Forest landscapes and global change. New frontiers in management, conservation and restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference

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Bragança · Portugal

IUFRO Landscape Ecology Working Group

International Conference

New Frontiers

in Management,

Conservation

and Restoration

Proceedings

Edited by

João Carlos Azevedo

Manuel Feliciano

José Castro

Maria Alice Pinto

Landscapes

Forest

and Global

Change

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Forest Landscapes and Global Change

New Frontiers in Management, Conservation and Restoration

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The contributions to this volume have not been peer-reviewed. Only minor changes in

format may have been carried out by the editors.

Title: Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal.

Editors: João Carlos Azevedo, Manuel Feliciano, José Castro & Maria Alice Pinto Published by: Instituto Politécnico de Bragança

Apartado 1038, 5301-854 Bragança, Portugal

http://www.ipb.pt

Printed by: Serviços de Imagem do Instituto Politécnico de Bragança ISBN: 978-972-745-110-4

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New Frontiers in Management, Conservation and Restoration

Proceedings of the

IUFRO Landscape Ecology Working Group International Conference

September 21-27, 2010

Bragança, Portugal

Edited by

João Carlos Azevedo

Manuel Feliciano

José Castro

Maria Alice Pinto

Instituto Politécnico de Bragança, Portugal

September, 2010

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Landscape assessment tools for adaptive management of tropical forested landscapes 653 Socio-economic diagnosis of a small region using an economic farming system modeling tool (Olympe). An 654 approach from household to landscape scales to assist decision making processes for development projects

supporting conservation agriculture in Madagascar Eric Penot

Network theory to conserve and reconnect forested landscapes 660 Connectivity loss in human dominated landscape: operational tools for the identification of suitable habitat patches 661 and corridors on amphibian’s population

Samuel Decout, Stéphanie Manel, Claude Miaud & Sandra Luque

Landscape genetics 667

GEOME. Towards an integrated web-based landscape genomics platform 668 Stéphane Joost, Michael Kalbermatten & Nicolas Ray

Road ecology: improving connectivity 673

The effect of highways on native vegetation and reserve distribution in the State of São Paulo, Brazil 674 Simone R. Freitas, Cláudia O. M. Sousa & Jean Paul Metzger

Detecting vulnerable spots for ecological connectivity caused by minor road network in Alicante, Spain 679 Beatriz Terrones, Sara Michelle Catalán, Aydeé Sanjinés, Encarnación Rico-Guzmán & Andreu Bonet

A landscape approach to sustainable forest management 685

Is it possible to combine adaptation to climate change and maintaining of forest biodiversity? 686 Marja Kolström, Terhi Vilén & Marcus Lindner

Ecosystem services from forests at the watershed scale 691

Forests in landscapes: modelling forest land cover patterns suitability for meeting future demands for landscape 692 goods and services

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João Pedro Nunes, José Javier Cancelo, María Ermitas Rial, Maruxa Malvar, Filipa Tavares, Diana Vieira, Frederike Schumacher, Francisco Díaz-Fierros, António Dinis Ferreira, Celeste Coelho & Jan Jacob Keizer

Management and conservation of Mediterranean forest landscapes 704 Testing the fire paradox: is fire incidence in Portugal affected by fuel age? 705 Paulo M. Fernandes, Carlos Loureiro, Marco Magalhães & Pedro Ferreira

Interfaces and interactions between forest and agriculture in rural landscapes 711 When forests are managed by farmers: Implications of farm practices on forest management 712 E. Andrieu, A. Sourdril, G du Bus de Warnaffe, M. Deconchat & G. Balent

A framework for characterizing convergence and discrepancy in rural forest management in tropical and 718 temperate environments

D. Genin, Y. Aumeerudy-Thomas, G. Balent & G. Michon

Do wooded elements in agricultural landscape contribute to biological control in crops? 724 A. Ouin, M. Deconchat, P. Menozzi, C. Monteil1, L. Raison, A. Roume, J.P. Sarthou, A. Vialatte & G. Balent

From abandoned farmland to self-sustaining forests: challenges and solutions 729 Harmonized measurements of spatial pattern and connectivity: application to forest habitats in the EBONE 730 European Project

Christine Estreguil & Giovanni Caudullo

Restoration of biodiversity and ecosystem services in cropland. Further research is needed but action is 736 desperately needed

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xiii

Foreword

Twenty years ago, Dr. T. Crow and Prof. B. Anko initiated a proposal to establish a new working party (WP) within the Division 8 of IUFRO, known as landscape ecology. Back then, the field was in its most rapid growth period with many unknowns. Quite a few scholars challenged us about whether this young discipline was science. This challenge was partially important because landscape ecology has strong components and commitments to managers and policymakers. Today, landscape ecology is matured with solid principles and implementations in resource management. Many members of the WP made significant contributions to advance this field for its recognition. At the first international conference in 1990, there were a small handful of participants. After the announcement of this conference, over 400 abstracts were submitted. By August 6, 2010, there were at least 233 registered individuals from 44 countries.

Previous bi-annual conferences had been held in the United States, Japan, Italy, Canada and China. In the last decade, the WP also paid much attention to publishing the papers presented at our bi-annual conferences. Several books and special issues based on these conferences have been published. The WP is now soliciting proposals for future conferences. Please contact any of the committee members during the conference to discuss your interests and plans. One particular effort made by conference organizers and the WP committee is to support students. We believe that student participation is vital for both the science of landscape ecology and the growth of the WP. In 2008, we offered travel fellowships to over 28 graduate students. This year, over 20 individuals received similar support.

