Timo A. Räsänen

Forest Loss in Protected Areas and Intact Forest Landscapes: A Global Analysis

In spite of the high importance of forests, global forest loss has remained alarmingly high during the last decades. Forest loss at a global scale has been unveiled with increasingly finer spatial resolution, but the forest extent and loss in protected areas (PAs) and in large intact forest landscapes (IFLs) have not so far been systematically assessed. Moreover, the impact of protection on preserving the IFLs is not well understood. In this study we conducted a consistent assessment of the global forest loss in PAs and IFLs over the period 2000–2012. We used recently published global remote sensing based spatial forest cover change data, being a uniform and consistent dataset over space and time, together with global datasets on PAs’ and IFLs’ locations. Our analyses revealed that on a global scale 3% of the protected forest, 2.5% of the intact forest, and 1.5% of the protected intact forest were lost during the study period. These forest loss rates are relatively high compared to global total forest loss of 5% for the same time period. The variation in forest losses and in protection effect was large among geographical regions and countries. In some regions the loss in protected forests exceeded 5% (e.g. in Australia and Oceania, and North America) and the relative forest loss was higher inside protected areas than outside those areas (e.g. in Mongolia and parts of Africa, Central Asia, and Europe). At the same time, protection was found to prevent forest loss in several countries (e.g. in South America and Southeast Asia). Globally, high area-weighted forest loss rates of protected and intact forests were associated with high gross domestic product and in the case of protected forests also with high proportions of agricultural land. Our findings reinforce the need for improved understanding of the reasons for the high forest losses in PAs and IFLs and strategies to prevent further losses.

Using Reanalysis and Remotely Sensed Temperature and Precipitation Data for Hydrological Modeling in Monsoon Climate: Mekong River Case Study

AbstractMany large basins in the “Monsoon Asia” region have sparse surface observation networks of the hydrometeorological parameters needed for hydrological modeling. These models are often used in water resources–related planning, impact assessments, and flood forecasting, which sets strict requirements for model accuracy and reliability. The aim of this study was to assess the performance of several publicly available reanalyses and remotely sensed datasets when used in modeling of discharges in the Mekong River basin. Tested precipitations were extracted from Tropical Rainfall Measuring Mission (TRMM) 3B42, versions 6 and 7; Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE); Climate Forecast System Reanalysis (CFSR); and Interim ECMWF Re-Analysis (ERA-Interim) datasets. Temperature data were extracted from CFSR and ERA-Interim datasets. The model results obtained using these datasets were compared to measured discharges and modeled val...

Decoding the drivers of bank erosion on the Mekong river: The roles of the Asian monsoon, tropical storms, and snowmelt.

We evaluate links between climate and simulated river bank erosion for one of the worlds largest rivers, the Mekong. We employ a process-based model to reconstruct multidecadal time series of bank erosion at study sites within the Mekongs two main hydrological response zones, defining a new parameter, accumulated excess runoff (AER), pertinent to bank erosion. We employ a hydrological model to isolate how snowmelt, tropical storms and monsoon precipitation each contribute to AER and thus modeled bank erosion. Our results show that melt (23.9% at the upstream study site, declining to 11.1% downstream) and tropical cyclones (17.5% and 26.4% at the upstream and downstream sites, respectively) both force significant fractions of bank erosion on the Mekong. We also show (i) small, but significant, declines in AER and hence assumed bank erosion during the 20th century, and; (ii) that significant correlations exist between AER and the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Of these modes of climate variability, we find that IOD events exert a greater control on simulated bank erosion than ENSO events; but the influences of both ENSO and IOD when averaged over several decades are found to be relatively weak. However, importantly, relationships between ENSO, IOD, and AER and hence inferred river bank erosion are not time invariant. Specifically, we show that there is an intense and prolonged epoch of strong coherence between ENSO and AER from the early 1980s to present, such that in recent decades derived Mekong River bank erosion has been more strongly affected by ENSO.

