Simultaneous Tracking of Multiple Objects Using Fast Level Set-Like Algorithm

A topological flexibility of implicit active contours is of great benefit, since it allows simultaneous detection of several objects without any a priori knowledge about their number and shapes. However, in tracking applications it is often required to keep desired objects mutually separated as well as allow each object to evolve itself, i.e., different objects cannot be merged together, but each object can split into several regions that can be merged again later in time. The former can be achieved by applying topology-preserving constraints exploiting either various repelling forces or the simple point concept from digital geometry, which brings, however, an indispensable increase in the execution time and also prevent the latter. In this paper, we propose more efficient and more flexible topology-preserving constraint based on a region indication function, that can be easily integrated into a fast level set-like algorithm [Maska, Matula, Danek, Kozubek, LNCS 6455, 2010] in order to obtain a fast and robust algorithm for simultaneous tracking of multiple objects. The potential of the modified algorithm is demonstrated on both synthetic and real image data

Deep-learning-based segmentation of small extracellular vesicles in transmission electron microscopy images

Small extracellular vesicles (sEVs) are cell-derived vesicles of nanoscale size (~30-200 nm) that function as conveyors of information between cells, reflecting the cell of their origin and its physiological condition in their content. Valuable information on the shape and even on the composition of individual sEVs can be recorded using transmission electron microscopy (TEM). Unfortunately, sample preparation for TEM image acquisition is a complex procedure, which often leads to noisy images and renders automatic quantification of sEVs an extremely difficult task. We present a completely deep-learning-based pipeline for the segmentation of sEVs in TEM images. Our method applies a residual convolutional neural network to obtain fine masks and use the Radon transform for splitting clustered sEVs. Using three manually annotated datasets that cover a natural variability typical for sEV studies, we show that the proposed method outperforms two different state-of-the-art approaches in terms of detection and segmentation performance. Furthermore, the diameter and roundness of the segmented vesicles are estimated with an error of less than 10%, which supports the high potential of our method in biological applications.We want to acknowledge the support of NVIDIA Corporation with the donation of the Titan X (Pascal) GPU used for this research. This work was supported by the Spanish Ministry of Economy and Competitiveness (TEC2013-48552-C2-1-R, TEC2015-73064-EXP, TEC2016-78052-R) (EGM-AMB), a 2017 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (EGM-AMB), and the Czech Science Foundation (GA17-05048S)(MM-PM) and (GJ17-11776Y) (AK-VP)

Structural changes caused by selective logging undermine the thermal buffering capacity of tropical forests

Selective logging is responsible for approximately 50 % of human-induced disturbances in tropical forests. The magnitude of disturbances from logging on the structure of forests varies widely and is associated with a multitude of impacts on the forest microclimate. However, it is still unclear how changes in the spatial arrangement of vegetation arising from selective logging affect the capacity of forests to buffer large-scale climate (i.e., macroclimate) variability. In this study, we leveraged hundreds of terrestrial LiDAR measurements across tropical forests in Malaysian Borneoto quantify the impacts of logging on canopy structural traits, using a space-for-time approach. This information was combined with locally measured microclimate temperatures of the forest understory to evaluate how logging disturbances alter the capacity of tropical forests to buffer macroclimate variability. We found that heavily logged forests were approximately 12 m shorter and had 65 % lower plant area density than unlogged forests, with most plant material allocated in the first 10 m above ground. Heavily logged forests were on average 1.5 °C warmer than unlogged forests. More strikingly, we show that subtle changes in the forest structure were sufficient to reduce the cooling capacity of forests during extremely warm days (e.g., anomalies > 2σ), while understory temperatures in heavily logged forests were often warmer than the macroclimate under the same conditions. Our results thus demonstrate that selective logging is associated with substantial changes in the fine-scale thermal regime of the understory. Hence, mitigating and managing logging disturbances will be critical for maintaining niches and thermal limits within tropical forests in the future

Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Nino

The past 40 years in Southeast Asia have seen about 50% of lowland rainforests converted to oil palm and other plantations, and much of the remaining forest heavily logged. Little is known about how fragmentation influences recovery and whether climate change will hamper restoration. Here, we use repeat airborne LiDAR surveys spanning the hot and dry 2015-16 El Nino Southern Oscillation event to measure canopy height growth across 3,300ha of regenerating tropical forests spanning a logging intensity gradient in Malaysian Borneo. We show that the drought led to increased leaf shedding and branch fall. Short forest, regenerating after heavy logging, continued to grow despite higher evaporative demand, except when it was located close to oil palm plantations. Edge effects from the plantations extended over 300 metres into the forests. Forest growth on hilltops and slopes was particularly impacted by the combination of fragmentation and drought, but even riparian forests located within 40m of oil palm plantations lost canopy height during the drought. Our results suggest that small patches of logged forest within plantation landscapes will be slow to recover, particularly as ENSO events are becoming more frequent. It is unclear whether tropical forest fragments within plantation landscapes are resilient to drought. Here the authors analyse LiDAR and ground-based data from the 2015-16 El Nino event across a logging intensity gradient in Borneo. Although regenerating forests continued to grow, canopy height near oil palm plantations decreased, and a strong edge effect extended up to at least 300m away.Peer reviewe

Forest diversity promotes individual tree growth in central European forest stands

Most experimental evidence on the relationship between biodiversity and ecosystem functioning comes from ecosystems with fast-growing plants, such as grasslands. Although forests provide essential ecological services, they have been less well investigated.  We used dendrochronology to compare the tree radial growth rates of four important timber species in replicated, spatially mapped stands that differed in tree composition and diversity within a central European managed forest.  Growth rates differed among species but were largely unaffected by the density of neighbouring trees.  Increasing stand diversity enhanced individual growth rates, after accounting for the effects of tree density and size. These increases were statistically indistinguishable among the four species. In contrast, the effects of stand and neighbourhood species composition on growth rates were non-significant.  Policy implications. Our study of long-established central European forest stands revealed levels of tree diversity can be increased in managed forests, with the potential for modest increases in tree growth rates. These results suggest that in addition to the biodiversity and risk mitigation benefits associated with shifting practices away from monoculture management, increased carbon sequestration and yields in mature forests are likely to be realized. Our results suggest that it is possible to increase forest diversity with little or no costs to production and even with the potential for modest increases in tree growth rates

Novel temperatures are already widespread beneath the world’s tropical forest canopies

Tropical forest biodiversity is potentially at high risk from climate change, but most species reside within or below the canopy, where they are buffered from extreme temperatures. Here, by modelling the hourly below-canopy climate conditions of 300,000 tropical forest locations globally between 1990 and 2019, we show that recent small increases in below-canopy temperature (<1 °C) have led to highly novel temperature regimes across most of the tropics. This is the case even within contiguous forest, suggesting that tropical forests are sensitive to climate change. However, across the globe, some forest areas have experienced relatively non-novel temperature regimes and thus serve as important climate refugia that require urgent protection and restoration. This pantropical analysis of changes in below-canopy climatic conditions challenges the prevailing notion that tropical forest canopies reduce the severity of climate change impacts

Words apart: Standardizing forestry terms and definitions across European biodiversity studies

Forest biodiversity studies conducted across Europe use a multitude of forestry terms, often inconsistently. This hinders the comparability across studies and makes the assessment of the impacts of forest management on biodiversity highly context-dependent. Recent attempts to standardize forestry and stand description terminology mostly used a top-down approach that did not account for the perspectives and approaches of forest biodiversity experts. This work aims to establish common standards for silvicultural and vegetation definitions, creating a shared conceptual framework for a consistent study on the effects of forest management on biodiversity. We have identified both strengths and weaknesses of the silvicultural and vegetation information provided in forest biodiversity studies. While quantitative data on forest biomass and dominant tree species are frequently included, information on silvicultural activities and vegetation composition is often lacking, shallow, or based on broad and heterogeneous classifications. We discuss the existing classifications and their use in European forest biodiversity studies through a novel bottom-up and top-driven review process, and ultimately propose a common framework. This will enhance the comparability of forest biodiversity studies in Europe, and puts the basis for effective implementation and monitoring of sustainable forest management policies. The standards here proposed are potentially adaptable and applicable to other geographical areas and could be extended to other forest interventions. Forest management Multi-taxon Terminology Silviculture Data harmonizationpublishedVersio