Does agricultural intensification cause tipping points in ecosystem services?

Context: Agricultural intensification is being widely pursued as a policy option to improve food security and human development. Yet, there is a need to understand the impact of agricultural intensification on the provision of multiple ecosystem services, and to evaluate the possible occurrence of tipping points. Objectives: I.To quantify and assess the long-term spatial dynamics of ecosystem service (ES) provision in a landscape undergoing agricultural intensification at four time points 1930, 1950, 1980 and 2015.II.Determine if thresholds or tipping points in ES provision may have occurred and if there are any detectable impacts on economic development and employment. Methods: We used the InVEST suite of software models together with a time series of historical land cover maps and an Input–Output model to evaluate these dynamics over an 85-year period in the county of Dorset, southern England. Results: Results indicated that trends in ES were often non-linear, highlighting the potential for abrupt changes in ES provision to occur in response to slight changes in underlying drivers. Despite the fluctuations in provision of different ES, overall economic activity increased almost linearly during the study interval, in line with the increase in agricultural productivity. Conclusions: Such non-linear thresholds in ES will need to be avoided in the future by approaches aiming to deliver sustainable agricultural intensification. A number of positive feedback mechanisms are identified that suggest these thresholds could be considered as tipping points. However, further research into these feedbacks is required to fully determine the occurrence of tipping points in agricultural systems

Understanding the accuracy of modelled changes in freshwater provision over time

Accurate modelling of changes in freshwater supplies is critical in an era of increasing human demand, and changes in land use and climate. However, there are concerns that current landscape-scale models do not sufficiently capture catchment-level changes, whilst large-scale comparisons of empirical and simulated water yield changes are lacking. Here we modelled annual water yield in two time periods (1: 1985–1994 and 2: 2008–2017) across 81 catchments in England and validated against empirical data. Our objectives were to i) investigate whether modelling absolute or relative change in water yield is more accurate and ii) determine which predictors have the greatest impact on model accuracy. We used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Annual Water Yield model. In this study, absolute values refer to volumetric units of million cubic metres per year (Mm3/y), either at the catchment or hectare level. Modelled annual yields showed high accuracy as indicated by the low Mean Absolute Deviation (MAD, based on normalised data, 0 is high and 1 is low accuracy) at the catchment (1: 0.013 ± 0.019, 2: 0.012 ± 0.020) and hectare scales (1: 0.03 ± 0.030, 2: 0.030 ± 0.025). But accuracy of modelled absolute change in water yield showed a more moderate fit on both the catchment (MAD = 0.055 ± 0.065) and hectare (MAD = 0.105 ± 0.089) scales. Relative change had lower accuracy (MAD = 0.189 ± 0.135). Anthropogenic modifications to the hydrological system, including water abstraction contributed significantly to the inaccuracy of change values at the catchment and hectare scales. Quantification of changes in freshwater provision can be more accurately articulated using absolute values rather than using relative values. Absolute values can provide clearer guidance for mitigation measures related to human consumption. Accuracy of modelled change is related to different aspects of human consumption, suggesting anthropogenic impacts are critically important to consider when modelling water yield

Integrating ecosystem markets to co-ordinate landscape-scale public benefits from nature

Ecosystem markets are proliferating around the world in response to increasing demand for climate change mitigation and provision of other public goods. However, this may lead to perverse outcomes, for example where public funding crowds out private investment or different schemes create trade-offs between the ecosystem services they each target. The integration of ecosystem markets could address some of these issues but to date there have been few attempts to do this, and there is limited understanding of either the opportunities or barriers to such integration. This paper reports on a comparative analysis of eleven ecosystem markets in operation or close to market in Europe, based on qualitative analysis of 25 interviews, scheme documentation and two focus groups. Our results indicate three distinct types of markets operating from the regional to national scale, with different modes of operation, funding and outcomes: regional ecosystem markets, national carbon markets and green finance. The typology provides new insights into the operation of ecosystem markets in practice, which may challenge traditionally held notions of Payment for Ecosystem Services. Regional ecosystem markets, in particular, represent a departure from traditional models, by using a risk-based funding model and aggregating both supply and demand to overcome issues of free-riding, ecosystem service trade-offs and land manager engagement. Central to all types of market were trusted intermediaries, brokers and platforms to aggregate supply and demand, build trust and lower transaction costs. The paper outlines six options for blending public and private funding for the provision of ecosystem services and proposes a framework for integrating national carbon markets and green finance with regional ecosystem markets. Such integration may significantly increase funding for regenerative agriculture and conservation across multiple habitats and services, whilst addressing issues of additionality and ecosystem service trade-offs between multiple schemes

