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Rew, Jehyeok, Yongjang Cho, Jihoon Moon, and Eenjun Hwang. "Habitat Suitability Estimation Using a Two-Stage Ensemble Approach." Remote Sensing 12, no. 9 (May 6, 2020): 1475. http://dx.doi.org/10.3390/rs12091475.
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Biodiversity conservation is important for the protection of ecosystems. One key task for sustainable biodiversity conservation is to effectively preserve species’ habitats. However, for various reasons, many of these habitats have been reduced or destroyed in recent decades. To deal with this problem, it is necessary to effectively identify potential habitats based on habitat suitability analysis and preserve them. Various techniques for habitat suitability estimation have been proposed to date, but they have had limited success due to limitations in the data and models used. In this paper, we propose a novel scheme for assessing habitat suitability based on a two-stage ensemble approach. In the first stage, we construct a deep neural network (DNN) model to predict habitat suitability based on observations and environmental data. In the second stage, we develop an ensemble model using various habitat suitability estimation methods based on observations, environmental data, and the results of the DNN from the first stage. For reliable estimation of habitat suitability, we utilize various crowdsourced databases. Using observational and environmental data for four amphibian species and seven bird species in South Korea, we demonstrate that our scheme provides a more accurate estimation of habitat suitability compared to previous other approaches. For instance, our scheme achieves a true skill statistic (TSS) score of 0.886, which is higher than other approaches (TSS = 0.725 ± 0.010).
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Hightower, Joseph E., Julianne E. Harris, Joshua K. Raabe, Prescott Brownell, and C. Ashton Drew. "A Bayesian Spawning Habitat Suitability Model for American Shad in Southeastern United States Rivers." Journal of Fish and Wildlife Management 3, no. 2 (December 1, 2012): 184–98. http://dx.doi.org/10.3996/082011-jfwm-047.
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Abstract Habitat suitability index models for American shad Alosa sapidissima were developed by Stier and Crance in 1985. These models, which were based on a combination of published information and expert opinion, are often used to make decisions about hydropower dam operations and fish passage. The purpose of this study was to develop updated habitat suitability index models for spawning American shad in the southeastern United States, building on the many field and laboratory studies completed since 1985. We surveyed biologists who had knowledge about American shad spawning grounds, assembled a panel of experts to discuss important habitat variables, and used raw data from published and unpublished studies to develop new habitat suitability curves. The updated curves are based on resource selection functions, which can model habitat selectivity based on use and availability of particular habitats. Using field data collected in eight rivers from Virginia to Florida (Mattaponi, Pamunkey, Roanoke, Tar, Neuse, Cape Fear, Pee Dee, St. Johns), we obtained new curves for temperature, current velocity, and depth that were generally similar to the original models. Our new suitability function for substrate was also similar to the original pattern, except that sand (optimal in the original model) has a very low estimated suitability. The Bayesian approach that we used to develop habitat suitability curves provides an objective framework for updating the model as new studies are completed and for testing the model's applicability in other parts of the species' range.
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McLeod, S. R., and A. R. Pople. "Modelling the distribution and relative abundance of feral camels in the Northern Territory using count data." Rangeland Journal 32, no. 1 (2010): 21. http://dx.doi.org/10.1071/rj09057.
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The objectives of this study were to predict the potential distribution, relative abundance and probability of habitat use by feral camels in southern Northern Territory. Aerial survey data were used to model habitat association. The characteristics of ‘used’ (where camels were observed) v. ‘unused’ (pseudo-absence) sites were compared. Habitat association and abundance were modelled using generalised additive model (GAM) methods. The models predicted habitat suitability and the relative abundance of camels in southern Northern Territory. The habitat suitability maps derived in the present study indicate that camels have suitable habitat in most areas of southern Northern Territory. The index of abundance model identified areas of relatively high camel abundance. Identifying preferred habitats and areas of high abundance can help focus control efforts.
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Aryanti, Nirmala Ayu, Tander Scila Serata Dwi Susilo, Ari Nadya Ningtyas, and Mahmuddin Rahmadana. "Pemodelan Spasial Kesesuaian Habitat Elang Jawa (Nisaetus bartelsi) di Taman Nasional Bromo Tengger Semeru (Spatial Modeling of Javan Hawk-Eagle (Nisaetus bartelsi) Habitat Suitability in Bromo Tengger Semeru National Park)." Jurnal Sylva Lestari 9, no. 1 (January 29, 2021): 179. http://dx.doi.org/10.23960/jsl19179-189.
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Bromo Tengger Semeru National Park (TNBTS) is a conservation area as the habitat of endemic species in Java Island, such as the Javan hawk-eagle (Nisaetus bartelsi). One of the spatial models of habitat is the Ecological Niche Modeling (ENM) approach. This study aimed to determine habitat suitability for the Javan hawk-eagle in TNBTS. The research was conducted from September 2019 to January 2020. The habitat suitability model used the present coordinate point data and the Javan hawk-eagle habitat environment variables. The data were then analyzed to build a Javan hawk-eagle habitat suitability model using the Maximum Entropy (MaxEnt) algorithm. The results showed three models of habitat suitability categories, i.e.: high of 15,131.18 ha (30%), medium 11,216.61 ha (22%), and low 23,298.41 ha (48%). The evaluation of the Javan hawk-eagle habitat suitability model in TNBTS has an excellent model accuracy with an AUC value of 0.97 and a standard deviation of 0.93.Keywords: endemic, habitat, Javan hawk-eagle, maximum entropy, spatial modeling
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Jeong, Seunggyu, Changwan Seo, Jaehyun Yoon, Dong Kun Lee, and Jonghoon Park. "A Study on Riparian Habitats for Amphibians Using Habitat Suitability Model." Journal of Environmental Impact Assessment 24, no. 2 (April 30, 2015): 175–89. http://dx.doi.org/10.14249/eia.2015.24.2.175.
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Li, Jie, Hui Qin, Shaoqian Pei, Liqiang Yao, Wei Wen, Liang Yi, Jianzhong Zhou, and Lingyun Tang. "Analysis of an Ecological Flow Regime during the Ctenopharyngodon Idella Spawning Period Based on Reservoir Operations." Water 11, no. 10 (September 29, 2019): 2034. http://dx.doi.org/10.3390/w11102034.
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The study of fish habitats is important for us to better understand the impact of reservoir construction on river ecosystems. Many habitat models have been developed in the past few decades. In this study, a fuzzy logic-based habitat model, which couples fuzzy inference system, two-dimensional laterally averaged hydrodynamic model, and two-dimensional shallow water hydrodynamic model, is proposed to identify the baseline condition of suitable habitat for fish spawning activities. The proposed model considers the reservoir and the downstream river channel, and explores the comprehensive effects of water temperature, velocity, and water depth on habitat suitability. A real-world case that considers the Ctenopharyngodon idella in the Xuanwei Reservoir of Qingshui River is studied to investigate the effect of in- and outflow of reservoir on fish habitat and the best integrative management measure of the model. There were 64 simulations with different reservoir in- and outflows employed to calculate the weighted usable area and hydraulic habitat suitability. The experimental results show that the ecological flow for Ctenopharyngodon idella spawning can satisfy the basic demand when the reservoir inflow is greater than 60 m3/s and the reservoir outflow is greater than 100 m3/s. The habitat ecological suitability is the best when the reservoir outflow is 120 m3/s. A more reasonable and reliable ecological flow range can be obtained based on the habitat model in this paper, which provides the best scenario for water resources planning and management in the Qingshui River Basin.
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Ouellet, Valerie, André St-Hilaire, Yves Secretan, Marc Mingelbier, Jean Morin, and Stephen J. Dugdale. "The Importance of Including Water Temperature Simulations in a 2D Fish Habitat Model for the St. Lawrence River." Water 13, no. 13 (June 23, 2021): 1736. http://dx.doi.org/10.3390/w13131736.
