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Aim To develop an integrative framework to evaluate variation in aboveground carbon storage ( AGC). A model that can be applied to understand and predict how global-change drivers influence tropical carbon sinks. Location Old-growth tropical forests world-wide. Methods Using structural equation modelling ( SEM), we propose an a priori model to evaluate the direct and indirect effects of climate, stand variables (basal area, tree diameter and wood density at plot level) and liana abundance on AGC. Our model indicated that stand variables increased AGC while liana abundance decreased AGC indirectly via negative effects on stand variables. We used a multigroup SEM to test the generality of our framework using a standardized dataset of 145 plots (0.1 ha) in dry, moist and wet tropical forests. Results Our model explained over 85% variation in AGC and showed a positive and consistent relationship between stand variables and AGC across forests types. The effects of climate on AGC were indirect rather than direct, with negative effects of temperature in all forests. Liana abundance reduced tree diameter and basal area in moist forests, but did not affect AGC in wet or dry forests. Main conclusions Our results suggest that climate affects AGC indirectly, via its direct influence on stand variables and liana abundance. The effects of lianas on AGC result from reductions in stand variables and are as important as climate for moist forests, which harbour the greatest tropical carbon pools. Our model was consistent across forest types. This highlights the usefulness of an integrative framework to improve predictions of the effects of drivers of global change on tropical carbon sinks. [ABSTRACT FROM AUTHOR]

Abstract: Variation in the leaf optical properties imposed by variation in genetics and location has been addressed in recent literature, but those stemming from forest seasonality and phenology have been less well explored. Here, we explore the effect of inter-seasonal spectral variation on the potential for automated classification methods to accurately discern species of trees and lianas from high-resolution spectral data collected at the leaf level at two tropical forest sites. Through the application of a set of data reduction techniques and classification methods to leaf-level spectral data collected at both rainforest and seasonally dry sites in Panama, we found that in all cases the structure and organization of spectrally-derived taxonomies varied substantially between seasons. Using principle component analysis and a non-parametric classifier, we found at both sites that species-level classification was possible with a high level of accuracy within a given season. Classification across season was not, however, with accuracy dropping on average by a factor of 10. This study represents one of the first systematic investigations of leaf-level spectro-temporal variability, an appreciation for which is crucial to the advancement of species classification methods, with broad applications within the environmental sciences. [Copyright &y& Elsevier]

Abstract: Research suggests that secondary forest structure and composition subsequent to human disturbance could be related to wind or vertebrate dependent seed dispersal mechanisms. This paper examines the capability of a waveform LiDAR system (LVIS: LiDAR Vegetation Imaging System) to detect the location of wind-dispersed or vertebrate-dispersed forest patches in a mosaic of a secondary Tropical Dry Forest in the Santa Rosa National Park, Guanacaste, Costa Rica. Canopy-height estimations derived from LVIS data were used to identify and locate two types of dispersal-dependent arrangements of canopy heights: flat-topped (windborne seed dispersed) or dome-shaped (vertebrate-dispersed) fragments. Following identification, a Ripley''s K indicator was used to compare the locations for each confirmed canopy type to those reported in existing maps. Results indicated that dome-shaped patches tended to be arranged in clusters at the middle of former pastures (far from older forests), and that flat-topped patches tended to be located adjacent to older forests, forming extensions from the old growth patches and at the downwind side of the slope. Such characteristics agree with the theoretical observation of the spatial configuration of vertebrate- and wind-dispersed fragments reported in the study site. Our findings demonstrate that processes controlling forest regeneration in the TDF can be successfully identified through LiDAR data. [Copyright &y& Elsevier]

Abstract: Increasing dominance of lianas in many tropical forests is considered a fingerprint of global environmental change. Despite the key role they play in ecosystem functioning, lianas remain one of the least studied life forms in tropical environments. This paper contrasts leaf traits and spectral properties (400–1100 nm) of liana and tree communities from a tropical dry forest and a tropical rainforest in Panama, Central America. Differences between lianas and tree leaf traits were analyzed using spectroscopy, leaf histology and pigment extractions. Results from this study indicate that many of the biochemical, structural, and optical properties of lianas and trees are different in the dry forest site but not in rainforest sites. In the dry forest site, liana leaves exhibited significantly lower chlorophyll and carotenoid contents and were thinner than the leaves of their host trees. Specific leaf area, dry to fresh mass ratio, and mean water content of liana leaves were significantly higher when compared with tree leaves. The differences observed in the tropical dry forest site indicate that lianas may have a higher rate of resource acquisition and usage, whereas trees tend to conserve acquired resources. We suggest that our results may be indicative of the presence of a liana syndrome related to water availability and thus best exhibited in tropical dry forests. Our findings have important implications for using remote sensing to accurately map the distribution of liana communities at regional scales and for the continued expansion of lianas in tropical environments as a result of global change. [Copyright &y& Elsevier]

