Two-dimensional gap analysis: a tool for efficient conservation planning and biodiversity policy implementation

The maintenance of biodiversity by securing representative and well-connected habitat networks in managed landscapes requires a wise combination of protection, management, and restoration of habitats at several scales. We suggest that the integration of natural and social sciences in the form of "Two-dimensional gap analysis" is an efficient tool for the implementation of biodiversity policies. The tool links biologically relevant "horizontal" ecological issues with "vertical" issues related to institutions and other societal issues. Using forest biodiversity as an example, we illustrate how one can combine ecological and institutional aspects of biodiversity conservation, thus facilitating environmentally sustainable regional development. In particular, we use regional gap analysis for identification of focal forest types, habitat modelling for ascertaining the functional connectivity of "green infrastructures", as tools for the horizontal gap analysis. For the vertical dimension we suggest how the social sciences can be used for assessing the success in the implementation of biodiversity policies in real landscapes by identifying institutional obstacles while implementing policies. We argue that this interdisciplinary approach could be applied in a whole range of other environments including other terrestrial biota and aquatic ecosystems where functional habitat connectivity, nonlinear response to habitat loss and a multitude of economic and social interests co-occur in the same landscape.     

Nitrogen dynamics in managed boreal forests: Recent advances and future research directions

Nitrogen (N) availability plays multiple roles in the boreal landscape, as a limiting nutrient to forest growth, determinant of terrestrial biodiversity, and agent of eutrophication in aquatic ecosystems. We review existing research on forest N dynamics in northern landscapes and address the effects of management and environmental change on internal cycling and export. Current research foci include resolving the nutritional importance of different N forms to trees and establishing how tree–mycorrhizal relationships influence N limitation. In addition, understanding how forest responses to external N inputs are mediated by above- and belowground ecosystem compartments remains an important challenge. Finally, forestry generates a mosaic of successional patches in managed forest landscapes, with differing levels of N input, biological demand, and hydrological loss. The balance among these processes influences the temporal patterns of stream water chemistry and the long-term viability of forest growth. Ultimately, managing forests to keep pace with increasing demands for biomass production, while minimizing environmental degradation, will require multi-scale and interdisciplinary perspectives on landscape N dynamics.     

Consequence of altered nitrogen cycles in the coupled human and ecological system under changing climate: The need for long-term and site-based research

Anthropogenically derived nitrogen (N) has a central role in global environmental changes, including climate change, biodiversity loss, air pollution, greenhouse gas emission, water pollution, as well as food production and human health. Current understanding of the biogeochemical processes that govern the N cycle in coupled human–ecological systems around the globe is drawn largely from the long-term ecological monitoring and experimental studies. Here, we review spatial and temporal patterns and trends in reactive N emissions, and the interactions between N and other important elements that dictate their delivery from terrestrial to aquatic ecosystems, and the impacts of N on biodiversity and human society. Integrated international and long-term collaborative studies covering research gaps will reduce uncertainties and promote further understanding of the nitrogen cycle in various ecosystems.     

A systematic review of biodiversity and demographic change: A misinterpreted relationship?

Demographic change is supposed to be the most important indirect driver for changing biodiversity. In this article, a systematic review of 148 studies was conducted to examine the scientific evidence for this relationship and to identify potential gaps in research. We explored the spatial distribution of studies, the categories addressed with respect to biodiversity and demographic change, and the ways in which their relationships were conceptualised (spatially and temporally) and valued. The majority of studies were carried out in Africa, Europe and North America. Our analysis confirms the trend that demographic phenomena were mostly found to negatively influence biodiversity. However, a considerable number of studies also point towards impacts that were context dependent, either positive or negative under certain circumstances. In addition to that we identified significant gaps in research. In particular, there is a lack of addressing (1) other demographic aspects such as population decline, age structure or gender differences, (2) spatial variability of, e.g. human population growth, (3) long-term effects of demographic processes, and (4) the context dependency (e.g. regulations/law enforcement, type of human activities, and choice of scale or proxy). We conclude there is evidence that the relationship between biodiversity and demographic change is much more complex than expected and so far represented in research. Thus, we call for a social–ecological biodiversity research that particularly focusses on the functional relation between biodiversity and human activities, namely the different types, context, and interdependent dynamics (spatial and temporal) of this complex relation.

