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Land degradation directly affects around 25% of land globally, undermining progress on most of the UN Sustainable Development Goals (SDG), particularly target 15.3. To assess land degradation, SDG indicator 15.3.1 combines sub-indicators of productivity, soil carbon and land cover. Over 100 countries have set Land Degradation Neutrality (LDN) targets. Here, we demonstrate application of the indicator for a well-established agricultural landscape using the case study of Great Britain. We explore detection of degradation in such landscapes by: 1) transparently evaluating land cover transitions; 2) comparing assessments using global and national data; 3) identifying misleading trends; and 4) including extra sub-indicators for additional forms of degradation. Our results demonstrate significant impacts on the indicator both from the land cover transition evaluation and choice or availability of data. Critically, we identify a misleading improvement trend due to a trade-off between improvement detected by the productivity sub-indicator, and 30-year soil carbon loss trends in croplands (11% from 1978 to 2007). This carbon loss trend would not be identified without additional data from Countryside Survey (CS). Thus, without incorporating field survey data we risk overlooking the degradation of regulating and supporting ecosystem services (linked to soil carbon), in favour of signals from improving provisioning services (productivity sub-indicator). Relative importance of these services will vary between socioeconomic contexts. Including extra sub-indicators for erosion or critical load exceedance, as additional forms of degradation, produced a switch from net area improving (9%) to net area degraded (58%). CS data also identified additional degradation for soil health, including 44% arable soils exceeding bulk density thresholds and 35% of CS squares exceeding contamination thresholds for metals.
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Agricultura , Ecossistema , Solo , Desenvolvimento Sustentável , Carbono , Conservação dos Recursos NaturaisRESUMO
Loss and fragmentation of natural land cover due to expansion of agricultural areas is a global issue. These changes alter the configuration and composition of the landscape, particularly affecting those ecosystem services (benefits people receive from ecosystems) that depend on interactions between landscape components. Hydrological mitigation describes the bundle of ecosystem services provided by landscape features such as woodland that interrupt the flow of runoff to rivers. These services include sediment retention, nutrient retention and mitigation of overland water flow. The position of woodland in the landscape and the landscape topography are both important for hydrological mitigation. Therefore, it is crucial to consider landscape configuration and flow pathways in a spatially explicit manner when examining the impacts of fragmentation. Here we test the effects of landscape configuration using a large number (>7,000) of virtual landscape configurations. We created virtual landscapes of woodland patches within grassland, superimposed onto real topography and stream networks. Woodland patches were generated with user-defined combinations of patch number and total woodland area, placed randomly in the landscape. The Ecosystem Service model used hydrological routing to map the "mitigated area" upslope of each woodland patch. We found that more fragmented woodland mitigated a greater proportion of the catchment. Larger woodland area also increased mitigation, however, this increase was nonlinear, with a threshold at 50% coverage, above which there was a decline in service provision. This nonlinearity suggests that the benefit of any additional woodland depends on two factors: the level of fragmentation and the existing area of woodland. Edge density (total edge of patches divided by area of catchment) was the best single metric in predicting mitigated area. Distance from woodland to stream was not a significant predictor of mitigation, suggesting that agri-environment schemes planting riparian woodland should consider additional controls such as the amount of fragmentation in the landscape. These findings highlight the potential benefits of fragmentation to hydrological mitigation services. However, benefits for hydrological services must be balanced against any negative effects of fragmentation or habitat loss on biodiversity and other services.
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Ecossistema , Florestas , Agricultura , Biodiversidade , HidrologiaRESUMO
Soil organic matter (SOM) is an indicator of sustainable land management as stated in the global indicator framework of the United Nations Sustainable Development Goals (SDG Indicator 15.3.1). Improved forecasting of future changes in SOM is needed to support the development of more sustainable land management under a changing climate. Current models fail to reproduce historical trends in SOM both within and during transition between ecosystems. More realistic spatio-temporal SOM dynamics require inclusion of the recent paradigm shift from SOM recalcitrance as an 'intrinsic property' to SOM persistence as an 'ecosystem interaction'. We present a soil profile, or pedon-explicit, ecosystem-scale framework for data and models of SOM distribution and dynamics which can better represent land use transitions. Ecosystem-scale drivers are integrated with pedon-scale processes in two zones of influence. In the upper vegetation zone, SOM is affected primarily by plant inputs (above- and belowground), climate, microbial activity and physical aggregation and is prone to destabilization. In the lower mineral matrix zone, SOM inputs from the vegetation zone are controlled primarily by mineral phase and chemical interactions, resulting in more favourable conditions for SOM persistence. Vegetation zone boundary conditions vary spatially at landscape scales (vegetation cover) and temporally at decadal scales (climate). Mineral matrix zone boundary conditions vary spatially at landscape scales (geology, topography) but change only slowly. The thicknesses of the two zones and their transport connectivity are dynamic and affected by plant cover, land use practices, climate and feedbacks from current SOM stock in each layer. Using this framework, we identify several areas where greater knowledge is needed to advance the emerging paradigm of SOM dynamics-improved representation of plant-derived carbon inputs, contributions of soil biota to SOM storage and effect of dynamic soil structure on SOM storage-and how this can be combined with robust and efficient soil monitoring.
