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Characterization of forest carbon stocks at the landscape scale in the Argentine Dry Chaco
... Accuracy assessment allows researchers to determine the quality of the remotely sensed data. It is highly accurate when used in tandem with data derived from aerial photos, close to the time of satellite overpass, or with ground reference data (Powell et al., 2018;Qun and Huizhi, 2013). Remote sensing is not expected to provide better accuracy of biomass estimates at the stand or plot level. ...
... Satellite imagery is employed to generate annual estimates of the amount of C stored in tree forests. However, in interpreting the relationships between AGB increase and other C stock attributes, one must consider that this imagery also captures shrub and herb productivity (Powell et al., 2018). As C accounts for half the dry-weight biomass of trees, spectral indices can also be applied to detecting C stor changes in trees (Davies et al., 2011;Powell et al., 2018). ...
... However, in interpreting the relationships between AGB increase and other C stock attributes, one must consider that this imagery also captures shrub and herb productivity (Powell et al., 2018). As C accounts for half the dry-weight biomass of trees, spectral indices can also be applied to detecting C stor changes in trees (Davies et al., 2011;Powell et al., 2018). As location-based inventory delivers explicit spatial information, it can be used for environmental education, improved mitigation policymaking, and in-depth examination of the relationship between city landscapes and GHG emissions distribution, which is beneficial to low C practice, city research (Li et al., 2017), and the emission discounting influences economic decisions (Fearnside et al., 2000;Watson et al., 2000). ...
Carbon capture, storage, and sequestration are crucial for mitigating climate change's adverse effects. To limit global temperature rise within the 2 °C target, it is essential to implement both artificial and natural carbon-capturing techniques and utilize renewable resources. Natural carbon sinks serve as vital resources for CO2 reduction, but quantifying their carbon sequestration is complex due to potential CO2 release from the upper ocean. Accurate assessment requires detailed modeling of interacting natural processes. This review critically examines various natural carbon pools, methodologies, and modeling techniques for carbon accounting, particularly in urban landscapes. The strengths and limitations of each approach are analyzed, leading to specific recommendations. Socio-economic benefits associated with natural carbon sinks are also presented. Ground and field measurements are found to be the most accurate methods, while accounting methods tend to be study-specific. Additionally, satellite earth observation, drone, and airborne measurements have significant potential for enhancing ecosystem analysis, assessment, and mapping. By comprehensively assessing these factors, this review contributes to the development of effective strategies for carbon accounting and management in diverse environments.
... Ante una gran transformación de cobertura natural en el Chaco seco argentino (Vallejos et al. 2015), el desarrollo en los cálculos de carbono y biomasa, ha permitido disponer actualmente de estimaciones a diferentes niveles ecológicos en dicha región (Bonino 2006, Manrique et al. 2009, Gasparri et al. 2010, Powell et al. 2018, Conti et al. 2019). Ejemplos de esto son las ecuaciones alométricas para determinar el contenido de biomasa a nivel individuo para algunas especies forestales nativas ( Gaillard de Benítez et al. 2002, 2014, arbustos (Conti et al. 2019), o las ecuaciones generales para tipos funcionales de leñosas en el Chaco árido argentino (Iglesias et al. 2012). ...
... desarrollaron modelos alométricos para estimación de biomasa aérea leñosa en 8 especies arbustivas no estudiadas anteriormente, logrando una gran variabilidad explicada en la estimación de sus biomasas, mediante la inclusión de rasgos como el número de tallos (i.e., simple o múltiple), el diámetro y forma de la copa. Powell et al. (2018), han clasificado tipologías de bosques en el Chaco seco en base a la altura total de árboles, densidad de la madera y modelos de aptitud del hábitat para 23 especies leñosas, logrando identificar fuertes influencias de estos atributos sobre la acumulación de carbono en la región. ...
... La precipitación media varía de 700 a 1000 mm anuales. Un gradiente de precipitaciones disminuye de Este a Oeste dentro de la región (Ricard et al. 2015, Powell et al. 2018. La vegetación nativa esta cubierta por bosques xerófitos, bosques abiertos y pastizales que en conjunto forman un mosaico a escala de paisaje (Cabrera 1976 (Clark et al. 2001, Houghton et al. 2009). ...
Ciclo de carbono en biomasa de bosque con relación al régimen de disturbios en el Chaco seco argentino TESIS PRESENTADA COMO REQUISITO PARA OBTENER EL GRADO DE DOCTOR EN CIENCIAS Y TECNOLOGÍAS FORESTALES por Dante Ernesto Loto Licenciado en Ciencias Biológicas.
... Scientific plant names were take from the "The Plant List Project" (http://www.theplantlist.org/). Species frequency and forest strata per site were evaluated considering height categories: a) low forest stratum (< 2 m in height); b) intermediate forest stratum (2 to 6 m in height), and c) canopy forest stratum (> 6 m in height) (López de Casenave et al., 1995;Powell et al., 2018). For each sampled individual, five PFTs were registered: (a) Number of stems: unique = 1, multiple = 2 (we regarded multiple stems as the plant having 2 or more main stems which emerged from the same spot on the ground); (b) Growth forms: sub-shrub = 1 (plants without without a main stem, height of < 2 m), shrub = 2 (plants without a main stem, height of < 5 m), tree = 3 (plants with a main stem, height of > 5 m); (c) Intensity of sprouts: non-sprout = 0, low sprout = 1 (< 20 per plant), high sprout = 2 (> 20 per plant); (d) Leaf texture: coriaceous leaf = 1, intermediate leaf = 2 (leaf texture between coriaceous and herbaceous), herbaceous leaf = 3 and (e) Spinescence: non-spine = 0, spine = 1. ...
... Thus, the main differences between the sampling sites were observed at the intermediate and lower forest strata, where 86% of the identified species were present. The similarity of species composition in the lower and intermediate forest strata reflects the slow growth rates in Chaco woody species (Powell et al. 2018) and highlights the need for more sustainable forest management of these strata. The dominance of Fabaceae and Capparaceae species is a frequent situation in dry tropical forests of semi-arid South American (Prado, 1993;Gentry et al., 1995;Tálamo et al., 2015). ...
Over the last two decades, the Chaco region has experienced accelerated land-conversion processes that have developed into a mosaic of disturbances attributable to fires, forest logging, and livestock grazing in its native forests. In this paper, we describe the species composition and structure of two forests in semi-arid Argentine Chaco. Both forests have kept two different land uses in the last three decades: (a) a protected area (NR-Pizarro), and (b) an experimental area (ER-Inta) with land management practices. We analyse changes in species composition and plant functional traits as a response to disturbance history. We differentiate the disturbance history of the last 30 years in both sampling sites. To measure the plant communities, we used transects. We determined species, plant stem diameter, and height of 1315 woody plants >1 cm in diameter. Selected plant functional traits included: growth form, number of stems, spinescence, intensity of sprouts, and leaf texture. We registered 36 native woody species belonging to the Fabaceae and Capparaceae families. We found differences in the species composition of both sampling areas. Plant diameter and height averages decreased when comparing the protected area to the experimental area. Shrubby growth form, coriaceous leaves, absence of spines, and low sprouts were more frequent in the protected area. By contrast, in the experimental area, subshrubs, spines, and high sprouts prevailed. We reaffirmed the gradient of disturbances in both areas. A broader separation in plant functional traits occurred in the two sampling areas due to disturbance histories.
... Plant diversity components focused on woody species, as this group plays a key role in structuring the landscape, accounting for most of the vegetation cover and biomass in the community, and in determining forest carbon stock Powell et al., 2018). We measured taxonomic diversity by counting woody plant species (i.e. ...
Forest ecosystems play a key role in providing multiple ecosystem services, such as carbon fixation and storage, but face pressures from human development that jeopardize their integrity and functioning. Accurately understanding the relationships between land use-intensity, biodiversity, and carbon storage is important for developing viable strategies to promote carbon sequestration. Here, we analyzed the effect of land-use intensity on the relationship between woody plant functional diversity and carbon storage in Prosopis woodlands of the central Monte desert of Argentina. We worked in sixteen 900 m2 square plots along disturbance gradients, eight located in highly disturbed woodlands close to livestock settlements and eight in slightly disturbed woodlands ca. 2 km away from settlements. We measured woody plant taxonomic and functional diversity and dominance metrics, and estimated carbon stocks in biomass, necromass and soil organic compartments. Our study shows that increasing land-use intensity erodes taxonomic and functional diversities and, ultimately, carbon storage. We found that lower carbon stocks around livestock settlements were driven by shrubs, trees, roots, litter, and dead plants, but were unaffected by the herb, woody debris, and soil compartments. Furthermore, positive relationships among woody species richness and functional trait diversity seem more important than the existence of few highly dominant species in determining carbon storage, providing stronger evidence for niche complementary than for mass ratio effects. We hope our study contributes to the understanding how livestock management practices influence carbon storage in Prosopis woodlands.
... The use of remote sensing, primarily orbital, as an aid to planning activities related to natural resources and the environment has facilitated, over the years, studies in different ecosystems [5,[14][15][16] and allied to these techniques, spatial simulation models have been receiving greater attention from researchers, becoming a promising field of research [17,18]. ...
