Evaluating the legacy of landscape history: extinction debt and species credit in bird and small mammal assemblages in the Brazilian Atlantic Forest

There is now an extensive literature on extinction debt following deforestation. However, the potential for species credit in landscapes that have experienced a change from decreasing to expanding forest cover has received little attention. Both delayed responses should depend on current landscape forest cover and on species life-history traits, such as longevity, as short-lived species are likely to respond faster than long-lived species. We evaluated the effects of historical and present-day local forest cover on two vertebrate groups with different longevities understorey birds and non-flying small mammals - in forest patches at three Atlantic Forest landscapes. Our work investigated how the probability of extinction debt and species credit varies (i) amongst landscapes with different proportions of forest cover and distinct trajectories of forest cover change, and (ii) between taxa with different life spans. Our results suggest that the existence of extinction debt and species credit, as well as the potential for their future payment and/or receipt, is not only related to forest cover trajectory but also to the amount of remaining forest cover at the landscape scale. Moreover, differences in bird and small mammal life spans seem to be insufficient to affect differently their probability of showing time-delayed responses to landscape change. Synthesis and applications. Our work highlights the need for considering not only the trajectory of deforestation/regeneration but also the amount of forest cover at landscape scale when investigating time-delayed responses to landscape change. As many landscapes are experiencing a change from decreasing to expanding forest cover, understanding the association of extinction and immigration processes, as well as their interactions with the landscape dynamic, is a key factor to plan conservation and restoration actions in human-altered landscapes.

Demographic processes in the montane Atlantic rainforest: Molecular and cytogenetic evidence from the endemic frog Proceratophrys boiei

Historical climatic refugia predict genetic diversity in lowland endemics of the Brazilian Atlantic rainforest. Yet, available data reveal distinct biological responses to the Last Glacial Maximum (LGM) conditions across species of different altitudinal ranges. We show that species occupying Brazil's montane forests were significantly less affected by LGM conditions relative to lowland specialists, but that pre-Pleistocene tectonics greatly influenced their geographic variation. Our conclusions are based on palaeoclimatic distribution models, molecular sequences of the cytochrome b, 16S, and RAG-1 genes, and karyotype data for the endemic frog Proceratophrys boiei. DNA and chromosomal data identify in P. boiei at least two broadly divergent phylogroups, which have not been distinguished morphologically. Cytogenetic results also indicate an area of hybridization in southern Sao Paulo. The location of the phylogeographic break broadly matches the location of a NW-SE fault, which underwent reactivation in the Neogene and led to remarkable landscape changes in southeastern Brazil. Our results point to different mechanisms underpinning diversity patterns in lowland versus montane tropical taxa, and help us to understand the processes responsible for the large number of narrow endemics currently observed in montane areas of the southern Atlantic forest hotspot. (C) 2011 Elsevier Inc. All rights reserved.

Environmental suitability of a highly fragmented and heterogeneous landscape for forest bird species in south-eastern Brazil

Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

Contribution and perspectives of quantitative genetics to plant breeding in Brazil

The purpose of this article is to show how quantitative genetics has contributed to the huge genetic progress obtained in plant breeding in Brazil in the last forty years. The information obtained through quantitative genetics has given Brazilian breeders the possibility of responding to innumerable questions in their work in a much more informative way, such as the use or not of hybrid cultivars, which segregating population to use, which breeding method to employ, alternatives for improving the efficiency of selection programs, and how to handle the data of progeny and/or cultivars evaluations to identify the most stable ones and thus improve recommendations.

A model of road effect using line integrals and a test of the performance of two new road indices using the distribution of small mammals in an Atlantic Forest landscape

Effects of roads on wildlife and its habitat have been measured using metrics, such as the nearest road distance, road density, and effective mesh size. In this work we introduce two new indices: (1) Integral Road Effect (IRE), which measured the sum effects of points in a road at a fixed point in the forest; and (2) Average Value of the Infinitesimal Road Effect (AVIRE), which measured the average of the effects of roads at this point. IRE is formally defined as the line integral of a special function (the infinitesimal road effect) along the curves that model the roads, whereas AVIRE is the quotient of IRE by the length of the roads. Combining tools of ArcGIS software with a numerical algorithm, we calculated these and other road and habitat cover indices in a sample of points in a human-modified landscape in the Brazilian Atlantic Forest, where data on the abundance of two groups of small mammals (forest specialists and habitat generalists) were collected in the field. We then compared through the Akaike Information Criterion (AIC) a set of candidate regression models to explain the variation in small mammal abundance, including models with our two new road indices (AVIRE and IRE) or models with other road effect indices (nearest road distance, mesh size, and road density), and reference models (containing only habitat indices, or only the intercept without the effect of any variable). Compared to other road effect indices, AVIRE showed the best performance to explain abundance of forest specialist species, whereas the nearest road distance obtained the best performance to generalist species. AVIRE and habitat together were included in the best model for both small mammal groups, that is, higher abundance of specialist and generalist small mammals occurred where there is lower average road effect (less AVIRE) and more habitat. Moreover, AVIRE was not significantly correlated with habitat cover of specialists and generalists differing from the other road effect indices, except mesh size, which allows for separating the effect of roads from the effect of habitat on small mammal communities. We suggest that the proposed indices and GIS procedures could also be useful to describe other spatial ecological phenomena, such as edge effect in habitat fragments. (C) 2012 Elsevier B.V. All rights reserved.

