Immigration rates in fragmented landscapes--empirical evidence for the importance of habitat amount for species persistence

Role of limiting dispersal on metacommunity stability and persistence

The role of dispersal on the stability and synchrony of a metacommunity is a topic of considerable interest in theoretical ecology. Dispersal is known to promote both synchrony, which enhances the likelihood of extinction, and spatial heterogeneity, which favors the persistence of the population. Several efforts have been made to understand the effect of diverse variants of dispersal in the spatially distributed ecological community. Despite that environmental change strongly affects the dispersal, the effects of controlled dispersal on the metacommunity stability and their persistence remain unknown. We study the influence of limiting the immigration using two-patch prey-predator metacommunity at both local and spatial scales. We find that the spread of the inhomogeneous stable steady states (asynchronous states) decreases monotonically upon limiting the predator dispersal. Nevertheless, at the local scale, the spread of the inhomogeneous steady states increases up to a critical value of the limiting factor, favoring the metacommunity persistence, and then starts decreasing for a further decrease in the limiting factor with varying local interaction. Interestingly, limiting the prey dispersal promotes inhomogeneous steady states in a large region of the parameter space, thereby increasing the metacommunity persistence at both spatial and local scales. Further, we show similar qualitative dynamics in an entire class of complex networks consisting of a large number of patches. We also deduce various bifurcation curves and stability conditions for the inhomogeneous steady states, which we find to agree well with the simulation results. Thus, our findings on the effect of the limiting dispersal can help to develop conservation measures for ecological communities.

Small mammals in high fragmented landscape in Cerrado/Atlantic Forest ecotone, Southeastern Brazil

ABSTRACT Exploratory human activities have resulted in small fragments inserted into a matrix which is inhospitable to small non-flying mammals. The effects of landscape changes alter the distribution patterns of species. Landscape fragmentation patterns for small mammals are controversial, especially considering small fragments and ecotonal regions. Based on these arguments, we investigated the diversity patterns of small mammals in small fragments in the ecotonal Cerrado/Atlantic Forest region. A total of 24 fragments (<40 ha) were studied using tomahawk, sherman and pitfall traps. We found low species richness (11 species, six marsupials and five rodents), which was not expected because it is an ecotonal region. It was verified that composition and community structure are simplified by the marked presence of generalist species and with the increase of species turnover. The small forest fragments present a microhabitat structure with lianas and streams as main environmental filters of groups with ecological similarities. Our findings suggest that these fragments must be managed in order to conserve the local biodiversity and maintain the needed characteristics to enable the occurrence of different ecological groups.

Small mammals in fragments of Atlantic Forest: species richness answering to field methods and environment

Small mammals can be used as environmental indicators and have been intensively studied in fragmented landscapes of Atlantic Forest, with a wide range of field methods. Our aim in this study was two-fold: we tested for the effects of methods and for the effects of the main environmental variables on observed small mammal richness in fragments of Atlantic Forest. We gathered information on small mammal richness, methods and environmental variables from 122 fragments of Atlantic Forest through literature review. These data were analysed using linear models and model selection based on AIC values along with a regression tree analysis. We found that studies will record more species with bigger trapping effort, using pitfall traps and sampling all forest strata. We also confirmed two important ecological assumptions: fragments at lower latitudes and bigger fragments were the ones with higher species richness. Methodological and environmental variables were analysed together on a regression tree, where trapping effort was the most important variable, surpassing any environmental effect. Considering that a significant number of the studies on Atlantic Forest fragments did not use pitfall traps or sample all forest strata, their results on forest fragmentation were affected by sampling bias.

Habitat quality versus spatial variables as determinants of small mammal assemblages in Atlantic Forest fragments

Fragment size, isolation, and matrix properties have received considerable attention as predictors of species richness, abundance, and composition in habitat patches. However, measurements of habitat attributes or habitat quality are more directly related to the proximate effects of habitat fragmentation and may be more determinant of assemblages than traditional explanatory variables at local scales. We determine how habitat structure in fragments—a measure of habitat quality—compares to fragment size, isolation, and matrix properties as determinants of richness, abundance, and composition of non-volant small mammals in a fragmented landscape of Atlantic Forest. Small mammals were surveyed once in 25 fragments in the Macacu River watershed, Rio de Janeiro, Brazil, from 1999 to 2001 and 2005 to 2009. A total of 83 candidate models were formulated and compared by Akaike Information Criteria. Habitat structure was one of the main determinants of small mammal assemblages in fragments, as important as fragment isolation for species composition and climatic season for species richness. Rodents were more abundant in fragments with increased overstory and understory vegetation density and more fallen logs. The contrary pattern was found for overall species richness and for species of terrestrial habit, which were more abundant in fragments with more open forest: decreased overstory and understory vegetation density and less fallen logs. Habitat quality in fragments may be a more important determinant of assemblages of small mammals and other vertebrates than previously considered in landscape and land use studies.