We would like to offer special thanks to Dr. Thomas Crow for his leadership since 1990. The WP has grown to have a permanent Webpage (http://research.eeescience.utoledo.edu/lees/IUFRO/), a listserv to promote communication (iufro8-l@mtu.edu), an online registration service and a committee structure that is composed of regional coordinators and liaisons with the International Association of Landscape Ecology (IALE). As of July, 2010, there are 475 members in the WP database. The journal of Landscape Ecology reserves a special page for us to publish important developments from the WP. Since 2008, the WP started sponsoring summer short courses and regional workshops for researchers, students and managers. To keep our communication beyond this conference, I strongly encourage you to subscribe to a membership via our Webpage and share your experiences, new developments, personnel changes, etc. via the WP’s listserv.

While growing, we face new challenges. The increasing influence from global change is, no doubt, a major one. The science of landscape ecology can no longer be independent of the changes surrounding us. An equally important issue is from the increasing demands of people and intensified activities. These challenges are the primary reasons for us to have the theme of this conference as “Forest Landscapes and Global Change: New Frontiers in Management, Conservation and Restoration”. Through face-to-face interactions during the conference, I am very confident that everyone will be stimulated for new initiatives under this theme. However, we hope the stimulations will go beyond the conference and are translated to your daily actions after returning to your home.

The WP appreciates the kindness of Instituto Politécnico de Bragança to organize this conference. We also owe a lot to the members of the Organization Committee, Scientific Committee and the Scholarship Committee for their quality work over the past 48 months. Without the financial and in-kind support of many organizations, we would not be able to have this great conference.

Jiquan Chen

Chair, IUFRO8.01.02

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Preface

This volume contains the contributions of numerous participants at the IUFRO Landscape Ecology Working Group International Conference, which took place in Bragança, Portugal, from 21 to 24 of September 2010. The conference was dedicated to the theme Forest Landscapes and Global Change - New Frontiers in Management, Conservation and Restoration. The 128 papers included in this book follow the structure and topics of the conference. Sections 1 to 8 include papers relative to presentations in 18 thematic oral and two poster sessions. Section 9 is devoted to a wide-range of landscape ecology fields covered in the 12 symposia of the conference. The Proceedings of the IUFRO Landscape Ecology Working Group International Conference register the growth of scientific interest in forest landscape patterns and processes, and the recognition of the role of landscape ecology in the advancement of science and management, particularly within the context of emerging physical, social and political drivers of change, which influence forest systems and the services they provide. We believe that these papers, together with the presentations and debate which took place during the IUFRO Landscape Ecology Working Group International Conference – Bragança 2010, will definitively contribute to the advancement of landscape ecology and science in general.

For their additional effort and commitment, we thank all the participants in the conference for leaving this record of their work, thoughts and science.

The Editors

João Carlos Azevedo Manuel Feliciano José Castro Maria Alice Pinto

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Section 1

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Environmental drivers of benthic communities: the importance of

landscape metrics

Rui Cortes

1

, Simone Varandas

1

, Samantha Hughes

1

, Marco Magalhães

1

& Amílcar

Teixeira

2*

1

CITAB, Universidade de Trás-os-Montes e Alto Douro, Portugal

2

CIMO, ESA, Instituto Politécnico de Bragança, Portugal

Abstract

The distribution of aquatic communities is dependent on processes that act at multiplescales. This study comprised 270 samples distributed over 2 years and used a nested sampling design to estimate the variance associated with three spatial scales: basin, site and microhabitat. Habitat assessment was made using River Habitat Survey. The derived Habitat Quality Indices and the benthic composition were crossed with landscape metrics and types of soil use, obtained from GIS data, using multiple non-parametric regressions and distance-based redundancy analysis. Invertebrate variation was mainly linked with intermediate scale (site) and landscape metrics were the main drivers determining local characteristics. The aquatic community exhibited a stronger relationship with landscape metrics, especially patch size and shape complexity of the dominant uses, than with habitat quality, suggesting that instream habitat improvement is a short-term solution and that stream rehabilitation must address the influence of components at higher spatial scales.

Keywords: landscape metrics, soil use, macroinvertebrates, habitat, spatial scale

1. Introduction

The hierarchy theory indicates that small scale physical and biological features are hierarchical nested by variables on larger spatial scales, which means that in-stream conditions are constrained and controlled by successive larger-sale factors, interacting as filters along those scales (Frissell et al. 1986; Poff, 1997). Lotic biological assemblages occurring at a given site are a subset of the potential pool of colonizers that have passed through a system of filters related to the environmental variables and their modification by human action (Boyero, 2003; Bonada et al., 2005). This is the case of geology, climate and landscape-level factors such as land use or vegetation patterns that have been shown to influence local habitat condition and therefore the composition of benthic fauna (Roth et al. 1996; Lammert & Allan, 1999; Joy & Death, 2004). More recently, studies tended to focus on analyzing the dependence of hydromorphological characteristics on catchment level features and land-use, in particular whether reach or catchment scale vegetation constitute suitable predictors of in-stream features (Allan, 2004; Buffagni et al., 2009; Sandin, 2009). There is a strong need to develop habitat assessment strategies that integrate different complementary spatial scales from microhabitat level (including hydraulics) to the assessment of river corridor condition and surrounding land use (Cortes et al., 2009). These aspects have been already incorporated into methodologies proposed in different field surveys (e.g. Raven, 1998). There is no doubt that the spatial hierarchy of fluvial ecosystems is a crucial aspect to consider, since identifying the relationships between different levels allows associations to be made between habitat features, processes and communities. This knowledge is essential for improving the implementation of appropriate

*Corresponding author: Email address: amilt@ipb.pt

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V. Cortes et al. 2010. Environmental drivers of benthic communities: the importance of landscape metrics 3

management and monitoring measures (Sandin, 2009), as the effect of multiple human pressures on aquatic habitats is spread over several spatial scales (Hughes et al., 2008).

