Systematic Temporal Patterns in the Relationship Between Housing Development and Forest Bird Biodiversity

As people encroach increasingly on natural areas, one question is how this affects avian biodiversity. The answer to this is partly scale‐dependent. At broad scales, human populations and biodiversity concentrate in the same areas and are positively associated, but at local scales people and biodiversity are negatively associated with biodiversity. We investigated whether there is also a systematic temporal trend in the relationship between bird biodiversity and housing development. We used linear regression to examine associations between forest bird species richness and housing growth in the conterminous United States over 30 years. Our data sources were the North American Breeding Bird Survey and the 2000 decennial U.S. Census. In the 9 largest forested ecoregions, housing density increased continually over time. Across the conterminous United States, the association between bird species richness and housing density was positive for virtually all guilds except ground nesting birds. We found a systematic trajectory of declining bird species richness as housing increased through time. In more recently developed ecoregions, where housing density was still low, the association with bird species richness was neutral or positive. In ecoregions that were developed earlier and where housing density was highest, the association of housing density with bird species richness for most guilds was negative and grew stronger with advancing decades. We propose that in general the relationship between human settlement and biodiversity over time unfolds as a 2‐phase process. The first phase is apparently innocuous; associations are positive due to coincidence of low‐density housing with high biodiversity. The second phase is highly detrimental to biodiversity, and increases in housing density are associated with biodiversity losses. The long‐term effect on biodiversity depends on the final housing density. This general pattern can help unify our understanding of the relationship of human encroachment and biodiversity response. Patrones Sistemáticos Temporales en la Relación entre Desarrollos Urbanos y la Biodiversidad de Aves de Bosque     

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.     

Effectiveness of Community Forestry in Prey Long Forest,Cambodia

Cambodia has 57% forest cover, the second highest in the Greater Mekong region, and a high deforestation rate (1.2%/year, 2005–2010). Community forestry (CF) has been proposed as a way to reduce deforestation and support livelihoods through local management of forests. CF is expanding rapidly in Cambodia. The National Forests Program aims to designate one million hectares of forest to CF by 2030. However, the effectiveness of CF in conservation is not clear due to a global lack of controlled comparisons, multiple meanings of CF, and the context‐specific nature of CF implementation. We assessed the effectiveness of CF by comparing 9 CF sites with paired controls in state production forest in the area of Prey Long forest, Cambodia. We assessed forest condition in 18–20 randomly placed variable‐radius plots and fixed‐area regeneration plots. We surveyed 10% of households in each of the 9 CF villages to determine the proportion that used forest products, as a measure of household dependence on the forest. CF sites had fewer signs of anthropogenic damage (cut stems, stumps, and burned trees), higher aboveground biomass, more regenerating stems, and reduced canopy openness than control areas. Abundance of economically valuable species, however, was higher in control sites. We used survey results and geographic parameters to model factors affecting CF outcomes. Interaction between management type, CF or control, and forest dependence indicated that CF was more effective in cases where the community relied on forest products for subsistence use and income. Efectividad de la Silvicultura Comunal en el Bosque Prey Long, Camboya     

Analytical Solutions to Trade‐Offs between Size of Protected Areas and Land‐Use Intensity

Abstract: Land‐use change is affecting Earth's capacity to support both wild species and a growing human population. The question is how best to manage landscapes for both species conservation and economic output. If large areas are protected to conserve species richness, then the unprotected areas must be used more intensively. Likewise, low‐intensity use leaves less area protected but may allow wild species to persist in areas that are used for market purposes. This dilemma is present in policy debates on agriculture, housing, and forestry. Our goal was to develop a theoretical model to evaluate which land‐use strategy maximizes economic output while maintaining species richness. Our theoretical model extends previous analytical models by allowing land‐use intensity on unprotected land to influence species richness in protected areas. We devised general models in which species richness (with modified species‐area curves) and economic output (a Cobb–Douglas production function) are a function of land‐use intensity and the proportion of land protected. Economic output increased as land‐use intensity and extent increased, and species richness responded to increased intensity either negatively or following the intermediate disturbance hypothesis. We solved the model analytically to identify the combination of land‐use intensity and protected area that provided the maximum amount of economic output, given a target level of species richness. The land‐use strategy that maximized economic output while maintaining species richness depended jointly on the response of species richness to land‐use intensity and protection and the effect of land use outside protected areas on species richness within protected areas. Regardless of the land‐use strategy, species richness tended to respond to changing land‐use intensity and extent in a highly nonlinear fashion.     

Monitoring of Triazine and Phenylurea Herbicides in the Surface Waters of Greece

A large-scale study was implemented to monitor triazine and phenylurea herbicides in the main surface water bodies of continental Greece from October 1998 to September 1999. Samples from 10 rivers and 7 lakes were analyzed for the presence of five triazine (atrazine, cyanazine, prometryne, simazine, terbuthylazine) and five phenylurea (chlorotoluron, diuron, linuron, metobromuron, monolinuron) herbicides. The samples were extracted with C18 cartridges and analyzed by high-performance liquid chromatography–diode array detection (HPLC-DAD). The most frequently detected herbicides were atrazine, followed by prometryne, cyanazine, and simazine. The concentrations of the compounds were generally low (< 0.78 μ g/L) and are not considered harmful for the freshwater ecosystem. Most of the positive samples were taken from the water bodies of northern Greece where agricultural activity is more intense.     