Indices representing landscape as a support for pedological survey in GIS environment

Mapping of soil has been highlighted in the scientific community, because as alertness about the environment increases, it is necessary to understand more and more about the distribution of the soil in the landscape, as well as its potential and its limitations for the use. In that way the main aim of this study was to apply indices representing landscape with the use of geoprocessing to give support in the delimitation of different compartments of landscape. Primary indices used were altitude above channel network (AACN) and secondary channel network base level (CNBL), multiresolution index of valley bottom flatness (MRVBF) and Wetness index (ITW), having as object of study the Canguiri Experimental Farm, located in Pinhais, Curitiba's Metropolitan region. To correlate the chemical attributes and granulometric ones in sampling groups, totalizing 17 points (Sugamosto, 2002), a matrix of a simple linear correlation (Pearson) with the indices of the landscape were generated in the Software Statistica. The conclusion is that the indices representing the landscape used in the analysis of groupings were efficient as support to map soil at the level of suborder of Brazilian Soil Classification System.

Is missing maxillary lateral incisor in complete cleft lip and palate a product of genetics or local environment?

Objective: To test the null hypothesis: Subjects with isolated complete unilateral cleft lip and palate (UCLP) show no differences in overall frequency of tooth agenesis (hypodontia), comparing a subsample with cleft-side maxillary lateral incisor (MxI2) agenesis to a subsample without cleftside MxI2 agenesis. Findings could clarify the origins of cleft-side MxI2 agenesis. Materials and Methods: Tooth agenesis was identified from dental radiographs of 141 subjects with UCLP. The UCLP cohort was segregated into four categories according to the status and location of MxI2 in the region of the unilateral cleft: group M: subjects with one tooth, located on the mesial side of the alveolar cleft; group D: subjects with one tooth, located on the distal side of the alveolar cleft; group MD: subjects with two teeth present, one mesial and one distal to the cleft; and group ABS: subjects with lateral incisor absent (agenesis) in the cleft area. Results: The null hypothesis was rejected. Among UCLP subjects, there was a twofold increase (P < .0008) in overall frequency of tooth agenesis outside the cleft region in a subsample with cleftside MxI2 agenesis (ABS), compared to a subsample presenting with no agenesis of the cleft-side MxI2 (M+D+MD). Conclusions: Cleft-side MxI2 agenesis in CLP subjects appears to be largely a genetically controlled anomaly associated with cleft development, rather than a collateral environmental consequence of the adjacent cleft defect, since increased hypodontia involving multiple missing teeth observed remote from a cleft clearly has a significant genetic basis. (Angle Orthod. 2012;82:959-963.)

The importance of landscape structure for seed dispersal in rain forest fragments

Questions What are the main features of the seed rain in a fragmented Atlantic forest landscape? Can seed rain species attributes (life form, dispersal mode, successional status) relate to the spatial arrangement (size and number of fragments, edge density and presence of corridor) of forest fragments in the landscape? How does the rain forest landscape structure affect the seed rain? Location Atlantic rainforest, Sao Paulo State, Southeastern Brazil. Methods Seed rain samples were collected monthly throughout 1yr, counted, identified and classified according to species dispersal mode, successional status and life form. Seed rain composition was compared with woody species near the seed traps. Relationships between seed rain composition and landscape spatial arrangement (fragment area, presence of corridor, number of fragments in the surroundings, proximity of fragments, and edge density) were tested using canonical correspondence analysis (CCA). Results We collected 20142 seeds belonging to 115 taxa, most of them early successional and anemochorous trees. In general, the seed rain had a species composition distinct from that of the nearby forest tree community. Small isolated fragments contained more seeds, mainly of anemochorous, epiphytic and early-successional species; large fragments showed higher association with zoochorous and late-successional species compared to small fragments. The CCA significantly distinguished the species dispersal mode according to fragment size and isolation, anemochorous species being associated to small and isolated fragments, and zoochorous species to larger areas and fragment aggregation. Nevertheless, a gradient driven by proximity (PROX) and edge density (ED) segregated lianas (in the positive extremity), early successional and epiphyte species (in the negative end); large fragments were positively associated to PROX and ED. Conclusions The results highlight the importance of the size and spatial arrangement of forest patches to promote habitat connectivity and improve the flux of animal-dispersed seeds. Landscape structure controls seed fluxes and affects plant dispersal capacity, potentially influencing the composition and structure of forest fragments. The seed rain composition may be used to assess the effects of landscape spatial structure on plant assemblages, and provide relevant information for biodiversity conservation.