The objective of this work was to carry out a multitemporal analysis of changes in land use and land cover in the municipality of Floresta, Pernambuco State in Brazil. Landsat images were used in the years 1985, 1989, 1993, 1997, 2001, 2005, 2009, 2014, and 2019, and the classes were broken down into areas: water, exposed soil, agriculture, and forestry, and using the Bhattacharya classifier, the classification was carried out for generating land use maps. The data was validated by the Kappa index and points collected in the field, and the projection of the dynamics of use for 2024 was constructed. The thematic maps of land use and coverage from 1985 to 2019 show more significant changes in the forest and exposed soil classes. The increase in the forest class and the consequent reduction in exposed soil are consequences of the interaction between climate and human activities and the quality of the spatial resolution of the satellite images used between the years analyzed.
... For a complete description of parameters used, see Appendix S1: Table S1. This database has been widely used in recent ecological studies (e.g., Boyer et al., 2020;Brown et al., 2018;Ivajnšič & Devetak, 2020;Marcondes et al., 2020;Pironon et al., 2019;Powell et al., 2018) and is particularly robust in providing more realistic precipitation data for mountainous areas in comparison with other databases (Karger et al., 2017). ...
The contribution of seasonality in species communities to elevational diversity of tropical insects remains poorly understood. We here assessed seasonal patterns and drivers of bee diversity in the Eastern Afromontane Biodiversity Hotspot, Kenya, to understand the contribution of seasonality to elevational biodiversity patterns. Bee species and plant species visited by bees were recorded on 50 study plots in regrowth vegetation across four major seasons along two elevation gradients from 525 to 2530 m above sea level. Bees were sampled by transect walks using sweep nets and aspirators. We examined how local species richness (α‐diversity) and seasonal changes in local species communities (β‐diversity) contribute to species richness across seasons (γ‐diversity) along elevation gradients. Using a multimodel inference framework, we identified the contribution of climate and floral seasonality to elevational patterns in bee diversity. We found that both α‐ and γ‐diversity decreased with elevation. Seasonal β‐diversity decreased with elevation and the high turnover of species across seasons contributed to a considerably higher γ‐ than α‐diversity on study plots. A combination of seasonality in climate and the seasonal turnover of floral resources best explained the seasonality in bee species communities (seasonal β‐diversity). We, therefore, conclude that, despite the more stable, and favorable climatic conditions in the tropics (in comparison to temperate regions), climatic seasonality and its influence on bees' floral resources largely determined seasonal patterns of bee species diversity along elevation gradients on tropical mountains.
... The relationships between structural attributes and abiotic variables suggest that precipitation and, to a lesser extent, temperature, are important drivers of canopy height, canopy cover, vegetation volume and vertical complexity. The positive relation of canopy height with MAP is in accordance with other studies in the Chaco region that used a global map of forest canopy height (Powell et al., 2018) and similar dry forests (Gillespie et al., 2006), although, these studies showed a negative relation with MAT, contrary to our results. In the case of canopy cover, the increment with MAP gradient is in line with previous findings from field data (Iglesias et al., 2012). ...
Logging, grazing, wood extraction, and anthropogenic fires are pervasive throughout the subtropical dry vegetation of South America leading to changes in woodlands structure and ultimately its degradation. The Chaco region encompasses the second-largest forest in South America and has a long history of intensive use. We sought to characterize structure and heterogeneity of its woodlands across biogeographic subunits and climatic gradients, and evaluate structure controls. We quantified canopy height, cover, vertical complexity, vegetation amount above 3 m and total vegetation amount over 58 woodlands along the Chaco region by means of Terrestrial Laser Scanner. We assessed the relationship between three groups near the maximum, average and minimum values of each structural variables and precipitation, temperature and temperature of the coldest month using quantile regressions. We found a large variability in structural attributes within each biogeographical subunit, evidencing that woodland areas with similar structure across broad gradients of climate. This suggests a considerable impact of current and past land use in shaping woodland structure across the Chaco. Overall, structural variables were positively associated with precipitation and temperature, albeit more strongly to the former, except for canopy height, which showed a strong association with mean temperature of the coldest month. We hypothesize that land-use impact on woodland structure decreases with increasing precipitation, as the lack of water may limit the recovery of vegetation structure. Our results contribute to a better understanding of variation in key structural variables of Chaco woodlands in relation to climate and land use.
... Los modelos de distribución de especies en función de variables bioclimáticas y edáficas han demostrado patrones significativos en la delimitación del nicho ecológico para muchas especies dominantes de árboles en la región del Chaco Seco argentino (Morello and Adamoli 1974;Torres et al. 2014;Powell et al. 2018). Gonopterodendron sarmientoi tiene un óptimo adaptativo en condiciones ambientales áridas y semiáridas de bosques secos en el sur de Sudamérica (Camps et al. 2018). ...
Forests structure of palo santo (Gonopterodendron sarmientoi): Regional assessment for forest
management and conservation in Argentine. Gonopterodendron sarmientoi is a threatened native tree of the Dry
Chaco region in South America, adapted to semiarid conditions. However, the relationships among climatic
and edaphic conditions and its forest structure have not been defined yet. Up to date, in Argentina, the study of
palo santo forest management and conservation is scarce and still depends on basic information. The objectives
of this study were 1) to classify forest groups based on forest stand a�ributes and species composition, 2) to
analyze relationships between dasometric parameters of palo santo with climatic and edaphic variables at
the regional level and forest types, and 3) to compare total aboveground biomass between forest types as a
tool for managing and conserving this species. We compiled forest inventories carried out during the years
2004-2019, containing dasometric data of palo santo for the northern part of the Argentine Dry Chaco region.
In the study area, we extracted climatic and edaphic conditions from global data base and national maps. We
obtained three forest groups: palosantal, forests with low presence of palo santo and forests with high presence
of palo santo. Temperature, precipitation, evapotranspiration and soil textures had significant effects on the
forest structure of palo santo at the regional level and on forest types. The total density of individuals of G.
sarmientoi has a different effect on the total biomass depending on the type of forest, which allows for different
management and conservation practices. Consolidating a national forest plan for palo santo could address
more viable proposals to manage and conserve the species in the region.
... Salah satu strategi mitigasi perubahan iklim yang paling umum diusulkan adalah penyerapan karbon oleh vegetasi. Penyerapan karbon tersebut juga bergantung pada laju serapan karbon melalui fotosintesis dan laju pelepasan melalu repirasi, serta kestabilan penyimpanan karbon (Powell et al., 2018). Berkaitan dengan emisi karbon dioksida, hutan memiliki dua fungsi utama, pertama hutan berperan sebagai penyerap utama kabon dioksida di atmosfer dan yang kedua penggunaan energi dari sisa biomassa hutan akan mengurangi emisi tambahan CO2 dari pembakaran bahan bakar fosil (Gil et al., 2011). ...
Hutan merupakan salah satu sumber jasa lanskap yang penting bagi keberlanjutan ekosistem. Kementerian Kehutanan telah memberikan akses kepada masyarakat desa untuk mengelola kawasan hutan secara legal, melalui skema hutan desa dengan hak akses pengelolaan selama 35 tahun. Pemetaan partisipatif adalah jenis partisipasi publik yang mencakup pembuatan dan/atau penggunaan informasi spasial untuk berbagai tujuan. Data spasial memungkinkan identifikasi hubungan antara jasa lanskap dan karakteristik lanskap serta unit administratifnya. Penelitian ini bertujuan untuk melakukan identifikasi potensi karakteristik dan potensi jasa lanskap kawasan Hutan Desa Pattaneteang. Metode yang digunakan dalam penelitian ini adalah metode analisis spasial yang dilakukan pada peta penggunaan lahan berdasarkan citra drone di Desa Pattaneteang dan metode kualitatif berupa wawancara terstruktur, kuesioner, dan diskusi kelompok terarah. Hasil penelitian menunjukkan bahwa kualitas jasa lanskap keanekaragaman hayati dan karbon tersimpan di Desa Pattaeneteang berada dalam tingkatan “sangat baik”, memiliki peran ekonomi bernilai tinggi dengan total skor 9 pada Hutan Desa Pemanfaatan. Total nilai skoring peran budaya Hutan Desa Pattanateang yaitu 4 untuk kawasan Hutan Desa Sengketa dan Hutan Desa Pemanfataan, yang artinya bernilai budaya rendah dan nilai 5 untuk kawasan Hutan Desa Inti artinya bernilai budaya sedang.
... That the bulk of the forest disturbances in the remaining forest occurred in relatively wet areas (i.e. between 500 mm and 1200 mm) can likely be explained by the higher presence of people (both farmers and forest smallholders) in these, relatively-speaking, more favourable areas compared to the driest parts of the Chaco. Also, this pattern might be explained by the lower availability or quality of forest resources in extremely dry areas, where some valuable species disappear and vegetation grows slower and less high (Powell et al., 2018;Prado, 1993). ...