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Ecossistema , Solo , Carbono , Clima , PlantasRESUMO
Soil fauna play a fundamental role on key ecosystem functions like organic matter decomposition, although how local assemblages are responding to climate change and whether these changes may have consequences to ecosystem functioning is less clear. Previous studies have revealed that a continued environmental stress may result in poorer communities by filtering out the most sensitive species. However, these experiments have rarely been applied to climate change factors combining multiyear and multisite standardized field treatments across climatically contrasting regions, which has limited drawing general conclusions. Moreover, other facets of biodiversity, such as functional and phylogenetic diversity, potentially more closely linked to ecosystem functioning, have been largely neglected. Here, we report that the abundance, species richness, phylogenetic diversity, and functional richness of springtails (Subclass Collembola), a major group of fungivores and detritivores, decreased within 4 years of experimental drought across six European shrublands. The loss of phylogenetic and functional richness was higher than expected by the loss of species richness, leading to communities of phylogenetically similar species sharing evolutionary conserved traits. Additionally, despite the great climatic differences among study sites, we found that taxonomic, phylogenetic, and functional richness of springtail communities alone were able to explain up to 30% of the variation in annual decomposition rates. Altogether, our results suggest that the forecasted reductions in precipitation associated with climate change may erode springtail communities and likely other drought-sensitive soil invertebrates, thereby retarding litter decomposition and nutrient cycling in ecosystems.
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Secas , Ecossistema , Animais , Biodiversidade , Europa (Continente) , FilogeniaRESUMO
The respiratory release of carbon dioxide (CO2) from soil is a major yet poorly understood flux in the global carbon cycle. Climatic warming is hypothesized to increase rates of soil respiration, potentially fueling further increases in global temperatures. However, despite considerable scientific attention in recent decades, the overall response of soil respiration to anticipated climatic warming remains unclear. We synthesize the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3,800 observations representing 27 temperature manipulation studies, spanning nine biomes and over 2 decades of warming. Our analysis reveals no significant differences in the temperature sensitivity of soil respiration between control and warmed plots in all biomes, with the exception of deserts and boreal forests. Thus, our data provide limited evidence of acclimation of soil respiration to experimental warming in several major biome types, contrary to the results from multiple single-site studies. Moreover, across all nondesert biomes, respiration rates with and without experimental warming follow a Gaussian response, increasing with soil temperature up to a threshold of â¼25 °C, above which respiration rates decrease with further increases in temperature. This consistent decrease in temperature sensitivity at higher temperatures demonstrates that rising global temperatures may result in regionally variable responses in soil respiration, with colder climates being considerably more responsive to increased ambient temperatures compared with warmer regions. Our analysis adds a unique cross-biome perspective on the temperature response of soil respiration, information critical to improving our mechanistic understanding of how soil carbon dynamics change with climatic warming.
