg; cm), el número de individuos vivos por hectárea (N) y la altura dominante (H0; m). La inclusión de otras variables como la edad, el índice de sitio, el diámetro máximo y el área basal no mejoraron los indicadores de ajuste y validación. Se seleccionaron los tres modelos que obtuvieron los mejores estadísticos de ajuste y validación (Coeficiente de determinación ajustado R2 aj.>0,69; Eficiencia del modelo>0,76; Raíz del error medio cuadrático0,69; Model efficiency>0,76; Root mean square error<3,3 m), seeking a compromise between prediction quality on the one hand and ease of use on the other. The models were recalibrated for the entire sample of 979 trees, and aimed to cover a wide range of possible uses. For expeditive applications, the local, exponential model 1 was selected. For those users looking for more accurate height estimates without measuring any stand height, the general model 4 was selected, which is based on d, dg and N. Finally, for those applications that require greater precision, we selected the general model 7, that employ d and H0 as predictor variables. The combined use of models 1, 4 and 7 allows h estimations with relative errors smaller than ±10%, in a range of tree sizes from 2 to 55 cm of d.Facultad de Ciencias Agrarias y Forestale