Climate Metrics Research Articles

Nitrogenous and Phosphorus Soil Contents in Tierra del Fuego Forests: Relationships with Soil Organic Carbon, Climate, Vegetation and Landscape Metrics

Soil nitrogen (SN) and soil phosphorus (SP) contents support several ecosystem services and define the forest type distribution at local scale in Southern Patagonia. The quantification of nutrients during forest surveys requires soil samplings and estimations that are costly and difficult to measure. For this, predictive models of soil nutrients are needed. The objective of this study was to quantify SN and SP contents (30 cm depth) using different modelling approaches based on climatic, topographic and vegetation variables. We used data from 728 stands of different forest types for linear regression models to map SN and SP. The fitted models captured the variability of forest types well (R²-adj. 92–98% for SN and 70–87% for SP). The means were 9.3 ton ha−1 for SN and 124.3 kg ha−1 for SP. Overall, SN values were higher in the deciduous forests than those in the mixed evergreen, while SP was the highest in the Nothofagus pumilio forests. SN and SP are relevant metrics for many applications, connecting major issues, such as forest management and conservation. With these models, the quantification of SN and SP stocks across forests of different protection status (National Law 26,331/07) and national/provincial reserve networks is possible, contributing to the determination of nutrient contents at landscape level.

A metric-based framework for climate-smart conservation planning.

Climate change is already having profound effects on biodiversity, but climate change adaptation has yet to be fully incorporated into area-based management tools used to conserve biodiversity, such as protected areas. One main obstacle is the lack of consensus regarding how impacts of climate change can be included in spatial conservation plans. We propose a climate-smart framework that prioritizes the protection of climate refugia-areas of low climate exposure and high biodiversity retention-using climate metrics. We explore four aspects of climate-smart conservation planning: (1) climate model ensembles; (2) multiple emission scenarios; (3) climate metrics; and (4) approaches to identifying climate refugia. We illustrate this framework in the Western Pacific Ocean, but it is equally applicable to terrestrial systems. We found that all aspects of climate-smart conservation planning considered affected the configuration of spatial plans. The choice of climate metrics and approaches to identifying refugia have large effects in the resulting climate-smart spatial plans, whereas the choice of climate models and emission scenarios have smaller effects. As the configuration of spatial plans depended on climate metrics used, a spatial plan based on a single measure of climate change (e.g., warming) will not necessarily be robust against other measures of climate change (e.g., ocean acidification). We therefore recommend using climate metrics most relevant for the biodiversity and region considered based on a single or multiple climate drivers. To include the uncertainty associated with different climate futures, we recommend using multiple climate models (i.e., an ensemble) and emission scenarios. Finally, we show that the approaches we used to identify climate refugia feature trade-offs between: (1) the degree to which they are climate-smart, and (2) their efficiency in meeting conservation targets. Hence, the choice of approach will depend on the relative value that stakeholders place on climate adaptation. By using this framework, protected areas can be designed with improved longevity and thus safeguard biodiversity against current and future climate change. We hope that the proposed climate-smart framework helps transition conservation planning toward climate-smart approaches.

Multi-scale remote sensing-based landscape epidemiology of the spread of rapid ‘Ōhiʻa Death in Hawaiʻi