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Extreme climatic conditions likely caused a massive fish mortality during the summer of 2001 in the St. Lawrence River. To corroborate this hypothesis, we used a physical habitat simulation approach incorporating hydraulic and water temperature models. Spawning Habitat Suitability Indices (HSI) for common carp (Cyprinus carpio) were developed using fuzzy logic and applied to the model outputs to estimate habitat weighted usable area during the event. The results revealed that areas suitable for common carp spawning (HSI > 0.3) were severely reduced by high water temperatures, which exceeded 28 °C during the mortality event. During the mortality event, the amount of suitable habitat was reduced to <200 ha/day, representing less than 15% of the maximum potential suitable habitat in the study reach. In addition, the availability of cooler habitats that could have been used as thermal refuges was also reduced. These results indicate that the high water temperature in spawning areas and reduced accessibility to thermal refuge habitats exposed the carp to substantial physiological and environmental stress. The high water temperatures were highly detrimental to the fish and eventually led to the observed mortalities. This study demonstrates the importance of including water temperature in habitat suitability models.
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Shiroyama, Risa, Manna Wang, and Chihiro Yoshimura. "Effect of sample size on habitat suitability estimation using random forests: a case of bluegill, Lepomis macrochirus." Annales de Limnologie - International Journal of Limnology 56 (2020): 13. http://dx.doi.org/10.1051/limn/2020010.
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Species distribution models (SDMs) have been used to understand the habitat suitability of key species. Habitat suitability plots, one outcome from SDMs, are valuable for understanding the habitat suitability and behavior of organisms. The sample size is often constrained by budget and time, and could largely influence the reliability of habitat suitability plots. To understand the effect of sample size on habitat suitability plots, the present study utilized random forests (RF) combined with partial dependence function. And the bluegill (Lepomis macrochirus), a main exotic fish species in the Japan rivers, was selected as target species in this study. Total of 1010 samples of bluegill observations along with four environmental variables were surveyed by the National Censuses on River Environments. The area under curves was calculated after generating RF models, to assess the predictive model performance, and this process was repeated 1000 times. To draw habitat suitability plots, we applied partial dependence function to the formulated RF models, and 15 different sample sizes were set to examine the effect on habitat suitability plots. We concluded that habitat suitability plots are affected by sample size and prediction performance. Notably, habitat suitability plots drawn from the sample size of 50 greatly varied among the 1000-time iterations, and they are all different from the observations. Furthermore, to deal with the case of limited samples, we proposed a novel approach “averaged habitat suitability plot” for delineating habitat suitability plots. The proposed approach enables us to assess the habitat suitability even with a small sample size.
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Adamczyk, Mikołaj, Piotr Parasiewicz, Paolo Vezza, Paweł Prus, and Giovanni De Cesare. "Empirical Validation of MesoHABSIM Models Developed with Different Habitat Suitability Criteria for Bullhead Cottus Gobio L. as an Indicator Species." Water 11, no. 4 (April 8, 2019): 726. http://dx.doi.org/10.3390/w11040726.
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Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool for water management planning, especially in terms of requirements of the Water Framework Directive. Therefore, model verification studies, which investigate the accuracy and reliability of the results generated, are essential. An electrofishing survey was conducted in September 2014 on the Stura di Demonte River located in north-western Italy. One hundred and sixteen bullhead—Cottus gobio L.—were captured in 80 pre-exposed area electrofishing (PAE) grids. Observations of bullhead distribution in various habitats were used to validate MesoHABSIM model predictions created with inductive and deductive habitat suitability indices. The inductive statistical models used electrofishing data obtained from multiple mountainous streams, analyzed with logistic regression. The deductive approach was based on conditional habitat suitability criteria (CHSC) derived from expert knowledge and information gathered from the literature about species behaviour and habitat use. The results of model comparison and validation show that although the inductive models are more precise and reflect site- and species-specific characteristics, the CHSC model provides quite similar results. We propose to use inductive models for detailed planning of measures that could potentially impair riverine ecosystems at a local scale, since the CHSC model provides general information about habitat suitability and use of such models is advised in pre-development or generic scale studies. However, the CHSC model can be further calibrated with localized electrofishing data at a lower cost than development of an inductive model.
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SASS, EMMA M., JENNIFER L. MORTENSEN, and J. MICHAEL REED. "Habitat suitability models indicate the White-breasted Thrasher Ramphocinclus brachyurus occupies all suitable habitat in Saint Lucia." Bird Conservation International 27, no. 1 (May 23, 2016): 96–110. http://dx.doi.org/10.1017/s0959270915000374.
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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.
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Virgl, John A., and François Messier. "Assessment of source-sink theory for predicting demographic rates among habitats that exhibit temporal changes in quality." Canadian Journal of Zoology 78, no. 8 (August 1, 2000): 1483–93. http://dx.doi.org/10.1139/z00-066.
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Within the framework of Pulliam's source-sink model we tested predictions of habitat-specific demography on a "closed" population of muskrats (Ondatra zibethicus L.) occupying three contiguous habitats that exhibited temporal changes in quality and quantity. We were able to distinguish between dispersal among habitats and mortality within each habitat, and induce temporal variation in operational-habitat availability and suitability by manipulating water level. Temporal variation in population size and density among habitats supported the source-sink model and was primarily associated with habitat-specific survival rates. For example, the mean annual over-winter mortality rate of individuals in the principal source habitat (0.87) was less than in the sink habitat (0.94), and subsequently the mean annual finite rate of increase (λ) was positive in the source habitat (λ = 1.41) and negative in the sink habitat (λ = 0.90). The high recruitment rate of juveniles in the prime habitat during autumn was also associated with significant emigration of juveniles from this habitat. Emigration of adults among habitats provided support for the role of spacing behaviour in regulating the breeding density of muskrats in prime habitat. However, in contrast to the assumption of source-sink theory, year-to-year variation in survival rate in the more marginal habitats appeared to be explained more by temporal changes in habitat suitability than by density. Significant emigration of juveniles from the sink habitat was not predicted and was largely dependent on current habitat conditions. In addition, the mean annual emigration rate was lowest in the principal source habitat (0.30) and highest in the more marginal habitats (0.62). Failure to detect directional emigration from prime to marginal habitats in the spring, as predicted by the source-sink model, was likely due to declining local population size. In environments where spatial differences in habitat quality are not static, and annual change in local population size is largely independent of density, current source-sink models must be modified to better predict individual dispersal strategies.
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Yao, Siyang, Xinyu Li, Chenglin Liu, Dongyang Yuan, Longhui Zhu, Xiangyu Ma, Jie Yu, Gang Wang, and Weiming Kuang. "Quantitative Assessment of Impact of the Proposed Poyang Lake Hydraulic Project (China) on the Habitat Suitability of Migratory Birds." Water 11, no. 8 (August 8, 2019): 1639. http://dx.doi.org/10.3390/w11081639.
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Poyang Lake is the largest wintering habitat for migratory birds in Asia. In the last decade, the lake has experienced an early-occurring and prolonged dry season that has deteriorated the lake’s ecological status. To tackle this issue, the Chinese government has proposed the construction of the Poyang Lake Hydraulic Project (PLHP) to regulate water flow to the lake. However, its impact on migratory bird habitats is unknown. In this study, we simulated the habitat suitability for migratory birds in Poyang Lake during wet and dry years, with and without the presence/operation of the hydraulic project. A two-dimensional hydrodynamic model was used to simulate the water conditions for each case. Matter-element theory, 3S technology and ecological knowledge were combined to develop a matter-element-based habitat suitability model in a geographic information system (GIS)-based platform. We assessed and compared the habitat suitability in four scenarios: (1) Wet year without the hydraulic project, (2) wet year with the hydraulic project, (3) dry year without the hydraulic project, and (4) dry year with the hydraulic project. The results showed that the operation of the hydraulic project can effectively alleviate the water shortage issue in the wetland and increase the area of habitats suitable for migratory birds in typical dry years. However, it can reduce the area of suitable habitats in the northern provincial nature reserve of the lake. In addition, a reasonable management of the lake’s fishing activities can also increase habitat suitability and promote balanced patterns between human activities and migratory bird habitats.
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Dussault, Christian, Réhaume Courtois, and Jean-Pierre Ouellet. "A habitat suitability index model to assess moose habitat selection at multiple spatial scales." Canadian Journal of Forest Research 36, no. 5 (May 1, 2006): 1097–107. http://dx.doi.org/10.1139/x05-310.
