The research was carried out by Ayşe Özlem Tursun of Malatya Turgut Özal University, who combined experimental plant physiology with species distribution modeling, a pairing that remains surprisingly uncommon in climate-impact studies. Conventional distribution models treat a species as a passive follower of climate envelopes, predicting where conditions might be tolerable but saying little about whether the organism will perform better or worse once it arrives. By integrating experimentally derived physiological responses, Tursun’s framework attempts to capture how photosynthesis, growth and secondary metabolite production in lemon balm shift under the novel thermal and atmospheric regimes of the coming decades, and then translates those responses into a scenario-based sensitivity analysis of range change.

The modeling backbone of the study is the Maximum Entropy algorithm, or MaxEnt, one of the most widely used tools for mapping potential species distributions from presence-only records. Tursun assembled 117 spatially independent occurrence records for lemon balm, drawing on a formally documented download from the Global Biodiversity Information Facility, and paired them with bioclimatic variables from the WorldClim version 2.1 database. To keep the projections honest, model complexity was tuned using spatial block cross-validation, a technique that separates training and testing data geographically so the model cannot simply memorize local conditions. The resulting statistics were strong: a training area under the curve of 0.825, a test AUC of 0.878, and a True Skill Statistic of 0.620, values that indicate the model discriminates suitable from unsuitable habitat considerably better than chance.

Two climatic variables emerged as the decisive levers shaping where lemon balm can live. The minimum temperature of the coldest month, known among modelers as Bio6, contributed most by variable importance, while the annual mean temperature, Bio1, ranked highest by permutation importance. In plain terms, lemon balm’s Turkish distribution is governed above all by how cold winters get and how warm the year runs on average. That makes intuitive sense for a herb of Mediterranean and Irano-Turanian affinity, and it also explains the geography of the projected expansion: as winters soften and annual temperatures climb, the cold walls that currently fence the species into parts of western and southern Türkiye begin to dissolve.

The spatial pattern of the forecast is striking. Under all scenarios and both future time horizons, 2050 and 2070, the model projects progressive habitat expansion rather than contraction, with newly suitable territory emerging along the Black Sea coastline and across the northern Central Anatolian plateau. The expansion is pronouncedly poleward and upward in elevation, a signature consistent with the general expectation that species will track their thermal niches toward higher latitudes and altitudes. For a country whose medicinal and aromatic plant sector is economically and culturally significant, the map carries practical weight: it identifies where lemon balm cultivation might plausibly be established in the coming decades and where current strongholds could face shifting competitive and climatic conditions.

What lifts the study beyond a standard MaxEnt exercise is its treatment of carbon dioxide. Rising atmospheric CO2 does not merely warm the planet; it also fertilizes photosynthesis in many plant species, a physiological effect that pure correlative models routinely ignore. Drawing on earlier experimental work in which lemon balm was grown under different temperature and CO2 concentrations, Tursun ran a scenario-based sensitivity analysis to estimate how much of the projected expansion could be attributed to this fertilization effect. The answer was roughly 25.1 percentage points of the total expansion, a substantial share, though the analysis concluded that rising temperatures remain the dominant driver of the range shift. The result is a rare quantitative partitioning of the climatic and physiological components of a forecast range change.

Robustness was addressed through an ensemble assessment across three CMIP6 general circulation models. The coefficient of variation across the ensemble came out at just 5.6 percent, a low figure indicating that the expansion signal is not an artifact of one particular climate model’s quirks. The projections were run under two Shared Socioeconomic Pathways, SSP2-4.5 representing a moderate emissions trajectory and SSP5-8.5 representing a fossil-fuel-intensive future, and the direction of change held under both, with magnitude scaling with emissions. In a field where projections often swing wildly between climate models, that degree of agreement is notable and lends credibility to the headline number of a doubling of suitable area by mid-to-late century.