We evaluated the intention, implementation, and impact of Costa Rica's program of payments for environmental services (PSA), which was established in the late 1990s. Payments are given to private landowners who own land in forest areas in recognition of the ecosystem services their land provides. To characterize the distribution of PSA in Costa Rica, we combined remote sensing with geographic information system databases and then used econometrics to explore the impacts of payments on deforestation. Payments were distributed broadly across ecological and socioeconomic gradients, but the 1997–2000 deforestation rate was not significantly lower in areas that received payments. Other successful Costa Rican conservation policies, including those prior to the PSA program, may explain the current reduction in deforestation rates. The PSA program is a major advance in the global institutionalization of ecosystem investments because few, if any, other countries have such a conservation history and because much can be learned from Costa Rica's experiences. [ABSTRACT FROM AUTHOR]

In this study, we investigated the use of Bayesian networks for inferring tropical dry forest leaf area index (LAI) from satellite imagery in dry and wet seasons. LAI was chosen as the variable of interest because leaf area is the exchange surface between the photosynthetically active component of the canopy and the atmosphere. Initial network estimates were obtained from ground truth plot data with known forest structure, LAI, and satellite reflectance in the red and near-infrared bands (as observed by the Landsat 7 Enhanced Thematic Mapper Plus sensor). We tested the performance of the Bayesian networks with scoring rules and also with confidence and surprise scores. We evaluated the networks on a per-pixel basis and created both LAI maps of the study area as well predicted the probability maps for the highest LAI states. Results not only demonstrate the predictive power of a Bayesian network but also its explanatory power which is far beyond what is typically available with current pixel classifier approaches such as spectral vegetation indices or other approaches such as neural networks. [ABSTRACT FROM AUTHOR]

Abstract: Studies of forest fragmentation in the tropics have systematically paid more attention to understanding processes contributing to the formation of landscapes that are the product of deforestation, while little or no attention has been paid to forested landscapes that are the product of secondary growth processes. In this paper, using information of forest cover from 1960 to 2000 derived from aerial photography and remote sensing data, we examine the dynamics associated with deforestation and secondary growth processes at the Chorotega region, Costa Rica. Our analysis is conducted using a comprehensive land capability map developed for the country. Our results indicate the occurrence of two well-defined land cover change processes over time. Extensive/intensive cattle ranching practices that contribute to significant forest degradation and forest cover loss characterize the first of these processes, occurring between 1960 and 1980. The second period (1980–2000) is characterized by a dynamic process of secondary forest growth resulting from a combination of internal and international market forces and conservation initiatives. Conclusions from this paper indicate that more attention needs to be paid to tropical secondary landscapes that are recuperating from years of constant degradation. This natural recovery process could be beneficial for biodiversity recovery, biological corridors and environmental services. [Copyright &y& Elsevier]

Most estimates of deforestation are derived for areas that are not intrinsically related to the causes of deforestation, making it hard to link such estimates with strategies for improved land management. In this paper a method is presented to identify local areas of high rates of deforestation within larger areas, using remote sensing and geographic information systems (GIS). These deforestation hot spots are identified using a local analysis approach, considering for every location only land cover changes taking place in the immediate vicinity, and they thus reflect local deforestation. This method has potential application in improved land policy development, land management and it could supplement land use change modeling at the landscape level. Specifically, the method could be used to undertake a risk assessment of the effectiveness of ecological corridors. The method was applied to the province of Limo´n in Costa Rica, where commercial agriculture has caused large scale deforestation. The deforestation hot spots in the period 1986–1997 that were identified with this method represent a large proportion of the total deforestation having taken place in the province, and for each of the hot spots specific drivers of deforestation could be identified. [Copyright &y& Elsevier]