Designing river flows to improve food security futures in the Lower Mekong Basin

Optimizing flow in dammed rivers Hydropower dams radically alter river flow regimes, often with consequences for the functioning and productivity of the waters downstream. Where fisheries in large tropical river systems are affected, there can be knock-on effects on food security. For the Mekong River, Sabo et al. used a data-based time series modeling approach to estimate the features of the flow regime that optimize the fishery that is crucial to food security in Cambodia (see the Perspective by Poff and Olden). Fish futures can be maximized within a managed hydrologic system with careful prescription of flows. Such data-driven approaches can be used to link hydrology to ecology and food production and specify design principles that could help to deliver food security in other river systems. Science, this issue p. eaao1053; see also p. 1252 An algorithm is developed to manage river flow that could augment future fisheries yield, despite diverse other ongoing human uses. INTRODUCTION The Mekong River provides renewable energy and food security for a population of more than 60 million people in six countries: China, Myanmar, Lao PDR, Thailand, Vietnam, and Cambodia. Seasonal rains flood the river’s floodplain and delta. This flood pulse fuels what is likely the world’s largest freshwater fishery in Cambodia’s Tonle Sap Lake, with >2 million tonnes of annual harvest valued at ~

Model-Based Assessment of Water, Food, and Energy Trade-Offs in a Cascade of Multipurpose Reservoirs: Case Study of the Sesan Tributary of the Mekong River

2 billion. Hydropower development is crucial to the region’s economic prosperity and is simultaneously a threat to fisheries and agriculture that thrived in the natural-flow regime. The Mekong is testament to the food, energy, and water challenges facing tropical rivers globally. RATIONALE We hypothesized that high fisheries yields are driven by measurable attributes of hydrologic variability, and that these relationships can be used to design and implement future flow regimes that improve fisheries yield through control of impending hydropower operations. Hydrologic attributes that drive strong fisheries yields were identified using a data-driven approach that combined 17 years of discharge and standardized harvest data with several time-series methods in the frequency and time domains. We then analyzed century-scale time series of discharge data on the Mekong and associated hydroclimate data sets to understand how current dams, independent of climate, have changed key drivers of the fishery since the early 1960s. Finally, we used estimated hydrologic drivers of the historical bag net, or “Dai,” fishery on the Tonle Sap River—the largest commercial fishery in the Mekong—to design better fisheries futures by comparing designed flows to current and pre-dam (natural-flow) regimes. RESULTS Our analysis identified several features of hydrologic variability that portend strong fisheries yield. These include two “high-level” descriptors: flood pulse extent (FPExt) and net annual anomaly (NAA). FPExt, which combines flood magnitude and duration, has long been hypothesized to drive fisheries yield in ecosystems subject to flood pulses, such as the Mekong. NAA is the annual sum of daily residual flows standardized to the long-term average hydrograph. Hence, NAA is a compact measure of hydrologic variance and can be further decomposed into nine shape “components.” Several of these components drive high fisheries yields, including a long low-flow period followed by a short, strong flood pulse with multiple peaks. All essential drivers of the flood pulse fishery have been changing since the closure of the first Mekong tributary dam and are independent of changes associated with climate observed over the past century. The direction of these changes is consistent with declining fisheries yield in the Tonle Sap. Projection of the fishery driven by a hypothetical “designer” hydrograph capturing the key shape features associated with strong yield improved harvest relative to current conditions; yield was projected to exceed that of the natural-flow regime by a factor of 3.7. This result was robust to the inclusion of density-dependent recruitment in our time-series model. CONCLUSION A data-driven approach reveals a new perspective on hydrologic drivers of fishery productivity in the Mekong. The extent of the flood pulse is paramount, as previous literature suggests, but so are other descriptors of hydrologic variation, including anomalous low flows. Variance is key—specifically, the sequence and timing of within-year anomalous high and low flows. A focus on variance shifts the conversation from “How much water do we need?” to “When do we need it the most, and when can we spare it?” Beneficial components of variance in the hydrograph can be described by a simple Fourier series—an asymmetric rectangular pulse train. A quantitative ecological objective function fills a critical gap in the balancing of fisheries harvest with other important objective functions including hydropower generation, rice production, and transportation. This opens the possibility of specifying and implementing flow regimes to manage rivers to satisfice trade-offs between fishery productivity and other ecosystem services provided by tropical rivers subject to flood pulses. Subsistence fisher tending nets on the Tonle Sap Lake, Cambodia. PHOTO BY J. L. SABO Rivers provide unrivaled opportunity for clean energy via hydropower, but little is known about the potential impact of dam-building on the food security these rivers provide. In tropical rivers, rainfall drives a periodic flood pulse fueling fish production and delivering nutrition to more than 150 million people worldwide. Hydropower will modulate this flood pulse, thereby threatening food security. We identified variance components of the Mekong River flood pulse that predict yield in one of the largest freshwater fisheries in the world. We used these variance components to design an algorithm for a managed hydrograph to explore future yields. This algorithm mimics attributes of discharge variance that drive fishery yield: prolonged low flows followed by a short flood pulse. Designed flows increased yield by a factor of 3.7 relative to historical hydrology. Managing desired components of discharge variance will lead to greater efficiency in the Lower Mekong Basin food system.

