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The methodology and applications of Agricultural
Landscape monitoring in Estonia
Kalev Sepp,
Institute of Environmental Protection
Estonian Agricultural University
EPI EAU
Proposed concept of landscape monitoring program
in Estonia
Landscapemonitoringprograms
Finacialcapacaties,
availabletechnologies
Scientificprinciples
Social andeconomical
values
Experinces ofother countries
Environmentalpolicy
Environmentaland landscape
indicators
Agriculturallandscapemonitoring
Remotesensing of
landscapes
Monitoring ofcoastal
landscapes
Monitoringprotected and
valuablelandscapes
The main purposes of the agricultural monitoring programme were
defined as follows
To follow up and evaluate the environmental effects of land and agricultural reforms
To define changes in land use structure in the different type of agricultural landscapes (intensive and extensive land use)
To study changes in land cover types, especially fallow land and semi-natural areas
To explain the connection between landscape structure indicators and the characteristics of ecological status of agricultural landscapes
EPI EAU
Conceptual scheme of agricultural
landscape monitoring programme MONITORING OFAGRICULTURAL
LANDSCAPES
ENVIRONMENTAL POLICY
LEVEL OF HUMANPRESSURE
- MICROORGANISMS- EARTHWORMS- BUMBLEBEES
SPATIALSTRUCTURE OF
LANDSCAPE
- AREAL ELEMENTS- LINEAR ELEMENTS- POINT ELEMENTS
HISTORICALOVERVIEW OF LAND
USE CHANGES
AERIAL PHOTOS
ENVIRONMENTAL INDICATORS
Monitoring of agricultural landscapes
Spatial structure of landscapeaerial
linear
point
Historical overview of landscape change
Level of human pressureearthworms
epigenic fauna of soils
soil-microorganisms
bumblbees
Test areasRegional distribution according to the Estonian landscape regions
Distribution all over the country
Intensive and extensive areas as well as marginal areas of agriculture
Availability of additional data
Good relation to other sites of environmental monitoring
Localities were divided into two groups• intensively used agricultural areas (IUAA) • extensively used agricultural areas (LIUAA)
Examples from landscape pattern analysis
buffer zones <5m
buffer zones >5m
ecotones between cultivated land and broad-leaved forests
ecotones between cultivated land and mixed or coniferous forests
ditches and brooks
arable land
semi-natural grasslands
fallow land
mixed forests
coniferous forests
broad–leaved forests
bushes
wetlands
cultivated grasslands
pastures
legumes
EPI EAU
Methods of studying human pressure on
agricultural land The following earthworm and soil microbial community parameters were described:· number of individuals and species of earthworms (Lumbricidae) per 1 m2;
· maximum dominance in earthworm community (%);· diversity of soil microbial and earthworm communities;· total hydrolytical activity of soil microorganisms;· the number of colony forming microorganisms per 1 g of dry soil.
Methods for analysing the landscape diversity
changes in monitoring areas Time period - over the last 50 years Time sections 1950–1955; 1970–1975; 1995–1999Black-and-white interpreted aerial photos in the scale of 1:10 000 were used. Aerial photos were scanned by AGFS scanner (A3) and transformed using the software ARC/Info. Scanned aerial photos were vectorised and encoded in the environment of the software MapInfo and GeoGraphics.
Classification included different polygon elements (e.g. arable lands, forests, grasslands, waters, bushes and brushwood, other lands).
The main objectives of the research
To investigate the relationship between the landscape structure and the abundance and composition of indicator species - bumble bees
To develop a general concept of agricultural landscape monitoring in Estonia
EPI EAU
Methods for bumblebee studies in agricultural landscapes
1. Counts were carried out in nine localities localities in 1996-1999
2. Localities were divided into two groups1. intensively used agricultural areas (IUAA) (the percentage of
arable land was >65%)
2. extensively used agricultural areas (LIUAA) (the percentage of
arable land was <45%). 3. Each locality included two transects (2×1,000 m)
4. Both transects were divided into 20×2 m plots
5. Transects were observed regularly from July to August
EPI EAU
Methods for bumblebee studies in agricultural landscapes
Counts were made by the same observer on the same day in the weather conditions optimal for bees
The following information was recorded each time: bumblebee individuals were encountered species and cast food plant(s) foraged
Study areas (1200 ha each) were mapped on the land use plan in scale 1: 10,000
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Statistical analysis of data sets
Principal Component Analysis (PCA) of the landscape elements and the bumble bee species found was carried out
The results of PCA are interpreted using scatters of the site scores connected with group centroids (star plot), and via correlation circlesThe effect of the grouping factor was estimated using a multivariate randomisation test (Manly, 1995) with 1,000 permutations
The influence of landscape structure on bumble bee communities was studied with co-inertia analysis
EPI EAU
PCA based on the regional bumble bee distribution
EPI EAU
IUAALIUAA
B. veteranus
B. pratorum
IUAALIUAA
The first and second principal components described 30.9% and 18.7% of the overall data variation,
respectively
PCA based on landscape elementsEPI EAU
LIUAA IUAA
PCA on landscape elements matrix described
28.7%, 21.9% and 19.8% of the overall data variation
wetlands
cultivated grasslands
arable lands
Results of co-inertia analysis
The permutation test revealed that the co-structure between the data sets of landscape elements and bumble bee species was highly significant (P<0.001)
The correlation coefficients between the two new sets of co-ordinates for the first and second axes of the co-inertia analysis were 0.87 and 0.97, respectively
The most important elements of landscape and bumblebee
species defining the first two factors of the co-inertia analysis F1 F2LANDSCAPE BUMBLEBEES LANDSCAPE BUMBLEBEES
Ecotonesbetweenagriculturalland andbroad-leavedforests
B. sylvarum Semi-naturalgrasslands
B. pratorum
CultivatedGrassland
B. terrestris Fallow land B. hypnorum
Legumes B.distinguendus
Broad-leavedforests
Wetlands B. schrencki Pastures B. ruderariusMixedforests
B. soroensis
Ecotonesbetweenagriculturalland andmixed andconiferousforests EPI EAU
Conclusion
The correlation circle of the bumble bee species found demonstrated that the species relevant to the grouping of study sites into IUAA and LIUAA were
B. pratorum (7)
B. sylvestris (9)
B. lapidarius (1)
B. veteranus (4)
EPI EAU
ConclusionThe species composition and abundance of bumble bees was to a great degree determined by landscape structure
The permutation test revealed that the co-structure between the data sets of landscape elements and bumble bee species was highly significant (P<0.001)
The correlation coefficients between the two new sets of co-ordinates for the first and second axes of the co-inertia analysis were 0.87 and 0.97, respectively
Bumble-bees can be use as bio-indicators for evaluation natureless of agricultural landscapes
EPI EAU
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