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We developed a habitat suitability index (HSI) model for moose (Alces alces) in the boreal forest. The model used two components: a suitability index for food (SIfood) and another for the interspersion between cover and food (SIedge). We used forest maps as the input data source, and the value of each stand type in terms of cover and food was based on field surveys. To validate the model, the habitat preference of moose equipped with global positioning system telemetry collars was assessed at both landscape and home-range scales. We expected the habitat-preference index to correlate with suitability indices determined using the global model and each of its two components. Habitat suitability was assessed in evaluation plots of 500, 100, and 10 ha. Unexpectedly, the habitat-preference index correlated better with SIfood and SIedge than with the global model. The suitability indices also performed better when assessed in large plots. Selection of 500 ha plots related mostly to SIedge, but SIfood was more important when smaller evaluation plots were used, especially for males. Females preferred plots with intermediate SIfood values. At the fine scale, SIedge was not as attractive to moose as was previously observed, presumably because snow conditions prevailing in our study area were relatively moderate. We recommend utilizing the model with SIedge in large plots (ca. 500 ha) and SIfood in smaller plots. Our model could be adapted and applied to other areas by using empirical data to adjust the relative value of stand types in terms of cover and food.
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Muhamad, Muhammad Abdul Hakim, Rozaimi Che Hasan, Najhan Md Said, and Jillian Lean-Sim Ooi. "Seagrass habitat suitability model for Redang Marine Park using multibeam echosounder data: Testing different spatial resolutions and analysis window sizes." PLOS ONE 16, no. 9 (September 23, 2021): e0257761. http://dx.doi.org/10.1371/journal.pone.0257761.
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Integrating Multibeam Echosounder (MBES) data (bathymetry and backscatter) and underwater video technology allows scientists to study marine habitats. However, use of such data in modeling suitable seagrass habitats in Malaysian coastal waters is still limited. This study tested multiple spatial resolutions (1 and 50 m) and analysis window sizes (3 × 3, 9 × 9, and 21 × 21 cells) probably suitable for seagrass-habitat relationships in Redang Marine Park, Terengganu, Malaysia. A maximum entropy algorithm was applied, using 12 bathymetric and backscatter predictors to develop a total of 6 seagrass habitat suitability models. The results indicated that both fine and coarse spatial resolution datasets could produce models with high accuracy (>90%). However, the models derived from the coarser resolution dataset displayed inconsistent habitat suitability maps for different analysis window sizes. In contrast, habitat models derived from the fine resolution dataset exhibited similar habitat distribution patterns for three different analysis window sizes. Bathymetry was found to be the most influential predictor in all the models. The backscatter predictors, such as angular range analysis inversion parameters (characterization and grain size), gray-level co-occurrence texture predictors, and backscatter intensity levels, were more important for coarse resolution models. Areas of highest habitat suitability for seagrass were predicted to be in shallower (<20 m) waters and scattered between fringing reefs (east to south). Some fragmented, highly suitable habitats were also identified in the shallower (<20 m) areas in the northwest of the prediction models and scattered between fringing reefs. This study highlighted the importance of investigating the suitable spatial resolution and analysis window size of predictors from MBES for modeling suitable seagrass habitats. The findings provide important insight on the use of remote acoustic sonar data to study and map seagrass distribution in Malaysia coastal water.
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Ariffin, N. A. T., M. A. Mustapha, T. M. Taher, N. F. Khodri, N. I. Abdullah, and S. M. Nor. "Potential habitat connectivity for Malayan gaur (Bos gaurus) in a fragmented forest area in Peninsular Malaysia." Journal of Environmental Biology 42, no. 3(SI) (May 31, 2021): 798–805. http://dx.doi.org/10.22438/jeb/42/3(si)/jeb-09.
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Aim: To predict the distribution of suitable habitats for Malayan gaur (Bos gaurus) at a highly fragmented forest area in Peninsular Malaysia and to identify the potential connectivity between suitable habitat patches. Methodology: Maximum entropy (MaxEnt) approach was used to predict the distribution of suitable habitats of the Malayan gaur. Gaur presence-only data and six environmental variables were collated for the habitat suitability modeling, and area under curve (AUC) value was used to estimate the performance of the model. The resulting model was then used to derive a potential connectivity map through least-cost analysis using Corridor Designer toolbox in ArcGIS 10.4. Results: The AUC value of the habitat suitability model was 0.84. Distance from urban areas indicated the highest relative contribution to the model (26.9%), followed by distance from water body (24.2%) land use (18.0%) elevation (14.3%), slope (14.0%) and lithology (2.6%). Predicted suitable habitats for gaur were found mostly in lowland forest areas, especially in the vicinity of rivers within forest reserves. A total of five wildland blocks were derived from the habitat suitability model, and several potential corridor swaths were identified connecting the wildland blocks. Interpretation: The absence of gaur occurrence in suitable habitats suggest that fragmented habitats greatly affected gaur distribution and population. Road network and agricultural lands are the major barriers of gaur movement as they are very sensitive towards disturbances and conflict. Thus, this research proposes potential connectivity at a regional scale for Malayan gaur for use in future planning in conservation, management and development.
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Tadesse, Solomon A., and Burt P. Kotler. "Habitat Choices of Nubian Ibex (Capra Nubiana) Evaluated with A habitat Suitability Modeling and Isodar Analysis." Israel Journal of Ecology and Evolution 56, no. 1 (May 6, 2010): 55–74. http://dx.doi.org/10.1560/ijee.56.1.55.
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The value of a habitat for a forager may be affected by habitat characteristics related to food availability, energetic costs of foraging, predation costs, and the foraging opportunities available in other habitats. Nubian ibex (Capra nubiana) are stout, sure-footed social wild goats that inhabit arid landscapes with steep terrain. We investigated their habitat selection behavior using indicators to (1) develop a habitat suitability index (HSI) model that would account for the variation in the activity densities of Nubian ibex across habitat types and seasons, (2) apply the isodar technique to look for density-dependent habitat selection behavior in Nubian ibex, and (3) investigate the proximate environmental factors that correlate to relative activity densities of Nubian ibex. We determined relative densities of the ibex by recording sightings of animals along standard walking transects. We incorporated the habitat variables that had greatest influence on the densities of Nubian ibex into habitat suitability index models for both spring and summer seasons.The HSI models revealed that Nubian ibex most preferred open cliff face habitat offering safety during the spring season, but their habitat preference shifted towards an area with watered gardens ("grave area habitat") during the summer season. Significant isodars were only obtained for the summer season comparisons between grave area versus cliff face, and between grave area versus plateau habitats. The slopes of the isodars suggest that the grave area habitat is 10.5 and 7.6 times more productive than the plateau and the cliff face habitats, respectively. Our results suggest that the relative abundances and habitat preferences of Nubian ibex varied with the seasonal availability of habitat resources, extent of predation risks, and human nuisance disturbances across the landscape. We recommend that wildlife managers dealing with the conservation and protection of the endangered Nubian ibex should focus on the various ecological and anthropogenic factors governing the habitat selection and preferences.
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Yen, Shih-Ching, Ying Wang, and Heng-You Ou. "Habitat of the Vulnerable Formosan sambar deerRusa unicolor swinhoiiin Taiwan." Oryx 48, no. 2 (October 17, 2013): 232–40. http://dx.doi.org/10.1017/s0030605312001378.
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AbstractThe sambar deerRusa unicoloris categorized as Vulnerable on the IUCN Red List because of continuous population decline across its native range. In Taiwan the Formosan sambar deerR. unicolor swinhoiiis listed as a protected species under the Wildlife Conservation Act because of human overexploitation. However, its population status remains unclear. We used presence and absence data from line transect and camera-trap surveys to identify key habitat variables and to map potential habitats available to this subspecies in Taiwan. We applied five habitat-suitability models: logistic regression, discriminant analysis, ecological-niche factor analysis, genetic algorithm for rule-set production, and maximum entropy. We then combined the results of all five models into an ensemble-forecasting model to facilitate a more robust prediction. This model indicated the existence of 7,865 km2of suitable habitat for the sambar deer. Distance from roads and elevation were identified as the most important environmental variables for habitat suitability, and deer preferred areas far from roads and > 1,500 m altitude. The results predicted that suitable deer habitat is mainly located in Taiwan's Central Mountain Range and Xue Mountain Range, with c. 70% of this suitable habitat in protected areas. However, the habitat predicted to be suitable is in five areas separated by mountain highways. We recommend that deer habitats close to the highways should be monitored for the future establishment of corridors between Formosan sambar deer sub-populations.
