a probabilistic approach for plant diversity monitoring in a european natura2000 network alessandro...

A probabilistic approach for A probabilistic approach for plant diversity monitoring in a plant diversity monitoring in a

European European NaturaNatura2000 network2000 network

AlessandroAlessandro Chiarucci, Chiarucci,GiovanniGiovanni Bacaro, Bacaro,DuccioDuccio Rocchini* Rocchini*

Department of Environmental Science “G. Sarfatti”Department of Environmental Science “G. Sarfatti”University of Siena, ItalyUniversity of Siena, Italy

**TerraData EnvironmetricsTerraData Environmetrics, www.terradata.it, www.terradata.it

49° IAVS Annual Conference - Palmerston North, New Zealand, 12-16 Feb 2007

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Nature Reserve NetworksNature Reserve NetworksA high number of protected areas is spread in European A high number of protected areas is spread in European countries, often arranged in territorial networks.countries, often arranged in territorial networks.

In Europe, the In Europe, the Natura 2000Natura 2000 is the most important network is the most important network pf protected areas and it is supposed to preserve almost pf protected areas and it is supposed to preserve almost all the terrestrial species and habitats.all the terrestrial species and habitats.

The following specific objective has been set: The following specific objective has been set: “to achieve by 2010 a significant reduction of the current “to achieve by 2010 a significant reduction of the current rate of biodiversity loss at the global, regional and rate of biodiversity loss at the global, regional and national level".national level".

To understand if the existing reserve networks can To understand if the existing reserve networks can achieveme of this objective we need to quantify in an achieveme of this objective we need to quantify in an affordable way how much biodiversity is present within it affordable way how much biodiversity is present within it and how it is changing through time!and how it is changing through time!


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Plant species diversityPlant species diversityVascular plants are the most important component of Vascular plants are the most important component of most terrestrial ecosystems because of their functional most terrestrial ecosystems because of their functional and structural role.and structural role.

The quantification and the monitoring of plant species The quantification and the monitoring of plant species diversity represents thus essential steps for the diversity represents thus essential steps for the management of protected areas and for understanding management of protected areas and for understanding how these are changing through time.how these are changing through time.

With this project we aimed to develop and test a method With this project we aimed to develop and test a method for evaluating and monitoring plant species diversity for evaluating and monitoring plant species diversity within a territorial Natura2000 Network, based on a within a territorial Natura2000 Network, based on a sample approach. sample approach.

This method is based on a constrained sampling effort This method is based on a constrained sampling effort and a high potential for spatial inference.and a high potential for spatial inference.


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Assessment of plant species diversityAssessment of plant species diversity

Assessing and monitoring plant species diversity over very Assessing and monitoring plant species diversity over very large and fragmented areas is a really difficult task. Large large and fragmented areas is a really difficult task. Large databases are presently available but they present many databases are presently available but they present many problems for spatial and temporal inference.problems for spatial and temporal inference.

Some national and local monitoring programs use remote Some national and local monitoring programs use remote sensing, mapping or structural indicators.sensing, mapping or structural indicators.

Taxonomic information is still an essential data source for Taxonomic information is still an essential data source for describing and monitoring, biodiversity, at least until the describing and monitoring, biodiversity, at least until the potential use of other indicators will be clearer. potential use of other indicators will be clearer.

However, it is virtually impossible to get complete lists of However, it is virtually impossible to get complete lists of species for large areas. It is also very difficult to use the species for large areas. It is also very difficult to use the records when they are collected on non-homogeneous records when they are collected on non-homogeneous criteria.criteria.


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Study AreaStudy AreaAs study area we As study area we used the network of used the network of SCIs present in the SCIs present in the province of Siena, province of Siena, Tuscany.Tuscany.

Descriptive data:Descriptive data:► ► 20 SCIs20 SCIs

► ≈ ► ≈ 593 km593 km22

► ► 5 - 137 km5 - 137 km2 2 eacheach

► ► Altitudinal range:Altitudinal range: 65 -1685 65 -1685


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Existing NetworksExisting NetworksThe whole country was divided into cells of 1x1 km

In each cell a random point was selected

Data were collected by using a three-stage sampling design

I. N. F. C.


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In each point vascular plants were sampled by using In each point vascular plants were sampled by using a 10x10 m plot, divided into 16 subplots.a 10x10 m plot, divided into 16 subplots.In preliminary tests, this plot size was found to In preliminary tests, this plot size was found to represent the best compromise between local represent the best compromise between local species richness and sampling accuracy.species richness and sampling accuracy.

