Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions

Potential distribution modelling for Haemonchus contortus (Nematoda: Trichostrongylidae) in South America

The species Haemonchus contortus occurs in many regions worldwide, mainly parasitising small ruminants and economically impacting animal production. Climate change is considered a driving force for the risk of diseases caused by helminths and can also affect relationships between parasites and their hosts, with the potential to cause losses in both animal production and biodiversity in general. The aim of this study was to model the potential distribution of H. contortus in South America. We used MaxEnt to perform the analyses and describe the contribution of important bioclimatic variables involved in the species distribution. Our results show that H. contortus colonised most of the areas with habitats that suit the species' environmental requirements and that this parasite presents habitat suitability in a future scenario. Understanding the effects of climate change on the occurrence and distribution of parasite species is essential for monitoring these pathogens, in addition to predicting the areas that tend to present future parasite outbreaks and identify opportunities to mitigate the impacts of the emergence of diseases caused by these organisms.

Predicting the suitable cultivation areas of breadfruit crops Artocarpus altilis (Moraceae) under future climate scenarios in Central Java, Indonesia

Artocarpus altilis, commonly known as breadfruit, is a potential crop adapted to a wide variety of climates and widely spread, including in Indonesia. However, information on how this species can adapt to climate change, in particular in Central Java, is still limited. In Indonesia, Central Java is the center for cultivation areas for many crop species to support the 145 million people living on Java Island. One of the potential crops being developed in Central Java is breadfruit. To assess the suitable cultivation areas for breadfruit, species distribution modeling (SDM) was used to predict the current and future (2050-2070) distribution of breadfruit. Two climate change scenarios, including optimistic RCP2.6 and pessimistic RCP8.5 models, were considered to represent future climate change impacts. Based on the results for both optimistic and pessimistic scenarios, the breadfruit's suitable cultivation areas will expand eastward. Implementing a mitigation climate change scenario and limiting the temperature increase to only 1°C under RCP2.6 will provide 270.967 km2 more of suitable cultivation areas for breadfruit in 2050 and 133.296 km2 in 2070. To conclude, this study provides important information on the status and potential cultivation areas for breadfruit, mainly in the Southeast Asia region. The identification of suitable areas will guide land conservation for breadfruit to support food security in this region.

The influence of climate change on the future distribution of two Thymus species in Iran: MaxEnt model-based prediction

Within a few decades, the species habitat was reshaped at an alarming rate followed by climate change, leading to mass extinction, especially for sensitive species. Species distribution models (SDMs), which estimate both present and future species distribution, have been extensively developed to investigate the impacts of climate change on species distribution and assess habitat suitability. In the West Asia essential oils of T. daenensis and T. kotschyanus include high amounts of thymol and carvacrol and are commonly used as herbal tea, spice, flavoring agents and medicinal plants. Therefore, this study aimed to model these Thymus species in Iran using the MaxEnt model under two representative concentration pathways (RCP 4.5 and RCP 8.5) for the years 2050 and 2070. The findings revealed that the mean temperature of the warmest quarter (bio10) was the most significant variable affecting the distribution of T. daenensis. In the case of T. kotschyanus, slope percentage was the primary influencing factor. The MaxEnt modeling also demonstrated excellent performance, as indicated by all the Area Under the Curve (AUC) values exceeding 0.9. Moreover, based on the projections, the two mentioned species are expected to undergo negative area changes in the coming years. These results can serve as a valuable achievement for developing adaptive management strategies aimed at enhancing protection and sustainable utilization in the context of global climate change.

Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia

Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate-only model, an environment-only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020-2039 and 2060-2079. The climate-only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment-only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020-2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060-2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.

Predicting current and future potential distributions of the greater bandicoot rat (Bandicota indica) under climate change conditions

BACKGROUND

Rodent infestation is a global problem. Rodents cause huge harm to agriculture, forestry, and animal husbandry around the world and spread various zoonoses. In this study, we simulated the potentially suitable habitats of Bandicota indica and predicted the impact of future climate change on its distribution under different socio-economic pathway scenarios of CMIP6 using a parameter-optimized maximum entropy (MaxEnt) model.

RESULTS

The average area under the receiver operating characteristic curve (AUC) value (0.958 ± 0.006) after ten repetitions proved the high accuracy of the MaxEnt model. Model results show that the annual mean temperature (≥ 15.93 °C), isothermality (28.52-80.49%), annual precipitation (780.13-3863.13 mm), precipitation of the warmest quarter (≥ 204.37 mm), and nighttime light (≥ 3.38) were important limiting environmental variables for the distribution of B. indica. Under current climate conditions, the projected potential suitable habitats for B. indica were mainly in India, China, Myanmar, Thailand, and Vietnam, which cover a total area of 301.70 × 104  km2 . The potentially suitable areas of B. indica in the world will expand under different future climate change scenarios by 1.61-17.65%.

CONCLUSIONS

These results validate the potential influence of climate change on the distribution of B. indica and aid in understanding the linkages between B. indica niches and the relevant environment, thereby identifying urgent management areas where interventions may be necessary to develop feasible early warning and prevention strategies to protect against this rodent's spread. © 2023 Society of Chemical Industry.

Prediction of suitable habitat shifts and assessment of ecological niche overlaps for three Tridentiger species with intertidal and subtidal characteristics under future climate changes

To show how dramatic global climate change affects marine ecosystem species in different habitats. We used a joint species distribution model (SDM) and an ecological niche model (ENM) to investigate the suitable habitat shifts and ecological niche overlaps of the Tridentiger fishes. In the present study, the SDM results showed that 5 hotspots were identified for T. trigonocephalus and T. barbatus, and 4 hotspots for T. bifasciatus. The study on center-of-mass transfer revealed notable reductions in the habitual range of the three Tridentiger species with future climate change and no significant bipolar shifts in the center of mass. The ENM results indicated that T. trigonocephalus and T. barbatus exhibited the greatest ecological niche overlap with Schoener's D (D) and Hellinger-based I (I) values of 0.4719 and 0.7690, respectively. Both SDM and ENM results have suggested that T. trigonocephalus occupied a wider distribution and greater adaptability to future climate change. This study sought to measure the variations in the effects of global climate change on marine species in different habitats. Our study first found that intertidal species with specific life histories may be more resilient to environmental change.

A field-validated ensemble species distribution model of Eriogonum pelinophilum, an endangered subshrub in Colorado, USA

Understanding the suitable habitat of endangered species is crucial for agencies such as the Bureau of Land Management to plan management and conservation. However, few species distribution models are directly validated, potentially limiting their application in management. In preparation for a Species Status Assessment of clay-loving wild buckwheat (Eriogonum pelinophilum), an endangered subshrub found in southwest Colorado, we ran a series of species distribution models to estimate the species' potential occupied habitat and validated these models in the field. A 1-meter resolution digital elevation model derived from LiDAR and a high-resolution geology mapping helped identify biologically relevant characteristics of the species' habitat. We employed a weighted ensemble model based on two Random Forest and one Boosted Regression Tree model, and discrimination performance of the ensemble model was high (AUC-PR = 0.793). We then conducted a systematic field survey of model habitat suitability predictions, during which we discovered 55 new subpopulations of the species and demonstrated that new species observations were strongly associated with model predictions (p < .0001, Cliff's delta = 0.575). We further refined our original models by incorporating the additional species occurrences collected in the field survey, a new explanatory variable, and a more diverse set of models. These iterative changes marginally improved performance of the ensemble model (AUC-PR = 0.825). Direct validation of species distribution models is extremely rare, and our field survey provides strong validation of our model results. This helps increase confidence to utilize predictions in planning. The final model predictions greatly improve the Bureau of Land Management's understanding of the species' habitat and increase our ability to consider potential habitat in planning land use activities such as road development and travel management.

