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Ecosystem Services (ES) study, which initially intended to capture externalities produced by economic activity, currently has been developed and expanded into numerous global frameworks. The multidimensional approach made the ES study applicable to a wide-ranging ecosystem, including peatland. While abundant research on spatial peatland ES has been carried out, only a fewest that attempted to use common drivers in deriving multiple ES. This study set out to value and map four peatland ES: provisioning, carbon regulating, water storage, and fire prevention services, using the common driver of land cover and peatland soil moisture. We exclusively apply the ES mapping concept to the status quo condition (2017), regional spatial planning (RTRW), and Indonesia’s Long Term Strategy (LTS) scenario for the peatland ecosystem unit of Gaung-Batang Tuaka KHG in Riau, Indonesia. Our results revealed provisioning services were at the highest to be produced under the RTRW scenario, particularly in the cultivation zone, with an additional USD 37.03 million in benefits for provisioning services compared to the status quo. However, the RTRW scenario failed to increase the carbon services, both in the ecological zones for cultivation and protection. For the Indonesia LTS scenario, immediate restoration using peat native commodity potentially add benefit from provisioning services amounted to USD 9.23 million while generating lower total emissions. However, spatially, negative carbon services were still dominating the study area in all three scenarios, which indicates ecosystem failure to regulate carbon. Omitting the peat subsidence factor, both RTRW and LTS scenarios are able to increase water storage services, while for the fire prevention services, changes in future rainfall due to climate change cause an increasing peatland burning area. While ecologically the LTS scenario performs the most optimum condition for both market and non-market benefit, the current system of valuing environmental benefits that neglects other essential ES beyond carbon is not aligned with the country's attempt to decarbonize the land sector. more...

Scripts and data associated with the publication "Social media and deep learning reveal specific cultural preferences for biodiversity". This repository contains a series of scripts (listed below) and key data including training weights and predictions from the beta=0.01 species interaction model and predictions from the species classification model. The prediction filescontain Flickr and iNaturalist ids which can be linked to metadata accessible through the platformAPIs. To train the human-species interaction model: 1. sample_grid.R (generate sample grid over Europe) (2.) For Flickr, we extracted metadata in Europe using the API and the sample grid coordinates* 3. inat_extract.R (extract metadata using iNaturalist API) 4. sample_inat_flickr.R (sample Flickr and iNaturalist metadata for model training, then split into train/val/test) 5. flickr_download.py (download Flickr images in sample boxes) 6. inat_download.py(download iNaturalist images in sample boxes) 7. diff_model_train.py (train the model using differentbeta coefficients) 8. diff_resnet.py (the model) 9. diff_data_loader.py (the data loader) To download Flickr and iNaturalist data for Great Britain: (10.) For Flickr, we used metadata and images downloaded in a previous study using the Flickr API* 11.inat_obs_gb.R (downloadiNaturalist metadata and add extra taxonomic information). To apply the iNaturalist species classification model: 12. inat_apply_gb.py (Flickr dataset) 13. inat_apply_gb_obs.py (iNaturalistdataset) 14. inception.py (iNaturalist model) To test, apply and integrate the predictions of the human-species interaction and species classification models: 15. predict_test.py (apply the model to the test dataset) 16. predict_gb.py (apply the model on the Flickr image dataset for Britain) 17. data_loader.py (data loader) 18. gb_metadata.R (attach species interaction model predictions to gb flickr metadata) 19. attach_species.R (attach species classification predictions to gb flickrand inaturalist metadata) 20. nat_model_stats.R (produce model accuracy results) To conduct analysis: 21. naturalist_activity.R (genus and spatial analysis of interactions on Flickr and iNaturalist) 22. biodiversity_comp.R (comparison with bird species richness and abundance) 23. species_time (comparison with threatened migratory birds) Functions: 24. functions.R (all functions) *additional scripts and data can be found here:https://doi.org/10.5281/zenodo.5534028 more...