     

New Perspectives on Marine Biodiversity

Marine and terrestrial ecosystems are so fundamentally different in some aspects that many of the issues concerning biodiversity cannot be interpreted using a single theory of common application to all ecosystems. Their limitation is evident when it comes to highly biodiverse and interconnected marine ecosystems such as coral reefs. Trophic links are a major factor, but space, breeding, shelter from predators, environmental cues, behavior ingrained in genotypes, genetic variability, mutations, and connectivity of marine critical habitats are also important. The importance of the connectivity of habitats such as coral reefs, seagrasses, and mangrove in biodiversity preservation should be recognized. Migratory species require corridors for gene flow and that influences diversity. The existing theories do not address the biodiversity issues related to life in the abyssal plains and deep sea trenches and the challenge posed by climate change. An accurate understanding of marine biodiversity requires comprehensive knowledge of ecological interrelationships and new perspectives that reflect the reality of global environmental change.     

Balancing urban growth and ecological conservation: A challenge for planning and governance in China

China has high biodiversity and is rapidly urbanizing. However, there is limited understanding of how urban expansion in the country is likely to affect its habitats and biodiversity. In this study, we examine urban expansion patterns and their likely impacts on biodiversity in China by 2030. Our analysis shows that most provinces are expected to experience urban expansion either near their protected areas or in biodiversity hotspots. In a few provinces such as Guangdong in the south, urban expansion is likely to impinge on both protected areas and biodiversity hotspots. We show that policies that could facilitate the integration of natural resource protection into urban planning exist on paper, but the prevailing incentives and institutional arrangements between the central and local governments prevent this kind of integration. Removing these obstacles will be necessary in order to safeguard the country’s rich biodiversity in light of the scale of urbanization underway.     

Ecosystem Response to Climatic Change: The Importance of the Cold Season

Winter climate and snow cover are the important drivers of plant community development in polar regions. However, the impacts of changing winter climate and associated changes in snow regime have received much less attention than changes during summer. Here, we synthesize the results from studies on the impacts of extreme winter weather events on polar heathland and lichen communities. Dwarf shrubs, mosses and soil arthropods were negatively impacted by extreme warming events while lichens showed variable responses to changes in extreme winter weather events. Snow mould formation underneath the snow may contribute to spatial heterogeneity in plant growth, arthropod communities and carbon cycling. Winter snow cover and depth will drive the reported impacts of winter climate change and add to spatial patterns in vegetation heterogeneity. The challenges ahead lie in obtaining better predictions on the snow patterns across the landscape and how these will be altered due to winter climate change.     

Ecosystem response to climatic change: the importance of the cold season

Winter climate and snow cover are the important drivers of plant community development in polar regions. However, the impacts of changing winter climate and associated changes in snow regime have received much less attention than changes during summer. Here, we synthesize the results from studies on the impacts of extreme winter weather events on polar heathland and lichen communities. Dwarf shrubs, mosses and soil arthropods were negatively impacted by extreme warming events while lichens showed variable responses to changes in extreme winter weather events. Snow mould formation underneath the snow may contribute to spatial heterogeneity in plant growth, arthropod communities and carbon cycling. Winter snow cover and depth will drive the reported impacts of winter climate change and add to spatial patterns in vegetation heterogeneity. The challenges ahead lie in obtaining better predictions on the snow patterns across the landscape and how these will be altered due to winter climate change.     

Nitrogen biogeochemistry in the Adirondack Mountains of New York: hardwood ecosystems and associated surface waters

Studies on the nitrogen (N) biogeochemistry in Adirondack northern hardwood ecosystems were summarized. Specific focus was placed on results at the Huntington Forest (HFS), Pancake-Hall Creek (PHC), Woods Lake (WL), Ampersand (AMO), Catlin Lake (CLO) and Hennessy Mountain (HM). Nitrogen deposition generally decreased from west to east in the Adirondacks, and there have been no marked temporal changes in N deposition from 1978 through 1998. Second-growth western sites (WL, PHC) had higher soil solution NO(3-) concentrations and fluxes than the HFS site in the central Adirondacks. Of the two old-growth sites (AMO and CLO), AMO had substantially higher NO(3-) concentrations due to the relative dominance of sugar maple that produced litter with high N mineralization and nitrification rates. The importance of vegetation in affecting N losses was also shown for N-fixing alders in wetlands. The Adirondack Manipulation and Modeling Project (AMMP) included separate experimental N additions of (NH4)2SO4 at WL, PHC and HFS and HNO3 at WL and HFS. Patterns of N loss varied with site and form of N addition and most of the N input was retained. For 16 lake/watersheds no consistent changes in NO(3-) concentrations were found from 1982 to 1997. Simulations suggested that marked NO(3-) loss will only be manifested over extended periods. Studies at the Arbutus Watershed provided information on the role of biogeochemical and hydrological factors in affecting the spatial and temporal patterns of NO(3-) concentrations. The heterogeneous topography in the Adirondacks has generated diverse landscape features and patterns of connectivity that are especially important in regulating the temporal and spatial patterns of NO(3-) concentrations in surface waters.     

Taking a ‘Big Data’ approach to data quality in a citizen science project

Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a ‘Big Data’ approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird’s data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a ‘sensor calibration’ approach to measure individual variation in eBird participant’s ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.     

Frontiers of protected areas versus forest exploitation: Assessing habitat network functionality in 16 case study regions globally

Exploitation of natural forests forms expanding frontiers. Simultaneously, protected area frontiers aim at maintaining functional habitat networks. To assess net effects of these frontiers, we examined 16 case study areas on five continents. We (1) mapped protected area instruments, (2) assessed their effectiveness, (3) mapped policy implementation tools, and (4) effects on protected areas originating from their surroundings. Results are given as follows: (1) conservation instruments covered 3–77%, (2) effectiveness of habitat networks depended on representativeness, habitat quality, functional connectivity, resource extraction in protected areas, time for landscape restoration, “paper parks”, “fortress conservation”, and data access, (3) regulatory policy instruments dominated over economic and informational, (4) negative matrix effects dominated over positive ones (protective forests, buffer zones, inaccessibility), which were restricted to former USSR and Costa Rica. Despite evidence-based knowledge about conservation targets, the importance of spatial segregation of conservation and use, and traditional knowledge, the trajectories for biodiversity conservation were generally negative.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01628-5.     

Redundancy and response diversity of functional groups: implications for the resilience of coral reefs

To improve coral reef management, a deeper understanding of biodiversity across scales in the context of functional groups is required. The focus of this paper is on the role of diversity within functional groups in securing important ecosystem processes that contribute to the resilience of coral-dominated reef states. Two important components of species biodiversity that confer ecosystem resilience are analyzed: redundancy and the diversity of responses within functional groups to change. Three critical functional groups are used to illustrate the interaction between these two components and their role in coral reef resilience: zooxanthellae (symbiotic micro algae in reef-building corals), reef-building corals, and herbivores. The paper further examines the consequences of undermining functional redundancy and response diversity and addresses strategies to secure ecological processes that are critical for coral reef resilience.     

Differentiating the effects of climate and land use change on European biodiversity: A scenario analysis

Current observed as well as projected changes in biodiversity are the result of multiple interacting factors, with land use and climate change often marked as most important drivers. We aimed to disentangle the separate impacts of these two for sets of vascular plant, bird, butterfly and dragonfly species listed as characteristic for European dry grasslands and wetlands, two habitats of high and threatened biodiversity. We combined articulations of the four frequently used SRES climate scenarios and associated land use change projections for 2030, and assessed their impact on population trends in species (i.e. whether they would probably be declining, stable or increasing). We used the BIOSCORE database tool, which allows assessment of the effects of a range of environmental pressures including climate change as well as land use change. We updated the species lists included in this tool for our two habitat types. We projected species change for two spatial scales: the EU27 covering most of Europe, and the more restricted biogeographic region of ‘Continental Europe’. Other environmental pressures modelled for the four scenarios than land use and climate change generally did not explain a significant part of the variance in species richness change. Changes in characteristic bird and dragonfly species were least pronounced. Land use change was the most important driver for vascular plants in both habitats and spatial scales, leading to a decline in 50–100% of the species included, whereas climate change was more important for wetland dragonflies and birds (40–50 %). Patterns of species decline were similar in continental Europe and the EU27 for wetlands but differed for dry grasslands, where a substantially lower proportion of butterflies and birds declined in continental Europe, and 50 % of bird species increased, probably linked to a projected increase in semi-natural vegetation. In line with the literature using climate envelope models, we found little divergence among the four scenarios. Our findings suggest targeted policies depending on habitat and species group. These are, for dry grasslands, to reduce land use change or its effects and to enhance connectivity, and for wetlands to mitigate climate change effects.     