Future habitat changes of Bactrocera minax Enderlein along the Yangtze River Basin using the optimal MaxEnt model

Background

Bactrocera minax (Enderlein, 1920) (Diptera: Tephritidae) is a destructive citrus pest. It is mainly distributed throughout Shaanxi, Sichuan, Chongqing, Guizhou, Yunnan, Hubei, Hunan, and Guangxi in China and is considered to be a second-class pest that is prohibited from entering that country. Climate change, new farming techniques, and increased international trade has caused the habitable area of this pest to gradually expand. Understanding the suitable habitats of B. minax under future climate scenarios may be crucial to reveal the expansion pattern of the insect and develop corresponding prevention strategies in China.

Methods

Using on the current 199 distribution points and 11 environmental variables for B. minax, we chose the optimal MaxEnt model to screen the dominant factors that affect the distribution of B. minax and to predict the potential future distribution of B. minax in China under two shared socio-economic pathways (SSP1-2.6, SSP5-8.5).

Results

The current habitat of B. minax is located at 24.1-34.6°N and 101.1-122.9°E, which encompasses the provinces of Guizhou, Sichuan, Hubei, Hunan, Chongqing, and Yunnan (21.64 × 104 km2). Under future climate scenarios, the potential suitable habitat for B. minax may expand significantly toward the lower-middle reaches of the Yangtze River. The land coverage of highly suitable habitats may increase from 21.64 × 104 km2 to 26.35 × 104 × 104 km2 (2050s, SSP5-8.5) ~ 33.51 × 104 km2 (2090s, SSP5-8.5). This expansion area accounts for 29% (2050s, SSP1-2.6) to 34.83% (2090s, SSP1-2.6) of the current habitat. The center of the suitable habitat was predicted to expand towards the northeast, and the scenario with a stronger radiative force corresponded to a more marked movement of the center toward higher latitudes. A jackknife test showed that the dominant variables affecting the distribution of B. minax were the mean temperature of the driest quarter (bio9), the annual precipitation (bio12), the mean diurnal range (bio2), the temperature annual range (bio7), and the altitude (alt).

Discussion

Currently, it is possible for B. minax to expand its damaging presence. Regions with appropriate climate conditions and distribution of host plants may become potential habitats for the insects, and local authorities should strengthen their detection and prevention strategies. Climate changes in the future may promote the survival and expansion of B. minax species in China, which is represented by the significant increase of suitable habitats toward regions of high altitudes and latitudes across all directions but with some shrinkage in the east and west sides.

Predicting the Potential Geographical Distribution of Rhodiola L. in China under Climate Change Scenarios

Rhodiola L. has high nutritional and medicinal value. Little is known about the properties of its habitat distribution and the important eco-environmental factors shaping its suitability. Rhodiola coccinea (Royle) Boriss., Rhodiola gelida Schrenk, Rhodiola kirilowii (Regel) Maxim., and Rhodiola quadrifida (Pall.) Fisch. et Mey., which are National Grade II Protected Plants, were selected for this research. Based on high-resolution environmental data for the past, current, and future climate scenarios, we modeled the suitable habitat for four species by MaxEnt, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results indicate that the growth distribution of R. coccinea, R. kirilowii, and R. quadrifida is most affected by bio10 (mean temperature of warmest quarter), bio3 (isothermality), and bio12 (annual precipitation), whereas that of R. gelida is most affected by bio8 (mean temperature of wettest quarter), bio13 (precipitation of wettest month), and bio16 (precipitation of wettest quarter). Under the current climate scenario, R. coccinea and R. quadrifida are primarily distributed in Tibet, eastern Qinghai, Sichuan, northern Yunnan, and southern Gansu in China, and according to the 2070 climate scenario, the suitable habitats for both species are expected to expand. On the other hand, the suitable habitats for R. gelida and R. kirilowii, which are primarily concentrated in southwestern Xinjiang, Tibet, eastern Qinghai, Sichuan, northern Yunnan, and southern Gansu in China, are projected to decrease under the 2070 climate scenario. Given these results, the four species included in our study urgently need to be subjected to targeted observation management to ensure the renewal of Rhodiola communities. In particular, R. gelida and R. kirilowii should be given more attention. This study provides a useful reference with valuable insights for developing effective management and conservation strategies for these four nationally protected plant species.

Ecogeography of Dioscorea remotiflora Kunth: An Endemic Species from Mexico

Dioscorea remotiflora, a perennial climbing herbaceous plant native to Mexico, produces tubers with great nutritional and ethnobotanical value. However, most ecological aspects of this plant remain unknown, which limits its cultivation and use. This is why the objective of this research was to characterize the ecogeography of D. remotiflora as a source to determine its edaphoclimatic adaptability and current and potential distribution. A comprehensive database encompassing 480 geo-referenced accessions was assembled from different data sources. Using the Agroclimatic Information System for México and Central America (SIAMEXCA), 42 environmental variables were formulated. The MaxEnt model within the Kuenm R package was employed to predict the species distribution. The findings reveal a greater presence of D. remotiflora in harsh environments, characterized by arid to semiarid conditions, poor soils, and hot climates with long dry periods. Niche modeling revealed that seven key variables determine the geographical distribution of D. remotiflora: precipitation of the warmest quarter, precipitation of the driest month, minimum temperature of the coldest month, November-April solar radiation, annual mean relative humidity, annual moisture availability index, and May-October mean temperature. The current potential distribution of D. remotiflora is 428,747.68 km2. Favorable regions for D. remotiflora coincide with its current presence sites, while other suitable areas, such as the Yucatán Peninsula, northeast region, and Gulf of Mexico, offer potential expansion opportunities for the species distribution. The comprehensive characterization of Dioscorea remotiflora, encompassing aspects such as its soil habitats and climate adaptation, becomes essential not only for understanding its ecology but also for maximizing its economic potential. This will enable not only its sustainable use but also the exploration of commercial applications in sectors such as the pharmaceutical and food industries, thus providing a broader approach for its conservation and optimal utilization in the near future.

