Distribution Of Suitable Habitat Research Articles

Prediction of Potential Suitable Distribution Areas for an Endangered Salamander in China.

Climate change has been considered to pose critical threats for wildlife. During the past decade, species distribution models were widely used to assess the effects of climate change on the distribution of species' suitable habitats. Among all the vertebrates, amphibians are most vulnerable to climate change. This is especially true for salamanders, which possess some specific traits such as cutaneous respiration and low vagility. The Wushan salamander (Liua shihi) is a threatened and protected salamander in China, with its wild population decreasing continuously. The main objective of this study was to predict the distribution of suitable habitat for L. shihi using the ENMeval parameter-optimized MaxEnt model under current and future climate conditions. Our results showed that precipitation, cloud density, vegetation type, and ultraviolet radiation were the main environmental factors affecting the distribution of L. shihi. Currently, the suitable habitats for L. shihi are mainly concentrated in the Daba Mountains, including northeastern Chongqing and western Hubei Provinces. Under the future climate conditions, the area of suitable habitats increased, which mainly occurred in central Guizhou Province. This study provided important information for the conservation of L. shihi. Future studies can incorporate more species distribution models to better understand the effects of climate change on the distribution of L. shihi.

Deteriorating habitat suitability and connectivity of waterbirds in the Bohai Sea Rim: Consequences of land use transformation

Wetlands in the Bohai Sea Rim play an indispensable role in maintaining the stability of waterbird populations on the East Asian-Australian flyway. However, motivated by economic development and urban expansion, coastal wetlands in this region have been extensively reclaimed, leading to a decline in the area and degradation of natural wetlands over the past two decades. We analyzed the temporal and spatial changes of suitable habitats of different groups of waterbirds and quantified habitat connectivity changes and the importance of different patches by using the Probability of Connectivity. The results show that the suitable habitat area of all the different groups of waterbirds decreased sharply from 2000 to 2020. In addition, the utilization ratio by waterbirds of artificial habitats increased. Land use is the primary environmental variable determining the distribution of suitable habitats. Meanwhile, the connectivity of habitats of different groups of waterbirds has also been declining. However, the patches of Tianjin and Hebei in Bohai Bay still have high importance for waterbirds, particularly shorebirds. Expanding existing protection areas to cover the above-mentioned patches is recommended. We also advocate stricter protection measures and necessary ecological restoration activities on both the natural and artificial wetlands.

Genetic structure of ten Artemia populations from China: cumulative effects of ancient geological events, climatic changes, and human activities

This study investigated the population genetics and distribution patterns of Artemia populations from ten inland salt lakes in China. A total of 1,274,698 Artemia single nucleotide polymorphisms (SNPs) were identified. The results showed that these populations could be geographically and genetically divided into four distinct groups, and that the Tibetan populations were further divided into two subpopulations with a trend of decreasing genetic diversity from west to east. The Tibetan population had the highest genetic diversity, whereas the Shanxi population had the lowest. There was moderate genetic differentiation between the Tibetan populations and greater genetic differentiation between the Xinjiang and Shanxi populations. IBD (isolation by distance) suggested that geographical isolation contributes to genetic differentiation. In addition, there was some degree of gene flow among the ten populations, with A. sinica showing unidirectional gene flow in all populations in the eastern Nagri region. Species distribution modeling showed that mean annual temperature, temperature seasonality, and annual precipitation were the main environmental factors affecting the distribution of Artemia populations and suitable habitats for Tibetan populations will be further reduced in the future. It is necessary to strengthen the protection of germplasm resources and formulate scientific protocols for the sustainable development and utilization of Artemia resources.

Prediction and validation of potential transmission risk of Dirofilaria spp. infection in Serbia and its projection to 2080.

