scholarly journals Assessing the performance and accuracy of invasive plant habitat suitability models in detecting new observations in Wisconsin

2021 ◽  
pp. 1-28
Author(s):  
Niels Jorgensen ◽  
Mark Renz
Keyword(s):  
Habitat Suitability ◽  
Invasive Plant ◽  
Model Performance ◽  
Tree Canopy ◽  
Boosted Regression Trees ◽  
Suitable Habitat ◽  
Correct Classification ◽  
Classification Rate ◽  
Habitat Suitability Models ◽  
Tree Canopy Cover

Abstract Land managers require tools that improve understanding of suitable habitat for invasive plants and be incorporated into survey efforts to improve efficiency. Habitat suitability models contain attributes that can meet these requirements, but it is not known how well they perform as they are rarely field tested for accuracy. We developed ensemble habitat suitability models in the state of Wisconsin for 15 species using five algorithms (boosted regression trees, generalized linear models, multivariate regression splines, MaxEnt, and random forests), evaluated performance, determined variables that drive suitability, and tested accuracy. All models had good model performance during the development phase (AUC>0.7 and TSS>0.4). While variable importance and directionality was species specific, the most important predictor variables across all of the species’ models were mean winter minimum temperatures, total summer precipitation and tree canopy cover. Post model development we obtained 5,005 new occurrence records from community science observations for all 15 focal species to test the models’ abilities to accurately predict results. Using a correct classification rate of 80%, just 8 of the 15 species correctly predicted suitable habitat (α≤0.05). Exploratory analyses found the number of reporters of these new data and the total number of new occurrences reported per species contributed to increasing correct classification. Results suggest that while some models perform well on evaluation metrics, relying on these metrics alone is not sufficient and can lead to errors when utilized for surveying. We recommend any model should be tested for accuracy in the field prior to use to avoid this potential issue.

scholarly journals Optimization of spatial scale, but not functional shape, affects the performance of habitat suitability models: a case study of tigers (Panthera tigris) in Thailand

2021 ◽  
Vol 36 (2) ◽  
pp. 455-474
Author(s):  
Eric Ash ◽  
David W. Macdonald ◽  
Samuel A. Cushman ◽  
Adisorn Noochdumrong ◽  
Tim Redford ◽  
...  
Keyword(s):  
Habitat Selection ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Spatial Scales ◽  
Model Performance ◽  
Panthera Tigris ◽  
Habitat Suitability Models ◽  
Multi Scale ◽  
Single Scale ◽  
Optimized Model

Abstract Context Species habitat suitability models rarely incorporate multiple spatial scales or functional shapes of a species’ response to covariates. Optimizing models for these factors may produce more robust, reliable, and informative habitat suitability models, which can be beneficial for the conservation of rare and endangered species, such as tigers (Panthera tigris). Objectives We provide the first formal assessment of the relative impacts of scale-optimization and shape-optimization on model performance and habitat suitability predictions. We explored how optimization influences conclusions regarding habitat selection and mapped probability of occurrence. Methods We collated environmental variables expected to affect tiger occurrence, calculating focal statistics and landscape metrics at spatial scales ranging from 250 m to 16 km. We then constructed a set of presence–absence generalized linear models including: (1) single-scale optimized models (SSO); (2) a multi-scale optimized model (MSO); (3) single-scale shape-optimized models (SSSO) and (4) a multi-scale- and shape-optimized model (MSSO). We compared performance and resulting prediction maps for top performing models. Results The SSO (16 km), SSSO (16 km), MSO, and MSSO models performed equally well (AUC > 0.9). However, these differed substantially in prediction and mapped habitat suitability, leading to different ecological understanding and potentially divergent conservation recommendations. Habitat selection was highly scale-dependent and the strongest relationships with environmental variables were at the broadest scales analysed. Modelling approach had a substantial influence in variable importance among top models. Conclusions Our results suggest that optimization of the scale of resource selection is crucial in modelling tiger habitat selection. However, in this analysis, shape-optimization did not improve model performance.

