Ecosystem Engineering Effects On Species Diversity Across Ecosystems: A Meta-analysis.

Ecosystem engineering is increasingly recognized as a relevant ecological driver of diversity and community composition. Although engineering impacts on the biota can vary from negative to positive, and from trivial to enormous, patterns and causes of variation in the magnitude of engineering effects across ecosystems and engineer types remain largely unknown. To elucidate the above patterns, we conducted a meta-analysis of 122 studies which explored effects of animal ecosystem engineers on species richness of other organisms in the community. The analysis revealed that the overall effect of ecosystem engineers on diversity is positive and corresponds to a 25% increase in species richness, indicating that ecosystem engineering is a facilitative process globally. Engineering effects were stronger in the tropics than at higher latitudes, likely because new or modified habitats provided by engineers in the tropics may help minimize competition and predation pressures on resident species. Within aquatic environments, engineering impacts were stronger in marine ecosystems (rocky shores) than in streams. In terrestrial ecosystems, engineers displayed stronger positive effects in arid environments (e.g. deserts). Ecosystem engineers that create new habitats or microhabitats had stronger effects than those that modify habitats or cause bioturbation. Invertebrate engineers and those with lower engineering persistence (<1 year) affected species richness more than vertebrate engineers which persisted for >1 year. Invertebrate species richness was particularly responsive to engineering impacts. This study is the first attempt to build an integrative framework of engineering effects on species diversity; it highlights the importance of considering latitude, habitat, engineering functional group, taxon and persistence of their effects in future theoretical and empirical studies.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Post Hoc Analysis Of The Patricia Randomized Trial Of The Efficacy Of Human Papillomavirus Type 16 (hpv-16)/hpv-18 As04-adjuvanted Vaccine Against Incident And Persistent Infection With Nonvaccine Oncogenic Hpv Types Using An Alternative Multiplex Type-specific Pcr Assay For Hpv Dna.

The efficacy of the human papillomavirus type 16 (HPV-16)/HPV-18 AS04-adjuvanted vaccine against cervical infections with HPV in the Papilloma Trial against Cancer in Young Adults (PATRICIA) was evaluated using a combination of the broad-spectrum L1-based SPF10 PCR-DNA enzyme immunoassay (DEIA)/line probe assay (LiPA25) system with type-specific PCRs for HPV-16 and -18. Broad-spectrum PCR assays may underestimate the presence of HPV genotypes present at relatively low concentrations in multiple infections, due to competition between genotypes. Therefore, samples were retrospectively reanalyzed using a testing algorithm incorporating the SPF10 PCR-DEIA/LiPA25 plus a novel E6-based multiplex type-specific PCR and reverse hybridization assay (MPTS12 RHA), which permits detection of a panel of nine oncogenic HPV genotypes (types 16, 18, 31, 33, 35, 45, 52, 58, and 59). For the vaccine against HPV types 16 and 18, there was no major impact on estimates of vaccine efficacy (VE) for incident or 6-month or 12-month persistent infections when the MPTS12 RHA was included in the testing algorithm versus estimates with the protocol-specified algorithm. However, the alternative testing algorithm showed greater sensitivity than the protocol-specified algorithm for detection of some nonvaccine oncogenic HPV types. More cases were gained in the control group than in the vaccine group, leading to higher point estimates of VE for 6-month and 12-month persistent infections for the nonvaccine oncogenic types included in the MPTS12 RHA assay (types 31, 33, 35, 45, 52, 58, and 59). This post hoc analysis indicates that the per-protocol testing algorithm used in PATRICIA underestimated the VE against some nonvaccine oncogenic HPV types and that the choice of the HPV DNA testing methodology is important for the evaluation of VE in clinical trials. (This study has been registered at ClinicalTrials.gov under registration no. NCT00122681.).

Is size structure a good measure of future trends of plant populations? an empirical approach using five woody species from the Cerrado (Brazilian savanna)

Size distributions in woody plant populations have been used to assess their regeneration status, assuming that size structures with reverse-J shapes represent stable populations. We present an empirical approach of this issue using five woody species from the Cerrado. Considering count data for all plants of these five species over a 12-year period, we analyzed size distribution by: a) plotting frequency distributions and their adjustment to the negative exponential curve and b) calculating the Gini coefficient. To look for a relationship between size structure and future trends, we considered the size structures from the first census year. We analyzed changes in number over time and performed a simple population viability analysis, which gives the mean population growth rate, its variance and the probability of extinction in a given time period. Frequency distributions and the Gini coefficient were not able to predict future trends in population numbers. We recommend that managers should not use measures of size structure as a basis for management decisions without applying more appropriate demographic studies.