Robust demonstration case-studies are needed to evaluatewhether improvements in ecosystem condition are translated into improvements in ecosystem services. This research is essential for effectively scaling-up nature-based solutions across Europe and providing the evidence to support transformation agendas in society and industries, and ultimately supporting the ambitions of the European Green Deal. Clear guidance and standardised indicators help monitor the impact of freshwater and wetland restoration measures on European Green Deal goals. These monitoring indicators should include environmental indicators (e.g. for biodiversity, greenhouse gas emissions and water storage capacity) as well as socio-economic indicators such as stakeholder representation, private finance mobilisation and job creation. A combined Before-After-Control-Intervention (BACI) monitoring design is recommended to provide robust evidence and attribute change to the restoration measures. Benchmark (cost or effort) and local/regional context data (e.g. land use, governance) are also needed alongside monitoring of impacts to not just measurewhathas happened at a site but to understandwhyit has happened. &nbsp more...

Background Bloodstream infections (BSIs) often lead to critical illness and death. The primary aim of this study was to determine the diagnostic accuracy of the biomarkers C-reactive protein (CRP), procalcitonin (PCT), and leukocyte count for the diagnosis of BSI in critically ill patients. Methods This was a nested case–control study based on the Procalcitonin And Survival Study (PASS) trial (n = 1200). Patients who were admitted to the intensive care unit (ICU) Results In total, there were 525 patients (n = 175 cases, 350 controls). The fixed low threshold for all 3 biomarkers (CRP = 20 mg/L; leucocytes = 10 × 109/L; PCT = 0.4 ng/mL) resulted in negative predictive values on day 1: CRP = 0.91; 95% CI, 0.75–1.00; leukocyte = 0.75; 95% CI, 0.68–0.81; PCT = 0.91; 95% CI, 0.84–0.96). Combining the 3 biomarkers yielded similar results as PCT alone (P = .5). Conclusions CRP and PCT could in most cases rule out BSI in critically ill patients. As almost no patients had low CRP and ∼20% had low PCT, a low PCT could be used, along with other information, to guide clinical decisions. more...

International audience; Over the past decade, several global maps of above-ground biomass (AGB) have been produced, but they exhibit significant differences that reduce their value for climate and carbon cycle modelling, and also for national estimates of forest carbon stocks and their changes. The number of such maps is anticipated to increase because of new satellite missions dedicated to measuring AGB. Objective and consistent methods to estimate the accuracy and uncertainty of AGB maps are therefore urgently needed. This paper develops and demonstrates a framework aimed at achieving this. The framework provides a means to compare AGB maps with AGB estimates from a global collection of National Forest Inventories and research plots that accounts for the uncertainty of plot AGB errors. This uncertainty depends strongly on plot size, and is dominated by the combined errors from tree measurements and allometric models (inter-quartile range of their standard deviation (SD) = 30–151 Mg ha−1). Estimates of sampling errors are also important, especially in the most common case where plots are smaller than map pixels (SD = 16–44 Mg ha−1). Plot uncertainty estimates are used to calculate the minimum-variance linear unbiased estimates of the mean forest AGB when averaged to 0.1∘. These are used to assess four AGB maps: Baccini (2000), GEOCARBON (2008), GlobBiomass (2010) and CCI Biomass (2017). Map bias, estimated using the differences between the plot and 0.1∘ map averages, is modelled using random forest regression driven by variables shown to affect the map estimates. The bias model is particularly sensitive to the map estimate of AGB and tree cover, and exhibits strong regional biases. Variograms indicate that AGB map errors have map-specific spatial correlation up to a range of 50–104 km, which increases the variance of spatially aggregated AGB map estimates compared to when pixel errors are independent. After bias adjustment, total pantropical AGB and its associated SD are derived for the four map epochs. This total becomes closer to the value estimated by the Forest Resources Assessment after every epoch and shows a similar decrease. The framework is applicable to both local and global-scale analysis, and is available at https://github.com/arnanaraza/PlotToMap. Our study therefore constitutes a major step towards improved AGB map validation and improvement. more...

Several million hectares of Indonesian peatlands have been converted to plantations, with oil palm being the most important plantation crop. This has contributed to the economic development of Indonesia. At the same time, it poses environmental challenges. An as yet insufficiently understood concern is that the drainage required for cultivation of peatlands causes soil subsidence. Subsidence progressively increases flood risks in plantations and will, over time, render peatlands unsuitable for cultivation since oil palm and other plantation crops are sensitive to waterlogged conditions. This paper assesses subsidence and flood risk in the main peatlands of Sumatra, and examines when peatlands will become unfit for crop production. We show that, under current management, 21% of oil palm production will be lost due to flooding, and 17% of oil palm plantations in East Sumatran peatlands will become unfit for agriculture in the coming 30 years. Over time, all peatlands will be lost for agriculture. With reduced drainage, these effects can be postponed, but not avoided. In the medium and long term, the only sustainable and economically profitable option for Indonesia is to use peatlands for no-drainage land use including crops that do not require drainage (paludiculture). This also strongly reduces the carbon footprint of cultivating in peatlands. Profitable no-drainage land use options have been tested, but their scaling up urgently needs further support from the government, industry, and international donors to materialize. more...

