Yet researchers have long criticized the field for a fundamental scale mismatch. A review cited in the study found that the grid cells of environmental data used in previous analyses were roughly 10,000 times larger than the body length of the focal animal species, and about 1,000 times larger for plants. For an animal whose home range spans just 1,822 to 11,530 square meters, a climate grid cell covering nearly 640,000 square meters smooths away precisely the topographic complexity that shapes its daily experience.

The coarse-resolution model used temperature data at 30 arcseconds, equivalent to grid cells of about 691 by 926 meters. The fine-resolution model downscaled the same data to 3 arcseconds, producing cells of roughly 69 by 93 meters that better reflect the ambient air conditions an individual pika actually encounters. In the rugged terrain of central Hokkaido, the difference is dramatic: within a single coarse grid cell, elevation can vary by as much as 770 meters, with a median difference of 182 meters, conditions that the coarse data simply cannot represent.

To build the models, the team compiled 305 presence records from published literature spanning 1963 to 2009, covering elevations from 50 to 2,210 meters. Most detections came from pika vocalizations, supplemented by direct sightings, haypiles, feces, and feeding marks. After spatial thinning to reduce sampling bias, 91 presence points remained for model fitting.

The researchers used the maximum entropy algorithm, MaxEnt, chosen for its consistently strong performance in comparative studies, and carefully tuned its hyperparameters to avoid overfitting. Predictor variables included mean summer temperature and diurnal temperature range for July and August, terrain slope angle derived from a high-resolution digital elevation model, and surface geology, since 99 percent of the known pika distribution in the region lies on igneous and metamorphic rocks and moraines. The results confirmed the first hypothesis: the fine-resolution model outperformed the coarse-resolution model, achieving a Continuous Boyce Index of 0.80 compared with 0.73.

Mean summer temperature dominated both models, accounting for roughly 75 percent of permutation importance, with a strong negative effect on occurrence probability. Surface geology ranked second, contributing around 18 to 20 percent. Notably, the response curve for temperature was steeper in the fine-resolution model, indicating that the finer data allowed the model to fit more accurately toward the cooler conditions pikas prefer.

Hindcasting to the period 1961 to 1980 further validated both models, with the fine-resolution model reaching a hindcast CBI of 0.96, demonstrating strong transferability across time. Pikas living in rocky landforms experience what the authors call a duality in thermal conditions. Above ground, they forage, vocalize, and collect vegetation for their winter haypiles, exposed to ambient air temperatures.

Below ground, they retreat into the interstices between rocks, which are buffered from surface heat and remain cool and stable. Previous field measurements in the study area had established an empirical relationship between ambient and interstice temperatures, allowing the researchers to convert their downscaled air temperature data into rock-interstice microclimate data for grid cells containing rocky landforms in three representative regions: Biei at 1,100 to 2,000 meters, Shikaribetsu at 600 to 1,250 meters, and Oketo at 400 to 800 meters. Incorporating this sub-ground microclimate transformed the predictions.

Habitat suitability in areas with rocky landforms was significantly higher in the microclimate-based predictions than in either the coarse-resolution model or the fine-resolution model based on ambient air alone. The researchers categorized locations into three combinations of above-ground and below-ground suitability: high-high, low-high, and low-low. Areas with low-high suitability, where ambient air is too warm but rock interstices remain cool, may function as habitat if pikas can behaviorally adapt, spending time above ground during cooler parts of the day and retreating below when heat stress builds, a flexibility documented in both northern pikas and their American relatives.

Under both the sustainable SSP1-2.6 and fossil-fuel-intensive SSP5-8.5 emission scenarios, and for both the 2041 to 2070 and 2071 to 2100 periods, models based on ambient air temperature predicted that more than 60 percent of suitable habitat would disappear compared with the baseline period of 1981 to 2010. Under the high-emission scenario, losses continued through the century, while under the lower-emission scenario the range appeared to stabilize after mid-century. Yet when rock-interstice microclimates were factored in, pikas were predicted to persist in nearly all three study regions across all future scenarios, with the sole exception of low-elevation Oketo under the far-future SSP5-8.5 scenario.

The discrepancies between the two prediction approaches were greatest at lower elevations and under the higher emission pathway. Coarse-resolution models risk overlooking microrefugia, the small pockets of favorable conditions where species can persist even as surrounding landscapes become unsuitable. Such overestimation of range shifts could lead conservation planners to misallocate protected areas and management resources.

The study also acknowledges its limitations: rocky landforms are highly heterogeneous, with temperatures varying by height and depth and across seasons, so the modeled microclimates remain a simplified representation of reality. Other factors such as precipitation and snow cover, which influence pika habitat suitability, were not considered, and the lack of extensive high-resolution mapping of rocky landforms restricted the microclimate analysis to three regions. Analyzing species distributions at biologically relevant scales, and accounting for the vertical heterogeneity of thermal conditions within a single landscape, can fundamentally alter assessments of climate vulnerability.

The authors advocate for systematic identification of rocky landforms to integrate microclimates into conservation planning, and for continued monitoring to verify whether the behavioral flexibility pikas display in avoiding heat translates into maintained populations over time.

Subject of Research: Fine-scale species distribution modeling of the northern pika incorporating rock-interstice microclimates in Hokkaido, Japan

Article Title: Mapping fine-scale distribution of the northern pika Ochotona hyperborea considering duality in microhabitat thermal conditions

Article References: Sakiyama, T., & García Molinos, J. (2025). Mapping fine-scale distribution of the northern pika Ochotona hyperborea considering duality in microhabitat thermal conditions. Frontiers of Biogeography, 18, Article e131541. https://doi.org/10.21425/fob.18.131541

Image Credits: AI Generated

DOI: 10.21425/fob.18.131541

Keywords: northern pika, species distribution models, microclimate, climate change, Hokkaido, rock interstices, MaxEnt, habitat suitability, microrefugia, thermal buffering, conservation biogeography, downscaling

The researchers assembled 838 occurrence records from 1970 to 2018 in the Neotropics. Of these, 478 included life-stage information and were used to fit the niche models, while 360 records without stage information were reserved as evaluation points. The fitting records included 99 observations of eggs, larvae or nymphs and 462 observations of adult ticks; Model 3 combined all stages. Occurrences were spatially thinned with a 22-kilometer filter to reduce spatial autocorrelation.

The models were calibrated in a two-variable environmental space comprising annual mean temperature from WorldClim and relative humidity from Coupled Model Intercomparison Project data. Both layers were downscaled to 0.2-degree resolution, approximately 22 kilometers. The study applied the Bayesian model of Jiménez et al. (2019), which represents the fundamental niche as an ellipse described by a multivariate normal distribution. Its parameters estimate the environmental center of the niche, its orientation and its extent.

Physiological information came from experiments published by Hitchcock in 1955 on an Australian population collected from cattle farms. In tests involving 300 eggs, the reported tolerance range for air temperature was 16.6–36.6 °C, while mean relative humidity ranged from 70% to 99%. These older experimental limits were supplied to the models as prior information, but the authors cautioned that they originated from one population and might not capture differences among populations or between laboratory and field conditions.

The estimated niche centers were similar among the immature-stage, adult-only and all-stage models: annual mean temperature was about 17 °C, and mean relative humidity ranged from 79% to 82%. The 95% confidence ellipse for the immature-stage model was smaller and more elongated along the temperature axis, whereas the adult and combined models had similar shapes and sizes. The combined Model 3 placed 96.11% of the 360 stage-unknown evaluation records within its 95% ellipse; the adult model placed 95.28% inside, and the immature-stage model placed 84.72% inside.

Model 3 identified mostly low climatic suitability across the Americas, with medium to moderate suitability in parts of the United States, Mexico, Central America and South America. High environmental suitability was concentrated in southernmost Brazil, Uruguay and northeastern Argentina. The model also left about 4% of evaluation points outside the estimated fundamental niche. Those outlying tick records occurred in environmental conditions where two abundant wild hosts—white-tailed deer and the cougar, or mountain lion—also had occurrence records, suggesting that host-associated movement could account for some occurrences beyond the climatic niche boundary.

To incorporate biotic information, the researchers compiled occurrence records for 10 wild host species with more than 20 records each and applied a 50-kilometer spatial filter. A kernel-density estimate across the Americas represented host availability. The researchers used the 5% quantile of estimated density values among host-presence sites as the minimum host-density threshold. Combining this binary host map with the 95% ellipse from Model 3 produced four classes: climatically unsuitable sites without hosts, unsuitable sites with hosts, suitable sites without hosts, and sites that were both climatically suitable and had hosts. The resulting map delineated areas potentially prone to infestation by combining environmental suitability with host availability.