10 m

etri

10 metri

P.R.

2,5 m

2,5 m

111 222 55 66

77333 88

14

444

13

1212

1010

1516 1111

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10 m

etri

10 metri

P.R.

2,5 m

2,5 m

10 m

etri

10 metri

P.R.

2,5 m

2,5 m

111 222 55 66

77333 88

14

444

13

1212

1010

1516 1111

99


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Points were localised with a high precision GPS system and the spatial data then submitted to differential correction.

Each plot was sampled by a team made by at two experienced botanists and herbarium specimens were collected.

Data CollectionData Collection


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Floristic data were stored on a web-based relational database that guarantees the preservation of the data and their easy access to all the authorised users, for both research and management aims.

Data storageData storage


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Sampling SummarySampling Summary

SCIs in Siena Province

SCIs sampled in 2006

SCIs sampled in 2005


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Data SummaryData Summary

20052005 20062006

N° of sampled SCIsN° of sampled SCIs 44 44

N° of plotsN° of plots 4848 173173

N° of field daysN° of field days 1616 4242

N° of field operators per N° of field operators per field dayfield day

2-42-4 2-62-6

N° of days * teamsN° of days * teams 1919 7373

N° recorded speciesN° recorded species 364364 ≈≈800800


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2005 Results2005 ResultsPigelleto

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of s

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2005 Results2005 Results

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Pooled Number of Plots

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AmiataLucciola BellaPigelletoRipa d'OrciaRandom


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Additive partitioning of diversityAdditive partitioning of diversityInventory Diversity Differentiation diversity Scale of sampling

Alpha1

Plots

SCIBeta3 among sites

Alpha2

Alpha3

NetworkAlpha4

Beta2 (among stands)

SubplotsBeta1 (within stands)

To test the significance of alfai and betai components, samples at level i-1 were randomly allocated among those samples at level i that belong to the same sample unit at i+1.


1515


Alfa 1

Beta 1

Beta 2

0%

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AMIA LUCC PIGE RIPA

Pro

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ecie

s d

iver

sity

Obs Ran Obs RanObs RanObs Ran


1616


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Pooled Number of Plots

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ole

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Plots SICs

α2= 25.5 sp.

α3= 137.8 sp.

β2 = 112.3 sp.

β3 = 224.2 sp.

α4= 362 sp.


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0%

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Observed Random

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alfa1 beta1 beta2 beta3


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ConclusionsConclusions Species composition data collected by a probabilistic

sample were useful in evaluating the partitioning of species diversity in a network of protected areas and gave useful insights for its future monitoring.

Species diversity is largely due to large scale variation, both at the within-site and the among sites levels.

The monitoring of plant species diversity in a network of protected areas should be performed by using a high number of plots, rather using few larger sites.

To provide spatial and temporal inference of plant species diversity, a limited number of plots selected with a probabilistic approach should be preferred over larger databases of preferentially selected plots.

Additive partitioning of species diversity combined with rarefaction curves can provide a useful method to quantify and monitoring plant species diversity.


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We acknowledge all the students and

We acknowledge all the students and

colleagues that contributed to the project:

colleagues that contributed to the project:

Andrea Billi, Arianna Vannini, Elisa Baragatti, E

lisa

Andrea Billi, Arianna Vannini, Elisa Baragatti, E

lisa

Santi, Fernando Cortés Selva, Francesco Geri, Giulia

Santi, Fernando Cortés Selva, Francesco Geri, Giulia

Bennati, Lia Pignotti, Mauro Taormina, Patrizia Mosca,

Bennati, Lia Pignotti, Mauro Taormina, Patrizia Mosca,

Sara Ghisleni.

Sara Ghisleni.

a probabilistic approach for plant diversity monitoring in a european natura2000 network alessandro...

Documents

plant diversity monitoring

new zealand

terrestrial species

large areas

complete lists of species

fragmented areas

management of protected

network of scis present