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Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
ABSTRACT
The exponential increase of the human population, the environmental changes associated with it, and
global warming are causing a dramatic rate of extinction and re-distribution of plant and animal
species. In response to these trends, there is urgent need for studies of biodiversity and factors affecting
it at the global, regional and local level. In addition, the scientific approach to conservation has shifted
from the protection of single species or sites to preservation of overall biodiversity. There is reasonable
agreement in the international scientific community about the main measurable components of
biodiversity. These include: (1) diversity of genes and of characters; (2) diversity of species; (3)
diversity of ecosystems; (4) functional diversity, i.e. diversity of ecological processes. To date,
quantitative studies of biodiversity have been few, often at coarse spatial scales, and based on only one
component of biodiversity. The few studies conducted in Italy are often below the international
scientific standards. The Trento region still lacks any quantitative study of biodiversity. Project
BIODIVERSITÀ is aimed at filling such gaps. Main objectives of the project will be to:
1. estimate the four biodiversity components, integrating them with vulnerability indexes;
2. build statistical models aimed at predicting field-recorded biodiversity estimates from topographic,
vegetational and land-use characteristics;
3. apply the predictive models and field-recorded estimates to the whole Trento region, so as to create
a GIS map of regional biodiversity;
4. highlight potential biodiversity hotspots within the Trento region;
5. Build statistical models capable to predict the loss of biodiversity associated with environmental
changes driven by local development, and propose sustainable development guidelines aimed at
integrating economic, touristic, selvicoltural, and agro-pastoral development with the conservation
of biodiversity.
Data used to build biodiversity estimates will include:
1. distribution databases of birds, mammals, reptiles and amphibians, completed by fish data from an
in-press publication;
2. intensive population studies of 11 predatory species and their main prey, chosen as indicators of
environmental health of the main regional macro-habitats, sampled at various levels of their trophic
pyramid;
3. progressive censuses and sessions of ringing of migrant birds, so as record estimates of “transient
biodiversity”.
Results of the project will be elaborated so as to be potentially integrated within the P.A.T.
management systems, in agreement with the units deputed to such duties. Results will be published on
international scientific journals and made public through conferences, an internet site, books for the
public and a museum exhibition.
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Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
1. INTRODUCTION
1.1. What is biodiversity?
The exponential growth of the human population and the environmental changes deriving from it are
causing a rate of extinction of animal and plant species judged to be 1000 times higher than the one
characteristic of the current geological period. In addition to such “biodiversity crisis”, global warming
is predicted to cause major redistribution of organisms on the planet. Such processes make the study of
biodiversity and of the factors affecting it extremely urgent on a global, regional, and local scale. In
association with such events, in the last decades the scientific approach to conservation has shifted
from the protection of single species or sites to the definition of wider, more diffuse targets, which
include the whole biological diversity of an area. The importance of preserving the whole biological
diversity of an area has been justified through various instrumental or ethical criteria, associated with
the economic, scientific, educative, ecological, spiritual, recreational and esthetical value of
biodiversity.
Biological diversity, or “diversity of life”, commonly defined as biodiversity, is a complex concept
which has assumed in time scientific, socio-political, and economic meanings. Biodiversity can be
defined as the genetic, taxonomic and ecosystem variety in living organisms of a given area,
environment, ecosystem or the whole planet. It must be noted how this is only one of the possible
definitions. In general in ecology, the term “diversity” is composed of two components: richness, the
absolute number of categories in a sample (e.g. number of species), and evenness, the degree of
uniform frequency of sample units within each category (e.g. the number of individuals within each
species). For example, a very diverse community will be composed of a high number of species, each
one represented by a similar number of individuals. When this concept is applied to biodiversity, we
are faced with the additional problem of incorporating a measure of relatedness, or genetic similarity,
among the elements of the sample system. For example, a community composed of two butterfly
species will be less diverse than a community composed of one butterfly and one vole species. In an
ideal world, biodiversity would be measured by one unique index incorporating richness, evenness and
genetic similarity. In the real world such an index does not exist; the complexity of biodiversity makes
it a conceptual entity, difficult to define quantitatively and measurable only in terms of some of its
components.
If there is disagreement about quantitative definitions of biodiversity, more consensus exists about
the hierarchical levels of measurement of biodiversity. With little variation, biodiversity has been
subdivided into the following components: genetic diversity and/or character diversity; diversity of
species or of higher taxonomic categories (e.g. genera or families); diversity of habitats and
ecosystems. These three categories are related to the spatio-temporal pattern of occurrence of
biodiversity elements. They ignore all those ecological processes which cause the observed pattern
(Gaston 1996a), where by ecological processes we intend all those activities associated with the
interactions among organisms and among organisms and their environment. Such fourth component of
biodiversity has been defined as “functional biodiversity”, i.e. the diversity of all those processes, such
as genetic flow and nutrients cycle, which determine the distribution pattern of biodiversity elements,
such as individuals, populations, or species.