For comparison, the team fitted 54 candidate MaxEnt models using the same 478 stage-known occurrences and two climatic variables. A 200-kilometer buffer around occurrence records represented the accessible area. Models were screened using partial ROC, an omission rate of 0.05 and AICc, and the selected configuration combined linear, quadratic and product features. It had an omission rate of 0.048 and an AICc score of 6939.5; the median of 10 bootstrapped versions became the final model.

The selected MaxEnt output did not display the concentric environmental pattern expected from the ellipse model. Its high-suitability region was hyperbolic and divided into two disconnected clusters: one cold and humid and the other hot with low-to-medium humidity. Geographically, it assigned medium to high suitability to much of the continent, including Alaska and Greenland, where the tick has not been documented. Its suitability values were concentrated around 0.5, and few fitting occurrences received high scores. These findings are comparisons within this study and do not establish that MaxEnt is generally unsuitable for distribution modeling. The analysis was also limited to two climatic variables, relied on stage-unknown evaluation records and sparse host data, and did not quantify interactions involving other ticks, fungi, bacteria or invertebrates.

Subject of Research: Modeling the climatic and host-associated potential distribution of the cattle tick Rhipicephalus (Boophilus) microplus in the Americas

Article Title: Integrating biotic factors into niche modeling: a case study with Rhipicephalus ( Boophilus ) microplus in the Americas

Article References: Marques, R., Jiménez, L., Ferreira-Krüger, R., & Jiménez-García, D. (2025). Integrating biotic factors into niche modeling: a case study with Rhipicephalus (Boophilus) microplus in the Americas. Frontiers of Biogeography, 18, Article e152671. https://doi.org/10.21425/fob.18.152671

Image Credits: AI Generated

DOI: 10.21425/fob.18.152671

Keywords: cattle tick, Rhipicephalus microplus, ecological niche modeling, MaxEnt, wild hosts, fundamental niche, realized niche, climate suitability, host density, the Americas, Integrating, biotic

The study examined Armadillidium nasatum , A. vulgare , Haplophthalmus danicus , Porcellio dilatatus , P. laevis , P. scaber and Porcellionides pruinosus , seven terrestrial isopods treated as exotic in Japan and associated originally with Europe or the Mediterranean region. The underlying Japanese database contained 17,412 specimens compiled from 159 publications, museum records and the first author’s personal collection. After duplicate locations were excluded, the seven species were represented by 1,516 Japanese sites, while the European and North American occurrence datasets supplied 4,135 and 1,953 locations, respectively.

Five species were first reported in Japan in 1927; A. nasatum and P. dilatatus were first reported in 1943. Researchers used Maxent version 3.4.1 to construct environmental niche models from 19 bioclimatic variables in WorldClim version 2.0, mapped at five-arc-minute resolution. The variables included measures of temperature and precipitation.

To reduce multicollinearity, highly correlated predictors were removed when the absolute value of their Pearson correlation coefficient was at least 0.75. Models used linear and quadratic features to describe relationships between occurrence probability and environmental conditions while limiting overfitting. Because the records came from non-random sources, the researchers generated a kernel-density estimate of sampling bias and selected 10,000 background points weighted by that surface, creating a target-group background intended to account for uneven collection effort.

Two modelling approaches were compared for each species. Regional models used occurrence records from Japan alone, whereas global models combined Japanese records with those from Europe and North America. Training area under the curve, or AUC, ranged from 0.681 to 0.910 for the global models and from 0.712 to 0.857 for the regional models.

AUC values above 0.9 indicate high discriminatory performance, values from 0.7 to 0.9 represent reasonable or moderate performance, and values from 0.5 to 0.7 indicate poor performance. Global models performed better for A. nasatum , A. vulgare and P. dilatatus . The researchers used the global approach to map potential Japanese distributions because records confined to an invaded country may understate the full environmental range occupied by a species in its native and other invaded regions.

Temperature-related variables supplied most of the strongest climatic signals in the global models. Annual mean temperature contributed more than 25 percent for three species: A. nasatum , H. danicus and P. scaber . Mean diurnal temperature range exceeded a 25 percent contribution for five species: A. vulgare , H. danicus , P. laevis , P. scaber and P. pruinosus .

Temperature seasonality was also a major predictor for P. dilatatus , contributing 37.6 percent. Among precipitation variables, seasonality contributed more than 25 percent for A. nasatum , P. dilatatus and P. laevis , while precipitation in the wettest month was especially important for A. nasatum , exceeding 65 percent contribution and permutation importance. The response curves revealed shared and species-specific temperature patterns.

Annual mean temperature responses differed among the remaining species: A. nasatum , H. danicus and P. scaber were associated with temperatures above 15°C, while P. pruinosus showed a hump-shaped response across a more moderate range of approximately 15–25°C. The study’s authors noted that the annual mean temperatures assigned probabilities above 0.5 covered roughly 10–25°C across most of Japan except mountainous areas, suggesting that annual mean temperature alone was not the principal national-scale constraint for these species. Global potential distributions generally included western Honshu, Shikoku and Kyushu, although their boundaries varied among species.

Suitable areas for A. vulgare , P. scaber and P. pruinosus extended farther inland than those for A. nasatum and H. danicus . The projected range for P. scaber also included coastal Hokkaido, while that of P. laevis was concentrated more heavily in southwestern Japan. For P. dilatatus , the global and regional models both identified most of Kyushu and Shikoku, but the regional model additionally projected suitable coastal areas of Honshu and southern Hokkaido.

The broader global projections for the other six species suggest that their Japanese occurrence records had not yet reached all areas classified as climatically suitable, not that those areas will inevitably be occupied. Invasion stages were inferred by plotting regional against global model probabilities and dividing the results at a probability of 0.5. Areas classified as highly suitable by both models represented stabilising populations.

High global probability combined with low regional probability indicated colonising populations, whereas low probability in both models identified sink populations. A high regional probability paired with low global probability was interpreted as a locally adapted population. A. vulgare , H. danicus , P. laevis , P. scaber and P. pruinosus contained mixtures of stabilising and colonising areas, with several sink areas also identified.

A. nasatum was composed mainly of stabilising areas and one sink, while P. dilatatus produced the pattern assigned to local adaptation. These labels describe relationships between model predictions rather than observed demographic outcomes. For example, a colonising classification means that an area is climatically suitable in the global model but poorly represented by the species’ Japanese regional occurrence pattern; it does not establish a population trajectory or guarantee establishment.

Likewise, a sink classification is consistent with the presence of a species in an area predicted to be unsuitable, including cooler inland and northern locations, but it does not demonstrate that a population is declining. The four categories did not form sharply separated geographic regions. The authors also warned that occurrence records could not cover every part of the species’ ranges and that the projected maps might change as a larger, more complete database became available.

A. vulgare had the widest recorded Japanese range, extending from 43°10′ north to 24°45′ north, and occurred at 770 sites. P. scaber was recorded at 393 sites and was the only species commonly reported in Hokkaido. The Japanese records for A. nasatum , P. dilatatus and P. laevis numbered 20, seven and 32 sites, respectively, while P. pruinosus occurred at 174 sites and reached Iriomotejima Island at 24°16′ north, the southernmost location in the dataset.

The authors considered the short time since the first Japanese reports of A. nasatum , together with its large projected suitable area and introduction to suitable areas, one possible reason for its limited number of records. They also suggested that the ecological niche and areas of introduction were more relevant than elapsed time to the narrow Japanese range of P. dilatatus . The results show why occurrence records from an invaded region alone may underestimate the potential range of these seven exotic isopods.

Combining Japanese, European and North American data produced wider projections for six species and exposed areas where further establishment may be possible. The analysis did not establish ecological harm, human exposure or the consequences of future expansion, and its macro-scale climate models did not include every local influence on isopods. Within those limits, the study identifies temperature and diurnal temperature variation as major climatic correlates and suggests that six of the seven modelled species retained geographic scope for potential expansion beyond their documented Japanese ranges.

