Landscape changes and ecological studies in agricultural regions,Québec,Canada

Most landscape definitions in the western world are based on soil, climatic, or physiographic features and do not integrate humans as an integral part of the landscape. We present an approach where landscape types have been delineated in southern Québec, Canada based on current land use where anthropogenic and agricultural activities are concentrated as a practical application of the holistic approach in landscape definition. Landsat-TM satellite images were classified and the 27 habitat classes were regrouped into 5 general land cover classes (cash crop, dairy farming, forest, anthropogenic, wetlands) and overlaid onto soil landscape polygons to characterize natural boundary units. Cluster analyses were used to aggregate these polygons into seven agricultural types of land scape forming a gradient from urban and high-intensity cash crop farming activities to landscapes dominated by a mosaic of agriculture and forested areas. Multivariate analyses of raw data and of socio-economic and farming practices variables were used to describe the defined types of landscape and these were projected over three established land classification systems of southern Québec (Canadian ecoregions, North American Bird Conservation Initiative regions and Corn Heat Unit regions) to compare their similarity in terms of land cover and for planning of future ecological studies. Because agricultural landscapes are highly dynamic, they are bound to undergo changes in the near future. Our landscape delineation may serve as an experimental setup where land scape dynamics and wildlife populations and community structures could be monitored. Because the information we used to delineate and characterize agricultural landscape types is readily available in other countries, our approach could easily be adapted to similar data sources under and a wide variety of landscape types. This revised version was published online in July 2006 with corrections to the Cover Date.     

我国大蒜产业现状及发展对策

大蒜是一种经济作物。我国大蒜种植历史悠久,目前以大蒜产业为主要收入的农户有千万人以上;在国际市场上,我国大蒜占据超过60%的份额,是世界上最大的大蒜生产国和消费国。然而,随着经济的发展,大蒜产业在发展过程中逐渐暴露出许多问题。本文针对我国大蒜产业的现状和问题,提出了解决对策,为我国调整大蒜产业发展结构提供理论依据。     

Optimizing landscape selection for estimating relative effects of landscape variables on ecological responses

Empirical studies of the relative effects of landscape variables may compromise inferential strength with common approaches to landscape selection. We propose a methodology for landscape sample selection that is designed to overcome some common statistical pitfalls that may hamper estimates of relative effects of landscape variables on ecological responses. We illustrate our proposed methodology through an application aimed at quantifying the relationships between farmland heterogeneity and biodiversity. For this project, we required 100 study landscapes that represented the widest possible ranges of compositional and configurational farmland heterogeneity, where these two aspects of heterogeneity were quantified as crop cover diversity (Shannon diversity index) and mean crop field size, respectively. These were calculated at multiple spatial extents from a detailed map of the region derived through satellite image segmentation and classification. Potential study landscapes were then selected in a structured approach such that: (1) they represented the widest possible range of both heterogeneity variables, (2) they were not spatially autocorrelated, and (3) there was independence (no correlation) between the two heterogeneity variables, allowing for more precise estimates of the regression coefficients that reflect their independent effects. All selection criteria were satisfied at multiple extents surrounding the study landscapes, to allow for multi-scale analysis. Our approach to landscape selection should improve the inferential strength of studies estimating the relative effects of landscape variables, particularly those with a view to developing land management guidelines.     

A fuzzy logic method to assess the relationship between landscape patterns and bird richness of the Rolling Pampas

The loss of biodiversity in productive ecosystems is a global concern of the last decades. The Rolling Pampas of Argentina is an intensively cropped region that underwent important land use and landscape change, with different impacts on biodiversity of both plants and animals. Land use type and habitat complexity are hypothesized to be the most important factors determining species richness in agro-ecosystems. But it is not easy to define these attributes in an unambiguous fashion, or determine their interactions at different spatial scales. A fuzzy logic approach allows overcoming some of these problems by using linguistic variables and logic rules to relate them and formulate hypothesis. We constructed fuzzy logic models to study how bird species richness in the Rolling Pampas is related to land use and habitat complexity, and how these variables interact at two spatial scales. Results showed that at the local scale, landscape complexity is the most important factor determining species numbers; trees and bodies of water are the most influential complexities. The effect of local scale landscape attributes was modified depending on the context at broader scales, so that agricultural sites were enriched when surrounded by more favorable landscapes. There was a high dispersion in the predicted/observed value relationship, indicating that landscape factors interact in more complex ways than those captured by the models we used. We suggest that the fuzzy logic approach is suitable for working with biological systems, and we discuss the advantages and disadvantages of its use.     

Ecosystem services in changing landscapes: An introduction

The concept of ecosystem services from landscapes is rapidly gaining momentum as a language to communicate values and benefits to scientists and lay alike. Landscape ecology has an enormous contribution to make to this field, and one could argue, uniquely so. Tools developed or adapted for landscape ecology are being increasingly used to assist with the quantification, modelling, mapping, and valuing of ecosystem services. Several of these tools and methods encased therein are described among the eleven papers presented in this special issue, and their application has the potential to facilitate the management and promotion of services within ecosystems. Papers are associated with each of the four key categories of services that ecosystems provide to humans: supporting, provisioning, regulating, and cultural. The papers represent work conducted in eleven different countries, especially from South America. Each carries a unique approach to address a particular question pertaining to a particular set of ecosystem services. These studies are designed to inform and improve the economic, environmental and social values of the ecosystem services. This knowledge should help to develop new management alternatives for sustaining and planning ecosystems and the services they provide at different scales in space and time. We believe that these papers will create interest and inform management of some potential methods to evaluate ecosystem services at the landscape level with an integrative approach, offering new tools for management and conservation.     