Yet the study’s own framing makes clear that a larger map is not an unalloyed good. Climate change poses what the author calls dual challenges to medicinal and aromatic plants: the contraction of suitable habitats on one hand, and the alteration of secondary metabolite biosynthesis under new thermal and atmospheric conditions on the other. For lemon balm, the commercial and medicinal value lies in its essential oils and phenolic compounds, and the scientific literature has long documented that environmental stressors, temperature and CO2 among them, can reshape the chemistry of such plants. A habitat that is climatically suitable may therefore produce raw material of different quality and potency than today’s harvests, a dimension that distribution maps alone cannot capture.

The methodological choices also deserve attention from practitioners. The occurrence data were spatially thinned to reduce sampling bias, the model was evaluated with metrics appropriate to presence-only modeling, and the threshold selection for converting continuous suitability scores into binary habitat maps followed established procedures for such data. The R script underlying the analysis was released as supplementary material, and the occurrence dataset carries a persistent citable DOI, making the workflow reproducible end to end. In an era when species distribution models increasingly inform conservation planning and agricultural policy, that transparency matters as much as the headline projection.

For Türkiye, the practical message is one of climate-smart agricultural planning. The identification of the Black Sea coast and northern Central Anatolia as zones of emerging suitability offers a forward-looking guide for growers, cooperatives and policymakers in the medicinal plant sector, suggesting where cultivation trials, land-use investments and conservation measures might be directed before the climate arrives. At the same time, the study is a reminder that even the winners of climate change live in a transformed world: a lemon balm field in 2070 will grow under different skies, breathe different air, and likely synthesize a different bouquet of compounds than its predecessors. The expansion of its habitat, dramatic as it is, is only the first chapter of the story.

Subject of Research: Projected habitat expansion of lemon balm in Türkiye under CMIP6 climate scenarios using integrated physiological and distribution modeling

Article Title: Integrating experimental physiological responses with species distribution modeling to forecast the future habitat expansion of Melissa officinalis L. in Türkiye under CMIP6 scenarios

Article References: Integrating experimental physiological responses with species distribution modeling to forecast the future habitat expansion of Melissa officinalis L. in Türkiye under CMIP6 scenarios. (n.d.). https://doi.org/10.1007/s00704-026-06613-0

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06613-0

Keywords: lemon balm, Melissa officinalis, species distribution modeling, MaxEnt, CMIP6, climate change, Türkiye, CO2 fertilization, medicinal plants, habitat expansion, bioclimatic variables, SSP scenarios

The research team, led by Hassan M. Alzain of the Yale School of the Environment, together with Hassan A. Alkhunaizi and Heba Bedair, set out to answer three questions that conservationists had never systematically addressed for this species: where could Ballota adenophora live today and in the future, how will climate change alter its habitat suitability, and which environmental variables control its distribution. The authors note that no global conservation assessment of the species exists under modern climate change scenarios, despite the plant’s endangered status and its restriction to one of the harshest environments on the planet.

To build their predictions, the researchers turned to species distribution modeling, or SDM, a technique that links known occurrence records with environmental data to map where a species can potentially survive. The team assembled 65 occurrence records from field surveys, published literature, unpublished reports, and the Global Biodiversity Information Facility. Because such a small sample can introduce serious bias into model predictions, the researchers generated ecologically realistic pseudo-absence points from areas where the species has not been reported, maintaining a balanced ratio of presences to pseudo-absences. They validated these points by comparing environmental conditions with true presence sites and ran sensitivity analyses to test how different selection strategies affected model performance.

Environmental data came from WorldClim 2.1 at a 2.5 arc-minute resolution, beginning with 19 standard bioclimatic variables. To avoid overfitting, the team screened the predictors for multicollinearity using the variance inflation factor, discarding any variable with a VIF above 5 or a correlation above 0.75. That filtering left three uncorrelated variables to drive the models: mean diurnal range, isothermality, and the mean temperature of the driest quarter. Future projections were based on the IPSL-CM6A-LR global circulation model, with ensemble averages applied to two contrasting Shared Socioeconomic Pathways for the far future period of 2061 to 2080. SSP126, the sustainability scenario, assumes low emissions and strong mitigation, while SSP585, the fossil-fueled development scenario, assumes high emissions with minimal climate action. By bracketing the range from optimistic to pessimistic futures, the study aimed to capture the full spectrum of possible outcomes.

