Potential distribution of Croton guatemalensis: a model with reproductive biology data

Background: The inclusion of information on the phenology of any given species can significantly improve the resulting of potential distribution models. Scientific literature does not provide up-to-date information on the abiotic and biotic factors that determine the distribution of Croton guatemalensis, a species native to communities in south Mexico. For the first time, the potential distribution of C. guatemalensis was determined using a model which includes reproductive biology data. Questions: Which bioclimatic and climatic variables most contribute to the distribution of C. guatemalensis? Does reproductive biology data contribute significantly to the prediction of the species distribution? Studied species/Mathematical model: Croton guatemalensis/ Maximum Entropy Modeling Study area and dates: Chiapas, Mexico, January - December 2020. Methods: The MaxEnt 4.4.4 algorithm was used, incorporating 16 variables, including bioclimatic, climatic and elevation. In addition, a habitat suitability layer was built. Results: The model presented a precision of AUC = 0.964 ± 0.004. Eight variables contributed to explain 86.5 % of the potential distribution of the species. According to their contribution to the model, the most important were the seasonality of precipitation, habitat suitability, elevation and April solar radiation. The species was found in the physiographic regions Central America South Mountain Range Subprovince, Central Depression of Chiapas Discontinuity, and Altos de Chiapas Subprovince. Conclusions: The inclusion reproductive biology data of C. guatemalensis contributed to improve the model. This information allows the development of more effective management and conservation plans by identifying the precise regions in which the species is found.

The Range Contraction and Future Conservation of Green Peafowl (Pavo muticus) in China

The Green Peafowl (Pavo muticus) is vulnerable to anthropogenic pressures and has undergone an extensive decline through much of its range in Southeast Asia. However, little is known about the changing distribution of Green Peafowl in China through historical periods. We described a 5000–6000 years distribution change of Green Peafowl in China by using historical archives. We examined the present distributions of Green Peafowl by using camera traps and transect surveys and predicted the suitable habitat to support future conservation planning for this species. Although Green Peafowl was once widely distributed across China, the species experienced a southward range retreat over the past 5000–6000 years and is now restricted to a small part of Yunnan. The results of prediction from maximum entropy modeling (MaxEnt) showed that the size of suitable habitat of Green Peafowl in Yunnan was 17,132 km2. The suitable habitat concentrated in nine prefectures of Yunnan and Pu’er, Chuxiong, and Yuxi accounted for 48.64%, 27.39% and 15.83%, respectively. These results suggest that central Yunnan can cover most of the current larger and more contiguous populations of Green Peafowl in China and should be protected. Moreover, some areas in southern Yunnan, such as Xishuangbanna, can be a candidate for reestablishing populations, given that the species disappeared in this region less than 20 years ago and has a large remaining habitat.

Mining divergent and conserved signals in 5′ splicing site sequences

Despite the fact that the main steps of the splicing process are similar across eukaryotes, differences in splicing factors, gene architecture and sequence divergences in splicing signals suggest clade-specific features of splicing and its regulation. In this work we study conserved and divergent signatures embedded in the sequence composition of eukaryotic 5′ splicing sites. We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequences of 14 different eukaryote organisms. Our approach allowed us to accommodate and extend, within a unified framework, many of the regularities observed in previous works like the relationship between the frequency of occurrence of natural sequences and the corresponding site's strength, or the negative epistatic effects between exonic and intronic consensus sites. In addition, performing a systematic and comparative analysis of 5′ss we showed that lineage information could be traced not only from single-site frequencies but also from joint di-nucleotide probabilities of donor sequences. Noticeably, we could also identify specific two-site coupling patterns for plants and for animals and argue that these differences, in association with taxon-specific features involving U6 snRNP, could be the basis for differences in splicing regulation previously reported between these groups.

