Hotspots of uncertainty in land‐use and land‐cover change projections: a global‐scale model comparison

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.     

Scale‐dependence of vegetation‐environment relationships in semi‐natural grasslands

Questions: Which environmental and management factors determine plant species composition in semi‐natural grasslands within a local study area? Are vegetation and explanatory factors scale‐dependent? Location: Semi‐natural grasslands in Lærdal, Sognog Fjordane County, western Norway. Methods: We recorded plant species composition and explanatory variables in six grassland sites using a hierarchically nested sampling design with three levels: plots randomly placed within blocks selected within sites. We evaluated vegetation‐environment relationships at all three levels by means of DCA ordination and split‐plot GLM analyses. Results: The most important complex gradient determining variation in grassland species composition showed a broad‐scale relationship with management. Soil moisture conditions were related to vegetation variation on block scale, whereas element concentrations in the soil were significantly related to variation in species composition on all spatial scales. Our results show that vegetation‐environment relationships are dependent on the scale of observation. We suggest that scale‐related (and therefore methodological) issues may explain the wide range of vegetation‐environment relationships reported in the literature, for semi‐natural grassland in particular but also for other ecosystems. Conclusions: Interpretation of the variation in species composition of semi‐natural grasslands requires consideration of the spatial scales on which important environmental variables vary.     

Physical and Chemical Limnology of 34 Lentic Waterbodies along a Tropical‐to‐Alpine Altitudinal Gradient in Nepal

Physical and chemical factors were studied in 34 lentic waterbodies distributed along a steep altitudinal gradient ranging from tropical (77 m) to high alpine (up to 4,980 m) environments in Nepal. Bicarbonate and calcium were dominant among anions and cations, respectively, reflecting a strong influence of carbonate weathering and watershed area, rather than altitudinal climate. The relative patterns of dominant ions were similar among lakes in all altitudinal regions, although total concentrations increased with decreasing altitude. Total suspended solids were relatively high in the study lakes, as is also typical of rivers in the Ganges watershed. Suspended solids had a greater influence on water transparency than did algal biomass in the study lakes. In general, high‐altitude waterbodies were oligotrophic, while those at low altitude were eutrophic. The productivity of high‐altitude study lakes appeared to be limited by both available phosphorus and nitrogen, while lowland ones were nitrogen‐limited. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Stochastic frontier analysis of a classic self‐thinning experiment

Abstract The classic experiment that gave rise to the self‐thinning rule 40 years ago was re‐analysed using stochastic frontier functions. The estimated slope of the self‐thinning boundary line was almost identical to the original proposed value. However, contrary to the original conclusion that the self‐thinning boundary line remained invariant across the soil fertility gradient, the intercept was found to increase with soil fertility. Stochastic frontier analysis also provided a more realistic estimate of the maximum asymptotic stand density than the original work, by separating the effects of density‐dependent and density‐independent mortalities during self‐thinning in a composed error term in the model specification. The time‐course of self‐thinning across the soil fertility gradient was described by a non‐linear function, which enabled the estimation of a minimum possible stand density that could still maintain full site occupancy (i.e. the maximum asymptotic stand density at the end of self‐thinning). The maximum asymptotic stand density decreased more rapidly on more fertile soils and the difference in maximum asymptotic stand density among the five levels of soil fertility increased non‐linearly with time. Site carrying capacity was defined as stand biomass shown by the point on the self‐thinning boundary line at the end of self‐thinning. This definition led to a direct functional link between the self‐thinning boundary line and site carrying capacity for even‐aged plant populations.     

A Stand‐Alone Si‐Based Porous Photoelectrochemical Cell

Wireless photoelectrochemical (PEC) devices promise easy device fabrication as well as reduced losses. Here, the design and fabrication of a stand‐alone ion exchange material‐embedded, Si membrane‐based, photoelectrochemical cell architecture with micron‐sized pores is shown, to overcome the i) pH gradient formation due to long‐distance ion transport, ii) product crossover, and iii) parasitic light absorption by application of a patterned catalyst. The membrane‐embedded PEC cell with micropores utilizes a triple Si junction cell as the light absorber, and Pt and IrO_x as electrocatalysts for the hydrogen evolution reactions and oxygen evolution reactions, respectively. The solar‐to‐hydrogen efficiency of 7% at steady‐state operation, as compared to an unpatterned η_PV of 10.8%, is mainly attributed to absorption losses by the incorporation of the micropores and catalyst microdots. The introduction of the Nafion ion exchange material ensures an intrinsically safe PEC cell, by reducing the total gas crossover to <0.1%, while without a cation exchange membrane, a crossover of >6% is observed. Only in a pure electrolyte of 1 m H₂SO₄, a pH gradient‐free system is observed thus completely avoiding the build‐up of a counteracting potential.     

