Forests are the most diverse terrestrial ecosystems and their biological diversity includes trees, but also other plants, animals, and micro-organisms. One-third of the forested land is in boreal zone; therefore, changes in biological diversity in boreal forests can shape biodiversity, even at global scale. Several forest attributes, including size variability, amount of dead wood, and tree species richness, can be applied in assessing biodiversity of a forest ecosystem. Remote sensing offers complimentary tool for traditional field measurements in mapping and monitoring forest biodiversity. Recent development of small unmanned aerial vehicles (UAVs) enable the detailed characterization of forest ecosystems through providing data with high spatial but also temporal resolution at reasonable costs. The objective here is to deepen the knowledge about assessment of plot-level biodiversity indicators in boreal forests with hyperspectral imagery and photogrammetric point clouds from a UAV. We applied individual tree crown approach (ITC) and semi-individual tree crown approach (semi-ITC) in estimating plot-level biodiversity indicators. Structural metrics from the photogrammetric point clouds were used together with either spectral features or vegetation indices derived from hyperspectral imagery. Biodiversity indicators like the amount of dead wood and species richness were mainly underestimated with UAV-based hyperspectral imagery and photogrammetric point clouds. Indicators of structural variability (i.e., standard deviation in diameter-at-breast height and tree height) were the most accurately estimated biodiversity indicators with relative RMSE between 24.4% and 29.3% with semi-ITC. The largest relative errors occurred for predicting deciduous trees (especially aspen and alder), partly due to their small amount within the study area. Thus, especially the structural diversity was reliably predicted by integrating the three-dimensional and spectral datasets of UAV-based point clouds and hyperspectral imaging, and can therefore be further utilized in ecological studies, such as biodiversity monitoring.

This article aims to contribute to the debate on the SUS regionalization policy and the establishment of health regions in Brazil. Understanding them require to recognize the dichotomy between public health and individual health -which marks the history of Brazilian public health -and identify the different rationalities that lead this process. Such rationalities allow not only to consider the legacy of municipalization in the current regionalization process, as well as to establish links between the two fields of fundamental knowledge to the debate, epidemiology and geography. Clinical epidemiology, privileging individual health, gives basis to a healthcare model that prioritizes the optimization of resources. The recognition of health in its broader concept, in the social epidemiology, bases an attention model aimed at social determinants. With geography, functional regions can be formulated, based on Christaller's theory, or lablachianas regions which recognize the social loco / regional structure, allowing intervention in determining or conditioning the way of illness and death of populations.

Forests are in a permanent state of change due to natural and anthropogenic processes. Long-term time series analysis makes it possible to reconstruct the forest history and perform a multitemporal analysis on the cause and effect of changes. This paper describes an approach for successional stage classification in a tropical forest based on vertical structure variations. Stereophotogrammetry and novel image matching methods are used to produce dense digital surface models (DSMs) from optical images (historical and contemporary). An approach was developed to classify the successional stages of trees using local height variations provided by a DSM and image intensity values. Experiments were performed in a semi-deciduous tropical forest fragment located in the West of São Paulo State, Brazil. Six test sample plots and a line transect were established and field surveys were conducted to collect forest variables. These variables were used to characterize and validate five successional classes based on secondary tree species that stratify the forest canopy. The current status of the entire forest fragment was characterized using recent photogrammetric imagery, and a map of historical successional stages was established by analyzing the historical photogrammetric imagery. The investigation demonstrated that the proposed technique can be used to reconstruct the geometric structure of a forest canopy from aerial images. The successional stages can be identified and compared over time using multitemporal photogrammetric imagery and DSMs, which enables an analysis of forest cover changes. The results indicated that the successional stage has changed dramatically during the 50 years period of time.

Question: Small and marginal forest populations are a focus of attention because of their high biodiversity value as well as the risk of population decline and loss. In this context, we ask to what extent a small, marginal Quercus suber (Cork oak) population located in the eastern Iberian Peninsula (Valencia, Spain) has the capacity for self‐regeneration and what are the factors that determine its recruitment variability. Location: Quercus suber forest in Pinet (Valencia, Spain). Methods: We performed a spatially explicit sampling both of the recruitment and of the potential parameters that could account for the recruitment variability. Using regression techniques we model the recruitment occurrence and abundance, and then we test to what extent the model obtained is still constrained by the spatial dependence. Results: Quercus suber recruitment density ranges from 0 to 18.66 individuals/25m2 (mean = 1.46, SD = 2.8), with a very skewed distribution. Recruitment is similar under Q. suber forests and under Pinus forests, but it is almost absent under shrublands. Thus the parameters that explain most of the recruitment variability in local vegetation types are: the presence and cover of shrubs (negative relationship with recruitment), the basal area of Q. suber and Pinus and the amount of bare soil (all positively related to recruitment). These parameters are strongly related to the ecological processes driving recruitment (i.e. dispersal and predation) and they remove most of the spatial dependence of recruitment. Most recruiters, however, are small, forming a seedling bank rather than growing to successfully colonize new habitats. Conclusion: The results suggest that although recruitment densities are not very high, they do not limit potential regeneration in the Pinet Q. suber forest. However, successful regeneration is not observed. If we aim to increase the Pinet Q. suber population size, land management measures need to provide appropriate conditions for both seedling establishment in shrublands (e.g. shrub clearing) and seedling growth in woodlands (e.g. Pinus logging).

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