Soil carbon and nitrogen mineralization: Theory and models across scales

In the last 80 years, a number of mathematical models of different level of complexity have been developed to describe biogeochemical processes in soils, spanning spatial scales from few μm to thousands of km and temporal scales from hours to centuries. Most of these models are based on kinetic and stoichiometric laws that constrain elemental cycling within the soil and the nutrient and carbon exchange with vegetation and the atmosphere. While biogeochemical model performance has been previously assessed in other reviews, less attention has been devoted to the mathematical features of the models, and how these are related to spatial and temporal scales. In this review, we consider ∼250 biogeochemical models, highlighting similarities in their theoretical frameworks and illustrating how their mathematical structure and formulation are related to the spatial and temporal scales of the model applications. Our analysis shows that similar kinetic and stoichiometric laws, formulated to mechanistically represent the complex underlying biochemical constraints, are common to most models, providing a basis for their classification. Moreover, a historic analysis reveals that the complexity and degree and number of nonlinearities generally increased with date, while they decreased with increasing spatial and temporal scale of interest. We also found that mathematical formulations specifically developed for certain scales (e.g., first order decay rates assumed in yearly time scale decomposition models) often tend to be used also at other spatial and temporal scales different from the original ones, possibly resulting in inconsistencies between theoretical formulations and model application. It is thus critical that future modeling efforts carefully account for the scale-dependence of their mathematical formulations, especially when applied to a wide range of scales.     

Residual Variance–Covariance Modelling in Analysis of Multivariate Data from Variety Selection Trials

Field trials for variety selection often exhibit spatial correlation between plots. When multivariate data are analysed from these field trials, there is the added complication in having to simultaneously account for correlation between the traits at both the residual and genetic levels. This may be temporal correlation in the case of multi-harvest data from perennial crop field trials, or between-trait correlation in multi-trait data sets. Use of parsimonious yet plausible models for the variance–covariance structure of the residuals for such data is a key element to achieving an efficient and inferentially sound analysis. In this paper, a model is developed for the residual variance–covariance structure firstly by considering a multivariate autoregressive model in one spatial direction and then extending this to two spatial directions. Conditions for ensuring that the processes are directionally invariant are presented. Using a canonical decomposition, these directionally invariant processes can be transformed into a set of independent separable processes. This simplifies the estimation process. The new model allows for flexible modelling of the spatial and multivariate interaction and allows for different spatial correlation parameters for each harvest or trait. The methods are illustrated using data from lucerne breeding trials at several environments.     

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature loggers systematically distributed across 2 mountain ranges. Four interpretable modes of variability were observed in average nighttime temperatures among Hobo sites: (1) regional/synoptic; (2) topoclimatic; (3) land surface feedback; (4) canopy cover and vegetation. PC time series captured temporal variability in nighttime temperatures and showed strong relationships with regional air temperatures, sky conditions and atmospheric pressure. PC2 captured the topographic variation among temperatures. A cold air drainage index was created by predicting PC2 loadings to elevation, slope position and dissection indices. Nightly temperature maps were produced by applying PC time series back to the PC2 loading surface, revealing complex temporal and spatial variation in nighttime temperatures. Further development of both physically and empirically based daily temperature models that account for synoptic atmospheric controls on fine-scale temperature variability in mountain ecosystems are needed to guide future monitoring efforts aimed at assessing the impact of climate change.     

黄土丘陵沟壑区中大流域侵蚀产沙模型与尺度转换研究

由于侵蚀产沙因子时间和空间上的变异性,中大流域的侵蚀产沙过程模拟相对于小流域更为复杂化,目前已存在的物理模型和经验模型均难以很好地运用在中大流域。分析了中大流域的侵蚀产沙特点及已有的模型,认为尺度转换技术是实现大中流域侵蚀产沙模拟研究重要的途径,并对尺度转换的方法进行了探讨。     

Dam construction and ecological change in the riparian forest of the Hadejia – Jama'are floodplain,Nigeria