Data quality in citizen science urban tree inventories

Citizen science has been gaining popularity in ecological research and resource management in general and in urban forestry specifically. As municipalities and nonprofits engage volunteers in tree data collection, it is critical to understand data quality. We investigated observation error by comparing street tree data collected by experts to data collected by less experienced field crews in Lombard, IL; Grand Rapids, MI; Philadelphia, PA; and Malmö, Sweden. Participants occasionally missed trees (1.2%) or counted extra trees (1.0%). Participants were approximately 90% consistent with experts for site type, land use, dieback, and genus identification. Within correct genera, participants recorded species consistent with experts for 84.8% of trees. Mortality status was highly consistent (99.8% of live trees correctly reported as such), however, there were few standing dead trees overall to evaluate this issue. Crown transparency and wood condition had the poorest performance and participants expressed concerns with these variables; we conclude that these variables should be dropped from future citizen science projects. In measuring diameter at breast height (DBH), participants had challenges with multi-stemmed trees. For single-stem trees, DBH measured by participants matched expert values exactly for 20.2% of trees, within 0.254 cm for 54.4%, and within 2.54 cm for 93.3%. Participants’ DBH values were slightly larger than expert DBH on average (+0.33 cm), indicating systematic bias. Volunteer data collection may be a viable option for some urban forest management and research needs, particularly if genus-level identification and DBH at coarse precision are acceptable. To promote greater consistency among field crews, we suggest techniques to encourage consistent population counts, using simpler methods for multi-stemmed trees, providing more resources for species identification, and more photo examples for other variables. Citizen science urban forest inventory and monitoring projects should use data validation and quality assurance procedures to enhance and document data quality.     

Using the connoisseur method during the introductory phase of landscape planning and management

The European Landscape Convention (ELC) has called for a broad anchoring in all sorts of landscape issues in local society. The connoisseur approach aims to improve communication in decision making processes by ensuring that personal and local knowledge on people, and their knowledge and feelings of everyday landscape is considered in projects on landscape development. The approach described here was tested in three Swedish case studies. Two were part of the European NeighbourWoods research project: the Skrylle Recreation Forest in south-west Sweden and the Ronneby Brunn area in south-east Sweden. Two areas that are heavily used for recreation by groups unrelated to the management of the forests. The Tinnerö area near Linköping was included as a third case. Our approach involved identifying and testing methods for introductory phase of management planning and countryside development.The methods developed in the connoisseur approach included in-depth interviews during field walks, walk-and-talk encounters, designating favourite places and routes on maps and management meetings between connoisseurs (local people, planners, and experts). Such concrete methods, which benefit from being mainly conducted outdoors, sought to empower local people, nurture a sense of belonging to a place and the management process, raise awareness of the local landscape and its potential, and identify shared values. The connoisseur approach proved to be a useful tool in the introductory phase, by clarifying the varying interests of local user groups, and was successful in creating links between the user groups, manager team, local politicians and administrators. Although unfamiliar to many people, the connoisseur method may effectively complement standardized, expert-dominated, top-down concepts of planning.     

The Effects of Uncertainty on Estimating the Relative Environmental Quality of Watersheds Across a Region

Landscape ecologists may be faced with ranking the relative environmental quality of watersheds across a region. The rankings would be based on measured or modeled variables with inherent sources of error. This paper examines the impact of data uncertainty on the ranking assigned to watersheds. The approach is Monte Carlo simulation in which the individual variables are considered to be estimated with uncertainty. The results show that watersheds in the best and the worst condition have rankings that are robust to uncertainty but intermediate watersheds may be difficult or impossible to assign to a rank. Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect offcial Agency policy.     

Application of artificial intelligence for tree risk assessment optimization in Itanhaém – São Paulo,Brazil

Tree risk assessment consists of the identification of a set of defects that may affect the stability of the tree, leading to a possible collapse or failure, either of the whole plant or a part of it; and also, the identification of the targets to be reached and the side effects caused by any eventual failure. Although this is a necessary practice, the large number of variables involved in this evaluation makes the analysis time-consuming. Thus, this research aimed to optimize the tree risk assessment by creating a new protocol with the three visual assessment methods common variables and generating a new protocol applied to trees of species frequently used in urban afforestation worldwide: Terminalia catappa, Ficus Benjamin and Delonix regia. Altogether 36 variables were used for tree risk visual assessment applied in the evaluation of 230 trees located in the urban forest in Itanhaém - São Paulo - Brazil. The data collection was carried out using a smartphone and a data spreadsheet created in ODK collect app, facilitating data storage and processing. To identify the variables with the greatest possibility to determine the risk of falling, artificial intelligence was used through the Decision Tree algorithm (C4.5) in the WEKA software. The results showed that, from the 36 variables evaluated, 14 were enough to determine the risk of tree falling, with 73% hit rate in the tree risk classification. It is concluded that the use of artificial intelligence was essential in detecting tree problems in order to redirect management practices.