Forest loss in the tropics affects large areas, but whereas full forest conversions are routinely assessed, forest degradation patters remain often unclear. This is particularly so for the world’s tropical dry forests, where remote sensing of forest disturbances is challenging due to high canopy complexity, strong phenology and climate variability, and diverse degradation drivers. Here, we used the full depth of the Landsat archive and devised an approach to detect disturbances related to forest degradation across the entire Argentine Dry Chaco (about 489,000 km²) over a 30-year timespan. We used annual time series of different spectral indices, summarized for three seasonal windows, and applied LandTrendr to temporally segment each time series. The resulting pixel-level forest disturbance metrics then served as input for a Random Forests classification which we used to produce an area-wide disturbance map, and associated yearly area estimates of disturbed forest. Finally, we evaluated disturbance trends in relation to climate and soil conditions. Our best model produced a disturbance map with an overall accuracy of 79%, with a balanced error distribution. A total of 8% (24,877 ± 860 km²) of the remaining forest in the Argentine Dry Chaco have been affected by forest disturbances between 1990 and 2017. Diverse spatial patterns of forest disturbances indicate a variety of agents driving disturbances. We also found the disturbed area to vary strongly between years, with larger areas being disturbed during drought years. Our approach shows that it is possible to robustly map forest disturbances in tropical dry forests using Landsat time series, and demonstrates the value of ensemble approaches to capture spectrally-complex and heterogeneous land-change processes. For the Chaco, a global deforestation hotspot, our analyses provide the first Landsat-based assessment of forest disturbance in remaining forests, highlighting the need to better consider such disturbances in assessments of carbon budgets and biodiversity change.
... For the analysis of the vertical structure of the forest, we set the lower height limits for the three forest strata, the canopy, sub-canopy, and shrubby stratum, at respectively 6 m, 4 m, and 0.5 m. The delimitation of the canopy layer (above 6 m) is the same used by Powell et al. [36] and somewhat different from work by de Casenave et al. [37] and Prado [38], and is here set at the lower height limit of the crown of the canopy. To select this threshold, we evaluated different canopy height values and defined the height for which all the crowns of the larger trees were included in the upper canopy height. ...
Anthropogenic activity leading to forest structural and functional changes needs specific ecological indicators and monitoring techniques. Since decades, forest structure, composition, biomass, and functioning have been studied with ground-based forest inventories. Nowadays, satellites survey the earth, producing imagery at different spatial and temporal resolutions. However, measuring the ecological state of large extensions of forest is still challenging. To reconstruct the three-dimensional forest structure, the structure from motion (SfM) algorithm was applied to imagery taken by an unmanned aerial vehicle (UAV). Structural indicators from UAV-SfM products are then compared to forest inventory indicators of 64 circular plots of 1000 m2 in a subtropical dry forest. Our data indicate that the UAV-SfM indicators provide a valuable alternative for ground-based forest inventory’ indicators of the upper canopy structure. Based on the correlation between ground-based measures and UAV-SfM derived indicators, we can state that the UAV-SfM technique provides reliable estimates of the mean and maximum height of the upper canopy. The performance of UAV-SfM techniques to characterize the undergrowth forest structure is low, as UAV-SfM indicators derived from the point cloud in the lower forest strata are not suited to provide correct estimates of the vegetation density in the lower strata. Besides structural information, UAV-SfM derived indicators, such as canopy cover, can provide relevant ecological information as the indicators are related to structural, functional, and/or compositional aspects, such as biomass or compositional dominance. Although UAV-SfM techniques cannot replace the wealth of data collected during ground-based forest inventories, its strength lies in the three-dimensional (3D) monitoring of the tree canopy at cm-scale resolution, and the versatility of the technique to provide multi-temporal datasets of the horizontal and vertical forest structure.
... Third, other intensity metrics would be beneficial to include in our classification of cattle systems (e.g. the type of cropland, forage storage). Finally, more detailed vegetation structure indicators, such as woodland biomass (Gasparri & Baldi, 2013), tree or shrub cover , or woodland functionality (Powell et al., 2018) could also further improve our maps. ...
Impacts of cattle production vary among different production systems, but data on their distribution is scarce for most world regions. In this work, we combine datasets on cattle vaccination locations and land cover in a regression framework to define and map major cattle production systems in the Argentinean Dry Chaco. We also explore how cattle occurrence relates to spatial determinants. Results indicate that the region harbors about 5.5 million heads. Cattle density was mainly described by the share of pasture (69.9%), cropland (28.1%) and aridity (23.8%). We identified 12-major cattle production systems: six cow-calf, three whole-cycle, and three fattening systems. Of these, four systems had high woodland cover (>85%).
The different ways in which biodiversity is distributed on Earth have always intrigued ecologists, promoting constant research to elucidate the causes and mechanisms that guide their spatial patterns. Numerous hypotheses have been proposed to explain biodiversity across the world. In South American Subtropical Dry forests, a global deforestation hotspot, this type of research remains poorly explored. We aimed to evaluate the response of forests bird communities to different biophysical and environmental factors analyzed simultaneously under three major hypotheses in ecology. Generalized linear mixed models (GLMMs) were used to analyze the seasonal richness and relative frequency in birds for 27 forest sites scattered through the Dry Chaco, Argentina, under the influence of the following predictors: (a) mean seasonal temperature, (b) forest biomass, (c) forest primary productivity using the NDVI (Normalized Difference Vegetation Index) and (d) landscape heterogeneity. Our results indicate that forest sites with high biomass and temperature values and with low landscape heterogeneity hold higher bird richness, without any influence of forest productivity. The relative frequency was higher in areas with high temperatures and high landscape heterogeneity around, although with low values of forest productivity. Overall, we highlight that the spatial pattern of bird communities in the Argentinean Dry Chaco forests is determined by areas with high biomass, high temperatures and mainly low landscape transformation in the surroundings. These associations must be considered in future decisions on land use for better territory planning and the conservation of these important areas for bird diversity.
Conservation planning relies on integrating existing knowledge, social-environmental contexts, and potential threats to identify gaps and opportunities for action. Here we present a case study on how priority areas for conservation can be determined using existing information on biodiversity occurrence and threats. Specifically, our goals are: (1) to model the ecological niche of twelve endemic snake species in the Dry Chaco Forest, (2) to quantify the impact of the deforestation rates on their distributions, (3) to propose high priority areas for conservation in order to improve the actual protected area system, and (4) to evaluate the influence of the human footprint on the optimization of selected priority areas. Our results demonstrate that Argentinian Dry Chaco represent, on average, ~74% of the distribution of endemic snake species and deforestation has reduced suitable areas of all snake species in the region. Further, the current protected areas are likely insufficient to conserve these species as only very low percentages (3.27%) of snakes' ranges occur within existing protected areas. Our models identified high priority areas in the north of the Chaco forest where continuous, well-conserved forest still exists. These high priority areas include transition zones within the foothill forest and areas that could connect patches of forest between the western and eastern Chaco forest. Our findings identify spatial priorities that minimize conflicts with human activities, a key issue for this biodiversity hotspot area. We argue that consultation with stakeholders and decision-makers are urgently needed in order to take concrete actions to protect the habitat, or we risk losing the best conservation opportunities to protect endemic snakes that inhabit the Argentinian Dry Chaco.
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth's land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979–2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better. Design Type(s) data integration objective • modeling and simulation objective Measurement Type(s) temperature of air • hydrological precipitation process Technology Type(s) data acquisition system Factor Type(s) Sample Characteristic(s) Earth • planetary atmosphere
El Chaco Seco experimenta altas tasas de deforestación y transformación productiva. Estimamos la magnitud de la apropiación humana de la productividad primaria neta (PPN) aérea de esta región por vías directas (producción ganadera, forestal y agrícola) e indirectas (fuego), su distribución regional, su relación con variables climáticas y socioeconómicas y sus contrastes entre vegetación natural, pasturas y cultivos. Para 69 departamentos se utilizaron datos censales, climáticos y satelitales (período 2002-2006) a partir de los que se estimó la PPN aérea con modelos climáticos, la apropiación de forraje por ganadería con datos de stock animal y modelos metabólicos, la apropiación de productos agrícolas y forestales con estadísticas nacionales y apropiación indirecta de biomasa por fuego a partir sensores remotos. La ganadería, desarrollada bajo vegetación natural y pasturas (90.9% del área), involucró una apropiación de 248 kgMS.ha-1.año-1, y aumentó en departamentos con mayor fracción de pasturas, ganado agrupado en rodeos más grandes y menores niveles de pobreza. La apropiación forestal, desarrollada bajo vegetación natural (88.7%), alcanzó 64 kgMS.ha-1.año-1 representados predominantemente por carbón vegetal y leña, y fue mayor en departamentos de clima más húmedo. En la fracción agrícola del territorio (6.3%), la apropiación directa trepó a 2293 kgMS.ha-1.año-1, representada principalmente por grano de soja y maíz. La apropiación indirecta por fuego promedió 746 kgMS.ha-1.año-1 para todo el territorio. Este flujo estuvo positivamente asociado a la tasa de desmonte, ascendiendo de -450 a >2000 kgMS.ha-1.año-1 al pasar de departamentos con mínimo a máximo desmonte. En la actualidad, la baja apropiación de la PPN de la vegetación natural del Chaco Seco constituye un incentivo para su reemplazo por pasturas y cultivos anuales. Una actividad ganadera y/o forestal más eficiente en los bosques representa un desafío tecnológico y político prioritario capaz de reconciliar la producción y la conservación en esta región.