Assessment of spatial variability of multiple ecosystem services in grasslands of different intensities

Grasslands provide multiple Ecosystem Services (ES) such as forage provision, carbon sequestration or habitat provision. Knowledge about the trade-offs between these ES is of great importance for grassland management. Yet, the outcome of different management strategies on ES provision is highly uncertain due to spatial variability. We aim to characterize the provision (level and spatial variability) of grassland ES under various management strategies. To do so, we combine empirical data for multiple ES with spatially explicit census data on land use intensities. We analyzed the variations of five ES (forage provision, climate regulation, pollination, biodiversity conservation and outdoor recreation) using data from biodiversity fieldwork, experimental plots for carbon as well as social network data from Flickr. These data were used to calculate the distribution of modelled individual and multiple ES values from different grassland management types in a Swiss case study region using spatial explicit information for 17,383 grassland parcels. Our results show that (1) management regime and intensity levels play an important role in ES provision but their impact depends on the ES. In general, extensive management, especially in pastures, favors all ES but forage provision, whereas intensive management favors only forage provision and outdoor recreation; (2) ES potential provision varies between parcels under the same management due to the influence of environmental drivers, related to topography and landscape structure; (3) there is a trade-offs between forage provision and other ES at the cantonal level but a synergy between forage provision and biodiversity conservation within the grassland categories, due to the negative impact of elevation on both ES. Information about multiple ES provision is key to support effective agri-environmental measures and information about the spatial variability can prevent uncertain outputs of decision-making processes

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5–2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility

Publisher Correction: Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper

Comparison of methods for a landscape-scale assessment of the cultural ecosystem services associated with different habitats

<p>Cultural ecosystem services (CES) are widely acknowledged as important but are often neglected by ecosystem service assessments, leading to a representational bias. This reflects the methodological challenges associated with producing robust and repeatable CES valuations. Here we provide a comparative analysis of three approaches for non-monetary valuation of CES, namely a structured survey, participatory GIS (PGIS) and GPS tracking methods. These were used to assess both recreation and aesthetic value of habitats within the New Forest National Park, UK. The association of CES with habitats enabled results of all three methods to be visualised at the landscape scale using maps, strengthening their value to conservation management. Broadleaved woodland and heathland habitats were consistently valued highly for both CES, whereas agricultural land tended to be associated with low values. Results obtained by the different methods were positively correlated in 6 out of 10 comparisons, indicating a degree of consistency between them. The spatial distribution of CES values at the landscape scale was also generally consistent between the three methods. These results highlight the value of comparative analyses of CES for identifying robust results, providing a way forward for their inclusion in land management decision-making.</p><p><b>EDITED BY</b> Matthias Schröter</p><p></p> <p><b>EDITED BY</b> Matthias Schröter</p

The journey to monitoring ecosystem services: are we there yet?

The Group on Earth Observations Biodiversity Observation Network (GEO BON) was established to promote and provide guidance toward a global observation network on biodiversity and ecosystems for decision makers and the scientific community. Here we comment on three key challenges in the development and implementation of monitoring schemes and indicators of ecosystem services (ES): (1) combining ES observations, data and methods across scales; (2) identifying operational ES metrics that consider the interactions between people and ecosystems; and (3) integrating the diversity of socio-cultural values and knowledge into monitoring activities. We discuss these challenges with the goal to stimulate the ES research community to help tackle these focus areas in ES monitoring

Whole-genome sequencing of patients with rare diseases in a national health system

Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 extensively phenotyped participants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data of UK Biobank participants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare