Forest structure in a mosaic of rainforest sites: The effect of fragmentation and recovery after clear cut

A variety of human-induced disturbances such as forest fragmentation and recovery after deforestation for pasture or agricultural activities have resulted in a complex landscape mosaic in the Una region of northeastern Brazil. Using a set of vegetation descriptors, we investigated the main structural changes observed in forest categories that comprise the major components of the regional landscape and searched for potential key descriptors that could be used to discriminate among different forest categories. We assessed the forest structure of five habitat categories defined as (I) interiors and (2) edges of large fragments of old-growth forest (>1000 ha), (3) interiors and (4) edges of small forest fragments (<100 ha), and (5) early secondary forests. Forest descriptors used here were: frequency of herbaceous lianas and woody climbers, number of standing dead trees, number of fallen trunks, litter depth, number of pioneer plants (early secondary and shade-intolerant species), vertical foliage stratification profile and distribution Of trees in different diameter classes. Edges and interiors of forest fragments were significantly different only in the number of standing dead trees. Secondary forests and edges of fragments showed differences in litter depth, fallen trunks and number of pioneer trees, and secondary forests were significantly different from fragment interiors in the number of standing dead trees and the number of pioneer trees. Horizontal and vertical structure evaluated via ordination analysis showed that fragment interiors, compared to secondary forests, were characterized by a greater number of medium (25-35 cm) and large (35-50 cm) trees and smaller numbers of thin trees (5-10 cm). There was great heterogeneity at the edges of small and large fragments, as these sites were distributed along almost the entire gradient. Most interiors of large and small fragments presented higher values of foliage densities at higher strata ( 15-20 m and at 20-25 m height), and lower densities at 1-5 m. All secondary forests and some fragment edge sites showed an opposite tendency. A discriminant function highlighted differences among forest categories, with transects of large fragment interiors and secondary forests representing two extremes along a disturbance gradient determined by foliage structure (densities at 15-20 m and 20-25 m), with the edges of both large and small fragments and the interiors of small fragments scattered across the gradient. The major underlying processes determining patterns of forest disturbance in the study region are discussed, highlighting the importance of forest fragments, independently of its size, as forests recovery after clear cut show a greatly distinct structure, with profound implications on fauna movements. (C) 2009 Elsevier BY. All rights reserved.

Fragmentation drives tropical forest fragments to early successional states: A modelling study for Brazilian Atlantic forests

Land use leads to massive habitat destruction and fragmentation in tropical forests. Despite its global dimensions the effects of fragmentation on ecosystem dynamics are not well understood due to the complexity of the problem. We present a simulation analysis performed by the individual-based model FORMIND. The model was applied to the Brazilian Atlantic Forest, one of the world`s biodiversity hot spots, at the Plateau of Sao Paulo. This study investigates the long-term effects of fragmentation processes on structure and dynamics of different sized remnant tropical forest fragments (1-100 ha) at community and plant functional type (PFT) level. We disentangle the interplay of single effects of different key fragmentation processes (edge mortality, increased mortality of large trees, local seed loss and external seed rain) using simulation experiments in a full factorial design. Our analysis reveals that particularly small forest fragments below 25 ha suffer substantial structural changes, biomass and biodiversity loss in the long term. At community level biomass is reduced up to 60%. Two thirds of the mid- and late-successional species groups, especially shade-tolerant (late successional climax) species groups are prone of extinction in small fragments. The shade-tolerant species groups were most strongly affected; its tree number was reduced more than 60% mainly by increased edge mortality. This process proved to be the most powerful of those investigated, explaining alone more than 80% of the changes observed for this group. External seed rain was able to compensate approximately 30% of the observed fragmentation effects for shade-tolerant species. Our results suggest that tropical forest fragments will suffer strong structural changes in the long term, leading to tree species impoverishment. They may reach a new equilibrium with a substantially reduced subset of the initial species pool, and are driven towards an earlier successional state. The natural regeneration potential of a landscape scattered with forest fragments appears to be limited, as external seed rain is not able to fully compensate for the observed fragmentation-induced changes. Our findings suggest basic recommendations for the management of fragmented tropical forest landscapes. (C) 2011 Elsevier B.V. All rights reserved.

Anthocyanins and tannins in ozone-fumigated guava trees

Psidium guajava ""Paluma"", a tropical tree species, is known to be an efficient ozone indicator in tropical countries. When exposed to ozone, this species displays a characteristic leaf injury identified by inter-veinal red stippling on adaxial leaf surfaces. Following 30 days of three ozone treatments consisting of carbon filtered air (CF - AOT40 = 17 ppb h), ambient non-filtered air (NF - AOT40 = 542 ppb h) and ambient non-filtered air + 40 ppb ozone (NF + O(3) - AOT40 - 7802 ppb h), the amounts of residual anthocyanins and tannins present in 10 P. guajava (""Paluma"") saplings were quantified. Higher amounts of anthocyanins were found in the NF + O(3) treatment (1.6%) when compared to the CF (0.97%) and NF (1.30%) (p < 0.05), and of total tannins in the NF + O(3) treatment (0.16%) compared to the CIF (0.14%). Condensed tannins showed the same tendency as enhanced amounts. Regression analyses using amounts of tannins and anthocyanins, AOT40 and the leaf injury index (LII), showed a correlation between the leaf injury index and quantities of anthocyanins and total tannins. These results are in accordance with the association between the incidence of red-stippled leaves and ozone polluted environments. (C) 2009 Elsevier Ltd. All rights reserved.