The main objective of this work was to assess the influence of environmental attributes expressed at different scales on stream communities, particularly macroinvertebrates, and to determine how the habitat descriptors are shaped by higher spatial scales, namely landscape patterns.

2. Methodology

A hierarchical nested design was used for sampling benthic communities. In this study it was considered 4 catchments (Rivers Olo, Corgo, Pinhão and Tua), 15 sites distributed by the river network, 3 transects in each site and 3 micro-habitats (replicates) in each site. All catchments are located in the Douro basin (Northern Portugal) and are subjected to distinct natural conditions (such as high gradient streams ranging from 1100 m to 50 m of altitude). Furthermore, there are preserved areas, like the Olo and Tua catchments, contrasting with other areas influenced by an intensive agriculture (specially vineyards), located in the downstream sectors of rivers Corgo and Pinhão (Figure 1).

Figure 1: Location of the 15 study sites along the Olo, Corgo, Pinhão and Tua rivers, all from the Douro catchment, Northern Portugal. Study sites are spread along the longitudinal axis of the main rivers, but the

Tua catchment, which was only sampled in the lower section.

Invertebrates sampling was made in 2006 and 2007 in these micro-habitats using surber samples. Invertebrates were identified to genus level to most of the families (except Diptera and Oligochaeta).The relationship between large scale variables and the benthic fauna was assessed using both species composition and species traits. The environmental variables considered covered two levels of observation:

a) At landscape and soil use scale the data was obtained from Corine Landcover and it was considered a circle of 1km radius around each site. In the first case we used a set of metrics that can be grouped in patch metrics of density and size, edge, shape and of diversity and interspersion. These metrics were further applied to each type of soil use originating a total of 48 variables (Table 1).

b) At the aquatic habitat and river corridor scale it was applied the River Habitat Survey methodology (RHS - Raven et al., 1997, 1998). Ten transects or “spot checks” were made at

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50m intervals along the 500m reach and discrete descriptions obtained (e.g. cover channel substrate, flow type, aquatic vegetation types, bank vegetation structure, artificial modifications). Continuous observations or “sweep up” along the 500m reach characterized features and modifications not described at the spot-checks (e.g. natural and man-made features, or riparian vegetation). Two habitat indices, derived from the RHS were determined: 1) Habitat Quality Assessment (HQA), that is an expression of the habitat quality (e.g., physical habitat, vegetation cover, the use of marginal land), and 2) Habitat Modification Score (HMS) that quantifies the extent of artificialization (e.g. weirs, bank protections) along the channel.

Table 1: Environmental descriptors used for describing landscape-land use and habitats at each of the 15 sites included in the Rivers Olo, Corgo, Pinhão and Tua, The landscape metrics were applied to the

different soil use types resulting in a total of 48 landscape variables.

Landscape metrics Soil use variables Habitat descriptors

PATCH DENSITY AND SIZE METRICS

Number of patches Total edge

Patch size stands dev.

SHAPE METRICS

Mean shape index

Mean patch fractal dimension Weighted mean patch fractal dimension

Agriculture land, except vineyards (area in m2 and %)

Vineyards (area: m2 and %) Coniferous woodland (are: m2 ; %) Broadleaf woodland (area: m2; %) Mixed woodland area (area: m2; %) Urban area (area in m2 and %) Scrub & shrubs (area in m2 and %) Water surface including reservoirs and wetlands (area in m2 and %)

ARTIFICIAL FEATURES

Habitat Modification Score (HMS)

HABITAT QUALITY

HQA flow HQA channel HQA bank features

HQA bank vegetation structure HQA point bars

HQA in-stream channel vegetation HQA land use

HQA trees

HQA special features

A nested permutational MANOVA from resemblance matrix based on the Bray-Curtis coeficient was used to test the significance of benthic composition from the different spatial levels (catchment, site and transect).

Multiple non-parametric regressions from

distance-based linear models (DISTLM) were established between invertebrate taxa and the

environmental variables by using the following independent variables (separately):

habitat quality indices, soil use variables and landscape metrics (Table 1).

Ordination

techniques using distance-based redundance analysis (dbRDA) were established between benthic fauna, but expressed as metrics sensitive to contamination and soil use and landscape metrics. The biological metrics were extracted from Varandas & Cortes (2009) since they proved to be the most sensitive to disturbance in catchments of North Portugal (Table 2). Multivariate analyses were carried out using the package PERMANOVA for PRIMER (Anderson et al., 2008).

Table 2: List of invertebrate metrics selected (Oliveira & Cortes, 2009). Acronyms are indicated in bold.

