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n Europe, forests cover around 40 % of the land
area (190 million ha), making Europe one of the
most forest-rich regions in the world. Forests are
important habitats for many species of wildlife.
Yet, forestry can also have negative impacts on
biodiversity as unsustainable forest operations can
lead to forest degradation and loss of biodiversity.
I...
Contexts in source publication
Context 1
... (1991) noted that an assessment of the degree 'to which [an eco]system would change if humans were removed from the scene' is a strictly hypothetical model without quantitative (measurable) variables. However, the Relative Quantitative Reference Approach for Naturalness Assessments (RANA) from Winter et al. (2010) presents an estimator of naturalness based on definitions of no naturalness (0) and full naturalness (1) with an intervening continuum. Based on preceding definitions, 0 % naturalness of a habitat is equivalent to 100 % hemeroby (see Figure 1.2). Even the greatest naturalness includes a certain direct or indirect impact from humans (for example, due to climate ...
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... studies were devoted in the last decade to naturalness assessment methods ( In reviewing approaches for forest naturalness assessment, McRoberts et al. (2012) identified two approximately complementary perspectives. The first approach is based on an assessment of ecosystem processes (Peterken, 1996). The advantage of this approach is that the assessment focuses on the ecosystem. The disadvantages are the difficulties in defining and measuring parameters that relate to ecosystem processes and that can be evaluated in a globally consistent manner at broad geographical scales. The second approach is based on the degree of human influence at play (Rolston, 1990;Anderson, 1991;Duncker et al., 2012), and focuses on human activity as the driver of ecosystem disturbance. Jalas (1955) introduced the term hemeroby, from the Greek hemeros meaning cultivated, tamed, or refined, as a measure of human impact on ecosystems. Both approaches may lead to a consistent quantification of forest naturalness through the use of indicators (see Figure ...
Context 3
... identification of HNV forest areas should be based on multiple criteria through the use of several indicators. This was clearly expressed in IEEP (2007) and suggested by previous experiences. Once the indicators for assessing forest naturalness are selected, for each forest type and biogeographical area in Europe, the benchmarks values of the different indicators must be defined. This can be done by measuring the values of the indicators in old-growth forests or from theoretical ecology studies. By comparing the current value of the indicator with the benchmark potential value, it is possible to assess the relative naturalness for a given indicator. The indicators can be aggregated by multicriteria analysis to derive a final quantification of forest naturalness ranging between 0 and 1 (see Figure 1.3): 0 for 100 % hemeroby and 0 % naturalness, and 1 for 0 % hemeroby and 100 % ...
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A significant loss of biodiversity resulting from human activity has caused biotic homogenisation to become the dominant process shaping forest communities. In this paper, we present a rare case of biotic differentiation in European temperate deciduous forest herb layer vegetation. The process is occurring in nutrient poor oak-hornbeam forests in m...
Citations
... Worldwide naturalness assessments usually set apart natural forests from planted forests based upon management intensity (FAO, 2015;Forest Europe, UNECE and FAO, 2011;Bastrup-Birk, 2014). The fact that a forest has been managed does not necessarily mean that it has been altered significantly (Barrette et al., 2014b). ...