The modeling itself used an ensemble approach, combining five algorithms within the sdm package in R: generalized linear models, random forest, support vector machines, radial basis function networks, and classification and regression trees. Ensembles are favored because they reduce the uncertainty and bias inherent in any single algorithm. Seventy percent of the data trained the models and thirty percent was reserved for testing, with accuracy evaluated using the area under the receiver-operating characteristic curve and the true skill statistic. The ensemble achieved a mean AUC of 0.75 and a TSS of 0.71, which the authors describe as exceptional accuracy for this kind of prediction. Random forest, support vector machines, and classification trees performed best among the individual algorithms.

The results paint a precise picture of where the plant can persist. High habitat suitability today concentrates in Madinah, Tabuk, the Hisma range, Jabal Al Lauz, and Jabal Radua north of Yanbu, with the northwestern and southwestern parts of the country emerging as the most suitable zones. Among the three climatic drivers, the mean temperature of the driest quarter dominated, explaining nearly 55 percent of the variance, while mean diurnal range and isothermality contributed the remainder. The response curves revealed a telling pattern: the probability of presence falls as the diurnal temperature range and the temperature of the driest quarter increase, but rises with greater isothermality, meaning the plant favors places where day-to-night temperature swings are proportionally large relative to seasonal swings.

Under both future scenarios, the story was similar and sobering. Potential distribution declined by more than four percent by 2061 to 2080, while newly gained suitable areas amounted to only about 0.9 percent. The climatically stable zones, where conditions should remain hospitable, cluster in western Saudi Arabia in the Abha, Mekkah, and Madinah regions and in the northwest near the Red Sea, with some gains appearing in the Uruq Bani Ma’arid protectorate. These refugia, the authors argue, are the places where conservation investment will pay the greatest dividends, because they could shelter the species as the surrounding landscape grows hotter and drier.

The emphasis on diurnal temperature variation is more than a statistical curiosity. Diurnal temperature range is known to regulate key plant functions, including stomatal opening, central carbon metabolism, and the photoperiodic timing of flowering and the transition from vegetative to reproductive growth. The authors link the species’ sensitivity to the extreme thermal environment it inhabits, where daytime heating is intense and nighttime cooling can be sharp. They also note that observed warming trends in southwestern Saudi Arabia, in regions such as Abha, Al-Baha, and Jazan, project temperature increases of roughly 0.8 to 2.1 degrees Celsius across the mid-century periods, compounding the stress on a plant already adapted to the edge of what a desert can offer. A decline in diurnal temperature range, driven by rising nighttime minimum temperatures, cloud cover changes, greenhouse gas emissions, and urbanization, may further disrupt these delicate physiological balances.

The study is candid about its limitations. Saudi Arabia lacks systematic surveys of its endemic plants, so most occurrence records come from herbaria, databases, and literature that skew toward easily accessible locations and conspicuous species. Some populations, and potentially even species new to science, may have been entirely overlooked. The authors acknowledge that the moderate accuracy of their models and the limited underlying data may introduce bias into the projections, and it remains unclear whether the species currently occupies all the areas flagged as suitable. They call for extensive ground-truthing surveys to validate the predictions and to uncover the full extent of Saudi Arabia’s endemic diversity, warning that vegetation loss in the kingdom may exceed that of any other Middle Eastern nation.

Even so, the conservation implications are clear and actionable. Saudi Arabia, a party to the Convention on Biological Diversity, currently protects roughly four percent of its land through fifteen protected areas that span the country’s major physiographic regions, wetlands, mountain and coastal ecosystems, and viable populations of threatened species. The study’s authors urge policymakers to declare the identified hotspots as protectorates, arguing that focusing on areas of high potential habitat suitability would protect the largest number of species per unit area. They further recommend building transboundary ecological corridors to connect fragmented habitats, which would facilitate gene flow and boost genetic diversity, alongside enforcement programs, habitat restoration, stakeholder engagement, and adaptive monitoring. In a country already celebrated for rescuing the Arabian oryx and other flagship species from the brink, the tiny yellow-flowered mint of the northwest shrublands may be next in line, provided the maps produced by these models are translated into protected ground before the climate closes in.