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Öhman, Karin, Lars Edenius, and Grzegorz Mikusiński. "Optimizing spatial habitat suitability and timber revenue in long-term forest planning." Canadian Journal of Forest Research 41, no. 3 (March 2011): 543–51. http://dx.doi.org/10.1139/x10-232.
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Effective tools must be developed that include consideration of biodiversity in the traditional forest planning process. The objective of this study is to present a spatial habitat suitability model that could be included in the optimization of long-term forest planning where the problem can be solved with an exact solution method. This could be an advantage, since, e.g., many forest planning systems available today are designed for problems that could be solved with an exact solution method. The habitat model consists of two parts: suitability assessment of stand-wise conditions and spatial conditions. To investigate whether the model works in a realistic setting, we used a case study and applied the model to the habitat demands for Hazel Grouse ( Bonasa bonasia L.). The results from the case study indicate that the model is effective for including spatial habitat consideration and that the model could be used for creating different degrees of the clustering of habitats. Further, the loss in net present value as a result of the spatial habitat demands was limited in the case study. We suggest that this modeling approach could be extended to other species with large area requirements and add to the existing tools for forest biodiversity assessment in forest management planning.
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Chang, Yi-Jay, Chi-Lu Sun, Yong Chen, Su-Zan Yeh, Gerard DiNardo, and Nan-Jay Su. "Modelling the impacts of environmental variation on the habitat suitability of swordfish, Xiphias gladius, in the equatorial Atlantic Ocean." ICES Journal of Marine Science 70, no. 5 (January 8, 2013): 1000–1012. http://dx.doi.org/10.1093/icesjms/fss190.
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Abstract Chang, Y.-J., Sun, C.-L., Chen, Y., Yeh, S.-Z., DiNardo, G., and Su, N.-J. 2013. Modelling the impacts of environmental variation on the habitat suitability of swordfish, Xiphias gladius, in the equatorial Atlantic Ocean. – ICES Journal of Marine Science, 70: 1000–1012. We developed a habitat suitability index (HSI) model to identify the optimal habitats of swordfish (Xiphias gladius) in the equatorial Atlantic Ocean. Environmental variables, including sea surface temperature (SST), mixed layer depth (MLD), chlorophyll-a concentrations, and sea surface height anomaly, as well as catch and effort data from Taiwanese longline fisheries, were used. The geometric mean model including all the above environmental variables was identified as the most parsimonious model for yielding HSI predictions coinciding with productive fishing grounds with high fishing effort. Swordfish mainly aggregated in the northwest region during March–May and spread southeast thereafter in response to seasonal shifts in oceanographic conditions. There was annual variation in the distribution of habitat patches, and the habitat quality was reduced in the northwest region of the equatorial Atlantic Ocean during 2005. The apparent spatial shifts in optimal habitats might be linked to reduced MLD and elevation in sea surface height, which might be related to climate variability (e.g. Niño-Southern Oscillation and/or Northern Atlantic Oscillation). Because environmental data regarding climate change scenarios are becoming readily available, we can utilize the proposed HSI models to evaluate possible changes in habitat suitability resulting from climate change and provide scientific advice for the development of management regulations.
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Zhang, Peng, Lu Cai, Zhi Yang, Xiaojuan Chen, Ye Qiao, and Jianbo Chang. "Evaluation of fish habitat suitability using a coupled ecohydraulic model: Habitat model selection and prediction." River Research and Applications 34, no. 8 (August 29, 2018): 937–47. http://dx.doi.org/10.1002/rra.3339.
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Stuart, Courtney E., Lisa M. Wedding, Simon J. Pittman, and Stephanie J. Green. "Habitat Suitability Modeling to Inform Seascape Connectivity Conservation and Management." Diversity 13, no. 10 (September 26, 2021): 465. http://dx.doi.org/10.3390/d13100465.
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Coastal habitats have experienced significant degradation and fragmentation in recent decades under the strain of interacting ecosystem stressors. To maintain biodiversity and ecosystem functioning, coastal managers and restoration practitioners face the urgent tasks of identifying priority areas for protection and developing innovative, scalable approaches to habitat restoration. Facilitating these efforts are models of seascape connectivity, which represent ecological linkages across heterogeneous marine environments by predicting species-specific dispersal between suitable habitat patches. However, defining the suitable habitat patches and migratory pathways required to construct ecologically realistic connectivity models remains challenging. Focusing on two reef-associated fish species of the Florida Keys, United States of America (USA), we compared two methods for constructing species- and life stage-specific spatial models of habitat suitability—penalized logistic regression and maximum entropy (MaxEnt). The goal of the model comparison was to identify the modeling algorithm that produced the most realistic and detailed products for use in subsequent connectivity assessments. Regardless of species, MaxEnt’s ability to distinguish between suitable and unsuitable locations exceeded that of the penalized regressions. Furthermore, MaxEnt’s habitat suitability predictions more closely aligned with the known ecology of the study species, revealing the environmental conditions and spatial patterns that best support each species across the seascape, with implications for predicting connectivity pathways and the distribution of key ecological processes. Our research demonstrates MaxEnt’s promise as a scalable, species-specific, and spatially explicit tool for informing models of seascape connectivity and guiding coastal conservation efforts.
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Pěknicová, J., D. Petrus, and K. Berchová-Bímová. "Application Natura 2000 Data For The Invasive Plants Spread Prediction." Scientia Agriculturae Bohemica 46, no. 4 (December 1, 2015): 159–66. http://dx.doi.org/10.1515/sab-2015-0031.
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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.
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Balčiauskas, Linas, Jack Wierzchowski, Andrius Kučas, and Laima Balčiauskienė. "Habitat Suitability Based Models for Ungulate Roadkill Prognosis." Animals 10, no. 8 (August 4, 2020): 1345. http://dx.doi.org/10.3390/ani10081345.
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Roads do not only have a detrimental effect on nature (fragmenting habitats, isolating populations and threatening biodiversity), but the increasing numbers of wildlife-vehicle collisions are also a direct threat to humans and property. Therefore, mitigation measures should be placed with respect to animal distribution and movements across the roads. We simulated red deer, roe deer and wild boar movements in Lithuania, focusing on the two main highways A1 and A2. Using regional habitat suitability and linkage models, we calculated movement pathways and the most probable crossing zones in 2009. The prognostic value of these models was tested by comparing the pathway predictions to the real roadkill and roadkill cluster locations in 2002–2009 and 2010–2017. Across both periods and on both highways, the roe deer roadkill locations were significantly closer to the model-predicted pathways than to randomly selected points. The prediction of roadkill locations was also good for wild boar. The roe deer roadkill clusters and multi-species clusters were significantly better represented by the model than by random distribution. On both highways, the biggest differences in distance from the predicted locations were near big cities. We recommended wildlife movement models as an additional tool for planning wildlife-vehicle collision mitigation measures and we advise measures for increasing their predicting power.
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Zhang, Jingjie, Feng Jiang, Zhenyuan Cai, Yunchuan Dai, Daoxin Liu, Pengfei Song, Yuansheng Hou, Hongmei Gao, and Tongzuo Zhang. "Resistance-Based Connectivity Model to Construct Corridors of the Przewalski’s Gazelle (Procapra Przewalskii) in Fragmented Landscape." Sustainability 13, no. 4 (February 4, 2021): 1656. http://dx.doi.org/10.3390/su13041656.
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Habitat connectivity is indispensable for the survival of species that occupy a small habitat area and have isolated habitat patches from each other. At present, the development of human economy squeezes the living space of wildlife and interferes and hinders the dispersal of species. The Przewalski’s gazelle (Procapra przewalskii) is one of the most endangered ungulates, which has experienced a significant reduction in population and severe habitat shrinkage. Although the population of this species has recovered to a certain extent, human infrastructure severely hinders the gene flow between several patches of this species. Therefore, we used the maximum entropy (MaxEnt) model to simulate the habitat suitability of the Przewalski’s gazelle. In addition, we combined habitat suitability and ecological characteristics of the species to obtain eight habitat patches. Finally, we used the least-cost path (LCP) and circuit theory based on the resistance model to simulate the landscape network of this species. The results showed that habitat patches and connectivity in the east of the Qinghai Lake were crucial to the communication between populations of the Przewalski gazelle, and our study provided important reference for the distribution of important habitats and the construction of corridor between patches. Our study aimed to provide habitat networks and maintain landscape connectivity for achieving the fundamental goal of protecting and revitalizing populations of the Przewalski’s gazelle.