To date, most biodiversity studies have been organized following the above cited hierarchical
structure or some variation of it. Below, we briefly review the most commonly employed methods of
data collection and analysis within each of the four biodiversity components cited above.
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Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
1.2. Methods of biodiversity measurement
Genetic diversity and character diversity
Measuring genetic diversity in a direct way at the level of chromosomes, enzymes and DNA is
practically impossible for studies at the regional level, both in terms of manpower and laboratory
analyses and of economic costs. New techniques have thus been recently developed to provide indirect
measures of genetic diversity, based on the diversity of characters among species, genera, and families.
We define as characters all those biochemical, morphological, or behavioural traits on the basis of
which organisms can be taxonomically separated. Such differences, at the heart of the science of
taxonomy, are considered to be the exterior, phenotypic expression of information encoded into the
gene pool of an organism. Phenotypic characters diversity can thus be used as an indirect estimate of
genetic diversity.
As it is generally impossible to count all the characters of all the sample organisms, the standard
method of measurement of character diversity consists of predicting the distribution of such characters
among organisms based on their genealogy, i.e. based on their phylogenetic tree. Such analyses yield
diversity estimates which take into account the evolution history, the phylogenetic distance, and thus
the character convergence or divergence among species or among other taxonomic categories. The
complex cladistic techniques used for such analyses, not detailed here for lack of space, were initially
proposed by Vane-Wright et al. (1991), and progressively refined by Williams et al. (1991, 1994),
Weitzman (1992) and Faith (1992, 1994) (review in Williams and Humphries 1996). Obviously, the
absence of phylogenetic trees for many organism groups precludes the usage of cladistic models. In
these cases the diversity of higher taxa, such as genera or families, is employed as an indirect estimate,
or surrogate, of character diversity.
Diversity of species
The species is considered by most authors as the fundamental currency of biodiversity. On this line, the
species has been defined as the base-unit of biodiversity, species diversity as the main expression of
biodiversity and species extinction as the main manifestation of the crisis or loss of biodiversity. To
date, most studies were thus conducted employing species diversity as the main estimate of
biodiversity; in particular, in most cases the simple species richness has been used as an estimate of
biodiversity. The usage of species richness instead of species diversity is caused more by practical,
logistical and economical reasons than theoretical ones: in fact, it is usually practically impossible to
census all individuals of all study species for studies at the regional level. Hereafter, we use species
richness as a surrogate for species diversity.
Methods to measure species richness are of two kinds:
1. sample-based methods: samples and estimates of species richness are collected within each area;
2. indirect methods, often defined as “surrogates”: these are estimates of species richness based on the
measurement of one or more predictive variables.
Indirect methods are usually based on one of the three following predictive variables:
1. environmental variables: the diversity of habitats or ecosystems is used to predict species richness;
2. indicator groups: the diversity or richness of certain indicator groups, often predators such as
raptors or carnivores, is used as an indirect estimate of the overall species richness;
3. higher taxa: the richness of higher taxonomic groups, such as genera or families, is used to estimate
species richness.
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Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
Diversity of habitats or ecosystems
Habitat or ecosystem diversity is sometimes recorded in the field, but nowadays is usually recorded
through topographic or satellite maps detailing vegetation or land-uses. Diversity is measured as the
presence and frequency occurrence of each habitat or ecosystem per unit space, estimated through
diversity indexes. Such measures often include estimates of the topographic and geophysical diversity
of the sample area, as these are often key factors regulating biodiversity.
Functional diversity
Ecosystem diversity has been recently advocated as one of the few measurable components of
biodiversity incorporating an estimate of the so called “functional diversity”. More direct measures of
functional diversity have been recently proposed. These consist of subdividing species on the basis of
the trophic role of organisms within the community, such as herbivores, parasites, meso-predators, or
top-predators. Functional diversity is then expressed as the number of trophic functions recorded in the
sample.
2. PROJECT BIODIVERSITÁ
In the past decades there has been a steady rise in the demand by public opinion for “transparent”
political actions, based on criteria as objective as possible, aimed at maximising the action efficacy
while minimising the economical expenditure of the tax payer. In addition, the steep rate of
biodiversity loss at the global level has increased the pressure for sustainable development, based on
environmentally-friendly policies. As a response, there is higher urgency for public administrations to
base their actions on technical, quantitative knowledge, in line with the standard level of scientific
knowledge of other European countries, and supplied by independent sources, such as universities and
museums.