Fiedler trees for multiscale surface analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the first nontrivial eigenfunction of the Laplace-Beltrami operator to recursively decompose the surface. For this reason we coin our surface decomposition the Fiedler tree. Using the Fiedler tree ensures a number of attractive properties, including: mesh-independent decomposition, well-formed and nearly equi-areal surface patches, and noise robustness. We show how the evenly distributed patches can be exploited for generating multiresolution high quality uniform meshes. Additionally, our decomposition permits a natural means for carrying out wavelet methods, resulting in an intuitive method for producing feature-sensitive meshes at multiple scales. Published by Elsevier Ltd.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Border trees of complex networks

The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small-world properties of real networks were fundamental to stimulate more realistic models and to understand important dynamical processes related to network growth. However, the properties of the network borders (nodes with degree equal to 1), one of its most fragile parts, remained little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze the border trees of complex networks, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider how their topological properties can be quantified in terms of their depth and number of leaves. We investigate the properties of border trees for several theoretical models as well as real-world networks. Among the obtained results, we found that more than half of the nodes of some real-world networks belong to the border trees. A power-law with cut-off was observed for the distribution of the depth and number of leaves of the border trees. An analysis of the local role of the nodes in the border trees was also performed.

Limit theorems for sequences of random trees

We consider a random tree and introduce a metric in the space of trees to define the ""mean tree"" as the tree minimizing the average distance to the random tree. When the resulting metric space is compact we have laws of large numbers and central limit theorems for sequence of independent identically distributed random trees. As application we propose tests to check if two samples of random trees have the same law.

Bootstrap percolation on homogeneous trees has 2 phase transitions

We study the threshold theta bootstrap percolation model on the homogeneous tree with degree b + 1, 2 <= theta <= b, and initial density p. It is known that there exists a nontrivial critical value for p, which we call p(f), such that a) for p > p(f), the final bootstrapped configuration is fully occupied for almost every initial configuration, and b) if p < p(f) , then for almost every initial configuration, the final bootstrapped configuration has density of occupied vertices less than 1. In this paper, we establish the existence of a distinct critical value for p, p(c), such that 0 < p(c) < p(f), with the following properties: 1) if p <= p(c), then for almost every initial configuration there is no infinite cluster of occupied vertices in the final bootstrapped configuration; 2) if p > p(c), then for almost every initial configuration there are infinite clusters of occupied vertices in the final bootstrapped configuration. Moreover, we show that 3) for p < p(c), the distribution of the occupied cluster size in the final bootstrapped configuration has an exponential tail; 4) at p = p(c), the expected occupied cluster size in the final bootstrapped configuration is infinite; 5) the probability of percolation of occupied vertices in the final bootstrapped configuration is continuous on [0, p(f)] and analytic on (p(c), p(f) ), admitting an analytic continuation from the right at p (c) and, only in the case theta = b, also from the left at p(f).

Examples from trees, related to discrete subsets, pseudo-radiality and omega-boundedness

We construct some examples using trees. Some of them are consistent counterexamples for the discrete reflection of certain topological properties. All the properties dealt with here were already known to be non-discretely reflexive if we assume CH and we show that the same is true assuming the existence of a Suslin tree. In some cases we actually get some ZFC results. We construct also, using a Suslin tree, a compact space that is pseudo-radial but it is not discretely generated. With a similar construction, but using an Aronszajn tree, we present a ZFC space that is first countable, omega-bounded but is not strongly w-bounded, answering a question of Peter Nyikos. (C) 2008 Elsevier B.V. All rights reserved.

Nuclear magnetic resonance characterization of metabolite disorder in orange trees caused by citrus sudden death disease

Citrus sudden death (CSD) is a new disease of sweet orange and mandarin trees grafted on Rangpur lime and Citrus volkameriana rootstocks. It was first seen in Brazil in 1999, and has since been detected in more than four million trees. The CSD causal agent is unknown and the current hypothesis involves a virus similar to Citrus tristeza virus or a new virus named Citrus sudden death-associated virus. CSD symptoms include generalized foliar discoloration, defoliation and root death, and, in most cases, it can cause tree death. One of the unique characteristics of CSD disease is the presence of a yellow stain in the rootstock bark near the bud union. This region also undergoes profound anatomical changes. In this study, we analyse the metabolic disorder caused by CSD in the bark of sweet orange grafted on Rangpur lime by nuclear magnetic resonance (NMR) spectroscopy and imaging. The imaging results show the presence of a large amount of non-functional phloem in the rootstock bark of affected plants. The spectroscopic analysis shows a high content of triacylglyceride and sucrose, which may be related to phloem blockage close to the bud union. We also propose that, without knowing the causal CSD agent, the determination of oil content in rootstock bark by low-resolution NMR can be used as a complementary method for CSD diagnosis, screening about 300 samples per hour.

Vedegenskaper i härskande och behärskade granar vid Remingstorp : Wood properties in dominant and sub-dominant trees of Norway spruce at Remingstorp

Variation in wood properties for Picea abies trees and logs of different dimensions has been studied at two sites in southern Sweden of different site quality class. Trees have been classified as dominant or sub-dominant, according to their height. Log and board grades were classified and strength grade of boards, basic density and annual ring width measured. A similar study made on four northern sites was used as reference material.Sub-dominant trees were of superior quality in comparison to dominant trees, when classified by log and board grades or strength grading. Differences were accentuated for the second log where the sub-dominant trees had superior strength and low amount of boards with coarse branches. The results correspond well to those from the northern region, Jämtland. The classifica¬tion of boards as well as bending strength indicated superior properties on timber from northern sites even though the basic density was similar.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.