ABSTRACT
Old‐growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human‐modified ...tropical landscapes (HMTLs). Secondary forests thus emerge as a potential repository for tropical biodiversity, and also as a source of essential ecosystem functions and services in HMTLs. Such critical roles are controversial, however, as they depend on successional, landscape and socio‐economic dynamics, which can vary widely within and across landscapes and regions. Understanding the main drivers of successional pathways of disturbed tropical forests is critically needed for improving management, conservation, and restoration strategies. Here, we combine emerging knowledge from tropical forest succession, forest fragmentation and landscape ecology research to identify the main driving forces shaping successional pathways at different spatial scales. We also explore causal connections between land‐use dynamics and the level of predictability of successional pathways, and examine potential implications of such connections to determine the importance of secondary forests for biodiversity conservation in HMTLs. We show that secondary succession (SS) in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio‐temporal scales. SS is relatively fast and more predictable in recently modified landscapes and where well‐preserved biodiversity‐rich native forests are still present in the landscape. Yet the increasing variation in landscape spatial configuration and matrix heterogeneity in landscapes with intermediate levels of disturbance increases the uncertainty of successional pathways. In landscapes that have suffered extensive and intensive human disturbances, however, succession can be slow or arrested, with impoverished assemblages and reduced potential to deliver ecosystem functions and services. We conclude that: (i) succession must be examined using more comprehensive explanatory models, providing information about the forces affecting not only the presence but also the persistence of species and ecological groups, particularly of those taxa expected to be extirpated from HMTLs; (ii) SS research should integrate new aspects from forest fragmentation and landscape ecology research to address accurately the potential of secondary forests to serve as biodiversity repositories; and (iii) secondary forest stands, as a dynamic component of HMTLs, must be incorporated as key elements of conservation planning; i.e. secondary forest stands must be actively managed (e.g. using assisted forest restoration) according to conservation goals at broad spatial scales.
Vision-based fall detection systems have experienced fast development over the last years. To determine the course of its evolution and help new researchers, the main audience of this paper, a ...comprehensive revision of all published articles in the main scientific databases regarding this area during the last five years has been made. After a selection process, detailed in the Materials and Methods Section, eighty-one systems were thoroughly reviewed. Their characterization and classification techniques were analyzed and categorized. Their performance data were also studied, and comparisons were made to determine which classifying methods best work in this field. The evolution of artificial vision technology, very positively influenced by the incorporation of artificial neural networks, has allowed fall characterization to become more resistant to noise resultant from illumination phenomena or occlusion. The classification has also taken advantage of these networks, and the field starts using robots to make these systems mobile. However, datasets used to train them lack real-world data, raising doubts about their performances facing real elderly falls. In addition, there is no evidence of strong connections between the elderly and the communities of researchers.
1. Seasonally dry tropical forests (SDTFs) are one of the most threatened forests world-wide. These species-rich forests not only cope with several acute (e.g. forest loss) and chronic (e.g. ...overgrazing and firewood extraction) human disturbances but also with climate change (e.g. longer and more severe droughts); yet, the isolated and combined effects of climate and acute and chronic human disturbances on SDTF vegetation are poorly known. 2. Given the environmental filter imposed by drought in SDTFs, the composition and structure of vegetation is expected to be strongly associated with annual precipitation, and thus the effects of human disturbances on vegetation may also depend on precipitation (i.e. interacting effect). 3. We tested these hypotheses in the Brazilian Caatinga – a SDTF threatened by climate change and human disturbances. We evaluated the isolated and combined (both additive and multiplicative) effect of precipitation, a chronic disturbance index and acute disturbance (landscape forest cover) on the diversity, stem density, evenness, taxonomic composition and above-ground biomass of adult trees and shrubs across 19 0·1-ha plots distributed along a disturbance and precipitation gradients. 4. We recorded 5541 stems from 129 species. Precipitation showed a stronger (positive) effect on species diversity than acute and chronic disturbances and, as expected, the effect of disturbance depended on precipitation (interacting effect): that is, species diversity (especially the number of rare species) was negatively related to forest loss but positively related to chronic disturbance in wetter sites, whereas in drier sites, species diversity was weakly related to forest cover, but strongly and negatively related to chronic disturbance. Contrary to species diversity, community evenness, stem density and biomass were weakly related to all predictors. 5. Synthesis. Precipitation appears to be a strong environmental filter determining the distribution of water-demanding plant species. Chronic disturbance in wetter (high-productive) forests may favour species diversity by increasing ecosystem heterogeneity (intermediate disturbance hypothesis). Yet, the biodiversity costs of chronic disturbance are higher in drier (low-productive) forests; that is, there is a co-limitation imposed by drought and disturbance in drier forests. Overall, our findings indicate that rapid climatic changes in the region will probably have strong negative effects on this seasonally dry tropical forest.