O tamanho e isolamento dos fragmentos e as propriedades da matriz têm recebido considerável atenção como preditores da riqueza, abundância e composição de espécies em manchas de habitat. Entretanto, medidas dos atributos do habitat ou da qualidade do habitat são mais diretamente relacionadas aos efeitos imediatos da fragmentação de habitat, e seriam mais determinantes das comunidades do que as variáveis explicativas tradicionais. Determinamos como a estrutura do habitat nos fragmentos—uma medida da qualidade do habitat—se compara ao tamanho e isolamento dos fragmentos, e às propriedades da matriz como determinantes da riqueza, abundância e composição de espécies de pequenos mamíferos não-voadores em uma paisagem fragmentada de Mata Atlântica. Os pequenos mamíferos foram amostrados uma vez em 25 fragmentos na Bacia do Rio Macacu, Rio de Janeiro, Brasil, de 1999 a 2001 e de 2005 a 2009. Um total de 83 modelos foram formulados e comparados utilizando o Critério de Informação de Akaike. A estrutura do habitat foi um dos principais determinantes das comunidades de pequenos mamíferos nos fragmentos de mata, tão importante quanto o isolamento entre fragmentos para a composição de espécies e os efeitos das estações climáticas sobre a riqueza de espécies. Os roedores foram mais abundantes nos fragmentos com estratificação vertical e sub-bosque mais densos e com maior presença de troncos caídos. O padrão contrário foi encontrado para a riqueza total de espécies e para espécies de hábito terrestre, que foram mais abundantes em fragmentos com estratificação vertical e sub-bosque menos densos e menor presença de troncos caídos. A qualidade do habitat em fragmentos pode ser determinante das comunidades de pequenos mamíferos e outros vertebrados, mais importante do que considerado previamente em estudos de paisagens e uso da terra.

The effects of climate change and land-use change on demographic rates and population viability

Understanding the processes that lead to species extinctions is vital for lessening pressures on biodiversity. While species diversity, presence and abundance are most commonly used to measure the effects of human pressures, demographic responses give a more proximal indication of how pressures affect population viability and contribute to extinction risk. We reviewed how demographic rates are affected by the major anthropogenic pressures, changed landscape condition caused by human land use, and climate change. We synthesized the results of 147 empirical studies to compare the relative effect size of climate and landscape condition on birth, death, immigration and emigration rates in plant and animal populations. While changed landscape condition is recognized as the major driver of species declines and losses worldwide, we found that, on average, climate variables had equally strong effects on demographic rates in plant and animal populations. This is significant given that the pressures of climate change will continue to intensify in coming decades. The effects of climate change on some populations may be underestimated because changes in climate conditions during critical windows of species life cycles may have disproportionate effects on demographic rates. The combined pressures of land-use change and climate change may result in species declines and extinctions occurring faster than otherwise predicted, particularly if their effects are multiplicative.

Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science

In recent years, there has been a fast development of models that adjust for imperfect detection. These models have revolutionized the analysis of field data, and their use has repeatedly demonstrated the importance of sampling design and data quality. There are, however, several practical limitations associated with the use of detectability models which restrict their relevance to tropical conservation science.

We outline the main advantages of detectability models, before examining their limitations associated with their applicability to the analysis of tropical communities, rare species and large‐scale data sets. Finally, we discuss whether detection probability needs to be controlled before and/or after data collection.

Models that adjust for imperfect detection allow ecologists to assess data quality by estimating uncertainty and to obtain adjusted ecological estimates of populations and communities. Importantly, these models have allowed informed decisions to be made about the conservation and management of target species.

