scholarly journals Using a Species Distribution Approach to Model Historic Camas (Camassia quamash) in Southern Idaho and Implications for Foraging in the Late Archaic

2020 ◽  
Author(s):  
Royce Johnson
Keyword(s):  
Pacific Northwest ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Diet Breadth ◽  
Habitat Characteristics ◽  
Distribution Model ◽  
Late Archaic ◽  
Human Diet ◽  
The Pacific ◽  
Suitable Habitats

Camas (Camassia quamash) is well documented as a traditional native food source throughout the Northwestern United States and Canada. A better understanding of the historic distribution of camas in Idaho would help to distinguish root foraging in this region from the Pacific Northwest. Modern grazing, development, climate change, and other factors have decimated native camas in this region. This study uses a species distribution model (MaxEnt) to provide a well-informed geospatial projection of the historic distribution and habitat characteristics of camas in Southern Idaho. Understanding the most significant landscape and climate characteristics for camas allows us to estimate suitable habitats, and therefore the potential influence of camas on human diet breadth and mobility in the Late Archaic.

Species Distribution Models (SDM) – A Strategic Tool for Predicting Suitable Habitats for Conserving the Target Species

2017 ◽  
pp. 427-440
Author(s):  
Balaguru Balakrishnan ◽  
Nagamurugan Nandakumar ◽  
Soosairaj Sebastin ◽  
Khaleel Ahamed Abdul Kareem
Keyword(s):  
Species Distribution ◽  
Spatial Data ◽  
Environmental Variables ◽  
Species Distribution Models ◽  
Species Distribution Model ◽  
Distribution Model ◽  
Suitable Habitat ◽  
Target Species ◽  
Distribution Models ◽  
Suitable Habitats

Conservation of the species in their native landscapes required understanding patterns of spatial distribution of species and their ecological connectivity through Species Distribution Models (SDM) by generation and integration of spatial data from different sources using Geographical Information System (GIS) tools. SDM is an ecological/spatial model which combines datasets and maps of occurrence of target species and their geographical and environmental variables by linking various algorithms together, that has been applied to either identify or predict the regions fulfilling the set conditions. This article is focused on comprehensive review of spatial data requirements, statistical algorithms and softwares used to generate the SDMs. This chapter also includes a case study predicting the suitable habitat distribution of Gnetum ula, an endemic and vulnerable plant species using maximum entropy (MaxEnt) species distribution model for species occurrences with inputs from environmental variables such as bioclimate and elevation.

scholarly journals Defining Conservation Requirements for the Suweon Treefrog (Dryophytes suweonensis) Using Species Distribution Models

Diversity ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 69
Author(s):  
Il-Kook Park ◽  
Daesik Park ◽  
Amaël Borzée
Keyword(s):  
Habitat Loss ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Rice Paddy ◽  
Habitat Characteristics ◽  
Distribution Model ◽  
Suitable Habitat ◽  
Rice Paddies ◽  
Agricultural Wetlands ◽  
North East

Numerous amphibian species are declining because of habitat loss and fragmentation due to urbanization of landscapes and the construction of roads. This is a mounting threat to species restricted to habitats close to urban areas, such as agricultural wetlands in North East Asia. The Suweon treefrog (Dryophytes suweonensis) falls into the list of species threatened with habitat loss and most populations are under threat of extirpation. Over the last decades, sub-populations have become increasingly disconnected and specifically the density of paved roads has increased around the only site connecting northern and southern Seoul populations. We surveyed this locality in Hojobeol, Siheung, Republic of Korea in 2012, 2015 and 2019 to first confirm the decline in the number of sites where D. suweonensis was present. The second objective was to analyze the habitat characteristics and determine the remaining suitable habitat for D. suweonensis through a species distribution model following the maximum entropy method. Our results show that rice paddy cover and distance from the paved road are the most important factor defining suitable habitat for D. suweonensis. At this locality, uninterrupted rice paddies are a suitable habitat for the species when reaching at least 0.19 km2, with an average distance of 138 ± 93 m2 from the roads. We link the decrease in the number of sites where D. suweonensis is present with the decrease in rice paddy cover, generally replaced by localized infrastructures, greenhouses and habitat fragmentation. Rice paddies should remain connected over a large area for the protection of the remaining populations. In addition, habitat requirements should be integrated in the requisites to designate protected areas.

scholarly journals Undetected but widespread: the cryptic invasion of non-native cattail (Typha spp.) in a Pacific Northwest estuary

2021 ◽  
Author(s):  
Daniel James Stewart ◽  
W. Gregory Hood ◽  
Tara G. Martin
Keyword(s):  
Cultural Values ◽  
Pacific Northwest ◽  
Species Distribution ◽  
Species Distribution Model ◽  
River Estuary ◽  
Typha Latifolia ◽  
Tidal Marshes ◽  
Distribution Model ◽  
Suitable Habitat ◽  
Hybrid Cattail

Abstract Early detection of invasive species is an important predictor of management success. Non-native narrow-leaved cattail (Typha angustifolia) has been detected in the Fraser River Estuary (FRE) in recent decades, but questions around their degree of establishment, and the potential emergence of hybrid cattail (Typha x glauca), remain unanswered. This study models the current and potential future distribution of non-native cattails in the FRE using a unique combination of spectral imagery analysis and species distribution modelling. Contrary to our expectation, we find that non-native cattails are already widespread, currently occupying approximately 4% of FRE tidal marshes. Though never formally recorded in the FRE, hybrid cattail is the more abundant of the two taxa, suggesting that heterosis may be facilitating this invasion. In our species distribution model, we distinguish between site suitability (ability to establish and persist) and site susceptibility (risk of being colonized when suitable). Our model predicts that 28% of the estuary has > 50% probability of suitability, and 21% has > 50% probability of susceptibility to non-native Typha, indicating the scale of this invasion may increase over time. Restoration projects had proportionally more cattail, susceptible habitat, and suitable habitat than the overall estuary, casting doubt on their effectiveness at mitigating wetland destruction. Due to their resemblance to native Typha latifolia, these cattails qualify as cryptic invaders, which explains how they were able to establish and remain undetected for decades. Regional eradication is unlikely given the extent of invasion, therefore management should prioritize areas of high conservation and cultural values.