Animal and human dirofilariosis is a vector-borne zoonotic disease, being one of the most important diseases in Europe. In Serbia, there are extensive studies reporting the presence of Dirofilaria immitis and D. repens, mainly in the north of the country, where the human population is concentrated and where there is a presence of culicid mosquitoes that transmit the disease. Ecological niche modeling (ENM) has proven to be a very good tool to predict the appearance of parasitosis in very diverse areas, with distant orography and climatologies at a local, continental, and global level. Taking these factors into account, the objective of this study was to develop an environmental model for Serbia that reflects the suitability of the ecological niche for the risk of infection with Dirofilaria spp. with which the predictive power of existing studies is improved. A wide set of variables related to the transmission of the parasite were used. The potential number of generations of D. immitis and the ecological niche modeling method (ENM) were used to estimate the potential distribution of suitable habitats for Culex pipiens. The highest probability of infection risk was located in the north of the country, and the lowest in the southern regions, where there is more orographic relief and less human activity. The model was corroborated with the location of D. immitis-infected dogs, with 89.28% of the country having a high probability of infection. In addition, it was observed that the percentage of territory with optimal habitat for Culex spp. will increase significantly between now and 2080. This new model can be used as a tool in the control and prevention of heartworm disease in Serbia, due to its high predictive power, and will serve to alert veterinary and health personnel of the presence of the disease in the animal and human population, respectively.

Changes in the Range of Four Advantageous Grasshopper Habitats in the Hexi Corridor under Future Climate Conditions.

Angaracris rhodopa (Fischer et Walheim), Calliptamus abbreviatus (Ikonnikov), Myrmeleotettix palpalis (Zubowsky), and Oedaleus decorus asiaticus (Bey-Bienko) are the main grasshoppers that harm the natural grassland in the Hexi Corridor in Gansu, northwest China. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers' habitats and to assess their distribution under current and future climate conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, distribution of suitable habitats for A. rhodopa, C. abbreviates, M. palpalis, O. decorus asiaticus were predicted under current and future climatic scenarios using the Maxent model. The average AUC (area under the ROC curve) and TSS (true skill statistic) values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, A. rhodopa, C. abbreviatus, and O. decorus asiaticus were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a suitable area of 1.29 × 104, 1.43 × 104, 1.44 × 104, and 2.12 × 104 km2, accounting for 13.7%, 15.2%, 15.3%, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of A. rhodopa, C. abbreviatus, and O. decorus asiaticus were mainly distributed in the eastern-central part of Zhangye City, the western part of Wuwei City, and the western and southern parts of Jinchang City, with areas of 0.20 × 104, 0.29 × 104, and 0.35 × 104 km2, accounting for 2.2%, 3%, and 3.7% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32 × 104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of A. rhodopa, C. abbreviatus, and O. decorus asiaticus was predicted to increase; the range of M. palpalis will decrease. The results of this study could provide a theoretical basis for the precise monitoring and control of key areas of grasshoppers in the Hexi Corridor.

Ecological niche modeling analysis (Cx. pipiens), potential risk and projection of Dirofilaria spp. infection in Greece

Vector-borne diseases continue to increase worldwide. Dirofilariosis is one of the most common vector-borne zoonotic diseases, mainly caused by Dirofilaria spp. (D. immitis and D. repens) and spread by culicid mosquitoes of different species. Greece is one of the countries in southern Europe where it is traditionally endemic, and its distribution is not homogeneous. The aim of this study was to develop an environmental model for Greece that reflects the suitability of the ecological niche for Dirofilaria spp. infection risk and its projection until 2080. For this purpose, we used the potential distribution of suitable habitats for Culex pipiens calculated using an ecological niche model (ENM) and the potential number of generations of Dirofilaria spp. The ecological niche model of Cx. pipiens in Greece showed good predictive power (AUC=0.897) with the parasite at a resolution of 1 km2. The variables that contributed most to the model were mean annual temperature, rivers and human footprint. The highest risk of infection was found in coastal areas and in riverside areas of the main river basins, as well as in irrigated areas of the mainland and peninsular regions and in the whole territory of island areas, and the lowest risk was found in areas of higher altitude. A positive relationship was found between the risk of dirofilariosis and the location of infected dogs, with 86.65% located in very high and high risk areas. In 2080, the percentage of territory gained by Cx. pipiens will increase by 261.52%. This model provides a high predictive value, predicted presence, and risk of Dirofilaria spp. infection and can serve as a tool for the management and control of this disease.