One-quarter of forest areas worldwide are managed for forestry purposes. Depending upon the type of practice and intensity of management, forestry may alter forests to various degrees and raise sustainability issues. To mitigate the alteration of natural forests by forestry and to promote sustainability, ecosystem management has been implemented widely over the past quarter century. A need remains for the development of comprehensive and operational assessment approaches to validate its effectiveness. Naturalness assessment could be used to validate effectiveness of ecosystem management since this concept relates to the degree to which a natural state has been altered. We developed an approach that integrates stand-and landscape-scale traits of naturalness into a single comprehensive assessment that can be performed using only forestry maps. To illustrate our approach, we assessed naturalness in four managed forest landscapes (2184 km 2), representing a management gradient of increasing intensity from passive restoration to plantation forestry. We defined four naturalness classes, i.e., natural, semi-natural, altered and artificial. Assessment was performed in two steps. At step one, we attributed a class to each managed stand by comparing its current composition with natural stand compositions of its potential natural vegetation. At the landscape scale, certain developmental stages or forest types could be in excess in managed forest landscapes compared with natural forest landscapes. At step two, we transferred numbers of stages or types in excess from the natural class to more altered classes. We demonstrated that naturalness decreased as management intensity increased. Passive restoration and extensive management generated a landscape where semi-natural forests predominated in mixtures with a lower abundance of natural forests. Intensive management generated a largely semi-natural forest landscape. Plantation forestry generated a landscape where semi-natural and altered forests predominated. In conclusion, it should now be possible to validate the effectiveness of different practices and intensity of ecosystem management in promoting sustainability, by performing our assessment approach periodically following every update of forestry maps. Our approach could also allow for more comprehensive assessment of forest management strategies developed to mitigate global change by putting into better perspective their potential effects upon forest alteration of various forestry practices that have been implemented to sequester carbon.
... Structured forest management systems have shaped the development of forest ecosystems within the NATURA 2000 network for centuries (Bastian 2013;European Commission 2015). IAS are among the severest threats to the biodiversity and ecosystem functions of European protected forest areas (Chirici et al. 2014;Seidl et al. 2014;Guerra et al. 2018). Protected forests are well-established across Europe, whilst unmanaged woodlands and primary natural forests are very rare (FAO 2015;Potapov et al. 2017). ...
Invasive alien plant species (IAS) are one of the greatest threats to global biodiversity and the sustainable functioning of ecosystems and mitigating the threat posed by them is therefore of great importance. This study presents the results of a 15-year investigation into how IAS occur within natural forest reserves (NFR): unmanaged forest ecosystems within Austria, concluding that unmanaged forests are not resistant to plant invasions. The study comprised ground vegetation, regeneration, and stand structure surveys. The presence or absence of IAS in different forest types was assessed and the influencing variables for their presence or absence were determined. In addition, the study analysed whether the abundance of IAS has increased at the site level within the past decade. Significant differences in the probability of IAS presences between forest types (photosociological alliances) were found. The results of the study show that natural riparian and floodplain forests are among the forest types most vulnerable to biological invasions, which is reflected in elevation and soil type being determined as the main factors influencing the spread of IAS in unmanaged forests. The results of this study may be useful for persons responsible for sustainable forest management programmes or for managing forested areas within national parks. They provide a case study on non-intervention forest management policy in order to mitigate the impacts of IAS in protected areas. Forest areas, where IAS begin to spread can be identified, which in turn leads to measures in the early stages of invasion, and to optimise monitoring and control measures for relevant species in Central European forest types.
... For å få til dette, må det defineres en referanseverdi som de målte verdiene (bestandene) vurderes i forhold til. Naturindeksen bruker tilsvarende tilnaerming som vanndirektivet (VD) (Klima-og miljødepartementet 2007), Biodiversity Intactness Index (BII) (Scholes & Biggs 2005), Natural Capital Index (NCI) (RIVM 2002), GLOBIO (Alkemade et al. 2009) og «Natural forests index» (Bastrup-Birk 2014) for å definere referansetilstand. GLOBIO er den modellen Konvensjonen for biologisk mangfold bruker for å vurdere tilstanden til jordens biologiske mangfold (www.globio.info). ...