scholarly journals Climate change impacts on migration of Pinus koraiensis during the Quaternary using species distribution models

Plant Ecology ◽  
2021 ◽  
Author(s):  
Takuto Shitara ◽  
Shunsuke Fukui ◽  
Tetsuya Matsui ◽  
Arata Momohara ◽  
Ikutaro Tsuyama ◽  
...  
Keyword(s):  
Species Distribution ◽  
Species Distribution Model ◽  
Eastern China ◽  
Disjunct Distribution ◽  
Distribution Model ◽  
Pinus Koraiensis ◽  
Japanese Archipelago ◽  
Bioclimatic Variables ◽  
The Japanese Archipelago ◽  
Suitable Habitats

AbstractClarifying the influences of paleoclimate changes on the disjunct distribution formation of plants allows a historical and mechanical understanding of current vegetation and biodiversity. This study investigated the influences of paleoclimate changes on the present disjunct distribution formation of Pinus koraiensis (Korean pine) using species distribution modeling. A species distribution model (SDM) was built using maximum entropy principle algorithms (MaxEnt), data from 152 occurrences of the species, and four bioclimatic variables at 2.5 arcminute (approximately 5 km) spatial resolution. The simulation revealed the excellent fit of the MaxEnt model performance, with an area under the curve (AUC) value of 0.922 and continuous Boyce index (BCI) value of 0.925 with fivefold cross-validation. The most important climatic factor was the minimum temperature of the coldest month. Suitable habitats for the species ranged between − 30.1 and − 4.1 °C. Projected suitable habitats under the Last Glacial Maximum (approximately 22,000 years ago [ka BP]: LGM) period showed wide distributions in eastern China, the southern part of the Korean Peninsula, and the Japanese Archipelago. After the mid-Holocene (approximately 6 ka BP), the suitable habitats expanded northwards in continental regions and retreated from both north and southwest of Japan. This eventually formed disjunct suitable habitats in central Japan. An increase in temperature after the LGM period caused the migration of P. koraiensis toward new, suitable habitats in continental Northeast Asia, while species in the Japanese Archipelago retreated, forming the present disjunct distributions.

Species Distribution Models (SDM) – A Strategic Tool for Predicting Suitable Habitats for Conserving the Target Species

2019 ◽  
pp. 555-568
Author(s):  
Balaguru Balakrishnan ◽  
Nagamurugan Nandakumar ◽  
Soosairaj Sebastin ◽  
Khaleel Ahamed Abdul Kareem
Keyword(s):  
Species Distribution ◽  
Spatial Data ◽  
Environmental Variables ◽  
Species Distribution Models ◽  
Species Distribution Model ◽  
Distribution Model ◽  
Suitable Habitat ◽  
Target Species ◽  
Distribution Models ◽  
Suitable Habitats

Conservation of the species in their native landscapes required understanding patterns of spatial distribution of species and their ecological connectivity through Species Distribution Models (SDM) by generation and integration of spatial data from different sources using Geographical Information System (GIS) tools. SDM is an ecological/spatial model which combines datasets and maps of occurrence of target species and their geographical and environmental variables by linking various algorithms together, that has been applied to either identify or predict the regions fulfilling the set conditions. This article is focused on comprehensive review of spatial data requirements, statistical algorithms and softwares used to generate the SDMs. This chapter also includes a case study predicting the suitable habitat distribution of Gnetum ula, an endemic and vulnerable plant species using maximum entropy (MaxEnt) species distribution model for species occurrences with inputs from environmental variables such as bioclimate and elevation.

Identifying suitable habitats and current conservation status of a rare and elusive reptile in Iran

2018 ◽  
Vol 39 (3) ◽  
pp. 355-362 ◽  
Author(s):  
Rosa M. Chefaoui ◽  
Mahboubeh Sadat Hosseinzadeh ◽  
Meysam Mashayekhi ◽  
Barbod Safaei-Mahroo ◽  
Seyed Mahdi Kazemi
Keyword(s):  
Protected Areas ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Conservation Status ◽  
Distribution Model ◽  
Reliable Estimate ◽  
Current Conservation ◽  
Mountain Ranges ◽  
Maximum Entropy Modeling ◽  
Suitable Habitats

Abstract Knowledge gaps regarding species distribution and abundance are great in remote regions with political instability, and they might be even larger concerning elusive and rare species. We predict the potential distribution for Hierophis andreanus, a poorly known endemic snake in the Iranian Plateau, and assess its conservation status in relation to existing protected areas. We used a maximum entropy modeling tool and Mahalanobis distance to produce an ensemble species distribution model. The most suitable habitats where located mainly in mountain ranges and adjacent areas of Iran and Afghanistan. Mean temperature and slope were the most important predictors for our models. Furthermore, just five localities for H. andreanus were inside the Iranian protected areas. A 10 km expansion from existing boundaries of protected areas in all directions would double protected localities to 10, and a 20 km buffer would result in 13 protected localities. Our findings are particularly valuable to select locations to conduct new surveys and produce a more reliable estimate of current population size to improve conservation and management for this reptile in the Irano-Anatolian region.

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.

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