Anatomically modern human dispersals into Europe during MIS 3: Climate stability, paleogeography and habitat suitability

The initial large-scale dispersal of Anatomically Modern Humans (AMHs) into Europe, associated with the Aurignacian technocomplex, occurred during Marine Isotope Stage 3 (MIS 3), a critically unstable climatic period. The impact of climate change (millennial-scale Dansgaard-Oeschger events) and climate variability (annual and seasonal variation) on the mobility and initial dispersal of AMHs on the continent is not fully demonstrated. Here we show that both climate change and variability affected the spatial behavior of Aurignacian groups and structured their arrival on the continent. Using Random Forest, a machine learning algorithm, we produced habitat suitability (HS) models for AMHs under stadial (GS) and interstadial (GI) climate conditions. These models demonstrate that climate variability was a key factor governing the spatial behavior of human groups across MIS 3. They also illustrate that the structure and distribution of suitable habitat in Europe were affected by climatic conditions, with implications in terms of our species’ adaptability and behavioral plasticity. Finally, our results support the suggestion that initial dispersals followed a Mediterranean coastal route, likely under interstadial conditions.

A species distribution model of the giant kelp Macrocystis pyrifera: Worldwide changes and a focus on the Southeast Pacific.

Worldwide climate-driven shifts in the distribution of species is of special concern when it involves habitat-forming species. In the coastal environment, large Laminarian algae-kelps-form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat-forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios with a focus on the Southeast Pacific shores. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the single most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the Southeast Pacific, we observed an upper range contraction of -17.08° S of latitude for 2090-2100 under the RCP8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to -27.83° S in Chile. Along the area of Northern Chile where a complete habitat loss is predicted by our model, natural stands are under heavy exploitation. The loss of habitat suitability will take place worldwide: Significant impacts on marine biodiversity and ecosystem functioning are likely. Furthermore, changes in habitat suitability are a harbinger of massive impacts in the socio-ecological systems of the Southeast Pacific.

Can ecological niche models be used to accurately predict the distribution of invasive insects? A case study of Hyphantria cunea in China.

In recent decades, ecological niche models (ENMs) have been widely used to predict suitable habitats for species. However, for invasive organisms, the prediction accuracy is unclear. In this study, we employed the most widely used maximum entropy (MaxEnt) model and ensemble model (EM) Biomod2 and verified the practical effectiveness of the ENM in predicting the distribution areas of invasive insects based on the true occurrence of Hyphantria cunea in China. The results showed that when only limited data of invasive areas were used, the two ENMs could not effectively predict the distribution of suitable habitats of H. cunea, although the use of global data can greatly improve the prediction accuracy of ENMs. When analyzing the same data, Biomod2's prediction accuracy was significantly better than that of MaxEnt. For long-term predictions, the area of suitable habitat predicted by the ENMs was much greater than the occurrence area; for short-term predictions, the accuracy of the predicted area was significantly improved. Under the current conditions, the area of suitable habitat for H. cunea in China is 118 × 104 km2, of which 59.32% is moderately or highly suitable habitat. Future climate change could significantly increase the suitable habitat area of H. cunea in China, and the predicted area of suitable habitats in all climate scenarios exceeded 355 × 104 km2, accounting for 36.98% of the total land area in China. This study demonstrates the use of ENMs to study invasive insects and provides a reference for the management of H. cunea in China.

