Shifts in potential geographical distribution of <i>Pterocarya stenoptera</i> under climate change scenarios in China

Zhang, Keliang; Liu, Huina; Pan, Haolei; Shi, Wenhao; Zhao, Yi; Li, Silei; Liu, Junchi; Tao, Jun

doi:10.1002/ece3.6236

Cited by 39 publications

(42 citation statements)

References 41 publications

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“…To reduce the sampling bias of the database, and to verify the location data related to the distribution of C. camphora, field investigations were conducted by visiting 20 locations randomly selected from the database. Thereafter, to reduce overfitting to sampling bias in ecological niche models, only one point was projected within every 10 km × 10 km grid cell [5]. Ultimately, 182 non-repeating geo-referenced occurrence records were gathered in this work.…”

Section: Occurrence Records Collectionmentioning

confidence: 99%

“…Desktop GARP version 1.1.3 [32] and Maxent version 3.3.3k [20] were applied for model construction based on environmental variables and species records. The same models and procedures were also used by Zhang et al [5]. These two models were selected because they are two common niche-based modeling approaches that adopt presence-only data.…”

Section: Model Simulationmentioning

confidence: 99%

“…GARP tends to result in models with a large number of commission errors than Maxent, i.e., GARP would predict a large suitable habitat area [37]. Those high commission errors were derived from sites with a possibly appropriate habitat where the species was predicted to be present, but where presence could not be illustrated since the species were not confirmed to exist there [5]. The use of a consistent prediction allows for the identification of inconsistencies between the modeling methods.…”

Section: Model Performancementioning

confidence: 99%

“…Global climate change has changed the distribution and frequency of many species over the past several decades, and in the meantime, led to the extinction or local extirpation of many species [1,3,4]. The potential threats that may alter the frequency and distribution of some species could be addressed through predictions about the impact of climate changes on the spatial distribution of the habitat for specific species at a landscape scale [5]. Thus, obtaining high quality distribution data is crucial to setting priorities and implementing efficient protective measures.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Suitable Environments and Potential Occurrences for Cinnamomum camphora (Linn.) Presl.

Meng

Guo

et al. 2021

Forests

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Global climate change has created a major threat to biodiversity. However, little is known about the habitat and distribution characteristics of Cinnamomum camphora (Linn.) Presl., an evergreen tree growing in tropical and subtropical Asia, as well as the factors influencing its distribution. The present study employed Maxent and a GARP to establish a potential distribution model for the target species based on 182 known occurrence sites and 17 environmental variables. The results indicate that Maxent performed better than GARP. The mean diurnal temperature range, annual precipitation, mean air temperature of driest quarter and sunshine duration in growing season were important environmental factors influencing the distribution of C. camphora and contributed 40.9%, 23.0%, 10.5%, and 7.2% to the variation in the model contribution, respectively. Based on the models, the subtropical and temperate regions of Eastern China, where the species has been recorded, had a high suitability for this species. Under each climate change scenario, the potential geographical distribution shifted farther north and toward a higher elevation. The predicted spatial and temporal distribution patterns of this species can provide guidance for the development strategies for forest management and species protection.

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Section: Occurrence Records Collectionmentioning

confidence: 99%

Section: Model Simulationmentioning

confidence: 99%

Section: Model Performancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Predicting Suitable Environments and Potential Occurrences for Cinnamomum camphora (Linn.) Presl.

Meng

Guo

et al. 2021

Forests

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“…Among the many SDMs, the combination of maximum entropy (MaxEnt) model and Beijing climate center-climate system model (BCC-CSM) is very suitable for predicting the current and future distribution of Chinese species, and its prediction results are highly accurate, which has been proved in many studies on the distribution prediction of Chinese species [15]. Therefore, MaxEnt model and BCC-CSM-MR model were used in this study to predict the distribution of the four original plants of Gentianae Macrophyllae Radix.…”

Section: Gentiana Crasicaulis Duthie Ex Burk Gentiana Daurica Fischmentioning

confidence: 99%

Predicting the current and future distribution of four original plants of Gentianae Macrophyllae Radix in China under climate change scenarios

Cao

Liu

et al. 2021

Preprint

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The wild resources of the four original plants (Gentiana crasicaulis Duthie ex Burk, Gentiana daurica Fisch, Gentiana straminea Maxim, and Gentiana macrophylla Pall) of Gentianae Macrophyllae Radix are becoming exhausted. Predicting the distribution under current and future climate scenarios is of significance for the sustainable utilization of resources and ecological protection. In this study, we constructed four species distribution models (SDMs) combining species distribution informations, 19 bioclimatic variables, and the maximum entropy (MaxEnt) model. The results showed that these 4 plants prefer a cool and humid climate. Under the future climate scenarios, the areas of the highly suitable habitats for Gentiana crasicaulis Duthie ex Burk and Gentiana daurica Fisch were likely to decrease, while Gentiana straminea Maxim was likely to expand, and Gentiana macrophylla Pall was less affected. In addition, the centroids of the highly suitable habitats for the four species shifted north or west. Most notably, most of the highly suitable habitats for the four species remained unchanged, which would be the preferred area for semi-artificial cultivation. The above information in this study would contribute to the development of reasonable strategies to reduce the impact of climate change on the four original plants.

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Current and future distribution of the deciduous shrub Hydrangea macrophylla in China estimated by MaxEnt

Yan

Wang

Duan

et al. 2021

Ecology and Evolution

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Climate change has a significant impact on the growth and distribution of vegetation worldwide. Hydrangea macrophylla is widely distributed and considered a model species for studying the distribution and responses of shrub plants under climate change. These results can inform decision‐making regarding shrub plant protection, management, and introduction of germplasm resources, and are of great importance for formulating ecological countermeasures to climate change in the future. We used the maximum entropy model to predict the change, scope expansion/reduction, centroid movement, and dominant climate factors that restrict the growth and distribution of H. macrophylla in China under current and future climate change scenarios. It was found that both precipitation and temperature affect the distribution of suitable habitat for H. macrophylla. Akaike information criterion (AICc) was used to select the feature combination (FC) and the regularization multiplier (RM). After the establishment of the optimal model (FC = QP, RM = 0.5), the complexity and over‐fitting degree of the model were low (delta AICc = 0, omission rate = 0.026, difference between training and testing area under the curve values = 0.0009), indicating that it had high accuracy in predicting the potential geographical distribution of H. macrophylla (area under the curve = 0.979). Overall, from the current period to future, the potential suitable habitat of this species in China expanded to the north. The greenhouse effect caused by an increase in CO2 emissions would not only increase the area of high‐suitability habitat in Central China, but also expand the area of total suitable habitat in the north. Under the maximum greenhouse gas emission scenario (RCP8.5), the migration distance of the centroid was the longest (e.g., By 2070s, the centroids of total and highly suitable areas have shifted 186.15 km and 89.84 km, respectively).

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Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Cited by 39 publications

References 41 publications

Predicting Suitable Environments and Potential Occurrences for Cinnamomum camphora (Linn.) Presl.

Predicting Suitable Environments and Potential Occurrences for Cinnamomum camphora (Linn.) Presl.

Predicting the current and future distribution of four original plants of Gentianae Macrophyllae Radix in China under climate change scenarios

Current and future distribution of the deciduous shrub Hydrangea macrophylla in China estimated by MaxEnt

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