Human Impacts on Regional Avian Diversity and Abundance

Abstract: Patterns of association between humans and biodiversity typically show positive, negative, or negative quadratic relationships and can be described by 3 hypotheses: biologically rich areas that support high human population densities co‐occur with areas of high biodiversity (productivity); biodiversity decreases monotonically with increasing human activities (ecosystem stress); and biodiversity peaks at intermediate levels of human influence (intermediate disturbance). To test these hypotheses, we compared anthropogenic land cover and housing units, as indices of human influence, with bird species richness and abundance across the Midwestern United States. We modeled richness of native birds with 12 candidate models of land cover and housing to evaluate the empirical evidence. To assess which species were responsible for observed variation in richness, we repeated our model‐selection analysis with relative abundance of each native species as the response and then asked whether natural‐history traits were associated with positive, negative, or mixed responses. Native avian richness was highest where anthropogenic land cover was lowest and housing units were intermediate based on model‐averaged predictions among a confidence set of candidate models. Eighty‐three of 132 species showed some pattern of association with our measures of human influence. Of these species approximately 40% were negatively associated, approximately 6% were positively associated, and approximately 7% showed evidence of an intermediate relationship with human influence measures. Natural‐history traits were not closely related to the direction of the relationship between abundance and human influence. Nevertheless, pooling species that exhibited any relationship with human influence and comparing them with unrelated species indicated they were significantly smaller, nested closer to the ground, had shorter incubation and fledging times, and tended to be altricial. Our results support the ecosystem‐stress hypothesis for the majority of individual species and for overall species diversity when focusing on anthropogenic land cover. Nevertheless, the great variability in housing units across the land‐cover gradient indicates that an intermediate‐disturbance relationship is also supported. Our findings suggest preemptive conservation action should be taken, whereby areas with little anthropogenic land cover are given conservation priority. Nevertheless, conservation action should not be limited to pristine landscapes because our results showed that native avian richness and the relative abundance of many species peaked at intermediate housing densities and levels of anthropogenic land cover.     

Evaluating Microbial Indicators of Environmental Condition in Oregon Rivers

Traditional bacterial indicators used in public health to assess water quality and the Biolog system were evaluated to compare their response to biological, chemical, and physical habitat indicators of stream condition both within the state of Oregon and among ecoregion aggregates (Coast Range, Willamette Valley, Cascades, and eastern Oregon). Forty-three randomly selected Oregon river sites were sampled during the summer in 1997 and 1998. The public health indicators included heterotrophic plate counts (HPC), total coliforms (TC), fecal coliforms (FC) and Escherichia coli (EC). Statewide, HPC correlated strongly with physical habitat (elevation, riparian complexity, % canopy presence, and indices of agriculture, pavement, road, pasture, and total disturbance) and chemistry (pH, dissolved O2, specific conductance, acid-neutralizing capacity, dissolved organic carbon, total N, total P, SiO2, and SO4). FC and EC were significantly correlated generally with the river chemistry indicators. TC bacteria significantly correlated with riparian complexity, road disturbance, dissolved O2, and SiO2 and FC. Analyzing the sites by ecoregion, eastern Oregon was characterized by high HPC, FC, EC, nutrient loads, and indices of human disturbance, whereas the Cascades ecoregion had correspondingly low counts of these indicators. The Coast Range and Willamette Valley presented inconsistent indicator patterns that are more difficult to characterize. Attempts to distinguish between ecoregions with the Biolog system were not successful, nor did a statistical pattern emerge between the first five principle components and the other environmental indicators. Our research suggests that some traditional public health microbial indicators may be useful in measuring the environmental condition of lotic systems.     

Allee Effect and the Uncertainty of Population Recovery

Recovery of depleted populations is fundamentally important for conservation biology and sustainable resource harvesting. At low abundance, population growth rate, a primary determinant of population recovery, is generally assumed to be relatively fast because competition is low (i.e., negative density dependence). But population growth can be limited in small populations by an Allee effect. This is particularly relevant for collapsed populations or species that have not recovered despite large reductions in, or elimination of, threats. We investigated how an Allee effect can influence the dynamics of recovery. We used Atlantic cod (Gadus morhua) as the study organism and an empirically quantified Allee effect for the species to parameterize our simulations. We simulated recovery through an individual‐based mechanistic simulation model and then compared recovery among scenarios incorporating an Allee effect, negative density dependence, and an intermediate scenario. Although an Allee effect significantly slowed recovery, such that population increase could be negligible even after 100 years or more, it also made the time required for biomass rebuilding much less predictable. Our finding that an Allee effect greatly increased the uncertainty in recovery time frames provides an empirically based explanation for why the removal of threat does not always result in the recovery of depleted populations or species. El Efecto Allee y la Incertidumbre de la Recuperación de Poblaciones