Abstract:We compared deforestation rates and the extent of fragmentation inside and outside protected areas in the Sarapiquí region of Costa Rica. We determined deforestation rates using remotely sensed images with supervised classification. We georeferenced the processed images and then transformed them to vector format for final mapping and parameter quantification. The deforestation rate in protected areas was low and declined sharply from 0.56% annually between 1976 and 1986 to 0.16% from 1991 to 1995. Outside the protected areas, the rate decreased from 3.6% in 1976–1986 to 2.8% in 1986–1991, but it increased again to 3.2% in 1991–1995. Fragmentation outside the protected areas increased considerably: the number of patches increased from 537 in 1976 to 1231 in 1996, while during the same period the average size of patches decreased from 0.95 to 0.25 km2. Forest landscapes in the Sarapiquí region are likely to lose considerable biodiversity because of the past forest loss and fragmentation even without further increases in deforestation and fragmentation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Low-cloud cover in cloud forests is declining. • Low-cloud trends over 23 years in 521 cloud forests were evaluated. • Seventy percent of the cloud forests experienced a decrease in low-clouds. • Cloud forests experience steeper declines in low-clouds than in tropical landmasses. • Low-cloud trends indicate potential threats to species and ecosystem services. Clouds are critical to the biodiversity and function of Tropical Montane Cloud Forests (TMCF) as they control water regimes and sunlight that can be perceived by plants. These ecosystems provide a key role in ecosystem services to humanity and are considered hotspots of endemism, given that the number of species is restricted to their microclimates. The cloudiness in these ecosystems is projected to decline owing to global warming, but recent temporal trends remain unclear. Here, we evaluated trends in low-cloud fractions (CF) (e.g., the proportion of an area covered by low-cloud) and other Essential Climatic Variables (ECV) (e.g., surface temperature, pressure, soil moisture, and precipitation) for 521 sites worldwide with TMFCs from 1997 to 2020. We hypothesize that recent traces of global warming over the last few decades have led to decreases in CF on TMCFs. The previous was also assessed globally and among biogeographic realms to identify regional trends. We calculated trends by aggregating hourly observations from ERA5 reanalysis and CHIRPS into annual averages and then using linear regressions to calculate slopes (i.e., rate of change) (Δ, year−1). Our results suggest that CF trends at the TMCFs range between −64.7×10−4 and 51.4×10−4 CF year−1, revealing that 70 % of the assessed sites have experienced reductions in CF. Declines in low-clouds in these ecosystems are 253 % more severe than tropical landmasses when peak values of density distribution are compared (TMCFs: −7.8×10−4 CF year−1; tropical landmasses −2.3×10−4 CF year−1). Despite this, CF trends differ among biogeographic realms, as those TMCFs from the Neotropics and Indomalayan realms have the most pronounced declines. Decreases in CF were also associated with increases in surface temperature and pressure and decreases in soil moisture, revealing that the TMCF's climate is changing to warmer environments. These climatic shifts may represent imprints of global change on TMCFs, highlighting a current threat to species and essential ecosystem services that these ecosystems provide. [ABSTRACT FROM AUTHOR]

Abstract Increases in liana abundance in tropical forests are pervasive threats to the current and future forest carbon stocks. Never before has the need been more evident for new approaches to detect the presence of liana in ecosystems, given their significance as fingerprints of global environmental change. In this study, we explore the use of longwave infrared reflectance (LWIR, 8–11 μm) as a wavelength region for the classification of liana and tree leaves and compare classification results with those obtained using visible-near infrared reflectance data (VIS-NIR, 0.45–0.95 μm). Twenty sun leaves were collected from each of 14 liana species and 21 tree species located at the canopy or forest edge (n = 700) in Santa Rosa National Park, Costa Rica. LWIR and VIS-NIR reflectance measurements were performed on these leaves using a portable calibrated Fourier Transform Infrared Spectroscopy (FTIR) Agilent ExoScan 4100 and a UniSpec spectral analysis system, respectively. The VIS-NIR and LWIR data were first resampled. Then these two spectral libraries were pre-processed for noise reduction and spectral feature enhancement resulting in three datasets for each spectral region as follows: filtered only, filtered followed by extraction of the first derivative, and continuous wavelet transformation (CWT). Data reduction was then applied to these data sets using principal components analysis (PCA). The outputs obtained from the PCA were used to conduct the supervised classification of liana and tree leaves. In total, 21 classifiers were applied to datasets of training and testing to extract the classification accuracy and agreement for liana and tree leaves. The results suggest that the classification of leaves based on LWIR data can reach accuracy values between 66 and 96% and agreement values between 32 and 92%, regardless of the type of classifier. In contrast, the classification based on VIS-NIR data shows accuracy values between 50 and 70% and agreement values between 0.01 and 40%. The highest classification rates of liana and tree leaves were obtained from datasets pre-processed using the CWT or from the extraction of the first derivative and classified using either random forest, k -nearest neighbor, or support vector machine with radial kernel. The results using the LWIR reflectance highlight the potential of this spectral region for the accurate detection of liana extent in tropical ecosystems. Future studies should consider this potential and test the regional monitoring of lianas. Highlights • Life form classification using visible-near infrared or longwave infrared spectra. • Four pre-processing approaches and 21 classifiers were evaluated. • Best classification of life forms obtained with longwave infrared reflectance. • Best discrimination by pre-processing with continuous wavelet transformation. • Radial kernel SVM and random forest are of the most promising classifiers. [ABSTRACT FROM AUTHOR]