Subject of Research: Climate change impacts on the potential distribution of the endangered endemic plant Ballota adenophora in Saudi Arabia

Article Title: Potential distribution of the endangered Ballota adenophora, endemic to Saudi Arabia under climate change scenarios: toward conservation prioritization

Article References: Alzain, H. M., Alkhunaizi, H. A., & Bedair, H. (2025). Potential distribution of the endangered Ballota adenophora, endemic to Saudi Arabia under climate change scenarios: toward conservation prioritization. Discover Ecology, 1(1), Article 6. https://doi.org/10.1007/s44396-025-00007-8

Image Credits: AI Generated

DOI: 10.1007/s44396-025-00007-8

Keywords: Ballota adenophora, species distribution modeling, climate change, Saudi Arabia, endemic plants, conservation prioritization, ensemble modeling, habitat suitability, SSP scenarios, bioclimatic variables, protected areas, desert biodiversity

Researchers led by Shimaa Mohamed Abduljalil of Tanta University and Mohamed G. Nasser and Sara A. Alashaal of Ain Shams University assembled an unusually large evidence base for their projections: 7,244 spatially independent occurrence records for the species, drawn largely from open biodiversity repositories such as the Global Biodiversity Information Facility. That scale matters. Presence-only distribution models are notoriously sensitive to sampling bias, and a species that lives alongside humans tends to be recorded wherever entomologists happen to live. By filtering records to remove spatial autocorrelation and evaluating model performance with spatially independent cross-validation, the team aimed to distinguish genuine climatic tolerances from the footprint of human observation.

The core of the analysis is maximum entropy modeling, or MaxEnt, a widely used machine-learning approach that estimates the probability of species presence by comparing known occurrence locations against the background environment. The authors paired their occurrence data with bioclimatic variables from the WorldClim database and, after testing for collinearity, settled on five optimized predictors: annual mean temperature (BIO1), annual temperature range (BIO7), temperature of the warmest quarter (BIO10), temperature of the coldest quarter (BIO11), and annual precipitation (BIO12). The resulting model performed strongly by the field’s standard benchmarks, achieving an area under the receiver operating curve of 0.82 and a true skill statistic of 0.86, indicating that the model discriminates suitable from unsuitable habitat far better than chance.

What limits the drain fly? According to the model, two variables dominate: annual mean temperature and annual precipitation. Annual temperature range, the difference between the hottest and coldest months, acts as an important constraint in regions with extreme thermal seasonality, a signal that the species is sensitive to large temperature fluctuations rather than simply to warmth alone. Meanwhile, cold-season thermal conditions, captured by the temperature of the coldest quarter, emerge as the principal brake on poleward expansion. In other words, the drain fly’s current distribution reflects a compromise between warmth, moisture, and a limited tolerance for harsh winters, an ecophysiological profile that makes its future fortunes tightly coupled to the trajectory of greenhouse gas emissions.

To peer into that future, the team projected habitat suitability under two contrasting representative concentration pathways. RCP 2.6 represents a mitigation scenario in which emissions are substantially curbed, while RCP 8.5 represents a high-emission future with continued strong warming. Projections were made for mid-century, around 2050, and end-of-century, around 2070, using coupled model outputs from CMIP5-class climate models. This two-scenario, two-timeframe design allows the researchers to separate the range dynamics that are essentially locked in from those that depend on how aggressively the world decarbonizes.

The projected changes are strikingly uneven across the globe. Under RCP 8.5, tropical and subtropical regions, which today form the heartland of suitable drain fly habitat, show net losses as conditions there shift beyond the species’ thermal tolerance or alter its moisture requirements. The Mediterranean basin and southwestern North America are projected to lose more than 8 percent of suitable habitat by 2070. The pattern echoes a growing body of evidence that some warm-adapted species face contraction at the equatorial edge of their ranges as temperatures climb past physiological limits, even while the cold barriers at their poleward edge dissolve.