Riparian forests in the Sahel zone of Africa are of considerable importance for human resource use and for their ecological and conservation value. Typical riparian forest tree species are dependent on river flows and a shallow aquifer, and the community and population structure of riparian forests is related to spatial and temporal patterns of flooding at a site. Therefore, changes in hydrology caused by dams cause changes in floodplain vegetation. This paper explores the spatio-temporal complexity of these changes through an analysis of regeneration in a Nigerian floodplain affected by dams built in the early 1970s. The study shows that under certain conditions, and given sufficient time, riparian forests may be changing to forest types more characteristic of unflooded, upland areas. The results of the study have implications for the way in which the sustainability of developments downstream of large dams are analysed, suggesting that assessment of impacts must take place within temporal parameters relevant to ecological processes and at spatial scales that encompass spatial variation in floodplain ecosystems.     

A stochastic-geometric model of soil variation

Stochastic models of soil variation are used in geostatistical analysis, but in general they bear no relation to our mechanistic understanding of the processes in soil that cause its properties to vary spatially. It is proposed that we require a suitable stochastic model in which space is partitioned into discrete domains as a first step towards random spatial models that incorporate our understanding of processes in soil. Even though the soil is essentially continuous in its spatial variation, there are components of soil variation (e.g. differences between parent materials) which are discontinuous. This paper shows how variogram models can be derived directly from the Poisson Voronoi Tessellation (PVT), a stochastic-geometric partition of d -dimensional space. The PVT variogram models, for d = 2 and 3, were fitted to variograms estimated from data over disparate scales, including computerized tomographic images of soil aggregates (pixels of a few tens of micrometres long) and the land systems of Swaziland. In all cases, PVT variogram models fitted better than the conventional geostatistical ones. The good performance of PVT variogram models at these disparate scales encourages further work on tessellation models for soil variation. In principle such models could incorporate information on underlying factors of soil formation such as the spatial distribution of individual plants, the origin and growth of microbial colonies, spatial processes in soil chemistry (such as reaction–diffusion processes) and geometrical information on boundaries between geological strata or contrasting plant communities. PVT models may therefore be one component of a random model of soil variation which reflects our understanding of soil-forming processes, and so have a stronger scientific basis than the models that are now in standard use.     

LISEM:一个基于GIS的流域土壤流失预报模型

９０年代初,荷兰学者以荷兰南部黄土区土壤侵蚀水土保持规划研究为基础,开发了基于土壤侵蚀物理过程和ＧＩＳ的土壤侵蚀的预报模型－ＬＩＳＥＭ（ＬＩｍｂｕｒｇＳｏｌｉＥｒｏｓｉｏｎＭｏｄｅｌ）为水土保持规划提供了一个支持工具,该模型考虑了土壤侵蚀发生的主要过程,可以与栅格ＧＩＳ集成,并可直接利用遥感动态数据,由于对土壤侵蚀和水文学过程的认识以及土壤水分时空变异性的描述方法还不尽成熟,所以ＬＩＳＥＭ模型仍需     

黄土区小尺度坡面土壤含水率时空变异性研究

土壤含水率在水平和垂直方向上均具有高度的时空异质性,关于水平方向变异的研究取得了很大进展,而对垂直方向变异的研究较为缺乏。为掌握土壤含水率在剖面上的垂直变异特征,采用经典统计、地统计及分形分析相结合的方法,研究了黄土高原典型坡地剖面土壤含水率的时空变异性。结果表明:不同测定时间下的剖面土壤含水率均服从自然对数正态分布,在空间上均表现为中等变异性,沿土层深度方向的变化趋势均为增长型,且这种变化规律具有时间稳定性;剖面土壤含水率在整个研究区域尺度、微尺度上的半方差函数均可用指数模型进行很好地拟合,均表现出强烈的空间依赖性,并且这种规律几乎不随时间的变化而变化;不同测定时间下剖面土壤含水率在整个研究尺度上均表现出有限的自相似性,在小于2.00 m的间距尺度下具有稳定的自相似性,大于2.00 m间距尺度的自相似性比较微弱,分维数的大小与控制土壤含水率的主要过程有关;不同测定时间下剖面土壤含水率的空间自相关性基本一致,即当滞后距离小于3.20 m时为空间正自相关,大于3.20 m时为负自相关,等于3.20 m时为不相关,而在剖面土壤含水率之间的相关性达到了极显著水平。     

