Review of indicators and field methods for monitoring biodiversity within national forest inventories. Core variable: Deadwood

Deadwood is one of the four elements taken into account in this review of indicators and field methods and is often considered as a key indicator of forest biodiversity. We have analysed the main types of surveys and have realised how greatly the needs and constraints used to monitor deadwood can vary among them. For instance, classical National Forest Inventories usually tend to avoid time-consuming collecting methods. In the wide variety of existing definitions of deadwood, such inventories require simple and clear definitions, especially in terms of quantified thresholds. Thus, deadwood is properly described by characterising several components, such as snags, logs, stumps, branches and fine woody debris. Deadwood sampling methods alter depending on the different components and dimensions considered (standing dead trees, lying dead trees and branches, etc. assessed quantitatively). Attributes such as tree species and stage of decay are used mainly to qualify the deadwood components. The deadwood volume estimations are usually based on classical approaches already applied to living or felled trees: volume equations and/or formulas giving the volumes of common geometric solids. The purpose of this paper is to focus on different deadwood assessment techniques and to provide the information necessary to identify the most relevant methods for collecting deadwood data. The latter is used to build indicators that characterise the evolution of forest biodiversity at the scale of large forest territories.     

Towards a sampling strategy for the assessment of forest condition at European level: combining country estimates

A correct characterization of the status and trend of forest condition is essential to support reporting processes at national and international level. An international forest condition monitoring has been implemented in Europe since 1987 under the auspices of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The monitoring is based on harmonized methodologies, with individual countries being responsible for its implementation. Due to inconsistencies and problems in sampling design, however, the ICP Forests network is not able to produce reliable quantitative estimates of forest condition at European and sometimes at country level. This paper proposes (1) a set of requirements for status and change assessment and (2) a harmonized sampling strategy able to provide unbiased and consistent estimators of forest condition parameters and of their changes at both country and European level. Under the assumption that a common definition of forest holds among European countries, monitoring objectives, parameters of concern and accuracy indexes are stated. On the basis of fixed-area plot sampling performed independently in each country, an unbiased and consistent estimator of forest defoliation indexes is obtained at both country and European level, together with conservative estimators of their sampling variance and power in the detection of changes. The strategy adopts a probabilistic sampling scheme based on fixed-area plots selected by means of systematic or stratified schemes. Operative guidelines for its application are provided.     

Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information

Many countries have a national forest inventory (NFI) designed to produce statistically sound estimates of forest parameters. However, this type of inventory may not provide reliable results for forest damage which usually affects only small parts of the forest in a country. For this reason, specially designed forest damage inventories are performed in many countries, sometimes in coordination with the NFIs. In this study, we evaluated a new approach for damage inventory where existing NFI data form the basis for two-phase sampling for stratification and remotely sensed auxiliary data are applied for further improvement of precision through post-stratification. We applied Monte Carlo sampling simulation to evaluate different sampling strategies linked to different damage scenarios. The use of existing NFI data in a two-phase sampling for stratification design resulted in a relative efficiency of 50 % or lower, i.e., the variance was at least halved compared to a simple random sample of the same size. With post-stratification based on simulated remotely sensed auxiliary data, there was additional improvement, which depended on the accuracy of the auxiliary data and the properties of the forest damage. In many cases, the relative efficiency was further reduced by as much as one-half. In conclusion, the results show that substantial gains in precision can be obtained by utilizing auxiliary information in forest damage surveys, through two-phase sampling, through post-stratification, and through the combination of these two approaches, i.e., post-stratified two-phase sampling for stratification.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Extending large-scale forest inventories to assess urban forests

Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.     

浮游动物DNA宏条形码多样性监测采样方法研究

浮游动物是水生生态系统的重要组成部分,对环境因子敏感,是水生生态健康状况的重要指示生物.基于传统形态学的浮游动物调查方法无法鉴定桡足类幼体,难以准确了解浮游动物群落组成.DNA宏条形码技术基于DNA序列差异识别物种,为浮游动物群落组成的准确解析提供了新方法.比较了不同浮游动物采样方法(直接过滤法和网富集法)对浮游动物D...     

A selection of forest condition indicators for monitoring

Regional monitoring and assessments of the health of forested ecosystems require indicators of forest conditions and environmental stresses. Indicator selections depend on objectives and the strategy for data collection and analysis. This paper recommends a set of indicators to signal changes in forest ecosystem distribution, productivity, and disturbance. Additional measurements are recommended to help ascribe those changes to climate variation, atmospheric deposition, and land use patterns. The rationale for these indicators is discussed in the context of a sequential monitoring and assessment strategy.     

Status and future of the forest health indicators program of the USA

For two decades, the US Department of Agriculture, Forest Service, has been charged with implementing a nationwide field-based forest health monitoring effort. Given its extensive nature, the monitoring program has been gradually implemented across forest health indicators and inventoried states. Currently, the Forest Service??s Forest Inventory and Analysis program has initiated forest health inventories in all states, and most forest health indicators are being documented in terms of sampling protocols, data management structures, and estimation procedures. Field data from most sample years and indicators are available on-line with numerous analytical examples published both internally and externally. This investment in national forest health monitoring has begun to yield dividends by allowing evaluation of state/regional forest health issues (e.g., pollution and invasive pests) and contributing substantially to national/international reporting efforts (e.g., National Report on Sustainability and US EPA Annual Greenhouse Gas Estimates). With the emerging threat of climate change, full national implementation and remeasurement of a forest health inventory should allow for more robust assessment of forest communities that are undergoing unprecedented changes, aiding future land management and policy decisions.     

Evaluating performance of stormwater sampling approaches using a dynamic watershed model

Accurate quantification of stormwater pollutant levels is essential for estimating overall contaminant discharge to receiving waters. Numerous sampling approaches exist that attempt to balance accuracy against the costs associated with the sampling method. This study employs a novel and practical approach of evaluating the accuracy of different stormwater monitoring methodologies using stormflows and constituent concentrations produced by a fully validated continuous simulation watershed model. A major advantage of using a watershed model to simulate pollutant concentrations is that a large number of storms representing a broad range of conditions can be applied in testing the various sampling approaches. Seventy-eight distinct methodologies were evaluated by "virtual samplings" of 166 simulated storms of varying size, intensity and duration, representing 14 years of storms in Ballona Creek near Los Angeles, California. The 78 methods can be grouped into four general strategies: volume-paced compositing, time-paced compositing, pollutograph sampling, and microsampling. The performances of each sampling strategy was evaluated by comparing the (1) median relative error between the virtually sampled and the true modeled event mean concentration (EMC) of each storm (accuracy), (2) median absolute deviation about the median or "MAD" of the relative error or (precision), and (3) the percentage of storms where sampling methods were within 10% of the true EMC (combined measures of accuracy and precision). Finally, costs associated with site setup, sampling, and laboratory analysis were estimated for each method. Pollutograph sampling consistently outperformed the other three methods both in terms of accuracy and precision, but was the most costly method evaluated. Time-paced sampling consistently underestimated while volume-paced sampling over estimated the storm EMCs. Microsampling performance approached that of pollutograph sampling at a substantial cost savings. The most efficient method for routine stormwater monitoring in terms of a balance between performance and cost was volume-paced microsampling, with variable sample pacing to ensure that the entirety of the storm was captured. Pollutograph sampling is recommended if the data are to be used for detailed analysis of runoff dynamics.     

European Farmland Bird Distribution Explained by Remotely Sensed Phenological Indices

Birds are important components of biodiversity conservation since they are capable of indicating changes in the general status of wildlife and of the countryside. The Pan-European Common Bird Monitoring Scheme (PECBM) has been launched by the BirdLife Partnership in Europe, where the European Bird Census Council has been collecting data from 20 independent breeding bird survey programs across Europe over the last 25 years. These data show dramatic declines in European farmland birds. We suggest that seasonal characteristics of vegetation cover derived from high temporal resolution remote sensing images could facilitate the monitoring the suitability of farmland bird habitats, and that these indicators may be a better choice for monitoring than climate data. We used redundancy analysis to link the PECBM data of the estimated number of farmland birds in Europe to a set of phenological and climatic indicators and to the biogeographic regions of Europe. Variance partitioning was used to account for the variation explained by the phenological and climate variables and by the area of the environmental strata individually, to define the pure effect of the variables, and to extract the total explained variance. The analysis revealed high statistical significance (p < 0.001) of the correlations between species and environment. Phenological indices explained 38% of the variance in community composition of the 23 farmland bird species, whereas climate explained 30% of the variance. After partitioning the other variables as covariables, the pure effect of phenology, climate, and environmental strata were 16%, 8%, and 16%, respectively. Based on the probability results, we suggest that phenological indicators derived from remote sensing may supply better indicators for continental scale biodiversity studies than climate only. In addition, these indicators are cost and time effective, are on continuous scale, and are readily repeatable on a large spatial coverage while supplying standardized results.     

Sampling The Soil In Long-Term Forest Plots: The Implications Of Spatial Variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.     

