Habitat change and restoration: Responses of a forest-floor mammal species to manipulations of fallen timber in floodplain forests

In forests and woodlands, fallen timber (logs and large branches) is an important habitat element for many species of animals. Fallen timber has been systematically stripped in many forests, eliminating an important structural element. This study describes results of a ‘meso-scale’ experiment in which fallen timber was manipulated in a floodplain forest of the Murray River in south-eastern Australia. A thousand tons of wood were redistributed after one-year’s pre-manipulation monitoring, while a further two-year’s post-manipulation monitoring was conducted. The response of the main forest-floor small-mammal species, the Yellow-footed Antechinus Antechinus flavipes, to alterations of fallen-wood loads is documented. Results of the experiment will help to frame guidelines for fallen-timber management in these extensive floodplain forests

Cambio y restauración del hábitat: respuestas de una especie de mamíferos del suelo forestal a las manipulaciones de los árboles caídos en bosques inundados

In forests and woodlands, fallen timber (logs and large branches) is an important habitat element for many species of animals. Fallen timber has been systematically stripped in many forests, eliminating an important structural element. This study describes results of a "meso–scale" experiment in which fallen timber was manipulated in a floodplain forest of the Murray River in south–eastern Australia. A thousand tons of wood were redistributed after one–year’s pre–manipulation monitoring, while a further two–year's post–manipulation monitoring was conducted. The response of the main forest–floor small–mammal species, the Yellow–footed Antechinus Antechinus flavipes, to alterations of fallen–wood loads is documented. Results of the experiment will help to frame guidelines for fallen–timber management in these extensive floodplain forests.En los bosques y montes los árboles caídos (troncos y ramas gruesas) constituyen un importante elemento del hábitat para muchas especies de animales. Los árboles caídos han sido sistemáticamente descortezados en muchos bosques, eliminándose así un importante elemento estructural. Este estudio describe resultados de un experimento a escala mediana en el que los árboles caídos fueron manipulados en un bosque inundado del río Murray, en el sureste de Australia. Se redistribuyeron 1.000 toneladas de madera después de efectuar un control previo a la manipulación durante un año, realizándose otro control durante dos años después de la manipulación. Se documenta la respuesta de la especie de mamífero del suelo del bosque, el ratón marsupial de pies amarillos Antechinus flavipes, a las alteraciones de la madera caída. Los resultados de este trabajo pueden servir de ayuda para elaborar unas directrices marco para la gestión de los árboles caídos en bosques inundados

Where and when to revegetate : a quantitative method for scheduling landscape reconstruction

Restoration of native vegetation is required in many regions of the world, but determining priority locations for revegetation is a complex problem. We consider the problem of determining spatial and temporal priorities for revegetation to maximize habitat for 62 bird species within a heavily cleared agricultural region, 11 000 km2 in area. We show how a reserve-selection framework can be applied to a complex, large-scale restoration-planning problem to account for multi-species objectives and connectivity requirements at a spatial extent and resolution relevant to management. Our approach explicitly accounts for time lags in planting and development of habitat resources, which is intended to avoid future population bottlenecks caused by delayed provision of critical resources, such as tree hollows. We coupled species-specific models of expected habitat quality and fragmentation effects with the dynamics of habitat suitability following replanting to produce species-specific maps for future times. Spatial priorities for restoration were determined by ranking locations (150-m grid cells) by their expected contribution to species habitat through time using the conservation planning tool, ‘‘Zonation.’’ We evaluated solutions by calculating expected trajectories of habitat availability for each species. We produced a spatially explicit revegetation schedule for the region that resulted in a balanced increase in habitat for all species. Priority areas for revegetation generally were clustered around existing vegetation, although not always. Areas on richer soils and with high rainfall were more highly ranked, reflecting their potential to support high-quality habitats that have been disproportionately cleared for agriculture. Accounting for delayed development of habitat resources altered the rank-order of locations in the derived revegetation plan and led to improved expected outcomes for fragmentation-sensitive species. This work demonstrates the potential for systematic restoration planning at large scales that accounts for multiple objectives, which is urgently needed by land and natural resource managers

