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Freshwater ecosystems host disproportionately high biodiversity and provide unique ecosystem services, yet they are being degraded at an alarming rate. Fires, which are becoming increasingly frequent and intense due to global change, can affect these ecosystems in many ways, but this relationship is not fully understood. We conducted a systematic review to characterize the literature on the effects of fires on stream ecosystems and found that (1) abiotic indicators were more commonly investigated than biotic ones, (2) most previous research was conducted in North America and in the temperate evergreen forest biome, (3) following a control-impact (CI) or before-after (BA) design, (4) predominantly assessing wildfires as opposed to prescribed fires, (5) in small headwater streams, and (6) with a focus on structural and not functional biological indicators. After quantitatively analyzing previous research, we detected great variability in responses, with increases, decreases, and no changes being reported for most indicators (e.g., macroinvertebrate richness, fish density, algal biomass, and leaf decomposition). We shed light on these seemingly contradicting results by showing that the presence of extreme hydrological post-fire events, the time lag between fire and sampling, and whether the riparian forest burned or not influenced the outcome of previous research. Results suggest that although wildfires and the following hydrological events can have dramatic impacts in the short term, most biological endpoints recover within 5-10 years, and that detrimental effects are minimal in the case of prescribed fires. We also detected that no effects were more often reported by BACI studies than by CI or BA studies, raising the question of whether this research field may be biased by the inherent limitations of CI and BA designs. Finally, we make recommendations to help advance this field of research and guide future integrated fire management that includes the protection of freshwater ecosystems.
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Ecossistema , Incêndios , Rios , Biodiversidade , Incêndios Florestais , Conservação dos Recursos Naturais , AnimaisRESUMO
The scarcity of long-term observational data has limited the use of statistical or machine-learning techniques for predicting intraannual ecological variation. However, time-stamped citizen-science observation records, supported by media data such as photographs, are increasingly available. In the present article, we present a novel framework based on the concept of relative phenological niche, using machine-learning algorithms to model observation records as a temporal sample of environmental conditions in which the represented ecological phenomenon occurs. Our approach accurately predicts the temporal dynamics of ecological events across large geographical scales and is robust to temporal bias in recording effort. These results highlight the vast potential of citizen-science observation data to predict ecological phenomena across space, including in near real time. The framework is also easily applicable for ecologists and practitioners already using machine-learning and statistics-based predictive approaches.
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The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4-43% higher growth rates, 14-17% higher survival rates and 4-7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks.
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Biodiversidade , Florestas , Folhas de Planta , Árvores , Folhas de Planta/crescimento & desenvolvimento , Árvores/crescimento & desenvolvimento , Ecossistema , Solo/química , ClimaRESUMO
Accurate measuring, mapping, and monitoring of mangrove forests support the sustainable management of mangrove blue carbon in the Asia-Pacific. Remote sensing coupled with modeling can efficiently and accurately estimate mangrove blue carbon stocks at larger spatiotemporal extents. This study aimed to identify trends in remote sensing/modeling employed in estimating mangrove blue carbon, attributes/variations in mangrove carbon sequestration estimated using remote sensing, and to compile research gaps and opportunities, followed by providing recommendations for future research. Using a systematic literature review approach, we reviewed 105 remote sensing-based peer-reviewed articles (1990 - June 2023). Despite their high mangrove extent, there was a paucity of studies from Myanmar, Bangladesh, and Papua New Guinea. The most frequently used sensor was Sentinel-2 MSI, accounting for 14.5 % of overall usage, followed by Landsat 8 OLI (11.5 %), ALOS-2 PALSAR-2 (7.3 %), ALOS PALSAR (7.2 %), Landsat 7 ETM+ (6.1 %), Sentinel-1 (6.7 %), Landsat 5 TM (5.5 %), SRTM DEM (5.5 %), and UAV-LiDAR (4.8 %). Although parametric methods like linear regression remain the most widely used, machine learning regression models such as Random Forest (RF) and eXtreme Gradient Boost (XGB) have become popular in recent years and have shown good accuracy. Among a variety of attributes estimated, below-ground mangrove blue carbon and the valuation of carbon stock were less studied. The variation in carbon sequestration potential as a result of location, species, and forest type was widely studied. To improve the accuracy of blue carbon measurements, standardized/coordinated and innovative methodologies accompanied by credible information and actionable data should be carried out. Technical monitoring (every 2-5 years) enhanced by remote sensing can provide accurate and precise data for sustainable mangrove management while opening ventures for voluntary carbon markets to benefit the environment and local livelihood in developing countries in the Asia-Pacific region.
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Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM.
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Carbono , Ecossistema , Humanos , Carbono/metabolismo , América Latina , Conservação dos Recursos Naturais/métodos , Florestas , Sequestro de CarbonoRESUMO
Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.