1. Carbon storage in vegetation and soil underpins climate regulation through carbon sequestration. Because plant species differ in their ability to capture, store and release carbon, the collective functional characteristics of plant communities (functional diversity) should be a major driver of carbon accumulation in terrestrial ecosystems. 2. Three major components of plant functional diversity could be put forward as drivers of carbon storage in ecosystems: the most abundant functional trait values, the variety of functional trait values and the abundance of particular species that could have additional effects not incorporated in the first two components. 3. We tested for associations between these components and carbon storage across 16 sites in the Chaco forest of Argentina under the same climate and on highly similar parental material. The sites differed in their plant functional diversity caused by different long-term land-use regimes. 4. We measured six plant functional traits in 27 species and weighted them by the species abundance at each site to calculate the community-weighted mean (CWM) and the functional divergence (FDvar) of each single trait and of multiple traits (FDiv). We also measured plant and soil carbon storage. Using a stepwise multiple regression analysis, we assessed which of the functional diversity components best explained carbon storage. 5. Both CWM and FDvar of plant height and wood-specific gravity, but no leaf traits, were retained as predictors of carbon storage in multiple models. Relationships of FDvar of stem traits and FDiv with carbon storage were all negative. The abundance of five species improved the predictive power of some of the carbon storage models. 6. Synthesis. All three major components of plant functional diversity contributed to explain carbon storage. What matters the most to carbon storage in these ecosystems is the relative abundance of plants with tall, and to a lesser extent dense, stems with a narrow range of variation around these values. No consistent link was found between carbon storage and the leaf traits usually associated with plant resource use strategy. The negative association of trait divergence with carbon storage provided no evidence in support to niche complementarity promoting carbon storage in these forest ecosystems.
In Argentina, deforestation due to agriculture expan-sion is threatening the Semi-arid Chaco, one of the largest forested biomes of South America. This study focuses on the north-west boundary of the Argentine Semi-arid Chaco, where soybean is the most important crop. Deforestation was estimated for areas with dif-ferent levels of soil and rainfall limitation for agricul-ture between 1972 and 2001, with a finer analysis in three periods starting in 1984, which are characterized by differences in rainfall, soybean price, production cost, technology-driven yield and national gross domestic product. Between 1972 and 2001, 588 900 ha (c. 20% of the forests) were deforested. Deforestation has been accelerating, reaching >28 000 ha yr −1 after 1997. The initial deforestation was associated with black bean cultivation following an increase in rainfall during the 1970s. In the 1980s, high soybean prices stimulated fur-ther deforestation. Finally, the introduction of soybean transgenic cultivars in 1997 reduced plantation costs and stimulated a further increase in deforestation. The domestic economy had little association with defo-restation. Although deforestation was more intense in the moister (rainfall >600 mm yr −1) areas, more than 300 000 ha have already been deforested in the drier areas, suggesting that climatic limitations are being overcome by technological and genetic improvement. Furthermore, more than 300 000 ha of forest occur in sectors without major soil and rainfall limitations. If global trends of technology, soybean markets and climate continue, and no active conservation policies are applied, vast areas of the Chaco will be deforested in the coming decades.
Forests in Flux
Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others. Hansen et al. (p. 850 ) examined global Landsat data at a 30-meter spatial resolution to characterize forest extent, loss, and gain from 2000 to 2012. Globally, 2.3 million square kilometers of forest were lost during the 12-year study period and 0.8 million square kilometers of new forest were gained. The tropics exhibited both the greatest losses and the greatest gains (through regrowth and plantation), with losses outstripping gains.
Vegetation states with low suitability for cattle raising (‘woody states’) are widespread in the Chaco region (NW Argentina). We assessed the success of roller-chopper (RR); roller-chopper with seeding of Panicum maximum cv green panic (RS), and roller chopper followed by prescribed fire (RF) in disrupting a woody state in two separate experiments, monitored from 1997 to 2002. We evaluated amount and temporal dynamics of woody plant volume, standing herbaceous biomass and livestock accessibility. We also monitored soil moisture at two soil depths, sunlight availability and the dynamics of germination of grass, forbs and woody species. Spatial variation was included as ecological sites, and all treatments were grazed. The longevity for each treatment was estimated by monitoring the woody volume through time. Data were analyzed using variance and regression analysis. MRPP techniques were used to study the effect on species diversity. Results were compared with information in literature to define thresholds and success of restoration. RF showed the lowest mean woody canopy (p > F = 0.0001), the largest mean accessibility (>70%), and longest return interval (>6 years) among treatments. RS showed the largest amount of herbaceous standing biomass (>5000 kg dry matter ha−1, p > F = 0.0001), and a longevity >5 years. Prescribed fire was successful in controlling the increase of woody volume only at lowland and midland ecosites. At upland ecosites in RS and RR, mean woody volume and accessibility were higher than in the other two sites. Plant diversity was significantly affected by ecosite rather than by treatment and time. Soil moisture was influenced by site (p > F = 0.001), while sunlight availability was affected by treatment (p > F = 0.001). Plant germination was affected by treatment and site. The roller chopper is an adequate tool for disrupting woody states in the Chaco and could be successfully combined with prescribed fire.
Aims
Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for different purposes of vegetation mapping. Generally, it needs to develop a vegetation classification at first for classifying and mapping vegetation cover from remote sensed images either at a community level or species level. Then, correlations of the vegetation types (communities or species) within this classification system with discernible spectral characteristics of remote sensed imagery have to be identified. These spectral classes of the imagery are finally translated into the vegetation types in the image interpretation process, which is also called image processing. This paper presents an overview of how to use remote sensing imagery to classify and map vegetation cover.
Methods
Specifically, this paper focuses on the comparisons of popular remote sensing sensors, commonly adopted image processing methods and prevailing classification accuracy assessments.
Important findings
The basic concepts, available imagery sources and classification techniques of remote sensing imagery related to vegetation mapping were introduced, analyzed and compared. The advantages and limitations of using remote sensing imagery for vegetation cover mapping were provided to iterate the importance of thorough understanding of the related concepts and careful design of the technical procedures, which can be utilized to study vegetation cover from remote sensed images.
Recently, interest in species distribution modelling has increased following the development of new methods for the analysis of presence‐only data and the deployment of these methods in user‐friendly and powerful computer programs. However, reliable inference from these powerful tools requires that several assumptions be met, including the assumptions that observed presences are the consequence of random or representative sampling and that detectability during sampling does not vary with the covariates that determine occurrence probability.
Based on our interactions with researchers using these tools, we hypothesized that many presence‐only studies were ignoring important assumptions of presence‐only modelling. We tested this hypothesis by reviewing 108 articles published between 2008 and 2012 that used the MAXENT algorithm to analyse empirical (i.e. not simulated) data. We chose to focus on these articles because MAXENT has been the most popular algorithm in recent years for analysing presence‐only data.
Many articles (87%) were based on data that were likely to suffer from sample selection bias; however, methods to control for sample selection bias were rarely used. In addition, many analyses (36%) discarded absence information by analysing presence–absence data in a presence‐only framework, and few articles (14%) mentioned detection probability. We conclude that there are many misconceptions concerning the use of presence‐only models, including the misunderstanding that MAXENT , and other presence‐only methods, relieve users from the constraints of survey design.
In the process of our literature review, we became aware of other factors that raised concerns about the validity of study conclusions. In particular, we observed that 83% of articles studies focused exclusively on model output (i.e. maps) without providing readers with any means to critically examine modelled relationships and that MAXENT 's logistic output was frequently (54% of articles) and incorrectly interpreted as occurrence probability.
We conclude with a series of recommendations foremost that researchers analyse data in a presence–absence framework whenever possible, because fewer assumptions are required and inferences can be made about clearly defined parameters such as occurrence probability.
The net flux of carbon from land use and land-cover change (LULCC) accounted for 12.5 % of anthro-pogenic carbon emissions from 1990 to 2010. This net flux is the most uncertain term in the global carbon budget, not only because of uncertainties in rates of deforestation and forestation, but also because of uncertainties in the carbon density of the lands actually undergoing change. Further-more, there are differences in approaches used to determine the flux that introduce variability into estimates in ways that are difficult to evaluate, and not all analyses consider the same types of management activities. Thirteen recent esti-mates of net carbon emissions from LULCC are summa-rized here. In addition to deforestation, all analyses consid-ered changes in the area of agricultural lands (croplands and pastures). Some considered, also, forest management (wood harvest, shifting cultivation). None included emissions from the degradation of tropical peatlands. Means and standard de-viations across the thirteen model estimates of annual emis-sions for the 1980s and 1990s, respectively, are 1.14 ± 0.23 and 1.12 ± 0.25 Pg C yr 1 (1 Pg = 10 15 g carbon). Four stud-ies also considered the period 2000–2009, and the mean and standard deviations across these four for the three decades are 1.14 ± 0.39, 1.17 ± 0.32, and 1.10 ± 0.11 Pg C yr 1 . For the period 1990–2009 the mean global emissions from LULCC are 1.14 ± 0.18 Pg C yr 1 . The standard deviations across model means shown here are smaller than previous estimates of uncertainty as they do not account for the errors that result from data uncertainty and from an incomplete understand-ing of all the processes affecting the net flux of carbon from LULCC. Although these errors have not been systematically evaluated, based on partial analyses available in the litera-ture and expert opinion, they are estimated to be on the order of ± 0.5 Pg C yr 1 .