Addressing statistical and operational challenges in designing large-scale stream condition surveys

Implementing a statistically valid and practical monitoring design for large-scale stream condition monitoring and assessment programs can be difficult due to factors including the likely existence of a diversity of ecosystem types such as ephemeral streams over the sampling domain; limited resources to undertake detailed monitoring surveys and address knowledge gaps; and operational constraints on effective sampling at monitoring sites. In statistical speak, these issues translate to defining appropriate target populations and sampling units; designing appropriate spatial and temporal sample site selection methods; selection and use of appropriate indicators; and setting effect sizes with limited ecological and statistical information about the indicators of interest. We identify the statistical and operational challenges in designing large-scale stream condition surveys and discuss general approaches for addressing them. The ultimate aim in drawing attention to these challenges is to ensure operational practicality in carrying out future monitoring programs and that the resulting inferences about stream condition are statistically valid and relevant.     

Developing a National Indicator of Soil Quality on U.S Forestlands: Methods and Initial Results

The Montreal Process was formed in 1994 to develop an internationally agreed upon set of criteria and indicators for the conservation and sustainable management of temperate and boreal forests. In response to this initiative, the Forest Inventory and Analysis (FIA) and Forest Health Monitoring (FHM) programs of the United States Department of Agriculture Forest Service have implemented soil measurements as part of a national monitoring program to address specific questions related to the conservation of soil and water resources. Integration of soil assessments into the national FIA program provides for systematic monitoring of soil properties across all forested regions of the U.S. using standardized collection, laboratory, and statistical procedures that are compatible with existing forest inventory data. The resulting information will provide quantitative benchmarks for regional, national, and international reporting on sustainable forest management and enhance our understanding of management effects on soil quality. This paper presents an overview of the FIA soil monitoring program, outlines the field and laboratory protocols as currently implemented, and provides examples of how these data may be used to assess indicators of sustainable management as defined by the Montreal Process.     

Towards a more holistic sustainability assessment framework for agro-bioenergy systems — A review

The use of life cycle assessment (LCA) as a sustainability assessment tool for agro-bioenergy system usually has an industrial agriculture bias. Furthermore, LCA generally has often been criticized for being a decision maker tool which may not consider decision takers perceptions. They are lacking in spatial and temporal depth, and unable to assess sufficiently some environmental impact categories such as biodiversity, land use etc. and most economic and social impact categories, e.g. food security, water security, energy security. This study explored tools, methodologies and frameworks that can be deployed individually, as well as in combination with each other for bridging these methodological gaps in application to agro-bioenergy systems. Integrating agronomic options, e.g. alternative farm power, tillage, seed sowing options, fertilizer, pesticide, irrigation into the boundaries of LCAs for agro-bioenergy systems will not only provide an alternative agro-ecological perspective to previous LCAs, but will also lead to the derivation of indicators for assessment of some social and economic impact categories. Deploying life cycle thinking approaches such as energy return on energy invested-EROEI, human appropriation of net primary production-HANPP, net greenhouse gas or carbon balance-NCB, water footprint individually and in combination with each other will also lead to further derivation of indicators suitable for assessing relevant environmental, social and economic impact categories. Also, applying spatio-temporal simulation models has a potential for improving the spatial and temporal depths of LCA analysis.     

Local versus landscape spatial influence on biodiversity: a case study across five European industrialized areas

Land use change—mostly habitat loss and fragmentation—has been recognized as one of the major drivers of biodiversity loss worldwide. According to the habitat amount hypothesis, these phenomena are mostly driven by the habitat area effect. As a result, species richness is a function of both the extent of suitable habitats and their availability in the surrounding landscape, irrespective of the dimension and isolation of patches of suitable habitat. In this context, we tested how the extent of natural areas, selected as proxies of suitable habitats for biodiversity, influences species richness in highly anthropogenic landscapes. We defined five circular sampling areas of 5 km radius, including both natural reserves and anthropogenic land uses, centred in five major industrial sites in France, Italy and Germany. We monitored different biodiversity indicators for both terrestrial and aquatic ecosystems, including breeding birds, diurnal butterflies, grassland vegetation, odonata, amphibians, aquatic plants and benthic diatoms. We studied the response of the different indicators to the extent of natural land uses in the sampling area (local effect) and in the surrounding landscape (landscape effect), identified as a peripheral ring encircling the sampling area. Results showed a positive response of five out of seven biodiversity indicators, with aquatic plants and odonata responding positively to the local effect, while birds, vegetation and diatoms showed a positive response to the landscape effect. Diatoms also showed a significant combined response to both effects. We conclude that surrounding landscapes act as important biodiversity sources, increasing the local biodiversity in highly anthropogenic contexts.     

