scholarly journals A comparison of Species Distribution Modeling approaches for an under-sampled parasite of public health importance, Echinococcus multilocularis

2016 ◽  
Author(s):  
Heather M. Williams ◽  
Brian Egan ◽  
Katharina Dittmar
Keyword(s):  
Public Health ◽  
High Resolution ◽  
North America ◽  
Species Distribution ◽  
Echinococcus Multilocularis ◽  
Research Effort ◽  
The United States ◽  
Distribution Models ◽  
Public Health Importance ◽  
Occurrence Data

AbstractBackgroundSpecies distribution models (SDMs) have an important role in predicting the range of emerging and understudied pathogens and parasites. Their use, however, is often limited by the lack of high-resolution unbiased occurrence records. Echinococcus multilocularis is a parasitic cestode of public health importance which is widely distributed throughout Eu rasia and is considered an emerging threat in North America. In common with many parasite species, available data for E. multilocularis occurrence are spatially biased and often poorly geo-referenced.ResultsHere we produce three separate SDMs using MaxEnt for E. multilocularis using varying complexities of sampling schemes and environmental predictors, designed to make the best possible use of non-ideal occurrence data. The most realistic model utilized both derived and basic climatic predictors; an occurrence sampling scheme which relied primarily on high resolution occurrences from the literature and a bias grid to compensate for an apparently uneven research effort. All models predicted extensive regions of high suitability for E. multilocularis in North America, where the parasite is poorly studied and not currently under coordinated surveillance.ConclusionsThrough a pragmatic approach to non-ideal occurrence data we were able to produce a statistically well supported SDM for an under-studied species of public health importance. Although the final model was only trained on data from Eurasia, the global model projection encompassed all known occurrences in the United States. The approach defined here may be applicable to many other such species and could provide useful information to direct resources for future field based surveillance programs for E. multilocularis in North America.

scholarly journals Exploring snake occurrence records: Spatial biases and marginal gains from accessible social media

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8059 ◽  
Author(s):  
Benjamin M. Marshall ◽  
Colin T. Strine
Keyword(s):  
Social Media ◽  
North America ◽  
South America ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Conservation Status ◽  
Model Performance ◽  
Distribution Models ◽  
Occurrence Data ◽  
Occurrence Records

A species’ distribution provides fundamental information on: climatic niche, biogeography, and conservation status. Species distribution models often use occurrence records from biodiversity databases, subject to spatial and taxonomic biases. Deficiencies in occurrence data can lead to incomplete species distribution estimates. We can incorporate other data sources to supplement occurrence datasets. The general public is creating (via GPS-enabled cameras to photograph wildlife) incidental occurrence records that may present an opportunity to improve species distribution models. We investigated (1) occurrence data of a cryptic group of animals: non-marine snakes, in a biodiversity database (Global Biodiversity Information Facility (GBIF)) and determined (2) whether incidental occurrence records extracted from geo-tagged social media images (Flickr) could improve distribution models for 18 tropical snake species. We provide R code to search for and extract data from images using Flickr’s API. We show the biodiversity database’s 302,386 records disproportionately originate from North America, Europe and Oceania (250,063, 82.7%), with substantial gaps in tropical areas that host the highest snake diversity. North America, Europe and Oceania averaged several hundred records per species; whereas Asia, Africa and South America averaged less than 35 per species. Occurrence density showed similar patterns; Asia, Africa and South America have roughly ten-fold fewer records per 100 km2than other regions. Social media provided 44,687 potential records. However, including them in distribution models only marginally impacted niche estimations; niche overlap indices were consistently over 0.9. Similarly, we show negligible differences in Maxent model performance between models trained using GBIF-only and Flickr-supplemented datasets. Model performance appeared dependent on species, rather than number of occurrences or training dataset. We suggest that for tropical snakes, accessible social media currently fails to deliver appreciable benefits for estimating species distributions; but due to the variation between species and the rapid growth in social media data, may still be worth considering in future contexts.

scholarly journals High-resolution topographic variables accurately predict the distribution of rare plant species for conservation area selection in a narrow-endemism hotspot in New Caledonia

2021 ◽  
Vol 30 (4) ◽  
pp. 963-990 ◽  
Author(s):  
Guillaume Lannuzel ◽  
Joan Balmot ◽  
Nicolas Dubos ◽  
Martin Thibault ◽  
Bruno Fogliani
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
New Caledonia ◽  
Heterogeneous Systems ◽  
Conservation Value ◽  
Environmental Predictors ◽  
Distribution Models ◽  
Conservation Area ◽  
Occurrence Data ◽  
Narrow Endemism