Subject of Research: Ecological niche modelling of seven exotic terrestrial isopod distributions and invasion stages in Japan

Article Title: Invasion stages and potential distributions of seven exotic terrestrial isopods in Japan

Article References: Karasawa, S., & Nakata, K. (2018). Invasion stages and potential distributions of seven exotic terrestrial isopods in Japan. BioRisk, 13, 53-76. https://doi.org/10.3897/biorisk.13.23514

Image Credits: AI Generated

DOI: 10.3897/biorisk.13.23514

Keywords: terrestrial isopods, Japan, ecological niche modelling, species distribution models, invasive species, climatic niche, temperature variables, Maxent, invasion stages, soil biodiversity, Invasion, stages

A new study published in the journal Nature Conservation tackles that question by reconstructing the species’ potential distribution across six climatic periods, from the Last Interglacial roughly 120,000 years ago to projected conditions in the 2050s and 2070s. Using an ecological niche modeling approach known as maximum entropy, or MaxEnt, the researchers combined 75 rigorously filtered occurrence records with 19 bioclimatic variables drawn from field surveys and herbarium collections. The result is the first comprehensive climate-driven distribution modeling ever conducted for this species, and it fills a long-standing gap in understanding how this orchid has weathered the Quaternary glacial cycles and what its future may hold.

The modeling workflow began with an extensive data-cleaning effort. The team gathered 229 latitude and longitude records from the Chinese Virtual Herbarium, the Global Biodiversity Information Facility, the Flora of China, and their own fieldwork, then applied a one-square-kilometer buffer across China to eliminate spatial bias from clustered sampling. Redundant and misidentified records were removed, leaving a single occurrence point per buffer zone. This kind of spatial thinning is critical for niche models, which can be misled by dense clusters of records that reflect collector access rather than true ecological preference.

Climate data came from the WorldClim database at a 30-arc-second resolution, generated by the CCSM4 general circulation model developed at the National Center for Atmospheric Research under the Coupled Model Intercomparison Project Phase 5. For future projections, the researchers used the Representative Concentration Pathway 2.6 scenario, a relatively optimistic low-emission trajectory aligned with global mitigation goals. Because multicollinearity among the 19 bioclimatic variables can cause model overfitting, the team screened them with Pearson correlation analysis, removing any factor with a correlation coefficient at or above 0.8. Seven variables survived the screening, and four of them ultimately dominated the model’s predictions.

Those four factors tell a clear story about what this orchid needs. Precipitation of the driest month contributed the most, at 30.6 percent, followed by annual precipitation at 27.0 percent, mean temperature of the warmest quarter at 25.9 percent, and mean diurnal temperature range at 8.5 percent. Together, these four variables accounted for 92 percent of the model’s total contribution. The pattern makes ecological sense: orchids are notoriously sensitive to water availability and seasonal drought, and C. graciliflora inhabits subtropical monsoon zones where rainfall is abundant but strongly seasonal. The response curves revealed surprisingly narrow tolerances. When the probability of occurrence exceeded 0.5, annual precipitation fell between 1,500 and 2,800 millimeters, precipitation of the driest month between 30 and 170 millimeters, mean diurnal range between 6.3 and 8 degrees Celsius, and mean temperature of the warmest quarter between 21.5 and 25 degrees Celsius. These thresholds represent the climatic envelope within which the species can grow and reproduce normally.

The model’s performance was exceptional. The average area under the receiver operating characteristic curve, a standard measure of predictive accuracy, reached 0.989 with a standard deviation of only 0.001, far exceeding the random-prediction benchmark of 0.5. With that level of confidence, the researchers could trace the species’ range through time with meaningful precision. During the Last Interglacial, suitable habitat covered roughly 123,770 square kilometers, concentrated in present-day Chongqing, Yunnan, Guizhou, Hainan, Fujian, and Zhejiang, with a notable concentration in the southern Hengduan Mountains. During the Last Glacial Maximum, those southern Hengduan habitats vanished entirely while suitable areas expanded northward into the Qinling Mountains, the Luoxiao Mountains, and Mount Wuyi.

That shift during the Last Glacial Maximum is the study’s most striking biogeographic finding. It suggests that the Qinling Mountains, Luoxiao Mountains, and Mount Wuyi served as glacial refugia where the orchid survived the coldest millennia of the Pleistocene. The evidence points to two distinct survival strategies operating simultaneously. In the Qinling Mountains, the species appears to have followed a migratory model, retreating northward into northern subtropical transitional forests as ice advanced. At Mount Wuyi, by contrast, suitable habitat persisted continuously through every Quaternary climatic event, consistent with a model of in situ evolution, where populations endured through genetic variation or phenotypic plasticity rather than range shifts. Both patterns have been documented in other Chinese plant species responding to glacial cycles, but this is the first time they have been identified for C. graciliflora specifically.

By the Middle Holocene, roughly 6,000 years ago, the distribution had largely returned to its present-day configuration, with highly suitable areas concentrated along the border of Chongqing and Hubei and in southern Hunan, Fujian, Zhejiang, and Taiwan. Today, the total suitable habitat covers approximately 98,080 square kilometers, about 1.014 percent of China’s land area, centered on the subtropical evergreen broad-leaved forests of central and eastern China. The highly suitable core regions sit in the Jiangxi-Hunan border area and in Fujian and Zhejiang, closely associated with the Luoxiao Mountains and Mount Wuyi, where montane forests between 600 and 2,500 meters elevation provide the humid, acidic, humus-rich soils and shaded understories the orchid requires.

The future projections are sobering. Under the RCP2.6 scenario, total suitable habitat is expected to shrink by approximately 52 percent by the 2050s, dropping from 98,080 to about 46,860 square kilometers, before partially recovering to roughly 69,400 square kilometers by the 2070s. The highly suitable area is projected to collapse by nearly 60 percent, from 29,220 to 11,700 square kilometers, in the 2050s, then rebound to 25,910 square kilometers by the 2070s. The researchers interpret this bimodal decline-and-recovery pattern as evidence of the species’ historical resilience to climate fluctuations. The initial crash likely reflects rapid warming that disrupts the fog-shade equilibrium in core montane habitats, while the subsequent recovery may result from elevational migration as warming pushes subtropical forest communities upward into newly suitable zones. Notably, a highly suitable region is predicted to emerge in the high-altitude areas of Taiwan by the 2050s but disappear again by the 2070s, underscoring how transient even newly available habitat can be under continued warming.

The conservation implications are concrete. The authors recommend prioritizing in situ protection south of the Qinling-Huaihe line, particularly montane forests between 800 and 1,200 meters in the Nanling Mountains and between 1,200 and 1,600 meters on Mount Wuyi, integrating these zones into existing or planned national park systems. For newly identified climatically suitable areas such as Taiwan, small-scale protected zones could facilitate species migration and buffer against human impacts. Ex situ measures, including seed banking, botanical garden cultivation, and assisted reproduction, are recommended where natural habitats are projected to decline, especially given the species’ characteristically low seed set and germination rates. The study also cautions that its focus on bioclimatic variables alone leaves out topography, competition, and other biological factors, and that plant responses to climate change often lag behind model projections. Still, as a baseline for future research on Calanthe and other terrestrial orchids, and as a call to incorporate climate vulnerability into Red List reassessments for a species already listed as near threatened and regulated under CITES, the work offers a template for how phylogeography and conservation planning can converge on the mountains where this resilient orchid has survived everything the past could throw at it.

Subject of Research: Climate-driven distribution modeling and conservation of the Chinese endemic orchid Calanthe graciliflora

Article Title: The past, present, and future distribution of Calanthe graciliflora : implications for conservation and phylogeography

Article References: Guo, P., Lu, A., Zheng, J., Chen, L., Wu, S., Hu, C., Li, M., Huang, W., & Zhai, J. (2025). The past, present, and future distribution of Calanthe graciliflora: implications for conservation and phylogeography. Nature Conservation, 60, 21-38. https://doi.org/10.3897/natureconservation.60.156661

Image Credits: AI Generated

DOI: 10.3897/natureconservation.60.156661

Keywords: Calanthe graciliflora, orchid conservation, MaxEnt, ecological niche modeling, glacial refugia, climate change, Qinling Mountains, Mount Wuyi, phylogeography, Last Glacial Maximum, habitat suitability, subtropical forests

The research, conducted as part of the European Union-funded SteamBioAfrica project, focused on three species that are already notorious across Namibia, Botswana, and South Africa: Senegalia mellifera, known as black thorn; Dichrostachys cinerea, the sickle bush; and Terminalia sericea, the silver cluster-leaf. These woody plants have been steadily colonizing open rangelands for more than a century, displacing the herbaceous vegetation that sustains livestock grazing and altering soil chemistry, water infiltration, and fauna dynamics. The phenomenon was first described as early as 1917, when botanist Bews documented the increasing density of acacia-type species in southern African grasslands, and it has since become one of the most pressing management challenges in arid and semi-arid rangelands worldwide.

