Accelerated shifts in terrestrial life zones under rapid climate change

How Much Warming Can Mosquito Vectors Tolerate?

Climate warming is expected to substantially impact the global landscape of mosquito-borne disease, but these impacts will vary across disease systems and regions. Understanding which diseases, and where within their distributions, these impacts are most likely to occur is critical for preparing public health interventions. While research has centered on potential warming-driven expansions in vector transmission, less is known about the potential for vectors to experience warming-driven stress or even local extirpations. In conservation biology, species risk from climate warming is often quantified through vulnerability indices such as thermal safety margins-the difference between an organism's upper thermal limit and its habitat temperature. Here, we estimated thermal safety margins for 8 mosquito species that are the vectors of malaria, dengue, chikungunya, Zika, West Nile and other major arboviruses, across their known ranges to investigate which mosquitoes and regions are most and least vulnerable to climate warming. We find that several of the most medically important mosquito vector species, including Ae. aegypti and An. gambiae, have positive thermal safety margins across the majority of their ranges when realistic assumptions of mosquito behavioral thermoregulation are incorporated. On average, the lowest climate vulnerability, in terms of both the magnitude and duration of thermal safety, was just south of the equator and at northern temperate range edges, and the highest climate vulnerability was in the subtropics. Mosquitoes living in regions including the Middle East, the western Sahara, and southeastern Australia, which are largely comprised of desert and xeric shrubland biomes, have the highest climate vulnerability across vector species.

Spatial benefit assessment and marine climate response of coastal zone in Fujian Province under cross-system influence

To gain a scientific understanding of the cross-system impact of coastal zones and promote the sustainable development and protection of coastal areas, we constructed a spatial benefit evaluation system that encompassed both terrestrial and marine systems, focusing on the ecological, economic, and social dimensions. We employed the entropy method, moving average method, and Mann-Kendall trend test to quantitatively characterize the spatial benefits of the coastal zone in Fujian Province, China, and the evolution of the marine climate from 2005 to 2020. Building on this, the grey relational analysis method was applied to investigate the correlation between spatial benefits and marine climate and to explore the trends and magnitude of the impact of marine climate on spatial benefits. During the study period, the spatial benefits of the coastal zone in Fujian Province exhibited a fluctuating pattern of an initial increase followed by a decrease, with spatial benefits varying among cities. The role of the economic system in enhancing spatial benefits was not considerable. Changes in the marine climate aligned with the global warming trend, with the most considerable changes observed in sea level and tropical cyclone frequency and intensity, which are sensitive to human activities. There was a high degree of correlation between coastal zone spatial benefits and marine climate, with seawater salinity being most closely related to spatial benefits, while tropical cyclones showed the weakest correlation. The results of this study support sustainable development efforts in coastal zones.

Spatially heterogeneous selection and inter-varietal differentiation maintain population structure and local adaptation in a widespread conifer

BACKGROUND

Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) plays a critical role in the ecology and economy of Western North America. This conifer species comprises two distinct varieties: the coastal variety (var. menziesii) along the Pacific coast, and the interior variety (var. glauca) spanning the Rocky Mountains into Mexico, with instances of inter-varietal hybridization in Washington and British Columbia. Recent investigations have focused on assessing environmental pressures shaping Douglas-fir's genomic variation for a better understanding of its evolutionary and adaptive responses. Here, we characterize range-wide population structure, estimate inter-varietal hybridization levels, identify candidate loci for climate adaptation, and forecast shifts in species and variety distribution under future climates.

RESULTS

Using a custom SNP-array, we genotyped 540 trees revealing four distinct clusters with asymmetric admixture patterns in the hybridization zone. Higher genetic diversity observed in coastal and hybrid populations contrasts with lower diversity in inland populations of the southern Rockies and Mexico, exhibiting a significant isolation by distance pattern, with less marked but still significant isolation by environment. For both varieties, we identified candidate loci associated with local adaptation, with hundreds of genes linked to processes such as stimulus response, reactions to chemical compounds, and metabolic functions. Ecological niche modeling revealed contrasting potential distribution shifts among the varieties in the coming decades, with interior populations projected to lose habitat and become more vulnerable, while coastal populations are expected to gain suitable areas.

CONCLUSIONS

Overall, our findings provide crucial insights into the population structure and adaptive potential of Douglas-fir, with the coastal variety being the most likely to preserve its evolutionary path throughout the present century, which carry implications for the conservation and management of this species across their range.