AbstractSpecies distribution models (SDMs) represent a widely acknowledged tool to identify priority areas on the basis of occurrence data and environmental factors. However, high levels of topographical and climatic micro-variation are a hindrance to reliably modelling the distribution of narrow-endemic species when based on classic occurrence and climate datasets. Here, we used high-resolution environmental variables and occurrence data obtained from dedicated field studies to produce accurate SDMs at a local scale. We modelled the potential current distribution of 23 of the 25 rarest species from Mount Kaala, a hotspot of narrow-endemism in New Caledonia, using occurrence data from two recent sampling campaigns, and eight high-resolution (10 m and 30 m) environmental predictors in a Species Distribution Modelling framework. After a first sampling operation, we surveyed six additional areas containing, overall, 13 of the 20 species modelled at this stage, to validate our projections where the highest species richness levels were predicted. The ability of our method to define conservation areas was largely validated with an average 84% of predicted species found in the validation areas, and additional data collected enabling us to model three more species. We therefore identified the areas of highest conservation value for the whole of Mount Kaala. Our results support the ability of SDMs based on presence-only data such as MaxEnt to predict areas of high conservation value using fine-resolution environmental layers and field-collected occurrence data in the context of small and heterogeneous systems such as tropical islands.

Very high resolution environmental predictors in species distribution models

2013 ◽  
Vol 38 (1) ◽  
pp. 79-96 ◽  
Author(s):  
Jean-Nicolas Pradervand ◽  
Anne Dubuis ◽  
Loïc Pellissier ◽  
Antoine Guisan ◽  
Christophe Randin
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Environmental Data ◽  
Swiss Alps ◽  
Fine Scale ◽  
Distribution Models ◽  
Model Quality ◽  
Vegetation Height ◽  
Very High

Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species’ micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions – and therefore local management – compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.

scholarly journals Application Natura 2000 Data For The Invasive Plants Spread Prediction

2015 ◽  
Vol 46 (4) ◽  
pp. 159-166 ◽  
Author(s):  
J. Pěknicová ◽  
D. Petrus ◽  
K. Berchová-Bímová
Keyword(s):  
Environmental Factors ◽  
Invasive Plants ◽  
Species Distribution ◽  
Natura 2000 ◽  
Distribution Model ◽  
Distribution Data ◽  
Habitat Types ◽  
Distribution Models ◽  
Occurrence Data ◽  
Heracleum Mantegazzianum

AbstractThe distribution of invasive plants depends on several environmental factors, e.g. on the distance from the vector of spreading, invaded community composition, land-use, etc. The species distribution models, a research tool for invasive plants spread prediction, involve the combination of environmental factors, occurrence data, and statistical approach. For the construction of the presented distribution model, the occurrence data on invasive plants (Solidagosp.,Fallopiasp.,Robinia pseudoaccacia,andHeracleum mantegazzianum) and Natura 2000 habitat types from the Protected Landscape Area Kokořínsko have been intersected in ArcGIS and statistically analyzed. The data analysis was focused on (1) verification of the accuracy of the Natura 2000 habitat map layer, and the accordance with the habitats occupied by invasive species and (2) identification of a suitable scale of intersection between the habitat and species distribution. Data suitability was evaluated for the construction of the model on local scale. Based on the data, the invaded habitat types were described and the optimal scale grid was evaluated. The results show the suitability of Natura 2000 habitat types for modelling, however more input data (e.g. on soil types, elevation) are needed.

Diversity and distribution of the superfamily Grylloidea (Orthoptera: Ensifera: Gryllidea) in the Nearctic region

Zootaxa ◽  
2021 ◽  
Vol 5040 (2) ◽  
pp. 283-288
Author(s):  
XIN ZHAO ◽  
DANDAN FENG ◽  
YUNTAO LI ◽  
HAOYU LIU
Keyword(s):  
United States ◽  
North America ◽  
Species Distribution ◽  
Coastal Plain ◽  
The United States ◽  
Asymmetric Distribution ◽  
Arctic Zone ◽  
Southeastern Coastal Plain ◽  
Regional Similarity ◽  
Nearctic Region

Based on the geographic distribution database of the Orthoptera Species File, the diversity and distribution of the superfamily Grylloidea in the Nearctic region was studied using the statistics and Sorensen dissimilarity coefficient. A total of 164 species or subspecies belonging to 4 families, 9 subfamilies and 27 genera were recorded from this region; among which Gryllidae (93, 56.70%), followed by Trigonidiidae (44, 26.83%), Mogoplistidae (25, 15.24%), and Phalangopsidae (2, 1.22%). The diversity exhibits an asymmetric distribution pattern, with the southeastern coastal plain, the Interior Plateau and Piedmont of the United States was the most abundant. At the same time, the regional similarity of species distribution was analyzed, and the Nearctic was divided into four subregions: Boreal & Arctic zone of North America, Eastern temperate North America, Northeast temperate North America, and Southern North America & western temperate North America.  