The conversion of Indonesian tropical peatlands has been associated with the recurring problems of peatland fires and smoke affecting humans and the environment. Yet, the local government and public in the affected areas have paid little attention to the impacts and costs of the poor air quality on human health. This study aims to analyse the long-term health impacts of the peat smoke exposure to the local populations. We applied the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to determine the smoke dispersion and the associated PM2.5 concentrations of the resulted plumes from the fire hotspots in the deep and shallow peatlands in Central Kalimantan, Indonesia, that occurred during a 5-year period (2011–2015). We subsequently quantified the long-term health impacts of PM2.5 on the local people down to the village level based on the human health risk assessment approach. Our study shows that the average increase in the annual mean PM2.5 concentration due to peatland fires in Central Kalimantan was 26 μg/m3 which is more than twice the recommended value of the World Health Organisation Air Quality Guidelines. This increase in PM2.5 leads to increased occurrence of a range of air pollution–related diseases and premature mortality. The number of premature mortality cases can be estimated at 648 cases per year (26 mortality cases per 100,000 population) among others due to chronic respiratory, cardiovascular and lung cancer. Our results shed further light on the long-term health impacts of peatland fires in Indonesia and the importance of sustainable peatland management. more...

To better manage our environment, systematic information is needed on the state of ecosystems and their interactions with society. Efforts have been undertaken to design monitoring and recording systems, notably the United Nations System of Environmental-Economic Accounting (SEEA). However, the diverse conceptualizations and applications on ecosystem accounting found the scientific literature have never been assessed in a systematic way. Here, a systematic literature review on ecosystem accounting, i.e. natural capital accounting approaches that focus on ecosystems, is conducted to detail the evolving trends in concepts, methodologies, and applications, and to identify main gaps and challenges for future work. Results yielded 378 scientific articles published between 1990 and 2021. This literature is diverse in terms of frameworks developed, ecosystems studied, valuation methods used, and accounts produced. Among the eleven ecosystem accounting frameworks identified, the SEEA is the most widely used. This literature is moving from focusing on conceptual elements towards addressing implementation issues. It is primarily conducted in European countries, on forest ecosystems, using biophysical methods and monetary valuation methods consistent with exchange values to produce accounts. The gaps that should be the focus of future work include the issue of implementation: methodologies (artificial Intelligence technologies and economic valuation), data, for instance making better use of remote sensing images, collaborations, and supporting the use of ecosystem accounts in decision-making. more...

Like many other tropical countries, the Philippines has suffered from decades of deforestation and forest degradation during and even after the logging era. Several open access Earth Observation (EO) products are increasingly being used for deforestation analysis in support of national and international initiatives and policymaking on forest conservation and management. Using a combination of annual forest loss and near-real time forest disturbance products, we provide a comprehensive analysis of the deforestation events in three forest frontiers of the Philippines. A space-time pattern mining approach was used to map quarterly deforestation hotspots at 1 km pixel size (100 hectares), where hotspots are classified according to the spatial and temporal variability of the 2000–2020 deforestation in the study area. Our results revealed that 79–81% of the hotspots overlap with primary forests and 27–29% are inside the state-declared protected areas. The intra-annual analysis of deforestation in 2020 revealed an alarming trend, where most deforestation occurred between the 1st and 2nd quarter (92–94% in hotspot forests, 87–89% in non-hotspot forests), highly overlapping within the slash-and-burn farming season. We also found “new” hotspots (2020) formed mostly from landslide scars and partly from selective logging, the latter is believed to be underestimated. Our study paves the way for rapid and regular assessment of the country’s deforestation, useful for the respective environmental institutions who convene several times a year. Moreover, our findings assert the imperative of alternative livelihoods to upland farmers, efficient forest protection activities, and even the mitigation of landslide risks. more...

