The effectiveness of a large protected area to conserve a global endemism hotspot may vanish in the face of climate and land-use changes

Endemic vertebrates are a crucial component of biodiversity, yet face disproportionally high extinction risk as climate and land-use changes drive habitat loss. Large protected areas are therefore deemed necessary to mitigate biodiversity loss. In 2021, China’s Giant Panda National Park (GPNP, 27,134 km2) was established in one of the global endemism hotspots. In this study we ask the question whether this large national park is able to conserve the many threatened endemic vertebrates occurring in the region in the face of climate and land-use changes, in order to assess the long-term effectiveness of the GPNP. We used species distribution modeling techniques to project the distributions of 40 threatened terrestrial (and freshwater) endemic vertebrates under land-use and climate change scenarios SSP2–4.5, SSP3–7.0 and SSP5–8.5 in 2081–2100, and assessed the extent to which their distributions are covered by the GPNP, now and in the future. We found that by 2081–2100, two thirds of the threatened endemic vertebrates are predicted to lose part (15–79%, N = 4) of or (nearly) their entire (80–100% loss, N = 23) range under all three climate and land-use change scenarios. Consequently, fewer species are predicted to occur in the GPNP than at present. Our findings confirm the high vulnerability of threatened endemic species to climate and land-use changes, despite protected areas. Habitat loss due to climate and land-use changes elevate extinction risk of species in endemism hotspots across the globe. Urgent, widespread and intensified mitigation measures and adaptation measures are required at a landscape scale for effective conservation efforts in the future.

Spermatozoa Survival in Egg Yolk-Based and Soybean-Based Extenders at Ambient and Chilling Temperature in Domestic Turkeys (Meleagris gallopavo)

Populations of many galliform species have declined mainly due to habitat loss and over-hunting, notably the Congo peacock, which has been classified as a vulnerable species by the International Union for Conservation of Nature (IUCN). The domestic turkey, being a species of least concern, which has been reported to be closely related to peacocks, could serve as a model for the optimization of assisted reproductive technologies for the Congo peacock. This study was aimed at developing a suitable turkey semen extender for artificial insemination in field conditions. Semen was collected using the dorso-abdominal massage technique from seven turkey toms and analyzed. Ejaculates with >70% motility and >80% live spermatozoa were pooled and divided into four aliquots (four treatments). Each of the four treatments was extended in a soybean-based extender or an egg yolk-based extender, with or without L-ascorbic acid. Two liquid preservation protocols (ambient temperature (35 °C) and chilled (4 °C)) were employed, and quality parameters including motility, viability and morphology were evaluated. The results show that the two extenders were similar with regard to semen quality parameters, and L-ascorbic acid supplementation of the turkey semen extenders improved semen quality during liquid storage.

Climate change has different predicted effects on the range shifts of two hybridizing ambush bug (Phymata, Family Reduviidae, Order Hemiptera) species

AIM

A universal attribute of species is that their distributions are limited by numerous factors that may be difficult to quantify. Furthermore, climate change-induced range shifts have been reported in many taxa, and understanding the implications of these shifts remains a priority and a challenge. Here, we use Maxent to predict current suitable habitat and to project future distributions of two closely related, parapatrically distributed Phymata species in light of anthropogenic climate change.

LOCATION

North America.

TAXON

Phymata americana Melin 1930 and Phymata pennsylvanica Handlirsch 1897, Family: Reduviidae, Order: Hemiptera.

METHODS

We used the maximum entropy modeling software Maxent to identify environmental variables maintaining the distribution of two Phymata species, Phymata americana and Phymata pennsylvanica. Species occurrence data were collected from museum databases, and environmental data were collected from WorldClim. Once we gathered distribution maps for both species, we created binary suitability maps of current distributions. To predict future distributions in 2050 and 2070, the same environmental variables were used, this time under four different representative concentration pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5; as well, binary suitability maps of future distributions were also created. To visualize potential future hybridization, the degree of overlap between the two Phymata species was calculated.

RESULTS

The strongest predictor to P. americana ranges was the mean temperature of the warmest quarter, while precipitation of the driest month and mean temperature of the warmest quarter were strong predictors of P. pennsylvanica ranges. Future ranges for P. americana are predicted to increase northwestward at higher CO2 concentrations. Suitable ranges for P. pennsylvanica are predicted to decrease with slight fluctuations around range edges. There is an increase in overlapping ranges of the two species in all future predictions.

MAIN CONCLUSIONS

These evidences for different environmental requirements for P. americana and P. pennsylvanica account for their distinct ranges. Because these species are ecologically similar and can hybridize, climate change has potentially important eco-evolutionary ramifications. Overall, our results are consistent with effects of climate change that are highly variable across species, geographic regions, and over time.

A checklist for maximizing reproducibility of ecological niche models

Reporting specific modelling methods and metadata is essential to the reproducibility of ecological studies, yet guidelines rarely exist regarding what information should be noted. Here, we address this issue for ecological niche modelling or species distribution modelling, a rapidly developing toolset in ecology used across many aspects of biodiversity science. Our quantitative review of the recent literature reveals a general lack of sufficient information to fully reproduce the work. Over two-thirds of the examined studies neglected to report the version or access date of the underlying data, and only half reported model parameters. To address this problem, we propose adopting a checklist to guide studies in reporting at least the minimum information necessary for ecological niche modelling reproducibility, offering a straightforward way to balance efficiency and accuracy. We encourage the ecological niche modelling community, as well as journal reviewers and editors, to utilize and further develop this framework to facilitate and improve the reproducibility of future work. The proposed checklist framework is generalizable to other areas of ecology, especially those utilizing biodiversity data, environmental data and statistical modelling, and could also be adopted by a broader array of disciplines.