Spatiotemporal effects of invertebrates on soil processes

Summary The processes of C and N mineralization carried out by microorganisms are affected directly and indirectly by invertebrates over a wide range of spatial and temporal scales. Microfauna track temporal changes in bacterial and fungal populations in soil microsites, particularly in the rhizosphere, which alters the dynamic balance between N mobilization and immobilization. The feeding activities of mesofauna can determined the distribution, activities and composition of fungal communities. Macrofauna have major effects on fungal and bacterial activities, both directly, through feeding and gut passage, and indirectly, by affecting the microbial environment in litter and soil.Soil biological processes can therefore be considered a hierarchy of successive levels of organization where the macro-, meso- and microfauna influence microbial activities at different scales in the habitat mosaic. The spatial components of this hierarchy are integrated by plant roots; root morphology must therefore define the scales at which the system operates under different plant nutrient regimes.This paper is dedicated to the memory of Professor M. S. Ghilarov in friendship and respect for his contributions to soil zoology     

Estimating the Risk of a Crop Epidemic From Coincident Spatio-temporal Processes

Fusarium Head Blight (FHB), or “scab,” is a very destructive disease that affects wheat crops. Recent research has resulted in accurate weather-driven models that estimate the probability of an FHB epidemic based on experiments. However, these predictions ignore two crucial aspects of FHB epidemics: (1) An epidemic is very unlikely to occur unless the plants are flowering, and (2) FHB spreads by its spores, resulting in spatial and temporal dependence in risk. We develop a new approach that combines existing weather-based probabilities with information on flowering dates from survey data, while simultaneously accounting for spatial and temporal dependence. Our model combines two space-time processes, one associated with pure weather-based FHB risks and the other associated with flowering date probabilities. To allow for scalability, we model spatiotemporal dependence via a process convolutions approach. Our sample-based approach produces a realistic assessment of areas that are persistently at high risk (where the probability of an epidemic is elevated for extended time periods), along with associated estimates of uncertainty. We conclude with the application of our approach to a case study from North Dakota.     

Environmental filtering vs. resource-based niche partitioning in diverse soil animal assemblages

Terrestrial invertebrates constitute most of described animal biodiversity and soil is a major reservoir of this diversity. In the classical attempt to understand the processes supporting biodiversity, ecologists are currently seeking to unravel the differential roles of environmental filtering and competition for resources in niche partitioning processes: these processes are in principle distinct although they may act simultaneously, interact at multiple spatial and temporal scales, and are often confounded in studies of soil communities. We used a novel combination of methods based on stable isotopes and trait analysis to resolve these processes in diverse oribatid mite assemblages at spatial scales at which competition for resources could in principle be a major driver. We also used a null model approach based on a general neutral model of beta diversity. A large and significant fraction of community variation was explainable in terms of linear and periodic spatial structures in the distribution of organic C, N and soil structure: species were clearly arranged along an environmental, spatially structured gradient. However, competition related trait differences did not map onto the distances separating species along the environmental gradient and neutral models provided a satisfying approximation of beta diversity patterns. The results represent the first robust evidence that in very diverse soil arthropod assemblages resource-based niche partitioning plays a minor role while environmental filtering remains a fundamental driver of species distribution.     