Peatland plays a pivotal role in providing natural resource production and environmental services for human welfare. However, many studies have mentioned the impact of dryland cultivation in peatland on the shifting carbon balance in the ecosystem that clearly will alter the interaction of these two ecosystem services. The goal of this study, conducted under the framework of the System of Environmental-Economic Accounting (SEEA) framework, was to monetary value the ecosystem services (ES) of provisioning and carbon regulating services of the Gaung-Batang Tuaka Peat Hydrological Unit (KHG). We focused on KHG in response to Regulation No.57/2016, which highlights ecosystem boundary as a new basis for peatland management. Under the SEEA framework, ecosystem services become a benefit when utilized by ecosystem beneficiaries. In this case, provisioning services will be valued only for cultivated land, while carbon services calculated for the entire study area (global beneficiaries). Our study showed that the provisioning services and carbon services are under the trade-off condition, where the monetary value of provisioning services increased at a slower rate (0.50 million USD annually) than the monetary loss of the benefit of carbon services (5.28 million USD annually), greatly exceeded the monetary value of provisioning services. We highlight two main strategies to increase the monetary value of the KHG towards a synergy condition, namely increased value-added by reducing the productivity gap among ES beneficiaries and large-scale adoption of a profitable cultivation system with minimum peat disturbance. The main enablers required include financing access and incentives (e.g., reduce tax) and disincentives to allow for peat-adaptive commodities to compete with dryland commodities in the future market., ecosystem services; monetary value; peatland management; peat hydrological unit; Riau more...

Scripts and data associated with the publication "Social media and deep learning capture the aesthetic quality of the landscape". If making use of this dataset in your research, we would appreciate a reference to the following paper: Havinga, I, Marcos, D., Bogaart, P. W., Hein, L., Tuia, D. (2021). Social media and deep learning capture the aesthetic quality of the landscape. Scientific Reports. DOI: https://doi.org/10.1038/s41598-021-99282-0. This repository contains a series of scripts (listed below) and key data which will allow reproducibility from different stages of the research. All data used in this study are open-source and publicly available. To generate the environmental indicator variables and split the study area into training, validation and test sets: 1. extract_dem.R 2. extract_poi.R 3. ind_generation.R 4. ind_reduction.R 5. son_split.R 6. ind_selection.R To collect images from SoN and train the SoN ResNet: 7. son_scrape.py 8. son_split.py 9. son_dataloader.py 10. son_resnet_train.py 11. son_resnet_test.py To download the Flickr metadata: 12. gb_search_bboxs.R 13. flickr_search.py To apply the deep learning models: 14. cell_imgs.R 15. cnn_results.py To generate the final sets of spatial models at 5km: 16. pud_models.R 17. imgs_models.R To generate predictions at 500m: 18. ldn_zoom.R 19. lake_zoom.R To analyse user activity: 19. user_activity.R To analyse changes over time in national park areas: 20. extract_mod10cm.R 21. national_park_time.R Figures: 22. figures.R Functions: 23. functions.R Elevation data produced using the EU DEM (source) with European funding. Ecosystem type map (source) copyright European Environment Agency (EEA). Historic POI data from OSM © OpenStreetMap contributors (cc-by-sa). more...

Maps of above-ground biomass (AGB) using remote sensing (RS) are valuable to countries like the Philippines for multi-purposes including national greenhouse gas reporting, carbon accounting and even reforestation monitoring. As RS data increase, both optical and radar satellite data have been combined to produce higher quality AGB maps, rather than using individual satellites alone. AGB is then produced after establishing a statistical relationship between combined RS data and plot-based AGB often using machine learning (ML) regression tasks. Here we model a country-wide AGB map of the Philippines while assessing the effects of combining freely and easily accessible satellite data as AGB predictors: Landsat-8 (optical RS), and ALOS-2 PALSAR-2 and Sentinel-1 (radar RS). Using annual composites of each satellite data along with other ecological variables and the National Forest Inventory (NFI) 2014–2015, we trained, cross-validated and compared ML models: Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN). Model evaluation results were found similar between RF and SVM models i.e., 63 and 65 Mg ha−1 RMSE respectively; while the NN model showed the lowest accuracy i.e., $\text{RMSE} =84$ Mg ha−1, likely a consequence of limited training data. The effect of combining Landsat-8 and ALOS-2 PALSAR-2 was indicated by better AGB predictions in the upland forests, while the inclusion of Sentinel-1 improved the AGB estimates in the agricultural lowland. Using the three satellite data and an RF model not only provides the map with the least bias, but also complements the ridge-to-reef topography of the country where woody vegetations exist from forested mountains down to agricultural lands and mangroves. This study is helpful also to other tropical countries in addressing the problem on expensive forest inventories as well as inaccessible forest lands and conflict areas, while providing spatially explicit and reliable AGB estimates. more...