Fungal pathogens of the genus Ceratocystis recently introduced to the Island of Hawaiʻi have killed hundreds of thousands of native ‘Ōhiʻa trees, an ecologically and culturally important keystone species. Symptoms of the associated disease, Rapid ‘Ōhiʻa Death (ROD), have been found to be easily detectable with high resolution imaging spectroscopy. We used wall-to-wall maps of affected ‘Ōhiʻa canopy built in four consecutive years (2016–2019) to analyze how changes in the distribution and density of browning canopy detections over this time period corresponded to environmental drivers at two spatial scales. Island-wide we found 256,387 brown crowns across the 4-year period. The total amount of affected forest area nearly doubled from 66,972.2 ha in 2016 to 121,464.7 ha in 2019, cumulatively representing 42.5% of the 264,372 ha of forest area observed at least once in the study. However, most browning activity was concentrated in 18 hotspots totaling approximately 29,836 ha with brown crown densities as high as 26 ha−1. Using Random Forest (RF) models, we assessed the correspondence between 32 mapped environmental variables and measures of ROD spread calulated at 1-year time steps on a 300 m × 300 m grid across the island. We found that modelled probability of regional infection, or “susceptibility”, was dominated by distance to existing infection at the start of a time step; increasing distance from 0 to 600 m decreased susceptibility from 0.8 to 0.3. Other important factors – tree cover, average windspeeds, and LiDAR-derived 3-d crown exposure – were 4–10 times less important to the model. In a second RF model we studied regional infection “severity”, measured as detection density in first year of infection. In contrast to susceptibility, the severity model was significantly affected by numerous factors including windspeed metrics, canopy height and exposure as well as most weather and climate metrics related to water regime. Severity model predictions were less dominated by proximity to existing infection. In a separate regional analysis at 2 m resolution we found that taller trees were more prone to infection, and that trees on younger “historic” lava flows (i.e., substrates < 230 years old) showed slight but significantly lower infection rates than immediately adjacent older substrates. Our results document the extent and severity of ‘Ōhiʻa mortality across Hawaiʻi Island and provides insight into factors that appear to affect the spread of ROD; this information will inform management efforts to lessen the spread and impact of the disease on all the Hawaiian Islands.

Protected area planning to conserve biodiversity in an uncertain future.

Protected areas are a key instrument for conservation. Despite this, they are vulnerable to risks associated with weak governance, land-use intensification, and climate change. We used a novel hierarchical optimization approach to identify priority areas for expanding the global protected area system that explicitly accounted for such risks while maximizing protection of all known terrestrial vertebrate species. To incorporate risk categories, we built on the minimum set problem, where the objective is to reach species distribution protection targets while accounting for 1 constraint, such as land cost or area. We expanded this approach to include multiple objectives accounting for risk in the problem formulation by treating each risk layer as a separate objective in the problem formulation. Reducing exposure to these risks required expanding the area of the global protected area system by 1.6% while still meeting conservation targets. Incorporating risks from weak governance drove the greatest changes in spatial priorities for protection, and incorporating risks from climate change required the largest increase (2.52%) in global protected area. Conserving wide-ranging species required countries with relatively strong governance to protect more land when they bordered nations with comparatively weak governance. Our results underscore the need for cross-jurisdictional coordination and demonstrate how risk can be efficiently incorporated into conservation planning. Planeación de las áreas protegidas para conservar la biodiversidad en un futuro incierto.

OH reaction rate coefficients, infrared spectra, and climate metrics for (E)‐ and (Z)‐ 2‐perfluoroheptene (2‐C7F14) and 3‐perfluoroheptene (3‐C7F14)

AbstractIn this work, perfluoroheptene 2‐ and 3‐C7F14 stereoisomer specific gas‐phase OH reaction rate coefficients, k, were measured at 296 K in ∼600 Torr (He bath gas) using a relative rate (RR) method. Gas‐chromatography (GC) with electron capture detection (ECD) was used for the separation and detection of the stereoisomers. Rate coefficients for (E)‐2‐C7F14, (Z)‐2‐C7F14, (E)‐3‐C7F14, and (Z)‐3‐C7F14 were measured to be (in units of 10−13 cm3 molecule−1 s−1) (3.60 ± 0.51), (2.22 ± 0.21), (3.43 ± 0.47), and (1.48 ± 0.19), respectively, where the uncertainties include estimated systematic errors. Rate coefficients for the (E)‐ stereoisomers were found to be systematically greater than the (Z)‐ stereoisomers by a factor of 1.6 and 2.3 for 2‐C7F14 and 3‐C7F14, respectively. Atmospheric lifetimes with respect to OH radical reaction for (E)‐2‐C7F14, (Z)‐2‐C7F14, (E)‐3‐C7F14, (Z)‐3‐C7F14 were estimated to be ∼33, ∼56, ∼36, and ∼86 days, respectively, for an average OH radical concentration of 1 × 106 molecule cm−3. Quantitative infrared absorption spectra were measured as part of this work. Complimentary theoretically calculated infrared absorption spectra using density functional theory (DFT) are included in this work. The theoretical spectra were used to evaluate stereoisomer climate metrics. Radiative efficiencies (adjusted) and global warming potentials (GWPs, 100‐year time‐horizon), were estimated to be 0.12, 0.19, 0.12, and 0.23 W m−2 ppb−1 and 1.9, 5.1, 2.1, 9.3 for (E)‐2‐C7F14, (Z)‐2‐C7F14, (E)‐3‐C7F14, (Z)‐3‐C7F14, respectively. Atmospheric degradation mechanisms are discussed.