Invertebrate metrics

Families of Predators fP % Shredders %Shr

Fam. of Ephem., Plecop., Trichop. fEPT % Scrapers %Scr

Families of Swimmers fSwi % Filterers %Fil

Families of Clingers fCling % Gatherers %Gath

% Rheophilous %Rhe % Predators %Pred

Genus of shredders gShr % Limnophilous %Lim

Genus of Filterers gFil % Omnivorous %Omn

Families of Gatherers fGath % organisms with branchial respiration %br

% Intolerants %Int % organisms with cutaneous respiration %cr

Index IBMWP % organisms with aerial respiration %ar

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Results

The results of the MANOVA for benthic composition are presented on Table 3, separately for each year, and showed that site produced the significant differences for both years (p <0.05) whereas differences between catchments were less evident.

Table 3: Hierarchical MANOVA performed separately for both years of field study (2006 and 2007)

Source of variation (2006) df Mean squares Pseudo-F P

Catchment 3 16625 1.482 0.044*

Site 11 11157 5.415 0.001*

Transect 30 2062 1.439 0.001*

Residual 90 1433

Source of variation (2007) df Mean squares Pseudo-F P

Catchment 3 11771 1.290 0.115

Site 11 9122 4.859 0.001*

Transect 30 1178 1.065 0.182

Residual 90 1763

Multiple non-parametric regressions (DISTLM) between macroinvertebrate taxa and

habitat quality illustrated the greater importance of landscape metrics in shaping benthic

composition, in particular the fractal dimension of hardwood forest, agriculture patches

and number of vineyard patches, followed by soil use (agriculture; p < 0.05) (Table 4).

Table 4. Multiple non-parametric regressions, using AIC criterion, between benthic invertebrate communities, habitat indices, land uses and landscape metrics.

MODEL with RHS indices; R2= 0.218 Variables selected (Best model 2 var.)

HQA flow type

HQA vegetation channel

AIC 109.60 109.26 Pseudo-F 1.22 2.03 P 0.269 0.380

MODEL with Land use variables; R2= 0.313 Variables selected (Best model 2 var.)

Agriculture area Hardwood forest AIC 107.75 107.31 Pseudo-F 3.09 2.12 P 0.04* 0.22

MODEL with Landscape metrics; R2= 0.978 Variables selected (Best model 13 var.)

Area weighted patch fractal dimension of agriculture Total edge hardwood forest

Patch size standard deviation of mixed forest Number of patches of vineyard

Mean fractal dimension area patch of hardwood Number of patches of agriculture

Area weighted patch fractal dimensionof mixed forest

AIC 106.93 106.19 105.98 105.22 104.63 103.51 101.24 Pseudo-F 4.00 2.40 1.75 2.01 1.70 1.85 2.30 P 0.01* 0.05 0.11 0.02* 0.07 0.07 0.03*

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The dbRDA ordinations, grouping biological and environmental data are represented on Figure 2, with separate plots for biological and environmental variables. The 1st axis reflected the longitudinal variation, where the landscape variables linked to the natural cover (forest and shrubs) define the sites located upstream and the ones associated with the vineyard influence more the lower reaches. On the first sites we may notice the presence of less disturbed communities reflected by higher values of the biotic index, EPT, shredders and intolerant fauna, whereas this pattern is replaced downstream by a dominance of organisms with branchial and cutaneous respiration, belonging to trophic groups with mainly filterers and gatherers.

Concerning the relation between benthic fauna and soil use it was also detected a

longitudinal gradient related to soil use from natural areas (e.g. hardwood forest) to

agriculture (including vineyards).

Figure 2: Redundance analysis (dbRDA) between invertebrate metrics and landscape metrics. The left diagram represents the biological metrics and on the one on the right represents the landscape patterns. Acronyms for landscape metrics: N number of patches; SD- patch size standard deviation,SI- mean shape index, SH- mean patch fractal dimension, FR- area weighted mean patch fractal dimension; the last

letters represent vegetation types: VIN vineyard; AG agriculture; FF broadleaf forest; FR coniferous forest; FM mixed forest; URB urban area (see Table 2 for the biological metric codes)

Discussion

Many studies using environmental variables determined at different spatial levels,

attempt to extract the relevant scales that lend structure to aquatic communities such as

benthic macroinvertebrate assemblages (Roth et al., 1996; Lammert and Allan, 1999).

Lowe et al. (2006), who made a revision on patterns and processes across multiple

scales of stream-habitat organization, emphasize the fractal network structure of stream

systems at a landscape scale and mention the need to understand how the spatial

configuration of habitats within a network affect fluxes of individuals and materials.

The same authors conclude that broader use of multiscale approaches to explore

population and community dynamics and species-ecosystem linkages in streams will

produce research results that are applicable to management and conservation challenges.

This study found that landscape metrics provided a powerful tool for assessing both

macroinvertebrate dynamics, instream habitats and also the river corridor. It was also

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found that soil use descriptors were associated with the typological functioning of the

river system displayed by the longitudinal succession of benthic assemblages.

References

Allan J.D., 2004. Landscapes and riverscapes: The influence of land use on stream ecosystems.

Annual Review of Ecology Evolution and Systematics, 35: 257-284.

Anderson M.J., Gorley R.N. and Clarke K.R., 2008. PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods. Plymouth, U.K.: Primer-E Ltd.

Bonada N., Zamora-Muñoz C., Rieradevall M. and Prat N., 2005. Ecological and historical filters constraining spatial caddisfly distribution in Mediterranean rivers. Freshwater Biology, 50: 81-797.