Landscape and soil regionalization in southern Brazilian Amazon and contiguous areas: methodology and relevance for ecological studies

Soils of a large tropical area with differentiated landscapes cannot be treated uniformly for ecological applications. We intend to develop a framework based on physiography that can be used in regional applications. The study region occupies more than 1.1 million km² and is located at the junction of the savanna region of Central Brazil and the Amazon forest. It includes a portion of the high sedimentary Central Brazil plateau and large areas of mostly peneplained crystalline shield on the border of the wide inner-Amazon low sedimentary plain. A first broad subdivision was made into landscape regions followed by a more detailed subdivision into soil regions. Mapping information was extracted from soil survey maps at scales of 1:250000-1:500000. Soil units were integrated within a homogenized legend using a set of selected attributes such as taxonomic term, the texture of the B horizon and the associated vegetation. For each region, a detailed inventory of the soil units with their area distribution was elaborated. Ten landscape regions and twenty-four soil regions were recognized and delineated. Soil cover of a region is normally characterized by a cluster composed of many soil units. Soil diversity is comparable in the landscape and the soil regions. Composition of the soil cover is quantitatively expressed in terms of area extension of the soil units. Such geographic divisions characterized by grouping soil units and their spatial estimates must be used for regional ecological applications.

Mercury-induced autoimmunity : Genetics and immunoregulation

The existence of immune self-tolerance allows the immune system to mount responses against infectious agents, but not against self-molecular constitutes. Although self-tolerance is a robust phenomenon, in some individuals as well as in experimental models, the self-tolerance breaks down and as a result, a self-destructive autoimmune disease emerges. The underlying mechanisms for the development of autoimmune diseases are not known, but genetic, environmental and immunological factors are suggested to be involved. In this thesis, we used murine mercury-induced autoimmunity to test this suggestion. In susceptible mice mercuric chloride induces a systemic autoimmune disease characterized by increased serum levels of IgG1 and IgE, production of anti-nucleolar autoantibodies (ANolA) and formation of renal IgG deposits. In contrast, in resistant DBA/2 (H-2d) mice, none of these characteristics develop after exposure to mercury. By crossing and backcrossing mercury-resistant DBA/2 mice to mercury susceptible strains, we found that the resistance was inherited as a dominant trait in F1 hybrids and that one gene or a cluster of genes located in the H-2 loci determined the resistance to ANolA production, whereas resistance to the other characteristics was found to be controlled by two or three non-H-2 genes. We further put forward the “cryptic peptide hypothesis” to investigate whether mercury and another xenobiotic metal use similar pathway(s) to induce the H-2 linked production of ANolA. We found that while mercury stimulated ANolA synthesis in all H-2 susceptible (H-2s, H-2q and H-2f) mouse strains, silver induced only ANolA responses in H-2s and H-2q mice, but not in H-2f mice. Further studies showed that the resistance to silver-induced ANolA production in H-2f mice was inherited as a dominant trait. We next tested the proposition that mercury induces more adverse immunological effects in mouse strains, which are genetically prone to develop autoimmune diseases, using tight-skin 1 mice, an animal model for human Scleroderma. It was found that in this strain, mercury induced a strong immune activation with autoimmune characteristics, but did not accelerate the development of dermal fibrosis, a characteristic in Tsk/1 mice. Finally we addressed the Th1/Th2 cross-regulation paradigm by examining if a Th1-type of response could interact with a Th2-type of response if simultaneous induced in susceptible mice. Our findings demonstrated that mercury-induced autoimmunity (Th2-type) and collagen-induced arthritis (CIA) (Th1-type) can interact in a synergistic, antagonistic or additive fashion, depending on at which stage of CIA mercury is administered.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.