Human-induced biotic invasions and changes in plankton interaction networks

Summary: Pervasive and accelerating changes to ecosystems due to human activities remain major sources of uncertainty in predicting the structure and dynamics of ecological communities. Understanding which biotic interactions within natural multitrophic communities are weakened or augmented by invasions of non-native species in the context of other environmental pressures is needed for effective management. We used multivariate autoregressive models with detailed time-series data from largely freshwater and brackish regions of the upper San Francisco Estuary to assess the topology, direction and strength of trophic interactions following major invasions and establishment of non-native zooplankton in the early 1990s. We simultaneously compared the effects of fish and clam predation, environmental temperature and salinity intrusion using time-series data from >60 monitoring locations spanning more than three decades. We found changes in the networks of biotic interactions in both regions after the major zooplankton invasions. Our results imply an increased pressure on native herbivores; intensified negative interactions between herbivores and omnivores; and stronger bottom-up influence of juvenile copepods but weaker influence of phytoplankton as a resource for higher trophic levels following the invasions. We identified salinity intrusion as a primary pressure but showed relatively stronger importance of biotic interactions for understanding the dynamics of entire communities. Synthesis and applications. Our findings highlight the dynamic nature of biotic interactions and provide evidence of how simultaneous invasions of exotic species may alter interaction networks in diverse natural ecosystems over large spatial and temporal scales. Efforts to restore declining fish stocks may be in vain without fully considering the trophic dynamics that limit the flow of energy to target populations. Focusing on multitrophic interactions that may be threatened by invasions rather than a limited focus on responses of individual species or diversity is likely to yield more effective management strategies. © 2014 British Ecological Society

Estimating and Modelling Bias of the Hierarchical Partitioning Public-Domain Software: Implications in Environmental Management and Conservation

BACKGROUND: Hierarchical partitioning (HP) is an analytical method of multiple regression that identifies the most likely causal factors while alleviating multicollinearity problems. Its use is increasing in ecology and conservation by its usefulness for complementing multiple regression analysis. A public-domain software "hier.part package" has been developed for running HP in R software. Its authors highlight a "minor rounding error" for hierarchies constructed from >9 variables, however potential bias by using this module has not yet been examined. Knowing this bias is pivotal because, for example, the ranking obtained in HP is being used as a criterion for establishing priorities of conservation. METHODOLOGY/PRINCIPAL FINDINGS: Using numerical simulations and two real examples, we assessed the robustness of this HP module in relation to the order the variables have in the analysis. Results indicated a considerable effect of the variable order on the amount of independent variance explained by predictors for models with >9 explanatory variables. For these models the nominal ranking of importance of the predictors changed with variable order, i.e. predictors declared important by its contribution in explaining the response variable frequently changed to be either most or less important with other variable orders. The probability of changing position of a variable was best explained by the difference in independent explanatory power between that variable and the previous one in the nominal ranking of importance. The lesser is this difference, the more likely is the change of position. CONCLUSIONS/SIGNIFICANCE: HP should be applied with caution when more than 9 explanatory variables are used to know ranking of covariate importance. The explained variance is not a useful parameter to use in models with more than 9 independent variables. The inconsistency in the results obtained by HP should be considered in future studies as well as in those already published. Some recommendations to improve the analysis with this HP module are given

Range area matters, and so does spatial configuration: predicting conservation status in vertebrates

The current rapid loss of biodiversity globally calls for improved tools to predict conservation status. Conservation status varies among taxa and is influenced by intrinsic species’ traits and extrinsic factors. Among these predictors, the most consistently recognized and widely available is geographic range area. However, ranges of equal area can have diverse spatial configurations that reflect variation in threatening processes and species’ characteristics (e.g., dispersal ability), and can affect local and regional population dynamics. The aim of this study is to assess if and how the spatial configuration of a species’ range relates to its conservation status. We obtained range maps and two descriptors of conservation status: extinction risk and population trend, from the IUCN for 11,052 species of amphibians, non-marine birds, and terrestrial mammals distributed across the World. We characterized spatial configuration using descriptors of shape and fragmentation (fragment number and size heterogeneity) and used regression analysis to evaluate their role in explaining current extinction risk and population trend. The most important predictor of conservation status was range area, but our analyses also identified shape and fragmentation as valuable predictors. We detected complex relationships, revealed by multiple interaction terms, e.g. more circular shapes were negatively correlated with population trend, and heterogeneity was positively correlated with extinction risk for small range areas but negatively for bigger ranges. Considering descriptors of spatial configuration beyond size improves our understanding of conservation status among vertebrates. The metrics we propose are relatively easy to define (although values can be sensitive to data quality), and unlike other correlates of status, like species’ traits, are readily available for many species (all of those with range maps). We argue that considering spatial configuration predictors is a straightforward way to improve our capacity to predict conservation status and thus, can be useful to promote more effective conservation