Measurement of Atmospheric Deposition Under Forest Canopies: Some Recommendations for Equipment and Sampling Design

Quantification of the forest water flux provides valuable information for the understanding of forest ecosystem functioning. As such, throughfall (and stemflow to a lesser extent) has been frequently measured. Although throughfall collection may seem relatively simple, the requirements to obtain reliable estimates are often underestimated. This review addresses the criteria to take into account when working out the sampling procedure, from the selection of equipment to implementation in the field. Sound sampling of the forest water flux is difficult due to its high spatial and temporal variation. The high costs entailed by the ideal sampling design often prohibit its implementation. Different procedures are available, some of which are compromises between the aim of the study (monitoring or experimental study, short or long term objectives, absolute or relative estimates, quality of the assessment to be achieved) and the available means.     

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Monitoring of Biodiversity Indicators in Boreal Forests: a Need for Improved Focus

The general principles of scale and coarse and fine filters have been widely accepted, but management agencies and industry are still grappling with the question of what to monitor to detect changes in forest biodiversity following forest management. Part of this problem can be attributed to the lack of focused questions for monitoring including absence of null models and predicted effects, a certain level of disconnect between research and management, and recognition that monitoring can be designed as a research question. Considerable research from the past decade has not been adequately synthesized to answer important questions, such as which species or forest attributes might be the best indicators of change. A disproportionate research emphasis has been placed on community ecology, and mostly on a few groups of organisms including arthropods, amphibians, migratory songbirds, and small mammals, while other species, including soil organisms, lichens, bats, raptors, some carnivores, and larger mammals remain less well-known. In most studies of community ecology, the question of what is the importance, if any, of the regularly observed subtle changes in community structures, and causes of observed changes is usually not answered. Hence, our ability to deal with questions of persistence is limited, and demographic research on regionally--defined key species (such as species linked to processes, species whose persistence may be affected, species with large home ranges, species already selected as indicators, and rare and threatened species) is urgently needed. Monitoring programs need to be designed to enable managers to respond to unexpected changes caused by forest management. To do this, management agencies need to articulate null models for monitoring that predict effects, focus fine--scale monitoring on key species (defined by local and regional research) in key habitats (rare, declining, important) across landscapes, and have a protocol in place to adapt management strategies to changes observed. Finally, agencies must have some way to determine and define when a significant change has occurred and to predict the persistence of species; this too should flow from a well--designed null model.     

Alberta Biodiversity Monitoring Program – Monitoring Effectiveness of Sustainable Forest Management Planning

A conceptual model of sustainable forest management is described based on three connected and necessary components: Policy/Strategic Planning, Operational Planning, and EffectivenessMonitoring/Science.Alberta’s proposed Forest Management Planning Standard is described as an example of operational planning. The standard utilizes coarse and fine filter approaches to conserving biodiversity and sets requirements for implementation monitoring.The Alberta Biodiversity Monitoring Program (ABMP) is described as an example of effectiveness monitoring supporting Operational Planning. The ABMP is a rigorous science-based initiative that is being developed to monitor and report on biodiversity status and trends throughout the province of Alberta, Canada. The basic survey design consists of 1656 sites, 20 km apart, evenly spaced on a grid pattern across Alberta. Sites will be sampled over a five-year period at a rate of 350 sites/year. Standardized sampling protocols will be used to cover a broad range of species and habitat elements within terrestrial and aquatic environments, as well as broader landscape-level features.Trends and associations detected by ABMP products will be validated through cause-effect research. ABMP focuses research on critical issues and informs both operational planning and the development of policy and strategic-level plans. The Alberta Forest Management Planning Standard and the ABMP are described as key components to implementing resource planning based on ecosystem management principles.     

我国流域水生态完整性评价方法构建

流域水生态完整性评价是指通过对水生态系统中不同水生态指标(生物和非生物)的监测以及由数学方法综合形成的综合评价指数,来反映水生态系统完整性状况。近年来,世界各国水环境管理政策发生了变化,开始强调生态保护,重视水体的生态质量。中国现行的常规理化监测指标(如COD、氨氮、BOD5)很难满足水环境管理的需求,难以全面准确地反映水环境质量变化的趋势。因此,在借鉴欧美发达国家流域水生态完整性评价方法的基础上,结合中国目前监测现状以及流域水环境管理需求,构建了包括物理生境指标、理化指标、水生生物指标在内的流域水生态完整性监测与评价方法,以期为中国流域水质目标管理技术体系的业务化运行提供可资借鉴的技术支撑,实现从单一的化学指标监测转向综合的水生态系统监测,实现流域水生态完整性的监测与评价。