Temporal Scale Of Analysis Research Articles

Errors in climate datasets and their effects on statistical crop models

Although weather data are widely acknowledged to contain measurement errors, the implications of these errors for models that relate weather to yields have not been adequately examined. From statistical theory and applications in many other fields, it is clear that measurement error in a single predictor variable can lead to bias in estimating the effects of that variable, as well as any other correlated predictors. Of particular concern for statistical crop models is that errors in measuring precipitation can lead to bias in inferences about yield responses to both temperature and precipitation. In this study, simulation extrapolation (SIMEX) is used to gauge the importance of measurement error for two recent studies that employed statistical crop models. In both cases, estimates of yield responses to temperature were only slightly changed when considering measurement errors. However, yield responses to precipitation were significantly larger when assuming that precipitation is measured with 30% error, compared to the common assumption of error-free measurements. Thus, results indicate that studies that ignore measurement errors are unlikely to be biased for estimating T sensitivity of yields, but can easily underestimate P sensitivity by a factor of two or more. More work is needed to test effects of measurement errors in other cases, as well as to better quantify the magnitudes of errors in weather measurements for cropped regions. As a rough substitute for detailed measurement error analysis, sensitivity tests that double the yield response to precipitation are advised when applying statistical crop models to projections from climate ensembles. Depending on the magnitude of precipitation projections, which in turn depend on the spatial and temporal scale of analysis, the conclusions of a study may or may not be altered by considering the effects of measurement errors.

Windows of change: temporal scale of analysis is decisive to detect ecosystem responses to climate change

Long-term ecological research has become a cornerstone of the scientific endeavour to better understand ecosystem responses to environmental change. This paper provides a perspective on how such research could be advanced. It emphasizes that a profound understanding of the mechanisms underlying these responses requires that records of ecologic processes be not only sufficiently long, but also collected at an appropriate temporal resolution. We base our argument on an overview of studies of climate impacts in limnic and marine ecosystems, suggesting that lakes and oceans respond to (short-term) weather conditions during critical time windows in the year. The observed response patterns are often time-lagged or driven by the crossing of thresholds in weather-related variables (such as water temperature and thermal stratification intensity). It becomes clear from the previous studies that average annual, seasonal or monthly climate data often fall short of characterizing the thermal dynamics that most organisms respond to. To illustrate such literature-based evidence using a concrete example, we compare 2 years of water temperature data from Muggelsee (Berlin, Germany) at multiple temporal scales (from hours to years). This comparison underlines the pitfalls of analysing data at resolutions not high enough to detect critical differences in environmental forcing. Current science initiatives that aim at improving the temporal resolution of long-term observatory data in aquatic systems will help to identify adequate timescales of analysis necessary for the understanding of ecosystem responses to climate change.

The Goldilocks effect: intermittent streams sustain more plant species than those with perennial or ephemeral flow

Summary1. Drylands worldwide are typified by extreme variability in hydrologic processes, which structures riparian communities at various temporal and spatial scales. One key question is how underlying differences in hydrology over the length of interrupted perennial rivers influence spatial and temporal patterns in species richness and species composition.2. We examined effects of differences in dry season hydrology on species richness, composition and cover of herbaceous plant communities in the streamside zone (the zone influenced directly by low flows in the channel). Data were collected at ephemeral, intermittent and perennial flow reaches on three rivers of the desert Southwest (Arizona, U.S.A.): Lower Cienega Creek, Hassayampa River and Lower San Pedro River.3. Patterns of species richness varied with temporal scale of analysis, that is between single‐year and multi‐year time frames. At the annual timescale, quadrat species richness (m−2) and herbaceous cover were higher at sites with perennial flow than at either intermittent or ephemeral sites. In contrast to this single‐year pattern, the highest long‐term richness occurred at intermittent sites.4. Quadrat species richness, total species richness at a site (per 18 1‐m2 plots) and cover were more variable year to year at non‐perennial sites than at perennial flow sites. On two of the three rivers, ephemeral sites had the highest inter‐annual compositional variance, while the perennial sites had the lowest.5. Compositional differences between the hydrologic site types were dominated by species turnover, not nestedness. The perennial sites had more wetland and perennial species than the other two site types. The intermittent sites had more annual species than did the other two types.6. High long‐term species richness and distinct species composition of intermittent sites are probably sustained by pronounced temporal variability in environmental conditions (i.e. frequent and persistent flow events, and dry periods). Plants at these sites take advantage of greater moisture than those at ephemeral sites and also experience less competition from resident species than those at perennial sites.7. Conservation of desert riparian diversity depends upon the protection of consistently wet conditions at perennial flow sites, as well as the maintenance of the processes that cause fluctuations in environmental conditions at non‐perennial sites.