Adaptability Evaluation of Human Settlements in Chengdu Based on ArcGIS

This study establishes the evaluation index system of Chengdu’s habitat suitability based on three dimensions (the ecological livability environment, economic development environment, and social security environment) and quantitatively investigates the habitat suitability of Chengdu using the Analytic Hierarchy Process (AHP) and ArcGIS10.8 tools. Additionally, it analyzes the spatial pattern characteristics of Chengdu’s habitat suitability to provide insights into the rational optimization of Chengdu’s habitat system, and show that (1) the adaptability index of Chengdu’s human settlement is between 18.39 to 92.35, and the habitat suitability exhibits a high spatial distribution in the central area and a low spatial distribution in the surrounding regions, with obvious differences between hot spots and cold spots. (2) According to the suitability index from high to low, the habitat of Chengdu is divided into five regions: the most suitable area (895.62 km2, 6.25%), highly suitable area (2136.82 km2,14.91%), moderately suitable area (5755.80 km2,40.15%), low-suitability area (4580.61 km2, 31.95%) and the unsuitable area (966.15 km2, 6.74%). (3) The spatial distribution of habitat suitability in Chengdu demonstrates a certain coupling relationship with the city’s circular social development model. Moreover, the spatial distribution characteristics of each area exhibit good consistency with population density, natural environment, economic conditions, and social conditions. (4) The influence of each indicator factor shows spatial heterogeneity, with variations in different subregions. Additionally, different regions have their own advantages and disadvantages. The results show that there are obvious regional characteristics with the suitability of human settlements in Chengdu; the main urban area exhibits the highest degree of habitat suitability, while the western Longmen Mountain area shows relatively lower suitability in its habitat. Considering these spatial characteristics, future development should explore corresponding development modes for each region based on local conditions, aiming to reduce spatial differences and promote the integrated development of urban and rural areas.

Distribution of suitable habitat of Firmiana danxiaensis H.H.Hsue and H.S.Kiu in China: An integrated analysis based on changes in climate and high forest thematic resolution land use

The distribution of species is mostly influenced by climate synergistic effects and land use. The prediction of endangered species is dependent on fine-scale environmental features, especially in forests. The capture of fine-scale suitable habitats is bounded by low spatial resolution and coarse categorization. In this study, we improved the land use information and forest spatial detail through high forest thematic resolution land use data. To understand the relative influence of environmental factors, suitable habitat models for Chinese endangered tree species (Firmiana danxiaensis) under three climate and high forest thematic resolution land use conditions was constructed. We also assess F. danxiaensis 's response to climate and land use, and differential performance in land use on the suitable habitat. The area of suitable habitat for F. danxiaensis grows slowly under the SSP1-2.6 (shared social pathway scenario) scenario, decreases by 21.33% from the present to 2090 under the SSP2-4.5 scenario, and expands significantly under the SSP5-8.5 scenario. We conclude that high forest thematic resolution land use is beneficial in capturing species' requirements for specific habitats and especially necessary in predicting endangered species. At the same time, the distribution of suitable habitats for species is primarily driven by climate, and limited their development by land use. The study shows that the synthetic effects of climate and land use change on F. danxiaensis are positive, with a marked trend toward the northeast. As a consequence, some endangered species are able to benefit from future SSPs scenarios, in particular they respond more strongly to the SSP5-8.5 scenario than to the other scenarios. Assessing the role of changes in the climate and high forest thematic resolution land use on F. danxiaensis will help promote sustainable land use management and contribute to the conservation policy for Chinese endangered species.

High-resolution species distribution modelling reveals spatio-temporal variability of habitat suitability in a declining grassland bird

Abstract Context Species distribution models (SDMs) may provide accurate predictions of species occurrence across space and time, being critical for effective conservation planning. Objectives Focusing on the little bustard (Tetrax tetrax), an endangered grassland bird, we aimed to: (i) characterise the drivers of the species distribution along its key phenological phases (winter, breeding, and post-breeding); and (ii) quantify spatio-temporal variation in habitat suitability across phenological phases and over the years 2005–2021. Methods Combining remotely sensed metrics at high temporal resolution (MODIS) with long-term (> 12 years) GPS telemetry data collected for 91 individuals at one of the species’ main strongholds within the Iberian Peninsula, we built SDMs (250 m resolution) for the species key phenological phases. Results The use of both dynamic and static predictors unveiled previously unknown ecological responses by little bustards, revealing a marked change in the spatial distribution of suitable habitat among phenological phases. Long-term habitat suitability trends showed considerable fluctuations, mainly in the breeding and post-breeding phases. Overall, SDM projections into the past revealed that while the species’ winter and post-breeding habitats apparently increased since 2005, suitable habitat during the species’ most critical phenological phase, breeding, apparently reduced in area over time. Conclusions Our findings show that matching remotely sensed data with GPS tracking data results in accurate habitat suitability predictions throughout the yearly cycle. Additionally, our findings stress the importance of quantifying habitat loss and its potential impact on little bustard decline over nearly 20 years. Spatio-temporal variations in habitat suitability are also identified in this work, which can help prioritize conservation areas, particularly the breeding areas that have remained stable over time, as this is a key requirement for little bustard lek breeding system.

