Benchmarks provide context and are a critical element of all ecological assessments. Over the last 25 y, hundreds of papers have been published on various aspects of ecological assessments, and most of the analyses described in these papers depend on specifying an ecological benchmark for context. Freshwater scientists and managers usually use reference sites (typically sites in natural or least-disturbed condition) to assess the ecological conditions at other sites. Accurate and precise assessments require that assessed sites be matched with appropriate reference conditions. Two general types of approaches have been proposed to predict reference conditions: classifications based on natural environmental settings and models that use continuously variable environmental attributes as inputs. Two types of classifications have been examined: geographic-dependent regionalizations based on general landscape features and geographic-independent typologies that are typically based on combinations of regional and channel features. We examined .1000 papers that addressed some aspect of predicting the reference condition in freshwater ecosystems. We focused on 5 types of benchmarks: ecological, thermal, hydrologic, geomorphic, and chemical. Our review showed that over the last 25 y, researchers have developed increasingly sophisticated methods that can be used to predict reference conditions. Most disciplines have increasingly moved toward site-specific modeling approaches as a way to improve both accuracy and precision of predictions, although typological approaches dominate geomorphic characterizations. Papers published in J-NABS have been especially important in advancing and refining methods for predicting ecological benchmarks. Much of the progress made in the science of ecological assessment emerged from research that advanced our understanding of how the spatial and temporal distributions of freshwater biota are related to naturally occurring environmental features and how those relationships can be most accurately and precisely described and predicted. Thus, the performance of ecological assessments is critically linked to how well we characterize freshwater environments, and research in the watershed sciences that addresses predicting thermal, hydrologic, geomorphic, and chemical attributes of freshwater ecosystems has paralleled research focused on predicting biota. We anticipate that knowledge produced from future collaborations between ecologists and watershed scientists coupled with the application of modern modeling techniques will largely determine progress in characterizing and predicting biotaenvironment relationships and, thus, the accuracy and precision of future ecological assessments.

Preface 54There is much interest in using Earth Observation (EO) technology to track biodiversity, 55 ecosystem functions, and ecosystem services, understandable given the fast pace of 56 biodiversity loss. However, because most biodiversity is invisible to EO, EO-based 57 indicators could be misleading, which can reduce the effectiveness of nature 58 conservation and even unintentionally decrease conservation effort. We describe an 59 approach that combines automated recording devices, high-throughput DNA Meeting the Aichi Biodiversity Targets 64From Google Earth to airborne sensors, the Copernicus Sentinels, and cube satellites, 65Earth Observation is undergoing a rapid expansion in capacity, accessibility, resolution, 66and signal-to-noise ratio, resulting in a recognised shift in our capability for using 67 remote-sensing technologies to monitor biophysical processes on land and water [1][2][3] . 68These advances are motivating calls to use Earth Observation products to manage our 69 natural environment and to track progress toward global and national policy targets on 70 biodiversity and ecosystem services [4][5][6] . Foremost among these policies are the Strategic 71Plan for Biodiversity and the Aichi Biodiversity Targets, which were adopted in 2010 by products (net primary productivity and fire incidence) that could serve as Essential 108Biodiversity Variables for the Sahara, despite this biome's suitability for remote sensing 109 due to its visible biodiversity hotspots, remoteness, and availability of long time series. 110Many of the Aichi Targets require data with species-level resolution, either because some 111 species are direct policy targets (e.g. Target 9: "invasive species controlled or eradicated") 112 or because species compositional data define the metric (e.g. Target 11: "protected areas 113 are ecologically representative and conserved effectively"). species, but information could be 'borrowed' from data-rich species to increase the 294 precision of predictions for rare species. These procedures were able to compensate for 295 the fact that only 134 total bird species had been detected in the survey, which is less The GDM was parameterised with a training dataset of 2280 surveys and fourteen 303 environmental variables and explained 57% of the variation in beta diversity. In addition, for linking pure-EO data to biodiversity. 382The major remaining components of uncertainty relate to generalisability, because only a 383 single FSC-certified reserve was sampled; the applicability of results to arboreal species, 384 which tend to be detected more frequently in forests with disturbed canopy but are not 385 necessarily more widespread in these forests; and wide confidence intervals around 386 parameter estimates for some species as a consequence of sparse data and a fairly 394Another example of the CEOBE approach is the use of Generalised Dissimilarity 395Modelling to connect EO-derived metrics of habitat degradation and fragmentation 89,90 396 to over 300 million records of more ...

Wetland salinization. Feeder creek at Bottle Bend Lagoon, a wetland near Midura, Australia, where inadequate water management in the past has led to salinization and acid sulfate soils.

This paper compares the responses of consumers who submitted answers to a survey instrument focusing on Internet purchasing patterns both electronically and using traditional paper response methods. We present the results of a controlled experiment within a larger data collection effort. The same survey instrument was completed by 416 Internet customers of a major office supplies company, with approximately 60% receiving the survey in paper form and 40% receiving the electronic version. In order to evaluate the efficacy of electronic surveys relative to traditional, printed surveys we conduct two levels of analysis. On a macro-level, we compare the two groups for similarity in terms of fairly aggregate, coarse data characteristics such as response rates, proportion of missing data, scale means and inter-item reliability. On a more fine-grained, micro-level, we compare the two groups for aspects of data integrity such as the presence of data runs and measurement errors. This deeper, finer-grained analysis allows an examination of the potential benefits and flaws of electronic data collection.Our findings suggest that electronic surveys are generally comparable to print surveys in most respects, but that there are a few key advantages and challenges that researchers should evaluate. Notably, our sample indicates that electronic surveys have fewer missing responses and can be coded/presented in a more flexible manner (namely, contingent coding with different respondents receiving different questions depending on the response to earlier questions) that offers researchers new capabilities.