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Haxton, Tim J., C. Scott Findlay, and R. W. Threader. "Predictive Value of a Lake Sturgeon Habitat Suitability Model." North American Journal of Fisheries Management 28, no. 5 (October 2008): 1373–83. http://dx.doi.org/10.1577/m07-146.1.
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Albayrak, Tamer, Ali Erdogğan, and Mehmet Ziya Firat. "A model of habitat suitability for Krueper's NuthatchSitta krueperi." Bird Study 58, no. 1 (February 2011): 50–56. http://dx.doi.org/10.1080/00063657.2010.512953.
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Sutomo, R. Iryadi, and F. Kurniawati. "Habitat suitability model of Agarwood in a changing climate." IOP Conference Series: Earth and Environmental Science 724, no. 1 (April 1, 2021): 012022. http://dx.doi.org/10.1088/1755-1315/724/1/012022.
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Mbuh, Mbongowo J., and Neil Vruno. "Habitat Suitability Analysis for Mountain Lions (Puma Concolor) Recolonization/ Reintroduction in Minnesota." European Journal of Ecology 4, no. 2 (December 31, 2018): 28–40. http://dx.doi.org/10.2478/eje-2018-0013.
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Abstract The mountain lion range once extended throughout the state of Minnesota. The breeding population has been greatly reduced with time, new roads, and timber harvesting, which have broken large tracts of contiguous forest into isolated patches that are too small and no longer suitable for the breeding mountain lion population. The objective of this study is to use suitability analysis to determine the most suitable habitat to conserve mountain lion populations threatened by habitat fragmentation. To attain our objective, we created three sub models that contribute to the overarching goal of the suitability model. A habitat sub model was developed for finding the best habitat, a food sub model for access to the maximum amount of food needed, and a security sub model focusing on the distance from houses, roads, and urban development. Using the Weighted Sum tool, the three sub models were combined to produce a suitability surface based on the trade-off of the preferences of the goals represented by each sub model. Our suitability model shows large areas of high-quality mountain lion habitat in the northern and north-eastern sections of the state. These areas contain favourable locations for mountain lion habitat, such as forested land cover, low-density populations, steep slopes, short distances to streams, and area unimpeded by major roads. The southern and western parts of the state are characterized by lower slopes, more agricultural land, grassland, developed land, and higher population density, which results in lower quality habitat. The twin cities have the worst mountain lion habitat.
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Rahimian Boogar, Abdolrahman, Hassan Salehi, Hamid Reza Pourghasemi, and Thomas Blaschke. "Predicting Habitat Suitability and Conserving Juniperus spp. Habitat Using SVM and Maximum Entropy Machine Learning Techniques." Water 11, no. 10 (September 30, 2019): 2049. http://dx.doi.org/10.3390/w11102049.
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Support vector machine (SVM) and maximum entropy (MaxEnt) machine learning techniques are well suited to model the habitat suitability of species. In this study, SVM and MaxEnt models were developed to predict the habitat suitability of Juniperus spp. in the Southern Zagros Mountains of Iran. In recent decades, drought extension and climate alteration have led to extensive changes in the geographical occurrence of this species and its growth and regeneration are extremely limited in this area. This study evaluated the habitat suitability of Juniperus through spatial modeling and predicts appropriate regions for future cultivation and resource conservation. We modeled the natural habitat of Juniperus for an area of 700 ha in Sepidan Area in the Fars province using (1) data regarding the presence of the species (295 samples) collected through field surveys and GPS, (2) habitat soil information and indices derived from 60 soil samples collected in the study area, and (3) climatic and topographic datasets collected from various sources. In total, 15 conditioning factors were used for this spatial modeling approach. Receiver operator characteristic (ROC) curves were applied to estimate the accuracy of the habitat suitability models produced by the SVM and MaxEnt techniques. Results indicated logical and similar area under the curve (AUC)-ROC values for the SVM (0.735) and MaxEnt (0.728) models. Both the SVM and MaxEnt methods revealed a significant relationship between the Juniperus spp. distribution and conditioning factors. Environmental factors played a vital role in evaluating the presence of Juniperus sp. as Max and Min temperatures and annual mean rainfall were the three most important factors for habitat suitability in the study area. Finally, an area with high and very high suitability for the future cultivation of Juniperus sp. and for landscape conservation was suggested based on the SVM model.
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Meißner, Karin, and Alexander Darr. "Distribution of Magelona species (Polychaeta: Magelonidae) in the German Bight (North Sea): a modeling approach." Zoosymposia 2, no. 1 (August 31, 2009): 567–86. http://dx.doi.org/10.11646/zoosymposia.2.1.39.
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The aim of the present study was the development of species-habitat models for four Magelona species (Polychaeta: Magelonidae) found in the German Bight in the SE North Sea. Analyses were based on field data and data obtained from reexamination of material deposited in museum collections. In addition, data on environmental variables were retrieved from the sediment map by Figge (1981) and from long-term monitoring data sets. The statistical modeling technique applied was multivariate adaptive regression splines (MARS). Predictive accuracy measures were calculated for each model. The candidate model with highest discriminatory power was selected for predictive mapping. Models with excellent predictive performance were developed for Magelona johnstoni, M. filiformis and M. alleni based on the analyzed set of environmental predictors. In each of the developed habitat models the most important predictor was a sediment parameter, either median grain size diameter (M. johnstoni) or mud content (M. alleni, M. filiformis). Salinity and water depth were also of importance. Model predictions were aimed to allow evaluation of habitat suitability for the investigated species in the German Bight. According to our results suitable habitats for M. johnstoni are numerous and a wide distribution of this species could be expected. Habitat suitability for M. filiformis in the German Bight was suggested to be high in areas with mud contents below 10 % at water depths between 25 and 35 m. The M. alleni habitat model indicated the presence of suitable habitats where sands with elevated mud contents are present and where water depths exceed 30 m.
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Ksiksi, Taoufik Saleh, Remya K., Mohamed T. Mousa, Shima K. Al-Badi, Salama K. Al Kaabi, Shamsa M. Alameemi, Sanad M. Fereaa, and Fatima E. Hassan. "Climate change-induced species distribution modeling in hyper-arid ecosystems." F1000Research 8 (June 27, 2019): 978. http://dx.doi.org/10.12688/f1000research.19540.1.
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Background: The impact of climate change on selected plant species from the hyper-arid landscape of United Arab Emirates (UAE) was assessed through modeling of their habitat suitability and distribution. Calotropis procera, Prosopis cineraria and Ziziphus spina-christi were used for this study. The specific objectives of this study were to identify the current and future (for 2050s and 2070s) suitable habitats distribution using MaxEnt, an Ecological Envelope Model. Methods: The adopted method consists of extraction of current and future bioclimatic variables together with their land use cover and elevation for the study area. MaxEnt species distribution model was then used to simulate the distribution of the selected species. The projections are simulated for the current date, the 2050s and 2070s using Community Climate System Model version 4 with representative concentration pathway RCP4.5. Results: The current distribution model of all three species evolved with a high suitable habitat towards the north eastern part of the country. For C. procera, an area of 1775 km2 is modeled under highly suitable habitat for the current year, while it is expected to increase for both 2050s and 2070s. The current high suitability of P. cinararia was around an area of 1335 km2 and the future projection revealed an increase of high suitability habitats. Z. spina-christi showed a potential area of 5083 km2 under high suitability and it might increase in the future. Conclusions: Precipitation of coldest quarter (BIO19) had the maximum contribution for all the three species under investigation.
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Favata, Carl Anthony, David R. Christensen, Robert Thompson, Kelly Anne McKeown, and Jennifer A. Hanselman. "Evaluation of a Modified Habitat Suitability Index Model for Eastern Brook Trout: Implications for Efficient Habitat Assessment." Journal of Student Research 4, no. 1 (February 1, 2015): 90–98. http://dx.doi.org/10.47611/jsr.v4i1.195.