Highway to the Comfort Zone: History of the Psychrometric Chart

The psychrometric chart is the most common data visualization technique for the designers of thermal comfort systems worldwide. From its humble roots as means of expressing the characteristics of air in building systems design, the use of the chart has grown to include the representation of the zones of human thermal comfort according to both conventional and adaptive models. In this paper, we present an extensive history of this development and the fallacies with representing comfort simply as a box that sometimes moves on the chart. The origins of the link between refrigeration control and comfort control are examined through archival reviews, examining the works of Carrier, Yagoglou, and their contemporaries in the context of modern comfort mischaracterizations. A clearer understanding of the mapping of comfort, control, and climate metrics with psychrometrics is reported, and a critique of the conflation is reported to increase awareness of the limitations of such treatment of these three critical domains.

Impact of Building Energy Mitigation Measures on Future Climate

As cities are increasing technological efficacy on greenhouse gas (GH) emission reduction efforts, the surrounding urban ecosystems and natural resources may be affected by these measures. In this research, climate indicators such as heat index, extreme heat events, intensified urban heat islands (UHIs), and sea breeze are projected for the middle and end of the 21st century to understand the climate change signal on these variables with and without building energy mitigation measures. Cities amplify extreme heat and UHI impacts by concentrating large populations and critical infrastructure in relatively small areas. Here, we evaluate the combined climate and building energy mitigation impacts on localized climate metrics throughout the 21st century across extreme emission scenarios (RCP8.5) for the tropical coastal city of San Juan. The analysis of statistically downscaled global circulation model outputs shows underestimation for uncorrected summer daily maximum temperatures, leading to lower extreme heat intensity and duration projections from the present time which are corrected using bias-corrected techniques. High-resolution dynamic downscaling simulations reveal a strong dependency of changes in extreme heat events in urban settings, however, the intensities shift to lower-level grasslands and croplands with energy mitigation measures (combination of white roof, tilted photovoltaic roof, and efficient heating ventilation and air conditioning systems). The building energy mitigation measures have the potential of reducing the UHI intensities to 1 °C and 0.5 °C for the 2050 and 2100 climate periods, respectively.

Measurements of perfluoro-n-heptane and perfluoro-n-octane absorption cross-sections from 300 to 350 K

Perfluoroalkanes are fully fluorinated greenhouse gases. These compounds are chemically inert due to their C–F bonds and therefore have atmospheric lifetimes of thousands of years. Although regulated under the Kyoto Protocol, atmospheric concentrations of perfluoroalkanes have continued to increase since 1997. To quantify the climate impact of perfluoro-n-heptane and perfluoro-n-octane, spectral data are required to calculate climate metrics such as the radiative efficiency and global warming potential. Experimental measurements are scarce for these compounds and are only available at 296 and 297 K. In this work, a set of absorption cross-sections is provided in the range 515–1500 cm−1 at 0.1 cm−1 resolution for nine temperatures between 300 and 350 K. There is general agreement between literature values and the absorption cross-sections and climate metrics measured in this work. These quantities do not show significant temperature dependence. The temperature averaged radiative efficiency is 0.50 ± 0.06 and 0.54 ± 0.07 Wm−2ppbv−1 for n–C7F16 and n–C8F18, respectively. The temperature averaged 100-year global warming potential is 8738 ± 1149 for n–C7F16 and 8392 ± 1103 for n–C8F18.

Health Risks of Temperature Variability on Hospital Admissions in Cape Town, 2011-2016.