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Well-defined productivity-precipitation relationships of ecosystems are needed as benchmarks for the validation of land models used for future projections. The productivity-precipitation relationship may be studied in two ways: the spatial approach relates differences in productivity to those in precipitation among sites along a precipitation gradient (the spatial fit, with a steeper slope); the temporal approach relates interannual productivity changes to variation in precipitation within sites (the temporal fits, with flatter slopes). Precipitation-reduction experiments in natural ecosystems represent a complement to the fits, because they can reduce precipitation below the natural range and are thus well suited to study potential effects of climate drying. Here, we analyse the effects of dry treatments in eleven multiyear precipitation-manipulation experiments, focusing on changes in the temporal fit. We expected that structural changes in the dry treatments would occur in some experiments, thereby reducing the intercept of the temporal fit and displacing the productivity-precipitation relationship downward the spatial fit. The majority of experiments (72%) showed that dry treatments did not alter the temporal fit. This implies that current temporal fits are to be preferred over the spatial fit to benchmark land-model projections of productivity under future climate within the precipitation ranges covered by the experiments. Moreover, in two experiments, the intercept of the temporal fit unexpectedly increased due to mechanisms that reduced either water loss or nutrient loss. The expected decrease of the intercept was observed in only one experiment, and only when distinguishing between the late and the early phases of the experiment. This implies that we currently do not know at which precipitation-reduction level or at which experimental duration structural changes will start to alter ecosystem productivity. Our study highlights the need for experiments with multiple, including more extreme, dry treatments, to identify the precipitation boundaries within which the current temporal fits remain valid.
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Clima , Ecologia/métodos , Ecossistema , Chuva , ÁguaRESUMO
Increasing soil organic carbon (SOC) confers benefits to soil health, biodiversity, underpins carbon sequestration and ameliorates land degradation. One recommendation is to increase SOC such that the SOC to clay ratio (SOC/clay) exceeds 1/13, yet normalising SOC levels based on clay alone gives misleading indications of soil structure and the potential to store additional carbon. Building on work by Poeplau & Don (2023) to benchmark observed against predicted SOC, we advance an alternative indicator: the ratio between observed and "typical" SOC (O/T SOC) for pan-European application. Here, "typical" SOC is the average concentration in different pedo-climate zones, PCZs (which, unlike existing SOC indicators, incorporate land cover and climate, alongside soil texture) across Europe, determined from mineral (<20 % organic matter) topsoils (0-20 cm) sampled during 2009-2018 in LUCAS, Europe's largest soil monitoring scheme (n = 19,855). Regression tree modelling derived 12 PCZs, with typical SOC values ranging 5.99-39.65 g kg-1. New index classes for comparison with SOC/clay grades were established from the quartiles of each PCZ's O/T SOC distribution; these were termed: "Low" (below the 25th percentile), "Intermediate" (between the 25th and 50th percentiles), "High" (between the 50th and 75th percentiles), and "Very high" (above the 75th percentile). Compared with SOC/clay, O/T SOC was less sensitive to clay content, land cover, and climate, less geographically skewed, and better reflected differences in soil porosity and SOC stock, supporting 2 EU Soil Health Mission objectives (consolidating SOC stocks; improving soil structure for crops and biota). These patterns held for 2 independent datasets, and O/T SOC grades were sensitive enough to reflect land management differences across several long-term field experiments. O/T SOC used in conjunction with several other physical, chemical and biological soil health indicators can help support the EU Soil Monitoring Law and achieve several United Nations Sustainable Development Goals.
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Anthropogenically forced changes in global freshwater biodiversity demand more efficient monitoring approaches. Consequently, environmental DNA (eDNA) analysis is enabling ecosystem-scale biodiversity assessment, yet the appropriate spatio-temporal resolution of robust biodiversity assessment remains ambiguous. Here, using intensive, spatio-temporal eDNA sampling across space (five rivers in Europe and North America, with an upper range of 20-35 km between samples), time (19 timepoints between 2017 and 2018) and environmental conditions (river flow, pH, conductivity, temperature and rainfall), we characterise the resolution at which information on diversity across the animal kingdom can be gathered from rivers using eDNA. In space, beta diversity was mainly dictated by turnover, on a scale of tens of kilometres, highlighting that diversity measures are not confounded by eDNA from upstream. Fish communities showed nested assemblages along some rivers, coinciding with habitat use. Across time, seasonal life history events, including salmon and eel migration, were detected. Finally, effects of environmental conditions were taxon-specific, reflecting habitat filtering of communities rather than effects on DNA molecules. We conclude that riverine eDNA metabarcoding can measure biodiversity at spatio-temporal scales relevant to species and community ecology, demonstrating its utility in delivering insights into river community ecology during a time of environmental change.