Predicted community consequences of spatially explicit global change-induced processes on plant-insect networks

Plant-insect trophic systems should be particularly sensitive to processes altering species spatial co-occurrences, as impacts on one level can cascade effectively through the strong trophic reliance to the other level. Here, we predicted the biogeography of Lepidoptera-plant communities under global-change scenarios, exploiting spatially resolved data on 423 Lepidoptera species and their 848 food plants across the German state of Baden-Württemberg (ca. 36,000 km2). We performed simulations of plant extinction and Lepidoptera expansion, and respectively assessed their cascading consequences-namely secondary extinction of Lepidoptera and change in functional distance of plants-on the interaction networks. Importantly, the simulations were spatially explicit, as we accounted for realistic landscape contexts of both processes: Plant extinctions were simulated as "regional" (a species goes extinct in the whole region at once) vs. "isolation-driven" (a species gradually goes extinct from the peripheral or isolated localities according to its real regional distribution); Lepidoptera expansions were simulated with random, northward, and upward directions according to real topography. The consequences were assessed based on empirical community composition and trophic relationships. When evaluated by regional richness, the robustness of Lepidoptera assemblages against secondary extinctions was higher under isolation-driven plant extinctions than regional plant extinction; however, this relationship was reversed when evaluated by averaged local richness. Also, with isolation-driven plant extinctions, Lepidoptera at the central sub-region of Baden-Württemberg appeared to be especially vulnerable. With Lepidoptera expansions, plants' functional distances in local communities dropped, indicating a possible increase of competition among plants, yet to a lesser extent particularly with upward movements. Together, our results suggested that the communities' composition context at the landscape scale (i.e., how communities, with respective species composition, are arranged within the landscape) matters when assessing global-change influences on interaction systems; spatially explicit consideration of such context can reveal localised consequences that are not necessarily captured via a spatially implicit, regional perspective.

Evaluating ecosystem protection and fragmentation of the world's major mountain regions

Conserving mountains is important for protecting biodiversity because they have high beta diversity and endemicity, facilitate species movement, and provide numerous ecosystem benefits for people. Mountains are often thought to have lower levels of human modification and contain more protected area than surrounding lowlands. To examine this, we compared biogeographic attributes of the largest, contiguous, mountainous region on each continent. In each region, we generated detailed ecosystems based on Köppen-Geiger climate regions, ecoregions, and detailed landforms. We quantified anthropogenic fragmentation of these ecosystems based on human modification classes of large wild areas, shared lands, and cities and farms. Human modification for half the mountainous regions approached the global average, and fragmentation reduced the ecological integrity of mountain ecosystems up to 40%. Only one-third of the major mountainous regions currently meet the Kunming-Montreal Global Biodiversity Framework target of 30% coverage for all protected areas; furthermore, the vast majority of ecosystem types present in mountains were underrepresented in protected areas. By measuring ecological integrity and human-caused fragmentation with a detailed representation of mountain ecosystems, our approach facilitates tracking progress toward achieving conservation goals and better informs mountain conservation.

Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

Prediction of volatility and seasonality vegetation by using the GARCH and Holt-Winters models

Seasonality and volatility of vegetation in the ecosystem are associated with climatic sensitivity, which can have severe consequences for the environment as well as on the social and economic well-being of the nation. Monitoring and forecasting vegetation growth patterns in ecosystems significantly rely on remotely sensed vegetation indices, such as Normalized Difference Vegetation Index (NDVI). A novel integration of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and the Holt-Winters (H-W) models was used to simulate the seasonality and volatility of the three different agro-climatic zones in Jharkhand, India: the central north-eastern, eastern, and south-eastern agro-climatic zones. MODIS Terra Vegetation Indices NDVI data MOD13Q1, from 2001 to 2021, was used to create NDVI time series volatility and seasonality modeled by the GARCH and the H-W models, respectively. GARCH-based Exponential GARCH (EGARCH) [1,1] and Standard GARCH (SGARCH) [1,1] models were used to check the volatility of vegetation growth in three different agro-climatic zones of Jharkhand. The SGARCH [1,1] and EGARCH [1,1] models for the western agro-climatic zone experienced the best indicator as it has maximum likelihood and minimal Schwarz-Bayesian criterion and Akaike information criterion. The seasonality results showed that the additive H-W model showed better results in the eastern agro-climatic zone with the optimized values of MAE (16.49), MAPE (0.49), NSE (0.86), RMSE (0.49), and R2 (0.82) followed by the south-eastern and central north-eastern agro-climatic zones. By utilizing the H-W and GARCH models, the finding demonstrates that vegetation orientation and monitoring seasonality can be predicted using NDVI.