Multi-scale assessment of human-induced changes to Amazonian instream habitats

Context Land use change and forest degradation have myriad effects on tropical ecosystems. Yet their consequences for low-order streams remain very poorly understood, including in the world´s largest freshwater basin, the Amazon. Objectives Determine the degree to which physical and chemical characteristics of the instream habitat of low-order Amazonian streams change in response to past local- and catchment-level anthropogenic disturbances. Methods To do so, we collected field instream habitat (i.e., physical habitat and water quality) and landscape data from 99 stream sites in two eastern Brazilian Amazon regions. We used random forest regression trees to assess the relative importance of different predictor variables in determining changes in instream habitat response variables. Results Multiple drivers, operating at multiple spatial scales, were important in determining changes in the physical habitat and water quality of the sites. Although we found few similarities in modelled relationships between the two regions, we observed non-linear responses of specific instream characteristics to landscape change; for example 20 % of catchment deforestation resulted in consistently warmer streams. Conclusions Our results highlight the importance of local riparian and catchment-scale forest cover in shaping instream physical environments, but also underscore the importance of other land use changes and activities, such as road crossings and upstream agriculture intensification. In contrast to the property-scale focus of the Brazilian Forest code, which governs environmental regulations on private land, our results reinforce the importance of catchment-wide management strategies to protect stream ecosystem integrity

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Predicting Landscape-Genetic Consequences of Habitat Loss, Fragmentation and Mobility for Multiple Species of Woodland Birds

Inference concerning the impact of habitat fragmentation on dispersal and gene flow is a key theme in landscape genetics. Recently, the ability of established approaches to identify reliably the differential effects of landscape structure (e.g. land-cover composition, remnant vegetation configuration and extent) on the mobility of organisms has been questioned. More explicit methods of predicting and testing for such effects must move beyond post hoc explanations for single landscapes and species. Here, we document a process for making a priori predictions, using existing spatial and ecological data and expert opinion, of the effects of landscape structure on genetic structure of multiple species across replicated landscape blocks. We compare the results of two common methods for estimating the influence of landscape structure on effective distance: least-cost path analysis and isolation-by-resistance. We present a series of alternative models of genetic connectivity in the study area, represented by different landscape resistance surfaces for calculating effective distance, and identify appropriate null models. The process is applied to ten species of sympatric woodland-dependant birds. For each species, we rank a priori the expectation of fit of genetic response to the models according to the expected response of birds to loss of structural connectivity and landscape-scale tree-cover. These rankings (our hypotheses) are presented for testing with empirical genetic data in a subsequent contribution. We propose that this replicated landscape, multi-species approach offers a robust method for identifying the likely effects of landscape fragmentation on dispersal

Second rate or a second chance? Assessing biomass and biodiversity recovery in regenerating Amazonian forests

© 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. Secondary forests (SFs) regenerating on previously deforested land account for large, expanding areas of tropical forest cover. Given that tropical forests rank among Earth’s most important reservoirs of carbon and biodiversity, SFs play an increasingly pivotal role in the carbon cycle and as potential habitat for forest biota. Nevertheless, their capacity to regain the biotic attributes of undisturbed primary forests (UPFs) remains poorly understood. Here, we provide a comprehensive assessment of SF recovery, using extensive tropical biodiversity, biomass, and environmental datasets. These data, collected in 59 naturally regenerating SFs and 30 co-located UPFs in the eastern Amazon, cover >1,600 large- and small-stemmed plant, bird, and dung beetles species and a suite of forest structure, landscape context, and topoedaphic predictors. After up to 40 years of regeneration, the SFs we surveyed showed a high degree of biodiversity resilience, recovering, on average among taxa, 88% and 85% mean UPF species richness and composition, respectively. Across the first 20 years of succession, the period for which we have accurate SF age data, biomass recovered at 1.2% per year, equivalent to a carbon uptake rate of 2.25 Mg/ha per year, while, on average, species richness and composition recovered at 2.6% and 2.3% per year, respectively. For all taxonomic groups, biomass was strongly associated with SF species distributions. However, other variables describing habitat complexity—canopy cover and understory stem density—were equally important occurrence predictors for most taxa. Species responses to biomass revealed a successional transition at approximately 75 Mg/ha, marking the influx of high-conservation-value forest species. Overall, our results show that naturally regenerating SFs can accumulate substantial amounts of carbon and support many forest species. However, given that the surveyed SFs failed to return to a typical UPF state, SFs are not substitutes for UPFs