The U.S. Forest Service's analysis of cumulative effects to wildlife: A study of legal standards, current practice, and ongoing challenges on a National Forest

Cumulative effects analysis (CEA) allows natural resource managers to understand the status of resources in historical context, learn from past management actions, and adapt future activities accordingly. U.S. federal agencies are required to complete CEA as part of environmental impact assessment under the National Environmental Policy Act (NEPA). Past research on CEA as part of NEPA has identified significant deficiencies in CEA practice, suggested methodologies for handling difficult aspects of CEA, and analyzed the rise in litigation over CEA in U.S. courts. This article provides a review of the literature and legal standards related to CEA as it is done under NEPA and then examines current practice on a U.S. National Forest, utilizing qualitative methods in order to provide a detailed understanding of current approaches to CEA. Research objectives were to understand current practice, investigate ongoing challenges, and identify impediments to improvement. Methods included a systematic review of a set of NEPA documents and semi-structured interviews with practitioners, scientists, and members of the public. Findings indicate that the primary challenges associated with CEA include: issues of both geographic and temporal scale of analysis, confusion over the purpose of the requirement, the lack of monitoring data, and problems coordinating and disseminating data. Improved monitoring strategies and programmatic analyses could support improved CEA practice.

INTRODUCTION Crossing thresholds in regional climate research: synthesis of the IPCC expert meeting on regional impacts, adaptation, vulnerability, and mitigation Neil Leary1,*, Kristen Averyt2, Bruce Hewitson3, Jose Marengo4

Contributions of regional scale climate change research to the management of climate risks were explored at a meeting of researchers, policymakers, and practitioners in June 2007 (convened by the Task Group on Data and Scenario Support for Impact and Climate Analysis of the Intergovernmental Panel on Climate Change). Although existing knowledge is already being used to inform a wide variety of decisions in multiple contexts, there remain significant knowledge gaps that hamper effective climate-risk management, particularly at the interfaces of different spatial and temporal scales of analysis and cross-system interactions. In this Introduction we synthe- size discussions of such knowledge gaps, and highlight recommendations for user-oriented research that produces and communicates information that is credible, defensible, and actionable for climate- risk management.

Net changes in aboveground woody carbon stock in western juniper woodlands, 1946–1998

Although regional increases in woody plant cover in semiarid ecosystems have been identified as a worldwide phenomenon affecting the global carbon budget, quantifying the impact of these vegetation shifts on C pools and fluxes is challenging. Challenges arise because woody encroachment is governed by ecological processes that occur at fine spatial resolutions (1–10 m) and, in many cases, at slow (decadal‐scale) temporal rates over large areas. We therefore analyzed time series aerial photography, which exhibits both the necessary spatial precision and temporal extent, to quantify the expansion of western juniper into sagebrush steppe landscapes in southwestern Idaho. We established upper and lower bounds of aboveground woody carbon change across the landscape via two‐dimensional spatial wavelet analysis, image texture analysis, and field data collection. Forty‐eight 100‐ha blocks across a 330,000‐ha region were stratified by topography, soil characteristics, and land stewardship for analyses. Across the area we estimate aboveground woody carbon accumulation rates of 3.3 gCm−2yr−1 and 10.0 gCm−2yr−1 using the wavelet and texture method, respectively, during the time period 1946–1998. Carbon accumulation rates were significantly affected by soil properties and were highly dependent on the spatial and temporal scales of analysis. For example, at a 100‐ha scale the aboveground carbon accumulation varied from −1.7 to 9.9 gCm−2yr−1, while at the 1‐ha scale the range of variability increased to −11 to 22 gCm−2yr−1. These values are an order of magnitude lower than those previously suggested due to woody encroachment, highlighting the need for examining multiple spatial scales when accounting for changes in terrestrial carbon storage.

Spatial boundary choice and the views of different actors

The selection of spatial and temporal scales of analysis is an important and challenging activity at the start of any Policy Analysis or Strategic Environmental Assessment (SEA). The scale sets bounds on the types of problems to be addressed, the solutions to be found and the impacts to be evaluated. Particular scale choices may be more or less beneficial to different actors and are therefore politically loaded. Despite its importance, this topic has rarely been specifically addressed through empirical research. This paper presents an assessment of the impacts of scale choice from varying points of view – those of political actors, commissioners, analysts and scientists – focusing on one type of scale choice: the spatial boundary of the study. An examination of the completed transboundary Long Term Vision Study (LTV) of the Scheldt Estuary, commissioned by the Flemish and Dutch governments, is used to illustrate how actors vary both in the boundaries they choose and the assessment they make of the implications of that boundary choice. Consequently, no perfect spatial scale choice appears to exist. The paper recommends ways to structure the problem of scale selection to facilitate rational deliberation. It is suggested that the methods used to analyse different actors perspectives for the completed LVT study, in future could be employed up-front at the start of other projects. Scale-dependent decision trade-offs could then be made more transparent.