天气发生器MulGETS和k-NN对区域历史气象场特征重现能力的比较

传统单站点天气发生器未考虑不同站点气象变量间的空间相关性,导致其在区域影响评价中的应用受到限制,而多站点天气发生器可以克服单站点天气发生器的缺点,近年来得到迅速发展。评估和验证多站点天气发生器对区域历史气象场特征的重现能力是开展影响评价的前提和基础。为此,本研究选取MulGETS（参数型）和k-NN（非参数型）发生器为代表模型,利用湘江流域12个气象站点1981−2010年日序列降水量、最高气温、最低气温资料,通过均值、标准差、偏度、极值、空间相关系数、空间连接度和自相关系数等指标的对比,评估了MulGETS和k-NN模型的优缺点及适用性。结果表明：MulGETS和k-NN模型均较好地再现了原气象场的均值、标准差和偏度,k-NN表现稍好于MulGETS。同时k-NN相比MulGETS在保持气象要素空间相关性上具有优势,特别是降水量的空间间歇性。由于算法本身的限制,k-NN无法模拟出超出历史数据范围的极值,而MulGETS具备一定的极值模拟能力。此外,MulGETS和k-NN在重现原始日尺度降水量的自相关性上均存在不足。总体来看,两个模型各具优势和不足,MulGETS更适于极端气象事件模拟,而k-NN可以更好地体现原始气象场的空间差异,实际使用时应根据不同的研究目的选择合适的模型。     

Patterns and processes of initial terrestrial‐ecosystem development

Ecosystems are characterized as complex systems with abiotic and biotic processes interacting between the various components that have evolved over long‐term periods. Most ecosystem studies so far have been carried out in mature systems. Only limited knowledge exists on the very initial phase of ecosystem development. Concepts on the development of ecosystems are often based on assumptions and extrapolations with respect to structure–process interactions in the initial stage. To characterize the effect of this initial phase on structure and functioning of ecosystems in later stages, it is necessary to disentangle the close interaction of spatial and temporal patterns of ecosystem structural assemblages with processes of ecosystem development. The study of initial, less complex systems could help to better identify and characterize coupled patterns and processes. This paper gives an overview of concepts for the initial development of different ecosystem compartments and identifies open questions and research gaps. The artificial catchment site “Chicken Creek” is introduced as a new research approach to investigate these patterns and processes of initial ecosystem development under defined boundary conditions. This approach allows to integrate the relevant processes with related pattern and structure development over temporal and spatial scales and to derive thresholds and stages in state and functioning of ecosystems at the catchment level.     

Gully erosion and environmental change: importance and research needs

Assessing the impacts of climatic and, in particular, land use changes on rates of soil erosion by water is the objective of many national and international research projects. However, over the last decades, most research dealing with soil erosion by water has concentrated on sheet (interrill) and rill erosion processes operating at the (runoff) plot scale. Relatively few studies have been conducted on gully erosion operating at larger spatial scales.Recent studies indicate that (1) gully erosion represents an important sediment source in a range of environments and (2) gullies are effective links for transferring runoff and sediment from uplands to valley bottoms and permanent channels where they aggravate off site effects of water erosion. In other words, once gullies develop, they increase the connectivity in the landscape. Many cases of damage (sediment and chemical) to watercourses and properties by runoff from agricultural land relate to (ephemeral) gullying. Consequently, there is a need for monitoring, experimental and modelling studies of gully erosion as a basis for predicting the effects of environmental change (climatic and land use changes) on gully erosion rates.In this respect, various research questions can be identified. The most important ones are:

What is the contribution of gully erosion to overall soil loss and sediment production at various temporal and spatial scales and under different climatic and land use conditions?

What are appropriate measuring techniques for monitoring and experimental studies of the initiation and development of various gully types at various temporal and spatial scales?

Can we identify critical thresholds for the initiation, development and infilling of gullies in different environments in terms of flow hydraulics, rain, topography, soils and land use?

How does gully erosion interact with hydrological processes as well as with other soil degradation processes?

What are appropriate models of gully erosion, capable of predicting (a) erosion rates at various temporal and spatial scales and (b) the impact of gully development on hydrology, sediment yield and landscape evolution?

What are efficient gully prevention and gully control measures? What can be learned from failures and successes of gully erosion control programmes?