Epidemiological studies have provided compelling evidence of associations between temperature variability (TV) and health outcomes. However, such studies are limited in developing countries. This study aimed to investigate the relationship between TV and hospital admissions for cause-specific diseases in South Africa. Hospital admission data for cardiovascular diseases (CVD) and respiratory diseases (RD) were obtained from seven private hospitals in Cape Town from 1 January 2011 to 31 October 2016. Meteorological data were obtained from the South African Weather Service (SAWS). A quasi-Poisson regression model was used to investigate the association between TV and health outcomes after controlling for potential effect modifiers. A positive and statistically significant association between TV and hospital admissions for both diseases was observed, even after controlling for the non-linear and delayed effects of daily mean temperature and relative humidity. TV showed the greatest effect on the entire study group when using short lags, 0-2 days for CVD and 0-1 days for RD hospitalisations. However, the elderly were more sensitive to RD hospitalisation and the 15-64 year age group was more sensitive to CVD hospitalisations. Men were more susceptible to hospitalisation than females. The results indicate that more attention should be paid to the effects of temperature variability and change on human health. Furthermore, different weather and climate metrics, such as TV, should be considered in understanding the climate component of the epidemiology of these (and other diseases), especially in light of climate change, where a wider range and extreme climate events are expected to occur in future.

Evaluation of the CAS-ESM2-0 Performance in Simulating the Global Ocean Salinity Change

The second version of the Chinese Academy of Sciences Earth System Model, CAS-ESM2-0, is a newcomer that contributes to Coupled Model Intercomparison Project simulations in the community. We evaluated the model’s performance in simulating the salinity for climatology, seasonal cycles, long-term trends, and time series of climatic metrics by comparing it with the ensemble mean of available gridded observations. The results showed that CAS-ESM2-0 could reproduce large-scale patterns of ocean salinity climatology and seasonal variations, despite the fresh biases in the low- and mid-latitudes for climatology, stronger seasonal variation of sea surface salinity within 20° S–20° N, and large uncertainty with the zonal-band structure for 0–1000 m averaged salinity. For long-term changes, the model revealed increased contrast between the salinity of the Atlantic and Pacific basins. However, regional differences in locations and strengths for salinity pattern amplification suggest substantial uncertainty when simulating regional multidecadal salinity changes. The simulated variations in climate metrics for salinity pattern amplification are consistent with the observations and will continue to intensify until the end of this century. Our assessment provides new features of the CAS-ESM2-0 model and supports further studies on model development.

Climate change impacts of e-fuels for aviation in Europe under present-day conditions and future policy scenarios

‘E-fuels’ or ‘synthetic fuels’ are hydrocarbon fuels synthesized from hydrogen (H2) and carbon dioxide (CO2), where H2 can be produced via electrolysis of water or steam reforming of natural gas, and CO2 is captured from the combustion of a fossil or biogenic source or directly from the atmosphere. E-fuels are drop-in substitutes for fossil fuels, but their climate change mitigation benefits are largely unclear. This study evaluates the climate change impacts of e-fuels for aviation by combining different sources of CO2 and H2 up to 2050 under two contrasting policy scenarios. The analysis includes different climate metrics and the effects of near-term climate forcers, which are particularly relevant for the aviation sector. Results are produced for European average conditions and for Poland and Norway, two countries with high and low emission intensity from their electricity production mix. E-fuels can either have higher or lower climate change impacts than fossil fuels, depending on multiple factors such as, in order of importance, the electricity mix, the origin of CO2, the technology for H2 production, and the electrolyzer efficiency. The climate benefits are generally higher for e-fuels produced from CO2 of biogenic origin, while e-fuels produced from CO2 from direct air capture or fossil fuel combustion require countries with clean electricity to outperform fossil fuels. Synthetic fuels produced from H2 derived from natural gas have higher impacts than fossil fuels even when coupled with carbon capture and storage, if CO2 is sourced from fossil fuels or the atmosphere. Climate change impacts of e-fuels improve in the future, and they can all achieve considerable climate change mitigation in 2050relative to fossil jet fuel, provided that strict climate policy measures are implemented to decarbonize the electricity sector. Under reduced policy efforts, future climate impacts in 2050 of e-fuels from atmospheric or fossil CO2 are still higher than those of fossil jet fuels with an average European electricity mix. This study shows the conditions to maximize the climate change mitigation benefits of e-fuels, which essentially depend on progressive decarbonization of the electricity sector and on reduced use of CO2 sourced from fossil fuels.