The nature index is a framework for condensed reporting of the state of nature. The composite index deals with the issue of synthesizing and communicating knowledge about states and trends in nature to policy makers and the public, who have an intuitive rather than scientific un-derstanding of concepts like biodiversity and state of nature. The Nature Index does this by summarizing measurements and assessments made by experts on the state of a selection of the components or indicators, which, together, represent biodiver-sity. In the current implementation, one choose to focus on species as indicators, because these also partly reflect genetic diversity and the state of ecosystems. However, the nature in-dex framework also facilitates the construction of an index that measures the state of ecosys-tems and habitats (nature types). To meet the objectives, the set of indicators should ideally represent taxonomy or genetic variation, ecological functions (trophic levels), human pres-sures, ecosystems, habitats and phases in natural ecological successions as homogeneously as possible. The set should not include alien species. The nature index is calculated for a major ecosystem in a delimited geographical area and a given year. The major ecosystems included in the current implementation are ocean bottom, ocean pelagic, coast bottom, coast pelagic, open lowland, mires and wetland, freshwater, for-est, and mountain. The index does not account for changes in the aerial extent of major eco-systems. Mathematically, the nature index is a weighted average of scaled indicators. Fifty percent of the weightings per spatial unit is assigned to key- or extra-representative indicators. The criteria for regarding an indicator as an extra-representative indicator are that the indicator has signifi-cance for populations of one hundred or more species, it occurs over a large area, and there are good data for it. The other indicators are weighted so that trophic groups contribute equally per spatial unit to the nature index value. Non-linear scaling functions transform indicators measured on different scales to a common one, before taking the average. The common scale ranges from zero to one. The scaling func-tions have only one parameter, which defines a base line called the reference value. Reference values serve two aims; first, they act as scaling factors that determines which values of the var-ious indicators correspond to the same state, and second, they set limits for how much an in-crease in one indicator may compensate a decrease in another when combined in a composite index. The nature index framework includes a common conceptual basis for setting reference values for indicators belonging to the same major ecosystem, the so-called reference state. For “natu-ral” major habitats (i.e. all major habitats except “open lowland”), reference values are estimat-ed relative to a common reference state that represents intact ecosystems with little or no hu-man impact. A little impacted state means that species richness, the state of the various popu-lations, and the system’s ecological functions are intact. The corresponding reference state for semi-natural systems (i.e. “open lowland”) is defined as a system that is “in good condition” relative to the species diversity normally associated with the type of semi-natural habitat in question, which results from the application of traditional practices for a long time. The current report further elaborates and specifies reference states for each of the nine major ecosystems. This approach to setting reference values together with the shapes of scaling functions means that scaled indicators measure the indicators’ negative deviance from the reference state, and that the nature index and thematic indices are averages of such deviations. One may interpret the difference between the index value and the reference state value (=1) as the total load from human activity with a negative impact on biodiversity. Simulations based on real and artificial data suggest that the nature index is robust to adjustments of reference concept. Such adjust-ments will not result in significantly different descriptions of the state of Norwegian nature than those the nature index gives today. Experts provide observations of indicators. These observations are associated with measure-ment error. When estimating the nature index one models each observation as a statistical dis-tribution. The dispersion (measured as the interquartile range) measures the uncertainty of the observations and the location along the number line (the expected value) represent the obser-vations’ magnitude. The corresponding sampling distribution for the nature index is simulated using Monte Carlo methods. The median in this distribution provides an estimate of the index. The data behind the nature Index for Norway comprises observations of 301 indicators for the nine major ecosystems. The research institutions Norwegian Institute for Agricultural and Envi-ronmental Research (Bioforsk), Institute of Marine Research (IMR), Norwegian institute for Na-ture Research (NINA), Norwegian Forest and Landscape Institute, Norwegian Institute for Wa-ter Research (NIVA), and NTNU University Museum provide data. Between 29 and 37 indica-tors, describe the state of each major ecosystem, with the exception of forests, which are char-acterized by 87 indicators. The data are monitoring data, model-based estimates of state and estimates based on expert assessments. Expert assessments are subjective judgments based on data and information that are not collected systematically as in a designed monitoring pro-gram. Expert assessments constitute 46% of the available data for calculating the nature index for Norway, model-based estimates 19%, and observations from monitoring programs consti-tute 35%. We have developed a web-based information system for recording, storage and presentation of data used for calculating the nature index and the results from the calculations. The system consists of an SQL relational database for storing indicator observations and other data as well as results from index calculations done in R. It further includes a web-interface for entering da-ta to the database where the individual expert can update information for those indicators the expert is responsible for, and one set of R-scripts that calculate the nature index and analyze raw data and results. In addition, one is currently constructing a website for presentation of re-sults and background data to the public.