These questions need to be answered first if we want to improve our insights into the impacts of environmental change on gully erosion. This paper highlights some of these issues by reviewing recent examples taken from various environments.     

NCAR/CLM系列陆面模式对内蒙古地表温度的模拟评估

地表温度是影响陆-气之间能量和物质交换的重要地球物理变量,对调节全球气候系统能量循环起着不可或缺的作用。为探讨美国国家大气研究中心(The National Center for Atmospheric Research,NCAR)公共陆面模式(Community Land Model,CLM)对地表温度的模拟能力,利用1948—2004年美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)大气强迫场和NCAR陆面模式CLM3.0、CLM3.5、CLM4.0和CLM4.5对内蒙古地区1981—2004年的地表温度进行off-line模拟,并与观测地面温度资料进行对比。结果表明:NCAR/CLM系列陆面模式模拟地表温度都能较好地再现内蒙古地表温度的时空变化特征,与台站观测有着较好的一致性,其中CLM4.5在内蒙古地区模拟能力最好,与观测的相关系数最高、平均偏差和均方根误差都最小,这主要得益于CLM4.5对粗糙度计算的改进;不同版本CLM模拟地表温度普遍较观测数值偏低,在冬季各版本CLM模拟结果与观测值之间的平均偏差达到最小,在夏季的偏差增大,尤其是在东部地区,夏季偏差3℃以上,说明对最高地表温度的模拟能力东部和中部地区明显低于西部地区;西部地区各个版本差别并不如东部和中部地区明显,这与CLM4.0和CLM4.5改进了雪模式和水文过程有关。综上,CLM4.0和CLM4.5在内蒙古地区有较好的适用性,且模拟值均低于实测地表温度,冬季偏差较小,夏季偏差增大,东部地区偏差大于中部和西部地区。     

Continuous-Time Proportional Hazards Regression for Ecological Monitoring Data

We consider a continuous-time proportional hazards model for the analysis of ecological monitoring data where subjects are monitored at discrete times and fixed sites across space. Since the exact time of event occurrence is not directly observed, we rely on dichotomous event indicators observed at monitoring times to make inference about the model parameters. We use autoregression on the response at neighboring sites from a previous time point to take into account spatial dependence. The interesting fact is utilized that the probability of observing an event at a monitoring time when the underlying hazards is proportional falls under the class of generalized linear models with binary responses and complementary log-log link functions. Thus, a maximum likelihood approach can be taken for inference and the computation can be carried out using standard statistical software packages. This approach has significant computational advantages over some of the existing methods that rely on Monte Carlo simulations. Simulation experiments are conducted and demonstrate that our method has sound finite-sample properties. A real dataset from an ecological study that monitored bark beetle colonization of red pines in Wisconsin is analyzed using the proposed models and inference. Supplementary materials that contain technical details are available online.     

Modeling Tree Loss Versus Tree Recruitment Processes in SW Iberian Rangelands as Influenced by Topography and Land use and Management

The sustainability of Iberian open wooded rangelands is threatened by recent land use changes and lack of tree recruitment. As trees are key elements of these systems, the characterization of their spatiotemporal trend is essential for the system's management. Our objective is to develop spatial models reflecting the temporal dynamic of trees in terms of recent tree loss and tree gain processes in farms, evaluating the influence on the models of topography and land use and management. Aerial photographs of 1956 and 2009 were compared, analyzing lost and new trees in five dehesas of Extremadura (Spain). Multivariate adaptive regression splines was used to produce the spatial models that characterize the proneness of an area to undergo tree loss or recruitment. Models showed good performances. Although land use and management intensively influenced on tree dynamics, because it depends on topography, models built by considering just the topographic variables showed only slightly lower fitness. Tree recruitment mostly happened in the marginal places with steep slopes, while tree loss occurred in elevated, gently undulated and more intensively used places of the farms. A spatial polarization of both processes has been observed that leads to the lack of replacement of lost trees. The work provides some clues on the design of tree management procedures for dehesas and montados. The implementation of measures to address the degradation processes in dehesas should take into account the spatial arrangement of the areas where tree loss or gain is actually happening or it is likely to occur. Copyright © 2017 John Wiley & Sons, Ltd.     

