Explore the vast range of titles available.

Groundwater is the most ubiquitous source of liquid freshwater globally, yet its role in supporting diverse ecosystems is rarely acknowledged 1 , 2 . However, the location and extent of groundwater-dependent ecosystems (GDEs) are unknown in many geographies, and protection measures are lacking 1 , 3 . Here, we map GDEs at high-resolution (roughly 30 m) and find them present on more than one-third of global drylands analysed, including important global biodiversity hotspots 4 . GDEs are more extensive and contiguous in landscapes dominated by pastoralism with lower rates of groundwater depletion, suggesting that many GDEs are likely to have already been lost due to water and land use practices. Nevertheless, 53% of GDEs exist within regions showing declining groundwater trends, which highlights the urgent need to protect GDEs from the threat of groundwater depletion. However, we found that only 21% of GDEs exist on protected lands or in jurisdictions with sustainable groundwater management policies, invoking a call to action to protect these vital ecosystems. Furthermore, we examine the linkage of GDEs with cultural and socio-economic factors in the Greater Sahel region, where GDEs play an essential role in supporting biodiversity and rural livelihoods, to explore other means for protection of GDEs in politically unstable regions. Our GDE map provides critical information for prioritizing and developing policies and protection mechanisms across various local, regional or international scales to safeguard these important ecosystems and the societies dependent on them. Mapping of groundwater-dependent ecosystems, which support biodiversity and rural livelihoods, shows they occur on more than one-third of global drylands analysed, but lack protections to safeguard these critical ecosystems and the societies dependent upon them from groundwater depletion.

Due to climatic constraints in dryland regions, wetlands usually occur at confluences of flow paths, whether from surface flow, inter-flow or at locations of groundwater discharge. Long-term landscape processes that shape valleys and focus the movement of water and sediment are accountable for providing a suitable template with which hydrology interacts to allow wetland formation. Current hydrogeomorphic classification systems do not address system-scale linkages of sediment and water transport across the landscape, and are therefore unable to contextualise long-term process dynamics. Misunderstanding long-term earth system processes can result in the application of inappropriate restoration strategies that isolate wetlands from longitudinal drivers of their formation. We propose a genetic classification system that focuses on the mode of wetland formation, and is based on the understanding that genetic processes impact on the outcome hydrology, sedimentology, geomorphology, ecosystem service provision and long-term dynamics of wetlands in drylands. The classification aims to impart understanding of dynamic processes of sediment transport through wetlands, such that restoration plans can be sensitive to long-term landscape processes. The classification system, derived from a combination of international literature and published South African case studies, has four wetland macrotypes based on sediment source (colluvial, alluvial, aeolian and geochemical). These are subdivided into 8 wetland types; hillslope seep, floodplain, valley-bottom, plain, blocked-valley, alluvial fan, aeolian depression and geochemical depression. The classification is based on landscape location, shape and the occurrence of geomorphic characteristics indicative of process.

The typology of wetlands provides important information for both water resource managers and conservation planners. One of the most important aims of allocating wetlands to a certain type or class is to provide information about the ecosystem services that the wetland provides. There are two main approaches towards wetland classification. Firstly, there are top-down approaches whereby wetlands are divided into several categories based on a conceptual understanding of how the wetland functions (mostly with regards to water flows). Secondly there are bottom-up approaches whereby the classification of wetlands is based on the collection of data in the wetland that is then subjected to various clustering techniques (mostly with regards to biodiversity). The most utilized system of top-down classification assigns wetlands into hydrogeomorphic units, which function as a single unit in terms of hydrology and geomorphology. This type of classification is most useful for water resource planning, as it provides information about how the wetland is connected to the drainage network and what are the water inflows, throughflows and outflows of the wetland. The bottom-up classification approach typically focusses on the classification of wetland habitats rather than complete wetlands, where wetland habitat represents a spatial unit delineated on the basis of vegetation, embedded within the (complete) hydrogeomorphic unit, and defined as an area of wetland that is homogeneous in terms of opportunities for plant growth. At a broad scale, most ecosystem services can be superficially derived from the hydrogeomorphic unit type and the way water moves through a wetland, but habitat units and the plant species that define them would have a specific effect on the delivery of ecosystem services, for example, with different assemblages providing different resistance to flow. Some types of ecosystem services are exclusively linked to specific wetland habitats, especially provisioning services. For this reason, it is proposed that a combined approach of hydrogeomorphic classification together with a vegetation map, offers the maximum information value for ecosystem service determination. In order to account for the potential pitfall of “double counting” when combining the top-down and bottom-up approaches, each service needs to be considered individually with reference to the degree to which a service is either: (a) primarily determined by HGM class/attributes and modified by the vegetation class/attributes; or (b) primarily determined by the vegetation class/attributes.

Given limited time, staffing and specialist expertise, management of wetlands within biodiversity-rich protected areas of developing countries is often held back by a lack of information on the extent and nature of wetland resources. Rapid, realistic and effective wetland ecosystem assessment methods are needed to develop a baseline for monitoring that detects trends and guides management. Lack of available in-house wetland expertise stimulated a novel team which harnessed wide-ranging complementary and, ultimately, indispensable expertise, spanning all branches of the park, including park management and rangers, Scientific Services and Biodiversity Social Projects. Within a year, the team developed a sufficiently comprehensive inventory which captured the variation of wetlands present in Mountain Zebra National Park, South Africa. A total of 267 wetlands were mapped, while 62 were visited in the field and assessed through rapid verification. Careful collation of existing data and imagery informed a catchment approach, an emphasis on wetland-landscape connectivity, and strategic targeting of a sub-set of important and representative sites deserving of targeted, high effort field assessment. The remaining wetlands not visited in the field were subject to desktop review. Overall, this resulted in a comprehensive overview assessment of the entire Park at multiple scales. The approach of convening a multi-disciplinary team supports strengthened governance and integrated implementation of the findings into park planning, management and rehabilitation. The process provides a potential template for rolling out similar work in other parks and other areas that have limited funding and capacity.

