Using species distribution models and decision tools to direct surveys and identify potential translocation sites for a critically endangered species

Analysis of the Distribution Pattern of Phenacoccus manihoti in China under Climate Change Based on the Biomod2 Model

The changing global climate has significantly impacted the spread of plant pests. The cassava mealybug (Phenacoccus manihoti) is among the most dangerous quarantine pests affecting cassavas worldwide, causing substantial losses in agricultural production and food security across several regions. Although China is currently free of the cassava mealybug, its proximity to affected countries and extensive trade with these regions necessitate a detailed understanding of the pest's distribution pattern and dynamic ecological niche changes. Using the Biomod2 model, we selected two historical climate scenarios and two future climate scenarios (SSP1-2.6 and SSP5-8.5) to investigate the distribution patterns, potential habitats, distribution centers, and dynamic ecological niches of cassava mealybugs in China. Key environmental variables influencing the distribution were identified, including bio4, bio8, bio12, bio18, and bio19. The potential habitat of cassava mealybugs is mainly located in several provinces in southern China. In the future, the suitable habitat is projected to expand slightly under the influence of climate change, maintaining the overall trend, but the distribution center of suitable areas will shift northward. Dynamic ecological niche prediction results indicate the potential for further expansion; however, the ecological niches may be unequal and dissimilar in the invaded areas. The predictions could serve as a valuable reference for early warning systems and management strategies to control the introduction of cassava mealybugs.

Habitat suitability maps for Australian flora and fauna under CMIP6 climate scenarios

BACKGROUND

Spatial information about the location and suitability of areas for native plant and animal species under different climate futures is an important input to land use and conservation planning and management. Australia, renowned for its abundant species diversity and endemism, often relies on modeled data to assess species distributions due to the country's vast size and the challenges associated with conducting on-ground surveys on such a large scale. The objective of this article is to develop habitat suitability maps for Australian flora and fauna under different climate futures.

RESULTS

Using MaxEnt, we produced Australia-wide habitat suitability maps under RCP2.6-SSP1, RCP4.5-SSP2, RCP7.0-SSP3, and RCP8.5-SSP5 climate futures for 1,382 terrestrial vertebrates and 9,251 vascular plants vascular plants at 5 km2 for open access. This represents 60% of all Australian mammal species, 77% of amphibian species, 50% of reptile species, 71% of bird species, and 44% of vascular plant species. We also include tabular data, which include summaries of total quality-weighted habitat area of species under different climate scenarios and time periods.

CONCLUSIONS

The spatial data supplied can help identify important and sensitive locations for species under various climate futures. Additionally, the supplied tabular data can provide insights into the impacts of climate change on biodiversity in Australia. These habitat suitability maps can be used as input data for landscape and conservation planning or species management, particularly under different climate change scenarios in Australia.

Impacts of physiological characteristics and human activities on the species distribution models of orchids taking the Hengduan Mountains as a case

The biogeography research of orchids through species distribution models (SDMs), a vital tool in the biogeography field, is critical to understanding the fundamental geographic distribution patterns and identifying conservation priorities. The correspondence between species occurrence and environmental information is crucial to the model's performance. However, ecological preferences unique to different orchid species, such as their life forms, are often overlooked during the modeling process. This oversight can introduce bias and increase model uncertainty. Additionally, human activities, as an important potential predictor, have not been quantified in any orchid SDMs. Taking the Hengduan Mountains as an example, we preprocessed all orchid species' occurrences based on physiological characteristics. Choosing five spatial factors related to human activities to quantify the interference and enter into models as HI factor. Using different modeling methods (GLM, MaxEnt, and RF) and evaluation indices (AUC, TSS, and Kappa), diverse modeling strategies have been constructed in the study. A double-ranking method has been adopted to select the critical orchid distribution regions. The results showed that classification models based on physiological characteristics significantly improved the model's accuracy while adding the HI factor had the same effect but the absence of enough significance. Suitability maps indicated that highly heterogeneous mountainous areas were vital for the distribution of orchids in the Hengduan Mountains. Different distribution patterns and critical regions existed between various orchid life forms geographically - terrestrial orchids were dominant in the mountain, and mycoherterophical orchids were primarily located in the north, more influenced by vegetation and temperature. Critical regions of epiphytic orchids were in the south due to a greater dependence on precipitation and temperature. These studies are informative for understanding the orchids' geographic distribution patterns in the Hengduan Mountains, promoting conservation and providing references for similar research beyond orchids.

Future distribution of the epiphytic leafless orchid (Dendrophylax lindenii), its pollinators and phorophytes evaluated using niche modelling and three different climate change projections

The identification of future refugia for endangered species from the effects of global warming is crucial for improving their conservation. Because climate-driven shifts in ranges and local extinctions can result in a spatial mismatch with their symbiotic organisms, however, it is important to incorporate in niche modelling the ecological partners of the species studied. The aim of this study was to evaluate the effect of climate change on the distribution of suitable niches for the ghost orchid (Dendrophylax lindenii) and its phorophytes and pollinators. Thus, its five species of host trees and three pollen vectors were included in the analysis. Climatic preferences of all the species studied were evaluated. The modelling was based on three different climate change projections and four Shared Socio-economic Pathway trajectories. All the species analysed are characterized by narrow temperature tolerances, which with global warming are likely to result in local extinctions and range shifts. D. lindenii is likely to be subjected to a significant loss of suitable niches, but within a reduced geographical range, both host trees and pollen vectors will be available in the future. Future conservation of this orchid should focus on areas that are likely be suitable for it and its ecological partners.

