Impacts of global change on iberian forest ecosystems inferred from the spanish national forest inventory = Impactos del cambio global en ecosistemas forestales ibéricos a partir del inventario forestal nacional

Los efectos del cambio global sobre los bosques son una de las grandes preocupaciones de la sociedad del siglo XXI. Algunas de sus posibles consecuencias como son los efectos en la producción, la sostenibilidad, la pérdida de biodiversidad o cambios en la distribución y ensamblaje de especies forestales pueden tener grandes repercusiones sociales, ecológicas y económicas. La detección y seguimiento de estos efectos constituyen uno de los retos a los que se enfrentan en la actualidad científicos y gestores forestales. En base a la comparación de series históricas del Inventario Forestal Nacional Español (IFN), esta tesis trata de arrojar luz sobre algunos de los impactos que los cambios socioeconómicos y ambientales de las últimas décadas han generado sobre nuestros bosques. En primer lugar, esta tesis presenta una innovadora metodología con base geoestadística que permite la comparación de diferentes ciclos de inventario sin importar los diferentes métodos de muestreo empleados en cada uno de ellos (Capítulo 3). Esta metodología permite analizar cambios en la dinámica y distribución espacial de especies forestales en diferentes gradientes geográficos. Mediante su aplicación, se constatarán y cuantificarán algunas de las primeras evidencias de cambio en la distribución altitudinal y latitudinal de diferentes especies forestales ibéricas, que junto al estudio de su dinámica poblacional y tasas demográficas, ayudarán a testar algunas hipótesis biogeográficas en un escenario de cambio global en zonas de especial vulnerabilidad (Capítulos 3, 4 y 5). Por último, mediante la comparación de ciclos de parcelas permanentes del IFN se ahondará en el conocimiento de la evolución en las últimas décadas de especies invasoras en los ecosistemas forestales del cuadrante noroccidental ibérico, uno de los más afectados por la invasión de esta flora (Capítulo 6). ABSTRACT The effects of global change on forests are one of the major concerns of the XXI century. Some of the potential impacts of global change on forest growth, productivity, biodiversity or changes in species assembly and spatial distribution may have great ecological and economic consequences. The detection and monitoring of these effects are some of the major challenges that scientists and forest managers face nowadays. Based on the comparison of historical series of the Spanish National Forest Inventory (NFI), this thesis tries to shed some light on some of the impacts driven by recent socio-economic and environmental changes on our forest ecosystems. Firstly, this thesis presents an innovative methodology based on geostatistical techniques that allows the comparison of different NFI cycles regardless of the different sampling methods used in each of them (Chapter 3). This methodology, in conjunction with other statistical techniques, allows to analyze changes in the spatial distribution and population dynamics of forest species along different geographic gradients. By its application, this thesis presents some of the first evidences of changes in species distribution along different geographical gradients in the Iberian Peninsula. The analysis of these findings, of species population dynamics and demographic rates will help to test some biogeographical hypothesis on forests under climate change scenarios in areas of particular vulnerability (Chapters 3, 4 and 5). Finally, by comparing NFI cycles with permanent plots, this thesis increases our knowledge about the patterns and processes associated with the recent evolution of invasive species in the forest ecosystems of North-western Iberia, one of the areas most affected by the invasion of allien species at national scale (Chapter 6).

Wisconsin forest inventory publication.

Mode of access: Internet.

A Blueprint for forest inventory and analysis research and vision for the future.

"October 1993"--P. [1].

Assessing soil compaction on forest inventory & analysis phase 3 field plots using a pocket penetrometer /

"April 2004."

PRELIMINARY RESULTS OF A LARGE-SCALE TREE INVENTORY OF UPLAND RAIN FOREST IN THE CENTRAL AMAZON

A large-scale inventory of trees > 10cm DBH was conducted in the upland "terra firme" rain forest of the Distrito Agropecuário da SUFRAMA (Manaus Free Zone Authority Agricultural District) approximately 65Km north of the city of Manaus (AM), Srasil. Thegeneral appearance and structure of the forest is described together with local topography and soil texture. Thepreliminary results of the Inventory provide a minimum estimate of 698 tree species in 53 families in the 40Km radius sampled, including 17 undescribed species. Themost numerically abundant families, Lecythidaceae, Leguminosae, 5apotaceae and Burseraceae as also among the most species rich families. One aspect of this diverse assemblage is the proliferation of species within certain genera, Including 26 genera In 17 families with 6 or more species or morphospecies. Most species have very low abundances of less than 1 tree per hectare. While more abundant species do exist at densities ranging up to a mean of 12 trees per ha, many have clumped distributions leading to great variation in local species abundance. The degree of similarity between hectare samples based int the Coefficient of Community similarity Index varies widely over different sample hectares for five ecologically different families. Soil texture apparently plays a significant role In determining species composition in the different one hectare plots examined while results for other variable were less consistent. Greater differences in similarity indices are found for comparisons with a one hectare sample within the same formation approximately 40Km to the south. It is concluded that homogeneity of tree community composition within this single large and diverse yet continuous upland forest formation can not be assumed.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Using FCD Mapper Software and Landsat Images to Assess Forest Canopy Density in Landscapes in Australia and the Philippines