Streamflow predictions in ungauged basins (PUB) has been geared towards data-driven methods, including the use of machine learning methods such as random forest (RF). Such methods are applied in PUB regionalization or the transfer of a streamflow model from gauged to ungauged (sub) basins or watersheds after grouping watersheds on similarity rules. Regionalized streamflow models are needed for tropical-mountainous regions like Luzon, Philippines - where gauged data is limited - but demands on streamflow modelling for water resources accounting and management are high. In 21 watersheds in Luzon, we “regionalize” RF streamflow models after grouping watersheds based on: a principal components analysis (PCA-clustered), by major river basins (basin-clustered), whole study area scale (one-clustered). Another method without watershed grouping (watershed-level) was also included and inter-compared. Among the four methods, goodness-of-fit evaluations revealed that PCA-clustered method was higher by at most 0.35 coefficient of determination R2 and 0.31 nash-sutcliffe efficiency NSE, and the least bias in 8 of 12 monthly flows. These are attributed to the added-value of homogeneous watershed grouping, reflected by higher importance (to RF models), of static covariates from open and high-resolution data. Normalized errors from monthly streamflow showed a clear bias (least with the PCA-clustered metohd), linked to season and water management practices in the study area. Ungauged watersheds in the Philippines can effectively use streamflow models from gauged watersheds if they belong to the same cluster.Key PointsUngauged sub-basins (watersheds) can effectively use RF streamflow models from gauged watersheds if both belong to the same cluster.Biophysical data from high-resolution open data are valuable: as basis for watershed clustering and as streamflow predictors to RF models.The predicted streamflow from the RF models reflects seasonal deviations in streamflow caused by natural and man-made water regulation more...

Ecosystems contribute to economic development through the supply of ecosystem services such as food and fresh water. Information on ecosystems and their services is required to support policy making, but this information is not captured in economic statistics. Ecosystem accounting has been developed to integrate ecosystems and ecosystem services into national accounts. Ecosystem accounting includes the compilation of an ecosystem services supply and use account, which reflects actual flows of ecosystem services, and the ecosystem capacity account, which reflects the capacity of ecosystems to sustainably supply ecosystem services. A capacity assessment requires detailed data on ecosystem processes, which are often not available over large scales. In this study, we examined how net primary productivity derived from remote sensing can be used as an indicator to assess changes in the capacity of ecosystems to supply services. We examine the spatial and temporal patterns in this capacity for the Orinoco river basin from 2001 to 2014. Specifically, we analyze the capacity of six types of ecosystems to supply timber, pastures for grazing cattle, oil palm fresh fruit bunches and to sequester carbon. We compared ecosystem capacities with the level of ecosystem service supply to assess a sustainable use of ecosystems. Our study provides insights on how the capacity of ecosystems can be quantified using remote sensing data in the context of ecosystem accounting. Ecosystem capacity indicators indicate ecosystems change and harvesting-regeneration patterns which are important for the design and monitoring of sustainable management regimes for ecosystems. more...

Understanding and monitoring pressures on ecosystems and their consequences for ecosystem services (ES) is essential for management decisions and verification of progress towards national and international policies (e.g. Aichi Biodiversity Targets, Sustainable Development Goals). Remote sensing (RS) offers a unique capability to assess ES systematically and regularly across spatial and temporal scales. We aim to evaluate the benefits of RS to monitor spatio-temporal variations of ES by assessing several ES in Switzerland between 2004 and 2014. We coupled mechanistic ES models and RS data to estimate time series of three regulating (i.e. carbon dioxide regulation (CO₂R), soil erosion prevention (SEP), and air quality regulation (AQR)) and one cultural ES (re- creational hiking (RH)). The resulting ES were used to assess spatial and temporal changes, trade-offs and sy- nergies of ES potential supply and flow in Switzerland between 2004 and 2014. Resulting ES trends showed diverse spatial patterns across Switzerland with largest changes in CO₂R and AQR. ES interactions revealed a scale and elevation dependency. We identified weak to strong synergies between all ES combinations except for trade-offs between CO₂R–AQR and AQR–RH at Swiss scale. Spatially, all ES interactions revealed a hetero- geneous mix of synergies and trade-offs within Switzerland. Our results demonstrate the strength of RS for systematic and regular spatio-temporal ES monitoring and contribute insights to the large potential of RS, which will be extended with future Earth observation missions. Derived spatially explicit ES information will facilitate decision-making in landscape planning and conservation and will allow examining progress towards environmental policies. more...

