Research resource review

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Resilience viewed through the lens of climate change and water management

Resilience is not a new idea but there has been an upsurge in efforts to operationalize the concept within water management. This review begins with a synopsis of related themes around persistent and emerging pressures on freshwaters; environmental thresholds (or tipping points); ‘safe’ operating conditions; multiple stable states; regime shifts. A case is made for viewing and managing the resilience of water systems at nested scales. Indicators are needed to track evolving climate risks as well as to measure socio-ecological responses. Catchment properties can identify those river systems that are more or less likely to return to a pre-disturbance state; resilience further depends on institutional and social landscapes. Ideally, allied notions of resistance and reliability are applied alongside resilience to broaden the portfolio of adaptation measures. Water managers would also benefit from more consistent use of resilience terminology; incentives to build back better after catastrophes; strategic monitoring of incipient threats and tipping points; availability of long-term adaptation indicators; coordinated efforts to reduce non-climatic pressures on freshwaters (especially in headwaters); evidence-based, practical guidance on adaptation measures that build resilience

Climate for development in Africa (ClimDev) – climate sciences and services for Africa. Strategic research opportunities for ClimDev-Africa

The purpose of this report is to present the ClimDev Partnership with a much narrower set of strategic research options by which ACPC and AfDB in particular could establish a unique presence in the realm of climate research and resilience planning. As a result, hitherto under-represented sectors and regions would be better equipped to manage risks as well as maximise development opportunities presented by climate variability and change. A gap analysis was undertaken using different sources of evidence drawn from bibliographic metrics, previous research prioritisation exercises, peer-reviewed and grey literature, meta-analysis of web-based material, conference proceedings, ClimDev reports and proposal short-listing, an inventory of climate data requests, case studies and consultations with African experts. Six research opportunities are proposed for consideration by ClimDev

Information sources to support ADB climate risk assessments and management

This technical note provides information that supports climate risk assessment experts undertaking early stages of project development in Asia and the Pacific region. The Asia and Pacific region is vulnerable to extreme temperatures, flooding by heavy rainfall, sea level rise, coastal erosion, and damage by tropical cyclones. This technical note provides information that supports climate risk assessment experts undertaking early stages of project development in the region. The information is grouped into four major categories: inventories of national emissions, climate risks, vulnerability, and impacts; historic weather, climate, and environmental change; regional climate change projections; and climate change impacts and adaptation. The note also identifies opportunities for capacity development in key skills such as geospatial analysis, data testing and post-processing, regional climate downscaling, and impact assessment

A global hydrology research agenda fit for the 2030s

Global assessments show profound impacts of human activities on freshwater systems that, without action, are expected to reach crisis points in the 2030s. By then, the capacity of natural systems to meet rising demands for water, food and energy could be hampered by emerging signals of anthropogenic climate change. The hydrologic community has always been solution-orientated, but our generation faces perhaps the greatest array of water challenges in human history. Ambitious programmes of research are needed to fill critical data, knowledge and skills gaps. Priorities include filling data sparse places, predicting peak water, understanding the physical drivers of mega droughts, evaluating hyper-resolution models, managing compound hazards, and adjusting water infrastructure designs to climate change. Despite the opportunities presented by big data, we must not lose sight of the deep uncertainties affecting both our raw input data and hydrological models, nor neglect the human dimensions of water system change. Community-scale projects and international research partnerships are needed to connect new hydrological knowledge with most vulnerable communities as well as to achieve more integrated and grounded solutions. With these elements in place, we will be better equipped to meet the global hydrological challenges of the 2030s and beyond.</div

Robust adaptation to climate change

Robust adaptation to climate chang

Measuring the changing pulse of rivers

River flood risks are expected to rise as climate change intensifies the global hydrological cycle and more people live in floodplains (1). Changing risk may be revealed by trends in flood frequency, magnitude, or seasonality, as well as by shifts in the mechanisms that generate inundations (2). However, detection and attribution of climate signals in flood records is often hampered by brief, incomplete, or poor-quality flood data (3). Additionally, it can be difficult to disentangle the effects of changing climate, land cover, channel morphology, and human activities (2, 4). On page 588 of this issue, Blöschl et al. (5) overcome these problems through a consistent pan-European assessment of observed flood seasonality trends between 1960 and 2010. They thus provide the first evaluation of how climatic changes are influencing flood regimes at the continental scale

