Bird Species Distribution in the Galapagos and Other Archipelagoes: Competition or Chance?

Ecology ◽  
1982 ◽  
Vol 63 (4) ◽  
pp. 881-887 ◽  
Author(s):  
Rauno V. Alatalo
Keyword(s):  
Species Distribution ◽  
Bird Species

scholarly journals Roadkill records of reptiles and birds in Cerrado and Pantanal landscapes

Check List ◽  
2018 ◽  
Vol 14 (5) ◽  
pp. 845-876 ◽  
Author(s):  
Wagner Fischer ◽  
Raquel Faria de Godoi ◽  
Antonio Conceição Paranhos Filho
Keyword(s):  
Species Distribution ◽  
Road Safety ◽  
New Records ◽  
Bird Species ◽  
Vehicle Collisions ◽  
Reptile Species

We monitored reptile and bird roadkills in Cerrado–Pantanal landscapes along the Campo Grande to Corumbá highway BR-262. We describe species distribution in different landscape zones, including the first geographic record for Hydrodynastes bicinctus Herrmann, 1804 in the Pantanal basin. The roadkill occurrence of Spizaetus melanoleucus (Vieillot, 1816) is an outstanding record. We recorded 930 individuals belonging to 29 reptile and 47 bird species; 20 of these species are new roadkill records in Brazil. The 8 new records of reptile species include Eunectes notaeus Cope, 1862, Bothrops mattogrossensis Amaral,1925, Dracaena paraguayensis Amaral,1950 and H. bicinctus; and 12 new records of bird species include S. melanoleucus, Heterospizias meridionalis Latham, 1790, Urubitinga urubitinga (Gmelin, 1788), Pulsatrix perspicillata (Latham, 1790), Aramus guarauna (Linnaeus, 1766), and Jabiru mycteria (Lichtenstein, 1819). Richness of road-killed species on the BR-262 highway seemed to be high, reinforcing concerns about wildlife-vehicle collisions where these accidents occur, as they lead to long term and chronic impacts on wildlife and road safety in the Pantanal region. 

scholarly journals Model-Assisted Bird Monitoring Based on Remotely Sensed Ecosystem Functioning and Atlas Data

2020 ◽  
Vol 12 (16) ◽  
pp. 2549 ◽  
Author(s):  
Adrián Regos ◽  
Pablo Gómez-Rodríguez ◽  
Salvador Arenas-Castro ◽  
Luis Tapia ◽  
María Vidal ◽  
...  
Keyword(s):  
Life History ◽  
Energy Balance ◽  
Species Distribution ◽  
Ecosystem Functioning ◽  
Life History Traits ◽  
Vegetation Index ◽  
Bird Species ◽  
Remotely Sensed ◽  
Distribution Models ◽  
Atlas Data

Urgent action needs to be taken to halt global biodiversity crisis. To be effective in the implementation of such action, managers and policy-makers need updated information on the status and trends of biodiversity. Here, we test the ability of remotely sensed ecosystem functioning attributes (EFAs) to predict the distribution of 73 bird species with different life-history traits. We run ensemble species distribution models (SDMs) trained with bird atlas data and 12 EFAs describing different dimensions of carbon cycle and surface energy balance. Our ensemble SDMs—exclusively based on EFAs—hold a high predictive capacity across 71 target species (up to 0.94 and 0.79 of Area Under the ROC curve and true skill statistic (TSS)). Our results showed the life-history traits did not significantly affect SDM performance. Overall, minimum Enhanced Vegetation Index (EVI) and maximum Albedo values (descriptors of primary productivity and energy balance) were the most important predictors across our bird community. Our approach leverages the existing atlas data and provides an alternative method to monitor inter-annual bird habitat dynamics from space in the absence of long-term biodiversity monitoring schemes. This study illustrates the great potential that satellite remote sensing can contribute to the Aichi Biodiversity Targets and to the Essential Biodiversity Variables framework (EBV class “Species distribution”).

scholarly journals Bird species distribution and conservation in Serra do Cipó, Minas Gerais, Brazil

2001 ◽  
Vol 11 (03) ◽  
Author(s):  
TADEU A. MELO-JÚNIOR ◽  
MARCELO F. DE VASCONCELOS ◽  
GERALDO W. FERNANDES ◽  
MIGUEL Â MARINI
Keyword(s):  
Species Distribution ◽  
Bird Species ◽  
Minas Gerais ◽  
Serra Do Cipó

scholarly journals Trogon rufus Gmelin, 1788, Baryphthengus ruficapillus (Vieillot, 1818), Notharchus swainsoni (Gray, 1846), Synallaxis ruficapilla Vieillot, 1819, Tyrannopsis sulphurea (Spix, 1825) and Procnias nudicollis (Vieillot, 1817) (Aves): documented records in the state of Mato Grosso do Sul, Brazil

Check List ◽  
2012 ◽  
Vol 8 (6) ◽  
pp. 1325
Author(s):  
José Carlos Morante Filho ◽  
Mauricio Neves Godoi
Keyword(s):  
Species Distribution ◽  
Bird Species ◽  
The State ◽  
Distribution Range ◽  
Ecological Studies ◽  
Mato Grosso ◽  
Conservation Plans ◽  
First Time ◽  
Mato Grosso Do Sul

A better understanding of patterns of species distribution is critical to carrying out the ecological studies needed to develop more appropriate conservation plans. Here we present records for six bird species in the state of Mato Grosso do Sul, Brazil. Five of these species (Trogon rufus, Baryphthengus ruficapillus, Notharchus swainsoni, Synallaxis ruficapilla and Procnias nudicollis) are rare and their distribution range is still poorly understood; one species (Tyrannopsis sulphurea) was recorded for the first time in the state.

scholarly journals Deep Multi-species Embedding

2017 ◽  
Author(s):  
Di Chen ◽  
Yexiang Xue ◽  
Daniel Fink ◽  
Shuo Chen ◽  
Carla P. Gomes
Keyword(s):  
Neural Network ◽  
Species Distribution ◽  
Species Interactions ◽  
Deep Neural Network ◽  
Species Distribution Models ◽  
Habitat Preferences ◽  
Bird Species ◽  
Single Species ◽  
Additional Contribution ◽  
Distribution Models

Understanding how species are distributed across landscapes over time is a fundamental question in biodiversity research. Unfortunately, most species distribution models only target a single species at a time, despite strong ecological evidence that species are not independently distributed. We propose Deep Multi-Species Embedding (DMSE), which jointly embeds vectors corresponding to multiple species as well as vectors representing environmental covariates into a common high-dimensional feature space via a deep neural network. Applied to bird observational data from the citizen science project eBird, we demonstrate how the DMSE model discovers inter-species relationships to outperform single-species distribution models (random forests and SVMs) as well as competing multi-label models. Additionally, we demonstrate the benefit of using a deep neural network to extract features within the embedding and show how they improve the predictive performance of species distribution modelling. An important domain contribution of the DMSE model is the ability to discover and describe species interactions while simultaneously learning the shared habitat preferences among species. As an additional contribution, we provide a graphical embedding of hundreds of bird species in the Northeast US.

Sign in / Sign up

Export Citation Format

Share Document