Tree mortality is an important process in forest ecology. We explored the extent to which tropical tree death is a predictable outcome of taxon and individual level properties by means of mixed‐species logistic regression, for trees ≥ 10 cm in diameter. We worked in two lowland forest regions with markedly different floristic composition and dynamic regimes – the high wood density, low‐mortality northeastern (NE) Amazon (in eastern Venezuela), and the low wood density, high‐mortality northwestern (NW) Amazon (in northern Peru).
Among those genera that are shared between regions there were no detectable regional differences in mortality rates. This suggests that floristic compositional differences are a major driver of the twofold regional contrast in stand‐level mortality.
In NE forests, mortality risk of individual trees is best predicted by low taxon‐level wood density, slow relative growth, and large size, reflecting phylogenetically determined life‐history strategy, physiological stress and senescence.
In NW forests, trees with low wood density and slow relative growth are also at most risk, but probability of death is independent of tree size, indicating that senescence is unimportant in this region.
Synthesis. This study shows that despite fundamental floristic and dynamic differences between the two Amazonian regions, mortality risk can be predicted with mixed‐species, individual‐based statistical models and that the predictors are remarkably similar, such that tree growth and wood density both play important roles.
We estimated carbon pools and emissions from deforestation in northern Argentine forests between 1900 and 2005, based on forest
inventories, deforestation estimates from satellite images and historical data on forests and agriculture. Carbon fluxes were
calculated using a book-keeping model. We ran 1000 simulations for a 105-year period with different combinations of values
of carbon stocks (MgCha−1), soil carbon in the top 0.2m, and annual deforestation series. The 1000 combinations of parameters were performed as a
sensitivity analysis that for each run, randomly selected the values of each variable within a predefined range of values
and probability distributions. Using the simulation outputs, we calculated the accumulated C emissions due to deforestation
from 1900 to 2005 and the annual emission as the average of the 1000 simulations, and uncertainties of our estimates as the
standard deviation. We found that northern Argentine forests contain an estimated 4.54Pg C (2.312 Pg C in biomass and 2.233
Pg C in soil). Between 1900 and 2005 approximately 30% of the forests were deforested, yielding carbon emissions of 0.945
(SD=0.270) Pg C. Estimated average annual carbon emissions between 1996 and 2005, mostly from deforestation of the Chaco
dry forests, were 20,875 (SD=6,156) Gg C y−1 (1 Gg=10−6 Pg). These values represent the largest source of carbon from land-cover change in the extra-tropical southern hemisphere,
between 0.9 and 2.7% of the global carbon emissions from deforestation, and approximately 10% of carbon emissions from the
Brazilian Amazon. Deforestation, which has accelerated during the last decades as a result of modern agriculture expansion,
represents a major national source of greenhouse gases and the second emission source, after fossil fuel consumption by fixed
sources. We conclude that Argentine forests are an important carbon pool and emission source that need more attention for
accurate global estimates, and seasonally dry forest deforestation is a key component of the Argentine carbon cycle.
One way of mitigating global climate change is protecting and enhancing biosphere carbon stocks. The success of mitigation initiatives depends on the long-term net balance between carbon gains and losses. The biodiversity of ecological communities, including composition and variability of traits of plants and soil organisms, can alter this balance in several ways. This influence can be direct, through determining the magnitude, turnover rate, and longevity of carbon stocks in soil and vegetation. It can also be indirect through influencing the value and therefore the protection that societies give to ecosystems and their carbon stocks. Biodiversity of forested ecosystems has important consequences for long-term carbon
storage, and thus warrants incorporation into the design,
implementation, and regulatory framework of mitigation
initiatives.
The global carbon budget is, of course, balanced. The conservation of carbon and the first law of thermodynamics are intact. "Balancing the carbon budget" refers to the state of the science in evaluating the terms of the global carbon equation. The annual increases in the amount of carbon in the atmosphere, oceans, and land should balance the emissions of carbon from fossil fuels and deforestation. Balanc- ing the carbon budget is not the real issue, however. The real issue is understanding the processes responsible for net sources and sinks of carbon. Such understanding should lead to more accurate predic- tions of future concentrations of CO2 and more accurate predictions of the rate and extent of climatic change. The recent past may be in- sufficient for prediction, however. Oceanic and terrestrial sinks that have lessened the rate of growth in atmospheric CO2 until now may diminish as feedbacks between the carbon cycle and climate become more prominent.
Information on net primary production in tropical forests is needed for the development of realistic global carbon budgets, for projecting how these ecosystems will be affected by climatic and atmospheric changes, and for evaluating eddy covariance mea- surements of tropical forest carbon flux. However, a review of the database commonly used to address these issues shows that it has serious flaws. In this paper we synthesize the data in the primary literature on NPP in old-growth tropical forests to produce a consistent data set on NPP for these forests. Studies in this biome have addressed only a few NPP com- ponents, all aboveground. Given the limited scope of the direct field measurements, we sought relationships in the existing data that allow estimation of unmeasured aspects of production from those that are more easily assessed. We found a predictive relationship between annual litterfall and aboveground biomass increment. For 39 diverse tropical forest sites, we then developed consistent, documented estimates of the upper and lower bounds around total NPP to serve as benchmarks for calibrating and validating biogeochemical models with respect to this biome. We developed these estimates based on existing field measurements, current understanding of aboveground consumption and biogenic volatile organic carbon emissions, and our judgment that belowground production is bounded by the range 0.2-1.2 3 ANPP (aboveground NPP). Across this broad spectrum of tropical forests (dry to wet, lowland to montane, nutrient-rich to nutrient-poor soils), our estimates of lower and upper bounds on total NPP range from 1.7 to 11.8 Mg C·ha 21 ·yr 21 (lower bounds) and from 3.1 to 21.7 Mg C·ha 21 ·yr 21 (upper bounds). We also showed that two relationships that have been used for estimating NPP (the Bray-Gorham relationship based on leaf litterfall and the Miami model based on temperature or precipitation) are not valid for the tropical forest biome.
The terrestrial carbon sink has been large in recent decades, but its size and location remain uncertain. Using forest inventory
data and long-term ecosystem carbon studies, we estimate a total forest sink of 2.4 ± 0.4 petagrams of carbon per year (Pg
C year–1) globally for 1990 to 2007. We also estimate a source of 1.3 ± 0.7 Pg C year–1 from tropical land-use change, consisting of a gross tropical deforestation emission of 2.9 ± 0.5 Pg C year–1 partially compensated by a carbon sink in tropical forest regrowth of 1.6 ± 0.5 Pg C year–1. Together, the fluxes comprise a net global forest sink of 1.1 ± 0.8 Pg C year–1, with tropical estimates having the largest uncertainties. Our total forest sink estimate is equivalent in magnitude to the
terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks.
Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ± 6% to ± 53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ± 5% and ca. ± 1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.
Tropical tree height-diameter ( H:D ) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were:
1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap).
2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A ).
3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass.
Annual precipitation coefficient of variation ( P <sub>V</sub>), dry season length ( S <sub>D</sub>), and mean annual air temperature ( T <sub>A</sub>) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D . After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere.
The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within a median –2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D . Pantropical and continental-level models provided only poor estimates of H , especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.
Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees >or= 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle.
Covering 16% of global land surface, dry forests play a key role in the global carbon budget. The Southern Hemisphere still preserves a high proportion of its native dry forest cover, but deforestation rates have increased dramatically in the last decades. In this paper, we quantified for the first time the magnitude and temporal variability of carbon dioxide and water vapor fluxes and their environmental controls based on eddy covariance measurements in a dry forest site of central Argentina. Continuous measurements of CO 2 and water vapor exchanges spanning a 15-month period (Dec. 2009 – March 2011) showed that the studied dry forest was a net sink of carbon, with an overall integrated net ecosystem exchange (NEE) of −172 g C m −2 (−132.8 g C m −2 for year 2010). The cool dry season (May–Sept.) accounted for a quarter of the total annual NEE of year 2010 with low but steady CO 2 uptake rates (1 g C m −2 d −1 on average) that were more strongly associated with temperature than with soil moisture. By contrast, in the warm wet season (Oct.–April), almost three times greater CO 2 uptake rates (2.7 g C m −2 d −1 on average) resulted from a highly pulsed behavior in which CO 2 uptake showed sharp increases followed by rapid declines after rainfall events. Cumulative evapotranspiration (ET) during the whole study (595 mm) accounted for most of the rainfall inputs (674 mm), with daily water vapor fluxes during the wet season being four times greater compared to those observed during the dry season (1.7 mm d −1 vs. 0.45 mm d −1). Modeling of the partition of all evaporative water losses suggested that transpiration was the dominant vapor flux (67% of ET), followed by interception (20%) and soil evaporation (13%). The influence of air temperature on half-hourly CO 2 fluxes was notably different for the dry and wet seasons. In the 11–34 °C air temperature range, CO 2 uptake rates were higher in the warm wet rather than the cool dry season, yet this difference narrowed with temperatures > 26 °C. The dry forest became a net CO 2 source at 40 °C. Our study provides new insights about the functioning of dry forests and the likely response of their CO 2 and water vapor exchange with the atmosphere under future climate and land use/cover changes.
