Landscape and flow metrics affecting the distribution of a federally-threatened fish: Improving management, model fit, and model transferability

Potential Ecological Distribution of the Beetle Agrilus mali Matsumura (Coleoptera: Buprestidae) in China under Three Climate Change Scenarios, with Consequences for Commercial and Wild Apple Forests

The apple jewel beetle (AJB), Agrilus mali Matsumura (Coleoptera: Buprestidae), is a dangerous pest of commercial apple orchards across China, the largest apple production country in the world, and has recently become invasive in the Xinjiang Uygur Autonomous Region (XUAR) of northwestern China, where wild apple forests also occur. This pest poses a serious threat to apple production and wild apple forests throughout the world. Global warming is expected to change the geographical distribution of A. mali in China, but the extent of this is unknown. Based on empirical data from 1951 to 2000, a MaxEnt model was used to forecast the ecological distribution of A. mali under three different climate scenarios projected in the fifth report of the Intergovernmental Panel on Climate Change. The results showed that the most important variables were the maximum temperature of November, precipitation in January, and minimum temperatures in April. Under all climate scenarios, the forecasted suitable regions for A. mali in China will expand northward in the 2050s and 2070s. The forecasted highly suitable regions will be 1.11-1.34 times larger than they are currently, and their central distributions will be 61.57-167.59 km further north. These findings suggest that the range and damage caused by A. mali in China will increase dramatically in the future. Monitoring and management measures should be implemented urgently to protect both the commercial apple industry and wild apple resources.

Revealing suitable habitats for Juniperus procera and Olea europaea tree species in the remnant dry Afromontane forests of Ethiopia: Insights from ensemble species distribution modeling approach

Human activities and climate change pose a significant threat to the dry Afromontane forests in Ethiopia, which are essential for millions of people both economically and ecologically. In Ethiopia, trees are planted elsewhere even if they are not likely to be well suited to the area. This study aims to identify the suitable habitat for the most exploited Juniperus procera (J. procera) and Olea europaea (O. europaea) tree species in northern Ethiopia. As inputs, least correlated temperature, moisture, soil, and topographic variables were selected through a stepwise procedure. The study evaluated five individual and ensemble models using the area under the curve (AUC) and true skill statistic (TSS) values. The ensemble model outperformed with mean AUC of 0.95 and TSS of 0.78 for J. procera, while securing the second position for O. europaea with an AUC of 0.88 and TSS of 0.71. Climatic factors emerged as the most influential, followed by soil and topography. Suitable areas for both species were found when Isothermality (Bio3) values range from 52% to 62%, temperature seasonality (Bio4) of 16-29°C. Moreover, well drained soils with soil texture not heavier than sandy clay, and soil organic carbon ranging from 5 to 42 g kg-1 were found suitable. The optimal suitable altitude for J. procera and O. europaea was determined to be 2200-2600 and 2100-2500 m.a.s.l., respectively. The suitable areas for J. procera and O. europaea were estimated to be 3130 and 3946 km2, respectively. Furthermore, potential plantation areas were identified beyond Desa'a and Hugumbirda Grat-Kahsu protected forests, covering 2721 km2 (86.9%) for J. procera and 3576 km2 (90.6%) for O. europaea. These findings hold significance for the conservation and sustainable management of these valuable tree species in northern Ethiopia. We recommend implementing a similar approach for other locally restricted dry Afromontane tree species with wider potential distribution.

Mapping Species Distributions of Latoia consocia Walker under Climate Change Using Current Geographical Presence Data and MAXENT (CMIP 6)

Latoia consocia Walker is an important phytophagous pest that has rapidly spread across North China in recent years, posing a severe threat to related plants. To study the impact of climatic conditions on its distribution and to predict its distribution under current and future climate conditions, the MaxEnt niche model and ArcGIS 10.8 software were used. The results showed that the MaxEnt model performs well in predicting the distribution of L. consocia, with an AUC value of 0.913. The annual precipitation (Bio12), the precipitation of the driest month (Bio14), the temperature annual range (Bio7), and the minimum temperature of the coldest month (Bio6) are key environmental factors affecting the potential distribution of L. consocia. Under current climate conditions, L. consocia has a highly suitable growth area of 2243 km2 in China, among which Taiwan has the largest high-suitable area with a total area of 1450 km2. With climate warming, the potential habitat area for L. consocia shows an overall decreasing trend in future. This work provides a scientific basis for research on pest control and ecological protection. A "graded response" detection and early warning system, as well as prevention and control strategies, can be developed for potentially suitable areas to effectively address this pest challenge.