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Biodiversidade , Código de Barras de DNA Taxonômico , DNA Ambiental , Ecossistema , Peixes , Rios , DNA Ambiental/genética , DNA Ambiental/análise , Código de Barras de DNA Taxonômico/métodos , Animais , Peixes/genética , Peixes/classificação , Europa (Continente) , América do Norte , Análise Espaço-Temporal , Estações do AnoRESUMO
Soil organic carbon (SOC) is a soil health indicator and understanding dynamics changing SOC stocks will help achieving net zero goals. Here we present four datasets featuring 11,750 data points covering co-located aboveground and below-ground metrics for exploring ecosystem SOC dynamics. Five sites across England with an established land use contrast, grassland and woodland next to each other, were rigorously sampled for aboveground (n = 109), surface (n = 33 soil water release curves), topsoil, and subsoil metrics. Commonly measured soil metrics were analysed in five soil increments for 0-1 metre (n = 4550). Less commonly measured soil metrics which were assumed to change across the soil profile were measured on a subset of samples only (n = 3762). Additionally, we developed a simple method for soil organic matter fractionation using density fractionation which is part of the less common metrics. Finally, soil metrics which may impact SOC dynamics, but with less confidence as to their importance across the soil profile were only measured on topsoil (~5-15 cm = mineral soil) and subsoil (below 50 cm) samples (n = 2567).
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Carbono , Pradaria , Solo , Solo/química , Carbono/análise , Inglaterra , Florestas , EcossistemaRESUMO
Efforts to improve soil health require that target values of key soil properties are established. No agreed targets exist but providing population data as benchmarks is a useful step to standardise soil health comparison between landscapes. We exploited nationally representative topsoil (0-15 cm) measurements to derive soil health benchmarks for managed and semi-natural environments across Great Britain. In total, 4587 soil organic matter (SOM), 3860 pH, 2908 bulk density (BD), and 465 earthworm abundance (EA) datapoints were used. As soil properties are sensitive to site-specific characteristics, data were stratified by habitat, soil type, and mean annual precipitation, with benchmarks defined as the middle 80 % of values in each distribution - yielding 135 benchmarks. BD and pH decreased with land management intensity (agriculture > semi-natural grasslands > woodlands > heathlands > wetlands), and vice versa for SOM and EA. Normalising benchmark ranges by medians revealed soil health indicator benchmark widths increased in the order: pH < BD < SOM < EA, while width increased with decreasing land management intensity. Arable and horticulture and improved grassland exhibited narrow benchmarks for SOM, pH and BD, yet the widest EA benchmark, suggesting additional drivers impact EA patterns. Upland wetlands had the widest BD benchmarks, important when determining carbon stocks. East Anglia currently possesses the largest proportions of atypical soils, including below typical SOM (19.2 %), above typical BD (17.4 %) and pH (39.1 %), and the smallest proportions of above typical SOM (2.4 %), and below typical BD (5.8 %) and pH (2.3 %). This is found even after land use, soil type and rainfall have been considered, underscoring how urgently soil health should be addressed here. Our benchmarking framework allows landowners to compare where their measured soil health indicators fall within expected ranges and is applicable to other biomes, national and multinational contexts.
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Benchmarking , Solo , Solo/química , Ecossistema , Agricultura , Florestas , CarbonoRESUMO
Climatic changes, including altered precipitation regimes, will affect key ecosystem processes, such as plant productivity and biodiversity for many terrestrial ecosystems. Past and ongoing precipitation experiments have been conducted to quantify these potential changes. An analysis of these experiments indicates that they have provided important information on how water regulates ecosystem processes. However, they do not adequately represent global biomes nor forecasted precipitation scenarios and their potential contribution to advance our understanding of ecosystem responses to precipitation changes is therefore limited, as is their potential value for the development and testing of ecosystem models. This highlights the need for new precipitation experiments in biomes and ambient climatic conditions hitherto poorly studied applying relevant complex scenarios including changes in precipitation frequency and amplitude, seasonality, extremity and interactions with other global change drivers. A systematic and holistic approach to investigate how soil and plant community characteristics change with altered precipitation regimes and the consequent effects on ecosystem processes and functioning within these experiments will greatly increase their value to the climate change and ecosystem research communities. Experiments should specifically test how changes in precipitation leading to exceedance of biological thresholds affect ecosystem resilience and acclimation.
