A multi‐data ensemble approach for predicting woodland type distribution: Oak woodland in Britain

Ray, Duncan; Marchi, Maurizio; Rattey, Andrew; Broome, Alice

doi:10.1002/ece3.7752

Cited by 7 publications

(4 citation statements)

References 54 publications

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“…The uncertainty of a single distribution model can be reduced to some extent by building an EM [31,64]. The "Biomod2" software package can not only predict the current distribution of L. principis-rupprechtii in an ensemble way but also predict the potential distribution area under future climate scenarios [35,65]. In this study, based on the "Biomod2" software package, 10 single species distribution models and EM were constructed using the latest CMIP6 climate data, and the results were evaluated by KAPPA, ROC, and TSS.…”

Section: Ensemble Model Evaluationmentioning

confidence: 99%

“…The ensemble model (EM) is considered to be an effective method to evaluate the potential distribution of species at a large spatial scale [33], and can effectively solve the uncertainty caused by a single model [34]. The EM has been used to predict the distribution of forests [35,36] and other species [37], and good prediction accuracy has been obtained.…”

Section: Introductionmentioning

confidence: 99%

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Predicting the Potential Suitable Distribution of Larix principis-rupprechtii Mayr under Climate Change Scenarios

Cheng

Wang

Zhang

et al. 2022

Forests

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Larix principis-rupprechtii Mayr (larch) is a native conifer species in North China, and also a major silvicultural and timber species in the region. Climate change has led to a change in its suitable distribution area. However, the dominant factors affecting changes in its suitable distribution and migration trends are not clear. In this study, based on forest resource inventory data and bioclimatic data in Hebei and Shanxi provinces, China, we built an ensemble model based on seven algorithms to simulate the larch’s potential suitable distribution areas under three shared socioeconomic pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the current and future (2021–2040, 2041–2060 and 2080–2100). The results revealed that: (1) ensemble models significantly improved the predictive accuracy (ROC = 0.95, TSS = 0.81, KAPPA = 0.65); (2) the current potentially suitable distribution area was concentrated in the Bashang Plateau and the northwestern mountain range of the study area. Among them, 12.38% were highly suitable distribution areas, 12.67% were moderately suitable distribution areas, and 12.01% were lowly suitable distribution areas; (3) the main climatic factors affecting larch distribution were mean temperature of driest quarter, mean diurnal range, precipitation of warmest quarter, and temperature annual range; (4) under different future climate scenarios, the contraction of the suitable distribution area of larch increased significantly with increasing SSP radiation intensity. By 2100, the suitable distribution area of larch was expected to decrease by 26.5% under SSP1-2.6, 57.9% under SSP2-4.5, and 75.7% under SSP5-8.5 scenarios; (5) from 2021 to 2100, the different suitable distribution areas of larch showed a trend of migration to the northeast. Under the SSP5-8.5 scenario, the migration distance of different suitable distribution areas was the largest, in which the high suitable distribution area migrated 232.60 km, the middle suitable distribution area migrated 206.75 km, and the low suitable distribution area migrated 163.43 km. The results revealed the impact of climate change on the larch distribution, which provided a scientific basis for making forest management decisions.

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Section: Ensemble Model Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predicting the Potential Suitable Distribution of Larix principis-rupprechtii Mayr under Climate Change Scenarios

Cheng

Wang

Zhang

et al. 2022

Forests

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“…In this study, surface range envelope strategy was used, and as a result, pseudo-absence points were randomly generated with the same number as true-presence records 26 . Then, eight commonly used algorithms were applied: GLM, RF, MaxEnt, ANN, MARS, FDA, CTA and SRE 27 . A model option in Biomod 2, each algorithm was run 15 times, for a total of 120 runs for the eight algorithms.…”

Section: Methodsmentioning

confidence: 99%

Biomod2 modeling for predicting the potential ecological distribution of three Fritillaria species under climate change