The relative importance of plasticity versus genetic differentiation in explaining between population differences; a meta‐analysis

Both plasticity and genetic differentiation can contribute to phenotypic differences between populations. Using data on non‐fitness traits from reciprocal transplant studies, we show that approximately 60% of traits exhibit co‐gradient variation whereby genetic differences and plasticity‐induced differences between populations are the same sign. In these cases, plasticity is about twice as important as genetic differentiation in explaining phenotypic divergence. In contrast to fitness traits, the amount of genotype by environment interaction is small. Of the 40% of traits that exhibit counter‐gradient variation the majority seem to be hyperplastic whereby non‐native individuals express phenotypes that exceed those of native individuals. In about 20% of cases plasticity causes non‐native phenotypes to diverge from the native phenotype to a greater extent than if plasticity was absent, consistent with maladaptive plasticity. The degree to which genetic differentiation versus plasticity can explain phenotypic divergence varies a lot between species, but our proxies for motility and migration explain little of this variation.     

Inverse‐probability‐of‐treatment weighted estimation of causal parameters in the presence of error‐contaminated and time‐dependent confounders

Inverse‐probability‐of‐treatment weighted (IPTW) estimation has been widely used to consistently estimate the causal parameters in marginal structural models, with time‐dependent confounding effects adjusted for. Just like other causal inference methods, the validity of IPTW estimation typically requires the crucial condition that all variables are precisely measured. However, this condition, is often violated in practice due to various reasons. It has been well documented that ignoring measurement error often leads to biased inference results. In this paper, we consider the IPTW estimation of the causal parameters in marginal structural models in the presence of error‐contaminated and time‐dependent confounders. We explore several methods to correct for the effects of measurement error on the estimation of causal parameters. Numerical studies are reported to assess the finite sample performance of the proposed methods.     

Ti‐Gradient Doping to Stabilize Layered Surface Structure for High Performance High‐Ni Oxide Cathode of Li‐Ion Battery

High‐Ni layered oxide cathodes are considered to be one of the most promising cathodes for high‐energy‐density lithium‐ion batteries due to their high capacity and low cost. However, surfice residues, such as NiO‐type rock‐salt phase and Li₂CO₃, are often formed at the particle surface due to the high reactivity of Ni³⁺, and inevitably result in an inferior electrochemical performance, hindering the practical application. Herein, unprecedentedly clean surfaces without any surfice residues are obtained in a representative LiNi_0.8Co_0.2O₂ cathode by Ti‐gradient doping. High‐resolution transmission electron microscopy (TEM) reveals that the particle surface is composed of a disordered layered phase (≈6 nm in thickness) with the same rhombohedra structure as its interior. The formation of this disordered layered phase at the particle surface is electrochemically favored. It leads to the highest rate capacity ever reported and a superior cycling stability. First‐principles calculations further confirm that the excellent electrochemical performance has roots in the excellent chemical/structural stability of such a disordered layered structure, mainly arising from the improved robustness of the oxygen framework by Ti doping. This strategy of constructing the disordered layered phase at the particle surface could be extended to other high‐Ni layered transition metal oxides, which will contribute to the enhancement of their electrochemical performance.     

A Bayesian Chi‐Squared Goodness‐of‐Fit Test for Censored Data Models

Summary We propose a Bayesian chi‐squared model diagnostic for analysis of data subject to censoring. The test statistic has the form of Pearson's chi‐squared test statistic and is easy to calculate from standard output of Markov chain Monte Carlo algorithms. The key innovation of this diagnostic is that it is based only on observed failure times. Because it does not rely on the imputation of failure times for observations that have been censored, we show that under heavy censoring it can have higher power for detecting model departures than a comparable test based on the complete data. In a simulation study, we show that tests based on this diagnostic exhibit comparable power and better nominal Type I error rates than a commonly used alternative test proposed by Akritas (1988, Journal of the American Statistical Association 83, 222–230). An important advantage of the proposed diagnostic is that it can be applied to a broad class of censored data models, including generalized linear models and other models with nonidentically distributed and nonadditive error structures. We illustrate the proposed model diagnostic for testing the adequacy of two parametric survival models for Space Shuttle main engine failures.