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Mudança Climática , Ecossistema , Desenvolvimento Vegetal , Chuva , Adaptação Biológica , Biodiversidade , Biomassa , Previsões , Pesquisa/tendências , SoloRESUMO
Cattle grazing profoundly affects abiotic and biotic characteristics of ecosystems. While most research has been performed on grasslands, the effect of large managed ungulates on forest ecosystems has largely been neglected. Compared to a baseline seminatural state, we investigated how long-term cattle grazing of birch forest patches affected the abiotic state and the ecological community (microbes and invertebrates) of the soil subsystem. Grazing strongly modified the soil abiotic environment by increasing phosphorus content, pH, and bulk density, while reducing the C:N ratio. The reduced C:N ratio was strongly associated with a lower microbial biomass, mainly caused by a reduction of fungal biomass. This was linked to a decrease in fungivorous nematode abundance and the nematode channel index, indicating a relative uplift in the importance of the bacterial energy-channel in the nematode assemblages. Cattle grazing highly modified invertebrate community composition producing distinct assemblages from the seminatural situation. Richness and abundance of microarthropods was consistently reduced by grazing (excepting collembolan richness) and grazing-associated changes in soil pH, Olsen P, and reduced soil pore volume (bulk density) limiting niche space and refuge from physical disturbance. Anecic earthworm species predominated in grazed patches, but were absent from ungrazed forest, and may benefit from manure inputs, while their deep vertical burrowing behavior protects them from physical disturbance. Perturbation of birch forest habitat by long-term ungulate grazing profoundly modified soil biodiversity, either directly through increased physical disturbance and manure input or indirectly by modifying soil abiotic conditions. Comparative analyses revealed the ecosystem engineering potential of large ungulate grazers in forest systems through major shifts in the composition and structure of microbial and invertebrate assemblages, including the potential for reduced energy flow through the fungal decomposition pathway. The precise consequences for species trophic interactions and biodiversity-ecosystem function relationships remain to be established, however.
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The physical, chemical and biological attributes of a soil combined with abiotic factors (e.g. climate and topography) drive pedogenesis and some of these attributes have been used as proxies to soil quality. Thus, we investigated: (1) whether appropriate soil quality indicators (SQIs) could be identified in soils of Great Britain, (2) whether conventional soil classification or aggregate vegetation classes (AVCs) could predict SQIs and (3) to what extent do soil types and/ or AVCs act as major regulators of SQIs. Factor analysis was used to group 20 soil attributes into six SQI which were named as; soil organic matter (SOM), dissolved organic matter (DOM), soluble N, reduced N, microbial biomass, DOM humification (DOMH). SOM was identified as the most important SQI in the discrimination of both soil types and AVCs. Soil attributes constituting highly to the SOM factor were, microbial quotient and bulk density. The SOM indicator discriminated three soil type groupings and four aggregate vegetation class groupings. Among the soil types, only the peat soils were discriminated from other groups while among the AVCs only the heath and bog classes were isolated from others. However, the peat soil and heath and bog AVC were the only groups that were distinctly discriminated from other groups. All other groups heavily overlapped with one another, making it practically impossible to define reference values for each soil type or AVC. The two-way ANOVA showed that the AVCs were a better regulator of the SQIs than the soil types. We conclude that conventionally classified soil types cannot predict the SQIs defined from large areas with differing climatic and edaphic factors. Localised areas with similar climatic and topoedaphic factors may hold promise for the definition of SQI that may predict the soil types or AVCs.
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Solo/química , Biomassa , Microbiota , Reino UnidoRESUMO
High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalizing syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterize taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from survey metadata. Specifically, we modeled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on both the shape of landscape scale pH-abundance responses, and pH optima (pH at which OTU abundance is maximal). We identify that most of the soil OTUs examined exhibited a non-flat relationship with soil pH. Further, the pH optima could not be generalized by broad taxonomy, highlighting the need for tools and databases synthesizing ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER/), and flat files are made available for use in bioinformatic pipelines. The further development of advanced informatics infrastructures incorporating modeled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.
