Dependence of anuran diversity on environmental descriptors in farmland ponds

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Assessing ``inherent vulnerability'' of forests: a methodological approach and a case study from Western Ghats, India

The objective of this study is to present a methodological approach to assess the inherent vulnerability of forests and apply it to a case study. Addressing inherent vulnerability, resulting from current stresses, is a necessary step for building resilience to long-term climate change. The proposed approach includes use of analytical framework that enables selection of vulnerability criteria and indicators systematically, application of pairwise comparison method (PCM) for assigning weights, and synthesis of a composite vulnerability index. This methodological approach has been applied at local scale to Aduvalli Protected Forest in Western Ghats in South India, where a vulnerability index value of 0.248 is estimated. Results of the case study indicate that `preponderance of invasive species' and forest dependence of community are the major sources of vulnerability at present for Aduvalli Protected Forest. Adoption of this methodology can assist in development of forest management plans to enhance adaptability of Aduvalli PF to current as well as future stresses, including climate change. This methodological approach can be applied across forest-types after appropriate changes to criteria and indicators and their weights, to estimate the inherent vulnerability to enable development of adaptation strategy.

Avian assemblages in bamboo and non-bamboo habitats in a tropical rainforest

Some species of bird are closely associated with bamboos (bamboo specialists) but community-wide studies comparing the avian assemblages in bamboo and non-bamboo habitats are lacking. Using point counts, we compared the species richness, abundance and composition of the avian assemblages in bamboo and non-bamboo habitats in the Brazilian Atlantic forest. Apart from considering bamboo specialists and non-specialist species, we contrasted birds from different categories of forest dependence, forest strata and diet. We recorded a total of 81 species of birds (74 in bamboo, 55 in non-bamboo habitats), including 15 bamboo specialists. Species richness was greater in bamboo habitats in all categories of diet and forest dependence. Bamboo and non-bamboo habitats had a similar number of canopy species, but bamboo habitats had a greater number of non-canopy species. The abundance of the whole avian community or of each of the dietary categories did not differ between habitats. The overall species composition differed between habitats, with a more homogeneous composition in non-bamboo habitats. A great number of species use bamboo habitats, even if they are not bamboo specialists. The initial expansion of bamboos, forming discrete patches of bamboo within mature forest, represents an intermediate-level disturbance that enhances forest heterogeneity and promotes the diversity of avian communities. © BirdLife Australia 2013.

Fragmentação florestal: efeitos em múltipla escala sobre a diversidade de aves em remanescentes florestais no noroeste do Estado de São Paulo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The structure of bird communities in areas revegetated after mining in southern Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito da estrutura espacial de cobertura arbórea na comunidade de aves em parques urbanos no município de Jundiaí, SP

Pós-graduação em Engenharia Civil e Ambiental - FEB

Context-dependence in seed removal by lekking and non-lekking frugivorous birds in Brazilian Atlantic forest

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Negative density dependence and environmental heterogeneity effects on tree ferns across succession in a tropical montane forest.

Although tree ferns are an important component of temperate and tropical forests, very little is known about their ecology. Their peculiar biology (e.g., dispersal by spores and two-phase life cycle) makes it difficult to extrapolate current knowledge on the ecology of other tree species to tree ferns. In this paper, we studied the effects of negative density dependence (NDD) and environmental heterogeneity on populations of two abundant tree fern species, Cyathea caracasana and Alsophila engelii, and how these effects change across a successional gradient. Species patterns harbor information on processes such as competition that can be easily revealed using point pattern analysis techniques. However, its detection may be difficult due to the confounded effects of habitat heterogeneity. Here, we mapped three forest plots along a successional gradient in the montane forests of Southern Ecuador. We employed homogeneous and inhomogeneous K and pair correlation functions to quantify the change in the spatial pattern of different size classes and a case-control design to study associations between juvenile and adult tree ferns. Using spatial estimates of the biomass of four functional tree types (short- and long-lived pioneer, shade- and partial shade-tolerant) as covariates, we fitted heterogeneous Poisson models to the point pattern of juvenile and adult tree ferns and explored the existence of habitat dependencies on these patterns. Our study revealed NDD effects for C. caracasana and strong environmental filtering underlying the pattern of A. engelii. We found that adult and juvenile populations of both species responded differently to habitat heterogeneity and in most cases this heterogeneity was associated with the spatial distribution of biomass of the four functional tree types. These findings show the effectiveness of factoring out environmental heterogeneity to avoid confounding factors when studying NDD and demonstrate the usefulness of covariate maps derived from mapped communities.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Role of Temperature in the Biological Activity of a Boreal Forest