At the heart of the encroachment problem lies the two-layer theory of savanna ecology. Savannas are structured in two distinct vertical strata: trees and shrubs dominate the upper layer, while grasses and herbaceous plants occupy the lower one. When overgrazing or disrupted fire regimes weaken the grass layer, it loses its ability to compete for water and nutrients, and more rainfall percolates into deeper soil horizons where tree and shrub roots can access it. This gives woody plants a decisive competitive advantage, allowing them to take over. The process is driven by a complex interplay of factors, including changes in fire regimes, livestock grazing pressure, the loss of browsing herbivores, fuelwood harvesting, rising atmospheric carbon dioxide, and climate change itself, making it nearly impossible to attribute encroachment to any single cause.

Paradoxically, encroaching shrubs are not entirely villainous. Under controlled grazing, soils beneath shrub canopies often contain more organic matter, nutrients, and seeds than open grassland, creating so-called “fertile islands” that can foster biodiversity and improve soil quality. Soil carbon, microbial activity, nitrogen storage, and above-ground productivity have all been found to be higher under woody cover than under grasses. However, species like Senegalia mellifera develop aggressive lateral root systems that displace herbaceous vegetation entirely, crashing biodiversity and fundamentally altering habitat. The challenge for land managers is maintaining a balance between woody and herbaceous cover that preserves ecosystem services without triggering runaway thicketization, which also increases evapotranspiration and can intensify droughts.

To predict where these species will spread, the research team employed MaxEnt, a widely used machine learning approach in ecological niche modeling that predicts suitable habitat from presence-only occurrence records combined with environmental variables. The researchers compiled thousands of occurrence records from the Global Biodiversity Information Facility and published literature, then spatially rarefied the data at roughly 10-kilometer resolution to eliminate sampling bias and spatial autocorrelation. After rarefaction, 286 points remained for Terminalia sericea, 281 for Senegalia mellifera, and 186 for Dichrostachys cinerea. The models incorporated 30 candidate variables spanning bioclimatic measures from WorldClim, soil properties from SoilGrids, and topographic features derived from elevation data, with highly correlated variables excluded to prevent overfitting.

The predictive power of the final models was strong. Performance, assessed by the area under the receiver operator characteristic curve, reached 0.836 for Terminalia sericea, 0.822 for Dichrostachys cinerea, and 0.738 for Senegalia mellifera, all comfortably above the 0.7 threshold generally considered satisfactory. The analysis revealed that precipitation and temperature variables overwhelmingly govern the distribution of all three species, though each responds to a distinct combination. Terminalia sericea’s habitat was best explained by annual precipitation, which contributed 55.2% of the model, and annual mean temperature at 31.2%. Senegalia mellifera responded most strongly to the mean temperature of the wettest quarter at 50.9%, while Dichrostachys cinerea was driven primarily by precipitation of the driest month at 41.3%.

Under current conditions, the models show that Senegalia mellifera is already the most pervasive of the three, with suitable habitat covering 56% of the study area, or roughly 1.46 million square kilometers. Dichrostachys cinerea follows with 43.9% suitable habitat, and Terminalia sericea with 37.9%. The future projections paint an even starker picture. Drawing on three structurally distinct Earth system models from the sixth phase of the Coupled Model Intercomparison Project, and spanning three shared socioeconomic pathways from a moderate mitigation scenario to a high-emission scenario, the researchers generated 54 future distribution maps for two time horizons, 2041 to 2060 and 2061 to 2080. In every scenario, unsuitable areas shrank and habitat suitability expanded.

The magnitude of expansion depended on emissions. Under the moderate SSP245 pathway, habitat gains were smallest, but under the high-emission SSP585 scenario, Senegalia mellifera’s suitable area grew by up to 29.4%, Dichrostachys cinerea’s by 24.2%, and Terminalia sericea’s by 24%. By 2061 to 2080 under SSP585, the most climate-sensitive model predicted that 85.4% of the entire study area would be suitable for Senegalia mellifera, making it the clear winner in a hotter, drier future. The change maps also revealed a clear geographic trend: shrub expansion flows southward toward South Africa and Botswana, consistent with climate projections of declining rainfall in the east and north of the region, conditions that favor competitively dominant shrubs over grasses.

These findings align with broader evidence of vegetation change across the continent. Previous studies have documented annual increases in shrub cover of up to 0.27% per year, alongside satellite-detected increases in vegetation optical depth across southern, western, and central Africa, confirming global greening trends driven in part by rising carbon dioxide, shifting rainfall, and warming temperatures. The model outputs also closely match existing published distribution maps for the three species, lending credibility to the future projections, though the authors caution that such models cannot capture biotic interactions, genetic adaptation, or the full complexity of socio-ecological processes.

The practical motivation behind the mapping effort is the SteamBioAfrica project itself, which aims to turn the encroachment problem into an opportunity. The initiative is demonstrating a superheated steam technology that converts invasive woody biomass into clean solid biofuel and condensate water across Namibia, Botswana, and South Africa. Dichrostachys cinerea, with its rapid growth, high biomass density, and low burning emissions, is particularly suited to clean energy generation, while Terminalia sericea and Senegalia mellifera are already valued locally as fuelwood, medicinal plants, and livestock feed. By identifying where these species are most likely to thrive, the habitat maps will help target harvesting operations, guide land restoration, and strengthen soil management plans. The researchers recommend local-scale validation studies measuring shrub regeneration in newly suitable areas, arguing that a deeper understanding of how woody species respond to a changing climate is essential for keeping southern Africa’s savannas, and the livelihoods they support, in balance.

Subject of Research: Predicting habitat suitability of bush encroacher shrubs in southern Africa under climate change scenarios using MaxEnt species distribution modeling

Article Title: Mapping the potential habitat suitability and opportunities of bush encroacher species in Southern Africa: a case study of the SteamBioAfrica project

Article References: Bravo-García, J., Camarillo-Naranjo, J., Blanco-Velázquez, F. J., González-Peñaloza, F., & Anaya-Romero, M. (2024). Mapping the potential habitat suitability and opportunities of bush encroacher species in Southern Africa: a case study of the SteamBioAfrica project. Frontiers of Biogeography, 17, Article e136222. https://doi.org/10.21425/fob.17.136222

Image Credits: AI Generated

DOI: 10.21425/fob.17.136222

Keywords: bush encroachment, MaxEnt, species distribution modeling, savanna ecosystems, climate change, Senegalia mellifera, Dichrostachys cinerea, Terminalia sericea, Southern Africa, rangeland management, biofuel, thicketization

The Desert Monitor as a whole occupies a vast sweep of the Sahara-Gobi Desert region, stretching from North Africa and the Middle East through Central and South Asia to Pakistan and northwestern India. Within this enormous range, three subspecies are recognized: the nominate V. g. griseus in the west, from northwestern Africa to the Zagros Mountains of Iran; the Central Asian V. g. caspius in the center, from the Zagros to the mountain systems of Pakistan; and the Indian V. g. koniecznyi in the plains of Pakistan and northwestern India. The Central Asian subspecies reaches its northern limits near the Aral Sea and the city of Kyzylorda in southern Kazakhstan, making it a true flagship of the region’s desert fauna.

Despite more than 150 years of documentation, recent publications have depicted the monitor’s range either in very generalized terms or as scattered points on a map. To resolve this uncertainty, the research team assembled an extraordinary dataset: 820 occurrence records drawn from historical literature, zoological collections, electronic databases, surveys of local residents and inspectors, personal communications from colleagues, and the authors’ own field observations from 2008 to 2023. The tally included 354 records from Kazakhstan, 180 from Uzbekistan, 140 from Turkmenistan, 86 from Iran, 45 from Tajikistan, and 9 each from Kyrgyzstan and Afghanistan. Where precise coordinates were missing, the authors used satellite and topographic maps to georeference textual locality descriptions, discarding data too vague to place reliably.