Those dissolving barriers are exactly what the model shows in temperate and boreal Eurasia. Central Asia and East Asia stand out as major winners, gaining 8.9 percent and 9.2 percent suitable habitat respectively under RCP 8.5 by 2070. Under the mitigation scenario RCP 2.6, by contrast, distributional changes remain modest. That contrast is one of the study’s clearest messages: the magnitude of future range reshuffling for this synanthropic insect depends directly on emissions choices made over the coming decades. A world that keeps warming near the low pathway keeps the drain fly’s map roughly stable; a high-warming world hands it a large new climatic frontier.

Why should anyone care about a harmless-looking fly that hovers over bathroom sinks? The public health dimension is the reason the authors frame their results as more than biogeographic curiosity. Clogmia albipunctata has been documented as a mechanical vector of pathogenic microorganisms, carrying microbes picked up in drains and sewage into human environments. Studies in nosocomial settings have isolated a range of microorganisms from these flies, and the species has been implicated in cases of myiasis, the infestation of living human or animal tissue by fly larvae. A drain fly does not bite, but its close and constant association with human dwellings, hospitals, and wastewater infrastructure makes it an efficient bridge between contaminated substrates and the spaces where people live and receive care.

The synanthropic lifestyle also amplifies the model’s predictions. Unlike wildlife species whose range shifts depend on dispersal through fragmented natural habitat, the drain fly moves with human settlement and plumbing. Because suitable urban habitat exists across a broad swath of the temperate world, climatic suitability, rather than habitat availability, is likely the main gate on its expansion. As winters warm across Central Asia, East Asia, and other high-latitude regions, the cold-season constraint that currently holds the species back may relax, allowing established urban populations to persist and spread. The study’s authors argue that their suitability maps can therefore serve as a surveillance tool, helping public health authorities and vector control programs decide where to monitor first.

Methodologically, the paper sits within a mature tradition of species distribution modeling that has transformed climate change biology over the past two decades. MaxEnt’s presence-only framework, the use of spatially filtered occurrence data, collinearity screening of predictors, and spatially independent model evaluation all reflect hard-won lessons about what makes ecological niche models reliable rather than artifacts of sampling effort. The authors acknowledge, as the field broadly does, that bioclimate envelope models capture the climatic dimension of a species’ niche but not every ecological factor, from competition to human pest control, that shapes real distributions. Still, with a dataset of more than seven thousand records and performance metrics as strong as these, the projections offer a quantitative foundation for anticipating geographic shifts in a medically relevant species.

The broader story is one of biotic homogenization in the human age. As urbanization knits the planet’s cities into a continuous web of suitable microhabitat, and as warming erases the thermal fences that once kept warm-adapted insects out of temperate latitudes, species like Clogmia albipunctata are positioned to become even more ubiquitous. Whether that future materializes gently or dramatically depends, according to these models, on which emissions pathway humanity follows. For a fly that lives in our drains, the climate choices of the next few decades will help write its itinerary.

Subject of Research: Climate-driven global range shifts of the synanthropic drain fly Clogmia albipunctata modeled with species distribution projections

Article Title: Climate change-driven range shifts in a cosmopolitan synanthropic insect: global habitat suitability modeling and projections for Clogmia albipunctata

Article References: Abduljalil, S. M., Al-Quraishy, S., Abdel-Baki, A., Salem, M. L., Aboelhadid, S. M., Awad, E. M., Nasser, M. G., & Alashaal, S. A. (2026). Climate change-driven range shifts in a cosmopolitan synanthropic insect: global habitat suitability modeling and projections for Clogmia albipunctata. The Science of Nature, 113(5), Article 121. https://doi.org/10.1007/s00114-026-02164-6

Image Credits: AI Generated

DOI: 10.1007/s00114-026-02164-6

Keywords: drain fly, Clogmia albipunctata, climate change, range shift, species distribution modeling, MaxEnt, bioclimatic variables, public health, vector, synanthropic species, RCP scenarios, habitat suitability