scholarly journals Rana temporaria on Monti della Laga (Central Italy): isolated population or wide distribution? First record in Abruzzo and Marche

2021 ◽  
Vol 16 (1) ◽  
pp. 45-51
Author(s):  
Francesco Di Toro ◽  
Gianmarco Minuti ◽  
Luca Coppari ◽  
Matteo De Albentiis ◽  
Paolo Laghi ◽  
...  
Keyword(s):  
Species Distribution Model ◽  
Rana Temporaria ◽  
Central Italy ◽  
First Record ◽  
Wide Distribution ◽  
Distribution Model ◽  
Isolated Populations ◽  
Actual Distribution ◽  
Glacial Relict ◽  
Mountain Chain

In Central Italy Rana temporaria is only known to occur as a glacial relict on the eastern side of Monti della Laga (Lazio). In this study we report the presence of the species in other areas of the mountain chain, with documented sightings in five distinct localities in Marche and Abruzzo. We use these new records, together with other occurrence data from the Apennine chain, to generate a species distribution model and perform an analysis of the geological preference of the species in Central Italy. Although the model indicates a wide area of Marche and Abruzzo as suitable for R. temporaria, the actual distribution of the species in northern and central Apennine appears strongly associated with sandstones. Therefore, we argue that the presence of this geological substrate on Monti della Laga, but not in surrounding karst uplands, could be among the factors explaining its isolation. Our study aims at paving the way for future surveys and measures to protect these isolated populations from the threat posed by climate change.

The First Record of Tesselated Snake, Natrix tesselata Laurenti, 1768 in the Central Chernozem Territory of Russia and Some Other Results of the Herpetological Research in the Upper Don

2011 ◽  
Vol 4 (2) ◽  
pp. 192-194
Author(s):  
Georgy A. Lada ◽  
V. Y. Nedosekin
Keyword(s):  
Rana Temporaria ◽  
First Record ◽  
Isolated Population ◽  
Common Frog ◽  
Northern Border ◽  
Frog Rana Temporaria ◽  
Bombina Bombina ◽  
Central Chernozem

A small isolated population of tesselated snake, Natrix tesselata was found in the Upper Don (Lipetsk Region, Russia). It is the first record of this species in the Central Chernozem Territory of Russia, which is separated from the northern border of the main range by the distance of about 200 km. An isolated population of common frog, Rana temporaria and phenetically peculiar population of fire-bellied toad, Bombina bombina are found here too. Faunistic aspect of new herpetological records is discussed.

scholarly journals A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 388
Author(s):  
Riccardo De Blasis ◽  
Giovanni Batista Masala ◽  
Filippo Petroni
Keyword(s):  
Markov Model ◽  
Electricity Market ◽  
Wind Farm ◽  
Central Italy ◽  
High Order ◽  
Distribution Model ◽  
Spot Price ◽  
Model Parameters ◽  
Price Series ◽  
Cross Correlations

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm.

scholarly journals A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks

2021 ◽  
Vol 13 (8) ◽  
pp. 1495
Author(s):  
Jehyeok Rew ◽  
Yongjang Cho ◽  
Eenjun Hwang
Keyword(s):  
Neural Networks ◽  
Species Distribution ◽  
Best Practice ◽  
Deep Neural Networks ◽  
Species Distribution Models ◽  
Species Distribution Model ◽  
Environmental Data ◽  
Distribution Model ◽  
Distribution Models ◽  
Robust Prediction

Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have been proposed to construct effective species distribution models, but with limited success due to spatial biases in presences and imbalanced presence-absences. We propose a novel species distribution model to address these problems based on bootstrap aggregating (bagging) ensembles of deep neural networks (DNNs). We first generate bootstraps considering presence-absence data on spatial balance to alleviate the bias problem. Then we construct DNNs using environmental data from presence and absence locations, and finally combine these into an ensemble model using three voting methods to improve prediction accuracy. Extensive experiments verified the proposed model’s effectiveness for species in South Korea using crowdsourced observations that have spatial biases. The proposed model achieved more accurate and robust prediction results than the current best practice models.

scholarly journals A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Billy Joel M. Almarinez ◽  
Mary Jane A. Fadri ◽  
Richard Lasina ◽  
Mary Angelique A. Tavera ◽  
Thaddeus M. Carvajal ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Biological Control Agent ◽  
The Philippines ◽  
Distribution Model ◽  
Field Surveys ◽  
Probability Of Occurrence ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

scholarly journals The impact of data quality filtering of opportunistic citizen science data on species distribution model performance

2021 ◽  
Vol 444 ◽  
pp. 109453
Author(s):  
Camille Van Eupen ◽  
Dirk Maes ◽  
Marc Herremans ◽  
Kristijn R.R. Swinnen ◽  
Ben Somers ◽  
...  
Keyword(s):  
Data Quality ◽  
Citizen Science ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Model Performance ◽  
Distribution Model ◽  
Science Data ◽  
Quality Filtering ◽  
The Impact

scholarly journals Characterization of Gnomoniopsis idaeicola, the Causal Agent of Canker and Wilting of Blackberry in Serbia

Plant Disease ◽  
2019 ◽  
Vol 103 (2) ◽  
pp. 249-258 ◽  
Author(s):  
Miloš Stevanović ◽  
Danijela Ristić ◽  
Svetlana Živković ◽  
Goran Aleksić ◽  
Ivana Stanković ◽  
...  
Keyword(s):  
Disease Incidence ◽  
Initial Step ◽  
First Record ◽  
Wide Distribution ◽  
Causal Agent ◽  
Control Measures ◽  
Molecular Features ◽  
Intraspecies Diversity ◽  
Specific Symptoms

Blackberry cane diseases with the symptoms of necrosis, canker, and wilting are caused by several fungi worldwide. Surveys conducted from 2013 to 2016 in Serbia revealed the occurrence of Gnomoniopsis idaeicola, the causal agent of cane canker and wilting, which was found to be distributed in almost half of the surveyed orchards, in three blackberry cultivars, and with disease incidence of up to 80%. Wide distribution and high disease incidence suggest that G. idaeicola has been present in Serbia for some time. Out of 427 samples, a total of 65 G. idaeicola isolates were obtained (isolation rate of 34.19%). Reference isolates, originating from different localities, were conventionally and molecularly identified and characterized. G. idaeicola was detected in single and mixed infections with fungi from genera Paraconiothyrium, Colletotrichum, Diaporthe, Botryosphaeria, Botrytis, Septoria, Neofusicoccum, and Discostroma, and no diagnostically specific symptoms could be related directly to the G. idaeicola infection. In orchards solely infected with G. idaeicola, blackberry plant mortality was up to 40%, and yield loses were estimated at 50%. G. idaeicola isolates included in this study demonstrated intraspecies diversity in morphological, biological, pathogenic, and molecular features, which indicates that population in Serbia may be of different origin. This is the first record of a massive outbreak of G. idaeicola infection, illustrating its capability of harmful influence on blackberry production. This study represents the initial step in studying G. idaeicola as a new blackberry pathogen in Serbia, aiming at developing efficient control measures.

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