The modeling itself relied on the maximum entropy method implemented in the Maxent software, a standard tool in biogeography that predicts habitat suitability from georeferenced occurrence points and environmental raster layers. The team began with an unusually comprehensive set of 106 environmental variables, including WorldClim temperature and precipitation metrics, monthly vegetation indices, solar radiation, water vapor pressure, soil properties from SoilGrids, and soil water index data from the Copernicus Global Land Service. Because closely correlated variables can inflate predictions, the analysis proceeded in two stages: first with the full variable set, then with a reduced set in which variables with Pearson correlation coefficients above 0.7 were pruned, retaining whichever of each correlated pair contributed more to the initial model.

A further methodological subtlety involved the uneven distribution of occurrence records, which tend to cluster near roads and settlements where observers travel. To counteract this sampling bias, the researchers rarefied their points at minimum distances of 15, 25, and 50 kilometers, yielding modeling sets of 352, 261, and 149 records respectively. In total, 1,800 model runs were evaluated using the Area Under the ROC Curve (AUC) and the True Skill Statistic (TSS). The best configuration used 15-kilometer rarefaction, linear, quadratic, and hinge feature classes, and a regularization multiplier of 0.5. The final model achieved an AUC of 0.93, rated as excellent, and a TSS of 0.78, considered useful, indicating strong predictive performance.

The variables shaping the monitor’s distribution proved strikingly seasonal and specific. Five factors together contributed 75 percent of the final model: the mean temperature of the driest quarter, which alone accounted for 25.3 percent; the Normalized Difference Vegetation Index for March; precipitation during the warmest quarter; precipitation in March; and solar radiation in April. The authors interpret these as proxies for the lizard’s tightly choreographed annual cycle. Summer temperatures during the driest quarter likely govern egg incubation, since embryos must complete development before autumn cooling. March vegetation and April solar radiation relate to soil warming sufficient for monitors to emerge from hibernation burrows by early April, and to the availability of prey at that moment. Warm-quarter and March precipitation influence both spring food abundance and the soil moisture reserves needed to keep clutches viable in nesting chambers through the summer.

The comparison between model predictions and reality also exposed the fingerprints of human pressure. In southern Kazakhstan, for example, the model assigns very high suitability to the right bank of the Syr Darya River up to the Karatau range, yet monitors have only been recorded south of the 42nd parallel despite dense human settlement and frequent scientific visits to the area. The explanation, the authors argue, is anthropogenic: the region contains Shymkent, one of Kazakhstan’s largest cities, along with numerous villages, roads, and agricultural lands. Compounding the problem is local hostility—an encountered monitor often triggers fear, and although the species is listed in Kazakhstan’s Red Book, it is frequently killed. Survey data confirmed this pattern in most cases examined.

Some apparently outlying records also turned out to be misleading. Observations near Kyzylorda, far from the monitor’s core habitats, are best explained by intentional or accidental transport of individual animals. The authors recount one instance in which a monitor climbed into a car’s engine compartment in the Eastern Kyzylkum Desert and revealed itself only after the vehicle had stopped more than a hundred kilometers away, and another in which an individual was hauled to Shymkent in the back of a truck filled with sand. Similarly, historical records near the Aral Sea cannot be verified today; Uzbek colleagues and the fauna lists of the Barsakelmes State Nature Reserve both confirm that the monitor no longer occurs there.

The regional picture of range loss varies sharply across borders. Uzbekistan suffered the most severe contraction, with entire populations vanishing from the Tashkent and Syrdarya regions, eastern Jizzakh, river floodplains in the Samarkand, Kashkadarya, and Bukhara regions, and much of the Fergana Valley, where the lizard apparently survives only on narrow foothill strips unsuitable for agriculture. Tajikistan and Kyrgyzstan saw comparable losses, with plains and valley habitats completely converted to farmland and surviving populations confined to foothill zones. Turkmenistan retains large tracts of occupied territory—the species was even removed from the latest edition of the republic’s Red Book—though areas around the Kopetdag foothills and the cities of Tejen and Mary have been transformed. Kazakhstan, by contrast, has lost relatively little, with the monitor still widespread in the extreme south along the Syr Darya and in the Kyzylkum sands.

The updated range map is more than an academic exercise. The authors emphasize that it serves as a practical tool for conservation planning, population monitoring, and the development of nature protection programs across all five Central Asian republics. They also identify priority areas for future field surveys to test the model’s predictions, including the Kyzylkum Desert south of Kyzylorda, the northeastern Kyzylkum toward Zarafshan and Bukhara, and the northern Balkan, Lebap, and Dashoguz regions of Turkmenistan. Ultimately, the team argues that protecting the Desert Monitor will require not only biological research but social and international programs to raise awareness among local communities—because the fate of this formidable desert predator now depends as much on changing human attitudes as on the climate variables that define its ecological limits.

Subject of Research: Species distribution modeling and range contraction of the Central Asian Desert Monitor

Article Title: The range of the Desert Monitor Varanus griseus caspius (Eichwald, 1831) in Central Asia

Article References: Zima, Y. A., & Fedorenko, V. A. (2024). The range of the Desert Monitor Varanus griseus caspius (Eichwald, 1831) in Central Asia. Frontiers of Biogeography, 17, Article e138199. https://doi.org/10.21425/fob.17.138199

Image Credits: AI Generated

DOI: 10.21425/fob.17.138199

Keywords: Desert Monitor, Varanus griseus caspius, Central Asia, species distribution modeling, Maxent, habitat loss, biogeography, anthropogenic landscapes, conservation, Kazakhstan, Uzbekistan, ecological niche modeling

The research team, led by scientists at the University of Liège, set out to answer two questions that have long frustrated conservationists. First, which environmental conditions actually determine where Japanese giant salamanders can live? Second, how will those conditions shift as the planet warms? To do this, they deployed species distribution models, a cornerstone tool of modern macroecology, over an area of 282,916 square kilometres covering the entirety of Honshu, Shikoku and Kyushu islands. The models compared 477 high-resolution occurrence records, gathered from field surveys and published studies dating back to 1970, against seven remote-sensing environmental predictors spanning climate, topography and land use.

The occurrence data required careful preparation. The team collected 1,228 presence records in total, but to avoid spatial autocorrelation and overfitting, they thinned the dataset so that no two points fell within one kilometre of each other, a distance chosen because it matches the grid scale of the environmental data and the typical migratory range of the species. The result was a robust set of 477 presence points on which to train the models. Environmental predictors were selected based on the salamander’s ecology: four bioclimatic variables from the WorldClim dataset, including mean temperature of the wettest and warmest quarters and precipitation of the warmest and coldest quarters, alongside mean slope, agricultural area and urban area, all at a one-square-kilometre resolution.

The modelling itself used MaxEnt, a presence-background method that compares the environmental conditions at species locations with those available across the landscape. To ensure the model captured conditions specific to the salamander’s actual range, the team restricted the background to the known distribution during training, then projected the model across all of Japan to explore potential suitability beyond it. They corrected for sampling bias using a bias grid built from a minimum convex polygon around occurrence points buffered by 50 kilometres, and partitioned the data spatially into four folds to improve transferability across space and time. Model calibration tested 36 parameter combinations of feature classes and regularisation multipliers, with the optimal model selected using corrected Akaike Information Criteria and validated against null models built from 100 iterations.

The findings are striking. Climatic variables dominated the distribution model, contributing 76.21 percent of the total, with precipitation of the warmest quarter alone accounting for 36.73 percent. The salamanders favour areas with moderate precipitation during cold and wet seasons and mild summer temperatures, with the highest probability of presence at average air temperatures around 20 to 24 degrees Celsius. Excessive precipitation proved detrimental, with suitability dropping sharply above 500 millimetres in the wettest quarter, likely because strong currents and prolonged flooding threaten larvae and disrupt the submerged nests that males guard. Slope also mattered, with suitability rising up to a mean of 17 percent before declining in steeper terrain, while land-use variables contributed relatively little.

Perhaps the most unexpected result concerns geography. The current habitat suitability map reveals highly suitable areas both within and beyond the species’ known range. In the northern part of Honshu Island, far from any confirmed salamander populations, the model identified 42,508 square kilometres of high-suitability habitat. Yet the salamanders cannot reach them. The Japanese Alps, a mountain chain bisecting Honshu, form an impassable natural barrier for a fully aquatic species that cannot climb terrestrial environments outside of riverine areas. The team’s analysis suggests that climatic differences between northern and southern Japan do not explain the species’ absence in the north; rather, it is the biogeography of the Alps that has confined the salamander to the south-western regions of the island.