Collinearity in ecological niche modeling: Confusions and challenges

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the most frequently used niche modeling tools, and many studies have aimed to optimize its performance. However, scholars have conflicting views on the treatment of predictor collinearity in Maxent modeling. Despite this lack of consensus, quantitative examinations of the effects of collinearity on Maxent modeling, especially in model transfer scenarios, are lacking. To address this knowledge gap, here we quantify the effects of collinearity under different scenarios of Maxent model training and projection. We separately examine the effects of predictor collinearity, collinearity shifts between training and testing data, and environmental novelty on model performance. We demonstrate that excluding highly correlated predictor variables does not significantly influence model performance. However, we find that collinearity shift and environmental novelty have significant negative effects on the performance of model transfer. We thus conclude that (a) Maxent is robust to predictor collinearity in model training; (b) the strategy of excluding highly correlated variables has little impact because Maxent accounts for redundant variables; and (c) collinearity shift and environmental novelty can negatively affect Maxent model transferability. We therefore recommend to quantify and report collinearity shift and environmental novelty to better infer model accuracy when models are spatially and/or temporally transferred.

Gap analysis and implications for seasonal management on a local scale

BACKGROUND

Identifying biodiversity hotspots on a local scale, using multiple data sources, and ecological niche modeling, has the potential to contribute to more effective nature reserve management.

METHODS

In this study, we used infrared-triggered camera trapping, field surveys, and interviews to create a dataset on the distribution of species (mammals and birds) in Hebei Wulingshan Nature Reserve (Hebei Province, China).

RESULTS

We identified 101 species (14 orders, 38 families), 64 of which (2,142 effective records) were selected for environmental niche modeling. All results were reclassified into three groups: "priority areas" (areas including the potential distributions of over 80% of species), "important areas" (those with 50% of species), and "normal areas" (all other areas). Our results show that priority areas (1.31-1.82 km2) and important areas (7.73-21.44 km2) for conservation were mainly covered by the core and experimental zones of the reserve; additionally, a kilometer-wide margin around the outside of the nature reserve seems to be important to maintaining biodiversity.

DISCUSSION

We close by suggesting some actions for enhancing conservation of biodiversity in the reserve, including monitoring, strengthen law enforcements, introducing popular science, and co-operating with local people.

Changes in the range of the medicinal herb Eriocaulon buergerianum Körnicke. (Eriocaulaceae) under climate change

Eriocaulon buergerianum Körnicke. (Eriocaulaceae) is one of the most common and least expensive herbal medicines for eye disease. This species is facing potential threats from climate change. Insufficient biogeographic knowledge of this plant species can hinder its effective management for long-term population survival. We integrated ecological niche modelling (Biomod2) with 70 records of E. buergerianum and eight environmental variables to estimate changes in distribution over time. A core area Zonation algorithm was introduced to identify conservation priority areas. Our results indicate that the range of E. buergerianum will likely decrease in the future: the overall range change on average is -44.36 ± 21.56% (-3.70% to -77.73%); values of range loss and range gain are 45.79 ± 20.30% (9.29-78.19%) and 1.43 ± 1.53% (0.18-5.59%), respectively. According to conservation priority analysis, the mandatory reserve (top 5%), negotiable reserve (0.95-0.9) and partial reserve (0.9-0.8) areas are 19,799, 19,799 and 39,597 km² , respectively. The areas identified as conservation priority are located in the southeast, especially in northern Taiwan and the Wuyi Mountains. Based on these results, we suggest a re-evaluation of the threatened status of this species, with a potential upgrade to the vulnerable (VU) category. To overcome the adverse conditions faced by populations of E. buergerianum in China, we propose a multi-faceted conservation strategy involving more complete resource assessment, a monitoring system, medical research focused on revealing medicinal components or substitutes, and a regional development plan that considers both wildlife and socio-economic issues.

Geographic characteristics of sable (Martes zibellina) distribution over time in Northeast China

Understanding historical context can help clarify the ecological and biogeographic characteristics of species population changes. The sable (Martes zibellina) population has decreased dramatically in Northeast China since the l950s, and understanding the changes in its distribution over time is necessary to support conservation efforts. To achieve this goal, we integrated ecological niche modeling and historical records of sables to estimate the magnitude of change in their distribution over time. Our results revealed a 51.71% reduction in their distribution in 2000–2016 compared with the potential distribution in the 1950s. This reduction was related to climate change (Pearson's correlation: Bio1, −.962, p < .01; Bio2, −.962, p < .01; Bio5, .817, p < .05; Bio6, .847, p < .05) and human population size (−.956, p < .01). The sable population tended to migrate in different directions and elevations over time in different areas due to climate change: In the Greater Khingan Mountains, they moved northward and to lower elevations; in the Lesser Khingan Mountains, they moved northward; and in the Changbai Mountains, they move southward and to higher elevations. Active conservation strategies should be considered in locations where sable populations have migrated or may migrate to.