Huang,

An,

Huang

et al. 2023

Sci Rep

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The Fritillaria species ranked as a well-known traditional medicine in China and has become rare due to excessive harvesting. To find reasonable strategy for conservation and cultivation, identification of new ecological distribution of Fritillaria species together with prediction of those responses to climate change are necessary. In terms of current occurrence records and bioclimatic variables, the suitable habitats for Fritillaria delavayi, Fritillaria taipaiensis, and Fritillaria wabuensis were predicted. In comparison with Maxent and GARP, Biomod2 obtained the best AUC, KAPPA and TSS values of larger than 0.926 and was chosen to construct model. Temperature seasonality was indicated to put the greatest influence on Fritillaria taipaiensis and Fritillaria wabuensis, while isothermality was of most importance for Fritillaria delavayi. The current suitable areas for three Fritillaria species were distributed in south-west China, accounting for approximately 17.72%, 23.06% and 20.60% of China's total area, respectively. During 2021–2100 period, the suitable habitats of F. delavayi and F. wabuensis reached the maximum under SSP585 scenario, while that of F. taipaiensis reached the maximum under SSP126 scenario. The high niche overlap among three Fritillaria species showed correlation with the chemical composition (P ≤ 0.05), while no correlation was observed between niche overlap and DNA barcodes, indicating that spatial distribution had a major influence on chemical composition in the Fritillaria species. Finally, the acquisition of species-specific habitats would contribute to decrease in habitat competition, and future conservation and cultivation of Fritillaria species.

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“…We then used two cross-validation metrics, the area under curve of the receiver operating characteristic (AUC) (Fielding and Bell 1997) and the true skill statistic (TSS) (Allouche et al 2006), to evaluate model performance (Guisan and Zimmermann 2000). We selected the two best performing models with the highest AUC and TSS values, and used a weighted average method to construct a final ensemble model (Ray et al 2021). Our hypothesis assumed that the raccoon dog population will continue to grow until it occupies most of its suitable habitat.…”

Section: Modeling Approaches 231 Modeling Habitat Suitabilitymentioning

confidence: 99%

Predicting future distributions and dispersal pathways for precautionary management of human-raccoon dog conflicts in metropolitan landscapes

Zhao

Diao

Weng

et al. 2022

Environ. Res. Lett.

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Human-wildlife conflicts in cities are becoming increasingly common worldwide and are a challenge to urban biodiversity management and landscape planning. In comparison to compensatory management, which often focuses on addressing emergency conflicts, precautionary management allows decision-makers to better allocate limited resources on prioritized areas and initiate long-term actions in advance. However, precautionary approaches have rarely been developed or applied in biodiversity conservation. Since 2020, human-raccoon dog conflicts in Shanghai, one of the largest cities in the world, have tripled in reported number due to the rapid spread of the species in the city from 70 residential districts in 2020 to 249 residential districts in 2022. Here, we use ensemble and circuit modeling to predict suitable raccoon dog habitat and identify their potential dispersal pathways to aid the development of precautionary management strategies. We find that raccoon dog distribution is positively associated with several anthropogenic factors, including residential buildings and nighttime light, which could be signs that the species’ foraging behavior has adapted to the urban environment. We find that raccoon dogs only occupy 10.1% of its suitable habitat, and thus there is a high potential for the expansion of the raccoon dog population and more frequent human-raccoon dog conflicts in the near future. We predict 60 potential dispersal pathways across Shanghai, seven of which cross densely human populated areas and are likely to trigger excessive conflicts. Based on our findings, we propose priority areas where precautionary management strategies, such as constraining stray animal feeding and wildlife-vehicle collision prevention, would potentially alleviate human-raccoon dog conflicts. We present the first study on the precautionary approach of human-wildlife conflict in China’s major cities, and provide a practical example of how comprehensive modeling approaches can be used as the foundation of precautionary management in urban landscapes.

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A multi‐data ensemble approach for predicting woodland type distribution: Oak woodland in Britain

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 7 publications

References 54 publications

Predicting the Potential Suitable Distribution of Larix principis-rupprechtii Mayr under Climate Change Scenarios

Predicting the Potential Suitable Distribution of Larix principis-rupprechtii Mayr under Climate Change Scenarios

Biomod2 modeling for predicting the potential ecological distribution of three Fritillaria species under climate change

Predicting future distributions and dispersal pathways for precautionary management of human-raccoon dog conflicts in metropolitan landscapes

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