1,721,069 research outputs found
Plant functional traits and environmental variations
No full textSince the original Darwin’s definition of “functional traits” as predictors (proxies) of organism performance, a growing scientific community, mainly over the last three decades, used the “traitbased” approach to address fundamental ecological and multi-scale questions.\ud
The strong link between plant functional traits (PFTs), vegetation processes and ecosystem services, makes this approach particularly promising in the study of vegetation responses to environmental changes (i.e. land use change, climate change, management pressures, etc.).\ud
Despite the high amount of papers available, there are many questions still open.\ud
In this PhD thesis I describe several applications of the trait-based approach in forest and grassland mountain ecosystems, to explore: (i) the patterns and functional clonal groups and (ii) of community-level PFTs of the herb layer along a coppice forest succession; (iii) the intraspecific variability of PFTs in contrasting grasslands habitats; (iiii) the effects of simulated extreme climatic events on grassland ecosystems
Diachronic Observations Reveal Different and Scale-Dependent Response of Sand Dune Plants to Seashore Dynamics
No full textClimate change and human infrastructures heavily affect seashore dynamics with cascading consequences on coastal sand dunes. While there is a high number of studies conducted on plant communities, there is a lack of monitoring approaches conducted at population level. We studied the variations in spatial patterns of the population of three plant species in response to interannual coastline variation in a coastal Nature Reserve. We performed eight diachronic field observations over the course of eleven years, in which we registered the coastline variation and the position of each functional individual of the selected species. The population of the alien-naturalized and highly clonal Sporobolus pumilus demonstrated the ability to follow the interannual variations of the coastline, thus maintaining a constant distance from the seashore. In contrast, the native Polygonum maritimum and the dune-builder Thinopyrum junceum showed a progressive reduction of the distance from the seashore (− 21 m and − 16 m, respectively). However, this effect was detected only at a finer spatial scale, thus revealing the scale-dependence of this phenomenon. In addition, the spatial distribution patterns of T. junceum changed with the variation and stability of the seashore, showing spatial dispersion and aggregation patterns, respectively. Our study reveals how the plant response to the coastline variation was species-specific, probably depending on species functional strategies. Besides highlighting the importance of frequent diachronic surveys, our population-level approach may help in explaining the compositional changes observed at higher organizational level. Finally, our findings indicate that coastal erosion poses a serious threat for the conservation of dune ecosystems
Clonal growth modes in a beech copice context: social behaviour type and clonal strategy changes along a chronosequence.
No full textUnravelling the clonal trait space: Beyond above‐ground and fine‐root traits
Full text linkPlant trait variation is constrained by mechanical and energetic trade-offs as attested by the global spectrum of plant form and function and the fine-root economics space for above- and below-ground traits. However, traits that are key for fitness maintenance in some plant groups, such as clonal and bud bank traits, have not yet been integrated within the frameworks provided by the above-ground and the fine-root economics space.
By using an extensive dataset encompassing above-ground, fine-root, clonal and bud bank traits of 2000 species of Central European herbs, we asked whether clonal and bud bank traits correspond to the placement of species in the above-ground or fine-root trait space.
Perennial clonal and non-clonal herbs show indistinct positioning within the above-ground and fine-root trait spaces. This extends and reinforces previous fragmentary evidence of weak correlations between clonal and bud bank traits and above-ground trait dimensions. Additionally, we identify for the first time a limited correlation between clonal and fine-root traits as well. This disconnection suggests that clonal traits operate independently from other trait spectra. For this reason, we introduce the concept of a ‘clonal trait space’ for clonal herbs. The first dimension of this space is defined by bud bank size and the persistence of clonal connection, reflecting a gradient of species specialisation for on-spot persistence and tolerance to disturbance (persistence dimension). The second dimension, defined by multiplication rate and lateral spread, reflects a specialisation axis for clonal multiplication and horizontal size dimension (clonal multiplication dimension). Clonal trait dimensions add non-redundant information to the above-ground or fine-roots trait space.