Modes of climate variability and associated bird communities in India

Birds are sensitive to climate variability and change. This pilot study explores variations in bird communities in India under contrasting phases of the El NinoSouthern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Statistical analyses were performed using monthly bird data for the years 1990-2015 in Goa and Tamil Nadu. Monthly precipitation, temperature, the Oceanic Nino Index and the Dipole Mode Index were used as explanatory variables for species richness (SR) and counts of three marker species (Brahminy Kite, Indian Pond Heron and Lesser Whistling Duck). Due to highly autocorrelated series, small sample sizes and many test permutations there is greater likelihood of Type I errors when interpreting correlation results. However, pooling bird data by climate mode and state revealed that SR was generally greater under El Nino or negative IOD (locally wet conditions) than under La Nina or positive IOD (locally dry conditions). In Goa, the Brahminy Kite, Indian Pond Heron and Lesser Whistling Duck had significantly higher counts during El Nino than La Nina events. In Tamil Nadu, there were significantly more Kites under negative than positive IOD phases. Regional variations in sensitivity may reflect species-dependent factors such as food availability and security of nesting sites. Further research is needed to establish causal mechanisms between climate mode and SR as well as into the combined effects of ENSO and IOD on bird communities across South Asia

Role of low intensity environmental disturbance in structuring the earliest (Ediacaran) macrobenthic tiered communities

Rangeomorphs were important components of Ediacaran macrobenthic ecosystems, yet their biology and ecology remain poorly constrained. They formed high-density, tiered communities that were subjected to intermittent burial events, the largest of which killed entire communities. Abundant thin event beds in the Ediacaran succession of Charnwood Forest indicate the additional, frequent impact of minor obrution events. The type surface of Charnia masoni is immediately underlain by one such lamina (a tuff) and preserves a distinctly bimodal population. It is dominated by Charnia fronds that are of smaller or comparable length to the holotype (19.4. cm), but also includes notably larger specimens (>. 45. cm) that would traditionally have been assigned to Charnia grandis. Multiple morphological- and morphometric parameters (length, width, spacing of primary branches) demonstrate that these are indistinguishable from the holotype of C. masoni, affirming the synonymy of the two taxa. Nevertheless, these outsized individuals are distinguished by their proportionally fewer primary branches per unit length. Taphonomic evidence indicates that they were survivors of an incumbent population, the rest of which was culled by a minor ashfall. We suggest that this temporary reduction in competition from neighbours allowed the survivors to grow larger and thereby gain access to a greater proportion of the water column. As the community recovered, their large size would have continued to provide them with an advantage, divorcing them from the density-dependent competition seen in the new understory. The interlude between cohorts implies that new recruits were substrate-sensitive, presumably awaiting re-establishment of the biomat. Sub-lethal disturbance events thus played a significant role in structuring Ediacaran communities, and help explain the observed bed-by-bed variability. Taken as a whole, the growth trajectory of C. masoni resembles that of extant organisms with indeterminate growth programmes and no genetically-controlled upper size limit

Forecasting reservoir inflows using remotely sensed precipitation estimates: a pilot study for the River Naryn, Kyrgyzstan

This study explores the feasibility of applying remotely sensed precipitation estimates (in this case from the Tropical Rainfall Measuring Mission [TRMM]) for forecasting inflows to the strategically important Toktogul reservoir in the Naryn basin, Kyrgyzstan. Correlations between observed precipitation at Naryn and 0.5° TRMM totals is weaker for daily (r = 0.25) than monthly (r = 0.93) totals, but the Naryn gauge is representative of monthly TRMM precipitation estimates across ~60% of the basin. We evaluate predictability of monthly inflows given TRMM estimates, air temperature and antecedent flows. Regression model skill was superior to the zero order forecast (mean flow) for lead-times up to three months, and had lower errors in estimated peaks. Over 80% of the variance in monthly inflows is explained with three-month lead, and up to 65% for summer half-year average. The analysis also reveals zones that are delivering highest predictability and hence candidate areas for surface network expansion