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Sequestro de Carbono , Carbono , Conservação dos Recursos Naturais , Florestas , Biodiversidade , Carbono/análise , Carbono/metabolismo , Conservação dos Recursos Naturais/estatística & dados numéricos , Conservação dos Recursos Naturais/tendências , Atividades Humanas , Recuperação e Remediação Ambiental/tendências , Desenvolvimento Sustentável/tendências , Aquecimento Global/prevenção & controleRESUMO
Urban forests provide direct and indirect benefits to human well-being that are increasingly captured in residential property values. Remote Sensing (RS) can be used to measure a wide range of forest and vegetation parameters that allows for a more detailed and better understanding of their specific influences on housing prices. Herein, through a systematic literature review approach, we reviewed 89 papers (from 2010 to 2022) from 21 different countries that used RS data to quantify vegetation indices, forest and tree parameters of urban forests and estimated their influence on residential property values. The main aim of this study was to understand and provide insights into how urban forests influence residential property values based on RS studies. Although more studies were conducted in developed (n = 55, 61.7%) than developing countries (n = 34, 38.3%), the results indicated for the most part that increasing tree canopy cover on property and neighborhood level, forest size, type, greenness, and proximity to urban forests increased housing prices. RS studies benefited from spatially explicit repetitive data that offer superior efficiency to quantify vegetation, forest, and tree parameters of urban forests over large areas and longer periods compared to studies that used field inventory data. Through this work, we identify and underscore that urban forest benefits outweigh management costs and have a mostly positive influence on housing prices. Thus, we encourage further discussions about prioritizing reforestation and conservation of urban forests during the urban planning of cities and suburbs, which could support UN Sustainable Development Goals (SDGs) and urban policy reforms.
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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.
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Ecossistema , Árvores , Humanos , Árvores/metabolismo , Florestas , Folhas de Planta/metabolismo , Hábitos , Carbono/metabolismoRESUMO
Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.
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Biodiversidade , Meio Ambiente , Espécies Introduzidas , Árvores , Bases de Dados Factuais , Atividades Humanas , Espécies Introduzidas/estatística & dados numéricos , Espécies Introduzidas/tendências , Filogenia , Chuva , Temperatura , Árvores/classificação , Árvores/fisiologiaRESUMO
Multiwalled carbon nanotubes and Vulcan carbon were functionalized with a 30 %v/v hydrogen peroxide solution and employed as supports for Pt and PtSn catalysts prepared by the polyol method. PtSn catalysts with a Pt loading of 20â wt.% and a Pt : Sn atomic ratio equal to 3 : 1 were evaluated in the ethanol electrooxidation reaction. The effects of the oxidizing treatment on the surface area and the surface chemical nature were analyzed through N2 adsorption, isoelectric point, and temperature-programmed desorption measurements. Results showed that the H2 O2 treatment affects the surface area of the carbons to a great extent. Characterization results indicated that the performance of the electrocatalysts strongly depends both on the presence of Sn and on the support functionalization. PtSn/CNT-H2 O2 electrocatalyst displays a high electrochemical surface area and enhanced catalytic activity for ethanol oxidation in comparison to other catalysts in the present study.
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Climate teleconnections (CT) remotely influence weather conditions in many regions on Earth, entailing changes in primary drivers of fire activity such as vegetation biomass accumulation and moisture. We reveal significant relationships between the main global CTs and burned area that vary across and within continents and biomes according to both synchronous and lagged signals, and marked regional patterns. Overall, CTs modulate 52.9% of global burned area, the Tropical North Atlantic mode being the most relevant CT. Here, we summarized the CT-fire relationships into a set of six global CT domains that are discussed by continent, considering the underlying mechanisms relating weather patterns and vegetation types with burned area across the different world's biomes. Our findings highlight the regional CT-fire relationships worldwide, aiming to further support fire management and policy-making.
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Clima , Incêndios , Ecossistema , Tempo (Meteorologia) , Biomassa , Mudança ClimáticaRESUMO
Understorey vegetation plays a key role in Mediterranean forest ecosystem functioning. However, we still lack a thorough understanding of the patterns and drivers of understorey composition and diversity. As a result, understoreys are often ignored during assessments of forest functioning under climate change. Here we studied the effect of silvicultural management, topography, soil fungal community composition and soil physical and chemical properties on understorey community composition and diversity. The plant cover and number of individuals of understorey perennial plants, shrubs and non-dominant trees was recorded on 24 plots (paired: control-thinned) in a Mediterranean pine-dominated mountainous area in Northeast Spain. The study area represented a broad thinning intensity gradient (from 0 to 70 % in removed stand basal area) along a 400-m altitudinal range (from 609 m to 1013 m). Our results showed that thinning intensity and topography explained the greatest proportion of the total variance in the understorey species composition, i.e., 18 % and 16 %, respectively. Interestingly, the effects of the silvicultural treatments were significant only when considering the altitudinal effect, so that, the main impacts of thinning on the understorey community composition occurred at low altitudes (between 609 m and 870 m). Moreover, we found a significant decrease in both richness and abundance of understorey species in both the control and thinned plots with increasing altitude, with thinned plots being significantly richer in species compared to the control plots. The difference in the understorey community sensitivity to forest thinning along the altitudinal gradient suggests changes in factors that limit plant growth. Low elevation plots were restrained by light availability while high altitudes plots limited by winter freezing temperature.