Identifying and Managing Areas under Threat in the Iberian Peninsula: An Invasion Risk Atlas for Non-Native Aquatic Plant Species as a Potential Tool

Predicting the likelihood that non-native species will be introduced into new areas remains one of conservation's greatest challenges and, consequently, it is necessary to adopt adequate management measures to mitigate the effects of future biological invasions. At present, not much information is available on the areas in which non-native aquatic plant species could establish themselves in the Iberian Peninsula. Species distribution models were used to predict the potential invasion risk of (1) non-native aquatic plant species already established in the peninsula (32 species) and (2) those with the potential to invade the peninsula (40 species). The results revealed that the Iberian Peninsula contains a number of areas capable of hosting non-native aquatic plant species. Areas under anthropogenic pressure are at the greatest risk of invasion, and the variable most related to invasion risk is temperature. The results of this work were used to create the Invasion Risk Atlas for Alien Aquatic Plants in the Iberian Peninsula, a novel online resource that provides information about the potential distribution of non-native aquatic plant species. The atlas and this article are intended to serve as reference tools for the development of public policies, management regimes, and control strategies aimed at the prevention, mitigation, and eradication of non-native aquatic plant species.

Identifying the geographic distribution pattern of venomous snakes and regions of high snakebite risk in Iran

We describe species richness patterns of venomous snakes in Iran in order to produce snakebite risk prediction maps and identify gaps in regional health care centers capable of managing snakebites. We digitized distribution maps from the literature, Global Biodiversity Information Facility (GBIF), and the results of our own field studies of 24 terrestrial venomous snake species (including 4 endemic to Iran). Species richness patterns were associated with eight environmental factors. The variables have been extracted from the WorldClim dataset (bio12 = annual precipitation, bio15 = precipitation seasonality, bio17 = precipitation of the driest quarter, bio2 = mean diurnal range, bio3 = isothermality (bio2/bio7), bio4 = temperature seasonality, bio9 = mean temperature of the driest quarter and slope). Based on spatial analyses, species richness in Iran is highly affected by three environmental variables (bio12, 15, and 17) associated with precipitation. The relationship patterns among these predictors and species richness were strong and linear. The hotspot regions for venomous snakes species are concentrated on the western to southwestern and north to northeastern regions of Iran, which is partially consistent with the known Irano-Anatolian biodiversity hotspot. Because of the high number of endemic species and climatic conditions on the Iranian Plateau, the venoms of snakes distributed in those areas may contain novel properties and components.

An ensemble modeling approach to predict spatial risk patches of the Persian leopard-livestock conflicts in Lorestan Province, Iran

This study was conducted in the Lorestan Province in the west of Iran with two objectives of identifying major environmental variables in spatial risk modeling and identifying spatial risk patches of livestock predation by the Persian leopard. An ensemble approach of three models of maximum entropy (MaxEnt), generalized boosting model (GBM), and random forest (RF) were applied for spatial risk modeling. Our results revealed that livestock density, distance to villages, forest density, and human population density were the most important variables in spatial risk modeling of livestock predation by the leopard. The center of the study area had the highest probability of livestock predation by the leopard. Ten spatial risk patches of livestock predation by the leopard were identified in the study area. In order to mitigate the revenge killing of the leopards, the findings of this study highlight the imperative of implementing strategies by the Department of Environment (DoE) to effectively accompany the herds entering the wildlife habitats with shepherds and a manageable number of guarding dogs. Accordingly, the identified risk patches in this study deserve considerable attention, especially three primary patches found in the center and southeast of Lorestan Province.

Assessment of the impact of climate change on endangered conifer tree species by considering climate and soil dual suitability and interspecific competition

Climate change results in the habitat loss of many conifer tree species and jeopardizes species biodiversity and forest ecological functions. Delineating suitable habitats for tree species via climate niche model (CNM) is widely used to predict the impact of climate change and develop conservation and management strategies. However, the robustness of CNM is broadly debated as it usually does not consider soil and competition factors. Here we developed a new approach to combine soil variables with CNM and evaluate interspecific competition potential in the niche overlapping areas. We used an endangered conifer species - Chamaecyparis formosensis (red cypress) - as a case study to predict the impact of climate change. We developed a novel approach to integrate the climate niche model and soil niche model predictions and considered interspecific competition to predict the impacts of climate change on tree species. Our results show that the suitable habitat for red cypress would decrease significantly in the future with an additional threat from the competition of an oak tree species. Our approach and results may represent significant implications in making conservation strategies and evaluating the impacts of climate change, and providing the direction of the refinement of the ecological niche model.

Modeling climate change impacts on potential global distribution of Tamarixia radiata Waterston (Hymenoptera: Eulophidae)

The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama (Hemiptera: Liviidae), is an efficient vector of "Candidatus Liberibacter" species, the causative agents implicated in citrus greening or huanglongbing (HLB). HLB is the most devastating citrus disease and has killed millions of citrus trees worldwide. Classical biological control using Tamarixia radiata Waterston (Hymenoptera: Eulophidae) against ACP has been successful in some regions. Climatic conditions are critical in determining suitable areas for the geographical distribution of T. radiata. However, paucity of information on climate change impacts on the global spread of T. radiata restricts international efforts to manage ACP with T. radiata. We investigated the potential global distribution of T. radiata using 317 native and non-native occurrence records and 20 environmental data sets (with correlation coefficients (|r| > 0.7)). Using the Maximum Entropy model, these data were analyzed for two shared socioeconomic pathways (SSPs) and two time periods (2030s and 2050s). We showed that habitat suitability for T. radiata occurred in all continents except Antarctica. However, the highly suitable areas for T. radiata were found in parts of the Americas, Asia, Africa and Oceania. The climate suitable areas would increase until the 2050s. The predictions showed that mean temperature of coldest quarter and precipitation of warmest quarter were the most important environmental variables that influenced the distribution of T. radiata. The model reliably predicted habitat suitability for T. radiata, which can be adapted in classical biological control programs to effectively manage ACP in an environmentally friendly manner.

Current and future potential distribution of the invasive scale Ceroplastes rusci (L., 1758) (Hemiptera: Coccidae) under climate niche

BACKGROUND

The fig wax scale, Ceroplastes rusci is an invasive pest that feeds on more than 94 genera from 52 families that is spread across 60 countries, causing negative impacts to agriculture and forestry. Understanding the potential distribution of invasive species under climate change is crucial for the management and monitoring purposes. Thus, we predicted the potential distribution areas of C. rusci using Maximum Entropy (MaxEnt) based on the occurrence data and environmental variables under current and future climatic scenarios.

RESULTS

Our results showed that the temperature annual range (Bio 7) and mean temperature of the warmest quarter (Bio 10) attributed to a higher contribution to the current model of the distribution of C. rusci. The potential distribution maps illustrated the main concentrated areas of C. rusci which included South America, Africa, Asia, and Oceania. In addition, potential range expansions or reductions were predicted under different future climate change scenarios, which showed that the total suitable areas of the fig wax scale presented an increasing trend until 2100.

CONCLUSION

Our study provides significant data to understand the potential distribution of C. rusci around the world. It also serves as an early warning for the highly suitable habitat areas that even offers a platform to the currently non-infested regions or countries who are yet to develop monitoring strategies in response to the possible C. rusci outbreak. © 2022 Society of Chemical Industry.