Spatial distribution and priority conservation areas identification in Three-River-Source National Park considering the multifaceted values of plants

Spatially differentiated conservation effort for natural resources is critical to achieving a balance between protection and development in national parks. However, the extent of priority conservation areas for plants that integrate multispecies and multifaceted values is unclear. Here, we selected fine-resolution environmental variables with stronger impacts on wild plant survival to spatialize the distribution of all modeling-eligible species using species distribution models in Three-River-Source National Park, China. These were then combined with in situ conservation results for insufficient data species to identify priority conservation areas (PCAs) in terms of diversity, ecological and economic values, respectively. We analyzed the spatial characteristics of the priority conservation areas and searched for conservation gaps not covered by national nature reserves. The results showed that this study obtained more precise results on the spatial distribution of species by improving environmental variables and upgrading the spatial resolution. In Three-River-Source National Park, the species richness of wild plants showed a decreasing trend from southeast to northwest. There were significant differences in the spatial distribution of the priority conservation areas identified based on the three values, which was the basis for the spatially differentiated conservation and development of wild plant resources. In addition, the priority conservation areas obtained based on ecological value found Top17% priority conservation areas in the Hoh Xil Natural Reserve, which could not be revealed based on diversity or economic value. These results highlight the urgency of implementing multispecies and multifaceted values studies in national parks. In the future, studying conflicts between wildlife priority conservation areas and human activities, and expanding to national parks on a global scale, will be the focus that this study will continue to explore.

Forest Orchids under Future Climate Scenarios: Habitat Suitability Modelling to Inform Conservation Strategies

Orchidaceae is one of the largest and most diverse families of flowering plants in the world but also one of the most threatened. Climate change is a global driver of plant distribution and may be the cause of their disappearance in some regions. Forest orchids are associated with specific biotic and abiotic environmental factors, that influence their local presence/absence. Changes in these conditions can lead to significant differences in species distribution. We studied three forest orchids belonging to different genera (Cephalanthera, Epipactis and Limodorum) for their potential current and future distribution in a protected area (PA) of the Northern Apennines. A Habitat Suitability Model was constructed for each species based on presence-only data and the Maximum Entropy algorithm (MaxEnt) was used for the modelling. Climatic, edaphic, topographic, anthropogenic and land cover variables were used as environmental predictors and processed in the model. The aim is to identify the environmental factors that most influence the current species distribution and the areas that are likely to contain habitats suitable for providing refuge for forest orchids and ensuring their survival under future scenarios. This will allow PA authorities to decide whether to invest more resources in conserving areas that are potential refuges for threatened species.

Geographical distribution and ecological niche dynamics of Crassostrea sikamea (Amemiya, 1928) in China's coastal regions under climate change

Global climate change drives species redistribution, threatening biodiversity and ecosystem heterogeneity. The Kumamoto oyster, Crassostrea sikamea (Amemiya, 1928), one of the most promising aquaculture species because of its delayed reproductive timing, was once prevalent in southern China. In this study, an ensemble species distribution model was employed to analyze the distribution range shift and ecological niche dynamics of C. sikamea along China's coastline under the current and future climate scenarios (RCP 2.6-8.5 covering 2050 s and 2100 s). The model results indicated that the current habitat distribution for C. sikamea consists of a continuous stretch extending from the coastlines of Hainan Province to the northern shores of Jiangsu Province. By the 2050 s, the distribution range will stabilize at its southern end along the coast of Hainan Province, while expanding northward to cover the coastal areas of Shandong Province, showing a more dramatic trend of contraction in the south and invasion in the north by the 2100 s. In RCP8.5, the southern end retracts to the coasts of Guangdong, whereas the northern end covers all of China's coastal areas north of 34°N. C. sikamea can maintain relatively stable ecological niche characteristics, while it may occupy different ecological niche spaces under future climate conditions. Significant niche expansion will occur in lower temperature. We concluded C. sikamea habitats are susceptible to climate change. The rapid northward expansion of C. sikamea may open new possibilities for oyster farming in China, but it will also have important consequences for the ecological balance and biodiversity of receiving areas. It's imperative that we closely examine and strategize to address these repercussions for a win-win situation.