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Micobioma , Pinus , Humanos , Altitude , Ecossistema , Solo/química , Florestas , Árvores , Plantas , BiodiversidadeRESUMO
High-resolution forest mapping technology is a powerful data source to assess the production capacity of forests regarding wood and non-wood ecosystem services. The study shows how to evaluate the potential benefits from forest management treatments devoted to increase mushroom supply. The study was developed in Central Spain, over a forest with important cultural and economic values attached to mushrooms. Airborne laser scanning (ALS), mushroom production models and mathematical programming as spatial optimization method are used to sequence, spatially and temporally, silviculture-oriented actions to enlarge mushroom provisioning. We present a tactical forest planning solution to incentivize mushroom yield driven by clustered silvicultural treatments applied to fine-grained segments derived from ALS data, and along a 5-year plan while embedding temporal and spatial dependencies. Mushroom yield can increase up to 18 % from current conditions if all area is treated. Our model integrates constraints to optimize the selection of segments yielding the highest benefits in terms of mushroom yield and timber removals during the treatments. The temporal sequencing was successful, so the annual interventions are scheduled aligned in space and in time to ease the actionability and realism of model outputs. The assessment of production potential is an informative, spatially and temporally explicit exercise to inform decision-makers on investment opportunities to enhance the supply of non-wood ecosystem services, tested with mushroom in this study but extendable to more non-wood ecosystem services.
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Agaricales , Agricultura Florestal , Florestas , Análise Espacial , Agaricales/crescimento & desenvolvimento , Agricultura Florestal/métodos , Árvores/microbiologiaRESUMO
The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.
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Biodiversidade , Florestas , Solo , ÁrvoresRESUMO
One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are â¼73,000 tree species globally, among which â¼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.
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Conservação dos Recursos Naturais , Florestas , Árvores/classificação , Planeta Terra , Árvores/crescimento & desenvolvimentoRESUMO
Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year-1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year-1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.
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Projections of future climate change impacts suggest an increase of wildfire activity in Mediterranean ecosystems, such as southern California. This region is a wildfire hotspot and fire managers are under increasingly high pressures to minimize socio-economic impacts. In this context, predictions of high-risk fire seasons are essential to achieve adequate preventive planning. Regional-scale weather patterns and climatic teleconnections play a key role in modulating fire-conducive conditions across the globe, yet an analysis of the coupled effects of these systems onto the spread of large wildfires is lacking for the region. We analyzed seven decades (1953-2018) of documentary wildfire records from southern California to assess the linkages between weather patterns and large-scale climate modes using various statistical techniques, including Redundancy Analysis, Superposed Epoch Analysis and Wavelet Coherence. We found that high area burned is significantly associated with the occurrence of adverse weather patterns, such as severe droughts and Santa Ana winds. Further, we document how these fire-promoting events are mediated by climate teleconnections, particularly by the coupled effects of El Niño Southern Oscillation and Atlantic Multidecadal Oscillation.
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In forests, ectomycorrhizal mycelium is pivotal for driving soil carbon and nutrient cycles, but how ectomycorrhizal mycelial dynamics vary in ecosystems with drought periods is unknown. We quantified the production and turnover of mycorrhizal mycelium in Mediterranean Pinus pinaster, Pinus sylvestris and Quercus ilex forests and related the estimates to standardised precipitation index (SPI), to study how mycelial dynamics relates to tree species and drought-moisture conditions. Production and turnover of mycelium was estimated between July and February, by quantifying the fungal biomass (ergosterol) in ingrowth mesh bags and using statistical modelling. SPI for time scales of 1-3 months was calculated from precipitation records and precipitation data over the study period. Forests dominated by Pinus trees displayed higher biomass but were seasonally more variable, as opposed to Q. ilex forests where the mycelial biomass remained lower and stable over the season. Production and turnover, respectively, varied between 1.4-5.9 kg ha-1 d-1 and 7.2-9.9 times yr-1 over the different forest types and were positively correlated with 2-month and 3-month SPI over the study period. Our results demonstrated that mycorrhizal mycelial biomass varied with season and tree species and we speculate that production and turnover are related to physiology and plant host performance during drought.