A multi-method approach for assessing the distribution of a rare, burrowing North American crayfish species

Primary burrowing crayfishes face high extinction risk, but are challenging to study, manage, and conserve due to their difficult-to-sample habitat (i.e., terrestrial burrows) and low population densities. We apply here a variety of methods to characterize the distribution, habitat associations, and conservation status of the Boston Mountains Crayfish Cambarus causeyi (Reimer, 1966), an endemic burrowing crayfish found only in the Ozark Mountains of Arkansas, United States. We used species distribution modeling (SDM) on historic occurrence records to characterize the distribution and macro-scale habitat associations of this species. We then ground-truthed SDM predictions with conventional sampling, modeled fine-scale habitat associations with generalized linear models (GLM), and lastly developed and tested an environmental DNA (eDNA) assay for this species in comparison to conventional sampling. This represents, to our knowledge, the first successful eDNA assay for a terrestrial burrowing crayfish. Our MaxEnt-derived SDM found a strong effect of average annual precipitation on the historic distribution of C. causeyi, which occurred most frequently at locations with moderately high average annual precipitation (140-150 cm/yr) within our study region. Cambarus causeyi was difficult to detect by conventional sampling in 2019 and 2020, found at only 9 of 51 sites (17.6%) sampled by searching for and manually excavating crayfish burrows. Surprisingly, habitat suitability predicted from our MaxEnt models was not associated with contemporary C. causeyi occurrences per GLMs. Instead, C. causeyi presence was negatively associated with both sandy soils and the presence of other burrowing crayfish species. Poor SDM performance in this instance was likely caused by the omission of high resolution fine-scale habitat data (e.g., soils) and biotic interactions from MaxEnt models. Finally, our eDNA assay detected C. causeyi from six of 25 sites (24.0%) sampled in 2020, out-performing conventional surveys by burrow excavation for this species. Given the difficulty of studying primary burrowing crayfishes and their high conservation need, we propose that eDNA may become an increasingly important monitoring tool for C. causeyi and similar species.

Is the Endangered Species Act living to its full potential? The reassessment of the conservation status and recovery of Macbridea alba Chapm. as a case study

Since 1988, the Cooperative Endangered Species Conservation Fund or “Section 6” fund facilitates partnerships between the U.S. Fish and Wildlife Service and state agencies that aim to provide data pertinent to the recovery of Endangered Species Act (ESA) protected species. Despite the success of these efforts, research for rare plants is chronically underfunded and many species experience long periods of research inactivity that hinders their conservation. One example is Macbridea alba Chapm. (white birds-in-a-nest, Lamiaceae, M. alba from hereon), a federally threatened and state endangered mint endemic to four counties within the Florida panhandle. The species is a candidate for delisting after 30 years of protection under the ESA, however a lack of up-to-date data associated with the species has continually challenged the implementation of effective conservation programs and prolonged the recovery process. The focus of this paper is to review the timeline of recovery goals for M. alba, present a summary of recent research findings (i.e., species distribution models, habitat associations, reproductive ecology), and identify achievements as well as persistent obstacles to recovery and delisting. Our research focused on 5 of 10 recovery actions listed in the recovery plan for M. alba. Our findings provide updated data and make novel contributions to the protection of M. alba that will prioritize and improve management efforts. Overall, our work highlights frequent barriers to the recovery and delisting of rare species, using an endemic plant species as a case-study. Importantly, we outline effective methods for the rapid assessment of at-risk plant species that due to enduring data gaps, face an uncertain future in listing and recovery. We hope our work provides a convincing case demonstrating the critical need for current and expanded ESA funding and encourages a diversity of individuals and institutions to participate in critical rare plant research to swiftly fill research gaps and expedite recovery of some of the rarest plant species across the United States.

Climate and Land-Cover Change Impacts and Extinction Risk Assessment of Rare and Threatened Endemic Taxa of Chelmos-Vouraikos National Park (Peloponnese, Greece)

Chelmos-Vouraikos National Park is a floristic diversity and endemism hotspot in Greece and one of the main areas where Greek endemic taxa, preliminary assessed as critically endangered and threatened under the IUCN Criteria A and B, are mainly concentrated. The climate and land-cover change impacts on rare and endemic species distributions is more prominent in regional biodiversity hotspots. The main aims of the current study were: (a) to investigate how climate and land-cover change may alter the distribution of four single mountain endemics and three very rare Peloponnesian endemic taxa of the National Park via a species distribution modelling approach, and (b) to estimate the current and future extinction risk of the aforementioned taxa based on the IUCN Criteria A and B, in order to investigate the need for designing an effective plant micro-reserve network and to support decision making on spatial planning efforts and conservation research for a sustainable, integrated management. Most of the taxa analyzed are expected to continue to be considered as critically endangered based on both Criteria A and B under all land-cover/land-use scenarios, GCM/RCP and time-period combinations, while two, namely Alchemilla aroanica and Silene conglomeratica, are projected to become extinct in most future climate change scenarios. When land-cover/land-use data were included in the analyses, these negative effects were less pronounced. However, Silene conglomeratica, the rarest mountain endemic found in the study area, is still expected to face substantial range decline. Our results highlight the urgent need for the establishment of micro-reserves for these taxa.

Effects of climate-change scenarios on the distribution patterns of Castanea henryi

Castanea henryi, with edible nuts and timber value, is a key tree species playing essential roles in China's subtropical forest ecosystems. However, natural and human perturbations have nearly depleted its wild populations. The study identified the dominant environmental variables enabling and limiting its distribution and predicted its suitable habitats and distribution. The 212 occurrence records covering the whole distribution range of C. henryi in China and nine main bioclimatic variables were selected for detailed analysis. We applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate-change scenarios. The limiting factors for distribution were accessed by Jackknife, percent contribution, and permutation importance. We found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces. The modeling results indicated temperature as the critical determinant of distribution patterns, including mean temperature of the coldest quarter, isothermality, and mean diurnal range. Winter low temperature imposed an effective constraint on its spread. Moisture served as a secondary factor in species distribution, involving precipitation seasonality and annual precipitation. Under future climate-change scenarios, excellent habitats would expand and shift northwards, whereas range contraction would occur on the southern edge. Extreme climate change could bring notable range shrinkage. This study provided a basis for protecting the species' germplasm resources. The findings could guide the management, cultivation, and conservation of C. henryi, assisted by a proposed three-domain operation framework: preservation areas, loss areas, and new areas, each to be implemented using tailor-made strategies.

Assessment of suitable habitat of mangrove species for prioritizing restoration in coastal ecosystem of Sundarban Biosphere Reserve, India

Mangrove forests being the abode of diverse fauna and flora are vital for healthy coastal ecosystems. These forests act as a carbon sequester and protection shield against floods, storms, and cyclones. The mangroves of the Sundarban Biosphere Reserve (SBR), being one of the most dynamic and productive ecosystems in the world are in constant degradation. Hence, habitat suitability assessment of mangrove species is of paramount significance for its restoration and ecological benefits. The study aims to assess and prioritize restoration targets for 18 true mangrove species using 10 machine-learning algorithm-based habitat suitability models in the SBR. We identified the degraded mangrove areas between 1975 and 2020 by using Landsat images and field verification. The reserve was divided into 5609 grids using 1 km gird size for understanding the nature of mangrove degradation and collection of species occurrence data. A total of 36 parameters covering physical, environmental, soil, water, bio-climatic and disturbance aspects were chosen for habitat suitability assessment. Niche overlay function and grid-based habitat suitability classes were used to identify the species-based restoration prioritize grids. Habitat suitability analysis revealed that nearly half of the grids are highly suitable for mangrove habitat in the Reserve. Restoration within highly suitable mangrove grids could be achieved in the areas covered with less than 75 percent mangroves and lesser anthropogenic disturbance. The study calls for devising effective management strategies for monitoring and conserving the degraded mangrove cover. Monitoring and effective management strategies can help in maintaining and conserving the degraded mangrove cover. The model proves to be useful for assessing site suitability for restoring mangroves. The other geographical regions interested in assessing habitat suitability and prioritizing the restoration of mangroves may find the methodology adopted in this study effective.

The Fate of Endemic Species Specialized in Island Habitat under Climate Change in a Mediterranean High Mountain

Mediterranean high-mountain endemic species are particularly vulnerable to climatic changes in temperature, precipitation and snow-cover dynamics. Sierra Nevada (Spain) is a biodiversity hotspot in the western Mediterranean, with an enormous plant species richness and endemicity. Moehringia fontqueri is a threatened endemic plant restricted to north-facing siliceous rocks along a few ridges of the eastern Sierra Nevada. To guide conservation actions against climate change effects, here we propose the simultaneous assessment of the current reproductive success and the possible species' range changes between current and future climatic conditions, assessing separately different subpopulations by altitude. Reproductive success was tested through the seed-set data analysis. The species' current habitat suitability was modeled in Maxent using species occurrences, topographic, satellite and climatic variables. Future habitat suitability was carried out for two climatic scenarios (RCP 2.6 and 8.5). The results showed the lowest reproductive success at the lowest altitudes, and vice versa at the highest altitudes. Habitat suitability decreased by 80% from current conditions to the worst-case scenario (RCP 8.5). The lowest subpopulations were identified as the most vulnerable to climate change effects while the highest ones were the nearest to future suitable habitats. Our simultaneous assessment of reproductive success and habitat suitability aims to serve as a model to guide conservation, management and climate change mitigation strategies through adaptive management to safeguard the persistence of the maximum genetic pool of Mediterranean high-mountain plants threatened by climate change.

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Astragalus variabilis is a locoweed of northwest China that can seriously impede livestock development. However, it also plays various ecological roles, such as wind protection and sand fixation. Here, we used an optimized MaxEnt model to predict the distribution of suitable habitat of A. variabilis under current (1970-2000) conditions and future (2021-2080) climate change scenarios based on recent occurrence records. The most important environmental variables (suitability ranges in parentheses) affecting the distribution of A. variabilis were average maximum temperature of February (-2.12-5.34^°C), followed by total precipitation of June (2.06-37.33 mm), and topsoil organic carbon (0.36-0.69%). The habitat suitability of A. variabilis was significantly correlated with the frequency of livestock poisoning (p < 0.05). Under current climate conditions, the suitable environment of A. variabilis was distributed in central and western Inner Mongolia, Ningxia, central and northwestern Gansu, central and northwestern Qinghai, and the four basins around the Tianshan Mountains in Xinjiang. Under future climate conditions, the suitable habitat of A. variabilis shifted to higher latitudes and altitudes. No previous studies have used niche models to predict the suitable environment of this species nor analyzed the relationship between the habitat suitability of poisonous plants and the frequency of animal poisoning. Our findings provide new insights that will aid the prevention of livestock animal poisoning and the control of poisonous plants, promote the development of the livestock husbandry industry, and provide basic information that will facilitate the maintenance of the ecological balance of grassland ecosystems.

Past, present, and future predictions on the suitable habitat of the Slender racer (Orientocoluber spinalis) using species distribution models

Species distribution models (SDMs) across past, present, and future timelines provide insights into the current distribution of these species and their reaction to climate change. Specifically, if a species is threatened or not well-known, the information may be critical to understand that species. In this study, we computed SDMs for Orientocoluber spinalis, a monotypic snake genus found in central and northeast Asia, across the past (last interglacial, last glacial maximum, and mid-Holocene), present, and future (2070s). The goal of the study was to understand the shifts in distribution across time, and the climatic factors primarily affecting the distribution of the species. We found the suitable habitat of O. spinalis to be persistently located in cold-dry winter and hot summer climatic areas where annual mean temperature, isothermality, and annual mean precipitation were important for suitable habitat conditions. Since the last glacial maximum, the suitable habitat of the species has consistently shifted northward. Despite the increase in suitable habitat, the rapid alterations in weather regimes because of climate change in the near future are likely to greatly threaten the southern populations of O. spinalis, especially in South Korea and China. To cope with such potential future threats, understanding the ecological requirements of the species and developing conservation plans are urgently needed.

Forest tree species distribution for Europe 2000-2020: mapping potential and realized distributions using spatiotemporal machine learning

This article describes a data-driven framework based on spatiotemporal machine learning to produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill., Corylus avellana L., Fagus sylvatica L., Olea europaea L., Picea abies L. H. Karst., Pinus halepensis Mill., Pinus nigra J. F. Arnold, Pinus pinea L., Pinus sylvestris L., Prunus avium L., Quercus cerris L., Quercus ilex L., Quercus robur L., Quercus suber L. and Salix caprea L.) at high spatial resolution (30 m). Tree occurrence data for a total of three million of points was used to train different algorithms: random forest, gradient-boosted trees, generalized linear models, k-nearest neighbors, CART and an artificial neural network. A stack of 305 coarse and high resolution covariates representing spectral reflectance, different biophysical conditions and biotic competition was used as predictors for realized distributions, while potential distribution was modelled with environmental predictors only. Logloss and computing time were used to select the three best algorithms to tune and train an ensemble model based on stacking with a logistic regressor as a meta-learner. An ensemble model was trained for each species: probability and model uncertainty maps of realized distribution were produced for each species using a time window of 4 years for a total of six distribution maps per species, while for potential distributions only one map per species was produced. Results of spatial cross validation show that the ensemble model consistently outperformed or performed as good as the best individual model in both potential and realized distribution tasks, with potential distribution models achieving higher predictive performances (TSS = 0.898, R2 logloss = 0.857) than realized distribution ones on average (TSS = 0.874, R2 logloss = 0.839). Ensemble models for Q. suber achieved the best performances in both potential (TSS = 0.968, R2 logloss = 0.952) and realized (TSS = 0.959, R2 logloss = 0.949) distribution, while P. sylvestris (TSS = 0.731, 0.785, R2 logloss = 0.585, 0.670, respectively, for potential and realized distribution) and P. nigra (TSS = 0.658, 0.686, R2 logloss = 0.623, 0.664) achieved the worst. Importance of predictor variables differed across species and models, with the green band for summer and the Normalized Difference Vegetation Index (NDVI) for fall for realized distribution and the diffuse irradiation and precipitation of the driest quarter (BIO17) being the most frequent and important for potential distribution. On average, fine-resolution models outperformed coarse resolution models (250 m) for realized distribution (TSS = +6.5%, R2 logloss = +7.5%). The framework shows how combining continuous and consistent Earth Observation time series data with state of the art machine learning can be used to derive dynamic distribution maps. The produced predictions can be used to quantify temporal trends of potential forest degradation and species composition change.

A UAS and Machine Learning Classification Approach to Suitability Prediction of Expanding Natural Habitats for Endangered Flora Species

In this study, we propose integrating unmanned aerial systems (UASs) and machine learning classification for suitability prediction of expanding habitats for endangered flora species to prevent further extinction. Remote sensing imaging of the protected steppe-like grassland in Bilje using the DJI P4 Multispectral UAS ensured non-invasive data collection. A total of 129 individual flora units of five endangered flora species, including small pasque flower (Pulsatilla pratensis (L.) Miller ssp. nigricans (Störck) Zämelis), green-winged orchid (Orchis morio (L.)), Hungarian false leopardbane (Doronicum hungaricum Rchb.f.), bloody cranesbill (Geranium sanguineum (L.)) and Hungarian iris (Iris variegate (L.)) were detected and georeferenced. Habitat suitability in the projected area, designated for the expansion of the current area of steppe-like grassland in Bilje, was predicted using the binomial machine learning classification algorithm based on three groups of environmental abiotic criteria: vegetation, soil, and topography. Four machine learning classification methods were evaluated: random forest, XGBoost, neural network, and generalized linear model. The random forest method outperformed the other classification methods for all five flora species and achieved the highest receiver operating characteristic (ROC) values, ranging from 0.809 to 0.999. Soil compaction was the least favorable criterion for the habitat suitability of all five flora species, indicating the need to perform soil tillage operations to potentially enable the expansion of their coverage in the projected area. However, potential habitat suitability was detected for the critically endangered flora species of Hungarian false leopardbane, indicating its habitat-related potential for expanding and preventing further extinction. In addition to the current methods of predicting current coverage and population count of endangered species using UASs, the proposed method could serve as a basis for decision making in nature conservation and land management.

MaxEnt Modelling and Impact of Climate Change on Habitat Suitability Variations of Economically Important Chilgoza Pine (Pinus gerardiana Wall.) in South Asia

Chilgoza pine is an economically and ecologically important evergreen coniferous tree species of the dry and rocky temperate zone, and a native of south Asia. This species is rated as near threatened (NT) by the International Union for Conservation of Nature (IUCN). This study hypothesized that climatic, soil and topographic variations strongly influence the distribution pattern and potential habitat suitability prediction of Chilgoza pine. Accordingly, this study was aimed to document the potential habitat suitability variations of Chilgoza pine under varying environmental scenarios by using 37 different environmental variables. The maximum entropy (MaxEnt) algorithm in MaxEnt software was used to forecast the potential habitat suitability under current and future (i.e., 2050s and 2070s) climate change scenarios (i.e., Shared Socio-economic Pathways (SSPs): 245 and 585). A total of 238 species occurrence records were collected from Afghanistan, Pakistan and India, and employed to build the predictive distribution model. The results showed that normalized difference vegetation index, mean temperature of coldest quarter, isothermality, precipitation of driest month and volumetric fraction of the coarse soil fragments (>2 mm) were the leading predictors of species presence prediction. High accuracy values (>0.9) of predicted distribution models were recorded, and remarkable shrinkage of potentially suitable habitat of Chilgoza pine was followed by Afghanistan, India and China. The estimated extent of occurrence (EOO) of the species was about 84,938 km2, and the area of occupancy (AOO) was about 888 km2, with 54 major sub-populations. This study concluded that, as the total predicted suitable habitat under current climate scenario (138,782 km2) is reasonably higher than the existing EOO, this might represent a case of continuous range contraction. Hence, the outcomes of this research can be used to build the future conservation and management plans accordingly for this economically valuable species in the region.

Modeling climate change effects on spatial distribution of wild Aegilops L. (Poaceae) toward food security management and biodiversity conservation in Iran

The demand for food resources is increasing quickly because human populations are growing; therefore, food security may become one of the largest human challenges of this century. Crop wild relatives (CWRs) are the most valuable plant genetic resources (PGR) for the conservation of genetic diversity in crops. However, climate change is an added pressure on biodiversity, particularly on this valuable group of plants. It is predicted that more than 50% of this group may be lost by 2055 as a result of the effects of climate change. Iran ranks high in the world in its conservation priorities for CWRs. This study investigates the impacts of climate change on Aegilops L. as important CWRs. MaxEnt was applied to predict the spatial distribution of seven Aegilops species under different climatic scenarios (RCP 2.6 and RCP 8.5) of 2050 and 2080. According to the findings, all species exhibited reduction or expansion responses under all of the above-mentioned climatic scenarios. However, the range change was negative for some species (i.e., Aegilops columnaris, Aegilops cylindrica, Aegilops speltoides, Aegilops tauschii [in all scenarios of 2050 and 2080], and Aegilops kotschyi [RCP 2.6 2050 and 2080]), and positive for others (i.e., Aegilops crassa, Aegilops triuncialis [in all scenarios of 2050 and 2080], and Aegilops kotschyi [RCP 8.5 2050 and 2080]). The results of this study emphasize the need for conservation plans for the country's genetic resources, including regular monitoring and assessment of ecological and demographic changes. Integr Environ Assess Manag 2022;18:697-708. © 2021 SETAC.

Climate Change Impacts and Extinction Risk Assessment of Nepeta Representatives (Lamiaceae) in Greece

The ongoing climate change has already left its imprint on species distributions, with rare, endemic species being more threatened. These changes are more prominent in regional biodiversity hotspots, such as Greece, which is already facing the short term impacts of human induced climate change. Greek flora hosts numerous endemic medicinal and aromatic plant taxa (MAPs), which are economically important and provide integral ecosystem services. The genus Nepeta is one of the largest Lamiaceae genera, containing several MAPs, yet, despite its taxonomical and economical significance, it remains vastly understudied in Greece. We explore the effects of climate change on the range of the Greek endemic Nepeta MAPs, via a species distribution models (SDMs) approach in an ensemble modeling framework, using soil, topographical and bioclimatic variables as predictors in three different time steps. By doing so, we attempt to estimate the current and future extinction risk of these taxa and to locate their current and future species richness hotspots in Greece. The taxa analyzed are expected to experience severe range retractions, with minor intraspecific variation across all time steps (p > 0.05), driven mainly by soil- and aridity-related variables. The extinction risk status of only one taxon is predicted to worsen in the future, while all other taxa will remain threatened. Current species richness hotspots are mainly located in southern Greece and are projected to shift both altitudinally and latitudinally over time (p < 0.01).

