Large-scale data for multiple-view stereopsis

The seminal multiple-view stereo benchmark evaluations from Middlebury and by Strecha et al. have played a major role in propelling the development of multi-view stereopsis (MVS) methodology. The somewhat small size and variability of these data sets, however, limit their scope and the conclusions that can be derived from them. To facilitate further development within MVS, we here present a new and varied data set consisting of 80 scenes, seen from 49 or 64 accurate camera positions. This is accompanied by accurate structured light scans for reference and evaluation. In addition all images are taken under seven different lighting conditions. As a benchmark and to validate the use of our data set for obtaining reasonable and statistically significant findings about MVS, we have applied the three state-of-the-art MVS algorithms by Campbell et al., Furukawa et al., and Tola et al. to the data set. To do this we have extended the evaluation protocol from the Middlebury evaluation, necessitated by the more complex geometry of some of our scenes. The data set and accompanying evaluation framework are made freely available online. Based on this evaluation, we are able to observe several characteristics of state-of-the-art MVS, e.g. that there is a tradeoff between the quality of the reconstructed 3D points (accuracy) and how much of an object’s surface is captured (completeness). Also, several issues that we hypothesized would challenge MVS, such as specularities and changing lighting conditions did not pose serious problems. Our study finds that the two most pressing issues for MVS are lack of texture and meshing (forming 3D points into closed triangulated surfaces)

Testing the Water–Energy Theory on American Palms (Arecaceae) Using Geographically Weighted Regression

Water and energy have emerged as the best contemporary environmental correlates of broad-scale species richness patterns. A corollary hypothesis of water–energy dynamics theory is that the influence of water decreases and the influence of energy increases with absolute latitude. We report the first use of geographically weighted regression for testing this hypothesis on a continuous species richness gradient that is entirely located within the tropics and subtropics. The dataset was divided into northern and southern hemispheric portions to test whether predictor shifts are more pronounced in the less oceanic northern hemisphere. American palms (Arecaceae, n = 547 spp.), whose species richness and distributions are known to respond strongly to water and energy, were used as a model group. The ability of water and energy to explain palm species richness was quantified locally at different spatial scales and regressed on latitude. Clear latitudinal trends in agreement with water–energy dynamics theory were found, but the results did not differ qualitatively between hemispheres. Strong inherent spatial autocorrelation in local modeling results and collinearity of water and energy variables were identified as important methodological challenges. We overcame these problems by using simultaneous autoregressive models and variation partitioning. Our results show that the ability of water and energy to explain species richness changes not only across large climatic gradients spanning tropical to temperate or arctic zones but also within megathermal climates, at least for strictly tropical taxa such as palms. This finding suggests that the predictor shifts are related to gradual latitudinal changes in ambient energy (related to solar flux input) rather than to abrupt transitions at specific latitudes, such as the occurrence of frost

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Ethnobotanical knowledge is vastly under-documented in northwestern South America

A main objective of ethnobotany is to document traditional knowledge about plants before it disappears. However, little is known about the coverage of past ethnobotanical studies and thus about how well the existing literature covers the overall traditional knowledge of different human groups. To bridge this gap, we investigated ethnobotanical data-collecting efforts across four countries (Colombia, Ecuador, Peru, Bolivia), three ecoregions (Amazon, Andes, Chocó), and several human groups (including Amerindians, mestizos, and Afro-Americans). We used palms (Arecaceae) as our model group because of their usefulness and pervasiveness in the ethnobotanical literature. We carried out a large number of field interviews (n = 2201) to determine the coverage and quality of palm ethnobotanical data in the existing ethnobotanical literature (n = 255) published over the past 60 years. In our fieldwork in 68 communities, we collected 87,886 use reports and documented 2262 different palm uses and 140 useful palm species. We demonstrate that traditional knowledge on palm uses is vastly under-documented across ecoregions, countries, and human groups. We suggest that the use of standardized data-collecting protocols in wide-ranging ethnobotanical fieldwork is a promising approach for filling critical information gaps. Our work contributes to the Aichi Biodiversity Targets and emphasizes the need for signatory nations to the Convention on Biological Diversity to respond to these information gaps. Given our findings, we hope to stimulate the formulation of clear plans to systematically document ethnobotanical knowledge in northwestern South America and elsewhere before it vanishesThis study was funded by the European Union, 7th Framework Programme (contract no. 212631), the Russel E. Train Education for Nature Program of the WWF (to NPZ), the Anne S. Chatham fellowship of the Garden Club of America (to NPZ), and the Universidad Autónoma de Madrid travel grants programme (to RCL

Integrated Brain Atlas for Unbiased Mapping of Nervous System Effects Following Liraglutide Treatment

Light Sheet Fluorescence Microscopy (LSFM) of whole organs, in particular the brain, offers a plethora of biological data imaged in 3D. This technique is however often hindered by cumbersome non-Automated analysis methods. Here we describe an approach to fully automate the analysis by integrating with data from the Allen Institute of Brain Science (AIBS), to provide precise assessment of the distribution and action of peptide-based pharmaceuticals in the brain. To illustrate this approach, we examined the acute central nervous system effects of the glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide. Peripherally administered liraglutide accessed the hypothalamus and brainstem, and led to activation in several brain regions of which most were intersected