Climate Change Threatens the Habitat of Pinus massoniana in China

Pinus massoniana Lamb. is one of the main timber tree species. There is a large artificial planting area in South China, and this tree has important economic and ecological value. In this research, we built a comprehensive habitat suitability model based on 115 current data and 22 environmental variables to analyze the potential suitable habitat distribution of this species. Future climate change scenarios were defined as four shared socioeconomic pathways (SSPs): SSP 1–2.6, SSP 2–4.5, SSP 3–7.0, SSP 5–8.5) and four periods (including 2021–2040, 2041–2060, 2061–2080, and 2081–2100) based on nine global circulation model datasets. To fully consider the potential distribution of P. massoniana under specific climate change conditions and soil conditions, we constructed an ensemble model using four commonly used model algorithms. The results indicated that the current suitable habitat for P. massoniana covers approximately 1.10 × 106 km2 in southeastern China. In the future, the model results showed that under different climate change scenarios and at different times, the change in suitable habitat for P. massoniana varied; moreover, under moderate climate change scenarios, the average temperature decreased by less than 3 °C and the suitable habitat area decreased slightly, with an area larger than 0.95 × 106 km2. However, under intense warming scenarios, for which the average temperature increased above 3 °C, the suitable habitat for P. massoniana decreased. In the most severe warming scenario, the suitable habitat area for P. massoniana was reduced to 44% of the base climate conditions with severe habitat fragmentation, which should be fully considered in future planting initiatives and plant protection.

Predicting the suitable habitat distribution of berry plants under climate change

ContextClimate change is altering suitable habitat distributions of many species at high latitudes. Fleshy fruit-producing plants (hereafter, “berry plants”) are important in arctic food webs and as subsistence resources for human communities, but their response to a warming and increasingly variable climate at a landscape scale has not yet been examined.ObjectivesWe aimed to identify environmental determinants of berry plant distribution and predict how climate change might shift these distributions.MethodsWe used species distribution models to identify characteristics and predict the distribution of suitable habitat under current (2006–2013) and future climate conditions (2081–2100; representative concentration pathways 4.5, 6.0, & 8.5) for five berry plant species: Vaccinium uliginosum L., Empetrum nigrum L., Rubus chamaemorus L., Vaccinium vitis-idaea L., and Viburnum edule (Michx.) Raf..ResultsElevation, soil characteristics, and January and July temperatures were important drivers of habitat distributions. Future suitable habitat predictions showed net declines in suitable habitat area for all species modeled under almost all future climate scenarios tested.ConclusionsOur work contributes to understanding potential geographic shifts in suitable berry plant habitat with climate change at a landscape scale. Shifting and retracting distributions may alter where communities can harvest, suggesting that access to these resources may become restricted in the future. Our prediction maps may help inform climate adaptation planning as communities anticipate shifting access to harvesting locations.

Current and Future Distribution of Camellia sinensis in China Estimated by MaxEnt

Tea (Camellia sinensis L.) is an important cash crop. In the context of climate change, analyzing the current distribution of tea trees and climate change environmental variables to predict the potential distribution area of tea trees in the future can help decision-makers make appropriate planting decisions and promote sustainable management. In this study, an optimized MaxEnt model was used to predict the limiting factors of tea tree growth and distribution under current and future climate change scenarios. The climate soil mixing model [area under the curve (AUC) = 0.934] performed excellently. The results showed that precipitation, temperature, slope, and soil factors all affected the distribution of suitable habitats for tea trees. Compared with the current distribution area of tea trees, under three shared socioeconomic pathways (SSP126, SSP245, and SSP585), the area of highly suitable habitats for tea trees will expand, especially in 2061–2080 and 2081–2100 years, and the suitable area will extend overall to the north of China, indicating that future climate change may create more new suitable habitats for tea production, especially in Shandong, Shaanxi, Guizhou, and Yunnan provinces. This study will provide important scientific insights for tea production decision-making, tea garden location selection, and future adaptation methods, and will help in the cultivation and transplantation of tea trees in the future.

