And we thought the Millennium Drought was bad: Assessing climate variability and change impacts on an Australian dryland wetland using an ecohydrologic emulator.

During the Millennium Drought in southeast Australia (2001-2009), dryland wetlands experienced widespread ecological deterioration, which highlighted their vulnerability to natural climate variability and the potential effects of drying climate change. Here we use 30-year observed streamflow data (1991-2020) and numerical models to assess the impacts of climate variability and climate change on the Macquarie Marshes (the Marshes), a large floodplain wetland complex in the semi-arid region of New South Wales, Australia. A fast ecohydrologic emulator based on network linear programming with side constraints was developed to simulate the spatial and temporal responses of different wetland vegetation types to water regime. The emulator represents the wetland by a series of inter-connected level-pool reservoirs with the volume-discharge relationship obtained from a calibrated quasi-2d hydrodynamic model. The emulator reproduces daily flows and volume with good accuracy (Nash-Sutcliffe statistic ranging from 0.61 to 0.96) with 1/26,000 of the computational effort. We use the emulator to simulate the potential effects of climatic variability on vegetation by running the model over 30 years of observed data and 1000 statistically representative 30-year streamflow time series, which were generated using a stochastic model calibrated to the gauged flows. The collection of results for all 1000 contemporary simulations indicates the Marshes experience severe conditions 43% (± 18%) of the time in a 30-year period. We then ran an additional 6000 simulations to assess the combined impacts of climate variability and future climate change at the end of the century. For the driest future climates (-60% and -30% reduction in runoff), the Marshes remain in severe condition 89% (± 6%) and 63% (± 16%) of the time, respectively, while no major differences with respect to the contemporary conditions were found for the wetter future. Our results highlight the importance of quantifying the extent and uncertainty in the degradation of these ecosystems due to climate variability and change for informing management decisions.

Soil-derived Nature's Contributions to People and their contribution to the UN Sustainable Development Goals.

This special issue provides an assessment of the contribution of soils to Nature's Contributions to People (NCP). Here, we combine this assessment and previously published relationships between NCP and delivery on the UN Sustainable Development Goals (SDGs) to infer contributions of soils to the SDGs. We show that in addition to contributing positively to the delivery of all NCP, soils also have a role in underpinning all SDGs. While highlighting the great potential of soils to contribute to sustainable development, it is recognized that poorly managed, degraded or polluted soils may contribute negatively to both NCP and SDGs. The positive contribution, however, cannot be taken for granted, and soils must be managed carefully to keep them healthy and capable of playing this vital role. A priority for soil management must include: (i) for healthy soils in natural ecosystems, protect them from conversion and degradation; (ii) for managed soils, manage in a way to protect and enhance soil biodiversity, health and sustainability and to prevent degradation; and (iii) for degraded soils, restore to full soil health. We have enough knowledge now to move forward with the implementation of best management practices to maintain and improve soil health. This analysis shows that this is not just desirable, it is essential if we are to meet the SDG targets by 2030 and achieve sustainable development more broadly in the decades to come. This article is part of the theme issue 'The role of soils in delivering Nature's Contributions to People'.

New hybrid-based approach for improving the accuracy of coastal aquifer vulnerability assessment maps.

Due to excessive exploitation, groundwater resources of coastal regions are exposed to seawater intrusion. Therefore, vulnerability assessments are essential for the quantitative and qualitative management of these resources. The GALDIT model is the most widely used approach for coastal aquifer vulnerability assessment, but suffers from subjectivity of the identification of rates and weights. This study aimes at developing a new hybrid framework for improving the accuracy of coastal aquifer vulnerability assessment using various statistical, metaheuristic, and Multi-Attribute Decision Making (MADM) methods to improve the GALDIT model. The Gharesoo-Gorgan Rood coastal aquifer in northern Iran is used as study site. In order to meet this aim, the Differential Evolution (DE) and Biogeography-Based Optimization (BBO) metaheuristic algorithms were employed to optimize the GALDIT weights. In addition, a novel MADM method, named Step-wise Weight Assessment Ratio Analysis (SWARA), and the bivariate statistical method called statistical index (SI) were used to modify the GALDIT ratings. Finally, correlation coefficients between the maps obtained from each method and Total Dissolved Solid (TDS) as an indicator of seawater intrusion were computed to evaluate the models' prediction power. Correlation coefficients of 0.72, 0.75, 0.76 and 0.78 were obtained for the GALDITSWARA-BBO, GALDITSI-BBO, GALDITSWARA-DE and GALDITSI-DE models, respectively. The results from the GALDITSI-DE model outperformed all other models at improving the accuracy of the vulnerability assessment. Moreover, the statistical-metaheuristic method yielded more accurate results than SWARA-metaheuristic hybrid models. The vulnerability map of the studied region indicates that the northwestern and western areas are very highly vulnerable. According to GALDITSI-DE model, 42%, 17%, 18% and 22% of the aquifer areas respectively have a low, medium, high and very high vulnerability to seawater intrusion. The research findings could be applied by regional authorities to manage and protect groundwater resources.