Impacts of climate change and human activity on the potential distribution of Aconitum leucostomum in China

Aconitum leucostomum is a poisonous grass that disturbs grassland populations and livestock development, and its spread is influenced by climate change and human activities. Therefore, exploring its potential distribution area under such conditions is crucial to maintain grassland ecological security and livestock development. The present study initially selected 39 variables that may influence the spatial distribution of A. leucostomum, including bioclimate, soil, topography, solar radiation, and human footprint data; the variables were screened by Spearman's correlation coefficient and the jackknife method. Twenty variables were finally identified, and three types of models based on the maximum entropy (MaxEnt) model were constructed to predict the distribution of A. leucostomum within China under three shared economy pathways (SSP126, SSP245, and SSP585): A: prediction of environmental variables under the current climate model; B: prediction of environmental variables + human footprint under the current climate model; and C: prediction of environmental variables under the future climate model (including the 2030s, 2050s, and 2070s). The effects of human activities and climate change on the potential geographic distribution of A. leucostomum were explored separately. The results show that precipitation seasonality, human footprint, solar radiation and mean diurnal range are the main factors affecting the distribution of A. leucostomum. Human activities inhibit the spread of A. leucostomum, and climate change promotes its growth, with areas of high suitability and area variation mainly in northern Xinjiang and northern Yunnan. With climate change, in the future, the distribution center of A. leucostomum shows a tendency to migrate to the southeast on the horizontal gradient and to move to higher altitudes on the vertical gradient. This study provides a positive reference value for the control of A. leucostomum and the maintenance of grassland ecological security.

Climate change impacts on optimal habitat of Stachys inflata medicinal plant in central Iran

Stachys inflata Benth. is a perennial shrub plant, with powerful natural antioxidant agents, which is recognized as a famous medicinal plant that is widely applied to treat Infection, Asthma, and Rheumatism. Iran is renowned as a center of diversity for Stachys, however, the ideal habitats of S. inflata in this nation remain unknown. The potential and future distribution of suitable habitats for S. inflata were projected using an ensembles ecological niche model in Isfahan province, Iran. We used occurrence data (using GPS), bioclimatic and topographic variables from the Chelsa and WorldClim databases to model the current and future potential distribution of this valuable species. The results showed that: (i) S. inflata is mainly distributed in the south, southwest, center, and west of the Isfahan province, and the excellent habitats of S. inflata accounted for 14.34% of the 107,000 km² study area; (ii) mean annual temperature, mean daily temperature of wettest quarter, annual precipitation, and elevation were the four most important variables that affect the distribution of S. inflata, with a cumulative contribution of 56.55%; and (iii) about the half (- 42.36%) of the currently excellent habitats of S. inflata show a tendency to decrease from now to the 2080s, while often the area of other S. inflata habitats increases (the area of unsuitable habitat: 5.83%, the area of low habitat suitability: 24.68%, the area of moderate habitat suitability: 2.66%, and the area of high habitat suitability: 2.88%). The increase in the area of other S. inflata habitats is different and they are less favorable than the excellent habitat. The results help establishing a framework for long-term in-situ and ex-situ conservation and management practices in habitats of S. inflata in rangeland and agricultural ecosystems.

Predicting the potential distribution of Campsis grandiflora in China under climate change

Because the research on the geographical distribution of species significantly influences people's understanding of species protection and utilization, it is important to study the influence of climate change on plants' geographical distribution patterns. Based on 166 distribution records and 11 climate and terrain variables, we used MaxEnt (Maximum Entropy) model and ArcGIS software to predict the potential distribution of Campsis grandiflora under climate change and then determined the dominant climate variables that significantly affected its geographical distribution. In our study, the area under the curve (AUC) value of the training data was 0.939, proving the accuracy of our prediction. Under current climate conditions, the area of potentially suitable habitat is 238.29 × 10⁴ km², mainly distributed in northern, central, southern, and eastern China. The dominant variables that affect the geographical distribution of C. grandiflora are temperature, precipitation and altitude. In the future climate change scenario, the total area of suitable habitat and highly suitable habitat will increase, whereas the area of moderately suitable habitat and poorly suitable habitat will decrease. In addition, the centroid of the potentially suitable area of C. grandiflora will migrate to higher latitude and higher altitudes areas. The results could give strategic guidance for development, protection, and utilization of C. grandiflora in China.

