Monitoring Long-Term Ecological Changes Through the Ecological Monitoring and Assessment Network: Science-Based and Policy Relevant

Ecological monitoring and its associated research programshave often provided answers to various environmental management issues. In the face of changing environmental conditions, ecological monitoring provides decision-makers with reliable information as they grapple with maintaining a sustainable economy and healthy environment. The EcologicalMonitoring and Assessment Network (EMAN) is a national ecological monitoring network consisting of (1) about 100 casestudy sites across the country characterized by long-term multi-disciplinary environmental work conducted by a multitudeof agencies (142 partners and counting); (2) a variety of lesscomprehensive yet more extensive monitoring sites; (3) a network where core monitoring variables of ecosystem change aremeasured; and (4) geo-referenced environmental observations. Environment Canada is the co-ordinating partner for the network through the EMAN Co-ordinating Office. EMAN's mission is to focus a scientifically-sound, policy-relevant ecosystem monitoring and research network based on (a) stabilizing a network of case-study sites operated by a varietyof partners, and (b) developing a number of cooperative dispersedmonitoring initiatives in order to deliver unique and needed goods and services. These goods and services include: (1) an efficient and cost-effective early warning system which detects,describes and reports on changes in Canadian ecosystems at a national or ecozone scale; and (2) cross-disciplinary and cross-jurisdictional assessments of ecosystem status, trends and processes. The early warning system and assessments of ecosystem status, trends and processes provide Environment Canada and partner organizations with timely information thatfacilitates increasingly adaptive policies and priority setting. Canadians are also informed of changes and trends occurring in Canadian ecosystems and, as a result, are betterable to make decisions related to conservation and sustainability.     

A spatial hierarchical framework for the co-management of ecosystems in Canada and the United States for the upper Great Lakes region

Over the past three decades, considerable effort has been invested in the development of complex and comprehensive ecosystem classifications and inventories in many parts of North America. Paralleling this has been an evolution in those hierarchical frameworks guiding the development and application of classifications. However, resource management agencies continue to grapple with the dilemma of applying multiple classification and inventory templates over large jurisdictions, especially as they attempt to address ecosystem management objectives. Given that Canada and the United States share ecosystems and that commitments have been made by all levels of government to make progress towards ecosystem-based approaches to management, there is a need to provide the proper tools. Comprehensive goals will not be achieved without collaboration and cooperation.This paper outlines the range of ecosystem classification approaches that exist in the Upper Great Lakes region. Canadian and American national hierarchical frameworks are briefly examined. Specific information needs and tasks are outlined which must be followed, independent of national boundaries, for the successful integration of planning and monitoring programs for large regional ecosystems.A general model is proposed for the development and application of an integrated, multi-scale and bi-national ecosystem classification, inventory and information system. This approach would facilitate data sharing and communication across jurisdictional boundaries.     

Forest ecological classification and mapping: Their application for ecosystem management in Newfoundland

A prerequisite to sustaining ecosystems is the inventory and classification of landscape structure and composition. Ecological classification and mapping involves the delineation of landscapes into easily recognizable units. Topography, soils, vegetation, physical landscape form, and successional pathways are delineation criteria commonly used.Damman (1967) developed a forest type classification system for Newfoundland using vegetation, soil and landforms as the defining criteria. Damman's forest types were used in combination with mensurational data to assign forest types to timber volume productivity classes. Since each of the Damman forest types is associated with characteristic soils, parent materials, moisture regime and topographic position, the mapping units are similar to Canada Land Inventory (CLI) mapping units. Field work to confirm the correlation between Damman forest types and CLI capability classes was initiated in 1993. CLI maps were recoded in 1994 and Damman forest types were determined; resulting ecosystem-based maps provide a common framework to assess forestry/wildlife interactions in an ecosystem planning process.     

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.     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

Establishing the Canadian Community Monitoring Network

Community-based ecosystem monitoring activities in Canada are increasing in response to a number of factors including: (i) the needs of decision-makers for timely information on local environmental changes; (ii) limited use of government monitoring data and information by decision makers; (iii) government cuts to monitoring programs; (iv) the increasingly recognized need to include stakeholders in planning and management processes; and (v) the desire of citizens to contribute to environmental protection. To date there has been no network coordination of community based monitoring in Canada. This paper reports on the establishment of the Canadian Community Monitoring Network by Environment Canada's Ecological Monitoring and Assessment Network Coordinating Office and the Canadian Nature Federation. Information on research prepared in support of network establishment is presented along with a discussion of the potential of the network.     