Computationally Efficient Statistical Differential Equation Modeling Using Homogenization

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA. This article has supplementary material online.     

Testing the MEDALUS hillslope model

In the Mediterranean environment formative erosional and runoff events are sporadic, intense and infrequent. They are difficult to study, their effects difficult to anticipate and the impact of vegetational and climatic change, whether natural or human-induced, difficult to predict. For these reasons, modelling has to augment the traditional approaches. In the Mediterranean Desertification and Land Use research programme, models have been developed to look at these problems at the hillslope (MEDALUS model) and large catchment scale (MEDRUSH model). Such models are only as good as their capacity to replicate, to an acceptable level, the magnitude, pattern in space and time and character of real world processes. These models can be tested by (a) examining their logical structure and performance against synthetic or control data (primary level) (b) evaluating their behaviour against published empirical spatial and temporal data (secondary level) and (3) by direct comparison with field test data (real world validation).The MEDALUS catena model comprises atmospheric, plant growth, overland flow and erosion, and subsurface water redistribution components involving a number of important novel features especially for dryland environments. It produces vegetation biomass and storm event runoff and sediment yield for different positions over a hillslope at different times. It is here tested against plot data for events and vegetation, soil moisture, runoff, erosion and slope armouring for annual series over several years. The model is found to perform moderately well for runoff and very well for sediment yield for event-based simulations. The results for longer simulations, tested at the secondary level, perform well in comparison with responses cited in the literature.     

Quantifying suspended sediment sources during runoff events in headwater catchments using spectrocolorimetry

Purpose

Understanding hydro-sedimentary dynamics at the catchment scale requires high temporal resolution data on suspended sediments such as their origin, in addition to the common measurements of sediment concentrations and discharges. Some rapid and low-cost fingerprinting methods based on spectroscopy have recently been developed. We investigated how visible spectra could be used to predict the proportion of various source materials in suspended sediment samples, paying particular attention to the potential alteration of spectrocolorimetric signatures between soils and suspended sediments during transport.

Materials and methods

The 22-km² Galabre catchment, France, is composed of black marls, limestones, molasses, undifferentiated deposits and gypsum. Forty-eight source materials were sampled and 328 suspended sediment samples were collected at the outlet during 23 runoff events. Measurements were taken with a diffuse reflectance spectrophotometer on dried samples. As the erosion processes are particle size selective, five particle size fractions of source material were measured in order to assess the potential alteration of the fingerprint signatures. As the biogeochemical processes occurring in the river could also affect the signatures, source materials were immersed in the river for durations ranging from 1 to 63 days and subsequently measured. Finally, partial least-squares regression models were constructed on 81 artificial laboratory mixtures to predict the proportions of source materials.

Results and discussion

The spectrocolorimetric measurements discriminated the primary source materials but not the Quaternary deposits. As the gypsum was not conservative, only the black marls, molasses and limestones were used in the fingerprinting procedure. The construction of the partial least-squares regression models led to a median absolute error of 1.1%. This error increased to 3.9% when the models were applied to source samples with: (1) different particle sizes; (2) different durations spent in the river; or (3) different origins than those used for their construction. The effect of particle size on the fingerprinting procedure was larger than the effect of biogeochemical reactions or the spatial variability of the spectrocolorimetric signatures. Half of the 23 runoff events analysed exhibited huge variations in the source proportions from one sediment sample to another.

Conclusions

The spectrocolorimetric fingerprinting approach was able to quantify routinely the proportion of primary source materials in all suspended sediment samples collected during runoff events. The high temporal resolution of the predicted proportions revealed that only analysing three or four suspended sediment samples during a runoff event could lead to a misunderstanding of the hydro-sedimentary processes for more than half of the investigated runoff events.