Performance of a species distribution model based on presence/absence for various population sizes in the amphidromous fish species Sicyopterus japonicus

2013 ◽  
Vol 61 (1) ◽  
pp. 90-96 ◽  
Author(s):  
Norio Onikura ◽  
Ryutei Inui ◽  
Shin Oikawa ◽  
Tomonori Kawamoto
Keyword(s):  
Fish Species ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Distribution Model ◽  
Model Based ◽  
Population Sizes

High-resolution species-distribution model based on systematic sampling and indirect observations

2016 ◽  
Vol 26 (2) ◽  
pp. 421-437 ◽  
Author(s):  
Oded Nezer ◽  
Shirli Bar-David ◽  
Tomer Gueta ◽  
Yohay Carmel
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Distribution Model ◽  
Systematic Sampling ◽  
Model Based

scholarly journals How barriers shape freshwater fish distributions: a species distribution model approach

2016 ◽  
Author(s):  
Mathias Kuemmerlen ◽  
Stefan Stoll ◽  
Peter Haase
Keyword(s):  
Freshwater Fish ◽  
Fish Species ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Freshwater Ecosystems ◽  
Distribution Model ◽  
Catchment Management ◽  
Stream Network ◽  
Species Specific ◽  
Fish Distributions

Aim: Barriers continue to be built globally despite their well-known negative effects on freshwater ecosystems. Fish habitats are disturbed by barriers and the connectivity in the stream network reduced. We implemented and assessed the use of barrier data, including their size and magnitude, in distribution predictions for 20 species of freshwater fish to understand the impacts on freshwater fish distributions. Location: Central Germany. Methods: Obstruction metrics were calculated from barrier data in three different spatial contexts relevant to fish migration and dispersal: upstream, downstream and along 10km of stream network. The metrics were included in a species distribution model and compared to a model without them, to reveal how barriers influence the distribution patterns of fish species. We assess impacts of barriers by estimating species’ specific range gains and losses due to barrier inclusion in the model. Results: Barriers were important for the predictions of many fish species with the metric upstream barriers being the most relevant barrier predictor across the fish community. With the inclusion of barriers, most species saw a reduction in their predicted range and habitat suitability decreased, particularly species with small ranges or considered as threatened. Main conclusions: Predictions from this SDM application point out how and where barriers influence fish distributions in the studied catchment. Our results indicate a reduction in suitable habitat due to barriers and suggest a higher extirpation risk. This species-specific and spatially-explicit information is highly valuable for target-oriented river restoration measures, biodiversity conservation efforts and catchment management in general.

scholarly journals How barriers shape freshwater fish distributions: a species distribution model approach

2016 ◽  
Author(s):  
Mathias Kuemmerlen ◽  
Stefan Stoll ◽  
Peter Haase
Keyword(s):  
Freshwater Fish ◽  
Fish Species ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Freshwater Ecosystems ◽  
Distribution Model ◽  
Catchment Management ◽  
Stream Network ◽  
Species Specific ◽  
Fish Distributions

Aim: Barriers continue to be built globally despite their well-known negative effects on freshwater ecosystems. Fish habitats are disturbed by barriers and the connectivity in the stream network reduced. We implemented and assessed the use of barrier data, including their size and magnitude, in distribution predictions for 20 species of freshwater fish to understand the impacts on freshwater fish distributions. Location: Central Germany. Methods: Obstruction metrics were calculated from barrier data in three different spatial contexts relevant to fish migration and dispersal: upstream, downstream and along 10km of stream network. The metrics were included in a species distribution model and compared to a model without them, to reveal how barriers influence the distribution patterns of fish species. We assess impacts of barriers by estimating species’ specific range gains and losses due to barrier inclusion in the model. Results: Barriers were important for the predictions of many fish species with the metric upstream barriers being the most relevant barrier predictor across the fish community. With the inclusion of barriers, most species saw a reduction in their predicted range and habitat suitability decreased, particularly species with small ranges or considered as threatened. Main conclusions: Predictions from this SDM application point out how and where barriers influence fish distributions in the studied catchment. Our results indicate a reduction in suitable habitat due to barriers and suggest a higher extirpation risk. This species-specific and spatially-explicit information is highly valuable for target-oriented river restoration measures, biodiversity conservation efforts and catchment management in general.

scholarly journals How barriers shape freshwater fish distributions: a species distribution model approach

2016 ◽  
Author(s):  
Mathias Kuemmerlen ◽  
Stefan Stoll ◽  
Peter Haase
Keyword(s):  
Habitat Fragmentation ◽  
Fish Species ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Freshwater Ecosystems ◽  
Distribution Model ◽  
Catchment Management ◽  
Distribution Models ◽  
Stream Network ◽  
Fish Distributions

Barriers, from dams to culverts, continue to be built globally despite their well-known negative effects on freshwater ecosystems. While large barriers strongly influence distribution through habitat fragmentation, the effects of smaller barriers on the distribution patterns of many fish species remains poorly studied. Obstruction metrics were calculated including different types and magnitudes of barriers considering upstream, downstream or barriers within a 10 km stream network distance. These were then included in species distribution models (SDMs) of 20 fish species and compared to predictions without barriers to understand their effects on fish distributions. Barriers were important for the predictions of many fish species with the metric upstream barriers being the most relevant barrier predictor across the fish community. With the inclusion of barriers, most species saw a reduction in their predicted range and habitat suitability decreased, suggesting habitat fragmentation and indicating a higher extirpation risk. Predictions from this SDM application point out how and where barriers influence fish distributions in the studied catchment. This species-specific and spatially-explicit information is highly valuable for target-oriented river restoration measures, biodiversity conservation efforts and catchment management in general.

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 Species distribution model reveals only highly fragmented suitable patches remaining for giant armadillo in the Brazilian Cerrado

2021 ◽  
Author(s):  
Katia Maria Paschoaletto Micchi de Barros Ferraz ◽  
Bruna Gomes de Oliveira ◽  
Nina Attias ◽  
Arnaud Leonard Jean Desbiez
Keyword(s):  
Species Distribution ◽  
Species Distribution Model ◽  
Distribution Model ◽  
Brazilian Cerrado

Confronting existing knowledge on ecological preferences of stream macroinvertebrates with independent monitoring data using a Bayesian multi-species distribution model

2020 ◽  
Author(s):  
Peter Vermeiren ◽  
Peter Reichert ◽  
Wolfram Graf ◽  
Patrick Leitner ◽  
Astrid Schmidt-Kloiber ◽  
...  
Keyword(s):  
Species Distribution ◽  
Species Distribution Model ◽  
Monitoring Data ◽  
Distribution Model ◽  
Ecological Preferences ◽  
Stream Macroinvertebrates

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
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