Fires and their key drivers in Mexico

Background Despite the regional and global effects of biomass burning at national and pantropical scales, little effort has focused on determining the influence of climate and socioeconomic conditions on fire regimes in tropical regions. Aims We explored the climate and human factors that explain remotely sensed burnt area and fire abundance in Mexico. Methods We used MCD64A1 data and climate and socioeconomic metrics to understand factors explaining the variation in number of fires and burned area. Key results The largest burned area (41.9% of the total) occurred in temperate forests, grasslands and hydrophilic vegetation, with numerous fire events of medium relative size. The next most extensive burned area (38%) was observed in croplands, with numerous small-size fires. The third group (17.8%) occurred in tropical forests, which had the smallest and most frequent fires. Finally, a fourth group (11.9%) was composed of shrublands, which showed the largest fire sizes and lowest-frequency events. The variability of burned area was related to variations in temperature and precipitation, poverty index, altitude, and distance to water bodies. Conclusions and Implications Our analysis suggests that an assessment integrating climate, human and topographic metrics predicts burned area and may improve fire forecasting in Mexico landscapes.

Developing a smart tool for integrated climate action planning (ICLAP 2050) in Asia-Pacific Cities

In light of the growing global environmental challenges, smart cities need to serve as testing workshops or labs to smartly tackle complex cross-sectional issues like jobs, seamless mobility, safety and security, sustained growth, while responding to the impending climate change too. This necessitates for developing a smart model or tool that integrates such varied but crucial climate concerns of a city into its direct decision-making and long-term planning. In this research, we conduct a literature review to have an overview of the state-of-the-affairs on urban climate planning in Asia-Pacific Cities covering China, Japan, India, Philippines, Singapore and Thailand. This is followed by an intensive theoretical understanding on the need of having a smart tool in urban climate action planning. This includes the study of recent urban climate metrics and tools, their different typologies based on key purpose, method, sectoral and geographical scope, and challenges and gaps in formulating smart urban climate tools. We then introduce the conceptual framework for integrated climate action planning (ICLAP) tool that transects spatial, statistical and bibliometric methods. We establish applicability of ICLAP in case of Indian cities by discerning climate vulnerabilities, GHG trends and relevant urban climate solutions. The paper eventually culminates with major scientific findings and policy recommendations, essentially underscoring more intensive and wider application of ICLAP like smart urban climate tools in local decision making and national urban policies duly supported by international scientific collaborations.

The Water-Enhanced Turbofan as Enabler for Climate-Neutral Aviation

A significant part of the current aviation climate impact is caused by non-carbon-dioxide emissions, mainly nitrogen oxides (NOx) and contrails. It is, therefore, important to have a holistic view on climate metrics. Today’s conventional, but already well-developed, aero-engines are based on the Joule–Brayton cycle, and leave only limited room for improvement in climate impact. The revolutionary Water-Enhanced Turbofan (WET) concept represents a technical step change addressing all relevant emissions by implementing the Cheng cycle, which combines the gas turbine cycle with a Clausius–Rankine steam cycle. This paper builds upon previous publications regarding the WET concept, and outlines the evolution since then. Promising WET configurations are evaluated according to their ability to reduce global warming potential compared to an evolutionarily advanced turbofan engine. A quantitative approach to estimate reduction of NOx emissions through steam injection is presented. The impact on the creation of contrails is considered using the Schmidt-Appleman criterion. In conclusion, all three climate-relevant emissions can be reduced with the WET concept compared to a technologically similar turbofan in terms of CO2 (up to 10%), NOx (more than 90%), and contrails (more than 50%). The resulting in-flight climate impact can be reduced by more than 40% when using fossil kerosene, paving the way to climate-neutral aviation.

Ecologically relevant moisture and temperature metrics for assessing dryland ecosystem dynamics

AbstractIn drylands, water‐limited regions that cover ~40% of the global land surface, ecosystems are primarily controlled by access to soil moisture and exposure to simultaneously hot and dry conditions. Quantifying ecologically relevant environmental metrics is difficult in drylands because the response of vegetation to moisture and temperature conditions is not easily explained solely by climate‐based metrics. To address this knowledge gap, we developed and examined 27 climate and ecological drought metrics across dryland areas of the western United States. Included in the 27 metrics is a suite of 19 largely new “ecological drought metrics” that are designed to quantify multiple aspects of environmental limitation in drylands, including overall growing conditions, seasonal fluctuations, seasonal moisture timing, exposure to extreme drought and recruitment potential for perennial plants. To quantify these metrics, we simulated water balance pools and fluxes of daily soil moisture at multiple depths with historical weather from 1970 to 2010 using the SOILWAT2 ecosystem water balance model. We assessed the relationships among these metrics and their spatial and temporal patterns. We found that the inclusion of ecological drought metrics substantially increased the dimensionality of the climate metrics dataset; the number of independent variables needed to explain 90% of the variance in the dataset increased with the addition of ecological drought metrics. Spatial patterns in overall growing conditions represented well‐known differences among ecoregions, for example, high temperatures and low precipitation in the southwest and cool temperatures and greater precipitation in the northeast. Seasonal fluctuation in soil water availability (SWA) was greatest in the southwest (Mojave Desert), whereas fluctuation in climatic water deficit (CWD) was greatest in the northwest (northern Great Basin and Columbia Plateau). Seasonal timing of moisture also differed among metrics; the timing of wet degree days (WDD), the timing of SWA and the timing of CWD were only weakly related to seasonal timing of precipitation. Plant recruitment metrics varied strongly across western drylands. In the Great Plains, recruitment events occurred more frequently and lasted longer than in the intermountain regions, where recruitment events were comparatively rare and short. These ecological drought metrics provide new insight into patterns of soil moisture and temperature that shape the structure and function of dryland ecosystems. The metrics will be useful for assessing the potential impact of climate change on dryland ecosystems and developing adaptive resource management strategies to sustain dryland ecosystem services in a changing world.

Non‐uniform changes of growing conditions for sweet cherry trees responses to climate warming in main production regions of China

AbstractGiven the strong sensitivity of sweet cherry trees to air temperature and the foreseeable warming under future climates, it becomes urgent to analyse spatiotemporal variability of growing conditions in main production areas of China. Here, we estimated changes of three climate metrics, that is, winter chill, heat accumulation and the risk of spring frost events, by using 22 global climate models over the historical and future (represented by central years 2050s and 2085s) time stages. Statistically downscaled daily maximum and minimum temperatures at 14 sites under representative concentration pathway (RCP) 4.5 and 8.5 scenarios were used. The results show a general increase of available winter chill for most sites in Bohai and Lanzhou–Lianyungang Railway line agro‐climatic zones, and the increase in chill accumulation could reach up to 15.2% in these regions for RCP4.5 by 2085 s. However, the most dramatic winter chill decrease is projected to occur in the southwest region under the RCP8.5 scenario by 2085 s. Additionally, the increase rate of heat accumulation during the forcing period shows spatially consistency, and the most pronounced increase is found in the RCP8.5 by 2085 s. In the north region, median heat accumulation increases by 17.5%–21.0% in the 2050 s under RCP4.5. Similar increasing range could be found in the southwest station. High frost risk areas are found in the southwestern region for both baseline and future climate scenarios. Across the 14 study sites, Mengzi and Kunming have the highest meteorologically defined risk of spring damaging frost with accumulated 335 growing degree days (GDDs) and 264 GDDs before the last spring frost event, respectively. Overall, this study provides projected characteristics of site‐specific growing conditions for sweet cherry trees in main production regions. The results could be useful for decision‐making such as selection of appropriate species and varieties in adapting to future warming.

Climate benefit of a future hydrogen economy

Hydrogen is recognised as an important future energy vector for applications in many sectors. Hydrogen is an indirect climate gas which induces perturbations of methane, ozone, and stratospheric water vapour, three potent greenhouse gases. Using data from a state-of-the-art global numerical model, here we calculate the hydrogen climate metrics as a function of the considered time-horizon and derive a 100-year Global Warming Potential of 12.8 ± 5.2 and a 20-year Global Warming Potential of 40.1 ± 24.1. The considered scenarios for a future hydrogen transition show that a green hydrogen economy is beneficial in terms of mitigated carbon dioxide emissions for all policy-relevant time-horizons and leakage rates. In contrast, the carbon dioxide and methane emissions associated with blue hydrogen reduce the benefit of a hydrogen economy and lead to a climate penalty at high leakage rate or blue hydrogen share. The leakage rate and the hydrogen production pathways are key leverages to reach a clear climate benefit from a large-scale transition to a hydrogen economy.