Economic development has increased pressures on natural resources during the last decades. The concept of planetary boundaries has been developed to propose limits on human activities based on earth processes and ecological thresholds. However, this concept was not developed to downscale planetary boundaries to sub-global level. The absence of boundaries at sub-global levels constrains the use of the concept in environmental governance and natural resource management, because decisions are typically taken at these levels. Decisions at the national level are currently supported, among others, by statistical frameworks in particular the System of National Accounts. However, statistical frameworks were not developed to compile environmental information, hindering environmental decision making. Our study examines if and how ecosystem accounting can be used in combination with the concept of planetary boundaries in guiding human activities at the level of a river basin. We assess the applicability of both frameworks for natural resource management in the Orinoco river basin, based on adaptive management components. Our analysis indicates that differences in the purpose of analysis, information provided, and methods constrain the potential integration of both frameworks. Nevertheless, the way both frameworks conceptualize the social system and the interactions between social and ecological systems can facilitate translating planetary boundaries into indicators considered in ecosystem accounting. The information recorded in national ecosystem accounts can support establishing ecological thresholds and, more fundamentally, to relate ecological thresholds to human impacts on ecosystem condition. Capitalizing on these synergies requires further exchange of experiences between the communities working on ecosystem accounting and planetary boundaries. more...

Large areas of Indonesian peatlands have been converted for agricultural and plantation forest purposes. This requires draining with associated CO2 emissions and fire risks. In order to identify alternative management regimes for peatlands, it is important to understand the sustainability of different peatland uses as well as the economic benefits peatlands supply under different land uses. This study explores the key sustainability issues in Indonesian peatlands, the ecosystem services supplied by peatlands, and potential responses to promote more sustainable peatland use. A literature review and spatial analysis were conducted. Based on predominantly government data, we estimate the amount of Indonesian peatlands that has been converted between 2000 and 2014. We quantify increases in oil palm and plantation forest crop production in this period, and we analyse key sustainability issues, i.e. peat fires and smoke-haze, soil subsidence and flood risk, CO2 emissions, loss of habitat (in protected areas), and social conflicts that influence sustainability of Indonesian peatlands management. Among others we show that CO2 emissions from peatlands in Indonesia can be estimated at between 350 and 400 million ton CO2 per year, and that encroachment of oil palm and plantation forestry (acacia, rubber) has taken place on 28% of protected areas. However, as we examine, the uncertainties involved are substantial. Based on our findings, we distil several implications for the management of the peatlands. more...

Reversing the ongoing degradation of the planet's ecosystems requires timely and detailed monitoring of ecosystem change and uses. Yet, the System of National Accounts (SNA), first developed in response to the economic crisis of the 1930s and used by statistical offices worldwide to record economic activity (for example, production, consumption, and asset accumulation), does not make explicit either inputs from the environment to the economy or the cost of environmental degradation (1, 2). Experimental Ecosystem Accounting (EEA), part of the System of Environmental-Economic Accounting (SEEA), has been developed to monitor and report on ecosystem change and use, using the same accounting approach, concepts, and classifications as the SNA (3). The EEA is part of the statistical community's response to move SNA measurement “beyond gross domestic product (GDP).” With the first generation of ecosystem accounts now published in 24 countries, and with a push to finalize a United Nations (UN) statistical standard for ecosystem accounting by 2021, we highlight key advances, challenges, and opportunities. more...