Suitable Habitat Prediction and Analysis of Dendrolimus houi and Its Host Cupressus funebris in the Chinese Region

The Dendrolimus houi, a phytophagous pest, displays a broad range of adaptations and often inflicts localized damage to its hosts. Cupressus funebris, an indigenous timber species in China, is significantly impacted by D. houi. Investigating the suitable habitat distribution and changes in D. houi and its host plant, C. funebris, within the context of climate warming, is essential for understanding D. houi’s development and providing novel insights for managing D. houi and conserving C. funebris resources. In this study, MaxEnt was employed to simulate the distribution of D. houi and its host plant, C. funebris, in their suitable habitats, evaluating the influence of environmental factors on their distribution and determining changes under a warming scenario. MaxEnt model parameters were adjusted using the Kuenm data package based on available distribution and climatic data. The minimum temperature of the coldest month emerged as the primary environmental factor influencing the distribution of a suitable habitat for D. houi and C. funebris, with a percentage contribution of environmental factors over 60%. There was a substantial similarity in the suitable habitat distributions of D. houi and C. funebris, with varying degrees of expansion in the total habitat area under different temporal and climatic scenarios. Intersection analysis results indicated that the 2041–2060 period, especially under low (SSP1-2.6) and high (SSP5-8.5) emission scenarios, is a critical phase for D. houi control. The habitat expansion of D. houi and C. funebris due to climate change was observed, with the distribution center of D. houi shifting northeast and that of C. funebris shifting northwest.

The interaction between temperature and precipitation on the potential distribution range of Betula ermanii in the alpine treeline ecotone on the Changbai Mountain

Alpine treeline ecotones are highly sensitive to climate warming. The low temperature-determined alpine treeline is expected to shift upwards in response to global warming. However, little is known about how temperature interacts with other important factors to influence the distribution range of tree species within and beyond the alpine treeline ecotone. Hence, we used a GF-2 satellite image, along with bioclimatic and topographic variables, to develop an ensemble suitable habitat model based on the species distribution modeling algorithms in Biomod2. We investigated the distribution of suitable habitats for B. ermanii under three climate change scenarios (i.e., low (SSP126), moderate (SSP370) and extreme (SSP585) future emission trajectories) between two consecutive time periods (i.e., current–2055, and 2055–2085). By 2055, the potential distribution range of B. ermanii will expand under all three climate scenarios. The medium and high suitable areas will decline under SSP370 and SSP585 scenarios from 2055 to 2085. Moreover, under the three climate scenarios, the uppermost altitudes of low suitable habitat will rise to 2,329 ​m a.s.l., while the altitudes of medium and high suitable habitats will fall to 2,201 and 2,051 ​m a.s.l. by 2085, respectively. Warming promotes the expansion of B. ermanii distribution range in Changbai Mountain, and this expansion will be modified by precipitation as climate warming continues. This interaction between temperature and precipitation plays a significant role in shaping the potential distribution range of B. ermanii in the alpine treeline ecotone. This study reveals the link between environmental factors, habitat distribution, and species distribution in the alpine treeline ecotone, providing valuable insights into the impacts of climate change on high-elevation vegetation, and contributing to mountain biodiversity conservation and sustainable development.