Using habitat suitability models to target invasive plant species surveys

2013 ◽  
Vol 23 (1) ◽  
pp. 60-72 ◽  
Author(s):  
Alycia W. Crall ◽  
Catherine S. Jarnevich ◽  
Brendon Panke ◽  
Nick Young ◽  
Mark Renz ◽  
...  
Keyword(s):  
Plant Species ◽  
Habitat Suitability ◽  
Invasive Plant ◽  
Invasive Plant Species ◽  
Habitat Suitability Models

scholarly journals Habitat Suitability modeling of Urial (Ovis orientalis arkal) in the Samelghan plain by using Maximum Entropy Method

2021 ◽  
Author(s):  
Abbas Naqibzadeh ◽  
Jalil Sarhangzadeh ◽  
Ahad Sotoudeh ◽  
Marjan Mashkour ◽  
Judith Thomalsky
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Model Performance ◽  
Threshold Value ◽  
Entropy Method ◽  
Suitable Habitat ◽  
Factors Affecting ◽  
Habitat Suitability Modeling ◽  
North East ◽  
The North

Habitat suitability models are useful tools for a variety of wildlife management objectives. Distributions of wildlife species can be predicted for geographical areas that have not been extensively surveyed. The basis of these models' work is to minimize the relationship between species distribution and biotic and abiotic environments. For some species, there is information about presence and absence that allows the use of a variety of standard statistical methods, however, the absence data is not available for most species. Nowadays, the methods that need presence-only data are expanded. One of these methods is the Maximum Entropy (MaxEnt) modeling. The purpose of this study is to model the habitat of Urial ( Ovis orientalis arkal ) in the Samelghan plain in the North East of Iran with the MaxEnt method. This algorithm uses the Jackknife plot and percent contribution values to determine the significance of the variables. The results showed that variables such as southern aspects, Juniperus-Acer, Artemisia-Perennial plants, slope 0-5%, and asphalt road were the most important factors affecting the species’ habitat selection. The area under curve (AUC) Receiver Operating Characteristic (ROC) showed an excellent model performance. Suitable habitat was classified based on the threshold value (0.0513) and the ROC, which based on the results 28% of the area was a suitable habitat for Urial.

Habitat suitability models indicate the White-breasted Thrasher Ramphocinclus brachyurus occupies all suitable habitat in Saint Lucia

2016 ◽  
Vol 27 (1) ◽  
pp. 96-110 ◽  
Author(s):  
EMMA M. SASS ◽  
JENNIFER L. MORTENSEN ◽  
J. MICHAEL REED
Keyword(s):  
Land Cover ◽  
Habitat Suitability ◽  
Habitat Management ◽  
Full Range ◽  
Species Conservation ◽  
Dry Forest ◽  
Suitable Habitat ◽  
Habitat Suitability Models ◽  
Full Range Model ◽  
Saint Lucia

SummaryHabitat suitability models can guide species conservation by identifying correlates of occurrence and predicting where species are likely to occur. We created habitat suitability models for the White-breasted Thrasher Ramphocinclus brachyurus, a narrowly distributed endangered songbird that occupies dry forest in Saint Lucia and Martinique. Eighty-five percent of the global population inhabits two ranges in Saint Lucia, both of which are largely unprotected and threatened by development. We developed three habitat suitability models using Maxent techniques and published occupancy datasets collected from the species’ two Saint Lucian ranges, and used abiotic, land cover, and predator distribution predictors. We built one model with occupancy data from both ranges, and two others with occupancy data specific to each range. The best full-range model included 11 predictors; high suitability was associated with close proximity to Saint Lucia fer-de-lance Bothrops caribbeaus range, moderately low precipitation, and areas near streams. Our assessment of suitable sites island-wide was more restricted than results from a recent model that considered older land cover data and omitted predator distributions. All sites identified in our full-range model as highly suitable were in or adjacent to the species’ current designated range. The model trained on southern range occurrences predicted zero suitable habitat in the northern range, where the population is much smaller. In contrast, the model trained on northern range occurrences identified areas of moderate suitability within the southern range and patches of moderately suitable habitat in the western part of the island, where no White-breasted Thrashers currently occur. We interpret these results as suggesting that White-breasted Thrashers currently occupy virtually all suitable habitat on the island, that birds in the northern range occupy marginal habitat, or that an important correlate of suitability is missing from the model. Our results suggest that habitat management should focus on currently occupied areas.