Notwithstanding such trends, very few biodiversity studies have been carried out in Europe, and
only a handful of them were conducted in Italy. Most studies were carried out at a very large spatial
scale, using only species richness as a biodiversity estimate and ignoring all its other components
(genetic, character, functional and ecosystem diversity); very rarely were such studies conducted at a
local scale and with sufficient detail. Finally, in many cases such studies lacked the necessary scientific
rigor which would have allowed them to be published on international journals; their results were thus
confined to local reports, not easily accessible to the scientific community and the general public. This
situation on one side reflects the recent birth of biodiversity as a formal science with a repertoire of
standard study methods, and on the other is caused by the economic and practical difficulty of
accomplishing such type of research.
In agreement with the general national situation, the Trento region still lacks any biodiversity
assessment based on advanced scientific criteria and in line with the standard methodologies set by the
international scientific community. This project aims to fill these gaps, by means of a study aimed at
sampling all the four main components of biodiversity. To this end, numerous complementary
techniques of data collection and analysis will be employed, with the final objective to develop a GIS
biodiversity map of the whole Trento region. Such map will allow to:
• integrate plans of regional development with the conservation of natural resources;
• simulate the loss or increase of biodiversity associated with potential environmental changes cause
by local development policies;
• outline the priority areas, sites or reserves for conservation action;
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Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
• optimise the management of present reserves.
In particular, aim of the project will be to:
1. record biodiversity estimates at various hierarchical scales of organization (individuals, species,
genera, families, ecosystems);
2. incorporate indexes of vulnerability or conservation priority into such biodiversity estimates;
3. build statistical models aimed at predicting field-recorded biodiversity estimates from topographic,
vegetational and land-use characteristics, so as to integrate biotic and abiotic components of
ecosystems;
4. validate the predictive models by applying them to samples statistically independent from the one
used to build the models;
5. apply the predictive models and field-recorded estimates to the whole Trento region, so as to create
a regional biodiversity map;
6. highlight areas of highest biodiversity and/or conservation priority, the so called “biodiversity
hotspots” (Myers 1988, 1990, Myers et al. 2000);
7. build statistical models easy to apply for the non-expert and capable to predict the loss or increase
of biodiversity associated with environmental changes driven by local development (e.g. land-use
changes, such as the currently ongoing conversion of Alpine meadows to scrubs and then forest);
8. propose databases to be integrated in the projects of environmental analysis and assessment
conducted by the Autonomous Province of Trento (e.g. forestry studies, environmental impact
assessment analysis, etc.).
3. METHODS AND EXPECTED RESULTS
3.1. Data collection on the field
Project BIODIVERSITÀ aims to estimate biodiversity using vertebrates as model organisms. This
choice is caused by the following reasons:
(1) censusing the invertebrate component of biodiversity is rarely possible over large areas;
(2) there is in-depth knowledge about the distribution of vertebrates (and scarce information about the
distribution of invertebrates) within the Trento region;
(3) vertebrates are often perceived in a more positive way by the public and are thus a better tool for
environmental education (Jacobson and McDuff 1998). Data collection in the field will be
organised on the basis of the three following aspects.
Atlases and databases of vertebrate distribution
Research carried out in last fifteen years has culminated in the creation of large databases on the
distribution of all species within the vertebrate classes of Birds, Mammals, Reptiles and Amphibians in
the Trento region. Data on fish distribution will be acquired by access to a database currently in press.
Such databases will be completed within 2001 through data collection in the few areas which
previously received little coverage. Such update will allow the publication of the distribution atlases,
used as tools to record species richness within each quadrat of the 1: 25 000 IGM topographic maps (n
= 81 quadrats).
Intensive population studies
Atlas work will allow usage of presence-absence data from sample quadrats; this approach yields
important data for large areas but with little detail: for example, a species may be present in a quadrat
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Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
but with only one non-breeding individual. There is thus high need for complementary estimates of
environmental quality, based on the density and breeding success of species in the quadrat. (Van Horne
1983). As recording density and productivity estimates for all species in each quadrat is not feasible,
such data will be obtained only for some sample species. These species and the areas where they will
be studied were chosen through the following procedure:
1. we first identified the main macro-habitats within the Trento region. We preferred to chose samplespecies on the basis of habitats because:
a. the main aim of the procedure was to find indicators of habitat quality;
b. habitats are one of the fundamental units on which to base plans of conservation
actions;
c. habitat conservation is a more efficient way to protect overall biodiversity than the
conservation of single species.
2. We chose one, or more than one top-predatory species within each macro-habitat. We preferred to
give emphasis to top-predators because:
a. being at the top of the food-pyramid, predators reflect perturbations at the lower levels
of the pyramid and may thus be reliable indicators of ecosystem health;
b. richness of predatory species is generally strongly and positively correlated to the
richness of prey species in the same area;
c. top-predators are often vulnerable, conservation-priority species, thus their conservation
is already an integral part of a strategy of biodiversity preservation;
d. top-predators exert a strong fascination on the general public and are thus optimal
models for the popularisation of issues of biodiversity conservation.