Accurate spatial maps of wetlands are critical for regional conservation and rehabilitation assessments, yet this often remains an elusive target. Such maps ideally provide information on wetland occurrence and extent; hydrogeomorphic (HGM) type; and condition/ level of degradation. All three elements are needed to provide ancillary layers to support mapping from remote imagery and ground-truthing. Knowledge of HGM types is particularly important, because different types show differential levels of sensitivity to degradation, and modeling accuracy for occurrence. Here, we develop and test a simple approach for predicting the most likely HGM type for mapped yet unattributed wetland polygons. We used a dataset of some 11,500 wetland polygons attributed by HGM types (floodplain, depression, seep, channeled and un-channeled valley-bottom) from the Western Cape Province in South Africa. Polygons were attributed and described in terms of nine landscape metrics, at a sub-catchment scale. Using a combination of box-and-whisker plots and PCA, we identified four variables (groundwater depth, relief ratio, slope and elevation) as being the most important variables in differentiating HGM types. We divided the data into equal parts for training and testing of a simple Bayesian network model. Model validation included field assessments. HGM types were most sensitive to elevation. Model predication was good, with error rates of only 32%. We conclude that this is a useful technique that can be widely applied using readily available data, for rapid classification of HGM types at a regional scale.

In South Africa, anthropogenic pressures such as water over-abstraction, invasive species impacts, land-use change, pollution, and climate change have caused widespread deterioration of the health of river ecosystems. This comes at great cost to both people and biodiversity, with freshwater fishes ranked as the country’s most threatened species group. Effective conservation and management of South Africa’s freshwater ecosystems requires access to reliable and comprehensive biodiversity data. Despite the existence of a wealth of freshwater biodiversity data, access to these data has been limited. The Freshwater Biodiversity Information System (FBIS) was built to address this knowledge gap by developing an intuitive, accessible and reliable platform for freshwater biodiversity data in South Africa. The FBIS hosts high quality, high accuracy biodiversity data that are freely available to a wide range of stakeholders, including researchers, conservation practitioners and policymakers. We describe how the system is being used to provide freshwater fish data to a national conservation decision-support tool—The Department of Forestry, Fisheries, and the Environment (DFFE) National Environmental Screening Tool (NEST). The NEST uses empirical and modelled biodiversity data to guide Environmental Impact Assessment Practitioners in conducting environmental assessments of proposed developments. Occurrence records for 34 threatened freshwater fishes occurring in South Africa were extracted from the FBIS and verified by taxon specialists, resulting in 6 660 records being used to generate modelled and empirical national distribution (or sensitivity) layers. This represents the first inclusion of freshwater biodiversity data in the NEST, and future iterations of the tool will incorporate additional freshwater taxa. This case study demonstrates how the FBIS fills a pivotal role in the data-to-decision pipeline through supporting data-driven conservation and management decisions at a national level.

The Cape Floristic Region (CFR) and Succulent Karoo are global biodiversity hotspots. The CFR is one of six plant kingdoms worldwide. The CFR and most of the Succulent Karoo lie within South Africa. South Africa has ratified the Biodiversity Convention, and must accordingly safeguard its biodiversity. Environmental assessment (EA) can help to achieve this end. Environmental legislation in South Africa requires EA for activities at project, not strategic level. However, strategic environmental assessment has been mandatory since 2000 for preparing municipal spatial development frameworks (SDFs). By setting targets for ecosystem conservation and providing thresholds of significance, systematic conservation planning can make a significant contribution to the sound preparation of SDFs, and effective EA at planning and project levels. In South Africa, the integration of systematic conservation planning with spatial planning and EA is recent. Based on examples, the main challenges for the future are identified.

The Cape Floristic Region (CFR) and the Succulent Karoo in South Africa have been identified as global biodiversity hotspots. Environmental assessment (EA) can contribute to meeting the objectives of the Biodiversity Convention, and is required at the project level nationally, and at the strategic level in municipal planning. Conservation planning is essential to sound spatial development frameworks (SDFs) at the municipal level. Challenges with this integration include overselectivity, a primary focus on listed species, poor precedents in spatial and temporal planning, inadequate biodiversity information, limited understanding of biodiversity among practitioners, problematic assignments of significance ratings, and the tendency of the issue based scoping process to rely on uninformed stakeholders.

We describe an approach to detect the frequency of interaction between any two genomic loci. Generation of a matrix of interaction frequencies between sites on the same or different chromosomes reveals their relative spatial disposition and provides information about the physical properties of the chromatin fiber. This methodology can be applied to the spatial organization of entire genomes in organisms from bacteria to human. Using the yeast Saccharomyces cerevisiae, we could confirm known qualitative features of chromosome organization within the nucleus and dynamic changes in that organization during meiosis. We also analyzed yeast chromosome III at the G1 stage of the cell cycle. We found that chromatin is highly flexible throughout. Furthermore, functionally distinct AT- and GC-rich domains were found to exhibit different conformations, and a population-average 3D model of chromosome III could be determined. Chromosome III emerges as a contorted ring.