From lake to estuary,the tale of two waters: a study of aquatic continuum biogeochemistry

The balance of fresh and saline water is essential to estuarine ecosystem function. Along the fresh-brackish-saline water gradient within the C-43 canal/Caloosahatchee River Estuary (CRE), the quantity, timing and distribution of water, and associated water quality significantly influence ecosystem function. Long-term trends of water quality and quantity were assessed from Lake Okeechobee to the CRE between May 1978 and April 2016. Significant changes to monthly flow volumes were detected between the lake and the estuary which correspond to changes in upstream management. and climatic events. Across the 37-year period, total phosphorus (TP) flow-weighted mean (FWM) concentration significantly increased at the lake; meanwhile, total nitrogen (TN) FMW concentrations significantly declined at both the lake and estuary headwaters. Between May 1999 and April 2016, TN, TP, and total organic carbon (TOC), ortho-P, and ammonium conditions were assessed within the estuary at several monitoring locations. Generally, nutrient concentrations decreased from upstream to downstream with shifts in TN/TP from values >?20 in the freshwater portion, ~?20 in the estuarine portion, and <?20 in the marine portion indicating a spatial shift in nutrient limitations along the continuum. Aquatic productivity analysis suggests that the estuary is net heterotrophic with productivity being negatively influenced by TP, TN, and TOC likely due to a combination of effects including shading by high color dissolved organic matter. We conclude that rainfall patterns, land use, and the resulting discharges of runoff drive the ecology of the C-43/CRE aquatic continuum and associated biogeochemistry rather than water management associated with Lake Okeechobee.     

The ITE Land classification: Providing an environmental stratification of Great Britain

The surface of Great Britain (GB) varies continuously in land cover from one area to another. The objective of any environmentally based land classification is to produce classes that match the patterns that are present by helping to define clear boundaries. The more appropriate the analysis and data used, the better the classes will fit the natural patterns. The observation of inter-correlations between ecological factors is the basis for interpreting ecological patterns in the field, and the Institute of Terrestrial Ecology (ITE) Land Classification formalises such subjective ideas. The data inevitably comprise a large number of factors in order to describe the environment adequately. Single factors, such as altitude, would only be useful on a national basis if they were the only dominant causative agent of ecological variation.The ITE Land Classification has defined 32 environmental categories called land classes, initially based on a sample of 1-km squares in Great Britain but subsequently extended to all 240 000 1-km squares. The original classification was produced using multivariate analysis of 75 environmental variables. The extension to all squares in GB was performed using a combination of logistic discrimination and discriminant functions. The classes have provided a stratification for successive ecological surveys, the results of which have characterised the classes in terms of botanical, zoological and landscape features.The classification has also been applied to integrate diverse datasets including satellite imagery, soils and socio-economic information. A variety of models have used the structure of the classification, for example to show potential land use change under different economic conditions. The principal data sets relevant for planning purposes have been incorporated into a user-friendly computer package, called the Countryside Information System.     

Limitations of habitats as biodiversity surrogates for conservation planning in estuaries

Increasing pressures on global biodiversity and lack of data on the number and abundance of species have motivated conservation planners and researchers to use more readily available information as proxies or surrogates for biodiversity. “Habitat” is one of the most frequently used surrogates but its assumed value in marine conservation planning is not often tested. The present study developed and tested three alternative habitat classification schemes of increasing complexity for a large estuary in south-east Australia and tested their effectiveness in predicting spatial variation in macroinvertebrate biodiversity and selecting estuarine protected areas to represent species. The three habitat classification schemes were: (1) broad-scale habitats (e.g., mangroves and seagrass), (2) subdivision of each broad-scale habitat by a suite of environmental variables that varied significantly throughout the estuary, and (3) subdivision of each broad-scale habitat by the subset of environmental variables that best explained spatial variation in macroinvertebrate biodiversity. Macroinvertebrate assemblages differed significantly among the habitats in each classification scheme. For each classification scheme, habitat richness was significantly correlated with species richness, total density of macroinvertebrates, assemblage dissimilarity, and summed irreplaceability. However, in a reserve selection process designed to represent examples of each habitat, no habitat classification scheme represented species significantly better than a random selection of sites. Habitat classification schemes may represent variation in estuarine biodiversity; however, the results of this study suggest they are inefficient in designing representative networks of estuarine protected areas.     

