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As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of 'living in harmony with nature'1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management3. Ecosystems vary in their biota4, service provision5 and relative exposure to risks6, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth's ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework.

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Ecological models used to forecast range change (range change models; RCM) have recently diversified to account for a greater number of ecological and observational processes in pursuit of more accurate and realistic predictions. Theory suggests that process‐explicit RCMs should generate more robust forecasts, particularly under novel environmental conditions. RCMs accounting for processes are generally more complex and data hungry, and so, require extra effort to build. Thus, it is necessary to understand when the effort of building a more realistic model is likely to generate more reliable forecasts. Here, we review the literature to explore whether process‐explicit models have been tested through benchmarking their temporal predictive performance (i.e. their predictive performance when transferred in time) and model transferability (i.e. their ability to keep their predictive performance when transferred to generate predictions into a different time) against simpler models, and highlight the gaps between the rapid development of process‐explicit RCMs and the testing of their potential improvements. We found that, out of five ecological processes (dispersal, demography, physiology, evolution, species interactions) and two observational processes (sampling bias, imperfect detection) that may influence reliability of forecasts, only the effects of dispersal, demography and imperfect detection have been benchmarked using temporally‐independent datasets. Only nine out of twenty‐nine process‐explicit model types have been tested to assess whether accounting for processes improves temporal predictive performance. We found no benchmarks assessing model transferability. We discuss potential reasons for the lack of empirical validation of process‐explicit models. Considering these findings, we propose an expanded research agenda to properly test the performance of process‐explicit RCMs, and highlight some opportunities to fill the gaps by suggesting models to be benchmarked using existing historical datasets. [ABSTRACT FROM AUTHOR]

Bioturbating animals can affect physical and chemical soil properties on near-surface soil by either foraging for food or constructing suitable habitats. Thereby, bioturbation can influence the soil texture either sorting or mixing the different grain sizes clay, silt and sand during burrowing. Additionally, bioturbating animals can increase the macronutrients carbon (C), nitrogen (N) and phosphorus (P) through the transport of nutrients by vertically mixing the soil column and the addition of the bioturbators' feces to the soil surface. To date, it is not clear how the effects of bioturbation on soil properties vary along an ecological gradient. Therefore, we compared the physical properties clay, silt and sand and the chemical contents of the macronutrients C, N and P for soil samples from mounds and the surrounding area as controls in three different climatic regions (arid, semi-arid and Mediterranean) of coastal Chile. To do so, we calculated the difference between the concentrations of paired mound and control samples. When comparing soil texture, we did not find significant differences between mound and control soil samples. For the macronutrient contents, the difference between mound and control C and N contents increased in the arid site and decreased in the two other research sites with increasing vegetation cover. Since we aimed to cover bioturbation patterns on a broader scale, we additionally compared our findings to other bioturbation studies performed in different biomes. Thereby, we found that other studies also show small differences in soil properties caused by bioturbation which are already sufficient to increase soil fertility. [ABSTRACT FROM AUTHOR]

Soil bioturbation activity affects soil texture, bulk density, soil water content and redistribution of nutrients. All of these parameters influences sediment redistribution, which shapes the earth surface. Hence it is important to include bioturbation into erosion models. However, up to present, the inclusion of bioturbation into erosion models was limited. This is because to realistically include bioturbation into the modelling, the interplay between bioturbation, sediment redistribution and environmental parameters is not understood. Here, we included bioturbation into a soil erosion model and interpreted the impacts of bioturbation on sediment redistribution. To do this, we measured the needed soil properties and location of burrows created by bioturbating animals in four research sites located along the Chilean climate gradient. Then, we parametrized a semi-empirical erosion model by applying machine learning algorithms to upscale soil properties and burrow distribution. We ran the model for a time period of 6 years under two conditions: With and without bioturbation. We validated the model using several sediment fences in the field. We estimated the modelled sediment redistribution and surface runoff in all climate zones. Lastly, we identified environmental parameters determining the positive or negative impact of bioturbation on sediment redistribution. We found that the model with integrated bioturbation performed much better (R2 = 0.71, RMSE = 0.63) than the model without integrated bioturbation (R2 = 0.17, RMSE = 1.18), meaning that model runs which considered bioturbation predicted the sediment redistribution more realistically. Furthermore, bioturbation increased sediment redistribution in all but the humid climate zone, especially in the Mediterranean zone. The quantity of sediment redistributed due to bioturbation was reliant on an interplay between elevation, slope, surface roughness and sink connectivity. Overall, bioturbation enhances sediment erosion in areas where more erosion is expected, and enhances sediment accumulation in areas which are more prone to accumulate sediment. In other words, considering bioturbation when studying earth surface evolution means an amplification of existing tendencies in sediment redistribution, and leads to a faster hillslope relief equalisation. [ABSTRACT FROM AUTHOR]

Due to the Aichi targets, the international community committed to the sustainable management of silvoagricultural activities and to the elimination or reform of detrimental subsidies relative to biodiversity conservation. In this context, countries should have implemented specific actions to address these commitments. In Chile, the Instruments of Productive Promotion to Finance Field Work (IPP-FFW) framework was used to fund activities related to silvoagricultural systems, including, irrigation, plantations with exotic species, and the recovery of soils. However, concerns have been raised that are associated with the need for evaluating their effectiveness, including whether impact assessments should be carried out systematically. Considering that these subsidized activities may negatively impact nature, whether IPP-FFWs had been allocated is analyzed regardless of the threat degree of terrestrial ecosystems at the commune level in Chile using the International Union for Conservation of Nature (IUCN) ecosystem risk assessment methodology; moreover, the eventual relationship between changes in land use and ecosystem service provisions in case study for the Biobio region in Chile is also examined, for which the monetary consequences of the loss of ecosystem services—via the analysis of benefit transfers—are calculated. Evidence reveals that higher amounts of IPP-FFWs are allocated in communes with higher levels of threats and that a decrease in ecosystem service provision is associated with IPP-FFW's allocation. [ABSTRACT FROM AUTHOR]