Modeling habitat suitability of bats to identify high priority areas for field monitoring and conservation

Bats provide important ecosystem services but face severe threats due to land and climate changes. Although bats are an important component of mammal diversity in Iran, the ecology of many species remains virtually unstudied in the country. Here we applied the maximum entropy approach to model habitat suitability of bat species in Iran, identify the most important variables for their distribution, predict high priority areas for field monitoring and conservation, and estimate the coverage of the bat species' suitable habitats by the existing protected areas. We created a richness map for the twelve species to identify high priority areas for field monitoring and conservation. The results of species distribution modeling showed that Pipistrellus kuhlii (828,977.2 km²) and Miniopterus pallidus (646,581.9 km²) had the largest distribution ranges and Rhinopoma microphyllum (211,202.7 km²) and Rousettus aegyptiacus (218,278.6 km²) had the smallest distribution ranges in Iran. By averaging the importance of each ecological variable across the 12 species, we found that distance to forests (with a negative association) is the most important ecological driver of bat distribution in Iran. The Zagros Mountains were identified as a hotspot of bats based on the distribution of the 12 species. Our findings showed that small proportions of each species suitable habitats were covered by protected areas and protected suitable habitats varied from 3.2%for Pipistrellus kuhlii to15.9% for Tadarida teniotis. This study highlights the importance of forests for bat conservation showing that forest conservation is a high priority in the country. Areas which have the highest richness should be prioritized for field monitoring and conservation.

Identifying Potential Planting Sites for Three Non-Native Plants to Be Used for Soil Rehabilitation in the Tula Watershed

The Tula watershed in Mexico, located in a semiarid and sub-humid climate zone, is experiencing intensive population growth, the expansion of mining concessions for construction materials, and agricultural and urban development, resulting in the degradation of soils and vegetation and a greater demand on natural resources. The aims of this study were to evaluate the survival rates and identify potential habitats within the Tula watershed for planting three non-native forage species (Atriplex canescens, Cynodon dactylon, and Leucaena collinsii) using the Kaplan-Meier estimator and the MaxEnt model with the purpose of rehabilitating degraded soils via agroforestry systems. There were 19 edaphoclimatic variables used and the occurrences of three species, obtained from the GBIF, MEXU, and SNIB databases. The models generated with MaxEnt were very accurate (area under the curve [AUC] ≥ 0.7). The species Atriplex canescens and Cynodon dactylon showed areas of potential planting sites (>0.4) and high survival rates (80% and 92%, respectively). The species Leucaena collinsii presented areas with lower potential planting (<0.4) but registered the greater survival rate (100%). The results provide a solid basis to evaluate the survival rates of forage species within potential planting sites in the Tula watershed using agroforestry systems to rehabilitate degraded soils.

Setting the priorities straight - Species distribution models assist to prioritize conservation targets for the mangroves

Mangrove forests provide a wide range of ecosystem services, yet they are declining rapidly due to climate change and human activities. Identification of conservation priority targets across spatial and temporal scales may assist in planning and decision making, especially in areas having rich mangrove diversity but with limited response capacity. In this study, we aimed to identify the species and areas which should be prioritized for conservation in the Indo-West Pacific (IWP) region, one of the two global hotspots of mangroves. We used an ensemble species distribution modelling framework to map the potential distribution of ten species, including true mangroves and mangrove associates, in current, past, and future environmental conditions. The priority targets were then identified through a weighted-scoring approach with the current distribution and the modelled outputs. Our study revealed that precipitation and surface elevation could influence the distribution of the true mangroves, while the temperature was the important variable for the mangrove associates. Although suitable habitat for the mangroves is predicted to increase in future, primarily due to the northward range expansion of six species, areas with high species richness would decrease. We found 7.09% and 4.16% areas of the IWP should be prioritized for conservation of the true mangroves and mangrove associates, respectively. The characteristics of these priority sites indicated that the inclusion of the anthropogenic component in the conservation framework and species-targeted management plans in the protected areas are required for the effective implementation of conservation actions. Five of the studied species, namely Acanthus ilicifolius, Dolichandrone spathacea, Heritiera littoralis, Pemphis acidula and Xylocarpus granatum, were found to have the highest priority score for conservation. The glacial refugia of the species, mostly distributed in the Philippines, New Guinea, southern India and Madagascar, should be explored further for species-specific conservation actions.

Comparative Genomics, Phylogenetics, Biogeography, and Effects of Climate Change on Toddalia asiatica (L.) Lam. (Rutaceae) from Africa and Asia

In the present study, two samples of Toddalia asiatica species, both collected from Kenya, were sequenced and comparison of their genome structures carried out with T. asiatica species from China, available in the NCBI database. The genome size of both species from Africa was 158, 508 base pairs, which was slightly larger, compared to the reference genome of T. asiatica from Asia (158, 434 bp). The number of genes was 113 for both species from Africa, consisting of 79 protein-coding genes, 30 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes. Toddalia asiatica from Asia had 115 genes with 81 protein-coding genes, 30 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes. Both species compared displayed high similarity in gene arrangement. The gene number, orientation, and order were highly conserved. The IR/SC boundary structures were the same in all chloroplast genomes. A comparison of pairwise sequences indicated that the three regions (trnH-psbA, rpoB, and ycf1) were more divergent and can be useful in developing effective genetic markers. Phylogenetic analyses of the complete cp genomes and 79 protein-coding genes indicated that the Toddalia species collected from Africa were sister to T. asiatica collected from Asia. Both species formed a sister clade to the Southwest Pacific and East Asian species of Zanthoxylum. These results supported the previous studies of merging the genus Toddalia with Zanthoxylum and taxonomic change of Toddalia asiatica to Zanthoxylum asiaticum, which should also apply for the African species of Toddalia. Biogeographic results demonstrated that the two samples of Toddalia species from Africa diverged from T. asiatica from Asia (3.422 Mya, 95% HPD). These results supported an Asian origin of Toddalia species and later dispersal to Africa and Madagascar. The maxent model analysis showed that Asia would have an expansion of favorable areas for Toddalia species in the future. In Africa, there will be contraction and expansion of the favorable areas for the species. The availability of these cp genomes will provide valuable genetic resources for further population genetics and biogeographic studies of these species. However, more T. asiatica species collected from a wide geographical range are required.

Comparative Genomics, Phylogenetics, Biogeography, and Effects of Climate Change on Toddalia asiatica (L.) Lam. (Rutaceae) from Africa and Asia

In the present study, two samples of Toddalia asiatica species, both collected from Kenya, were sequenced and comparison of their genome structures carried out with T. asiatica species from China, available in the NCBI database. The genome size of both species from Africa was 158, 508 base pairs, which was slightly larger, compared to the reference genome of T. asiatica from Asia (158, 434 bp). The number of genes was 113 for both species from Africa, consisting of 79 protein-coding genes, 30 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes. Toddalia asiatica from Asia had 115 genes with 81 protein-coding genes, 30 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes. Both species compared displayed high similarity in gene arrangement. The gene number, orientation, and order were highly conserved. The IR/SC boundary structures were the same in all chloroplast genomes. A comparison of pairwise sequences indicated that the three regions (trnH-psbA, rpoB, and ycf1) were more divergent and can be useful in developing effective genetic markers. Phylogenetic analyses of the complete cp genomes and 79 protein-coding genes indicated that the Toddalia species collected from Africa were sister to T. asiatica collected from Asia. Both species formed a sister clade to the Southwest Pacific and East Asian species of Zanthoxylum. These results supported the previous studies of merging the genus Toddalia with Zanthoxylum and taxonomic change of Toddalia asiatica to Zanthoxylum asiaticum, which should also apply for the African species of Toddalia. Biogeographic results demonstrated that the two samples of Toddalia species from Africa diverged from T. asiatica from Asia (3.422 Mya, 95% HPD). These results supported an Asian origin of Toddalia species and later dispersal to Africa and Madagascar. The maxent model analysis showed that Asia would have an expansion of favorable areas for Toddalia species in the future. In Africa, there will be contraction and expansion of the favorable areas for the species. The availability of these cp genomes will provide valuable genetic resources for further population genetics and biogeographic studies of these species. However, more T. asiatica species collected from a wide geographical range are required.

