Modelling Web Service Composition for Deductive Web Mining

Composition of simpler web services into custom applications is understood as promising technique for information requests in a heterogeneous and changing environment. This is also relevant for applications characterised as deductive web mining (DWM). We suggest to use problem-solving methods (PSMs) as templates for composed services. We developed a multi-dimensional, ontology-based framework, and a collection of PSMs, which enable to characterise DWM applications at an abstract level; we describe several existing applications in this framework. We show that the heterogeneity and unboundedness of the web demands for some modifications of the PSM paradigm used in the context of traditional artificial intelligence. Finally, as simple proof of concept, we simulate automated DWM service composition on a small collection of services, PSM-based templates, data objects and ontological knowledge, all implemented in Prolog

Structural changes caused by selective logging undermine the thermal buffering capacity of tropical forests

Selective logging is responsible for approximately 50 % of human-induced disturbances in tropical forests. The magnitude of disturbances from logging on the structure of forests varies widely and is associated with a multitude of impacts on the forest microclimate. However, it is still unclear how changes in the spatial arrangement of vegetation arising from selective logging affect the capacity of forests to buffer large-scale climate (i.e., macroclimate) variability. In this study, we leveraged hundreds of terrestrial LiDAR measurements across tropical forests in Malaysian Borneoto quantify the impacts of logging on canopy structural traits, using a space-for-time approach. This information was combined with locally measured microclimate temperatures of the forest understory to evaluate how logging disturbances alter the capacity of tropical forests to buffer macroclimate variability. We found that heavily logged forests were approximately 12 m shorter and had 65 % lower plant area density than unlogged forests, with most plant material allocated in the first 10 m above ground. Heavily logged forests were on average 1.5 °C warmer than unlogged forests. More strikingly, we show that subtle changes in the forest structure were sufficient to reduce the cooling capacity of forests during extremely warm days (e.g., anomalies > 2σ), while understory temperatures in heavily logged forests were often warmer than the macroclimate under the same conditions. Our results thus demonstrate that selective logging is associated with substantial changes in the fine-scale thermal regime of the understory. Hence, mitigating and managing logging disturbances will be critical for maintaining niches and thermal limits within tropical forests in the future

Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Nino

The past 40 years in Southeast Asia have seen about 50% of lowland rainforests converted to oil palm and other plantations, and much of the remaining forest heavily logged. Little is known about how fragmentation influences recovery and whether climate change will hamper restoration. Here, we use repeat airborne LiDAR surveys spanning the hot and dry 2015-16 El Nino Southern Oscillation event to measure canopy height growth across 3,300ha of regenerating tropical forests spanning a logging intensity gradient in Malaysian Borneo. We show that the drought led to increased leaf shedding and branch fall. Short forest, regenerating after heavy logging, continued to grow despite higher evaporative demand, except when it was located close to oil palm plantations. Edge effects from the plantations extended over 300 metres into the forests. Forest growth on hilltops and slopes was particularly impacted by the combination of fragmentation and drought, but even riparian forests located within 40m of oil palm plantations lost canopy height during the drought. Our results suggest that small patches of logged forest within plantation landscapes will be slow to recover, particularly as ENSO events are becoming more frequent. It is unclear whether tropical forest fragments within plantation landscapes are resilient to drought. Here the authors analyse LiDAR and ground-based data from the 2015-16 El Nino event across a logging intensity gradient in Borneo. Although regenerating forests continued to grow, canopy height near oil palm plantations decreased, and a strong edge effect extended up to at least 300m away.Peer reviewe

Extreme and Highly Heterogeneous Microclimates in Selectively Logged Tropical Forests

Microclimate within forests influences ecosystem fluxes and demographic rates. Anthropogenic disturbances, such as selective logging can affect within-forest microclimate through effects on forest structure, leading to indirect effects on forests beyond the immediate impact of logging. However, the scope and predictability of these effects remains poorly understood. Here we use a microclimate thermal proxy (sensitive to radiative, convective, and conductive heat fluxes) measured at the forest floor in three 1-ha forest plots spanning a logging intensity gradient in Malaysian Borneo. We show (1) that thermal proxy ranges and spatiotemporal heterogeneity are doubled between old growth and heavily logged forests, with extremes often exceeding 45°C, (2) that nearby weather station air temperatures provide estimates of maximum thermal proxy values that are biased down by 5–10°C, and (3) that lower canopy density, higher canopy height, and higher biomass removal are associated with higher maximum temperatures. Thus, logged forests are less buffered from regional climate change than old growth forests, and experience much higher microclimate extremes and heterogeneity. Better predicting the linkages between regional climate and its effects on within-forest microclimate will be critical for understanding the wide range of conditions experienced within tropical forests

Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data

Funding Information: This work is a product of the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk). J.A.G. was funded by the Natural Environment Research Council (NERC; NE/T011084/1 and NE/S011811/1) and the Netherlands Organisation for Scientific Research (NWO) under the Rubicon programme with project number 019.162LW.010. The traits field campaign was funded by a grant to Y.M. from the European Research Council (Advanced Grant GEM-TRAIT: 321131) under the European Union‘s Seventh Framework Programme (FP7/2007-2013), with additional support from NERC Grant NE/D014174/1 and NE/J022616/1 for traits work in Peru, NERC Grant ECOFOR (NE/K016385/1) for traits work in Santarem, NERC Grant BALI (NE/K016369/1) for plot and traits work in Malaysia and ERC Advanced Grant T-FORCES (291585) to Phillips for traits work in Australia. Plot setup in Ghana and Gabon were funded by a NERC Grant NE/I014705/1 and by the Royal Society-Leverhulme Africa Capacity Building Programme. The Malaysia campaign was also funded by NERC GrantNE/K016253/1. Plot inventories in Peru were supported by funding from the US National Science Foundation Long-Term Research in Environmental Biology program (LTREB; DEB 1754647) and the Gordon and Betty Moore Foundation Andes-Amazon Program. Plots inventories in Nova Xavantina (Brazil) were supported by the National Council for Scientific and Technological Development (CNPq), Long Term Ecological Research Program (PELD), Proc. 441244/2016-5, and the Foundation of Research Support of Mato Grosso (FAPEMAT), Project ReFlor, Proc. 589267/2016. During data collection, I.O. was supported by a Marie Curie Fellowship (FP7-PEOPLE-2012-IEF-327990). GEM trait data in Gabon was collected under authorisation to Y.M. and supported by the Gabon National Parks Agency. D.B. was funded by the Fondation Wiener-Anspach. W.D.K. acknowledges support from the Faculty Research Cluster ‘Global Ecology’ of the University of Amsterdam. M.S. was funded by a grant from the Ministry of Education, Youth and Sports of the Czech Republic (INTER-TRANSFER LTT19018). Y.M. is supported by the Jackson Foundation. We thank the two anonymous reviewers and Associate Editor G. Henebry for their insightful comments that helped improved this manuscript.Peer reviewedPostprin

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications