MULTIDIMENSIONAL PERCEPTION OF RESIDENTIAL ENVIRONMENT QUALITY AND NEIGHBOURHOOD ATTACHMENT IN THE URBAN ENVIRONMENT

This study tests a path model in which residential satisfaction, operationalized in terms of multidimensional perceived residential environment quality (PREQ), predicts neighbourhood attachment considered as the final criterion. Socio-demographic (age, sex, socio-economic level) and residential (length of residence both in the neighbourhood and in Rome, number of persons living together) variables are also included in the theoretical model as predictors of both PREQ and neighbourhood attachment. Using a multidimensional questionnaire for the measurement of PREQ and a unidimensional scale for the measurement of neighbourhood attachment, the study focuses on a sample of 497 inhabitants from 20 different neighbourhoods in the city of Rome. The multidimensional PREQ questionnaire comprises 20 different scales covering four main areas: architectural and town-planning features (six scales); social relations features (three scales); punctual and in-network services (six scales); context features (five scales). First, the path model is tested separately in each area using structural equation analysis. Then, the best predictors emerging from each area, together with all socio-demographic and residential variables, are included in a final model. This model shows both the relevance of predictors from all four areas in predicting attachment, and also a hierarchy between the areas in the power of the prediction (context area giving the most powerful predictors, services giving the weakest ones, architectural and town-planning, and social relations having intermediate importance). Length of residence in the neighbourhood and socio-economic level are the most relevant of the residential and socio-demographic variables. Results are discussed with reference to the multicomponential nature of the process of neighbourhood attachment.     

Cost‐Effectiveness of Using Small Vertebrates as Indicators of Disturbance

In species‐rich tropical forests, effective biodiversity management demands measures of progress, yet budgetary limitations typically constrain capacity of decision makers to assess response of biological communities to habitat change. One approach is to identify ecological‐disturbance indicator species (EDIS) whose monitoring is also monetarily cost‐effective. These species can be identified by determining individual species’ responses to disturbance across a gradient; however, such responses may be confounded by factors other than disturbance. For example, in mountain environments the effects of anthropogenic habitat alteration are commonly confounded by elevation. EDIS have been identified with the indicator value (IndVal) metric, but there are weaknesses in the application of this approach in complex montane systems. We surveyed birds, small mammals, bats, and leaf‐litter lizards in differentially disturbed cloud forest of the Ecuadorian Andes. We then incorporated elevation in generalized linear (mixed) models (GL(M)M) to screen for EDIS in the data set. Finally, we used rarefaction of species accumulation data to compare relative monetary costs of identifying and monitoring EDIS at equal sampling effort, based on species richness. Our GL(M)M generated greater numbers of EDIS but fewer characteristic species relative to IndVal. In absolute terms birds were the most cost‐effective of the 4 taxa surveyed. We found one low‐cost bird EDIS. In terms of the number of indicators generated as a proportion of species richness, EDIS of small mammals were the most cost‐effective. Our approach has the potential to be a useful tool for facilitating more sustainable management of Andean forest systems. Rentabilidad del Uso de Pequeños Vertebrados como Indicadores de Perturbaciones     

Spatial and Seasonal Patterns of Bird Communities in Italian Agroecosystems

Abstract:  Despite agricultural landscapes covering almost 60% of the total land area of Italy, knowledge of the effects of agriculture and its intensification on bird communities is still scarce. I analyzed the effects of land uses on bird diversity and community structure in different farmland habitats of lowland northwestern Italy. I surveyed breeding and overwintering birds with a hierarchically nested sampling design and used generalized linear and mixed models to investigate the relationships between the diversity and abundance of birds and habitat or landscapes attributes. The effects of agriculture on α avian diversity varied with season and spatial scale, whereas nonagricultural habitats (long-term fallows or woodlands) had a generally positive effect that was constant throughout time and space. As the amount of woodland habitat increased, spatial turnover (β diversity) of breeding birds decreased. Arable landscapes supported low levels of avian diversity throughout the year but were favored by emblematic farmland birds that have declined severely in Europe and in the study area. Farmland birds (40% of which are experiencing population declines) were more abundant or foraged more frequently in the less-disturbed habitat types such as fallows, grasslands, and winter stubbles and tended to avoid the prevailing cultivations (maize, vineyard, and wheat). Landscape simplification, the expansion of maize cultivation, winter plowing practices, and the conversion of highly diverse grasslands to tilled lands are likely to be responsible for the local decline of most farmland species (Skylark [Alauda arvensis ], Starling [Sturnus vulgaris ], buntings [Emberiza spp.], and wagtails [Motacilla spp.]) and for the increase of birds that are turning into agricultural pests (Hooded Crow [Corvus corone cornix ]).