In northern latitudes, temperature is the key factor driving the temporal scales of biological activity, namely the length of the growing season and the seasonal efficiency of photosynthesis. The formation of atmospheric concentrations of biogenic volatile organic compounds (BVOCs) are linked to the intensity of biological activity. However, interdisciplinary knowledge of the role of temperature in the biological processes related to the annual cycle and photosynthesis and atmospheric chemistry is not fully understood. The aim of this study was to improve understanding of the role of temperature in these three interlinked areas: 1) onset of growing season, 2) photosynthetic efficiency and 3) BVOC air concentrations in a boreal forest. The results present a cross-section of the role of temperature on different spatial (southern northern boreal), structural (tree forest stand - forest) and temporal (day-season- year) scales. The fundamental status of the Thermal Time model in predicting the onset of spring recovery was confirmed. However, it was recommended that sequential models would be more appropriate tools when the onset of the growing season is estimated under a warmer climate. A similar type of relationship between photosynthetic efficiency and temperature history was found in both southern and northern boreal forest stands. This result draws attention to the critical question of the seasonal efficiency of coniferous species to emit organic compounds under a warmer climate. New knowledge about the temperature dependence of the concentrations of biogenic volatile organic compounds in a boreal forest stand was obtained. The seasonal progress and the inter-correlation of BVOC concentrations in ambient air indicated a link to biological activity. Temperature was found to be the main driving factor for the concentrations. However, in addition to temperature, other factors may play a significant role here, especially when the peak concentrations are studied. There is strong evidence that the spring recovery and phenological events of many plant species have already advanced in Europe. This study does not fully support this observation. In a boreal forest, changes in the annual cycle, especially the temperature requirement in winter, would have an impact on the atmospheric BVOC composition. According to this study, more joint phenological and BVOC field observations and laboratory experiments are still needed to improve these scenarios.

Development of biogenic VOC emission inventories for the boreal forest

Luonnosta haihtuvat orgaaniset yhdisteet, joita pääsee ilmaan etenkin metsistä, voivat vaikuttaa paikalliseen ja alueelliseen ilmanlaatuun, koska ne reagoivat ilmakehässä. Niiden reaktiotuotteet voivat myös osallistua uusien hiukkasten muodostumiseen ja kasvuun, millä voi olla vaikutusta ilmakehän säteilytaseeseen ja tätä kautta myös ilmastoon. Hiukkaset absorboivat ja sirottavat auringon säteilyä ja maapallon lämpösäteilyä minkä lisäksi ne vaikuttavat pilvien säteilyominaisuuksiin, määrään ja elinikään. Koko maapallon mittakaavassa luonnosta tulevat hiilivetypäästöt ylittävät ihmistoiminnan aiheuttamat päästöt moninkertaisesti. Tämän vuoksi luonnon päästöjen arviointi on tärkeää kun halutaan kehittää tehokkaita ilmanlaatu- ja ilmastostrategioita. Tämä tutkimus käsittelee boreaalisen metsän hiilivetypäästöjä. Boreaalinen metsä eli pohjoinen havumetsä on suurin maanpäällinen ekosysteemi, ja se ulottuu lähes yhtenäisenä nauhana koko pohjoisen pallonpuoliskon ympäri. Sille on tyypillistä puulajien suhteellisen pieni kirjo sekä olosuhteiden ja kasvun voimakkaat vuodenaikaisvaihtelut. Työssä on tutkittu Suomen yleisimmän boreaalisen puun eli männyn hiilivetypäästöjen vuodenaikaisvaihtelua sekä päästöjen riippuvuutta lämpötilasta ja valosta. Saatuja tuloksia on käytetty yhdessä muiden boreaalisilla puilla tehtyjen päästömittaustulosten kanssa Suomen metsiä varten kehitetyssä päästömallissa. Malli perustuu lisäksi maankäyttötietoihin, suomen metsille kehitettyyn luokitukseen ja meteorologisiin tietoihin, joiden avulla se laskee metsien hiilivetypäästöt kasvukauden aikana. Suomen metsien päästöt koostuvat koko kasvukauden ajan suurelta osin alfa- ja beta-pineenistä sekä delta-kareenista. Kesällä ja syksyllä päästöissä on myös paljon sabineenia, jota tulee etenkin lehtipuista. Päästöt seuraavat lämpötilan keskimääräistä vaihtelua, ovat suurimmillaan maan eteläosissa ja laskevat tasaisesti pohjoiseen siirryttäessä. Metsän isopreenipäästö on suhteellisen pieni – Suomessa tärkein isopreeniä päästävä puu on vähäpäästöinen kuusi, koska runsaspäästöisten pajun ja haavan osuus metsän lehtimassasta on hyvin pieni. Tässä työssä on myös laskettu ensimmäinen arvio metsän seskviterpeenipäästöistä. Seskviterpeenipäästöt alkavat Juhannuksen jälkeen ja ovat kasvukauden aikana samaa suuruusluokkaa kuin isopreenipäästöt. Vuositasolla Suomen metsien hiilivetypäästöt ovat noin kaksinkertaiset ihmistoiminnasta aiheutuviin päästöihin verrattuna.

Seeing the forest for the fuel

We demonstrate a new approach to understanding the role of fuelwood in the rural household economy by applying insights from travel cost modeling to author-compiled household survey data and meso-scale environmental statistics from Ruteng Park in Flores, Indonesia. We characterize Manggarai farming households' fuelwood collection trips as inputs into household production of the utility yielding service of cooking and heating. The number of trips taken by households depends on the shadow price of fuelwood collection or the travel cost, which is endogenous. Econometric analyses using truncated negative binomial regression models and correcting for endogeneity show that the Manggarai are 'economically rational' about fuelwood collection and access to the forests for fuelwood makes substantial contributions to household welfare. Increasing cost of forest access, wealth, use of alternative fuels, ownership of kerosene stoves, trees on farm, park staff activity, primary schools and roads, and overall development could all reduce dependence on collecting fuelwood from forests. © 2004 Cambridge University Press.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.