Carbon emissions from land-use changes in tropical dry forest systems are poorly understood, although they are likely globally significant. The South American Chaco has recently emerged as a hot spot of agricultural expansion and intensification, as cattle ranching and soybean cultivation expand into forests, and as soybean cultivation replaces grazing lands. Still, our knowledge of the rates and spatial patterns of these land-use changes and how they affected carbon emissions remains partial. We used the Landsat satellite image archive to reconstruct land-use change over the past 30 years and applied a carbon bookkeeping model to quantify how these changes affected carbon budgets. Between 1985 and 2013, more than 142 000 km(2) of the Chaco's forests, equaling 20% of all forest, was replaced by croplands (38.9%) or grazing lands (61.1%). Of those grazing lands that existed in 1985, about 40% were subsequently converted to cropland. These land-use changes resulted in substantial carbon emissions, totaling 824 Tg C between 1985 and 2013, and 46.2 Tg C for 2013 alone. The majority of these emissions came from forest-to-grazing-land conversions (68%), but post-deforestation land-use change triggered an additional 52.6 Tg C. Although tropical dry forests are less carbon-dense than moist tropical forests, carbon emissions from land-use change in the Chaco were similar in magnitude to those from other major tropical deforestation frontiers. Our study thus highlights the urgent need for an improved monitoring of the often overlooked tropical dry forests and savannas, and more broadly speaking the value of the Landsat image archive for quantifying carbon fluxes from land change.
On the basis of several floristic, structural, morpho-ecological and climatic features, four tropical seasonal formations of the Caribbean area of northern South America were compared with nine seasonal subtropical types occurring in southern South America. The main features considered were: number of woody families and genera; generic composition; floristic elements; generic diversity; layering; leaf size and leaf type of canopy layer species; number of woody genera with thorny, succulent and aphyllous representatives; mean annual rainfall and number of dry months. The main facts disclosed by this comparison were as follows. (1) The tropical American formations are floristically richer than their equivalent subtropical types; α-diversity decreases toward the arid extremes of each series, but in a more irregular way in the subtropical group. (2) Tropical elements predominate in the less seasonal types of both series, whilst the most seasonal formations have a more heterogeneous flora from the distributional viewpoint. (3) A two-axis ordination of the thirteen types is given, showing the relative floristic affinity between them. The Gallery forest of the Paranά-Paraguay rivers, a southward extension of the Austro-Brazilian subtropical Rain forest is the subtropical type closely related to the tropical seasonal formations. (4) Subtropical units are lower and structurally simpler than tropical types occurring under equivalent climate (same number of dry months). (5) Figures for the various leaf types also show that each subtropical formation compares best with a more seasonal tropical type. However, in the subtropical area, the mixed character of leaf type is more evident when only the dominant species in each formation are considered. (6) Subtropical types have significantly smaller leaf sizes, whilst the proportion of taxa showing xeromorphic features is greater than in the Caribbean types. (7) The subtropical seasonal formations of southern South America are then floristically poorer but morphologically more diversified than the tropical types of the Caribbean area. Some morphological features, such as aphylly, are more widespread in the former types. (8) It is not possible to arrange the seasonal subtropical types along a single gradient as is the case for the tropical units. The group of seasonal formations in the subtropical area varies irregularly, probably due to the combined action of the two main environmental stresses: drought and cold.
The MaxEnt software package is one of the most popular tools for species distribution and environmental niche modeling, with over 1000 published applications since 2006. Its popularity is likely for two reasons: 1) MaxEnt typically outperforms other methods based on predictive accuracy and 2) the software is particularly easy to use. MaxEnt users must make a number of decisions about how they should select their input data and choose from a wide variety of settings in the software package to build models from these data. The underlying basis for making these decisions is unclear in many studies, and default settings are apparently chosen, even though alternative settings are often more appropriate. In this paper, we provide a detailed explanation of how MaxEnt works and a prospectus on modeling options to enable users to make informed decisions when preparing data, choosing settings and interpreting output. We explain how the choice of background samples reflects prior assumptions, how nonlinear functions of environmental variables (features) are created and selected, how to account for environmentally biased sampling, the interpretation of the various types of model output and the challenges for model evaluation. We demonstrate MaxEnt’s calculations using both simplified simulated data and occurrence data from South Africa on species of the flowering plant family Proteaceae. Throughout, we show how MaxEnt’s outputs vary in response to different settings to highlight the need for making biologically motivated modeling decisions.
Latin American subtropical dry ecosystems have experienced significant human impact for more than a century, mainly in the form of extensive livestock grazing, forest products extraction, and agriculture expansion. We assessed the regional-scale effect of land use and land cover (LULC) on patterns of richness distribution of trees, birds, amphibians, and mammals in the Northern Argentine Dry Chaco (NADC) over c. 19 million hectares. Using species distribution models in a hierarchical framework, we modeled the distributions of 138 species. First, we trained the models for the entire Argentinean Chaco with climatic and topographic variables. Second, we modeled the same species for the NADC including the biophysical variables identified as relevant in the first step plus four LULC-related variables: woody biomass, distance to crops, density of livestock-based rural settlements (puestos), and vegetation cover. Third, we constructed species richness maps by adding the models of individual species and considering two situations, with and without LULC variables. Four, richness maps were used for assessing differences when LULC variables are added and for determining the main drivers of current patterns of species richness. We found a marked decrease in species richness of the four groups as a consequence of inclusion of LULC variables in distribution models. The main factors associated with current richness distribution patterns (both negatively) were woody biomass and density of livestock puestos. Species richness in present-day Semiarid Chaco landscapes is strongly affected by LULC patterns, even in areas not transformed to agriculture. Regional-scale biodiversity planning should consider open habitats such as grasslands and savannas in addition to woodlands.
Soybean expansion, driven by growing global meat demand, has accompanied neotropical deforestation in past decades. A recent decoupling between soybean production and deforestation in Brazil is taken as evidence of efficient deforestation regulation. Here, we assessed the relationships between soybean economy, livestock production and deforestation from 1972 to 2011 in Northern Argentina Dry Chaco. We used Panel Analysis to evaluate the relationship between soybean cultivated and deforested area in different periods and we used high resolution time series analysis of a deforestation hotspot, to explore links between soybean economy, cattle ranching and deforestation. In northern Argentina, 2.7 millions ha were deforested from 1972 to 2011, 56% of which occurred after 2002. The results of the Panel analysis indicate a strong link between soybean expansion and deforestation but with variation among periods mediated by the links between soybean and livestock productions. Deforestation was strongly coupled with soybean expansion during the 1972–1997 and 2002–2011 periods; but was largely decoupled between 1997 and 2002, when strong increments in production were accompanied by low deforestation. The high resolution analysis also indicated contrasting levels of association after and before 1997. The soybean deforestation decoupled periods in Brazil and Argentina shared similarly weak economic incentives for soybean production, rapid technological innovation and preceding high deforestation periods. In the Argentine case, when economic incentives turned positive after a 5-years decoupled period, new government measures were unable to regulate deforestation. Our study suggests that macroeconomic factors can be a much stronger deforestation force compared with domestic legal frameworks. Effectiveness of neotropical deforestation regulation should be carefully monitored and interpreted with caution paying special attention to global economic context for soybean expansion.
Data from spaceborne light detection and ranging (lidar) opens the
possibility to map forest vertical structure globally. We present a
wall-to-wall, global map of canopy height at 1-km spatial resolution,
using 2005 data from the Geoscience Laser Altimeter System (GLAS) aboard
ICESat (Ice, Cloud, and land Elevation Satellite). A challenge in the
use of GLAS data for global vegetation studies is the sparse coverage of
lidar shots (mean = 121 data points/degree2 for the L3C
campaign). However, GLAS-derived canopy height (RH100) values were
highly correlated with other, more spatially dense, ancillary variables
available globally, which allowed us to model global RH100 from forest
type, tree cover, elevation, and climatology maps. The difference
between the model predicted RH100 and footprint level lidar-derived
RH100 values showed that error increased in closed broadleaved forests
such as the Amazon, underscoring the challenges in mapping tall (>40
m) canopies. The resulting map was validated with field measurements
from 66 FLUXNET sites. The modeled RH100 versus in situ canopy height
error (RMSE = 6.1 m, R2 = 0.5; or, RMSE = 4.4 m,
R2 = 0.7 without 7 outliers) is conservative as it also
includes measurement uncertainty and sub pixel variability within the
1-km pixels. Our results were compared against a recently published
canopy height map. We found our values to be in general taller and more
strongly correlated with FLUXNET data. Our map reveals a global
latitudinal gradient in canopy height, increasing towards the equator,
as well as coarse forest disturbance patterns.
