National Forest Inventory Contributions to Forest Biodiversity Monitoring

Chirici, Gherardo; McRoberts, Ronald E.; Winter, Susanne; Bertini, Roberta; Brändli, Urs-Beat; Alberdi, Iciar; Bastrup-Birk, Annemarie; Rondeux, Jacques; Barsoum, Nadia; Marchetti, Marco

doi:10.5849/forsci.12-003

Cited by 95 publications

(64 citation statements)

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“…Much of this shift in the United States and other regions of the world is due to an interest in conserving biodiversity (FEMAT 1993, Montre´al Process Working Group 2009, Forest Europe 2011, often represented by the diversity of plant and animal species and habitat conditions (Lindenmayer et al 2000, Chirici et al 2012. Recent concerns about climate change have extended management objectives further to include carbon (C) storage for the abatement of increases in atmospheric CO 2 (Pacala andSocolow 2004, McKinley et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Management trade‐off between aboveground carbon storage and understory plant species richness in temperate forests

Burton

Ares

Olson

et al. 2013

Ecological Applications

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Abstract. Because forest ecosystems have the capacity to store large quantities of carbon (C), there is interest in managing forests to mitigate elevated CO 2 concentrations and associated effects on the global climate. However, some mitigation techniques may contrast with management strategies for other goals, such as maintaining and restoring biodiversity. Forest thinning reduces C storage in the overstory and recruitment of detrital C. These C stores can affect environmental conditions and resource availability in the understory, driving patterns in the distribution of early and late-seral species. We examined the effects of replicated (N ¼ 7) thinning experiments on aboveground C and understory vascular plant species richness, and we contrasted relationships between aboveground C and early-vs. lateseral species richness. Finally, we used structural equation modeling (SEM) to examine relationships among early-and late-seral species richness and live and detrital aboveground C stores.Six years following thinning, aboveground C was greater in the high-density treatment and untreated control than in moderate-(MD) and variable-density (VD) treatments as a result of reductions in live overstory C. In contrast, all thinning treatments increased species richness relative to controls. Between the growing seasons of years 6 and 11 following treatments, the live overstory C increment tended to increase with residual density, while richness decreased in MD and VD treatments. The richness of early-seral species was negatively related to aboveground C in MD and VD, while late-seral species richness was positively (albeit weakly) related to aboveground C. Structural equation modeling analysis revealed strong negative effects of live overstory C on early-seral species richness balanced against weaker positive effects on late-seral species richness, as well as positive effects of detrital C stocks. A trade-off between carbon and plant species richness thus emerges as a net result of these relationships among species traits, thinning treatments, and live and detrital C storage. Integrating C storage with traditional conservation objectives may require managing this trade-off within stands and landscapes (e.g., maintain early-seral habitat and species within dense, C-rich forests and, conversely, live and detrital C stores in early-seral habitats) or separating these goals across scales and species groupings.

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Section: Introductionmentioning

confidence: 99%

Management trade‐off between aboveground carbon storage and understory plant species richness in temperate forests

Burton

Ares

Olson

et al. 2013

Ecological Applications

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“…Timber production traditionally was the core focus of NFI and data were often difficult to compare internationally due to different NFI designs, variation of assessed criteria, etc. In recent years, many NFIs were expanded to more comprehensibly assess multiple forest functions and considerable attempts were made to harmonise the data between countries (Chirici, 2011;Tomppo, 2010 Numerous empirical studies have examined forest biodiversity and used such results to provide widely applicable indicators of biodiversity values based on various aspects of forest structure and composition. A common approach to "measuring" biodiversity is to estimate the abundance of chosen species or taxa, often focusing on "umbrellas'' or "indicators" covering large number of cooccurring species and thus serving as proxies for valuable habitats, (cf.…”

Section: Forest Condition Indicatorsmentioning

confidence: 99%

Linking forest management, policy and biodiversity indicators – A comparison of Lithuania and Southern Sweden

Brukas¹,

Felton²,

Lindbladh³

et al. 2013

Forest Ecology and Management

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Lithuania and Southern Sweden share similar natural conditions, but differ considerably in forest policies and management; thereby providing an opportune basis for comparative studies. Since the 1990s, Sweden has attempted to reduce the negative impact of its forest management on biodiversity, after decades of intensive production forestry. In contrast, Lithuania has been intensifying forestry practices associated with the post-soviet socioeconomic transition. Here we assess the actual outcomes by comparing selected forest structure and composition variables known to be indicators for forest biodiversity; and estimate the prospective trends by scrutinising current forest policies and management. Our results indicate that Lithuanian forests consistently possessed higher rankings in six indices related to tree species composition, stand age, and deadwood quantities that are positively associated with forest biodiversity. The reverse is indicated by those data on stand age and tree diameter that are associated with centennial dynamics in forest utilisation intensity. With respect to policy instruments, Lithuania designates a substantially greater share of forest area to non-timber functions and legislates more severe management restrictions in forests targeting timber production. Concurrently, all estimates of forestry activities indicate more intensive forest management in Southern Sweden, including a higher share of artificial regeneration and shorter rotations. This allows concluding that, if current forest management practices persist, then an increased "biodiversity gap" may be expected between the two countries. The study concludes with discussing to what degree the identified trends are the direct product of targeted policies versus merely by-products of other factors.

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“…A questionnaire developed within the COST Action E43 ("Harmonisation of National Forest Inventories in Europe: Techniques for Common Reporting") revealed that forest age is currently estimated in the 96% of the European NFIs (Chirici et al 2012a). However, age definitions, sampling designs and protocols, make age data harmonization and aggregation across countries very difficult (Chirici et al 2012a).…”

Section: Introductionmentioning

confidence: 99%

Spatially explicit estimation of forest age by integrating remotely sensed data and inverse yield modeling techniques

Frate¹,

Carranza²,

Garfì³

et al. 2016

iForest

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We present an innovative method based on the application of inverse yield models for producing spatially explicit estimations of forest age. Firstly, a raster growing stock volume map was produced using the non-parametric kNearest Neighbors estimation method on the basis of IRS LISS-III remotely sensed imagery and field data collected in the framework of a local forest inventory. Secondly, species-specific inverted yield equations were applied to estimate forest age as a function of growing stock volume. The method was tested in 128 000 ha of even-aged forests in central Italy (Molise region). The accuracy of the method was assessed using an independent dataset of 305 units from a local standwise forest inventory. The results demonstrated that the forest age map was accurate, with a root mean square error of 15.8 years (30% of the mean of field values), and useful for supporting forest management purposes, such as the assessment of harvesting potential and ecosystem services. Thanks to the use of remotely sensed data and spatial modeling, the proposed approach is cost-effective and easily replicable for vast regions.

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National Forest Inventory Contributions to Forest Biodiversity Monitoring

Cited by 95 publications

References 0 publications

Management trade‐off between aboveground carbon storage and understory plant species richness in temperate forests

Management trade‐off between aboveground carbon storage and understory plant species richness in temperate forests

Linking forest management, policy and biodiversity indicators – A comparison of Lithuania and Southern Sweden

Spatially explicit estimation of forest age by integrating remotely sensed data and inverse yield modeling techniques

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