Synthesis: We champion the integration of the persistence and clonal multiplication dimensions from the ‘clonal trait space’ into the frameworks provided by the above-ground trait and the fine-root economics spaces, thereby enhancing our comprehension of the multifaceted trait strategies exhibited by plants
Relationships between Urban Green Spaces and Surrounding Nature Areas.
No full textGreen urban areas and forest continuity: The amount and availability of green space is strongly and positively
associated with people’s perceived general health than urbanity. State of the art; research advances with respect to the current debate; expected results and impact in increasing quality of life
Unravelling the clonal trait space: Beyond above-ground and fine-root traits
No full textPlant trait variation is constrained by mechanical and energetic trade-offs as attested by the global spectrum of plant form and function and the fine-root economics space for above- and below-ground traits. However, traits that are key for fitness maintenance in some plant groups, such as clonal and bud bank traits, have not yet been integrated within the frameworks provided by the above-ground and the fine-root economics space. By using an extensive dataset encompassing above-ground, fine-root, clonal and bud bank traits of 2000 species of Central European herbs, we asked whether clonal and bud bank traits correspond to the placement of species in the above-ground or fine-root trait space. Perennial clonal and non-clonal herbs show indistinct positioning within the above-ground and fine-root trait spaces. This extends and reinforces previous fragmentary evidence of weak correlations between clonal and bud bank traits and above-ground trait dimensions. Additionally, we identify for the first time a limited correlation between clonal and fine-root traits as well. This disconnection suggests that clonal traits operate independently from other trait spectra. For this reason, we introduce the concept of a ‘clonal trait space’ for clonal herbs. The first dimension of this space is defined by bud bank size and the persistence of clonal connection, reflecting a gradient of species specialisation for on-spot persistence and tolerance to disturbance (persistence dimension). The second dimension, defined by multiplication rate and lateral spread, reflects a specialisation axis for clonal multiplication and horizontal size dimension (clonal multiplication dimension). Clonal trait dimensions add non-redundant information to the above-ground or fine-roots trait space. Synthesis: We champion the integration of the persistence and clonal multiplication dimensions from the ‘clonal trait space’ into the frameworks provided by the above-ground trait and the fine-root economics spaces, thereby enhancing our comprehension of the multifaceted trait strategies exhibited by plants
Validation of a priori forest type classifications to predict floristic composition.
No full textForest type classifications based on field or satellite data collection have been used
to identify conservation priorities, and thereby support decision-making, zoning
and conservation planning. For these reasons, the capacity of different methods of
forest classification to predict floristic composition is a crucial topic and needs to
be examined.
Here, three predictions are tested, considering how floristic composition is consistent
with different forest type classifications: (1) forest type classifications are
valid for floristic inferences (2) biogeography-based forest types perform better
than stand structure-based forest types; (3) the efficiency in predicting floristic
composition is depending on which factors affect floristic patterns: biogeographic
or anthropogenic drivers.
Species presence-absence of all vascular plants, sampled in the Italian Network
Level I (CONECOFOR), are analysed to determine the best floristic classification
using cluster analysis and non-metric multidimensional scaling. Analyses of similarity
are used to test for differences between the National Inventory of Forests
and Carbon (INFC), the European Forest Type Categories (EFTC) and the Corine
Land Cover 2006, and factors affecting floristic patterns are tested
The diversity of Italian forests: a interactive product of biogeography and ecology.
No full textBackground: Italian forests contains a high total diversity of plants species and
this is likely due to the huge biogeographical gradients covered by the country
(from the Alps to the Mediterranean) as well as to the long lasting human exploitation
and management practices.
This study aims to investigate the interactive effects of ecology and biogeography
in determining the total plant diversity of Italian forests using a spatially
representative sample of forests made of 201 plots sampled all over the country
(CONECOFOR LI network).