Land use change, particularly in forested ecosystems, has a direct impact on the global carbon cycle. Consequently, the regional assessment of biomass and the understanding of its current spatial controls are research priorities for regional ecology and land use. Field data and satellite imagery were combined here to map woodlands and estimate their above-ground biomass (AGB) in the Dry Chaco ecoregion of northern Argentina. Allometric equations were used to derive AGB from diameter at breast height data collected at 50 samples during 2007. In order to generate the AGB regional map, this information was later associated with MODIS-Terra spectral data (NDVI) using the Random Forest (RF) method. Finally, AGB spatial patterns were associated with potential biophysical and human controlling factors through correlation and regression analyses. Results indicate that the use of RF and NDVI of the dry season derived from MODIS-Terra was suitable to map regional AGB, what makes this methodology applicable to other dry woodlands. The RF model used to map AGB showed a mean deviation of 2.9 % and a precision of 15 % for one prediction. At this regional scale of analysis, biophysical rather than human factors controlled AGB spatial patterns, in part because the region includes a wide range of environmental situations. Warmer conditions showed a higher biomass, suggesting an energetic limitation for AGB accumulation. However, human controls (distance to towns, cultivation, and roads) also conditioned AGB patterns, suggesting lower AGB values near cultivated areas. The relation between AGB and water availability was surprisingly weak, but partially obscured by the land use history and degradation due to extensive cattle ranching. We propose that a combination of environmental factor and land use affects the AGB regional patterns and promotes unexpected relationships with environmental factors. This work represents the first spatially explicit AGB (patterns and controls) analysis for an extensive subtropical dry woodland area (113,000 km2) and shows how biophysical and human factors co-control regional patterns.
Wood florulas from southwestern Australia were analyzed to determine whether wood anatomy is sufficiently correlated with ecology so that vessel element features can be said to have a predictive value. Indices for vulnerability (vessel diam: vessels per sq. mm) and mesomorphy (vulnerability X vessel element length) were calculated for each species in the following florulas: karri forest understory, coastal granitic slopes, bogs, sand heaths, and desert. Wood indices for the species studied and for each florula show that these florulas form a sequence in increasing xeromorphy in the order listed. Genera represented in more than one florula validate the trends. Data for Gyrostemonaceae, Loranthaceae, and Cupressaceae are calculated separately because these are succulents, epiparasites, and conifers, respectively. Comparison with categories from floras elsewhere in the world shows the flora of Western Australia as a whole to be relatively xeromorphic. The indices devised show promise of great reliability because correlations with rainfall, temperature, and other factors are very close. Functional nature of the vessel element is thereby believed to be clarified.
Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar ( li ght d etection and r anging) instruments measure the vertical structure of forests and thus hold great promise for remotely sensing the quantity and spatial organization of forest biomass. In this study, we compare the relationships between lidar-measured canopy structure and coincident field measurements of above-ground biomass at sites in the temperate deciduous, temperate coniferous, and boreal coniferous biomes. A single regression for all three sites is compared with equations derived for each site individually. The single equation explains 84% of variance in above-ground biomass ( P < 0.0001) and shows no statistically significant bias in its predictions for any individual site.
1] The Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's satellites, Terra and Aqua, dramatically improves our ability to accurately and continuously monitor the terrestrial biosphere. MODIS information is used to estimate global terrestrial primary production weekly and annually in near-real time at a 1-km resolution. MODIS terrestrial primary production requires daily gridded assimilation meteorological data as inputs, and the accuracy of the existing meteorological reanalysis data sets show marked differences both spatially and temporally. This study compares surface meteorological data sets from three well-documented global reanalyses, NASA Data Assimilation Office (DAO), European Centre for Medium-Range Weather Forecasts (ECMWF) (ERA-40) and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis 1, with observed weather station data and other gridded data interpolated from the observations, to evaluate the sensitivity of MODIS global terrestrial gross and net primary production (GPP and NPP) to the uncertainties of meteorological inputs both in the United States and the global vegetated areas. NCEP tends to overestimate surface solar radiation, and underestimate both temperature and vapor pressure deficit (VPD). ECMWF has the highest accuracy but its radiation is lower in tropical regions, and the accuracy of DAO lies between NCEP and ECMWF. Biases in temperature are mainly responsible for large VPD biases in reanalyses. MODIS NPP contains more uncertainties than GPP. Global total MODIS GPP and NPP driven by DAO, ECMWF, and NCEP show notable differences (>20 Pg C/yr) with the highest estimates from NCEP and the lowest from ECMWF. Again, the DAO results lie somewhere between NCEP and ECMWF estimates. Spatially, the larger discrepancies among reanalyses and their derived MODIS GPP and NPP occur in the tropics. These results reveal that the biases in meteorological reanalyses can introduce substantial error into GPP and NPP estimations, and emphasize the need to minimize these biases to improve the quality of MODIS GPP and NPP products.
The rapid growth rates of light‐demanding tree species have been attributed in part to their low‐density, low‐cost stems. We evaluated the influence of light and biomass support costs on growth rates of trees 8–25 cm in diameter at breast height (d.b.h.) among 21 species differing in wood density in two aseasonal rain forests.
Measurements of crown width, tree height, d.b.h. and wood density (ρ) were used to estimate the stem biomass ( M s ) of a standard‐sized tree (17 m tall and 16 m ² in crown area), i.e. the cost in stem biomass of supporting a given sized crown at a given height.
The species showed a three‐fold range in support cost, which was highly correlated with wood density ( M s ∝ ρ 0.77 , r ² = 0.72 for the log‐transformed relationship). This relationship is due to the high interspecific variation in wood density and the fact that the stem diameter of the standard‐sized tree increased only slightly with decreasing wood density, i.e. light‐wooded species did not compensate for their lighter, weaker wood by substantially increasing stem thickness.
Mean growth rate per species showed a 10‐fold range and increased with the fraction of trees at least partly in gaps (gap fraction), the reciprocal of support cost (1/ M s ), and the reciprocal of wood density (1/ρ). The relationship between mean growth rate and 1/ M s was particularly strong when one outlier was excluded ( r ² = 0.88) and among the Dipterocarpaceae ( r ² = 0.89).
Log(mortality rate), as determined for all trees per species ≥ 1 cm d.b.h., increased linearly with 1/ M s , 1/ρ and gap fraction.
These results suggest an important role for wood density and support costs in the classic tradeoff between rapid growth and increased risks of damage and death.
Evaluating the role of terrestrial ecosystems in the global carbon cycle requires a detailed understanding of carbon exchange between vegetation, soil, and the atmosphere. Global climatic change may modify the net carbon balance of terrestrial ecosystems, causing feedbacks on atmospheric CO2 and climate. We describe a model for investigating terrestrial carbon exchange and its response to climatic variation based on the processes of plant photosynthesis, carbon allocation, litter production, and soil organic carbon decomposition. The model is used to produce geographical patterns of net primary production (NPP), carbon stocks in vegetation and soils, and the seasonal variations in net ecosystem production (NEP) under both contemporary and future climtes. For contemporary climte, the estimated global NPP is 57.0 Gt C y-1, carbon stocks in vegetation and soils will increase by, respectively 133 Gt C and 160 Gt C, and the seasonal amplitude of NEP will increase by 76%. A doubling of atmospheric CO2 without climate change may enhance NPP by 25% and result in a substantial increase in carbon stocks in vegetation and soils. Climate change without CO2 elevation will reduce the global NPP and soil carbon stocks, but leads to an increase in vegetation carbon because of a forest extension and NPP enhancement in the north. By combining the effects of CO2 doubling, climate change, and the consequent redistribution of vegetation, we predict a strong enhancement in NPP and carbon stocks of terrestrial ecosystems. This study simulates the possible variation in the carbon exchange at equilibrium state. We anticipate to investigate the dynamic responses in the carbon exchange to atmosperic CO2 elevation and climate change in the past and future.
Variation in climate and soils results in inter‐site differences in the assemblages of tree life history strategies within a community, which has important implications for ecosystem structure and dynamics. I investigated interspecific and inter‐site variation in wood specific gravity–an easily measured indicator of tree life history strategy–in four Neotropical forests and analyzed its correlates. Mean wood specific gravity (oven‐dry weight divided by fresh volume, sometimes also referred to as wood density in the literature) differed significantly among sites, varying inversely with soil fertility and independently of rainfall, seasonality, and temperature. Mean wood specific gravity values were much higher at Kilometer 41, Manaus, Brazil, where soils are extremely poor, than at Cocha Cashu, Peru, Barro Colorado Island, Panama, or La Selva, Costa Rica, where soils are better and mortality rates of trees are higher. Within sites, wood specific gravity varied widely among species. On Barro Colorado Island, among‐species variation was significantly, albeit weakly, negatively correlated with sapling and tree mortality and relative growth rates. Altogether, the results suggest that the distribution of tree life history strategies in a community varies substantially among sites, with important consequences for community and ecosystem properties such as aboveground carbon stores.