Within the current distribution range, which covers 59,193 square kilometres, the picture is already mixed. Thirty percent of the area was identified as unsuitable, 37 percent as low suitability, 22 percent as moderate and just 11 percent as high suitability. The projections for the future are more alarming. Considering the extent of the current range, more than 50 percent of the geographic area is expected to lose habitat suitability at any point between 2050 and 2090, under both the optimistic SSP126 scenario and the pessimistic SSP370 scenario. The most severe loss, affecting 64.5 percent of the area, is predicted for 2090 under the pessimistic scenario. Gains in suitability do occur, reaching 14.5 percent of the area in 2070 under the optimistic scenario, but they are insufficient to offset the losses.

The mechanisms behind these projected losses are rooted in the salamander’s physiology. Japanese giant salamanders prefer relatively cold mountainous streams with high levels of dissolved oxygen, which promotes cutaneous respiration. Rising air temperatures raise water temperatures and reduce dissolved oxygen concentrations, a critical parameter for survival. Heavy and sustained rainfall is also expected to increase across Japan, raising the frequency of flooding events that particularly affect larval stages and nesting sites. A study on the North American giant salamander, or hellbender, showed that a two-degree increase in water temperature decreased immune function and growth rate while increasing physiological stress, offering a sobering parallel for what warming may mean for the Japanese species.

The conservation implications are complex. The species was reassessed from Near Threatened to Vulnerable on the 2022 IUCN Red List, but many populations are declining and the salamander’s long life expectancy makes the true status of populations difficult to assess. Habitat fragmentation from dams, built for agriculture and flood control, blocks movement along waterways and reduces breeding microhabitat availability. Without connectivity between habitats, even the suitable areas identified by the models would be inaccessible to the salamanders. Interestingly, the declining human population in rural Japan may offer some relief, as unmaintained agricultural dams eventually burst and restore connectivity, though new flood-control infrastructure linked to climate change threatens many habitats.

The study calls for new surveys based on the projected maps, particularly on Shikoku and Kyushu islands where distribution data remain sparse, and for fine-scale research on disturbances to aquatic habitats. Environmental DNA surveys could identify previously unknown populations, followed by visual confirmation at positive sites. Because giant salamanders act as top predators structuring aquatic communities, protecting their habitat may benefit other species relying on the same streams, an umbrella effect that amplifies the conservation value of every stream saved. As climate change tightens its grip on the cold, clear waters these ancient creatures depend upon, the race is on to understand and preserve what remains of their world before the living fossil becomes a fossil in fact.

Subject of Research: Projected climate-driven loss of habitat suitability and distribution range of the endangered Japanese giant salamander

Article Title: Loss of habitat suitability and distribution range of the endangered Japanese giant salamander under climate change

Article References: Duret, C., Bartet, T., Hambuckers, A., Kishida, O., Okada, S., Taguchi, Y., Takahashi, M. K., & Denoël, M. (2025). Loss of habitat suitability and distribution range of the endangered Japanese giant salamander under climate change. Frontiers of Biogeography, 18, Article e133105. https://doi.org/10.21425/fob.18.133105

Image Credits: AI Generated

DOI: 10.21425/fob.18.133105

Keywords: Japanese giant salamander, Andrias japonicus, climate change, species distribution models, MaxEnt, habitat suitability, amphibian conservation, biogeography, Japanese Alps, habitat fragmentation, Frontiers of Biogeography, freshwater megafauna

Plestiodon tamdaoensis has a long and scattered history in the scientific literature. The species was described in 1937 by the French herpetologist René Bourret from specimens collected in Tam Dao National Park in northern Vietnam, and for decades it remained known from only a handful of localities. Today it is recorded from evergreen forests in the Vietnamese provinces of Ha Giang, Cao Bang, Bac Kan, Vinh Phuc, Bac Giang, Hai Duong, Son La, Hoa Binh, Thanh Hoa, and Nghe An, as well as from Hong Kong in southern China, at elevations between 300 and 1,200 meters above sea level. Despite this spread, the International Union for Conservation of Nature currently lists the species as Least Concern largely because so little is known about its true distribution and population status.

Scincella devorator, by contrast, is a much younger species with an even murkier record. Darevsky, Orlov and Ho described it in 2004 from Quang Ninh Province in northeastern Vietnam, originally placing it in the genus Sphenomorphus. In 2011, Nguyen reported the species from Yen Tu Mountain in Bac Giang Province and transferred it to the genus Scincella based on two diagnostic traits: a lower eyelid bearing an opaque window, and a lower secondary temporal scale that overlaps the upper one. Subsequent records from Vinh Phuc and Son La provinces extended its known range, but the species remains endemic to northern Vietnam and is classified as Data Deficient on the IUCN Red List, meaning scientists lack even the basic information needed to assess its extinction risk.

The new records come from Ba Vi National Park, a 10,814.6-hectare protected area that spans Ba Vi District of Hanoi and the Luong Son and Ky Son districts of Hoa Binh Province. The park sits in the subtropical climate zone of northern Vietnam, with an annual average rainfall of 900 millimeters, an average temperature of 21.8 degrees Celsius, and average humidity of 79 percent. Its natural habitat above 600 meters consists of evergreen mixed forest of conifers and broadleaf trees. Survey teams working along two forest trails, one leading toward Vua Peak and another toward the Old Church, searched for reptiles between 8:30 in the morning and 4:00 in the afternoon, collecting specimens by hand under guidelines approved by the American Society of Ichthyologists and Herpetologists.

The Plestiodon tamdaoensis specimen, a subadult collected on 28 August 2024 near the Old Church trail at 810 meters elevation, matched the historical descriptions of the species in every measurable detail. Its snout-vent length was 30.5 millimeters and its tail length 46.5 millimeters. The researchers documented large supranasal scales in contact with each other, frontoparietals touching, an interparietal larger than the frontoparietals, separated parietals, two pairs of nuchal scales, four supraoculars, and a scaly lower eyelid. The animal had 24 rows of smooth midbody scales, 45 paravertebral scales, and 52 transverse rows of ventral scales. In life, its head and body were black with two cream stripes running from head to tail base, its flanks were black-brown with a cream stripe on each side, and its tail glowed bright green above, a striking coloration that fades to brown in preservation.

The Scincella devorator specimen, an adult female collected on 28 July 2023 near Vua Peak at 1,105 meters, was found under a carpet of fallen leaves at mid-morning. It measured 56.5 millimeters in snout-vent length with a 76.1-millimeter tail. Key anatomical features confirmed its identity, including the large undivided opaque window in the lower eyelid that gives Scincella skinks their characteristic appearance, the absence of supranasals, prefrontals separated from each other by the frontal scale, three pairs of enlarged nuchal scales, and 28 rows of midbody scales. In life the animal was lightly brownish gray with a wide black vertebral stripe, two pale gray bands extending from the head to the tail base, and a distinct black stripe running from behind the eye to the hind limb. Both skinks were found in disturbed evergreen forest of medium hardwood and shrub, with humidity between 70 and 85 percent and air temperatures between 26 and 32 degrees Celsius.

To understand where else these skinks might occur, the team turned to species distribution modeling, a technique that uses known occurrence records together with environmental data to predict suitable habitat across the landscape. The researchers compiled all published records of both species from papers, field reports, and proceedings, cleaned the datasets following standard protocols, and used the spThin package in R to remove spatial autocorrelation by thinning localities closer than five kilometers apart. This produced a final input set of just six records for Scincella devorator and eleven for Plestiodon tamdaoensis, small numbers that reflect how rarely these animals are encountered. The team then ran MaxEnt version 3.4.4, a widely used maximum-entropy modeling program, with 19 bioclimatic variables from the WorldClim 2.1 database at 30-arcsecond resolution, restricting the study area to a two-degree buffer around the minimum convex polygon of known localities.

The modeling workflow was carefully tuned for reliability. The researchers tested feature class combinations and regularization multiplier values from 0.5 to 10.0 in increments of 0.5, used 10,000 background points, and applied the jackknife method, which is recommended for species with few occurrence records. Model performance was assessed with the area under the curve, or AUC, a standard metric in which values above 0.9 generally indicate strong predictive power. The optimal model for Plestiodon tamdaoensis used a regularization multiplier of 2.5 with linear and quadratic feature classes and achieved an AUC of 0.9142, while the best model for Scincella devorator used a multiplier of 2.0 with the same feature classes and reached an AUC of 0.8967. Final maps were thresholded using the 10 percent training presence rule to separate suitable from unsuitable areas.