Using Landsat imagery, forest canopy density (FCD) estimated with the FCD Mapper®, was correlated with predominant height (PDH, measured as the average height of the tallest 50 trees per hectare) for 20 field plots measured in native forest at Noosa Heads, south-east Queensland, Australia. A corresponding image was used to calculate FCD in Leyte Island, the Philippines and was validated on the ground for accuracy. The FCD Mapper was produced for the International Tropical Timber Organisation and estimates FCD as an index of canopy density using reflectance characteristics of Landsat Enhanced Thematic (ETM) Mapper images. The FCD Mapper is a ‘semi-expert’ computer program which uses interactive screens to allow the operator to make decisions concerning the classification of land into bare soil, grass and forest. At Noosa, a positive strong nonlinear relationship (r2 = 0.86) was found between FCD and PDH for 15 field plots with variable PDH but complete canopy closure. An additional five field plots were measured in forest with a broken canopy and the software assessed these plots as having a much lower FCD than forest with canopy closure. FCD estimates for forest and agricultural land in the island of Leyte and subsequent field validation showed that at appropriate settings, the FCD Mapper differentiated between tropical rainforest and banana or coconut plantation. These findings suggest that in forests with a closed canopy this remote sensing technique has promise for forest inventory and productivity assessment. The findings also suggest that the software has promise for discriminating between native forest with a complete canopy and forest which has a broken canopy, such as coconut or banana plantation.

The relationship between stem vessel parameters and the development of strata in the early stages of secondary forest succession in Amazonia

In order to compare the development of strata in the early stages of secondary forest succession with vessel parameters of the tree species, a forest inventory was carried out in 4-year (Q1: 48 m2), 11-year (Q2: 400 m2) and 20-year (Q3: 400 m2) forests and vessel parameters were investigated from stem cross sections of 18 species obtained in Q2. Thirty three species (21 families), 77 species (35 families), 39 species (20 families) were found in Ql, Q2, Q3, respectively. The percentage of dead individuals, dead stems and the percentage of individuals with multiple stems increased with time after clear cutting. Also, the total D2H of Q3 was 26.1 times that of Q1, and the development of strata started in Q2 and Q3. The image analysis of vessel size, area and number of vessels revealed that species which reach the forest canopy had a large D2H value, vessel diameter and area, while species which remain near the forest floor had smaller ones. Poecilanthe effusa (Huber) Ducke is an example of the latter case, with a large number of individuals and abundant sprouting of new stems from stumps, but with high mortality.

Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

A discrete forest in a continuous landscape : investigating interactions between natural resource management and sustainable development