RESUMEN
La variación climática y edáfica da lugar a diferencias entre sitios con respecto a los ensambles de las estrategias de historia de vida de los árboles de una comunidad, lo cual tiene consecuencias importantes para la estructura y la dinámica del ecosistema. Investigué la variación interespecífica y espacial en la gravedad específica de la Madera–un indicador de fácil medición de la estrategia de historia de vida de los árboles–en cuatro bosques neotropicales y analizé sus factores asociados. La gravedad especifica media de la madera (el peso seco dividido por el volumen fresco, frecuentemente llamado “densidad de la madera” en la literatura ecológica) fue significativamente diferente entre sitios, variando inversamente con la fertilidad del suelo, e independientemence de la precipitación, la estacionalidad, y la temperatura. La gravedad especifica media de la madera fue mucho más alta en Kilómetro 41, Manaus, Brasil, donde los suelos son extremadamente pobres, en comparación con Cocha Cashu, Perú, Barro Colorado, Panamá, o La Selva, Costa Rica, donde los suelos son mejores y las tasas de mortalidad de los árboles son más altas. Dentro de los sitios, la gravedad especifica de la madera varió extensamente entre especies. En Barro Colorado, la variación entre especies estuvo correlacionada negativamente, aunque sólo débilmente, con las tasas de mortalidad y de crecimiento relativo de los árboles juveniles y adultos. En conjunto, los resultados sugieren que la distribución de las estrategias de historia de vida de los árboles en una comunidad varía sustancialmente entre sitios, con consecuencias importantes para características comunitarias y del ecosistema tales como las reservas de carbono.
Wood density (D
t), an excellent predictor of mechanical properties, is typically viewed in relation to support against gravity, wind, snow, and other environmental forces. In contrast, we show the surprising extent to which variation in D
t and wood structure is linked to support against implosion by negative pressure in the xylem pipeline. The more drought-tolerant the plant, the more negative the xylem pressure can become without cavitation, and the greater the internal load on the xylem conduit walls. Accordingly, D
t was correlated with cavitation resistance. This trend was consistent with the maintenance of a safety factor from implosion by negative pressure: conduit wall span (b) and thickness (t) scaled so that (t/b)2 was proportional to cavitation resistance as required to avoid wall collapse. Unexpectedly, trends in D
t may be as much or more related to support of the xylem pipeline as to support of the plant.
Aboveground biomass (AGB) reflects multiple and often undetermined ecological and land-use processes, yet detailed landscape-level studies of AGB are uncommon due to the difficulty in making consistent measurements at ecologically relevant scales. Working in a protected mediterranean-type landscape (Jasper Ridge Biological Preserve, California, USA), we combined field measurements with remotely sensed data from the Carnegie Airborne Observatory's light detection and ranging (lidar) system to create a detailed AGB map. We then developed a predictive model using a maximum of 56 explanatory variables derived from geologic and historic-ownership maps, a digital elevation model, and geographic coordinates to evaluate possible controls over currently observed AGB patterns. We tested both ordinary least-squares regression (OLS) and autoregressive approaches. OLS explained 44% of the variation in AGB, and simultaneous autoregression with a 100-m neighborhood improved the fit to an r2 = 0.72, while reducing the number of significant predictor variables from 27 variables in the OLS model to 11 variables in the autoregressive model. We also compared the results from these approaches to a more typical field-derived data set; we randomly sampled 5% of the data 1000 times and used the same OLS approach each time. Environmental filters including incident solar radiation, substrate type, and topographic position were significant predictors of AGB in all models. Past ownership was a minor but significant predictor, despite the long history of conservation at the site. The weak predictive power of these environmental variables, and the significant improvement when spatial autocorrelation was incorporated, highlight the importance of land-use history, disturbance regime, and population dynamics as controllers of AGB.
This paper shows the results of an assessment on the current extent of Neotropical dry forests based on a supervised classification of MODIS surface reflectance imagery at 500-m resolution. Our findings show that tropical dry forests extend for 519,597 km2 across North and South America. Mexico, Brazil and Bolivia harbor the largest and best-preserved dry forest fragments. Mexico contains the largest extent at 181,461 km2 (38% of the total), although it remains poorly represented under protected areas. On the other hand, Brazil and Bolivia contain the largest proportion of protected tropical dry forests and the largest extent in continuous forest fragments. We found that five single ecoregions account for more than half of the tropical dry forests in the Americas (continental and insular) and these ecoregions are: the Chiquitano dry forests, located in Bolivia and Brazil (27.5%), the Atlantic dry forests (10.2%), the Sinaloan dry forests in Mexico (9.7%), the Cuban dry forests (7.1%) and the Bajio dry forests in Mexico (7%). Chiquitano dry forests alone contain 142,941 km2 of dry forests. Of the approximately 23,000 km2 of dry forest under legal protection, 15,000 km2 are located in just two countries, Bolivia and Brazil. In fact, Bolivia protects 10,609 km2 of dry forests, where 7600 km2 are located within the Chiquitano dry forest ecoregion and protected by a single park. Low extent and high fragmentation of dry forests in countries like Guatemala, Nicaragua, Ecuador, Costa Rica and Peru means that these forests are at a higher risk from human disturbance and deforestation.
The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis. The use of the AIC criterion in the factor analysis is particularly interesting when it is viewed as the choice of a Bayesian model. This observation shows that the area of application of AIC can be much wider than the conventional i.i.d. type models on which the original derivation of the criterion was based. The observation of the Bayesian structure of the factor analysis model leads us to the handling of the problem of improper solution by introducing a natural prior distribution of factor loadings.
Trees, shrubs, lianas and herbs have widely different mechanical architectures, which can also vary phenotypically with the environment. This review investigates how environmental effects, particularly mechanical perturbation, can influence biomechanical development in self-supporting and climbing growth forms. The bifacial vascular cambium is discussed in terms of its significance to growth form variation, ecology and evolution among extant plants, and during its appearance and early evolution. A key aspect of this developmental innovation concerned its potential for architectural and mechanical variation in response to environmental effects as well as optimizing hydraulic supply before the appearance of laminate leaves. Growth form diversity and its importance to past and present ecosystems are discussed in relation to both evolutionary constraints and ecological factors such as climatic change and atmospheric CO2 concentrations. We discuss how widely ranging growth forms such as climbers show a large range of developmental and phenotypic variation that has much to offer in understanding how the environment can modify plant development, particularly in terms of the bifacial vascular cambium. The broad approach we propose would benefit a wide range of studies from research into wood development to long-term ecological censuses of today's potentially changing ecosystems.
Much comparative ecophysiological research has focused on contrasting species-specific behavior or ecological strategies with regard to regulation of basic physiological processes such as transpiration, photosynthesis and growth, leading to an emphasis on divergence rather than convergence in plant functioning. This review highlights selected examples in which substantial functional convergence among taxonomically, phylogenetically and architecturally diverse species has been revealed by applying appropriate scaling factors and identifying universal constraints or trade-offs. Recent empirical and theoretical scaling models emphasize the strong role that plant size, architecture, allometry and chemistry play in constraining functional traits related to water and carbon economy and growth. Taken together, the findings summarized here strongly suggest that there are a limited number of physiological solutions to a given problem of plant adaptation to the environment. Comparative ecophysiological studies will therefore benefit from consideration of the constraints that plant anatomical, structural and chemical attributes place on physiological functioning.
Wood density is a crucial variable in carbon accounting programs of both secondary and old-growth tropical forests. It also is the best single descriptor of wood: it correlates with numerous morphological, mechanical, physiological, and ecological properties. To explore the extent to which wood density could be estimated for rare or poorly censused taxa, and possible sources of variation in this trait, we analyzed regional, taxonomic, and phylogenetic variation in wood density among 2456 tree species from Central and South America. Wood density varied over more than one order of magnitude across species, with an overall mean of 0.645 g/cm3. Our geographical analysis showed significant decreases in wood density with increasing altitude and significant differences among low-altitude geographical regions: wet forests of Central America and western Amazonia have significantly lower mean wood density than dry forests of Central and South America, eastern and central Amazonian forests, and the Atlantic forests of Brazil; and eastern Amazonian forests have lower wood densities than the dry forests and the Atlantic forest. A nested analysis of variance showed that 74% of the species-level wood density variation was explained at the genus level, 34% at the Angiosperm Phylogeny Group (APG) family level, and 19% at the APG order level. This indicates that genus-level means give reliable approximations of values of species, except in a few hypervariable genera. We also studied which evolutionary shifts in wood density occurred in the phylogeny of seed plants using a composite phylogenetic tree. Major changes were observed at deep nodes (Eurosid 1), and also in more recent divergences (for instance in the Rhamnoids, Simaroubaceae, and Anacardiaceae). Our unprecedented wood density data set yields consistent guidelines for estimating wood densities when species-level information is lacking and should significantly reduce error in Central and South American carbon accounting programs.
Conservation assessment of the terrestrial ecoregions of Latin America and the Caribbean. International Bank for Reconstruction and Development
- E Dinerstein
- D M Olson
- D J Graham
- A L Webster
- S A Primm
Dinerstein, E., Olson, D.M., Graham, D.J., Webster, A.L., Primm, S.A., 1995. Conservation
assessment of the terrestrial ecoregions of Latin America and the Caribbean. International Bank for Reconstruction and Development, Washington, DC (United States).
Confronting a biome crisis: global disparities of habitat loss and protection
- J M Hoekstra
- T M Boucher
- T H Ricketts
- C Roberts
Hoekstra, J.M., Boucher, T.M., Ricketts, T.H., Roberts, C., 2005. Confronting a biome crisis: global disparities of habitat loss and protection. Ecol. Lett. 8 (1), 23-29.
Working Group I Contribution to the Fifth Assessment Report of the Intergovernamental Panel of Climate Change
IPCC, 2014. Observations: Atmosphere and Surface, Climate Change 2013: The Physical
Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernamental Panel of Climate Change. Cambridge University Press, New York,
pp. 1535.