The general hypothesis to be tested is that the effects of present day ecological
factors are less important than biogeographical factors in determining the total
diversity of forested areas.
The plant diversity of the sampled forest plan communities was divided into different
spatial components, in particular: plot, site, forest type (used as a proxy for
present day ecological conditions) and biogeographical region. Species presence\
absence was only used. The three following hypotheses have then been tested:
Hypothesis 1: The diversity component accounted by the biogeographical region
is higher that the diversity accounted by the lower scale components (plot, site,
forest type).
Hypothesis 2: Distance decay rate across biogeographical regions is higher than
distance decay rate within biogeographical regions (after correction for extent).
Hypothesis 3: Beta nestedness is higher within than across biogeographical
regions (after correction for extent); on the other hand Beta complementarity is
lower within than across biogeographical regions (after correction for extent).
Results encouraged to enlarge the study in order to consider a wider range of
forest types and bigeographical features in determining the forest plant diversity patterns
Predicting the habitat type distribution to assess the representativeness of the Natura 2000 network
No full textThe Nature 2000 sites based on the Habitats Directive are considered the cornerstone of European Union nature conservation policy. They are the main tools that European nations have to conserve biodiversity across Europe. Therefore, assessing the effectiveness of the Nature 2000 network is a demanding topic in conservation biology.
As defined in the Annex I of the Habitat Directive, the site selection is based on habitats, therefore as accurate information as possible about the extent and distribution of habitats is needed.
Several scientific efforts has been made on this direction, mainly for large scale habitat monitoring through traditional and remote sensing approaches. However large scale species assessment suffer of the lack of standard procedures and not homogeneous data.
Here the ICP Forests LI dataset, the first harmonized assessment of European biodiversity on representative bases is used as baseline information to predict the extent and distribution of habitats types. This data set includes about 3200 plots sampled in European forests by using a probabilistic sampling, therefore represents an opportunity to achieve a representative picture of the EU forest habitat types.
Predictive models of habitat types are developed combining information of the vegetation relevés with environmental predictors. As a result, maps representing European habitat types distribution are obtained. In order to assess the appropriateness of the Natura 2000 sites, the degree of spatial overlap between them and the distribution map of habitat types is calculated
Il rilievo della diversità della vegetazione erbacea
Full text linkL’impatto dei disturbi che agiscono sulle foreste è oggetto di monitoraggio dal 1996 con l’attivazione
del programma nazionale CON.ECO.FOR. (Controllo Ecosistemi Forestali), che include una rete di
Livello I (261 aree permanenti su cui ogni anno vengono effettuati rilievi sulle condizioni delle chiome)
e una rete di Livello II (31 aree permanenti dove vengono svolte indagini più approfondite di tipo
causa-effetto, con diverso grado di approfondimento). Queste reti fanno parte del programma pan-europeo
ICP Forests, e si basano sulla misura costante e periodica di indicatori di stato nell’ambito di
azioni regolamentate da manuali comuni.
Il progetto LIFE MODERn(NEC), nell’ambito della direttiva europea 2016/2284/UE (NEC - National
Emission Ceilings) si propone, fra le altre cose, l’obbiettivo di sviluppare nuovi e più sofisticati indicatori
per monitorare l’ impatto dei vecchi e dei nuovi fattori di stress, in modo da rendere più efficace
l’individuazione precoce degli impatti e le relazioni causa-effetto. Questi nuovi indicatori, una volta
testati tramite la loro pratica applicazione, potranno essere poi proposti per un’applicazione su più
larga scala europea.
I manuali che vengono presentati in questo volume rappresentano un prodotto del gruppo di lavoro
LIFE MODERn(NEC) - Azione B4 (Training for field operators) a supporto degli operatori di campo.
Essi sono parte di un articolato sistema di QA (Quality Assurance) che ha lo scopo finale di uniformare
i criteri con cui i dati vengono raccolti e prodotti, in modo da rendere i risultati del monitoraggio
attendibili e riproducibili
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