... For å få til dette, må det defineres en referanseverdi som de målte verdiene (bestandene) vurderes i forhold til. Naturindeksen bruker tilsvarende tilnaerming som vanndirektivet (VD) (Klima-og miljødepartementet 2007), Biodiversity Intactness Index (BII) (Scholes & Biggs 2005), Natural Capital Index (NCI) (RIVM 2002), GLOBIO (Alkemade et al. 2009) og «Natural forests index» (Bastrup-Birk 2014) for å definere referansetilstand. GLOBIO er den modellen Konvensjonen for biologisk mangfold bruker for å vurdere tilstanden til jordens biologiske mangfold (www.globio.info). ...
... For å få til dette, må det defineres en referanseverdi som de målte verdiene (bestandene) vurderes i forhold til. Naturindeksen bruker tilsvarende tilnaerming som vanndirektivet (VD) (Klima-og miljødepartementet 2007), Biodiversity Intactness Index (BII) (Scholes & Biggs 2005), Natural Capital Index (NCI) (RIVM 2002), GLOBIO (Alkemade et al. 2009) og «Natural forests index» (Bastrup-Birk 2014) for å definere referansetilstand. GLOBIO er den modellen Konvensjonen for biologisk mangfold bruker for å vurdere tilstanden til jordens biologiske mangfold (www.globio.info). ...
Natura 2000 is the core pillar in the European Union’s (EU) biodiversity conservation policy. It is an EU-wide ecological network of protected areas that cuts across countries’ borders, administrative levels, policy sectors and socio-economic contexts. The network is established and managed according to the legally-binding provisions of the 1979 EU Birds Directive (79/409/EEC, revised in 2009) and the 1992 EU Habitats Directive (92/43/EEC). Natura 2000 aims to achieve biodiversity conservation and to combine it with the sustainable development of land and natural resources. It can allow for continuation of land uses (eg agriculture, forestry) as long as they do not significantly compromise conservation objectives for habitats and species within and beyond the network. The Natura 2000 network now covers almost 18% of the EU’s territory. Forests are of crucial importance for Natura 2000 and vice versa. Almost 50% of the whole coverage of the network is comprised of forests. This means that nearly 25% of the total forest area in the EU-28 is part of the EU-wide network of protected areas. Yet knowledge about the implementation of Natura 2000 in forests and its effects on biodiversity, forest management and other land uses across the EU is fragmented. This science-based study aims to narrow the gaps in the scholarly, practical and policy- related knowledge. It looks from policy, economic and ecological perspectives at the monitoring of forest biodiversity in Europe, as well as the challenges, achievements, effectiveness and efficiency of the implementation of Natura 2000 in forests in the EU- 28. The study provides conclusions and recommendations that can support decisionmaking in policy and practice.
Options are derivative contracts that give the purchaser the right to buy (call options) or sell (put options) a given underlying asset at a particular price at a future date. The purchaser of a put option may exercise the right to sell the asset to the issuer at any point in the future before the expiration of the contract. These rights may be contracted directly between two parties (i.e. over-the-counter), or may be sold publicly on formal exchanges, such as the Chicago Board Options Exchange. If the latter, they are called tradeable put options (TPOs) because they can be bought and sold by third-parties via a secondary market. The World Bank has a Pilot Auction Facility for methane and carbon mediation which uses TPOs in carbon-relevant markets, giving producers (of e.g. forest restoration) a floor price for their product [1]. This enables long-term producer planning.
