How far can we go in simplifying biomonitoring assessments? An integrated analysis of taxonomic surrogacy, taxonomic sufficiency and numerical resolution in a megadiverse region

The need for biodiversity conservation is increasing at a rate much faster than the acquisition of knowledge of biodiversity, such as descriptions of new species and mapping species distributions. As global changes are winning the race against the acquisition of knowledge, many researchers resort to the use of surrogate groups to aid in conservation decisions. Reductions in taxonomic and numerical resolution are also desirable, because they could allow more rapid the acquisition of knowledge while requiring less effort, if little important information is lost. In this study, we evaluated the congruence among 22 taxonomic groups sampled in a tropical forest in the Amazon basin. Our aim was to evaluate if any of these groups could be used as surrogates for the others in monitoring programs. We also evaluated if the taxonomic or numerical resolution of possible surrogates could be reduced without greatly reducing the overall congruence. Congruence among plant groups was high, whereas the congruence among most animal groups was very low, except for anurans in which congruence values were only slightly lower than for plants. Liana (Bignoniaceae) was the group with highest congruence, even using genera presence-absence data. The congruence among groups was related to environmental factors, specifically the clay and phosphorous contents of soil. Several groups showed strong spatial clumping, but this was unrelated to the congruence among groups. The high degree of congruence of lianas with the other groups suggests that it may be a reasonable surrogate group, mainly for the other plant groups analyzed, if soil data are not available. Although lianas are difficult to count and identify, the number of studies on the ecology of lianas is increasing. Most of these studies have concluded that lianas are increasing in abundance in tropical forests. In addition to the high congruence, lianas are worth monitoring in their own right because they are sensitive to global warming and the increasing frequency and severity of droughts in tropical regions. Our findings suggest that the use of data on surrogate groups with relatively low taxonomic and numerical resolutions can be a reliable shortcut for biodiversity assessments, especially in megadiverse areas with high rates of habitat conversion, where the lack of biodiversity knowledge is pervasive. (c) 2012 Elsevier Ltd. All rights reserved.PhD scholarship from the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq

Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change

Forecasts of species range shifts under climate change are fraught with uncertainties and ensemble forecasting may provide a framework to deal with such uncertainties. Here, a novel approach to partition the variance among modeled attributes, such as richness or turnover, and map sources of uncertainty in ensembles of forecasts is presented. We model the distributions of 3837 New World birds and project them into 2080. We then quantify and map the relative contribution of different sources of uncertainty from alternative methods for niche modeling, general circulation models (AOGCM), and emission scenarios. The greatest source of uncertainty in forecasts of species range shifts arises from using alternative methods for niche modeling, followed by AOGCM, and their interaction. Our results concur with previous studies that discovered that projections from alternative models can be extremely varied, but we provide a new analytical framework to examine uncertainties in models by quantifying their importance and mapping their patterns

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.

The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low

Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation

Coefficient shifts in geographical ecology: An empirical evaluation of spatial and non-spatial regression

12 páginas, 4 figuras, 3 tablas.A major focus of geographical ecology and macroecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modeling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; "OLS models" hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation.The western Andalusia database generated by RGA and AA was supported by the Andalusian Regional Government (Consejería de Medio Ambiente and Consejería de Innovación, Ciencia y Empresa project P06-RNM-01499). MÁR, MR and MÁO-T were supported by the Spanish Ministry of Science and Innovation (grant CGL2006-03000/BOS and FPU fellowship AP2005-0636 to MA´ O-T). Work by LMB, JAFDF, TFLVBR, PMJ, JML and MBA on species distribution modeling and spatial analysis was supported by the BBVA Foundation BIOIMPACT project. LMB, JAFDF and PMJ have been supported by several CNPq grants, and TFLVBR was further supported by a CAPES/Fulbright PhD Fellowship.Peer reviewe

Current climate, climate change since Last Glacial Maximum and diversity gradients throughout Europe

Peer Reviewe

Efeitos de diferentes intervenções no processo de eutrofização do lago Paranoá (Brasília - DF)