The article focuses on the need for integrated research for a sustainable future in tropical dry forests. Tropical rain forests have received little or no attention compared with the tropical rainforests. The lack of conservation effort in tropical dry forests is reflected in the fact that few national parks and biological reserves protect and preserve their natural richness. There are only a handful of real biological research stations with a mandate to bridge the gap between ecology and conservation biology in these ecosystems.

Premise of the study: The function of most ecosystems has been altered by human activities. To asses the recovery of plant communities, we must evaluate the recovery of plant functional traits. The seasonally dry tropical forest (SDTF), a highly threatened ecosystem, is assumed to recover relatively quickly from disturbance, but an integrated evaluation of recovery in floristic, structural, and functional terms has not been performed. In this study we aimed to (a) compare SDTF plant functional, floristic, and structural change along succession: (b) identify tree functional groups; and (c) explore the spectral properties of different successional stages. Methods: Across a SDTF successional gradient, we evaluated the change of species composition, vegetation structure, and leaf spectral reflectance and functional traits (related to water use, light acquisition, nutrient conservation, and CO2 acquisition) of 25 abundant tree species. Key results: A complete recovery of SDTF takes longer than the time period inferred from floristic or structural data. Plant functional traits changed along succession from those that maximize photoprotection and heat dissipation in early succession, where temperature is an environmental constraint, to those that enhance light acquisition in late succession, where light may be limiting. A spectral indicator of plant photosynthetic performance (photochemical reflectance index) discriminated between early and late succession. This constitutes a foundation for further exploration of remote sensing technologies for studying tropical succession. Conclusions: A functional approach should be incorporated as a regular descriptor of forest succession because it provides a richer understanding of vegetation dynamics than is offered by either the floristic or structural approach alone. [ABSTRACT FROM AUTHOR]

Despite centuries of research addressing amber and its various inclusions, relatively little is known about the specific events having stimulated the production of geologically relevant volumes of plant resin, ultimately yielding amber deposits. Although numerous hypotheses have invoked the role of insects, to date these have proven difficult to test. Here, we use the current mountain pine beetle outbreak in western Canada as an analogy for the effects of infestation on the stable isotopic composition of carbon in resins. We show that infestation results in a rapid (approx. 1 year) 13C enrichment of fresh lodgepole pine resins, in a pattern directly comparable with that observed in resins collected from uninfested trees subjected to water stress. Furthermore, resin isotopic values are shown to track both the progression of infestation and instances of recovery. These findings can be extended to fossil resins, including Miocene amber from the Dominican Republic and Late Cretaceous New Jersey amber, revealing similar carbon-isotopic patterns between visually clean ambers and those associated with the attack of wood-boring insects. Plant exudate δ13C values constitute a sensitive monitor of ecological stress in both modern and ancient forest ecosystems, and provide considerable insight concerning the genesis of amber in the geological record. [ABSTRACT FROM AUTHOR]