We discuss the potentially broader use of these options contracts in carbon dioxide removal (CDR) markets generally and at scale. We conclude that they can, if priced correctly, encourage rapid investment both in CDR technology and in operational capacity. TPOs could do this without creating the same type of systemic risk associated with other instruments (e.g. long-dated futures). Nevertheless, the widespread use of such instruments potentially creates novel risks. These include the political risk of premature closure [2] (conventionally rendered as 'counting your chickens before they are hatched'); and the economic risk of overpaying for carbon removal services. These instruments require careful structuring, and do not inoculate the CDR market against regulatory disruption, or political pressure. Accordingly, we note the potential for the development of TPO markets in CDR, but we urge caution in respect of identified risks.
Questions
To what extent are the sub‐stand size class distributions at the neighborhood patch scale masked at the stand‐level via spatial smoothing? What are the implications for naturalness assessment of obscuring, at the stand‐level, structures that arise from endogenous processes at the neighborhood scale?.
Location
Elborz Mountain range south of the Caspian Sea, natural uneven‐aged old‐growth Oriental beech (Fagus orientalis) forest subject to fine‐scale disturbances.
Methods
In a 1.2 ha stem‐mapped plot of live trees >7.5 cm DBH, neighborhoods were delineated across multiple scales using the tree‐centered floating neighborhood approach of spatial tessellation to connect trees to their natural neighbors. Cluster analysis was used to identify an optimal number of recurring diameter distribution types (DDT) based on the proportion of trees in each of the five size classes. The richness of DDTs was assessed and the extent of DDTs was modeled as a function of tree size.
Results
The number of member trees and spatial extent increased with neighborhood scale. While the stand‐level tree size class distribution exhibited a rotated sigmoid shape, the nine most distinct DDTs were characterized by four different distribution shapes (negative exponential, increasing‐q, rotated sigmoid, and unimodal) and varied considerably in the abundance of trees in different size classes. Each individual tree contributed to at least three of the nine DDTs, which were nonetheless spatially distinct and varied in extent with size‐class composition. As expected, all metrics exhibited spatial smoothing (i.e., increasing homogeneity with increasing scale) as small, heterogeneous tree neighborhoods were expanded into larger neighborhoods with more similar average composition, which converged on a rotated‐sigmoid shape by the broadest scale.
Conclusions
The stand‐level rotated sigmoid distribution reflected spatial smoothing across more heterogeneous fine‐scale tree neighborhood patches. Further studies are needed to assess if a better measure of natural forest structure may be the diversity of sub‐stand structures and the contribution of individual trees to that diversity, rather than an aggregated metric that averages across the hallmark heterogeneity of neighborhood dynamics.
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Coppice systems are amongst the earliest forms of woodland management known, and on some sites, their use has been documented for centuries. Distinctive assemblages of plants and animals are associated with such systems and are highly valued in nature conservation terms. The richness of such assemblages, and conversely, the species that do not thrive under coppice, are linked to the alternation of relatively short light and dark phases, and the juxtaposition of stands at different stages in the coppice cycle. Vascular plants in the ground flora, invertebrates of open glades and scrub, and small birds of the understorey may have become more abundant in coppice than they would have been under ‘natural’ forest conditions. By contrast, epiphytes dependent on mature trees and species of large-sized deadwood are less favoured by coppice management. Coppice systems developed to meet the local community needs. As social and economic conditions changed, so coppicing declined and the woods were transformed into high forest through neglect or deliberate management. High forests differ from coppice stands in their spatial and temporal dynamics, and consequently, in their wildlife, particularly with respect to their vertical structure pattern, extent of open space and young growth, spatial heterogeneity, tree and shrub composition, and browsing levels. Three issues for the conservation of biodiversity arise from these changes: (1) What priority and resources should be given to halting further decline, by maintaining coppice compared to allowing sites to develop with more ‘natural’ high forest structures and dynamics; will associated high-forest species recolonize? (2) If we restore coppice systems, will the species assemblages present in the past also recover, under current and future changes in environmental conditions; i.e is the transformation reversible under current environmental conditions? (3) Are there other ways in which ‘coppice-associated’ species might be maintained? We identify research gaps and proposals to address these issues.