Prediction under uncertainty as a boundary problem

AbstractThe Mekong River Basin in Southeast Asia is undergoing rapid development in the exploitation of its water resources. Although hydropower is the most dominant driver for water development, t...

Response to Comments on “Designing river flows to improve food security futures in the Lower Mekong Basin”

Making predictions about environmental systems is a challenge due to the high level of uncertainty involved. In this paper we give a general formulation of prediction under uncertainty as a boundary problem. This leads to development of a methodology for making predictions under uncertainty, named Iterative Closed Question Modelling (ICQM). ICQM involves iteratively devising questions and testing the certainty of their answers by creating complete model scenarios (complete taken to include structure, parameters and inputs for each scenario instance). The model scenarios are categorised in terms of which answer they support, and whether they are plausible or not. Using a simple two-parameter flow duration curve model, the paper demonstrates the application of ICQM using eight alternative uncertainty analysis techniques. ICQM provides a useful and generic approach to making predictions under uncertainty, helps to understand how existing techniques address the boundary problem differently and promotes the development of new techniques. Display Omitted Prediction under uncertainty is formulated as a boundary problem.A modelling methodology to approach uncertainty is proposed.It is broadly applicable, with eight techniques shown.

Spatiotemporal Hydroclimate Variability in Finland: Past Trends

Sabo et al. presented an empirically derived algorithm defining the socioecological response of the Tonle Sap Dai fishery in the Cambodian Mekong to basin-scale variation in hydrologic flow regime. Williams suggests that the analysis leading to the algorithm is flawed because of the large distance between the gauge used to measure water levels (hydrology) and the site of harvest for the fishery. Halls and Moyle argue that Sabo et al.’s findings are well known and contend that the algorithm is not a comprehensive assessment of sustainability. We argue that Williams’ critique stems from a misunderstanding about our analysis; further clarification of the analysis is provided. We regret not citing more of the work indicated by Halls and Moyle, yet we note that our empirical analysis provides additional new insights into Mekong flow-fishery relationships.

Future changes in Mekong River hydrology: impact of climate change and reservoir operation on discharge

AbstractOver the past decades, Finland has experienced changes in its climate: temperature and precipitation have increased, resulting in varying runoff patterns. These trends are well studied, but the changes in interannual variability are less known, despite their importance for understanding climate change. This research aims to assess spatiotemporal changes in variability of temperature, precipitation, and runoff for 1962–2014 at the subbasin scale in Finland. Temporal changes in variability were analyzed by constructing moving-window median absolute deviation time series at annual and seasonal scales. Subbasins with similar patterns of temporal variability were identified using principal component analysis and agglomerative hierarchical clustering. Presence of monotonic trends in variability was tested. Distinct areas with similar patterns of statistically significant changes in variability were found. Decreases in annual, winter, and summer temperature variability were discovered across Finland, in ...