The current drainage-based peatland management systems in Indonesia result in high fire risks, soil subsidence and CO2emissions. This study aims to assess different alternatives of peatland crops in order to help prevent further degradation of peatlands in Indonesia. We focus on tropical peatland crops that provide food and that are of particular interest to smallholders. We compare various peatland food crops that are commonly grown with no drainage (paludiculture) or drainage below 50 cm in our study area, Central Kalimantan, Indonesia in terms of sustainability, profitability, scalability of the market and acceptability to farmers. Our results show that sago (Metroxylon sagu), banana (Musa paradisiaca) and pineapple (Ananas comosus) followed by water spinach/kangkong (Ipomoea aquatica), kelakai/edible fern (Stenochlaena palustris), illipe nut/tengkawang (Shoreaspp.), dragon fruit (Hylocereus undatus), mangosteen (Garcinia mangostana) and sweet melon/melon (Cucumis melo) are the best options based on the aggregated scores for these criteria (but precaution should be taken when planting crops that require low drainage). Sago palm and illipe nut have the highest scores for both sustainability and scalability of market, whereas banana, pineapple and sweet melon have the highest scores in term of the scalability of market and acceptability to farmers. We also address key opportunities and bottlenecks for the development of paludiculture food crops and present recommendations for the implementation of paludiculture in Indonesian peatlands. more...

Cultural ecosystem services (CES) are some of the most valuable contributions of ecosystems to human well-being. Nevertheless, these services are often underrepresented in ecosystem service assessments. Defining CES for the purposes of spatial quantification has been challenging because it has been difficult to spatially model CES. However, rapid increases in mobile network connectivity and the use of social media have generated huge amounts of crowdsourced data. This offers an opportunity to define and spatially quantify CES. We inventoried established CES conceptualisations and sources of crowdsourced data to propose a CES definition and typology for spatial quantification. Furthermore, we present the results of three spatial models employing crowdsourced data to measure CES on Texel, a coastal island in the Netherlands. Defining CES as information-flows best enables service quantification. A general typology of eight services is proposed. The spatial models produced distributions consistent with known areas of cultural importance on Texel. However, user representativeness and measurement uncertainties affect our results. Ethical considerations must also be taken into account. Still, crowdsourced data is a valuable source of information to define and model CES due to the level of detail available. This can encourage the representation of CES in ecosystem service assessments. more...

The Government of Indonesia has published a number of policies and regulations to better manage its vast amount of tropical peatland, yet the degradation and conversion of Indonesian peatlands still continues. This paper analyses the institutional fit between Indonesian regulations related to peatland use and the characteristics of peatland users. We reviewed Indonesian legal policies and regulations on peatland use and management and conducted questionnaires and interviews with peatland users and policy makers in order to understand their practices and incentives in relation to the implementation of the four main peatland regulations. We focus on two provinces with large peatland areas: Jambi and Central Kalimantan. Using a framework for assessing the degrees of fit between the rule creators and adopters for peatland management, this paper shows that the degree of technical, political, and cultural fit of Indonesian peatland regulations can be classified as low to moderate. The paper shows that many peatland users are insufficiently aware of peatland regulations. The lack of socialisation on the contents of the regulations and the alternatives for peatland best practices, together with the lack of field monitoring and law enforcement are the important causes of non-compliance with peatland regulations. However, there are ongoing processes of fitting visible that are largely driven by the local government and NGOs. We discuss the degrees of fit and present some lessons for increasing the degree of fit for peatland regulations. more...

Payments for ecosystem services (PES) have been developed as a policy instrument to help safeguard the contributions of ecosystems to human well-being. A critical measure of a programme’s effectiveness is whether it is generating an additional supply of ecosystem services (ES). So far, there has been limited analysis of PES programmes based on the actual supply of ES. In line with ecosystem accounting principles, we spatially quantified three ES recognised by Costa Rica’s Pago de Servicios Ambientales (PSA) programme: carbon storage, soil erosion control and habitat suitability for biodiversity as a cultural ES. We used the machine learning algorithm random forest to model carbon storage, the Revised Universal Soil Loss Equation (RUSLE) to model soil erosion control and Maxent to model habitat suitability. The additional effect of the PSA programme on carbon storage was examined using linear regression. Forested land was found to store 235.3 Mt of carbon, control for 148 Mt yr−1 of soil erosion and contain 762,891 ha of suitable habitat for three iconic but threatened species. PSA areas enrolled in the programme in both 2011 and 2013 were found to store an additional 9 tonC ha−1 on average. As well as enabling a direct quantification of additionality, spatial distribution analysis can help administrators target high-value areas, confirm the conditional supply of ES and support the monetary valuation of ES. Ultimately, this can help improve the social efficiency of payments by enabling a comparison of societal costs and benefits. more...