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Species-specific habitat suitability models have potential for use in restoration efforts, but their efficiency still remains in question. As eastern brook trout, Salvelinus fontinalis, populations in New England have declined over the last few decades as a result of anthropogenic and natural impacts on critical habitat, habitat suitability models have become a common tool for conservation efforts. These models, however, have inherent flaws that prevent widespread and uniform use. To better adapt these models, the flaws must be properly addressed. Using a modified habitat suitability index (HSI) model developed for eastern brook trout, we explained the correlation between catch per unit effort (CPUE) of brook trout with designated HSI variables such as temperature, dominant substrate type, and percent riffle fines for nineteen reaches within the Westfield River watershed. CPUE was not significantly correlated with HSI outputs. A principal components analysis (PCA) was employed and revealed driving factors within the system. Four variables were shown to yield the highest explained variance over the first two axes: velocity, instream cover, percent pools, and thalweg depth. Evidence suggests that habitat assessment based around these core variables may lead to a more efficient and accurate assessment. Recommendations for improved methodologies include revised tolerance curves, a reworked index rating system, and revised model variables based on current field research. Alterations to existing models provide hope for more accurate assessment, and increased efficiency in conservation efforts.
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Vayghan, Ali Haghi, Ming-An Lee, Jinn-Shing Weng, Sandipan Mondal, Ching-Te Lin, and Yi-Chen Wang. "Multisatellite-Based Feeding Habitat Suitability Modeling of Albacore Tuna in the Southern Atlantic Ocean." Remote Sensing 12, no. 16 (August 5, 2020): 2515. http://dx.doi.org/10.3390/rs12162515.
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Decision strategies in fisheries management are often directed by the geographic distribution and habitat preferences of target species. This study used remote sensing data to identify the optimal feeding habitat of albacore tuna in the Southern Atlantic Ocean (SAO) using an empirical habitat suitability model applying longline fisheries data during 2009–2015. An arithmetic mean model with sea surface temperature (SST) and sea surface chlorophyll-a concentration (SSC) was determined to be suitable for defining the albacore habitat in the SAO. The optimal ranges of SST and SSC for the habitat were approximately 16.5 °C–19.5 °C and 0.11–0.33 mg/m3, respectively. The study revealed a considerable positive trend between the suitable habitat area and standardized catch per unit effort (r = 0.97; p < 0.05); due to the west-to-east and northward development of the suitable habitat, albacore schools moved to the northeast of the SAO, thus increasing catch probability in April to August in that region. Overall, the frontal structure of SST and SSC plays an essential role in the formation of potential albacore habitats in the SAO. Our findings could contribute to the establishment of regional ecosystem-based fisheries management in the SAO.
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Bowman, Jeff, and Jean-François Robitaille. "An assessment of expert-based marten habitat models used for forest management in Ontario." Forestry Chronicle 81, no. 6 (November 1, 2005): 801–7. http://dx.doi.org/10.5558/tfc81801-6.
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We used marten snow tracking data and a previously developed empirical habitat model from northeastern Ontario to validate a number of expert-based, non-spatial marten habitat models. In particular, we tested the non-spatial Ontario Wildlife Habitat Analysis Model, the Boreal East Habitat Suitability Matrix (including tests of both standard forest units and development stages), and Allen's (1982) HSI model. Marten habitat use as measured by tracks in the snow was consistent with predictions of all the expert-based models, suggesting that these models correctly characterized the stand-level forest cover selected by marten in winter. Suitability ranks for individual stands derived from standard forest units and development stages also were consistent with their use by marten. The empirical model was consistent with the expert-based models in that it considered suitable forest stands to be those with tall trees dominated by spruce (Picea spp.) and balsam fir (Abies balsamea) trees, with a large amount of coarse woody debris, and high canopy closure. Our findings suggested that the expert-based models were able to characterize stand structure used by marten despite some of the models using only inputs available from stand inventories. This was accomplished because stand structural elements such as coarse woody debris were integrated into OWHAM and HSM indirectly, through relationships with stand age and species composition. Key words: boreal forest, forest inventory, habitat, habitat suitability, guidelines, Forest Ecosystem Classification, landscape, Martes americana, resource selection, snow tracking, spatial autocorrelation, stand structure
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Muhamad, M. A. H., and R. Che Hasan. "SEAGRASS HABITAT SUITABILITY MAP AT MERAMBONG SHOAL, JOHOR: A PRELIMINARY STUDY USING MULTIBEAM ECHOSOUNDER AND MAXENT MODELLING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 463–70. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-463-2019.
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Abstract. In recent years, there has been an increasing interest to use high-resolution multibeam dataset and Species Distribution Modelling (SDM) for seagrass habitat suitability model. This requires a specific variable derived from multibeam data and in-situ seagrass occurrence samples. The purpose of this study was (1) to derive variables from multibeam bathymetry data to be used in seagrass habitat suitability model, (2) to produce seagrass habitat suitability model using Maximum Entropy (MaxEnt), and (3) to quantify the contribution of each variable for predicting seagrass habitat suitability map. The study area was located at Merambong Shoal, covering an area of 0.04 km2, situated along Johor Strait. First, twelve (12) variables were derived from bathymetry data collected from multibeam echosounder using Benthic Terrain Modeller (BTM) tool. Secondly, all variables and seagrass occurrence samples were integrated in MaxEnt to produce seagrass habitat suitability map. The results showed that the Area Under Curve (AUC) values based on training and test data were 0.88 and 0.65, respectively. The northwest region of survey area indicated higher habitat suitability of seagrass, while the southeast region of survey area indicated lower suitability. Bathymetry mean found to be the most contributed variables among others. The spatial distribution of seagrass from modelling technique agreed with the previous studies and they are found to be distributed at depths ranging from 2.2 to 3.4 meters whilst less suitable with increasing of water depth. This study concludes that seagrass habitat suitability map with high-resolution pixel size (0.5 meter) can be produced at Merambong Shoal using acoustic data from multibeam echosounder coupled with MaxEnt and underwater video observations.
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Holmes, Stephen B., Lisa A. Venier, Brian J. Naylor, and J. Ryan Zimmerling. "A test of Ontario's Habitat Suitability Matrix as a forest management planning tool for forest birds." Forestry Chronicle 83, no. 4 (August 1, 2007): 570–79. http://dx.doi.org/10.5558/tfc83570-4.
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We used point-count data collected as part of Bird Studies Canada's Boreal Forest Bird Program to validate habitat suitability models for 22 forest bird species in Ontario's Habitat Suitability Matrix. We found that many of the species'models performed relatively poorly in discriminating between occupied and unoccupied sites, primarily due to the high error of commission rates (false positive predictions). Since species presence and abundance were assessed by single, five minute point counts, insufficient sampling was at least partly responsible for some of the observed over-prediction. Results suggested that model parameters for at least nine of the species tested (hairy woodpecker [Picoides villosus], blueheaded vireo [Vireo solitarius], red-eyed vireo [Vireo olivaceus], red-breasted nuthatch [Sitta canadensis], Swainson's thrush [Catharus ustulatus], hermit thrush [Catharus guttatus], Tennessee warbler [Vermivora peregrina], Blackburnian warbler [Dendroica fusca] and dark-eyed junco [Junco hyemalis]) should be reviewed to improve the predictive capability of the models and to ensure appropriate consideration of the habitat needs of these species during forest management planning. Key words: boreal forest, forest birds, discrimination capacity, habitat models, habitat suitability matrix, model accuracy, model validation, relative operating characteristic curve, ROC
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Metsaranta, Juha M., Frank F. Mallory, and Dale W. Cross. "Vegetation characteristics of forest stands used by woodland caribou and those disturbed by fire or logging in Manitoba." Rangifer 23, no. 5 (April 1, 2003): 255. http://dx.doi.org/10.7557/2.23.5.1709.
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This study examined woodland caribou (Rangifer tarandus caribou) in an area known as the Kississing-Naosap caribou range in west central Manitoba. The vegetation characteristics of areas used by caribou and areas disturbed by fire or logging were measured in order to develop a model to estimate habitat quality from parameters collected during stan¬dard resource inventories. There was evidence that habitat index values calculated using a visual score-sheet index could be used as the basis to relate parameters commonly collected during resource inventories to habitat suitability. Use of this model to select long and short-term leave areas during forest management planning could potentially mitigate some of the negative impacts of forest harvesting. Abundance of arboreal lichen and wind-fallen trees were important predictor variables in the suitability model, but their inclusion did not explain more variance in habitat suitability than models that did not include them. Extreme post-fire deadfall abundance may play a role in predator-prey dynamics by creating habitat that is equally unsuitable for all ungulates, and thus keeping both moose and caribou densities low.