The results were striking. The model predicts that Plestiodon tamdaoensis could occupy roughly 110,000 square kilometers across northern Vietnam and a small area of southern China, while Scincella devorator could range over approximately 130,000 square kilometers spanning northern Vietnam, southern China, and northern Laos. Both predictions encompass all known records, including the new Ba Vi localities, and both dramatically exceed the current IUCN range maps for the species. The authors caution, however, that the relatively high regularization multiplier values mean the final models are slightly generalized, and the small number of input localities means the predictions should be interpreted as potential zones rather than confirmed distributions, particularly at the edges of the mapped areas where populations may not actually exist.

Even with those caveats, the implications for conservation are significant. The models suggest that protected areas across northern Vietnam and adjacent parts of China and Laos, especially those covered by relatively large tracts of forest, probably form important strongholds for both skinks. The new records also bring the total number of reptile species recorded in Ba Vi National Park to 52. The researchers call for targeted surveys in promising but underexplored regions, particularly the Cuc Phuong, Ngoc Son Ngo Luong, Pu Luong, and Pu Hu areas spanning Thanh Hoa, Ninh Binh, and Hoa Binh provinces, and the Dong Son Ky Thuong area in Quang Ninh Province. For two skinks that have spent decades hiding in the leaf litter of Vietnam’s mountains, the message is clear: there is far more suitable habitat out there than anyone knew, and finding the animals that live in it will require looking in the right places.

Subject of Research: New distribution records and habitat modeling of two rare skink species in northern Vietnam

Article Title: New records and modeling potential distribution of Plestiodon tamdaoensis (Bourret, 1937) and Scincella devorator (Darevsky, Orlov & Ho, 2004) in Vietnam ( Scincidae )

Article References: Pham, A. V., Nguyen, A. T., Nguyen, A. M. H., Dao, L. T. T., Tran, C. H. T., Le, M. D., & Nguyen, T. Q. (2025). New records and modeling potential distribution of Plestiodon tamdaoensis (Bourret, 1937) and Scincella devorator (Darevsky, Orlov & Ho, 2004) in Vietnam (Scincidae). Herpetozoa, 38, 13-19. https://doi.org/10.3897/herpetozoa.38.e139606

Image Credits: AI Generated

DOI: 10.3897/herpetozoa.38.e139606

Keywords: skinks, Vietnam, Ba Vi National Park, Plestiodon tamdaoensis, Scincella devorator, species distribution modeling, MaxEnt, herpetology, conservation, IUCN Red List, Scincidae, biodiversity

The research team combined field surveys conducted during 2023 and 2024 with occurrence data drawn from the global GBIF biodiversity database, assembling records from all 13 population distribution areas where the species is found worldwide, including Vietnam, Thailand, Indonesia, Malaysia, Singapore, Australia and Papua New Guinea. With this dataset in hand, they turned to machine learning to answer a deceptively simple question: where, based on climate alone, could Bruguiera hainesii survive?

To model the species’ ecological niche, the researchers used Maxent, a widely adopted maximum-entropy algorithm that predicts species distributions from presence records and environmental layers. Nineteen bioclimatic variables were obtained from WorldClim version 2.1, and to avoid overfitting, any pair of variables correlated above 0.8 was pruned. Seven variables survived the screening: annual mean temperature, mean diurnal range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest quarter, annual precipitation and precipitation seasonality.

Two modelling pipelines were run in parallel. The first used Maxent software version 3.4.4 on a desktop platform, executed ten times with cross-validation, a random test-data seed and a maximum of 500 iterations, with a Jackknife test employed to evaluate the significance of each climatic variable and response curves generated to assess their impact. The second pipeline deployed the same algorithm on Google Earth Engine, a cloud-computing platform, incorporating both presence and pseudo-absence data. Model performance was validated using the Area Under the Curve (AUC) metric, where a value of 1 indicates perfect precision and values at or below 0.5 indicate performance no better than random guessing.

The desktop model decisively outperformed its cloud-based counterpart, achieving an AUC of 0.862 against 0.66 for the Google Earth Engine version. The high AUC indicates that the bioclimatic variables used in the model effectively explain the distribution range of Bruguiera hainesii, underscoring the critical role of climatic factors in shaping and maintaining its habitat. The weaker performance of the pseudo-absence model carries a practical lesson: for species with limited presence records or those inhabiting specialised environments such as mangrove forests, pseudo-absence data should be approached with caution, since random placement of absences can introduce inaccuracies.

Three climatic variables emerged as the decisive factors. The mean diurnal range — the difference between maximum and minimum temperatures within a day — contributed the most useful information when considered independently and also held the most distinct information not found in other variables, as revealed by the Jackknife test. The mean temperature of the driest quarter and the annual mean temperature completed the trio, together driving the model’s effectiveness in predicting habitat suitability. In other words, it is the stability of daily and seasonal temperatures, rather than rainfall alone, that defines where this rare mangrove can persist.

The resulting maps place the most suitable habitat squarely in Southeast Asia, encompassing Vietnam, Thailand, Indonesia, Malaysia, the Philippines, Singapore and Papua New Guinea, with parts of northern Australia also predicted to offer suitable conditions. Projections under the ACCESS-CM2 climate model — chosen for its high accuracy in the Asia region — and the medium-emission scenario SSP2-4.5, which assumes moderate socioeconomic development with coordinated emissions reductions, indicate a potential expansion of ideal habitats by 2080 to 2100, with a significant increase in the total area of high Habitat Suitability Index values across the region. The Habitat Suitability Index standardises predictions from 0 to 1, with values above 0.75 classified as highly suitable and below 0.45 as unsuitable.

The field component of the study provides the first detailed biological and ecological portrait of the Vietnamese population. The seven documented individuals on the Con Dao Islands average 15 metres in height with trunk diameters of 84 centimetres. The species possesses a distinctive aerial root system that resists erosion, stabilises soil and absorbs oxygen in the muddy, tidally submerged environment. Its small flowers, clustered in groups of two to three, predominantly bloom from January to March, yet fruiting trees are uncommon — a pattern consistent with the species’ notoriously low regeneration capacity. Soil analysis of 24 samples showed predominantly sandy composition exceeding 89 percent, slightly acidic to neutral pH between 4.62 and 6.77, moderate organic matter at 3.27 percent and low phosphorus at 0.04 percent.

The findings feed into a broader scientific conversation about mangroves and climate change. Research in the Gulf of Mexico and along the south-eastern coast of the United States indicates that warming temperatures and declining cold spells are enabling mangroves to expand poleward, with coverage increasing by 4.3 percent in Texas and southern Florida between 1980 and 2015. Mangroves possess complex adaptive mechanisms across morphology, anatomy, physiology and molecular biology that allow them to thrive in high-salinity, tidally fluctuating environments, and local assessments suggest Bruguiera hainesii may have reached the Con Dao Islands via ocean currents. Yet expansion is never straightforward: urbanisation, resource extraction and marine ecosystem changes can create barriers even where climatic conditions turn favourable, and local factors such as tidal range and sediment supply fundamentally shape how mangrove ecosystems respond to rising seas.

Herein lies the study’s central tension. The bioclimatic models suggest that Bruguiera hainesii could colonise new areas as temperatures and precipitation rise, potentially enhancing its distribution and ecological role. But climatic factors alone are evidently not responsible for the species’ global rarity. Its low regeneration capacity — possibly linked to poor seed viability, limited pollination or challenges in seedling establishment — remains a more critical limiting factor than climate in determining population dynamics. The authors recommend prioritising habitat protection where the species already exists, while simultaneously pursuing research into overcoming the physiological barriers to regeneration, whether through enhanced seedling establishment, improved pollination rates or genetic approaches. On a small island with limited access to external sediment sources, rising sea levels are likely to reduce the species’ geographical distribution in Con Dao National Park, making the preservation of existing populations and the management of suitable habitats essential to ensuring the long-term survival of this critically endangered mangrove and the coastal ecosystems it supports.

Subject of Research: Bioclimatic niche modelling extends the potential range of the critically endangered mangrove Bruguiera hainesii in Vietnam and Southeast Asia under current and future climates.