There is a significant variety of vascular conduits options for coronary bypass surgery. Adequate graft selection is the most important factor for the success of the intervention. To ensure ...durability, permeability, and bypass function, there must be a morphological similarity between the graft and the coronary artery. The objective of this review was to analyze the morphological characteristics of the grafts that are most commonly used in coronary bypass surgery and the coronary arteries that are most frequently occluded. We included clinical information regarding the characteristics that determine the behavior of the grafts and its permeability over time. Currently, the internal thoracic artery is the standard choice for bypass surgery because of the morphological characteristics of the wall that makes less prone to developing atherosclerosis and hyperplasia. The radial and right gastroepiploic arteries are the following second and third best options, respectively. The ulnar artery is the preferred choice when other conduits are not feasible.
With accelerated deforestation and fragmentation through the tropics, assessing the impact that landscape spatial changes may have on biodiversity is paramount, as this information is required to ...design and implement effective management and conservation plans. Primates are expected to be particularly dependent on the landscape context; yet, our understanding on this topic is limited as the majority of primate studies are at the local scale, meaning that landscape-scale inferences are not possible. To encourage primatologists to assess the impact of landscape changes on primates, and help future studies on the topic, we describe the meaning of a "landscape perspective" and evaluate important assumptions of using such a methodological approach. We also summarize a number of important, but unanswered, questions that can be addressed using a landscape-scale study design. For example, it is still unclear if habitat loss has larger consistent negative effects on primates than habitat fragmentation per se. Furthermore, interaction effects between habitat area and other landscape effects (e.g., fragmentation) are unknown for primates. We also do not know if primates are affected by synergistic interactions among factors at the landscape scale (e.g., habitat loss and diseases, habitat loss and climate change, hunting, and land-use change), or whether landscape complexity (or landscape heterogeneity) is important for primate conservation. Testing for patterns in the responses of primates to landscape change will facilitate the development of new guidelines and principles for improving primate conservation.
ABSTRACT
The legacy of the ‘SL > SS principle’, that a single or a few large habitat patches (SL) conserve more species than several small patches (SS), is evident in decisions to protect large ...patches while down‐weighting small ones. However, empirical support for this principle is lacking, and most studies find either no difference or the opposite pattern (SS > SL). To resolve this dilemma, we propose a research agenda by asking, ‘are there consistent, empirically demonstrated conditions leading to SL > SS?’ We first review and summarize ‘single large or several small’ (SLOSS) theory and predictions. We found that most predictions of SL > SS assume that between‐patch variation in extinction rate dominates the outcome of the extinction–colonization dynamic. This is predicted to occur when populations in separate patches are largely independent of each other due to low between‐patch movements, and when species differ in minimum patch size requirements, leading to strong nestedness in species composition along the patch size gradient. However, even when between‐patch variation in extinction rate dominates the outcome of the extinction–colonization dynamic, theory can predict SS > SL. This occurs if extinctions are caused by antagonistic species interactions or disturbances, leading to spreading‐of‐risk of landscape‐scale extinction across SS. SS > SL is also predicted when variation in colonization dominates the outcome of the extinction–colonization dynamic, due to higher immigration rates for SS than SL, and larger species pools in proximity to SS than SL. Theory that considers change in species composition among patches also predicts SS > SL because of higher beta diversity across SS than SL. This results mainly from greater environmental heterogeneity in SS due to greater variation in micro‐habitats within and across SS habitat patches (‘across‐habitat heterogeneity’), and/or more heterogeneous successional trajectories across SS than SL. Based on our review of the relevant theory, we develop the ‘SLOSS cube hypothesis’, where the combination of three variables – between‐patch movement, the role of spreading‐of‐risk in landscape‐scale population persistence, and across‐habitat heterogeneity – predict the SLOSS outcome. We use the SLOSS cube hypothesis and existing SLOSS empirical evidence, to predict SL > SS only when all of the following are true: low between‐patch movement, low importance of spreading‐of‐risk for landscape‐scale population persistence, and low across‐habitat heterogeneity. Testing this prediction will be challenging, as it will require many studies of species groups and regions where these conditions hold. Each such study would compare gamma diversity across multiple landscapes varying in number and sizes of patches. If the prediction is not generally supported across such tests, then the mechanisms leading to SL > SS are extremely rare in nature and the SL > SS principle should be abandoned.