SSPs 기후변화 시나리오에 따른 서양금혼초(Hypochaeris radicata)의 개화 생물계절 및 적합 서식지 분포 예측

SSPs 기후변화 시나리오에 따른 서양금혼초(Hypochaeris radicata)의 개화 생물계절 및 적합 서식지 분포 예측

Modelling the current and future distribution potential areas of Peperomia abyssinica Miq., and Helichrysum citrispinum Steud. ex A. Rich. in Ethiopia

BackgroundThe aim of this study is to investigate how climate change influences the distribution of economically and environmentally important species of P. abyssinica and H. citrispinum in Ethiopia. The species distribution modeling intends to forecast species' ecological niche ranges and habitat suitability by employing a variety of environmental parameters as predictors, which is vital for conservation planning and restoration success. Six representative concentration pathways (RCP 2.6, 4.5, and 8.5 for the years 2050 and 2070) with the same resolution of 2.5 min that shows the emission scenarios were used for the prediction. To predict the current and future distributions of H. citrispinum and P. abyssinica 56 and 45 occurrence records from National Herbarium, Addis Ababa University, GBIF, and available literatures were used respectively.ResultsThe MaxEnt model predicted habitat suitability for H. citrispinum species with an Area Under Curve (AUC) value of 0.961 ± 0.027, and 0.809 ± 0.045 for P. abyssinica, indicating excellent discriminatory ability or accuracy under the current climate scenario. The Future distribution of suitable habitat for both H. citrispinum and P. abyssinica plant species was accurately predicted with AUC values of 0.960 ± 0.017 and 0.780 ± 0.35, respectively under future climatic scenarios. The jackknife test result indicates that environmental variables such as topographic position index (92.5%), precipitation of the driest quarter (3%) and precipitation in the coldest quarter (1.8%) are associated with the distributions of H. citrispinum, while topographic position index (36.6%), precipitation of driest quarter (21.4%), precipitation of warmest quarter (16.2%) and precipitation seasonality (13.9%) were found to be limiting environmental variables for P. abyssinica under current and future climatic conditions in Ethiopia. The prediction map and interception calculation for both present and projected (in the 2050s and again in the 2070s) climate change scenarios indicate significant habitat loss, decreased, and fragmentation under all RCPs (2.6, 4.5, and 8.5) scenarios for P. abyssinica while habitat gain, and increasing for H. citrispinum in Ethiopia.ConclusionsTopographic position index (TPI) is the most impactful predictor variable on the distribution of the two species. Consequently, potentially habitable areas (with diverse aspects and slopes) are increasing for H. citrispinum while decreasing for P. abyssinica.

Improving prediction for potential spawning areas from a two-step perspective: A comparison of multi-model approaches for sparse egg distribution

Recently, much work has been put into improving species distribution models, especially for systematic conservation planning for important ecosystems. Understanding fish spawning sites requires a thorough examination of ichthyoplankton. These examinations usually produce sparse counts contaminated by inaccurate detection, making it impossible to directly infer the abundance or occurrence from observational data, which could lead to inaccurate model predictions. A flexible modeling framework for estimating and inference about the abundance of eggs with ensemble models that include the presence/absence and abundance components is described in this study. The generalized linear model, generalized additive model, integrated nested Laplace approximations, and random forest habitat modeling approaches were compared within this framework to those currently being used for fish conservation planning at regional scales. Additionally, the distribution of suitable habitats for small yellow croaker (Larimichthys polyactis) spawning stocks were mapped based on the ensemble model. Furthermore, the promotion ability of ensemble models with different weighting methods was evaluated. The outcomes demonstrated that machine learning algorithms performed better than statistical models, and the geometric weighted ensemble model further increased prediction accuracy. However, there was no significant difference compared to the optimal individual model (p > 0.05). The predicted distributions of the four models can be divided into two groups. The central sea of Jiangsu was recognized as the most suitable area by the GAM with a fixed effect for each year and INLA models, while the GLM was similar to the RF with spatial effect (RF-LL) and demonstrated Haizhou Bay as the most suitable area. The ensemble model discovered several areas of highly suitable habitat that dominated areas in the two groups of models and revealed many finer-scale patterns in the egg distribution. According to the ensemble model, although 5.37% of the area could be suitable habitat, only 0.12% was highly suitable. It is suggested that examining small yellow croaker spawning aggregation areas would benefit from using an ensemble modeling approach to identify and prioritize conservation areas.