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SHIMBO, Yumi, Katunori YAMAKI, and Masahiro TANAKA. "Development of Habitat Suitability Index Model for Corals in ports." Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering) 69, no. 2 (2013): I_1231—I_1235. http://dx.doi.org/10.2208/kaigan.69.i_1231.
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Reiley, Bryan M., James C. Bednarz, and Jeremy D. Brown. "A test of the Swainson's warbler habitat suitability index model." Wildlife Society Bulletin 38, no. 2 (March 13, 2014): 297–304. http://dx.doi.org/10.1002/wsb.414.
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Zeigenfuss, Linda C., Francis J. Singer, and Michelle A. Gudorf. "Test of a Modified Habitat Suitability Model for Bighorn Sheep." Restoration Ecology 8, no. 4S (December 2000): 38–46. http://dx.doi.org/10.1046/j.1526-100x.2000.80064.x.
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Rousseau, Raphaël, Guy McGrath, Barry J. McMahon, and Sophie O. Vanwambeke. "Multi-criteria Decision Analysis to Model Ixodes ricinus Habitat Suitability." EcoHealth 14, no. 3 (June 19, 2017): 591–602. http://dx.doi.org/10.1007/s10393-017-1247-8.
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Sarma, Pranjit Kumar, B. S. Mipun, Bibhab Kumar Talukdar, Rajeev Kumar, and Ajit Kumar Basumatary. "Evaluation of Habitat Suitability for Rhino (Rhinoceros unicornis) in Orang National Park Using Geo-Spatial Tools." ISRN Ecology 2011 (May 23, 2011): 1–9. http://dx.doi.org/10.5402/2011/498258.
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Orang National Park (Orang NP) is one of the important conservation areas in the Brahmaputra valley within North East India biogeographic zone covering an area of 78.8 km2. It is one of the prime habitats of one horned rhino (Rhinoceros unicornis) in its distribution range in south Asia. Satellite imagery of November 2008 was used to evaluate the rhino habitat pattern in the park. A habitat suitability model for one horned rhino was prepared using primary and secondary sources. Result indicates that out of total geographical area of the park 25.85% is covered by woodland. About 26.06% is covered by wet alluvial grassland and 17.97% is covered by dry savannah grassland. Similarly degraded grassland is covering 15.23% and eastern seasonal swamp forest is covering 1.72% of the park. About 8.22% of the park is covered by water body and 6.83% is covered by sandy area. The habitat suitability model for rhino shows that 25.13% of the park is most suitable habitat for rhino, 13.62% is moderately suitable and 61.23% is less suitable habitat for rhino in the park. This information will help the park managers to conserve rhino and its habitat in Orang NP.
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Wu, Wen, Yuehui Li, and Yuanman Hu. "Simulation of potential habitat overlap between red deer (Cervus elaphus) and roe deer (Capreolus capreolus) in northeastern China." PeerJ 4 (March 21, 2016): e1756. http://dx.doi.org/10.7717/peerj.1756.
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Background.Understanding species distribution, especially areas of overlapping habitat between sympatric species, is essential for informing conservation through natural habitat protection. New protection strategies should simultaneously consider conservation efforts for multiple species that exist within the same landscape, which requires studies that include habitat overlap analysis.Methods.We estimated the potential habitat of cervids, which are typical ungulates in northern China, using the present locations of red deer (Cervus elaphus;N= 90) and roe deer (Capreolus capreolus;N= 106) in a Maximum Entropy (MaxEnt) model. Our study area was a human-dominated landscape in the Tieli Forestry Bureau located at the southern slope of the Lesser Xing’an Mountains. We grouped 17 environmental predictor variables into five predictor classes (terrain, habitat accessibility, land cover, vegetation feature, and interference), which were used to build habitat suitability models.Results.Habitat accessibility and human interferences were found to have the strongest influence on habitat suitability among the five variable classes. Among the environmental factors, distance to farmland (26.8%), distance to bush-grass land (14.6%), elevation (13.5%), and distance to water source (12.2%) were most important for red deer, distance to farmland (22.9%), distance to settlement (21.4%), elevation (11.6%), and coverage of shrub-grass (8%) were most important for roe deer. Model accuracy was high for both species (mean area under the curve (AUC) = 0.936 for red deer and 0.924 for roe deer). The overlapping habitat comprised 89.93 km2within the study area, which occupied 94% of potentially suitable habitat for red deer and 27% for roe deer.Conclusions.In terms of habitat suitability, roe deer showed greater selectivity than red deer. The overlapping habitat was mostly located in the eastern mountains. The southwestern plain was not a suitable habitat for deer because it was close to Tieli City. Regarding management measures, we suggest that priority protection should be given to the potential areas of overlapping deer habitats found in this study.
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Lamouroux, Nicolas, and Ian G. Jowett. "Generalized instream habitat models." Canadian Journal of Fisheries and Aquatic Sciences 62, no. 1 (January 1, 2005): 7–14. http://dx.doi.org/10.1139/f04-163.
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Conventional instream habitat models (e.g., the physical habitat simulation system) predict the impact of regulation on the habitats of freshwater taxa. They link a hydraulic model with microhabitat-suitability models for taxa to predict habitat values at various discharge rates. Their use requires considerable field effort and experience. Recent analyses performed in France suggested that comparable results could be achieved using simplified hydraulic data. We tested this approach for 99 stream reaches and nine aquatic taxa in New Zealand. The resulting generalized habitat models predict habitat values similar to those predicted by conventional models from simplified hydraulic data (depthdischarge and widthdischarge relationships, average particle size, and mean annual discharge). As in France, within-reach changes in habitat values were linked to the specific discharge of reaches, while between-reach changes depended mainly on the Froude number at mean annual discharge. The generalized models perform well outside their calibration range. Models previously developed in France perform well in New Zealand. Such generalized models contribute to identifying the key hydraulic variables for freshwater taxa and should facilitate habitat studies worldwide.
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Shih, Shang-Shu. "Spatial Habitat Suitability Models of Mangroves with Kandelia obovata." Forests 11, no. 4 (April 23, 2020): 477. http://dx.doi.org/10.3390/f11040477.
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Mangrove forests provide important estuarine ecosystem services but are threatened by rising sea levels and anthropogenic impacts. Understanding the habitat characteristics required for mangrove growth is significant for mangrove restoration and integrated management. This study aims to build spatial habitat suitability index (HSI) models for Kandelia obovata mangrove trees. Biological and habitat-related environmental data were collected in the Wazwei and Guandu wetlands in northern Taiwan. We adopted inundation frequency, soil sorting coefficient, and water salinity as the key environmental factors to build HSI models. The dependent variable of these environmental factors was the mangrove biomass per unit area. Significant differences were found for the mangrove biomass on different substrata and shore elevations. The tidal creek had the lowest elevation, and mangrove areas were found at the highest elevations. The oxidization level of the substrate under mangrove forests was high, indicating that the root system of mangroves could carry oxygen into the soil and result in oxidation. Human activities were found to lead to the reduced growth conditions of mangroves. The validation of the HSI model, considering the inundation frequency and soil sorting coefficient, proved to be reliable, with an accuracy ranging from 78% to 90%. A better simulation was found after revising the model by incorporating the factor of water salinity. The model forecast of the mangrove responses to the sea-level rise indicated an increase in the inundation frequency and thus an induced shift and shrinkage of the mangrove area. The increased HSI values of the bare mudflat area demonstrate an option for the potential restoration of mangrove trees. Given the findings of this study, we concluded that mangroves could spread from estuaries to upstream areas due to rising sea levels and might be limited by humanmade impacts. Restoring degraded floodplains is suggested for mangrove habitat rehabilitation.
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Ceola, S., and A. Pugliese. "Regional prediction of basin-scale brown trout habitat suitability." Proceedings of the International Association of Hydrological Sciences 364 (September 16, 2014): 26–31. http://dx.doi.org/10.5194/piahs-364-26-2014.