Data requirements for obtaining unadjusted estimates are substantially lower than for detectability‐adjusted estimates, which require relatively high detection/recapture probabilities and a number of repeated surveys at each location. These requirements can be difficult to meet in large‐scale environmental studies where high levels of spatial replication are needed, or in the tropics where communities are composed of many naturally rare species. However, while imperfect detection can only be adjusted statistically, covariates of detection probability can also be controlled through study design. Using three study cases where we controlled for covariates of detection probability through sampling design, we show that the variation in unadjusted ecological estimates from nearly 100 species was qualitatively the same as that obtained from adjusted estimates. Finally, we discuss that the decision as to whether one should control for covariates of detection probability through study design or statistical analyses should be dependent on study objectives.

Synthesis and applications. Models that adjust for imperfect detection are an important part of an ecologist's toolkit, but they should not be uniformly adopted in all studies. Ecologists should never let the constraints of models dictate which questions should be pursued or how the data should be analysed, and detectability models are no exception. We argue for pluralism in scientific methods, particularly where cost‐effective applied ecological science is needed to inform conservation policy at a range of different scales and in many different systems.

Models that adjust for imperfect detection are an important part of an ecologist's toolkit, but they should not be uniformly adopted in all studies. Ecologists should never let the constraints of models dictate which questions should be pursued or how the data should be analysed, and detectability models are no exception. We argue for pluralism in scientific methods, particularly where cost‐effective applied ecological science is needed to inform conservation policy at a range of different scales and in many different systems.

Forest loss and the biodiversity threshold: an evaluation considering species habitat requirements and the use of matrix habitats

Habitat loss is the main driver of the current biodiversity crisis, a landscape-scale process that affects the survival of spatially-structured populations. Although it is well-established that species responses to habitat loss can be abrupt, the existence of a biodiversity threshold is still the cause of much controversy in the literature and would require that most species respond similarly to the loss of native vegetation. Here we test the existence of a biodiversity threshold, i.e. an abrupt decline in species richness, with habitat loss. We draw on a spatially-replicated dataset on Atlantic forest small mammals, consisting of 16 sampling sites divided between forests and matrix habitats in each of five 3600-ha landscapes (varying from 5% to 45% forest cover), and on an a priori classification of species into habitat requirement categories (forest specialists, habitat generalists and open-area specialists). Forest specialists declined abruptly below 30% of forest cover, and spillover to the matrix occurred only in more forested landscapes. Generalists responded positively to landscape heterogeneity, peaking at intermediary levels of forest cover. Open area specialists dominated the matrix and did not spillover to forests. As a result of these distinct responses, we observed a biodiversity threshold for the small mammal community below 30% forest cover, and a peak in species richness just above this threshold. Our results highlight that cross habitat spillover may be asymmetrical and contingent on landscape context, occurring mainly from forests to the matrix and only in more forested landscapes. Moreover, they indicate the potential for biodiversity thresholds in human-modified landscapes, and the importance of landscape heterogeneity to biodiversity. Since forest loss affected not only the conservation value of forest patches, but also the potential for biodiversity-mediated services in anthropogenic habitats, our work indicates the importance of proactive measures to avoid human-modified landscapes to cross this threshold.

MHC genotyping of non-model organisms using next-generation sequencing: a new methodology to deal with artefacts and allelic dropout

BACKGROUND

The Major Histocompatibility Complex (MHC) is the most important genetic marker to study patterns of adaptive genetic variation determining pathogen resistance and associated life history decisions. It is used in many different research fields ranging from human medical, molecular evolutionary to functional biodiversity studies. Correct assessment of the individual allelic diversity pattern and the underlying structural sequence variation is the basic requirement to address the functional importance of MHC variability. Next-generation sequencing (NGS) technologies are likely to replace traditional genotyping methods to a great extent in the near future but first empirical studies strongly indicate the need for a rigorous quality control pipeline. Strict approaches for data validation and allele calling to distinguish true alleles from artefacts are required.

RESULTS

We developed the analytical methodology and validated a data processing procedure which can be applied to any organism. It allows the separation of true alleles from artefacts and the evaluation of genotyping reliability, which in addition to artefacts considers for the first time the possibility of allelic dropout due to unbalanced amplification efficiencies across alleles. Finally, we developed a method to assess the confidence level per genotype a-posteriori, which helps to decide which alleles and individuals should be included in any further downstream analyses. The latter method could also be used for optimizing experiment designs in the future.

CONCLUSIONS

Combining our workflow with the study of amplification efficiency offers the chance for researchers to evaluate enormous amounts of NGS-generated data in great detail, improving confidence over the downstream analyses and subsequent applications.