Evidence of the variation in the rate of change of temperature and precipitation

One of the most pressing challenges currently is climate change, and to face it, it is desirable to have the most detailed information possible on the distribution of climate metrics and the covariates that alter their fluctuations. This study investigated the spatial variations of the temperature and precipitation variables more sensitive to the unit change in elevation above sea level, considering the relative effects of latitude and solar radiation as covariates. For this, the analysis of covariance was applied to analyze data from 32,111 sampling units, systematically distributed in mainland Mexico, hypothesizing a constant and uniform rate of change of climate variables as the values of elevation above sea level increase and a non-significant effect of the covariates on the elevation-climate relationships. The results show that the rate of change of the studied variables varies at different latitudinal and altitudinal gradients. For example, without considering any covariate, for each meter that the elevation increases, the mean annual temperature decreases on average by 0.00473 °C, the mean temperature of the driest quarter decreases by 0.00488 °C, and the mean temperature of the warmest quarter decreases by 0.00449 °C. This means that for every kilometer of elevation, these variables decrease by 4.73, 4.88, and 4.49 °C, respectively. Yet, when the data were stratified by covariates, these values, as well as the rates of change in precipitation, varied significantly. There were also signs of a stronger correlation between altitude and precipitation for the driest month and driest quarter of over 30°N than in latitudes nearer to the equator.

Climate and socioeconomic drivers of biomass burning and carbon emissions from fires in tropical dry forests: A Pantropical analysis.

Global burned area has declined by nearly one quarter between 1998 and 2015. Drylands contain a large proportion of these global fires but there are important differences within the drylands, for example, savannas and tropical dry forests (TDF). Savannas, a biome fire-prone and fire-adapted, have reduced the burned area, while the fire in the TDF is one of the most critical factors impacting biodiversity and carbon emissions. Moreover, under climate change scenarios TDF is expected to increase its current extent and raise the risk of fires. Despite regional and global scale effects, and the influence of this ecosystem on the global carbon cycle, little effort has been dedicated to studying the influence of climate (seasonality and extreme events) and socioeconomic conditions of fire regimen in TDF. Here we use the Global Fire Emissions Database and, climate and socioeconomic metrics to better understand long-term factors explaining the variation in burned area and biomass in TDF at Pantropical scale. On average, fires affected 1.4% of the total TDF' area (60,208 km2 ) and burned 24.4% (259.6Tg) of the global burned biomass annually at Pantropical scales. Climate modulators largely influence local and regional fire regimes. Inter-annual variation in fire regime is shaped by El Niño and La Niña. During the El Niño and the forthcoming year of La Niña, there is an increment in extension (35.2% and 10.3%) and carbon emissions (42.9% and 10.6%). Socioeconomic indicators such as land-management and population were modulators of the size of both, burned area and carbon emissions. Moreover, fires may reduce the capability to reach the target of "half protected species" in the globe, that is, high-severity fires are recorded in ecoregions classified as nature could reach half protected. These observations may contribute to improving fire-management.

Mapping Soil Organic Carbon Content in Patagonian Forests Based on Climate, Topography and Vegetation Metrics from Satellite Imagery

Soil organic carbon (SOC) content supports several ecosystem services. Quantifying SOC requires: (i) accurate C estimates of forest components, and (ii) soil estimates. However, SOC is difficult to measure, so predictive models are needed. Our objective was to model SOC stocks within 30 cm depth in Patagonian forests based on climatic, topographic and vegetation productivity measures from satellite images, including Dynamic Habitat Indices and Land Surface Temperature derived from Landsat-8. We used data from 1320 stands of different forest types in Patagonia, and random forest regression to map SOC. The model captured SOC variability well (R² = 0.60, RMSE = 22.1%), considering the huge latitudinal extension (36.4° to 55.1° SL) and the great diversity of forest types. Mean SOC was 134.4 ton C ha−1 ± 25.2, totaling 404.2 million ton C across Patagonia. Overall, SOC values were highest in valleys of the Andes mountains and in southern Tierra del Fuego, ranging from 53.5 to 277.8 ton C ha−1 for the whole Patagonia region. Soil organic carbon is a metric relevant to many applications, connecting major issues such as forest management, conservation, and livestock production, and having spatially explicit estimates of SOC enables managers to fulfil the international agreements that Argentina has joined.