EFFECTS OF INTERVENTIONS ON THE EUTROPHICATION PROCESS OF PARANOÁ LAKE RESERVOIR OF BRASILIA, BRAZIL. Long-term environmental monitoring of aquatic ecosystems is essential to understand their dynamics and to the proposition of management practices. Paranoá Reservoir was created in 1959 and was subject to a long period of eutrophication. In this paper, data obtained by the monitoring program carried out by the �Companhia de Abastecimento e Saneamento de Brasília�, between 1976 and 2001, were evaluated to measure the effects of three direct interventions on water quality (as measured by water transparency, P-total and chlorophyll-a concentrations): the activation of two water treatment plants (01/1993); the proper operation of these plants (01/1996), and a major fl ushing event (sudden release of water in 11/1999). The following results were obtained: i) the fi rst intervention had no effect on the mean values of the variables analyzed; ii) the chlorophyll-a and total phosphorus concentrations signifi cantly declined after the second intervention; iii) water transparency increased after the third intervention. An apparent mechanism of phosphorus feedback supported by phytoplankton was interrupted by the fl ushing and, after that intervention, the primary production of Paranoá Reservoir declined to a new level. The dataset obtained by the monitoring program was essential to understand this process and, therefore, the continuity (and even amplifi cation) of this program was fully justifi ed. Keywords: environmental monitoring, intervention analysis, primary production, tropical water reservoir.O monitoramento temporal das variáveis de um corpo d¿água possibilita o conhecimento de sua dinâmica e, por fi m, de seu manejo. O Lago Paranoá em Brasília, formado em 1959, passou por um longo período de eutrofi zação. Neste trabalho, usando dados de monitoramento de longa duração da CAESB, os efeitos da instalação de duas Estações de Tratamento de Esgoto (ETE) e de um evento de fl ushing foram avaliados para as variáveis Clorofi la-a, Fósforo Total e Transparência medidas entre 1976 e 2001. Utilizando- se da Análise de Intervenção foram mensuradas a efetividade de três intervenções: o início das operações das ETE (01/1993); o pleno funcionamento destas ETE (01/1996); e um evento de fl ushing (abertura abrupta das comportas, 11/1999). Os resultados mostram que: i) a 1a intervenção não surtiu nenhum efeito; ii) a 2ª intervenção fez com que os níveis de Fósforo Total e Clorofi la-a fossem reduzidos signifi cativamente; iii) apenas o fl ushing (3ª intervenção), fez com que a transparência da água aumentasse para mais de um metro na maioria dos pontos, inferindo-se que apesar da redução do aporte de fósforo ao lago com as ETE (1ª e 2ª intervenções), a abundância restante de fi toplâncton na água tenha mantido um mecanismo de feedback com o fósforo que só foi interrompido com a abertura abrupta das comportas que eliminou o fi toplâncton da superfície e conduziu o lago à um novo patamar de produção primária. O programa de monitoramento da CAESB foi fundamental para o entendimento deste processo e o que justi fi ca a manutenção e a ampliação deste programa. Palavras-chave: intervenção, reservatório tropical, CAESB, monitoramento, Paranoá

Forecasting conservation impact to pinpoint spatial priorities in the Brazilian Cerrado

Proper assessing the impacts of conservation interventions can create interaction spaces between researcher and implementation. For example, protected areas (PM) are the main strategy to conserve biodiversity, but there is a widespread bias in their location towards unproductive and inaccessible lands. Thus, investments on PM are likely to have been allocated to areas that did not need protection, at least in the short term, creating communication noise to the society. Here, we estimate the likely conservation impact of the recently established (2002-2012) PM and indigenous lands (ILs) in a future scenario of land use projected to 2050. We selected areas that were similar to the PAs/ILs with positive conservation impact to propose spatial priorities aiming to minimize loss of Cerrado vegetation in the future. In our analyses, PM in general and those of strict protection had significantly lower conversion rates than control areas, while sustainable use PM and ILs showed no difference between control and protected areas. We did not find differences in impact values between PAs and ILs, but impact values were higher for strict protection than for sustainable use areas. We found a high density of potential priority areas to maximize impact in northern Cerrado. This region is the next agricultural frontier in the biome, having extensive vegetation cover that can be legally converted according to national legislation. By pinpointing conservation priorities based on impact, we can improve the benefit from land protection and increase the space of interactions between science, policymaking and society at large

Shortfalls in our understanding of the causes and consequences of functional and phylogenetic variation of freshwater communities across continents

Abstract Freshwater ecosystems harbour a disproportionately high biodiversity relative to their area, being also one of the most threatened ecosystem types worldwide. However, our capacity to design evidence-based conservation plans for this realm is restricted by all biodiversity shortfalls that have been recognized so far. In this context, the paucity of comparable field data and information on traits and phylogenies of freshwater organisms should be emphasized. Here, we highlight how increased knowledge could be gained and where we should aim at in research on the functional and phylogenetic features of freshwater communities. First, attempts to combine datasets from different sources should pay careful attention to data harmonization. Second, more effort should be focused on natural history observations on species habitats and life histories, providing the backbone of information for multi-trait databases. Third, fully resolved phylogenies would be required for deciphering the evolutionary relationships of freshwater organisms. Provided that these three hurdles can be overcome, conducting studies of local freshwater communities across continental spatial extents would pave the way for mapping functionally important ecosystems and evolutionarily valuable areas for the conservation of freshwater organisms and their habitats