scholarly journals Global habitat suitability models of terrestrial mammals

2011 ◽  
Vol 366 (1578) ◽  
pp. 2633-2641 ◽  
Author(s):  
Carlo Rondinini ◽  
Moreno Di Marco ◽  
Federica Chiozza ◽  
Giulia Santulli ◽  
Daniele Baisero ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Iucn Red List ◽  
Red List ◽  
Conservation Strategies ◽  
Absolute Difference ◽  
Distribution Data ◽  
Suitable Habitat ◽  
Mammal Species ◽  
Habitat Suitability Models ◽  
Terrestrial Mammals

Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.

scholarly journals Habitat suitability of Proboscis monkey (Nasalis larvatus) in Berau Delta, East Kalimantan, Indonesia

2020 ◽  
Vol 21 (11) ◽  
Author(s):  
Tri Atmoko ◽  
Ani Mardiastuti ◽  
Muhammad Bismark ◽  
Lilik Budi Prasetyo ◽  
Entang Iskandar
Keyword(s):  
Habitat Suitability ◽  
Model Performance ◽  
Area Under The Curve ◽  
Suitable Habitat ◽  
Proboscis Monkey ◽  
Environmental Predictors ◽  
Swamp Forest ◽  
Nasalis Larvatus ◽  
East Kalimantan ◽  
Habitat Suitability Map

The proboscis monkey (Nasalis larvatus) is an endemic species to Borneos’ island and is largely confined to mangrove, riverine, and swamp forest. Most of their habitat is outside the conservation due to degraded and habitat converted. Habitat loss is a significant threat to a decreased in the monkey's population. Berau Delta is an unprotected habitat of proboscis monkey, lacking in attention and experiencing a lot of disturbances. This study was conducted on April – August 2019; with aims of the study is to determine Species Distribution Modeling (SDM) for identifying proboscis monkey habitat suitability in Delta Berau, East Kalimantan. The MaxEnt algorithm was used to produce a habitat suitability map based on this species’ occurrence records and environmental predictors. We built the models using 208 points of proboscis monkey presence and 12 environment variables within the study area. Model performance was assessed by examining the area under the curve. The variables most influencing the habitat suitability model were the riverine habitat (60.9%), distance from the pond (16.0%), and distance from the coastline (5.2%). The proboscis monkey suitable habitat is only 9.32% (8,726.58 ha) from 93,631.41 ha total area. The appropriate habitat areas are Sapinang Island, Bungkung Island, Sambuayan Island, Saodang Kecil Island, Besing Island, Lati River, Bebanir Lama, Batu-Batu, and Semanting Bay. We provide some suggestions for the proboscis monkey conservation, which are local protection of uninhabited islands, participatory ecotourism management, and company involvement in protection and management efforts.

