Potentially Suitable Area and Change Trends of Tulipa iliensis under Climate Change

Tulipa iliensis,as a wild plant resource,possesses high ornamental value and can provide abundant parental materials for tulip breeding.The objective of this research was to forecast the worldwide geographical spread of Tulipa iliensis by considering bioclimatic,soil,and topographic variables,the findings of this research can act as a benchmark for the conservation,management,and utilization of Tulipa iliensis as a wild plant resource.Research results indicate that all 12 models have an area under curve(AUC)of the receiver operating characteristic curve(ROC)values greater than 0.968 for the paleoclimatic,current,and future climate scenarios,this suggests an exceptionally high level of predictive accuracy for the models.The distribution of Tulipa iliensis is influenced by several key factors.These factors include the mean temperature of the driest quarter(Bio9),calcium carbonate content(T_CACO3),slope,precipitation of the driest month(Bio14),Basic saturation(T_BS),and precipitation of the coldest quarter(Bio19).During the three paleoclimate climate scenarios,the appropriate habitats for Tulipa iliensis showed a pattern of expansion-contraction expansion.Furthermore,the total suitable area accounted for 13.38%,12.28%,and 13.28%of the mainland area,respectively.According to the current climate scenario,the High-suitability area covers 61.78472×10^(4)km^(2),which accounts for 6.57%of the total suitable area,The Midsuitability area covers 190.0938×10^(4)km^(2),accounting for 20.2%of the total suitable area,this represents a decrease of 63.53%~67.13%compared to the suitable area of Tulipa iliensis under the paleoclimate scenario.Under the Shared Socioeconomic Pathways(SSP)scenarios,in 2050 and 2090,Tulipa iliensis is projected to experience a decrease in the High,Mid,and Low-suitability areas under the SSP126 climate scenario by 7.10%~12.96%,2.96%~4.27%and 4.80%~7.96%,respectively.According to the SSP245 scenario,the high suitability area experienced a slight expansion of 2.26%in 2050,but a reduction of 6.32%in 2090.In the SSP370 scenario,the High-suitability areas had a larger reduction rate of 11.24%in 2050,while the Mid-suitability and Low-suitability areas had smaller expansion rates of 0.36%and 4.86%,respectively.In 2090,the High-suitability area decreased by 4.84%,while the Mid and Low-suitability areas experienced significant expansions of 15.73%and 45.89%,respectively.According to the SSP585 scenario,in the future,the High,Mid,and Low-suitability areas are projected to increase by 5.09%~7.21%,7.57%~17.66%,and 12.30%~48.98%,respectively.The research offers enhanced theoretical direction for preserving Tulipa iliensis’genetic variety amidst evolving climatic scenarios.

Modeling habitat suitability of range plant species using random forest method in arid mountainous rangelands

Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.

Community Characteristics of Wild Fruit Forests Along Elevation Gradients and the Relationships Between the Wild Fruit Forests and Environments in the Keguqin Mountain Region ofⅠii

In this paper,the quantitative relationship between the wild fruit communities and direct environmental factors is discussed on the basis of detailed data on landscape scale habitats obtained through field vegetation investigation.The results from TWINSPAN and DCCA showed that:1) In the distribution sections of the wild fruit forest in the Keguqin Mountain region,the basic patterns characteristic of the different habitats are due to topographic factors,nutrients and moisture conditions;2) The elevation affected the most basic differentiation of plant communities in the study area,indicating that the elevation condition was the most important factor restricting the distribution of the wild fruit communities in the study area;3) The close relationship between the moisture content in the upper soil layer and the elevation reflected the influence of moisture conditions on both wild fruit and herb-layer communities;4) Nutrient differences not only indicated that the habitat conditions were different in themselves but also showed that the present nutrient conditions of the habitats were seriously affected by human activities.In summary,under complicated mountainous topographic conditions,the habitat conditions for the communities differed very significantly,and the combination of elevation,soil moisture content,total nitrogen,slope aspect,and pH value influenced and controlled the formation of community distribution patterns in the study area.

Sea Turtle Nesting: What Is Known and What Are the Challenges under a Changing Climate Scenario

The rate of climate change experienced globally in recent decades may compromise sea turtles’ survival;especially temperature increase, which is particularly fast, impacts life history characteristics, such as temperature-dependent sex determination (TSD), late maturity and sea turtles highly migratory nature. This review aims to identify and summarize the information that has been collected from 2009-2020 in order to aid future empirical studies that seek to fill these and other knowledge gaps, and subsequently assist conservationists in making multilevel decisions to protect sea turtle populations and species. In a summarized way the general knowledge acquired so far on the influence of environmental abiotic and biotic factors on nesting behaviour and hatching, emergence and survival successes of sea turtle hatchlings, was gathered. To accomplish this work, a search on Web of Science, Science Direct, NCBI/PubMed, and Google Scholar was carried out using the terms “sea turtles + climate change”. Published articles in the period 2009-2020 were selected, related to the nesting ecology of 5 species of sea turtles: Caretta caretta, Eretmochelys imbricata, Dermochelys coriacea, Chelonia mydas, Lepidochelys olivacea. Emphasis was also placed on geographical information and on population location (e.g. climatic conditions during the nesting season). These articles (N = 126) were analysed giving relevance to researcher’s data interpretations, comparisons with other researches, and the reached conclusions. An attempt was made to represent all 5 species of sea turtles when selecting articles on each of the environmental factors that influence sea turtle nesting: temperature, humidity, nesting substrate, gases, depth of the nest, sea surface temperature (SST), nest location on the beach, nesting phenology and geographic distribution of nesting habitats. The interaction between these parameters and their consequences on the terrestrial phase of reproduction are presented and discussed.