Summary Forests are key ecosystems of the earth and associated with a large range of functions. Many of these functions are beneficial to humans and are referred to as ecosystem services. Sustainable development requires that all relevant ecosystem services are quantified, managed and monitored equally. Natural resource management therefore targets the services associated with ecosystems. The main hypothesis of this thesis is that the spatial and temporal domains of relevant services do not correspond to a discrete forest ecosystem. As a consequence, the services are not quantified, managed and monitored in an equal and sustainable manner. The thesis aims were therefore to test this hypothesis, establish an improved conceptual approach and provide spatial applications for the relevant land cover and structure variables. The study was carried out in western Switzerland and based primarily on data from a countrywide landscape inventory. This inventory is part of the third Swiss national forest inventory and assesses continuous landscape variables based on a regular sampling of true colour aerial imagery. In addition, land cover variables were derived from Landsat 5 TM passive sensor data and land structure variables from active sensor data from a small footprint laserscanning system. The results confirmed the main hypothesis, as relevant services did not scale well with the forest ecosystem. Instead, a new conceptual approach for sustainable management of natural resources was described. This concept quantifies the services as a continuous function of the landscape, rather than a discrete function of the forest ecosystem. The explanatory landscape variables are therefore called continuous fields and the forest becomes a dependent and function-driven management unit. Continuous field mapping methods were established for land cover and structure variables. In conclusion, the discrete forest ecosystem is an adequate planning and management unit. However, monitoring the state of and trends in sustainability of services requires them to be quantified as a continuous function of the landscape. Sustainable natural resource management iteratively combines the ecosystem and gradient approaches. Résumé Les forêts sont des écosystèmes-clés de la terre et on leur attribue un grand nombre de fonctions. Beaucoup de ces fonctions sont bénéfiques pour l'homme et sont nommées services écosystémiques. Le développement durable exige que ces services écosystémiques soient tous quantifiés, gérés et surveillés de façon égale. La gestion des ressources naturelles a donc pour cible les services attribués aux écosystèmes. L'hypothèse principale de cette thèse est que les domaines spatiaux et temporels des services attribués à la forêt ne correspondent pas à un écosystème discret. Par conséquent, les services ne sont pas quantifiés, aménagés et surveillés d'une manière équivalente et durable. Les buts de la thèse étaient de tester cette hypothèse, d'établir une nouvelle approche conceptuelle de la gestion des ressources naturelles et de préparer des applications spatiales pour les variables paysagères et structurelles appropriées. L'étude a été menée en Suisse occidentale principalement sur la base d'un inventaire de paysage à l'échelon national. Cet inventaire fait partie du troisième inventaire forestier national suisse et mesure de façon continue des variables paysagères sur la base d'un échantillonnage régulier sur des photos aériennes couleur. En outre, des variables de couverture ? terrestre ont été dérivées des données d'un senseur passif Landsat 5 TM, ainsi que des variables structurelles, dérivées du laserscanning, un senseur actif. Les résultats confirment l'hypothèse principale, car l'échelle des services ne correspond pas à celle de l'écosystème forestier. Au lieu de cela, une nouvelle approche a été élaborée pour la gestion durable des ressources naturelles. Ce concept représente les services comme une fonction continue du paysage, plutôt qu'une fonction discrète de l'écosystème forestier. En conséquence, les variables explicatives de paysage sont dénommées continuous fields et la forêt devient une entité dépendante, définie par la fonction principale du paysage. Des méthodes correspondantes pour la couverture terrestre et la structure ont été élaborées. En conclusion, l'écosystème forestier discret est une unité adéquate pour la planification et la gestion. En revanche, la surveillance de la durabilité de l'état et de son évolution exige que les services soient quantifiés comme fonction continue du paysage. La gestion durable des ressources naturelles joint donc l'approche écosystémique avec celle du gradient de manière itérative.

Models in country scale carbon accounting of forest soils

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.

DYNAMICS AND PREDICTION OF DIAMETRIC STRUCTURE IN TWO ATLANTIC FOREST FRAGMENTS IN NORTHEASTERN BRAZIL

ABSTRACT Monitoring analyses aim to understand the processes that drive changes in forest structure and, along with prediction studies, may assist in the management planning and conservation of forest remnants. The objective of this study was to analyze the forest dynamics in two Atlantic rainforest fragments in Pernambuco, Brazil, and to predict their future forest diameter structure using the Markov chain model. We used continuous forest inventory data from three surveys in two forest fragments of 87 ha (F1) and 388 ha (F2). We calculated the annual rates of mortality and recruitment, the mean annual increment, and the basal area for each of the 3-year periods. Data from the first and second surveys were used to project the third inventory measurements, which were compared to the observed values in the permanent plots using chi-squared tests (a = 0.05). In F1, a decrease in the number of individuals was observed due to mortality rates being higher than recruitment rates; however, there was an increase in the basal area. In this fragment, the fit to the Markov model was adequate. In F2, there was an increase in both the basal area and the number of individuals during the 6-year period due to the recruitment rate exceeding the mortality rate. For this fragment, the fit of the model was unacceptable. Hence, for the studied fragments, the demographic rates influenced the stem density more than the floristic composition. Yet, even with these intense dynamics, both fragments showed active growth.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Phenotypic changes and small mammal impoverishment on a Brazilian Atlantic Forest Island

Faunal impoverishment and distorted species compositions are common phenomena in oceanic islands; however, many land-bridge islands are poorly inventoried, especially in the Neotropics. We sampled a small mammal community on a land-bridge island (Anchieta Island) along the Brazilian coast. We found only one marsupial Didelphis aurita (Wied-Neuwied, 1826) and two rodent species Oligoryzomys nigripes (Olfers, 1818) and Trinomys iheringi (Thomas, 1911) during 12 months of live trapping and 9195 trap-nights. The diversity of rodents and marsupials was not explained by species-area relations, indicating possible past extinctions. The abundance of D. aurita and O. nigripes was approximately three times higher, while the abundance of T. iheringi was approximately four times lower than abundances reported from other Brazilian Atlantic Forest sites. The population of D. aurita exhibited many phenotypic changes; males were on average 8 % smaller and females produced 30 % less litters than those from the mainland and other land-bridge islands. The long history of forest disturbance, habitat loss, reduction in forest productivity, and the recent introduction of mesopredators may be the major drivers that explain the small mammal community composition on this island. © 2013 Walter de Gruyter GmbH, Berlin/Boston.

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.