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A warming climate and expected changes in average and extreme rainfall emphasise the importance of understanding how the land surface routes and stores surface water. The availability and movement of water within an ecosystem is a fundamental control on biological and geophysical activity, and influences many climatic feedbacks. A key phenomenon influencing water infiltration into the land surface is soil hydrophobicity, or water repellency. Despite repellency dictating the speed, volume and pattern of water infiltration, there is still major uncertainty over whether this critical hydrological process is biologically or physicochemically controlled. Here we show that soil water repellency is likely driven by changes in the plant and soil microbial communities in response to environmental stressors. We carried out a field survey in the summers of 2013 to 2016 in a variety of temperate habitats ranging across arable, grassland, forest and bog sites. We found that moderate to extreme repellency occurs in 68% of soils at a national scale in temperate ecosystems, with 92% showing some repellency. Taking a systems approach, we show that a wetter climate and low nutrient availability alter plant, bacterial and fungal community structure, which in turn are associated with increased soil water repellency across a large-scale gradient of soil, vegetation and land-use. The stress tolerance of the plant community and associated changes in soil microbial communities were more closely linked to changes in repellency than soil physicochemical properties. Our results indicate that there are consistent responses to diverse ecosystem stresses that will impact plant and microbial community composition, soil properties, and hydrological behaviour. We suggest that the ability of a biological community to induce such hydrological responses will influence the resilience of the whole ecosystem to environmental stress. This highlights the crucial role of above-belowground interactions in mediating climatic feedbacks and dictating ecosystem health.
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Plantas , Microbiologia do Solo , Solo/química , Estresse Fisiológico , Bactérias , Biota , Ecossistema , Florestas , Fungos , Hidrologia , Microbiota , Estações do Ano , ÁguaRESUMO
Soil biota accounts for ~25% of global biodiversity and is vital to nutrient cycling and primary production. There is growing momentum to study total belowground biodiversity across large ecological scales to understand how habitat and soil properties shape belowground communities. Microbial and animal components of belowground communities follow divergent responses to soil properties and land use intensification; however, it is unclear whether this extends across heterogeneous ecosystems. Here, a national-scale metabarcoding analysis of 436 locations across 7 different temperate ecosystems shows that belowground animal and microbial (bacteria, archaea, fungi, and protists) richness follow divergent trends, whereas ß-diversity does not. Animal richness is governed by intensive land use and unaffected by soil properties, while microbial richness was driven by environmental properties across land uses. Our findings demonstrate that established divergent patterns of belowground microbial and animal diversity are consistent across heterogeneous land uses and are detectable using a standardised metabarcoding approach.
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Biodiversidade , Ecossistema , Microbiologia do Solo , Solo , Animais , Biologia Computacional , Código de Barras de DNA Taxonômico , Microbiota/genética , País de GalesRESUMO
Accurate quantification of biodiversity is fundamental to understanding ecosystem function and for environmental assessment. Molecular methods using environmental DNA (eDNA) offer a non-invasive, rapid, and cost-effective alternative to traditional biodiversity assessments, which require high levels of expertise. While eDNA analyses are increasingly being utilized, there remains considerable uncertainty regarding the dynamics of multispecies eDNA, especially in variable systems such as rivers. Here, we utilize four sets of upland stream mesocosms, across an acid-base gradient, to assess the temporal and environmental degradation of multispecies eDNA. Sampling included water column and biofilm sampling over time with eDNA quantified using qPCR. Our findings show that the persistence of lotic multispecies eDNA, sampled from water and biofilm, decays to non-detectable levels within 2 days and that acidic environments accelerate the degradation process. Collectively, the results provide the basis for a predictive framework for the relationship between lotic eDNA degradation dynamics in spatio-temporally dynamic river ecosystems.
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Ecosystem services modelling tools can help land managers and policy makers evaluate the impacts of alternative management options or changes in land use on the delivery of ecosystem services. As the variety and complexity of these tools increases, there is a need for comparative studies across a range of settings, allowing users to make an informed choice. Using examples of provisioning and regulating services (water supply, carbon storage and nutrient retention), we compare three spatially explicit tools - LUCI (Land Utilisation and Capability Indicator), ARIES (Artificial Intelligence for Ecosystem Services) and InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs). Models were parameterised for the UK and applied to a temperate catchment with widely varying land use in North Wales. Although each tool provides quantitative mapped output, can be applied in different contexts, and can work at local or national scale, they differ in the approaches taken and underlying assumptions made. In this study, we focus on the wide range of outputs produced for each service and discuss the differences between each modelling tool. Model outputs were validated using empirical data for river flow, carbon and nutrient levels within the catchment. The sensitivity of the models to land-use change was tested using four scenarios of varying severity, evaluating the conversion of grassland habitat to woodland (0-30% of the landscape). We show that, while the modelling tools provide broadly comparable quantitative outputs, each has its own unique features and strengths. Therefore the choice of tool depends on the study question.