Climate change,fisheries management and fishing aptitude affecting spatial and temporal distributions of the Barents Sea cod fishery

Climate change is expected to influence spatial and temporal distributions of fish stocks. The aim of this paper is to compare climate change impact on a fishery with other factors impacting the performance of fishing fleets. The fishery in question is the Northeast Arctic cod fishery, a well-documented fishery where data on spatial and temporal distributions are available. A cellular automata model is developed for the purpose of mimicking possible distributional patterns and different management alternatives are studied under varying assumptions on the fleets’ fishing aptitude. Fisheries management and fishing aptitude, also including technological development and local knowledge, turn out to have the greatest impact on the spatial distribution of the fishing effort, when comparing the IPCC’s SRES A1B scenario with repeated sequences of the current environmental situation over a period of 45 years. In both cases, the highest profits in the simulation period of 45 years are obtained at low exploitation levels and moderate fishing aptitude.     

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950–2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.     

Characterization of spatially homogeneous regions based on temporal patterns of fine particulate matter in the continental United States

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.     

Space-time analysis of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 1 air quality simulations

This study presents an evaluation of summertime ozone concentrations over North America (NA) and Europe (EU) using the database generated from Phase 1 of the Air Quality Model Evaluation International Initiative (AQMEII). The analysis focuses on identifying temporal and spatial features that can be used to stratify operational model evaluation metrics and to test the extent to which the various modeling systems can replicate the features seen in the observations. Using a synoptic map typing approach, it is demonstrated that model performance varies with meteorological conditions associated with specific synoptic-scale flow patterns over both eastern NA and EU. For example, the root mean square error of simulated daily maximum 8-hr ozone was twice as high when cloud fractions were high compared with when cloud fractions were low over eastern NA. Furthermore, results show that over both NA and EU the regional models participating in AQMEII were able to better reproduce the observed variance in ambient ozone levels than the global model used to specify chemical boundary conditions, although the variance simulated by almost all regional models is still less that the observed variance on all spatiotemporal scales. In addition, all modeling systems showed poor correlations with observed fluctuations on the intraday time scale over both NA and EU. Furthermore, a methodology is introduced to distinguish between locally influenced and regionally representative sites for the purpose of model evaluation. Results reveal that all models have worse model performance at locally influenced sites. Overall, the analyses presented in this paper show how observed temporal and spatial information can be used to stratify operational model performance statistics and to test the modeling systems’ ability to replicate observed temporal and spatial features, especially at scales the modeling systems are designed to capture.

Implications: The analyses presented in this paper demonstrate how observed temporal and spatial information can be used to stratify operational model performance and to test the modeling systems’ ability to replicate observed temporal and spatial features. Decisions for the improvement of regional air quality models should be based on the information derived from only regionally representative sites.     

Closing the collaborative gap: Aligning social and ecological connectivity for better management of interconnected wetlands

Understanding how governance structures align to ecological processes in a landscape is critical for effective management of ecological resources. Ecological resources are not independent from each other, instead they are interconnected, and their well-being is often critically dependent on upholding ecological connectivity, especially in times of change and disturbances. Coordination and collaboration among managing actors, each managing their own piece of the puzzle, is therefore essentially a requirement for effective management. We present a conceptual model that includes ecological resources, managing and coordinating actors, along with an explicit representation on how all these entities are connected to each other. We apply this model to 25 municipalities that manage 408 wetlands in central Sweden. The study shows a good social and ecological alignment, however with a high prevalence for coordination through third parties. We discuss this pattern emergence, its potential implications, and examine which municipalities adopt these coordinating functions.     

Measurement, Collaborative Learning and Research for Sustainable Use of Ecosystem Services: Landscape Concepts and Europe as Laboratory

Policies at multiple levels pronounce the need to encompass both social and ecological systems in governance and management of natural capital in terms of resources and ecosystems. One approach to knowledge production and learning about landscapes as social–ecological systems is to compare multiple case studies consisting of large spaces and places. We first review the landscape concepts’ biophysical, anthropogenic, and intangible dimensions. Second, we exemplify how the different landscape concepts can be used to derive measurable variables for different sustainability indicators. Third, we review gradients in the three dimensions of the term landscape on the European continent, and propose to use them for the stratification of multiple case studies of social–ecological systems. We stress the benefits of the landscape concepts to measure sustainability, and how this can improve collaborative learning about development toward sustainability in social–ecological systems. Finally, analyses of multiple landscapes improve the understanding of context for governance and management.     

Characterization of Spatially Homogeneous Regions Based on Temporal Patterns of Fine Particulate Matter in the Continental United States

Abstract

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM_2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM_2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM_2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.