Identifying monitoring information needs that support the management of fish in large rivers

Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are collected to characterize key ecosystem processes that could affect the outcome. Scientists from across the U.S. convened to develop a conceptual model that would help identify monitoring information needed to better understand how natural and anthropogenic factors affect large river fishes. We applied the conceptual model to case studies in four large U.S. rivers. The application of the conceptual model indicates the model is flexible and relevant to large rivers in different geographic settings and with different management challenges. By visualizing how natural and anthropogenic drivers directly or indirectly affect cascading ecosystem tiers, our model identified critical information gaps and uncertainties that, if resolved, could inform how to best meet management objectives. Despite large differences in the physical and ecological contexts of the river systems, the case studies also demonstrated substantial commonalities in the data needed to better understand how stressors affect fish in these systems. For example, in most systems information on river discharge and water temperature were needed and available. Conversely, information regarding trophic relationships and the habitat requirements of larval fishes were generally lacking. This result suggests that there is a need to better understand a set of common factors across large-river systems. We provide a stepwise procedure to facilitate the application of our conceptual model to other river systems and management goals.

Predicting distribution of Zanthoxylum bungeanum Maxim. in China

BACKGROUND

With the growth of economic benefits brought by Zanthoxylum bungeanum Maxim. and the increasing market demand, this species has been widely introduced and cultivated in China. It is important to scientifically select suitable areas for artificial planting and promotion, and to understand the status and potential of Z. bungeanum resources.

RESULTS

The maximum entropy (MaxEnt) model and ArcGIS technologies were used to analyze the climatic suitability of Z. bungeanum based on known distribution data, combined with environmental data in China. Z. bungeanum was mainly distributed in subtropical and mid-eastern warm temperate regions. The total suitable area (high and medium suitability) accounted for 32% of China's total land area, with high suitability areas composing larger percentage, reaching 1.93 × 10⁶ km². The suitable range (and optimum value) of the key environmental variables affecting the distribution of Z. bungeanum were the maximum temperature in February of 2.8-17.7 °C (10.4 °C), the maximum temperature in March of 8.6-21.4 °C (16.3 °C), the maximum temperature in December of 2.5-17.1 °C (9.9 °C), the maximum temperature in November of 7.7-22.2 °C (14.5 °C) and the mean temperature in March of 3.2-16.2 °C (12.0 °C).

CONCLUSIONS

The model developed by MaxEnt was applicable to explore the environmental suitability of Z. bungeanum.

Predictions of potential geographical distribution of Diaphorina citri (Kuwayama) in China under climate change scenarios

Climate change significantly affects geographic distribution of plants pests and diseases worldwide. Understanding the influence of future climate change on the suitable areas of Diaphorina citri (Kuwayama) in our country and taking timely countermeasures are crucial for improving the effectiveness of control of pest. Based on the occurrence points of D. citri and the selected environmental variables, the potential suitable areas of this pest under climate change scenarios in China were predicted by using MaxEnt and GIS tools. Our results showed that the higly suitable area were mainly located in Guangxi, Guangdong, Fujian, Southern Zhejiang, Southern Jiangxi, Eastern Hunan, Southwestern Guizhou, and the area was 43.7 × 10⁴ km². Areas of moderate and low suitability were centered on areas of high suitability and radiate to the North successively, with an area of 59.28 × 10⁴ km² and 93.46 × 10⁴ km² respectively. From current to 2070 s, the areas of the highly suitable areas will increase, and the geometric center of the highly and total suitable areas will move to north under three climate change scenarios.

Modeling and mapping the current and future distribution of Pseudomonas syringae pv. actinidiae under climate change in China

OBJECTIVE

Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China.

METHOD

Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation.

RESULT

The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa.

CONCLUSION

The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management.