Spatiotemporal analysis of bubonic plague in Pernambuco, northeast of Brazil: Case study in the municipality of Exu

Along with other countries in America, plague reached Brazil through the sea routes during the third pandemic. A brief ports phase was followed by an urban phase that took place in smaller inland cities and finally, it attained the rural area and established several foci where the ecological conditions were suitable for its continued existence. However, the geographic dispersion of plague in Brazil is still poorly studied. To better understand the disease dynamics, we accessed satellite-based data to trace the spatial occurrence and distribution of human plague cases in Pernambuco, Northeastern Brazil and using the municipality of Exu as study case area. Along with the satellite data, a historical survey using the Plague Control Program files was applied to characterize the spatial and temporal dispersion of cases in the period of 1945–1976. Kernel density estimation, spatial and temporal clusters with statistical significance and maximum entropy modeling were used for spatial data analysis, by means of the spatial analysis software packages. The use of geostatistical tools allowed evidencing the shift of the infection from the urban to the wild-sylvatic areas and the reemergence of cases after a period of quiescence, independent of the reintroduction from other plague areas.

Environmental Conditions, and Phenolic Compounds Potential in the Leaves of Vitis Tiliifolia

The wild vine Vitis tiliifolia is found in Mexico, Central América, and the Caribbean region. In the Veracruz State, in Mexico, grows in several municipalities and is used for nutritional and therapeutic purposes. The geographical distribution and environment where this Vitis grow has not been recorded. The leaves of V. tiliifolia are rich in phenolic compounds but potential areas with vines of high phenolic compounds are unknown. An agroecological zoning model to identify potential areas for the cultivation and development of this species was performed. Potential areas having wild vines of high phenolic compounds in the leaves were also determined. The model included 95 vine georeferences, obtained from four municipalities of central Veracruz. These were analyzed with maximum entropy modeling, mapped with ArcMap software, and correlated with the phenolic compounds found in leaves collected in the georeferenced areas. A zoning map was produced, with a potential area of ​​2763.72 km2, which included the states of San Luis Potosi, Hidalgo, Veracruz, Puebla, Oaxaca, and Chiapas. Agroclimatic variables of seasonality of temperature, precipitation, and organic matter in the soil were the most important for the development of this species. In the state of Veracruz, vines with the potential of high phenolic content were found in 29 municipalities with characteristics suitable for its cultivation. The highest phenolic content potential was found at altitudes between 1000 and 2000 meters in the municipalities of Huatusco and Cosautlán in the State of Veracruz.

Predicting synchronous firing of large neural populations from sequential recordings

A major goal in neuroscience is to understand how populations of neurons code for stimuli or actions. While the number of neurons that can be recorded simultaneously is increasing at a fast pace, in most cases these recordings cannot access a complete population: some neurons that carry relevant information remain unrecorded. In particular, it is hard to simultaneously record all the neurons of the same type in a given area. Recent progress have made possible to profile each recorded neuron in a given area thanks to genetic and physiological tools, and to pool together recordings from neurons of the same type across different experimental sessions. However, it is unclear how to infer the activity of a full population of neurons of the same type from these sequential recordings. Neural networks exhibit collective behaviour, e.g. noise correlations and synchronous activity, that are not directly captured by a conditionally-independent model that would just put together the spike trains from sequential recordings. Here we show that we can infer the activity of a full population of retina ganglion cells from sequential recordings, using a novel method based on copula distributions and maximum entropy modeling. From just the spiking response of each ganglion cell to a repeated stimulus, and a few pairwise recordings, we could predict the noise correlations using copulas, and then the full activity of a large population of ganglion cells of the same type using maximum entropy modeling. Remarkably, we could generalize to predict the population responses to different stimuli with similar light conditions and even to different experiments. We could therefore use our method to construct a very large population merging cells’ responses from different experiments. We predicted that synchronous activity in ganglion cell populations saturates only for patches larger than 1.5mm in radius, beyond what is today experimentally accessible.

New records and potential geographic distribution of Elongated Caecilian, Ichthyophis elongatus Taylor, 1965 (Amphibia, Gymnophiona, Ichthyophiidae), endemic to West Sumatra, Indonesia

We present new records of Ichthyophis elongatus Taylor, 1965 in West Sumatra. These records extend the known distribution of the species which was previously only known from the type locality in Padang, West Sumatra. We assess the morphology and habitats of this species and estimate its distribution. Predicted distribution based on maximum entropy modeling suggests a highly suitable habitat for the species throughout the Barisan Mountains at 500–1000 m above sea level. Our models suggest swamps, paddy fields, and secondary forests that are 100–150 m from rivers as the highest possible habitats for the species. Further surveys in two predicted areas based on the models discovered new populations of the species.