1. Secondary forests are increasingly dominant in human-modified tropical landscapes, but the drivers of forest recovery remain poorly understood. Soil conditions influence plant community ...composition, and are expected to change over a gradient of succession. However, the role of soil conditions as an environmental filter driving community assembly during forest succession has rarely been explicitly assessed. 2. We evaluated the role of stand basal area and soil conditions on community assembly and its consequences for community functional properties along a chronosequence of Atlantic forest regeneration following sugar cane cultivation. Specifically, we tested whether community functional properties are related to stand basal area, soil fertility and soil moisture. Our expectations were that edaphic environmental filters play an increasingly important role along secondary succession by increasing functional trait convergence towards more conservative attributes. 3. We sampled soil and woody vegetation features across 15 second-growth (3-30 years) and 11 old-growth forest plots (300 m² each). We recorded tree functional traits related to resource-use strategies (specific leaf area, SLA; leaf dry matter content, LDMC; leaf area, LA; leaf thickness, LT; and leaf succulence, LS) and calculated community functional properties using the community-weighted mean (CWM) of each trait and the functional dispersion (FDis) of each trait separately and all traits together. 4. With exception of LA, all leaf traits were strongly associated with stand basal area; LDMC and SLA increased, while LT and LS decreased with forest development. Such changes in LDMC, LT and LS were also related to the decrease in soil nutrient availability and pH along succession, while soil moisture was weakly related to community functional properties. Considering all traits, as well as leaf thickness and succulence separately, FDis strongly decreased with increasing basal area and decreasing soil fertility along forest succession, presenting the lowest values in oldgrowth forests. 5. Synthesis. Our findings suggest that tropical forest regeneration may be a deterministic process shaped by soil conditions. Soil fertility operates as a key filter causing functional convergence towards more conservative resource-use strategies, such as leaves with higher leaf dry matter content.
Land-use change pushes biodiversity into human-modified landscapes, where native ecosystems are surrounded by anthropic land covers (ALCs). Yet, the ability of species to use these emerging covers ...remains poorly understood. We quantified the use of ALCs by primates worldwide, and analyzed species' attributes that predict such use. Most species use secondary forests and tree plantations, while only few use human settlements. ALCs are used for foraging by at least 86 species with an important conservation outcome: those that tolerate heavily modified ALCs are 26% more likely to have stable or increasing populations than the global average for all primates. There is no phylogenetic signal in ALCs use. Compared to all primates on Earth, species using ALCs are less often threatened with extinction, but more often diurnal, medium or large-bodied, not strictly arboreal, and habitat generalists. These findings provide valuable quantitative information for improving management practices for primate conservation worldwide.
Trichoderma is a genus of filamentous fungi widely studied and used as a biological control agent in agriculture. However, its ability to form fungal networks for inter-plant communication by means ...of the so-called inter-plant "wired communication" has not yet been addressed. In our study we used the model plant Arabidopsis thaliana, the fungus Trichoderma hamatum (isolated from Brassicaceae plants) and the pathogens Sclerotinia sclerotiorum and Xanthomonas campestris (necrotrophic fungus and hemibiotrophic bacteria, respectively). We performed different combinations of isolated/neighboring plants and root colonization/non-colonization by T. hamatum, as well as foliar infections with the pathogens. In this way, we were able to determine how, in the absence of T. hamatum, there is an inter-plant communication that induces systemic resistance in neighboring plants of plants infected by the pathogens. On the other hand, the plants colonized by T. hamatum roots show a greater systemic resistance against the pathogens. Regarding the role of T. hamatum as an inter-plant communicator, it is the result of an increase in foliar signaling by jasmonic acid (increased expression of LOX1 and VSP2 genes and decreased expression of ICS1 and PR-1 genes), antagonistically increasing root signaling by salicylic acid (increased expression of ICS1 and PR-1 genes and decreased expression of LOX1 and VSP2). This situation prevents root colonization by T. hamatum of the foliarly infected plant and leads to massive colonization of the neighboring plant, where jasmonic acid-mediated systemic defenses are induced.
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•Inter-plant communication by non-mycorrhizal fungus is a new field of research.•There is inter-plant communication in A. thaliana plants foliar-pathogen-infected.•T. hamatum induces systemic resistance in A. thaliana plants.•T. hamatum acts as an inter-plant communicator in A. thaliana plants.•Root salicylic acid and foliar jasmonic acid are key in this communication.
Machine learning techniques combined with wearable electronics can deliver accurate short-term blood glucose level prediction models. These models can learn personalized glucose-insulin dynamics ...based on the sensor data collected by monitoring several aspects of the physiological condition and daily activity of an individual. Until now, the prevalent approach for developing data-driven prediction models was to collect as much data as possible to help physicians and patients optimally adjust therapy. The objective of this work was to investigate the minimum data variety, volume, and velocity required to create accurate person-centric short-term prediction models. We developed a series of these models using different machine learning time series forecasting techniques suitable for execution within a wearable processor. We conducted an extensive passive patient monitoring study in real-world conditions to build an appropriate data set. The study involved a subset of type 1 diabetic subjects wearing a flash glucose monitoring system. We comparatively and quantitatively evaluated the performance of the developed data-driven prediction models and the corresponding machine learning techniques. Our results indicate that very accurate short-term prediction can be achieved by only monitoring interstitial glucose data over a very short time period and using a low sampling frequency. The models developed can predict glucose levels within a 15-min horizon with an average error as low as 15.43 mg/dL using only 24 historic values collected within a period of sex hours, and by increasing the sampling frequency to include 72 values, the average error is reduced to 10.15 mg/dL. Our prediction models are suitable for execution within a wearable device, requiring the minimum hardware requirements while at simultaneously achieving very high prediction accuracy.
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