scholarly journals Evaluating ecological uniqueness over broad spatial extents using species distribution modelling

2021 ◽  
Author(s):  
Gabriel Dansereau ◽  
Pierre Legendre ◽  
Timothée Poisot
Keyword(s):  
North America ◽  
Species Distribution ◽  
Rare Species ◽  
Beta Diversity ◽  
Species Distribution Modelling ◽  
Distribution Models ◽  
Science Data ◽  
Distribution Modelling ◽  
Ecological Uniqueness ◽  
The Relationship

Aim: Local contributions to beta diversity (LCBD) can be used to identify sites with high ecological uniqueness and exceptional species composition within a region of interest. Yet, these indices are typically used on local or regional scales with relatively few sites, as they require information on complete community compositions difficult to acquire on larger scales. Here, we investigate how LCBD indices can be used to predict ecological uniqueness over broad spatial extents using species distribution modelling and citizen science data. Location: North America. Time period: 2000s. Major taxa studied: Parulidae. Methods: We used Bayesian additive regression trees (BARTs) to predict warbler species distributions in North America based on observations recorded in the eBird database. We then calculated LCBD indices for observed and predicted data and examined the site-wise difference using direct comparison, a spatial autocorrelation test, and generalized linear regression. We also investigated the relationship between LCBD values and species richness in different regions and at various spatial extents and the effect of the proportion of rare species on the relationship. Results: Our results showed that the relationship between richness and LCBD values varies according to the region and the spatial extent at which it is applied. It is also affected by the proportion of rare species in the community. Species distribution models provided highly correlated estimates with observed data, although spatially autocorrelated. Main conclusions: Sites identified as unique over broad spatial extents may vary according to the regional richness, total extent size, and the proportion of rare species. Species distribution modelling can be used to predict ecological uniqueness over broad spatial extents, which could help identify beta diversity hotspots and important targets for conservation purposes in unsampled locations.

scholarly journals Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning

Ecosphere ◽  
2013 ◽  
Vol 4 (3) ◽  
pp. art42 ◽  
Author(s):  
S. L. Farrell ◽  
B. A. Collier ◽  
K. L. Skow ◽  
A. M. Long ◽  
A. J. Campomizzi ◽  
...  
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Distribution Models

A comparative study of community medicine and public health curriculum at medical schools in Iran and North America

2021 ◽  
Vol 10 (1) ◽  
pp. 19-19
Author(s):  
Tahereh Changiz ◽  
Mahasti Alizadeh
Keyword(s):  
Public Health ◽  
North America ◽  
Comparative Study ◽  
General Medicine ◽  
Medical Schools ◽  
The United States ◽  
Community Medicine ◽  
Center Staff ◽  
Health Curriculum ◽  
Spiral Curriculum

Background: Community medicine and public health are the core subjects in medical education. One of the main competencies of general physicians in the national curriculum is having knowledge and skills in health promotion and disease prevention in the health system. Any curriculum revision in community medicine departments needs to incorporate the evidence and use pioneer countries’ experiences in this issue. This study aims to compare community medicine and public health courses in medical schools between Iran and selected universities in North America. Methods: The elements of a community medicine curriculum for medical students were compared in a descriptive-comparative study using the Bereday model. These elements included objectives and competencies, educational strategies, teaching and learning methods, assessment, and educational fields in a community medicine curriculum in Iran and in selected universities in North America. A literature search was conducted in CINAHL, SCOPUS, MEDLINE, Web of Science, EBSCO, and on university websites. Results: Essential aspects of community-based strategies among community medicine and public health curriculum of general medicine in universities in Canada and the United States included a longitudinal approach, training in urban and rural primary care centers, teaching by family physicians and health center staff, a spiral curriculum, focus on social determinants of health, taking of social and cultural histories and social prescriptions, learning teamwork, and using LIC (Longitudinal Integrated Curriculum). Conclusion: The objective of community medicine and public health curriculum in selected North American universities was to prepare general practitioners who work in Level 2 and 3 hospitals and to improve their skills to provide high-quality services to the community. Some of the successful points in the selected universities that could be replicated in Iranian faculties of medicine included using integration strategy, a spiral curriculum, and an LIC approach.

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