Boyero L., 2003. Multiscale patterns of spatial variation in stream macroinvertebrate communities. Ecological Research, 18: 365-379.

Buffagni A, Casalegno C. and Erba S., 2009. Hydromorphology and land use at different spatial scales: expectations in a changing climate scenario for medium-sized rivers of the Western Italian Alps. Fundamental and Applied Ecology, 74: 7-25.

Cortes R.M.V., Hughes S.J., Varandas S.G.P., Magalhães M. and Ferreira M.T., 2009. Habitat variation at different scales and biotic linkages in lotic systems: consequences for monitorization. Aquatic Ecology 43: 1107-1120.

Frissell C.A., Liss W.J., Warren C.E. and Hurley M.D., 1986. A Hierarchical Framework for Stream Habitat Classification- Viewing Streams in a Watershed Context. Environmental Management, 10: 199-214.

Hughes S.J, Ferreira M.T. and Cortes R.M.V., 2008. Hierarchical spatial patterns and drivers of change in benthic macroinvertebrate communities in an intermittent Mediterranean river.

Aquatic Conservation: Marine and Freshwater Ecosystems, 18: 742-760.

Joy M.K. and Death R.G., 2004. Predictive modelling and spatial mapping of freshwater fish and decapod assemblages: an integrated GIS and neural network approach. Freshwater Biology, 49: 1036-1052.

Lammert M. and Allan J.D., 1999. Environmental Auditing: Assessing biotic integrity of streams: Effects of scale in measuring the influence of land use/cover and habitat structure on fish and macroinvertebrates. Environmental Management, 23: 257–270.

Lowe, W.H., Likens G.E. and Power M.E., 2006. Linking Scales in Stream Ecology. BioScience, 55: 591-597.

Poff N.L., 1997. Landscape filters and species traits: Towards mechanistic understanding and prediction in stream ecology. Journal of the North American Benthological Society, 16: 391-409.

Raven P.J., P. Fox J.A., Everard M., Holmes N.T.H. and Dawson F.H., 1997. River Habitat Survey: a new system for classifying rivers according to their habitat quality. In: Boon, P.J., Howell, D.L. (eds). Freshwater quality: defining the indefinable? The Stationery office, Edinburg, 215-234 pp.

Raven P.J., Holmes N.T.H., Dawson F.H., Fox P.J.A., Everard M., Fozzard I.R. and Rouen K.J., 1998. River habitat quality: the physical character of rivers and streams in the UK and the Isle of Man. River Habitat Survey report no. 2, Environment Agency, Bristol.

Roth N.E., Allan J.D. and Erickson D.L., 1996. Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology, 11: 141–156.

Sandin L., 2009. The relationship between land-use, hydromorphology and river biota at different spatial and temporal scales: a synthesis of seven case studies. Fundamental and Applied Ecology, 174: 1-5.

Varandas S.G. & Cortes R.M.V., 2009. Evaluating macroinvertebrate biological metrics for ecological assessment of streams in northern Portugal. Environmental Monitoring Assessment, DOI 10.1007/s10661-009-0996-4.

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Habitat suitability models for two species of forest raptors in Catalonia.

Methodological consequences related with different scales and data

sources

David Sánchez de Ron

1

, Lluís Brotons

2

, Santiago Saura

3

& José M. García del Barrio

1,4

1

CIFOR-INIA, Madrid, Spain

2

Centre Tecnològic Forestal de Catalunya, Solsona, Spain

3

ETSIM-UPM Madrid, Spain

4

Instituto Universitario Investigación Gestión Forestal Sostenible, UVA-INIA, Spain

Abstract

Species distribution along a territory is a function of different environmental variables that changes in space and time. In this communication we use GIS based information from different sources and at different scales (1x1 km2 and 10x10 km2) for elaborating habitat suitability models of two forest raptors species (Buteo buteo and Accipiter gentilis) along a north-south gradient in Cataluña. The area of study has an extent of 7000 km2. Forest raptors species presence/absence data on 679 1x1 km2 grid cells of the Catalan Breeding Bird Atlas, and Spanish Forest Map at a scale 1:50,000 are the main information sources. Logistic regression methods have been essayed for comparison across different scales. Unexpectedly, preliminary results show no relation between variables like land use type or diversity of habitats and raptors presence at 1x 1 km2 , and this relationship is only significant for Buteo buteo at 10 x 10 km2 scale.

Keywords: Habitat suitability models, land uses, logistic regression, changing scales.

1. Introduction

Animal species related to forest habitats are dependent on habitat extension but on habitat quality as well. Advances in knowing species distribution and habitat requirements are essential for studies of population genetics, evolutionary and conservation biology, biodiversity maintenance and territorial planning, among others. Recent georeferenced information about not only species distribution in Spain, but also related to climate, lithology, changes in land uses or historical disturbances (wild fires, floods, wind storms) at different scales are valuable data sources that contribute to the elaboration of habitat suitability models that are the basis for connectivity or habitat fragmentation analysis (Pascual-Hortal & Saura, 2008). Specialist species have been affected by reduction of habitat extension and population fragmentation (see Farhig, 2001; Lindenmayer, et al, 2003; Alderman et al, 2005) with the consequence of reduction on effective population levels. Spanish forest raptors are not the exception, and a proper knowledge of habitat requirements and habitat suitability is needed. Underlying reasons for explain mismatch between potential and real distribution of a species are scale dependent, and the explanation of this dependence is one of the goals of habitat suitability models –HSM hereafter- (

Ottaviani et al, 2004; Guisan and Thuiller, 2005).