Modeling habitat distribution of Cornus officinalis with Maxent modeling and fuzzy logics in China

Aims Predicting suitable habitat distribution is an effective way to protect rare or endangered medicinal plants.Cornus officinalis is a perennial tree growing in forest edge and its air-dried pericarp is one of the traditional Chinese medicines(TCM)with significant medicinal values.In recent years,C.officinalis has undergone severe degeneration of its natural habitat owing to growing market demands and unprecedented damage to the forests.Moreover,the degeneration of suitable habitat has threatened the supply of medicinal materials,and even led to the extinction of some engendered medicinal plant species.In this case,there is a great risk to introduce and cultivate medicinal plants if planners determine the suitable cultivation regions based on personal subjective experience alone.Therefore,predicting suitable potential habitat distribution of medicinal plants(e.g.C.officinalis)and revealing the environmental factors determining such distribution patterns are important to habitat conservation and environmental restoration.Methods In this article,we report the results of a study on the habitat distribution of C.officinalis using maximum entropy(Maxent)modeling and fuzzy logics together with loganin content and environmental variables.The localities of 106 C.officinalis in China were collected by our group and other researchers and used as occurrence data.The loganin content of 234 C.officinalis germplasm resources were tested by high-performance liquid chromatography(HPLC)and used as content data.79 environmental variables were selected and processed with multicollinearity test by using Pearson Correlation Coefficient(r)to determine a set of independent variables.The chosen variables were then processed in the fuzzy linear model according to the cell values(maximum,minimum)of localities with estimated loganin content.The SDMtoolbox was used to spatially rarefy occurrence data and prepare bias files.Furthermore,combined Maxent modeling and fuzzy logics were used to predict the suitable habitat of C.officinalis.The modeling result was validated using null-model method.Important Findings As a result,six environmental factors including tmin3,prec3,bio4,alt,bio12 and bio3 were determined as key influential factors that mostly affected both the habitat suitability and active ingredient of C.officinalis.The highly suitable regions of C.officinalis mainly distribute in a‘core distribution zone’of the east-central China.The statistically significant AUC value indicated that combined Maxent modeling and fuzzy logics could be used to predict the suitable habitat distribution of medicinal plants.Furthermore,our results confirm that ecological factors played critical roles in assessing suitable geographical regions as well as active ingredient of plants,highlighting the need for effective habitat rehabilitation and resource conservation.

The impact of burning on lion Panthera leo habitat choice in an African savanna

Camivores play a central role in ecosystem processes by exerting top-down control, while fire exerts bottom-up con- trol in ecosystems throughout the world, yet, little is known about how fire affects short-term carnivore distributions across the landscape. Through the use of a long-term data set we investigated the distribution of lions, during the daytime, in relation to burned areas in Serengeti National Park, Tanzania. We found that lions avoid burned areas despite the fact that herbivores, their prey, are attracted to burned areas. Prey attraction, however, likely results from the reduction in cover caused by burning, that may thereby decrease lion hunting success. Lions also do not preferentially utilize the edges of burned areas over unburned areas de- spite the possibility that edges would combine the benefit of cover with proximity to abundant prey. Despite the fact that lions avoid burned areas, lion territory size and reproductive success were not affected by the proportion of the territory burned each year. Therefore, burning does not seem to reduce lion fitness perhaps because of the heterogeneity of burned areas across the landscape or because it is possible that when hunting at night lions visit burned areas despite their daytime avoidance of these ar- eas .

Habitat use and demography of Mus musculus in a rural landscape of Argentina

The main goal of the paper was to determine the habitat distribution of the house mouse(Mus musculus)within a rural landscape of Buenos Aires province,Argentina.We also studied the seasonal variation in abundance and reproductive activity.The habitats studied were poultry farms,human houses in a small village,cropfields,pastures,cropfield and pasture edges,riparian habitats(streams),railway embankments and woodlots.We captured 817 M.musculus and 690 individuals of 5 native rodent species.M.musculus was captured in poultry farms,houses,riparian habitats,cropfield and borders,but it showed a significantly higher abundance in poultry farms compared to the other habitats.Its presence outside poultry farms was significantly related to the distance to streams and poultry farms.The mean trapping success index of M.musculus did not show significant variations between periods,but the proportion of active males was significantly higher in the spring-summer period than in the autumn-winter period.All captures of M.musculus in cropfields,borders and riparian habitats occurred in the spring-summer period.The capture of M.musculus in many types of habitats suggests that it can disperse outside poultry farms,and streams may be used as corridors.