Article Title: Global range extension of bioclimatic zone of Bruguiera hainesii C.G.Rogers 1919 ( Rhizophoraceae )

Article References: Pham, M.-P., Hoang, T. T. T., Pham, V. D., Pham, T. T., & Vu, D. D. (2025). Global range extension of bioclimatic zone of Bruguiera hainesii C.G.Rogers 1919 (Rhizophoraceae). One Ecosystem, 10, Article e142064. https://doi.org/10.3897/oneeco.10.e142064

Image Credits: AI Generated

DOI: 10.3897/oneeco.10.e142064

Keywords: Bruguiera hainesii, mangrove, bioclimatic niche modelling, Maxent, climate change, Vietnam, Con Dao, conservation, Global, range, extension, bioclimatic

The headline number, however, conceals a stark concentration of animals in a handful of rivers. The Chambal River alone accounted for 2,097 individuals, or 69.1 percent of all gharials recorded, followed by the Ghaghra River with 463 animals and the Girwa River with 158. At the other extreme, the survey teams found just one gharial in the Kosi, two in the Bagmati, and seven in the Babai, while nine other rivers supported only small remnant groups. Encounter rates told the same story: on the short but dense Girwa River, observers sighted 7.90 individuals per kilometre on average, and the Chambal yielded 5.18 per kilometre, while the main stem of the Ganga and the Kosi registered barely 0.02 individuals per kilometre, effectively empty of the species despite its name being attached to the entire basin.

Methodologically, the study relied on standardised boat-based visual encounter surveys conducted during the post-monsoon winter months, when gharials bask for long periods on exposed sandbanks and detection probability peaks. Crews moved downstream at a constant speed of 8 to 10 kilometres per hour in daylight hours, with two observers scanning banks through binoculars, logging an estimated 2,280 observer-hours across 190 days of fieldwork. Because each river was surveyed only once, the team deliberately reports counts as minimum population size rather than true abundance, a conservative choice that avoids the assumption that every animal present was seen. Body lengths were estimated visually and converted to five size classes, from hatchlings under 0.6 metres to adults exceeding 3 metres, with adult males identifiable by the ghara, the nasal protuberance that gives the species its name.

The size-class data offer clues about which rivers hold genuine breeding populations. Only the Chambal, Gandak, and Ghaghra rivers contained individuals from every size class, with a high proportion of animals larger than 1.8 metres, a pattern consistent with established breeding. Adult males, which make up less than 1 percent of the basin-wide total, were overwhelmingly concentrated in the Chambal, where 80 of the 107 males recorded were sighted. The Ramganga held 14 males, the Gandak six, the Girwa four, and the Ghaghra three; the remaining occupied rivers had none. Rivers lacking adult males cannot sustain reproduction, and their small populations may represent remnants or habitats too degraded for long-term persistence, underscoring the need for targeted nesting surveys and potentially for translocation of animals from more viable populations.

The long-term recovery picture comes from the Chambal, where the team analysed census data spanning 1979 to 2024 and fitted an exponential growth model. The result was a rate of increase of 7 percent per annum over 45 years, but the trajectory splits into two distinct phases. During the intensive grow-and-release era from 1979 to 1993, when captive-reared juveniles were released into protected habitat, the population grew at 15.6 percent per year, one of the fastest documented recoveries for any crocodilian. After 1993, growth slowed to 4.3 percent annually, a deceleration the authors attribute plausibly to stabilisation following the initial augmentation, though density-dependent effects, changing release intensity, and mounting pressures outside protected boundaries remain alternative explanations. Crucially, the researchers warn that this success story cannot be extrapolated to the wider basin, where their river-wise data reveal a markedly uneven and fragile status.

That caution is grounded in the habitat analysis, which used maximum entropy modelling to predict suitability across the entire river network. The team compiled 1,049 gharial occurrence records, spatially thinned to 556 points, and evaluated 168 candidate models combining different feature classes and regularisation multipliers, selecting two top models with area under the curve values of 0.95 and 0.97. Hydrological variables dominated the predictions: water extraction contributed 22 to 24 percent of model gain, followed by channel width and channel depth, together explaining roughly two-thirds of the modelled pattern. Bioclimatic factors such as precipitation of the warmest quarter played a secondary role, while slope, sand mining, and dry-quarter precipitation contributed minimally. When the final map was classified, only 1,320 kilometres, about 10.4 percent of the network, rated as highly suitable, with another 905 kilometres in the moderate class, leaving 10,716 kilometres, or 84.1 percent, in the very low suitability category.

Perhaps the most instructive finding concerns what the model did not emphasise. Widespread anthropogenic pressures such as fishing intensity and sand mining scored low in statistical importance, but the authors are careful to explain why: these threats co-occur almost everywhere in the basin, giving them little spatial contrast for a correlative model to detect, even though their demographic impacts, including entanglement mortality, nest destruction, and loss of basking and nesting sandbanks, can be severe wherever they occur. Field observations confirmed the ubiquity of these pressures. Sand mining was recorded along 100 percent of the surveyed Kosi and 87 percent of the Betwa, water extraction reached 93 percent on the Betwa and 91 percent on the Bagmati, and fishing activity and human presence were the most frequently observed threats across the basin. Statistical silence, the authors argue, is not evidence of harmlessness.

Climate adds a further layer of uncertainty. Overlaying four decades of downscaled temperature and precipitation data from the CHELSA database onto the suitability map, the researchers found measurable warming along 8,330 kilometres of river, about 65 percent of the network, and precipitation change along 7,090 kilometres. Yet the distribution of suitable habitat showed no consistent spatial association with climatic change: several climatically stable rivers such as the Ghaghra and Girwa held extensive suitable stretches, while some segments experiencing substantial warming remained largely unsuitable. One potential consequence deserves particular attention because gharials exhibit temperature-dependent sex determination, meaning incubation temperature dictates whether hatchlings are male or female. Warming trends near nesting sites could skew sex ratios over time in small recovering populations, and the authors recommend nest-temperature logging and periodic sex-ratio assessment at active nesting beaches in the Chambal and Girwa to catch any shift early.

The deeper lesson of the study is that releasing animals alone cannot rebuild a population if the river itself is degraded. Despite the release of more than 9,000 gharials into Ganga Basin rivers over the decades, most rivers still hold fewer than 100 individuals, and the Ken River, despite a 16-kilometre sanctuary, no longer supports gharials at all after releases stopped in 2007. Across the eleven rivers with both release records and current survey data, historical release effort correlated strongly with present-day counts, but the authors emphasise that where releases were paired with genuine habitat protection, as in the Chambal and Girwa, recovery followed; where protection was absent or inconsistent, animals vanished. The Ghaghra’s unexpectedly large population, apparently sustained by downstream dispersal from the augmented Girwa population upstream rather than by local breeding, illustrates how recovery depends on connected, functioning river systems.

For a species that has hovered at the edge of extinction twice in a century, the new assessment offers both reassurance and a warning. The reassurance is that sustained legal protection, habitat defence, and captive rearing demonstrably work, having lifted the Chambal population from near collapse to more than two thousand animals at 7 percent annual growth. The warning is that this stronghold represents most of what remains: outside a few protected reaches, 84 percent of the basin’s river network is now classed as very low suitability, adult males are nearly absent from most rivers, and sand mining, water extraction, and fishing gear continue to degrade and fragment what is left. The authors identify the Ghaghra, Gandak, Yamuna, and Sharda as priority rivers for restoration and targeted supplementation, and they call for integrated basin-scale monitoring to replace the sporadic, site-specific surveys that have historically obscured the true state of the species. Whether the gharial’s comeback becomes a genuine range-wide recovery or remains confined to a few sanctuary stretches will depend, they conclude, on protecting the rivers themselves, not merely the animals that swim in them.

Subject of Research: Population status and habitat suitability of the critically endangered gharial in the Ganga River Basin

Article Title: Recovery of the critically endangered gharial (Gavialis gangeticus) amid escalating anthropogenic pressures in the Ganga River Basin

Article References: Hussain, S. A., Sharma, S. P., Panda, A. K., Usmani, A. A., Das, G. C., Mahar, N., Rawat, A. P., Sarkar, A., Pichaimuthu, G., Ugemuge, S., Ali, S. Z., Barthwal, S., & Badola, R. (2026). Recovery of the critically endangered gharial (Gavialis gangeticus) amid escalating anthropogenic pressures in the Ganga River Basin. Frontiers in Conservation Science, 7, Article 1920905. https://doi.org/10.3389/fcosc.2026.1920905

Image Credits: AI Generated

DOI: 10.3389/fcosc.2026.1920905

Keywords: gharial, Gavialis gangeticus, Ganga River Basin, crocodilian conservation, population survey, habitat suitability modelling, MaxEnt, National Chambal Sanctuary, sand mining, water extraction, critically endangered species, river restoration