In a previous paper (García del Barrio et al, 2009) we essayed HSM for two forest raptors on two forest districts of central-east Spain with presence/absence data at 10x10 km2 scale. The aim of this paper is to compare the performance of HSM at changing scales and using different data sources. Forest raptors species chosen are goshawk (Accipiter gentilis) and common

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D. S. de Ron et al. 2010. Habitat suitability models for two species of forest raptors in Catalonia 9

buzzard (Buteo buteo) distributed in a noth-south gradient of 140 km in Catalonia with presence/absence data at 1x1 km2 and frequency data at 10x10 km2 aggregation level.

2. Methodology

Study zone is located in Catalonia (northeast Spain). Seventy 10 x 10 km2 (5 x 14 quadrates) units were selected along a 140 km north-south gradient. Limits were 42º 32’ N - 41º 16’N and 1º 25’ E – 2º 3’E. Geographic gradient ranges from Pyrenees Mountain with altitude over 3000 m to Mediterranean coast at sea level.

Species data came from 679 1 x 1 km2 quadrates surveyed in the Catalan Breeding Bird Atlas 1999-2002 (Estrada et al. 2004), covering less than 10 % of the study zone. Land use data came from the Spanish Forest Map at a 1:50,000 scale. Forest raptors selected were goshawk (Accipiter gentilis) and common buzzard (Buteo buteo). Goshawk is a species with a wide distribution area across Europe, inhabits several types of forest from mountain coniferous to Mediterranean evergreen at low lands. Common buzzard is a species broadly distributed along Iberian Peninsula, less dependent than goshawk of extensive forested areas.

Land uses have been reclassified following Table 1. Mean elevation was the physiographic variable selected. Mean annual precipitation, mean annual temperature and summer precipitation were the climatic variables (Gonzalo, 2007).

Generalized linear models (GLZs) had been essayed; binomial-log for presence/absence data at 1 x 1 km2 level, and normal-log for frequency data at 10 x 10 km2 level (Statistica v.7). Firstly we examined each independent variable in relation with the dependent and secondly, if there was significance of any of the independent ones, they were put together and interactions were considered in the model.

3. Result

The analysis at 1 x 1 km2 resolution have not had noteworthy relationships between dependent and independent variables, neither land uses variables nor climatic or topographic ones. Table 2 shows, for the two raptors species, matches between land uses in habitat areas and total study area. Figure 1 represents the distribution of forested land use in three areas with the presence of the raptors and total study area.

Goshawk

presence is reduced to 28 of 679 quadrates (4.1 % of the effective sampled area) and main land uses in this area are very similar to that on the total area, only with the exception of fewer incidences of artificial land uses. C

ommon buzzard

reaches 24 % of presence (163 of 679 1 x 1 km2 quadrates are occupied) but no significant relationships between species presence and land use or climatic variables have been found. At 10 x 10 km2 scale, goshawk frequency has not relevant relationships with independent variables selected, and modeling is not possible. The case of common buzzard is different because an equation that explain 36 % of deviance can be formulated

FBb= -3.223+0.516xA+0.021xF+0.001xCxF-0.005xCxA-0.009xAxF (1) FBb: frequency of presence at 10 x 10 km 2 (nº presences/nº total) A: % of articial areas F: % of forest areas C: % of cultivated areas

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Equation 1 shows that final model includes only land uses variables, not topographic or climatic ones. Two single variables (A, F) and three interactions between A, F y C slightly explain actual distribution of common buzzard in the study area (Table 3). There is no evident explanation to the incidence of interaction variables, whereas the positive effect of forest areas is obvious but the same effect of artificial in not so much explainable.

4. Discussion

The paper explores the use of recently sampled data of nesting birds in Catalonia in relation with main land uses and other topographic and climatic variables. Presence/absence data at 1 x 1 km2 resolution and frequency data at 10 x 10 km2 where used for modeling Habitat Suitability for two forest raptors species. Surprisingly, no relationships where found at the more detailed scale, and only a slight relation could be modeled (Figure 2) for the more abundant raptor species (common buzzard) at a coarser resolution level.

These are not good news because high spatial resolution data of species distribution should be the basis for modeling connectivity, habitat fragmentation and other indicators relatives to species conservation. If we could not model in relation with the main territorial requirements of a species, and where they are located across the territory, it would be difficult to predict species colonization movements or habitat loss driving forces.

It should be possible that the two main reasons that affect the absence of correlation found at 1 x 1 km2 resolution, is that the sampled territory is less than 10 % of total territory and land uses distribution in species presence plots and total plots is quite similar, where no determinant for other species and other sampling areas at the same resolution levels, but there are not very much reasons to be optimist with the problem of true or false absences. Manel et al (2001) showed some problems that are not been solved in data acquisition methods, and modeling HSM with this kind of data is not so accurate.

Next question is relative to habitat saturation by a target species in a territory. This relationship depends not only of potential habitat or potential niche but also of the effective niche. There are some biotic interdependence that land uses variables or climatic and topographic ones do not reflect. Human pressure in Spain over raptor species had historically reduced their distribution areas, driving some of them near extinction. Absence of preys is other meaningful reason that we could not evaluate in these models, and for the migrant species maybe questions relative to synchronization of movements are important too.