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Abstract. In this study we propose a novel method for the estimation of ecological indices describing the habitat suitability of brown trout (Salmo trutta). Traditional hydrological tools are coupled with an innovative regional geostatistical technique, aiming at the prediction of the brown trout habitat suitability index where partial or totally ungauged conditions occur. Several methods for the assessment of ecological indices are already proposed in the scientific literature, but the possibility of exploiting a geostatistical prediction model, such as Topological Kriging, has never been investigated before. In order to develop a regional habitat suitability model we use the habitat suitability curve, obtained from measured data of brown trout adult individuals collected in several river basins across the USA. The Top-kriging prediction model is then employed to assess the spatial correlation between upstream and downstream habitat suitability indices. The study area is the Metauro River basin, located in the central part of Italy (Marche region), for which both water depth and streamflow data were collected. The present analysis focuses on discharge values corresponding to the 0.1-, 0.5-, 0.9-empirical quantiles derived from flow-duration curves available for seven gauging stations located within the study area, for which three different suitability indices (i.e. ψ10, ψ50 and ψ90) are evaluated. The results of this preliminary analysis are encouraging showing Nash-Sutcliffe efficiencies equal to 0.52, 0.65, and 0.69, respectively.
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Basile, Marco, Francesco Valerio, Rosario Balestrieri, Mario Posillico, Rodolfo Bucci, Tiziana Altea, Bruno De Cinti, and Giorgio Matteucci. "Patchiness of forest landscape can predict species distribution better than abundance: the case of a forest-dwelling passerine, the short-toed treecreeper, in central Italy." PeerJ 4 (September 8, 2016): e2398. http://dx.doi.org/10.7717/peerj.2398.
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Environmental heterogeneity affects not only the distribution of a species but also its local abundance. High heterogeneity due to habitat alteration and fragmentation can influence the realized niche of a species, lowering habitat suitability as well as reducing local abundance. We investigate whether a relationship exists between habitat suitability and abundance and whether both are affected by fragmentation. Our aim was to assess the predictive power of such a relationship to derive advice for environmental management. As a model species we used a forest specialist, the short-toed treecreeper (Family: Certhiidae;Certhia brachydactylaBrehm, 1820), and sampled it in central Italy. Species distribution was modelled as a function of forest structure, productivity and fragmentation, while abundance was directly estimated in two central Italian forest stands. Different algorithms were implemented to model species distribution, employing 170 occurrence points provided mostly by the MITO2000 database: an artificial neural network, classification tree analysis, flexible discriminant analysis, generalized boosting models, generalized linear models, multivariate additive regression splines, maximum entropy and random forests. Abundance was estimated also considering detectability, through N-mixture models. Differences between forest stands in both abundance and habitat suitability were assessed as well as the existence of a relationship. Simpler algorithms resulted in higher goodness of fit than complex ones. Fragmentation was highly influential in determining potential distribution. Local abundance and habitat suitability differed significantly between the two forest stands, which were also significantly different in the degree of fragmentation. Regression showed that suitability has a weak significant effect in explaining increasing value of abundance. In particular, local abundances varied both at low and high suitability values. The study lends support to the concept that the degree of fragmentation can contribute to alter not only the suitability of an area for a species, but also its abundance. Even if the relationship between suitability and abundance can be used as an early warning of habitat deterioration, its weak predictive power needs further research. However, we define relationships between a species and some landscape features (i.e., fragmentation, extensive rejuvenation of forests and tree plantations) which could be easily controlled by appropriate forest management planning to enhance environmental suitability, at least in an area possessing high conservation and biodiversity values.
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Provencher, Louis, Kevin Badik, Tanya Anderson, Joel Tuhy, Dan Fletcher, Elaine York, and Sarah Byer. "Landscape Conservation Forecasting for Data-Poor at-Risk Species on Western Public Lands, United States." Climate 9, no. 5 (May 11, 2021): 79. http://dx.doi.org/10.3390/cli9050079.
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Managing vast federal public lands governed by multiple land use policies creates challenges when demographic data on at-risk species are lacking. The U.S. Bureau of Land Management Cedar City Field Office used this project in the Black Mountains (Utah) to inform vegetation management supporting at-risk greater sage-grouse and Utah prairie dog planning. Ecological systems were mapped from satellite remote sensing imagery and used to model species habitat suitability under two levels of management activity (custodial, preferred) and climate scenarios for historic and two global circulation models. Spatial state-and-transition models of ecological systems were simulated for all six scenarios up to 60 years while coupled with expert-developed habitat suitability indices. All ecological systems are at least moderately departed from reference conditions in 2012, whereas habitat suitability was 50.5% and 48.4% for sage-grouse and prairie dog, respectively. Management actions replaced non-native annual grasslands with perennial grasses, removed conifers, and controlled exotic forbs. The drier climate most affected ecological departure and prairie dog habitat suitability at 30 years only. Different climates influenced spatial patterns of sage-grouse habitat suitability, but nonspatial values were unchanged. Climate impacts on fire, vegetation succession, and restoration explain many results. Front-loading restoration is predicted to benefit under future drier climate.
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Troy, Jeff R., Nick D. Holmes, Joseph A. Veech, André F. Raine, and M. Clay Green. "Habitat Suitability Modeling for the Newell's Shearwater on Kauai." Journal of Fish and Wildlife Management 5, no. 2 (September 1, 2014): 315–29. http://dx.doi.org/10.3996/112013-jfwm-074.
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Abstract The Newell's shearwater, or ‘A’o Puffinus newelli, is endemic to the main islands of the Hawaiian Archipelago and is listed as endangered on the International Union for Conservation of Nature Red List and as threatened under the U.S. Endangered Species Act. Using abiotic and biotic environmental variables, we developed a terrestrial habitat suitability model for this species on Kauai to predict habitat that could be suitable in the absence of anthropogenic threats. In addition, we developed a habitat/threat-isolation index incorporating information from our suitability model to identify regions of structurally suitable habitat with less exposure to certain anthropogenic threats (relative to other portions of the island). The habitat suitability model suggests that slope, density of rock fragments within the soil, and native vegetation cover are important factors associated with the current known distribution of the Newell's shearwater on Kauai, and that a moderate portion of the sloped interior terrain of Kauai could potentially be suitable nesting habitat for this species. The habitat/threat-isolation index identified the mountains on the north-central portion of the island as structurally suitable habitat most isolated from a combination of major anthropogenic disturbances (relative to other portions of the island). Much of this region, however, is privately owned and not designated as an official reserve, which could indicate a need for increased conservation action in this region in the future. This information is important for conservation biologists and private landowners because expanding efforts to control nonnative predators, as well as management of additional lands as reserves, may be necessary for the protection and preservation of the Newell's shearwater.
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Jarnevich, Catherine S., Pairsa N. Belamaric, Kent Fricke, Mike Houts, Liza Rossi, Grant Beauprez, Brett Cooper, and Russell Martin. "Challenges in updating habitat suitability models: An example with the lesser prairie-chicken." PLOS ONE 16, no. 9 (September 20, 2021): e0256633. http://dx.doi.org/10.1371/journal.pone.0256633.
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Habitat loss from land-use change is one of the top causes of declines in wildlife species of concern. As such, it is critical to assess and reassess habitat suitability as land cover and anthropogenic features change for both monitoring and developing current information to inform management decisions. However, there are obstacles that must be overcome to develop consistent assessments through time. A range-wide lek habitat suitability model for the lesser prairie-chicken (Tympanuchus pallidicinctus), currently under review by the U. S. Fish and Wildlife Service for potential listing under the Endangered Species Act, was published in 2016. This model was based on lek data from 2002 to 2012, land cover data ranging from 2001 to 2013, and anthropogenic features from circa 2011, and has been used to help guide lesser prairie-chicken management and anthropogenic development actions. We created a second iteration model based on new lek surveys (2015 to 2019) and updated predictors (2016 land cover and cleaned/updated anthropogenic data) to evaluate changes in lek suitability and to quantify current range-wide habitat suitability. Only three of 11 predictor variables were directly comparable between the iterations, making it difficult to directly assess what predicted changes resulted from changes in model inputs versus actual landscape change. The second iteration model showed a similar positive relationship with land cover and negative relationship with anthropogenic features to the first iteration, but exhibited more variation among candidate models. Range-wide, more suitable habitat was predicted in the second iteration. The Shinnery Oak Ecoregion, however, exhibited a loss in predicted suitable habitat that could be due to predictor source changes. Iterated models such as this are important to ensure current information is being used in conservation and development decisions.