The global biogeography of tree leaf form and habit

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Key triggers of adaptive genetic variability of sessile oak [Q. petraea (Matt.) Liebl.] from the Balkan refugia: outlier detection and association of SNP loci from ddRAD-seq data

Knowledge on the genetic composition of Quercus petraea in south-eastern Europe is limited despite the species' significant role in the re-colonisation of Europe during the Holocene, and the diverse climate and physical geography of the region. Therefore, it is imperative to conduct research on adaptation in sessile oak to better understand its ecological significance in the region. While large sets of SNPs have been developed for the species, there is a continued need for smaller sets of SNPs that are highly informative about the possible adaptation to this varied landscape. By using double digest restriction site associated DNA sequencing data from our previous study, we mapped RAD-seq loci to the Quercus robur reference genome and identified a set of SNPs putatively related to drought stress-response. A total of 179 individuals from eighteen natural populations at sites covering heterogeneous climatic conditions in the southeastern natural distribution range of Q. petraea were genotyped. The detected highly polymorphic variant sites revealed three genetic clusters with a generally low level of genetic differentiation and balanced diversity among them but showed a north-southeast gradient. Selection tests showed nine outlier SNPs positioned in different functional regions. Genotype-environment association analysis of these markers yielded a total of 53 significant associations, explaining 2.4-16.6% of the total genetic variation. Our work exemplifies that adaptation to drought may be under natural selection in the examined Q. petraea populations.

Threatened species could be more vulnerable to climate change in tropical countries

Climate change is a major threat impacting insects globally, yet the impact on tropical insects is largely unknown. Here, I assessed the climatic vulnerability of Bangladeshi butterflies (242 species). About 42 % of species could experience range contraction, and the impact could be significantly more severe among threatened species. Depending on Socio-Economic Pathways (ssps), the future climatic condition could be unsuitable for 2 (ssp126) - 34 % (ssp585) species. The mean elevation of the suitable habitat could increase by 238 %, and the situation could be more severe for the threatened butterflies. Further, 54 % of the realised niche of butterflies could be altered. Although there might be no significant association between the shift in habitat suitability along the elevational gradient, migratory species could experience a more significant shift than non-migrants. Overall, climate change could have a severe impact on Bangladeshi butterflies. To mitigate insect decline globally and meet the Post 2020 Biodiversity Framework targets, immediate detection of climate change impact on tropical insects and developing effective conservation strategies is essential.

Realizing the potential of restoration science

Restoration science is growing fast. The restoration of habitats is increasingly part of the discussion over how to tackle the challenges of climate change, biodiversity loss and rural development. With this increasing role and attendant visibility, restoration science has seen increasing controversy. Here I describe six aspects of robust restoration science that should be kept in mind to help realize its potential: do data-driven studies; focus on robust results; improve reproducibility; contextualize the results; give attention to economics; consider the wider goals of restoration. Realizing the potential of restoration science, via robust scientific studies, will provide society with the knowledge and tools to make better choices about which habitats to restore and where. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.

To harness traits for ecology, let’s abandon ‘functionality’

Traits are measurable features of organisms. Functional traits aspire to more. They quantify an organism's ecology and, ultimately, predict ecosystem functions based on local communities. Such predictions are useful, but only if 'functional' really means 'ecologically relevant'. Unfortunately, many 'functional' traits seem to be characterized primarily by availability and implied importance - not by their ecological information content. Better traits are needed, but a prevailing trend is to 'functionalize' existing traits. The key may be to invert the process, that is, to identify functions of interest first and then identify traits as quantifiable proxies. We propose two distinct, yet complementary, perspectives on traits and provide a 'taxonomy of traits', a conceptual compass to navigate the diverse applications of traits in ecology.

A climate risk analysis of Earth's forests in the 21st century

Earth's forests harbor extensive biodiversity and are currently a major carbon sink. Forest conservation and restoration can help mitigate climate change; however, climate change could fundamentally imperil forests in many regions and undermine their ability to provide such mitigation. The extent of climate risks facing forests has not been synthesized globally nor have different approaches to quantifying forest climate risks been systematically compared. We combine outputs from multiple mechanistic and empirical approaches to modeling carbon, biodiversity, and disturbance risks to conduct a synthetic climate risk analysis for Earth's forests in the 21st century. Despite large uncertainty in most regions we find that some forests are consistently at higher risk, including southern boreal forests and those in western North America and parts of the Amazon.