Bentgrass Distribution Surveys and Habitat Suitability Maps Support Ecological Risk Assessment in Cultural Landscapes

Weed Science ◽  
2011 ◽  
Vol 59 (2) ◽  
pp. 145-154 ◽  
Author(s):  
C. Ahrens ◽  
J. Chung ◽  
T. Meyer ◽  
C. Auer
Keyword(s):  
Ecological Risk ◽  
Habitat Suitability ◽  
Cultural Landscapes ◽  
Ecological Factors ◽  
Canopy Cover ◽  
Creeping Bentgrass ◽  
Tree Canopy ◽  
Tree Canopy Cover ◽  
Suitability Maps ◽  
Ecological Risk Assessments

The bentgrasses comprise an adaptable group of grasses that include introduced species, cultivated turfgrasses, and native plants in North America. Their distribution in cultural landscapes has not been documented, and this gap in knowledge has limited the development of predictive ecological risk assessments for creeping bentgrass engineered for herbicide resistance. In this study, bentgrass distribution and abundance were surveyed in 289 plots in an 8.5 km2 site surrounding a golf course in the northeastern United States. Four introduced species and two native bentgrasses were identified in seminatural and managed plant communities. Across the study site, 77% of the plots containing creeping bentgrass also had invasive plants. Bentgrasses co-occurred with critical habitat for threatened or endangered animals. Multivariate logistic regression analysis showed that bentgrasses were positively correlated with herbaceous plant cover and mowing, but negatively correlated with tree canopy cover, shrub cover, poorly drained soils, and leaf litter. The most influential ecological factors were tree canopy cover and soil moisture. Geospatial information about these two ecological factors was combined with mathematical models to generate two habitat suitability maps. The favorable environments map (FEM) showed that highly suitable bentgrass habitat covered 36% of the study site and included common features such as home lawns and railroad right-of-ways. Our results suggest that release of herbicide-resistant creeping bentgrass in this cultural landscape could potentially result in pollen-mediated gene flow, interspecific hybridization, environmental hazards, and herbicide selection pressure in some areas. Habitat suitability maps could be critical tools for predictive ecological risk assessments, monitoring projects, and management of herbicide-resistant bentgrasses.

Predicting bycatch hotspots based on suitable habitat derived from fishery-independent data

2020 ◽  
Vol 641 ◽  
pp. 159-175
Author(s):  
J Runnebaum ◽  
KR Tanaka ◽  
L Guan ◽  
J Cao ◽  
L O’Brien ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Gulf Of Maine ◽  
Homarus Americanus ◽  
Management Tool ◽  
American Lobster ◽  
Suitable Habitat ◽  
Climate Conditions ◽  
Suitability Index

Bycatch remains a global problem in managing sustainable fisheries. A critical aspect of management is understanding the timing and spatial extent of bycatch. Fisheries management often relies on observed bycatch data, which are not always available due to a lack of reporting or observer coverage. Alternatively, analyzing the overlap in suitable habitat for the target and non-target species can provide a spatial management tool to understand where bycatch interactions are likely to occur. Potential bycatch hotspots based on suitable habitat were predicted for cusk Brosme brosme incidentally caught in the Gulf of Maine American lobster Homarus americanus fishery. Data from multiple fisheries-independent surveys were combined in a delta-generalized linear mixed model to generate spatially explicit density estimates for use in an independent habitat suitability index. The habitat suitability indices for American lobster and cusk were then compared to predict potential bycatch hotspot locations. Suitable habitat for American lobster has increased between 1980 and 2013 while suitable habitat for cusk decreased throughout most of the Gulf of Maine, except for Georges Basin and the Great South Channel. The proportion of overlap in suitable habitat varied interannually but decreased slightly in the spring and remained relatively stable in the fall over the time series. As Gulf of Maine temperatures continue to increase, the interactions between American lobster and cusk are predicted to decline as cusk habitat continues to constrict. This framework can contribute to fisheries managers’ understanding of changes in habitat overlap as climate conditions continue to change and alter where bycatch interactions could occur.

Landscape-level habitat suitability models for twelve species in southern Missouri

2003 ◽  
Author(s):  
Michael A. Larson ◽  
William D. Dijak ◽  
Frank R. III Thompson ◽  
Joshua J. Millspaugh
Keyword(s):  
Habitat Suitability ◽  
Habitat Suitability Models ◽  
Landscape Level
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