Shrub density effects on the presence of an endangered lizard of the Carrizo Plain National Monument, California

Positive associations between animals and foundational shrub species are frequent in desert ecosystems for shelter, resources, refuge, and other key ecological processes. Herein, we tested the impact of the density of the shrub species Ephedra californica on the presence and habitat use of the federally endangered lizard species, Gambelia sila. To do this, we used a 3-year radio telemetry dataset and satellite-based counts of shrub density across sites at the Carrizo Plain National Monument in San Luis Obispo County, CA. The effect of shrub density on lizard presence was contrasted with previous shrub cover analyses to determine whether measures of shrub density were superior to shrub cover in predicting lizard presence. Increasing shrub density increased lizard presence. As shrub density increased, lizards were located more frequently "above ground" versus "below ground" in burrows. Male lizards had significantly larger home ranges than females, but both sexes were similarly associated with increasing shrub densities. Shrub density and shrub cover models did not significantly differ in their prediction of lizard presence. These findings suggest that both habitat measures are effective analogs and that ecologically, both cover and the density of foundation shrub species are key factors for some desert lizards.

Effects of Climate Change on the Habitat of the Leopard (Panthera pardus) in the Liupanshan National Nature Reserve of China

Simple Summary

Climate change affects animal populations by affecting their habitats. The leopard population has significantly decreased due to climate change and human disturbance. We studied the impact of climate change on leopard habitats using infrared camera technology in the Liupanshan National Nature Reserve of Jingyuan County, Ningxia Hui Autonomous Region, China, from July 2017 to October 2019. We captured 25 leopard distribution points and used the MAXENT model to predict and analyze the habitat. We studied the leopard’s suitable habitat area and distribution area under different geographical scales in the reserve. Changes in habitat area of leopards under three climate models in Guyuan in 2050 were also studied. We conclude that the current main factors affecting suitable leopard habitat area were vegetation cover and human disturbance. The most critical factor affecting future suitable habitat area is rainfall. Under the three climate models, the habitat area of the leopard decreased gradually because of an increase in carbon dioxide concentration.

Abstract

Climate change affects animal populations by affecting their habitats. The leopard population has significantly decreased due to climate change and human disturbance. We studied the impact of climate change on leopard habitats using infrared camera technology in the Liupanshan National Nature Reserve of Jingyuan County, Ningxia Hui Autonomous Region, China, from July 2017 to October 2019. We captured 25 leopard distribution points over 47,460 camera working days. We used the MAXENT model to predict and analyze the habitat. We studied the leopard’s suitable habitat area and distribution area under different geographical scales in the reserve. Changes in habitat area of leopards under the rcp2.6, rcp4.5, and rcp8.5 climate models in Guyuan in 2050 were also studied. We conclude that the current main factors affecting suitable leopard habitat area were vegetation cover and human disturbance. The most critical factor affecting future suitable habitat area is rainfall. Under the three climate models, the habitat area of the leopard decreased gradually because of an increase in carbon dioxide concentration. Through the prediction of the leopard’s distribution area in the Liupanshan Nature Reserve, we evaluated the scientific nature of the reserve, which is helpful for the restoration and protection of the wild leopard population.

Predicting Climate Change Impacts on the Rare and Endangered Horsfieldia tetratepala in China

Global climate change has become a major threat to biodiversity, posing severe challenges to species conservation. This is particularly true for species such as Horsfieldia tetratepala that have extremely small populations in the wild. Little is known about the species distribution of H. tetratepala in the current climate, as well as how that will change with potential future climates. The key environmental factors that influence its expansion, especially its habitat sustainability and its potential to adapt to climate change, are also unknown, though such information is vital for the protection of this endangered species. Based on six climate factors and 25 species distribution points, this study used the maximum entropy model (MaxEnt) to simulate the potential distribution for H. tetratepala in three periods (current, 2050s, and 2070s), and to investigate the changes in distribution patterns and the main environmental factors affecting species distribution. The modeling results show that the most important bioclimatic variables affecting H. tetratepala were precipitation of the warmest quarter (Bio_18) and temperature seasonality (Bio_4). The suitable areas for H. tetratepala will gradually be lost in Yunnan but will be generally offset in the northeastward direction, expanding in Hainan, Guangzhou, and Taiwan provinces under the future climate conditions. Therefore, we recommend protecting the habitats of H. tetratepala in Yunnan and strengthening the in-depth species investigation and monitoring in areas (Hainan, Guangzhou, and Taiwan) where no related reports of H. tetratepala have been reported. The results improve our understanding of this species’ response under the changing climate and benefit strategies for its conservation.