Does selective logging affect litter deposition rates in central Brazilian Amazonia?

Abstract Selective logging is one of the main human activities that are drastically modifying tropical forests around the world. Reduced-impact logging emerged as a rational model of timber harvesting that reduces the impacts on the ecosystems and contributes to the conservation of natural resources. Nevertheless, this type of activity may still alter the forest structure, nutrient cycling, soil drainage, and other important ecosystem processes. Here, we aimed at testing the effects of selective logging on litter deposition in central Brazilian Amazonia. We estimated litter production during one dry and one rainy season in 11 sites logged between 2003 and 2017 and one unlogged site. Mean litter deposition was greater during the dry season. Although litter deposition rates varied between a few study sites, this variation was independent of the time after logging. The results suggest that the low logging intensity in the study site (16.8 m³/ha) had no intense impacts on litter deposition. Reduced-impact logging may be an alternative for the use of forest resources in Amazonian forests without compromising nutrient cycles

Connected operators for unsupervised image segmentation

Image segmentation forms the first stage in many image analysis procedures including image sequence re-timing and the emerging field of content based retrieval. By dividing the image into a set of disjoint connected regions, each of which is homogeneous with respect to some measure of the image content, the scene can be analysed and metadata extracted more efficiently, and in many cases more effectively, than on a pixel by pixel basis. Though a great number of segmentation techniques exist (and continue to be developed,) many of them fall short of the requirements of these applications. This thesis first defines these requirements and reviews established segmentation methods describing their qualities and shortfalls. Selecting the watershed transform and connected operators from those techniques reviewed a number of novel adaptations are introduced, developed and shown to produce pleasing results both in terms of a new evaluation metric and subjective appraisal. Finally, the use of the image segmentation is shown to improve established methods of image noise removal using the discrete wavelet transform

Traditional scientific data vs. uncoordinated citizen science effort: A review of the current status and comparison of data on avifauna in Southern Brazil

<div><p>Data generated by citizen science is particularly valuable in ecological research. If used discerningly with data from traditional scientific references, citizen science can directly contribute to biogeography knowledge and conservation policies by increasing the number of species records in large geographic areas. Considering the current level of knowledge on south Brazilian avifauna, the large volume of data produced by uncoordinated citizen science effort (CS), and the growing need for information on changes in abundance and species composition, we have compiled an updated, general list of bird species occurrence within the state of Paraná. We have listed extinct, invasive and recently-colonizing species as well as indicator species of the state’s vegetation types. We further assess the degree of knowledge of different regions within the state based on data from traditional scientific references, and the effect of including CS data in the same analysis. We have compiled data on 766 bird species, based on 70,346 individual records from traditional scientific references, and 79,468 from CS. Extinct and invasive species were identified by comparing their occurrence and abundance over a series of three time periods. Indicator species analysis pointed to the existence of three areas with bird communities typically found within the state: the Semideciduous Tropical Forest, the Tropical Rainforest and the junction of Grassland and Araucaria Moist Forest. We used rarefaction to measure sampling sufficiency, and found that rarefaction curves reached stabilization for all vegetation types except in Savanna. We observed differences in the level of knowledge of bird biodiversity among the microregions of the state, but including CS data, these differences were mitigated. The same effect was observed in other exploratory analyzes conducted here, emphasizing the fundamental importance of including CS data in macroecological studies. Production of easily accessible data and its unrestricted availability makes CS a very important tool, especially in highly diverse regions as the Neotropics, as it can offer a more accurate picture of bird composition in comparison to the exclusive use of traditional scientific references.</p></div

Comparisons between traditional scientific references data alone, and including CS data.

<p>Boxplots comparing: (A) number of records per microregion, (B) number of species per microregion, (C) number of sources of information per microregion, and (D) number of sites with records per microregion, both excluding and including CS data. For ease of representation, due to the large range of values, logarithmic scale was used. * statistically significant differences. Open circles represent extreme values found for microregions.</p

Indicator species of each vegetation type.

<p>Number of species, indicator species and exclusive species for each vegetation type individually and in different combinations of types, both excluding (BM) and including CS data (BM+CS). Vegetation types: EGL–Grassland; FES–Semideciduous Tropical Forest; FOD–Tropical Rainforest; FOM–Araucaria Moist Forest; SA–Savanna. Data presented in descending order of number of indicator species (BM+CS).</p

Comparisons between traditional scientific references data by themselves and including CS data.

<p>Boxplots comparing: (A) number of species per vegetation type, (B) number of indicator species per vegetation type, (C) number of extinct species per vegetation type and in the whole state of Paraná, and (D) number of native invasive species per vegetation type, both excluding and including CS data. * Statistically significant differences. Open circles represent extreme values found for some vegetation types. SA—Savanna, FES—Semideciduous Tropical Forest.</p

Sample-based rarefaction curves comparing bird species richness in Paraná.

<p>Specimen occurrences were compiled from the primary and secondary lists, using decades as sample units and starting at 1820, (A) excluding CS data, and (B) including CS data. EGL—Grassland, FES -Semideciduous Tropical Forest, FOD—Tropical Rainforest, FOM—Araucaria Moist Forest, SA—Savanna, Total—considering the whole state of Paraná.</p

Extinct bird species in Paraná.

<p>Number of extinct bird species (per time period and total) and percentage of the total number of extinct species relative to the total number of species in each vegetation type, both excluding (BM) and including CS data (BM+CS). Some species were extinct in more than one vegetation type, and a complete list of extinct species is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0188819#pone.0188819.s008" target="_blank">S8 Table</a>. Vegetation types: EGL–Grassland; FES–Semideciduous Tropical Forest; FOD–Tropical Rainforest; FOM–Araucaria Moist Forest; SA–Savanna. Data presented in descending order of total number of regionally extinct species.</p

Phytogeographic map of Paraná state and quadrat divisions used for analyses.

<p>Vegetation types of the state of Paraná depicting quadrats analyzed, in a different color. For the analyses, only records obtained in the state of Paraná were used. Vegetation types: EGL–Grassland; FES–Semideciduous Tropical Forest; FOD–Tropical Rainforest; FOM–Araucaria Moist Forest; SA–Savanna.</p