Finally, we could conclude that the use of presence/absence data at 1 x 1 km2 resolution for two raptors species in Cataluña, in relation with land use, climatic and tophographic variables had not improved the slight predictive power of the HSM at 10 x 10 km2 resolution. Including variables of avian richness, potential prey’s richness or some relative could be improving the response of models but, in general, data relative to these variables are not available at broad scales.

References

Alderman, J., McCollin, D., Hinsley, S. A., Bellamy, P. E., Picton, P. & Crockett, R. 2005. Modelling the effects of dispersal and landscape configuration on population distribution and viability in fragmented habitat. Landscape Ecology. 20: 857-870

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Estrada J., Pedrocchi V., Brotons L., Herrando S. (eds), 2004.

Atles dels ocells

nidificants de Catalunya 1999-2002

. Institut Català d'Ornitologia (ICO)/Lynx

Edicions, Barcelona, España, 638 pp.

García del Barrio, J.M., Sánchez de Ron, D., de Miguel, J., Ortega, M., Elena-Rosselló, R. 2009. Modelos de disponibilidad de hábitat aplicados a dos especies de rapaces forestales en las comarcas de Urbión y el Alto Tajo. Actas del 5º congreso Forestal Español. CD publication.

Gonzalo, J. (2007).Diagnosis fitoclimática de la España Peninsular. Actualización y análisis geoestadístico aplicado. Tesis Doctoral.

Guisan, A. & Thuiller, W. 2005. Predicting species distribution; offering more than simple habitat models. Ecology Letters, 8: 993-1009.

Fahrig, L. 2001. How much habitat is enough? Biological Conservation, 100: 65-74.

Lindenmayer, D.B.,H. P. Possingham, R. C. Lacy, M. A. McCarthy and Pope M. L. 2003. How accurate are population models? Lessons from landscape-scale tests in a fragmented system. Ecology Letters 6: 41-47

Manel, S., Ceri Williams, H. and Ormerod, S. J. 2001. Evaluating presence-absence models in ecology: The need to account for prevalence. Journal of Applied Ecology 38: 921-931. Ottaviani,D., G. L. Lasiano y L. Boitani. 2004. Two statistical methods to validate habitat

suitability models using presence-only data. Ecological Modelling. 179: 417-443.

Pascual-Hortal, L. & S. Saura. 2008. Integrating landscape connectivity in broad-scale forest planning through a new graph-based habitat availability methodology: application to capercaillie (Tetrao urogallus) in Catalonia (NE Spain). European Journal of Forest Research 127: 23-31

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Tables and Figures

Table 1: Main land uses in the study area (14x 5 quadrates of 10 x 10 km2 in Catalonia) Land cover class Total Area (ha) %

Tree forested (F) 441000 63

Cultivated areas (C) 161000 23

Grassland and pastures ( G) 35000 5

Artificial (A) 35000 5

Scrub land (S) 21000 3

Others (O) 7000 1

Total 70000 100

Table 2: Relationships between land uses in total sampled area and areas with presence of raptor species

1x1 10X10

Total area

Accipiter

gentilis Buteo buteo Total area

Accipiter gentilis

Buteo buteo

n %area n %area n %area n %area n %area n %area

Tree forested (F) 679 62.4 28 63.2 163 66.0 70 62.6 19 60.4 56 63.2 Cultivated areas (C) 679 25.5 28 29.0 163 28.1 70 22.9 19 24.7 56 23.8 Artificial (A) 679 4.1 28 1.9 163 1.3 70 4.8 19 8.8 56 3.9 Grassland and pastures ( G) 679 3.2 28 2.6 163 1.7 70 5.3 19 2.7 56 5.0 Scrub land (S) 679 2.9 28 2.4 163 1.8 70 2.9 19 1.7 56 2.5 Mosaic with trees 679 0.7 28 0.0 163 0.3 70 0.5 19 0.6 56 0.5 Other forested 679 0.6 28 0.1 163 0.2 70 0.7 19 0.7 56 0.7 Body water 679 0.5 28 0.7 163 0.6 70 0.3 19 0.4 56 0.3 Mosaic without

trees 679 0.2 28 0.0 163 0.0 70 0.1 19 0.1 56 0.1

Table 3: Generalized Linear Model statistics for common buzzard frequency at 10 x 10 km2 scale.

Df Residual

Desviance

Scaled P

Chi2 Change desviance P desviance F

Intercept 69 3.15290 70

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Figure 1: Distribution of land use tree forested land use on total sampled area in quadrates of 1 x 1 km2, with presence of A. gentilis (Ag) or B. buteo (Bb). Min= Minimum, Pc= percentile, Max=

Maximum.

Figure 2: Real (A) and modeled distribution (B) on 10 x 10 km2 for common buzzard. Circles in both A and B represent presence/absence data at 1 x 1 km2 level.