Prediction of stream fish assemblages from land use characteristics: implications for cost-effective design of monitoring programmes

Increasing human impact on stream ecosystems has resulted in a growing need for tools helping managers to develop conservations strategies, and environmental monitoring is crucial for this development. This paper describes the development of models predicting the presence of fish assemblages in lowland streams using solely cost-effective GIS-derived land use variables. Three hundred thirty-five stream sites were separated into two groups based on size. Within each group, fish abundance data and cluster analysis were used to determine the composition of fish assemblages. The occurrence of assemblages was predicted using a dataset containing land use variables at three spatial scales (50 m riparian corridor, 500 m riparian corridor and the entire catchment) supplemented by a dataset on in-stream variables. The overall classification success varied between 66.1–81.1% and was only marginally better when using in-stream variables than when applying only GIS variables. Also, the prediction power of a model combining GIS and in-stream variables was only slightly better than prediction based solely on GIS variables. The possibility of obtaining precise predictions without using costly in-stream variables offers great potential in the design of monitoring programmes as the distribution of monitoring sites along a gradient in ecological quality can be done at a low cost.     

A New Statistical Dynamic Analysis of Ecosystem Patterns

While phenomenological investigations of ecosystem patterns often fail to reveal underlying dynamic mechanisms, we highlight a universal principle for pattern formation in ecosystems. We consider ecosystems to be typical complex adaptive systems that seek an optimal process to obtain maximized flux under given constraints. An analysis of the optimal process reveals underlying microscopic dynamic mechanisms that induce complex patterns in ecosystems. We emulate ecosystem patterns using a Self-Organization Feature Map: an artificial neural network theoretical model by which evolution processes, structural classifications, and the fractal growth of ecosystem patterns can be simulated. The results help us analyze the formation and dynamics of ecosystem patterns, with attending implications for the classification, protection, and optimization of ecosystems.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

Ecosystem types of boreal forest in the North Klondike River Valley,Yukon Territory,Canada, and their productivity potentials

Vegetation, environmental characteristics, and forest productivity were studied in the boreal forest in the North Klondike River Valley, Yukon Territory, Canada. The concept and approach of biogeoclimatic ecosystem classification were followed. For the treed vegetation, five ecosystem types were distinguished based on vegetation structure and physical and chemical properties of soils. They were: 1) spruce-lichen type, 2) spruce-moss type, 3) spruce-Equisetum type, 4) spruce-willow type, and 5) bog forest type. These types were differentiated mainly by moisture regime and base status of soils. The sequence of the ecosystem types reflected their topographical position from slope summit to valley bottom. The spruce-lichen type developed in the driest and nutritionally impoverished habitats, the spruce-Equisetum type occurred in moist and nutritionally enriched sites, and the spruce-moss type was found in between them. The bog forest type occurred where peat had accumulated sufficiently to generate ombrotrophic conditions in habitats of high water table underlain with permafrost. The spruce-willow type developed along small creeks where substrates were very coarse. Tree growth characteristics were measured, except for the bog forest type that did not have trees over 5 m tall. Total volume of standing trees ranged from 29 to 582 m³/ha, with an overall mean of 216.9 m³/ha. The spruce-Equisetum type exhibited the highest figure, 413.5 m³/ha, while spruce-lichen type the lowest one, 87.7 m³/ha. Mean annual increment ranged from 0.15 to 2.66 m³/ha, with an overall mean of 1.10 m³/ha. A similar tendency was noted for all other forestry characteristics, i.e., the spruce-Equisetum type showed the highest productivity while the spruce-lichen type the lowest. This tendency was considered to be attributed to the availability of moisture and basic cations in soils.     

Integrating classification and regression tree (CART) with GIS for assessment of heavy metals pollution

The classification and regression tree (CART) model integrated with geographical information systems and the assessment of heavy-metals pollution system was developed to assess the heavy metals pollution in Fuyang, Zhejiang, China. The integration of the decision tree model with ArcGIS Engine 9 using a COM implementation in Microsoft® Visual Basic 6.0 provided an approach for assessing the spatial distribution of soil Zn content with high predictive accuracy. The Zn concentration classes estimated by CART assigned the right classes with an accuracy of near 90%. This is a great improvement compared to the ordinary Kriging method for the spatial autocorrelation of the study area severely destroyed by human activities. Also, it can be used to investigate the inter-relationships between the heavy metals pollution and environmental and anthropogenic variables. Moreover, the research presents model predictions over space for further applications and investigations.     