Initiated in 1984, the Committee Earth Observing Satellites' Working Group on Calibration and Validation (CEOS WGCV) pursues activities to coordinate, standardize and advance calibration and validation of civilian satellites and their data. One subgroup of CEOS WGCV, Land Product Validation (LPV), was established in 2000 to define standard validation guidelines and protocols and to foster data and information exchange relevant to the validation of land products. Since then, a number of leaf area index (LAI) products have become available to the science community at both global and regional extents. Having multiple global LAI products and multiple, disparate validation activities related to these products presents the opportunity to realize efficiency through international collaboration. So the LPV subgroup established an international LAI intercomparison validation activity. This paper describes the main components of this international validation effort. The paper documents the current participants, their ground LAI measurements and scaling techniques, and the metadata and infrastructure established to share data. The paper concludes by describing plans for sharing both field data and high-resolution LAI products from each site. Many considerations of this global LAI intercomparison can apply to other products, and this paper presents a framework for such collaboration. [ABSTRACT FROM AUTHOR]

As the Earth warms, many species are likely to disappear, often because of changing disease dynamics. Here we show that a recent mass extinction associated with pathogen outbreaks is tied to global warming. Seventeen years ago, in the mountains of Costa Rica, the Monteverde harlequin frog (Atelopus sp.) vanished along with the golden toad (Bufo periglenes). An estimated 67% of the 110 or so species of Atelopus, which are endemic to the American tropics, have met the same fate, and a pathogenic chytrid fungus (Batrachochytrium dendrobatidis) is implicated. Analysing the timing of losses in relation to changes in sea surface and air temperatures, we conclude with ‘very high confidence’ (> 99%, following the Intergovernmental Panel on Climate Change, IPCC) that large-scale warming is a key factor in the disappearances. We propose that temperatures at many highland localities are shifting towards the growth optimum of Batrachochytrium, thus encouraging outbreaks. With climate change promoting infectious disease and eroding biodiversity, the urgency of reducing greenhouse-gas concentrations is now undeniable. [ABSTRACT FROM AUTHOR]

• Corticolous lichen classification using visible-near infrared spectra. • Linear spectral mixing between lichen and bark was evaluated. • Overall lichen signatures tend to present low spectral bark mixing. • Lichen classification is more accurate at higher, rather than lower taxonomic ranks. • Linear discriminant analysis presents the highest performance classifying species. The optical properties of lichens have been traditionally explored in the context of geological mapping where the encrustation of lichens on rocks may influence the detection of minerals of interest. As of today, few studies have looked into the potential of using the optical properties of lichens to classify them; however, none has investigated the classification of tropical lichens using spectroscopy. Here we explore the use of the visible-near infrared reflectance (VNIR; 450–1000 nm) to discriminate Neotropical corticolous lichens; the most abundant lichens in tropical forests. Reflectance measurements on lichens and their bark substrate were performed on 282 lichens samples of 32 species attached to their host's bark. Using these measurements, we first explored the degree of spectral mixing of bark and lichens by linear unmixing each lichen spectrum with the corresponding average species spectrum and bark spectrum. Overall, the results reveal that the lichen signatures tend to mask the spectral contributions from bark; however, there are some specific groups of species with high bark mixing probably due to their nature and the similarities between the lichen and bark spectra. Next, we classified the lichen spectra based on growth forms and taxonomic ranks (i.e., family, genus, species) using five machine learning classifiers. This analysis was conducted on raw reflectance spectra and wavelet-transformed spectra to enhance the absorption features prior to classification. As expected, the classification of lichen spectra is less accurate at species-specific levels, rather than higher taxonomic ranks. The wavelet transformation was found to enhance the general performance of classification; however, the accuracy of the classification depends on the classifier. Of the classifiers used in this study, linear discrimination applied to reflectance spectra presents the highest performance at the species level. Our results reveal the potential of using the VNIR reflectance as a method to discriminate Neotropical lichens. The introduced methodology may be conducted in the field, thus allowing the monitoring of lichen communities in forests; thereby furthering the current understanding of the role of lichens in ecosystem functioning. [ABSTRACT FROM AUTHOR]

Alford et al. question the working model underlying our test for a link between global warming and amphibian disappearances, and Di Rosa et al. criticize our emphasis on a single proximate agent, the chytrid fungus Batrachochytrium dendrobatidis. Both teams report key pieces of the amphibian-decline puzzle and new evidence from different parts of the world that climate change is a factor in these losses. Here we show why our working model was appropriate and highlight the complexity of the imminent threat to species survival that results as global warming conspires with various other agents. [ABSTRACT FROM AUTHOR]