Spatial and temporal dependencies of cross-orientation suppression in human vision

A well-known property of orientation-tuned neurons in the visual cortex is that they are suppressed by the superposition of an orthogonal mask. This phenomenon has been explained in terms of physiological constraints (synaptic depression), engineering solutions for components with poor dynamic range (contrast normalization) and fundamental coding strategies for natural images (redundancy reduction). A common but often tacit assumption is that the suppressive process is equally potent at different spatial and temporal scales of analysis. To determine whether it is so, we measured psychophysical cross-orientation masking (XOM) functions for flickering horizontal Gabor stimuli over wide ranges of spatio-temporal frequency and contrast. We found that orthogonal masks raised contrast detection thresholds substantially at low spatial frequencies and high temporal frequencies (high speeds), and that small and unexpected levels of facilitation were evident elsewhere. The data were well fit by a functional model of contrast gain control, where (i) the weight of suppression increased with the ratio of temporal to spatial frequency and (ii) the weight of facilitatory modulation was the same for all conditions, but outcompeted by suppression at higher contrasts. These results (i) provide new constraints for models of primary visual cortex, (ii) associate XOM and facilitation with the transient magno- and sustained parvostreams, respectively, and (iii) reconcile earlier conflicting psychophysical reports on XOM.

The problem of boundaries in defining ecosystems: A potential landmine for uniting geomorphology and ecology

Forging stronger linkages between geomorphology and ecosystem ecology depends, in part, upon developing common conceptualizations of an ecosystem. Because most ecosystem processes are scale dependent, the choice of boundaries is of profound importance to the conceptualization of an ecosystem and to the scope and validity of questions being asked within that ecosystem. Indeed, any conceptualization of an ecosystem requires constraining the spatial and temporal scales of analysis. Thus, it is of particular importance to match the ecosystem boundaries to the question being asked or to the processes being studied and, to facilitate better communication among disciplines, to be explicit in the definitions adopted for an ecosystem. Defining an ecosystem can be problematic when the processes of interest operate at potentially different scales, and little research exists comparing scales of geomorphic processes with those of ecological processes. Here we will discuss the importance of scale in geomorphic and ecological research, and compare and contrast disciplinary biases and inclinations. To highlight the problem of conflicting spatial scales, we will draw on recent attempts to link the structure of food webs to measures of ecosystem size. In particular, problems arise where little or no strong association exists among community membership, resource supply, and physical boundaries. Similar problems arise when trying to link geomorphologic and ecological processes that can operate at different, but variable, temporal scales.

Assessing the Roles of Patch Quality, Area, and Isolation in Predicting Metapopulation Dynamics

Abstract:Two aspects of patch geometry—area and isolation—currently dominate the field of metapopulation dynamics. Under this area‐and‐isolation paradigm, models commonly assume that the probability of local extinction decreases as patch area increases and that the probability of colonization increases as patch connectivity increases. Environmental variables other than patch area and isolation are assumed to have relatively little effect on metapopulation dynamics. Our work on a metapopulation of the butterflySpeyeria nokomis apacheanahighlights the need for a broader view of metapopulation dynamics. In this system, neither occupancy nor turnover patterns were best modeled as functions of patch area or isolation. Instead, other measures of habitat quality explained the most variance in occupancy and turnover. Our study also revealed temporal variation in the factors associated with occupancy and turnover. This variation can cause the results of analyses to vary with the temporal scale of analysis. For example, factors associated with turnover in this system differed among single‐year and multiple‐year analyses. We emphasize that factors other than patch geometry may drive extinction and colonization processes in metapopulations, especially in systems that experience substantial natural and anthropogenic environmental variability.

Frontiers and Boundaries in Archaeological Perspective

Most archaeological studies of frontiers and boundaries are informed by a colonialist perspective of core-periphery relationships. In this review, we identify three problems with colonialist models of territorial expansion, boundary maintenance, and homogeneousc olonial populations. These problems are (a) insular models of culture change that treat frontiers as passive recipients of core innovations, (b) the reliance on macro scales of analysis employed frontier research, and (c) the expectation of sharp frontier boundaries visible material culture. In the final section, we reconceptualize frontiers as zones of cross-cutting social networks based largely on our research on fur-trade outposts in western North America. Our approach considers the study of diverse and overlapping segmentary or factional groups that cross-cut traditionally perceived colonial-indigenous boundaries on the frontier at different spatial and temporal scales of analysis.