Combining Accuracy Assessment of Land-Cover Maps with Environmental Monitoring Programs

A scientifically valid accuracy assessment of a large-area, land-cover map is expensive. Environmental monitoring programs offer a potential source of data to partially defray the cost of accuracy assessment while still maintaining the statistical validity. In this article, three general strategies for combining accuracy assessment and environmental monitoring protocols are described. These strategies range from a fully integrated accuracy assessment and environmental monitoring protocol, to one in which the protocols operate nearly independently. For all three strategies, features critical to using monitoring data for accuracy assessment include compatibility of the land-cover classification schemes, precisely co-registered sample data, and spatial and temporal compatibility of the map and reference data. Two monitoring programs, the National Resources Inventory (NRI) and the Forest Inventory and Monitoring (FIM), are used to illustrate important features for implementing a combined protocol.     

面向生态监测与管理的国家级土地生态分类方案研究

遥感能够为生态监测和管理提供有用的技术手段,能够实现生态的持续、快速、动态监测。土地生态分类体系是实现生态遥感的基础。目前世界上已有的土地分类系统基本是从土地利用/土地覆盖或资源调查的角度设计的,尚不能满足宏观生态和管理的需求。该研究提出的面向生态监测与管理的国家级土地生态分类方案就是为了满足这种需求而设计的。     

Classification and mapping forest sites using geographic information system (GIS): a case study in Artvin Province

The productivity of forest sites has been indirectly determined with solo wood production objective in forest management. Forest site productivity should, however, be determined directly in order to implement ecosystem based multipurpose forest management philosophy. This article tackles the problem in distinguishing and mapping forest sites using both direct method and indirect method in Genya Mountain located in central of Artvin State Forest Enterprise. About 112 sample plots were designed and distributed over the area. In each sample plot, soil samples were collected and the classical timber inventory measurements were taken. According to direct method, Soil Moisture Regime (SMR) method is preferred due to a water deficiency in the study area. Water holding capacity was used as an essential criterion for the classification of the forest site. Forest site classifications were assigned regarding the physiographic factors such as landform, aspect, and slope. Five different forest sites classes; dry, moderate fresh, fresh, humid and hygric were determined. According to direct method, the guiding curve was used to generate anamorphic site index (SI) equations and three site index classes; good (SI=I–II), medium (SI=III) and low (SI=IV–V) were determined. Some important differences between the methods were realized. The forest sites determined with site index estimation method indicate that site index I and II is 505.99 ha, III 1095.79 ha and IV and V 992.95 ha, whereas forest sites determined with direct method related to dry site of 937.58 ha, moderate fresh site of 931.90 ha, fresh site of 1,797.71 ha, humid site of 80.48 ha and hygric site of 356.55 ha. The forest site maps of both methods were created using GIS functions. The forest sites of open and degraded areas should be determined according to direct method.     

Benthic Impacts of Intertidal Oyster Culture, with Consideration of Taxonomic Sufficiency

An investigation of the impacts from elevated intertidal Pacific oyster culture in a New Zealand estuary showed enhanced sedimentation beneath culture racks compared with other sites. Seabed elevation beneath racks was generally lower than between them, suggesting that topographic patterns more likely result from a local effect of rack structures on hydrodynamic processes than from enhanced deposition. Compared with control sites, seabed sediments within the farm had a greater silt/clay and organic content, and a lower redox potential and shear strength. While a marked trend in macrofaunal species richness was not evident, species composition and dominance patterns were consistent with a disturbance gradient, with farm effects not evident 35 m from the perimeter of the racks. Of the environmental variables measured, sediment shear strength was most closely associated with the distribution and density of macrofauna, suggesting that human-induced disturbance from farming operations may have contributed to the biological patterns. To evaluate the taxonomic sufficiency needed to document impacts, aggregation to the family level based on Linnean classification was compared with an aggregation scheme based on `general groups' identifiable with limited taxonomic expertise. Compared with species-level analyses, spatial patterns of impact were equally discernible at both aggregation levels used, provided density rather than presence/absence data were used. Once baseline conditions are established and the efficacy of taxonomic aggregation demonstrated, a `general group' scheme provides an appropriate and increasingly relevant tool for routine monitoring.