Tree forested land use

0 10 20 30 40 50 60 70 80 90 100 Min Pc 5 Pc 25 Pc 50 Pc 75 Pc 95 Max Total area Ag Bb

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Section 2

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B. Bożętka 2010. Recent relations between forestry and agriculture in Poland 15

Recent relations between forestry and agriculture in Poland -

the rural landscape on the axis of openness and enclosure

Barbara Bo

żę

tka

*

Gda

ń

sk University, 4 J. Ba

ż

y

ń

skiego Str., 80-952 Gda

ń

sk, Poland

Abstract

The paper refers to a complex problem of landscape change in Poland. It concentrates on quality as well as quantity transformation within forestry and agriculture and their consequences for the rural landscape. A systematic increase in a forest cover connected with a decrease in agricultural land is observed in Poland. The tendencies are accompanied by landscape disturbance processes, such as settlement sprawl and intensification of agriculture.

The work presented here stresses the influence of above mentioned factors on landscape structure; it employs a broad-scale analysis and focuses on the last two decades. The issue of landscape heterogeneity is widely investigated and regional differences have been underlined.

Since the landscape configurationexperiences crucial changes, an axis of openness- enclosure and its spatial redistribution received special attention.

Keywords: landscape, structure, rural areas, reforestation, Poland

1. Introduction

A spatial arrangement of elements demonstrating open or enclosed character strongly determines landscape configuration. Patterns of open and enclosed spaces organize and differentiate the land. Besides their compositional values (see Bell 2004), coexistence of open-enclosed units fulfils significant ecological functions, e.g. enhancing or inhibiting material and energy flows in ecosystems. The context of openness and enclosure may also underline variability of landscapes and their dependence on a man-made impact.

The Polish rural landscape has been facing considerable changes for the last two decades, which result mainly from operation of new driving forces appearing after a political reorientation in 1989. Demands of a market economy altogether with a global environmental agenda, restrictions and regulations introduced by EU accession in 2004 set in motion new processes. They modify traditional land-use patterns, influence structure, functions and values of the rural landscape. Interestingly, the processes are well pronounced in interrelations between forestry and agriculture- two main functions held by the rural areas in Poland.

2. The Polish rural landscape and its characteristic features

Regarding a landscape typology at a continental level, at least two types of the rural landscape should be distinguished in Poland: open fields and strip fields (e.g. Kostrowicki 1994, Meeus 1995). Agricultural land has had the greatest share in the total area of the country for centuries; nowadays it equals 50.9 % (Stat.Yearb.Rep. 2010) and consists mainly of arable fields and meadows. Noteworthy, non-natural factors have dominated the evolution of the agricultural landscape and very close relations between: 1. meadows, pastures and the river network and 2. arable land and settlement constitute a typical structural feature of the rural

*_{Corresponding author. Tel. 0048/58 523 65 61}

Forest landscapes and global change. New frontiers in management, conservation and restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference

Bragança · Portugal

IUFRO Landscape Ecology Working Group

International Conference

New Frontiers

in Management,

Conservation

and Restoration

Proceedings

Edited by

João Carlos Azevedo

Manuel Feliciano

José Castro

Maria Alice Pinto

Landscapes

Forest

and Global

Change

Forest Landscapes and Global Change

New Frontiers in Management, Conservation and Restoration

The contributions to this volume have not been peer-reviewed. Only minor changes in

format may have been carried out by the editors.

New Frontiers in Management, Conservation and Restoration

Proceedings of the

IUFRO Landscape Ecology Working Group International Conference

September 21-27, 2010

Bragança, Portugal

Edited by

João Carlos Azevedo

Manuel Feliciano

José Castro

Maria Alice Pinto

Instituto Politécnico de Bragança, Portugal

September, 2010

Table of contents

xiii

Foreword

Preface

Section 1

Environmental drivers of benthic communities: the importance of

landscape metrics

Rui Cortes

, Simone Varandas

, Samantha Hughes

, Marco Magalhães

& Amílcar

Teixeira

CITAB, Universidade de Trás-os-Montes e Alto Douro, Portugal

CIMO, ESA, Instituto Politécnico de Bragança, Portugal

Abstract

1. Introduction

2. Methodology

Multiple non-parametric regressions from

distance-based linear models (DISTLM) were established between invertebrate taxa and the

environmental variables by using the following independent variables (separately):

habitat quality indices, soil use variables and landscape metrics (Table 1).

Invertebrate metrics

Results

Multiple non-parametric regressions (DISTLM) between macroinvertebrate taxa and

habitat quality illustrated the greater importance of landscape metrics in shaping benthic

composition, in particular the fractal dimension of hardwood forest, agriculture patches

and number of vineyard patches, followed by soil use (agriculture; p < 0.05) (Table 4).

Concerning the relation between benthic fauna and soil use it was also detected a

longitudinal gradient related to soil use from natural areas (e.g. hardwood forest) to

agriculture (including vineyards).

Discussion

Many studies using environmental variables determined at different spatial levels,

attempt to extract the relevant scales that lend structure to aquatic communities such as

benthic macroinvertebrate assemblages (Roth et al., 1996; Lammert and Allan, 1999).

Lowe et al. (2006), who made a revision on patterns and processes across multiple

scales of stream-habitat organization, emphasize the fractal network structure of stream

systems at a landscape scale and mention the need to understand how the spatial

configuration of habitats within a network affect fluxes of individuals and materials.

The same authors conclude that broader use of multiscale approaches to explore

population and community dynamics and species-ecosystem linkages in streams will

produce research results that are applicable to management and conservation challenges.

This study found that landscape metrics provided a powerful tool for assessing both

macroinvertebrate dynamics, instream habitats and also the river corridor. It was also

found that soil use descriptors were associated with the typological functioning of the

river system displayed by the longitudinal succession of benthic assemblages.