The Current and Future Potential Geographical Distribution and Evolution Process of Catalpa bungei in China

Catalpa bungei C. A. Mey. (C. bungei) is one of the recommended native species for ecological management in China. It is a fast-growing tree of high economic and ecological importance, but its rare resources, caused by anthropogenic destruction and local climatic degradation, have not satisfied the requirements. It has been widely recommended for large-scale afforestation of ecological management and gradually increasing in recent years, but the impact mechanism of climate change on its growth has not been studied yet. Studying the response of species to climate change is an important part of national afforestation planning. Based on combinations of climate, topography, soil variables, and the multiple model ensemble (MME) of CMIP6, this study explored the relationship between C. bungei and climate change, then constructed Maxent to predict its potential distribution under SSP126 and SSP585 and analyzed its dominant environmental factors. The results showed that C. bungei is widely distributed in Henan, Hebei, Hubei, Anhui, Jiangsu, and Shaanxi provinces and others where it covers an area of 2.96 × 106 km2. Under SSP126 and SSP585, its overall habitat area will increase by more than 14.2% in 2080–2100, which mainly indicates the transformation of unsuitable areas into low suitable areas. The center of its distribution will migrate to the north with a longer distance under SSP585 than that under SSP126, and it will transfer from the junction of Shaanxi and Hubei province to the north of Shaanxi province under SSP585 by 2100. In that case, C. bungei shows a large-area degradation trend in the south of the Yangtze River Basin but better suitability in the north of the Yellow River Basin, such as the Northeast Plain, the Tianshan Mountains, the Loess Plateau, and others. Temperature factors have the greatest impact on the distribution of C. bungei. It is mainly affected by the mean temperature of the coldest quarter, followed by precipitation of the wettest month, mean diurnal range, and precipitation of the coldest quarter. Our results hence demonstrate that the increase of the mean temperature of the coldest quarter becomes the main reason for its degradation, which simultaneously means a larger habitat boundary in Northeast China. The findings provide scientific evidence for the ecological restoration and sustainable development of C. bungei in China.

Predicting potential distribution and evaluating biotic interactions of threatened species: a case study of Discocactus ferricola (Cactaceae)

Abstract: Information on distribution, number of populations, and biotic interactions are essential for assessing the threat status of species and to establish more effective conservation initiatives. Ecological niche modeling have been successfully applied to identify the potential distribution, even for rare species that have few recorded occurrence points. In this study, we evaluated the potential distribution and additionally generated the first data on the reproductive biology of Discocactus ferricola, due to its degree of threat and the absence of ecological data for that species. The potential distribution map highlighted areas with higher probability of occurrence of D. ferricola on the Residual Plateau of Maciço do Urucum located in Mato Grosso do Sul, Brazil. The occurrence of D. ferricola populations was limited to outcrops of flat ironstone (cangas) distributed in patches across the landscape, increasing the chances of serious threats, such as habitat loss due to mining and species extraction. We also found that D. ferricola is xenogamous. Therefore, in situ conservation actions must prioritize the maintenance of interactions with pollinators by preserving the flora and fauna of rocky outcrops and adjacent forests in areas of greater environmental suitability for D. ferricola. Our study highlights the use of ecological niche modeling and data on biotic interactions to evaluate species potential distribution, to guide new sampling efforts, and to assist conservation and management initiatives.

Mapping the occurrence and spatial distribution of noxious weed species with multisource data in degraded grasslands in the Three-River Headwaters Region, China

The invasion of noxious weed species has long been associated with the degradation of alpine grasslands ecosystems. However, traditional in situ-based methods for surveying noxious weed species are generally time consuming and inefficient over large-scale areas. This paper investigates the possibility of applying multisource data to map the occurrence and spatial distribution of noxious weed species in degraded alpine grasslands in the Three-River Headwaters Region, China. Sentinel-2 image-related vegetation indices (VIs), field sample data and environmental variables were integrated to build a noxious weed species detection model based on the maximum entropy (MaxEnt) species modeling framework. The modeling results suggest that based on both training and testing AUC (area under the receiver operating characteristic (ROC) curve) values higher than 0.82, the VI-only variable model, the environmental-only variable model and the combined environmental and VI variables model, all yielded good simulation results. The spatial distributions of noxious weed species mapped by the VI-only variable model and the combined environmental and VI variable model were more concentrated, while the VI-only variable model yielded more scattered results. This analysis also explains why noxious weed species are mainly distributed in the low-elevation flat riverine zone in the study area. The model combining Sentinel-2 imagery-related VIs, environmental variables and in situ sample data proposed in this study can successfully map the occurrence and spatial distributions of noxious weed species. The method and results of this research can be used to help monitor noxious weed species invasions and better manage grassland ecosystems.

The potential habitat of desert locusts is contracting: predictions under climate change scenarios

Desert locusts are notorious for their widespread distribution and strong destructive power. Their influence extends from the vast arid and semiarid regions of western Africa to northwestern India. Large-scale locust outbreaks can have devastating consequences for food security, and their social impact may be long-lasting. Climate change has increased the uncertainty of desert locust outbreaks, and predicting suitable habitats for this species under climate change scenarios will help humans deal with the potential threat of locust outbreaks. By comprehensively considering climate, soil, and terrain variables, the maximum entropy (MaxEnt) model was used to predict the potential habitats of solitary desert locusts in the 2050s and 2070s under the four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. The modeling results show that the average area under the curve (AUC) and true skill statistic (TSS) reached 0.908 ± 0.002 and 0.701, respectively, indicating that the MaxEnt model performed extremely well and provided outstanding prediction results. The prediction results indicate that climate change will have an impact on the distribution of the potential habitat of solitary desert locusts. With the increase in radiative forcing overtime, the suitable areas for desert locusts will continue to contract, especially in the 2070s under the SSP585 scenario, and the moderately and highly suitable areas will decrease by 0.88 × 10⁶ km² and 1.55 × 10⁶ km², respectively. Although the potentially suitable area for desert locusts is contracting, the future threat posed by the desert locust to agricultural production and food security cannot be underestimated, given the combination of maintained breeding areas, frequent extreme weather events, pressure from population growth, and volatile sociopolitical environments. In conclusion, methods such as monitoring and early warning, financial support, regional cooperation, and scientific prevention and control of desert locust plagues should be further implemented.