3. For each predator, we selected one or more of its main prey species, whose abundance will be
recorded in the same areas where predators will be studied. This will allow to sample biodiversity
at various levels of the trophic pyramid within each macro-habitat.
4. For each system “macro-habitat – top-predator – prey-species”, we selected random study plots
within the Trento region. All the study plots were selected so as to include a minimum area of 100
km2 or a minimum sample of 25-30 breeding pairs of the predatory species. This minimum sample
will allow us to build statistical models predicting the distribution of predatory and prey species,
and reapply the models to the whole Trento region.
Hotspots of “transient” biodiversity
There is a local component of biodiversity given by the flow of migrating birds passing through the
Trento region every year. This component, which could be defined as “transient” biodiversity, is
difficult to estimate through the above cited methods, and causes suddenly high biodiversity values
within small areas and time frames. To quantify such component, we will carry out progressive visual
and acoustic censuses, and sessions of mist-netting and ringing of migrant birds at various sites
suspected to be key areas for passage and stop-over of migrants. This work, often conducted within
nature reserves (“biotopi provinciali”), will also allow to explore the importance of current reserves as
biodiversity hotspots.
3.2. Expected results and methods to accomplish them
1) Record biodiversity estimates at various hierarchical scales of organization. Genetic and character
diversity will be analysed by means of cladistic, phylogenetic techniques applied to atlas data (review
in Williams and Humphries 1996). Species diversity will be investigated by using data from
distribution atlases and from intensive population studies, so as to estimate both species richness and
6
Sezione di Zoologia dei Vertebrati, Museo Tridentino di Scienze Naturali
Progetto Biodiversità: Integrare lo sviluppo del territorio con la conservazione della biodiversità in provincia di Trento.
Testo approfondito
evenness. Diversity of migrant species will be analysed separately, using data from the ringing stations
and from the progressive censuses within local reserves (“biotopi”). Diversity of habitats and
ecosystems will be quantified through a geographic Information System (GIS), accessing the available
GIS databases: the forest cover map of Servizio Foreste (1999), and the “Corine” land-use map. Such
data will be integrated with those from very recent aerial photographs. Finally, functional diversity will
be estimated through the techniques reviewed by Martinez (1996), using data from both distribution
atlases and intensive population studies.
2) Incorporate indexes of vulnerability into biodiversity estimates. Various vulnerability estimates
will be integrated with the biodiversity ones. The main vulnerability indexes which will be used will be
extracted from the IUCN classification, the Bern and Bonn Conventions, the “Habitats” Directive of
the EU and the categories of conservation priority proposed by BirdLife International for birds.
3) Build statistical predictive models. For each quadrat of the 1: 25 000 IGM grid (n = 81 quadrats) we
will record through a GIS variables related to: (1) topography (e.g. altitude, mean slope, ruggedness
indexes), (2) vegetation, (3) rate of local development (e.g. length of paved roads), and (4) land-use.
These will be used as independent predictor variables in statistical models aimed at predicting
biodiversity values recorded in each sample quadrat. This type of analyses usually yield reliable
models, capable to predict biodiversity values with reasonable accuracy. Employed models will
include univariate and multivariate analyses, mainly multiple and logistic regression, discriminant
analysis, and general linear models (GLM). The integration of environmental and geophysical
variables with biodiversity estimates will allow the construction of more complete estimates,
incorporating both the living (biotic) and non-living (abiotic) component of the ecosystem, and thus
related to the overall “biological integrity” of an area.
4) Validate the predictive models. The above cited models will be built with sub-samples of the
available data. Their predictive power will be tested by applying them to the rest of the originally
available sample, thus applying them to a statistically independent sample, a standard procedure in this
sort of studies.
5) Create a regional biodiversity map. Direct estimates and predictive models will be applied to the
whole Trento region. Various biodiversity maps will be initially created, one for each main
biodiversity component. An overall biodiversity map will be created by employing principal
component analysis (PCA) to incorporate all biodiversity and vulnerability estimates in one only index.
6) Highlight biodiversity hotspots. We will highlight areas characterised by high biodiversity and
simultaneous high abundance of vulnerable species. Such biodiversity hotspots will need more indepth studies on a finer spatial scale, following a commonly applied hierarchical procedure of study,
which involves the identification of priorities first at coarse levels and then at progressively finer
spatial scales.
7) Propose environmental simulation tools. Equations derived from the above models will be
proposed as potential tools to simulate the biodiversity loss or increase caused by potential
environmental changes in the future, such as those caused by incentive schemes of the EU Common
Agricultural Policy. The models will allow to chose among available options the least harmful for
biodiversity.
8) Propose tools to be integrated within the PAT management systems. Based on the results and
simulations obtained, we will propose tools, such as models and databases, which can be integrated
within the PAT projects of environmental study and/or analysis (e.g. forestry studies, environmental
impact assessment analyses, etc.).
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