Resilience to drought of dryland wetlands threatened by climate change.

Dryland wetlands are resilient ecosystems that can adapt to extreme periodic drought-flood episodes. Climate change projections show increased drought severity in drylands that could compromise wetland resilience and reduce important habitat services. These recognized risks have been difficult to evaluate due to our limited capacity to establish comprehensive relationships between flood-drought episodes and vegetation responses at the relevant spatiotemporal scales. We address this issue by integrating detailed spatiotemporal flood-drought simulations with remotely sensed vegetation responses to water regimes in a dryland wetland known for its highly variable inundation. We show that a combination of drought tolerance and dormancy strategies allow wetland vegetation to recover after droughts and recolonize areas invaded by terrestrial species. However, climate change scenarios show widespread degradation during drought and limited recovery after floods. Importantly, the combination of degradation extent and increase in drought duration is critical for the habitat services wetland systems provide for waterbirds and fish.

Patch organization and resilience of dryland wetlands.

Dryland wetlands are ecosystems of high ecological importance as they serve as habitat sanctuaries for aquatic and terrestrial biota in areas with very few resources; therefore, the study of such environments is of major importance for the conservation of biodiversity in arid and semi-arid areas. The vegetation organization in these ecosystems is driven by the water regime as the main driver, but local processes like seed banks and soil resources redistribution also play a crucial role in determining the spatial distribution of the vegetation. Assessment of vegetation dynamics and long-term resilience requires the use of realistic models that can integrate the water regime and that can continuously simulate vegetation extent and conditions under flood-drought cycles. Here we study the influence of the water regime as the main driver of the vegetation. We apply a vegetation-modelling framework to compare the performance of a simplified model at the cell scale and a model integrated at a patch scale. Our results show that aggregating the analysis of vegetation dynamics at the patch scale allows for the incorporation of the effects of both local drivers (acting within the patch) as well as the global drivers (acting over the patch as a whole). The water regime acts as a global driver for the vegetation and indirectly affects the local drivers. Our patch scale model successfully captures wetland vegetation dynamics using the water regime as the main driver for representing changes in the vegetation and assessment of the wetland resilience under flood-drought periods.

Potential increase in coastal wetland vulnerability to sea-level rise suggested by considering hydrodynamic attenuation effects.

The future of coastal wetlands and their ecological value depend on their capacity to adapt to the interacting effects of human impacts and sea-level rise. Even though extensive wetland loss due to submergence is a possible scenario, its magnitude is highly uncertain due to limited understanding of hydrodynamic and bio-geomorphic interactions over time. In particular, the effect of man-made drainage modifications on hydrodynamic attenuation and consequent wetland evolution is poorly understood. Predictions are further complicated by the presence of a number of vegetation types that change over time and also contribute to flow attenuation. Here, we show that flow attenuation affects wetland vegetation by modifying its wetting-drying regime and inundation depth, increasing its vulnerability to sea-level rise. Our simulations for an Australian subtropical wetland predict much faster wetland loss than commonly used models that do not consider flow attenuation.

Assessing landscape structure and pattern fragmentation in semiarid ecosystems using patch-size distributions.

Spatial vegetation patterns are recognized as sources of valuable information that can be used to infer the state and functionality of semiarid ecosystems, particularly in the context of both climate and land use change. Recent studies have suggested that the patch-size distribution of vegetation in drylands can be described using power-law metrics, and that these scale-free distributions deviate from power-law linearity with characteristic scale lengths under the effects of increasing aridity or human disturbance, providing an early sign of desertification. These findings have been questioned by several modeling approaches, which have identified the presence of characteristic scale lengths on the patch-size distribution of semiarid periodic landscapes. We analyze the relationship between fragmentation of vegetation patterns and their patch-size distributions in semiarid landscapes showing different degree of periodicity (i.e., banding). Our assessment is based on the study of vegetation patterns derived from remote sensing in a series of semiarid Australian Mulga shrublands subjected to different disturbance levels. We use the patch-size probability density and cumulative probability distribution functions from both nondirectional and downslope analyses of the vegetation patterns. Our results indicate that the shape of the patch-size distribution of vegetation changes with the methodology of analysis applied and specific landscape traits, breaking the universal applicability of the power-law metrics. Characteristic scale lengths are detected in (quasi) periodic banded ecosystems when the methodology of analysis accounts for critical landscape anisotropies, using downslope transects in the direction of flow paths. In addition, a common signal of fragmentation is observed: the largest vegetation patches become increasingly less abundant under the effects of disturbance. This effect also explains deviations from power-law behavior in disturbed vegetation which originally showed scale-free patterns. Overall, our results emphasize the complexity of structure assessment in dryland ecosystems, while recognizing the usefulness of the patch-size distribution of vegetation for monitoring semiarid ecosystems, especially through the cumulative probability distributions, which showed high sensitivity to fragmentation of the vegetation patterns. We suggest that preserving large vegetation patches is a critical task for the maintenance of the ecosystem structure and functionality.