Avian richness and abundance in temperate Danish forests: tree variables important to birds and their conservation

Many studies on avian diversity and forest structure have focused onfiner scale forest variables such as foliage height diversity, foliagediversity, foliage density, vertical distribution of vegetation and horizontalvegetation density. From a conservation and forestry operational point of viewit would be of great interest if tree variables influenced directly by forestrymanagement decisions also had significant influence on avian richness andabundance. The species, age and size of a tree are examples of such treevariables. A great number of studies also have focused on avian diversityindices to reveal relationships with vegetation variables. However, it may bemore appropriate for foresters and conservation officers to operate withrichness and abundance measures directly, because indices complicateinterpretations on the relative importance of the two variables (richness andabundance) constituting the index. Fourteen managed temperate forests in Denmarkwere investigated for avian species richness and abundance and related tomeasures on different tree variables influenced directly by forestry managementdecisions. A rapid assessment method of avian richness and abundance wasemployed. It consisted of point-counts of bird richness and abundance within 1km² of forest. General linear models were tested byanalyses of variance statistics to reveal the tree variables most important toavian richness and abundance. It was found that more old trees, more treespecies and more tree size-classes correlated with more bird species andindividuals. However, some variation in bird richness and abundance was alsorelated to site quality and/or chance colonization. Moreover, it was shown thatthe guild of cavity-nesting birds correlated positively to age of tree stand.The potential number of bird species in Danish forest is similar to that innearly pristine forest in Poland, and much larger than that recorded in any ofthe forests investigated. Together with the results above, this indicates a highpotential for squeezing in more avian species in a higher quality forest from abiodiversity point of view. Modern Danish forestry affects tree variablesinfluenced directly by forestry management decisions. Such tree variables havegreat influence on avian richness and abundance, but simple measures in forestrypractices can be taken to enhance the conservation of bird richness andabundance.     

Multimodel inference in ecology and evolution: challenges and solutions

Information theoretic approaches and model averaging are increasing in popularity, but this approach can be difficult to apply to the realistic, complex models that typify many ecological and evolutionary analyses. This is especially true for those researchers without a formal background in information theory. Here, we highlight a number of practical obstacles to model averaging complex models. Although not meant to be an exhaustive review, we identify several important issues with tentative solutions where they exist (e.g. dealing with collinearity amongst predictors; how to compute model-averaged parameters) and highlight areas for future research where solutions are not clear (e.g. when to use random intercepts or slopes; which information criteria to use when random factors are involved). We also provide a worked example of a mixed model analysis of inbreeding depression in a wild population. By providing an overview of these issues, we hope that this approach will become more accessible to those investigating any process where multiple variables impact an evolutionary or ecological response.     

An overview on the role of Hexanchiformes in marine ecosystems: biology, ecology and conservation status of a primitive order of modern sharks

The large size, high trophic level and wide distribution of Hexanchiformes (cow and frilled sharks) should position this order as important apex predators in coastal and deep-water ecosystems. This review synthesizes available information on Hexanchiformes, including information not yet published, with the purpose of evaluating their conservation status and assessing their ecological roles in the dynamics of marine ecosystems. Comprising six species, this group has a wide global distribution, with members occurring from shallow coastal areas to depths of c. 2500 m. The limited information available on their reproductive biology suggests that they could be vulnerable to overexploitation (e.g. small litter sizes for most species and suspected long gestation periods). Most of the fishing pressure exerted on Hexanchiformes is in the form of commercial by-catch or recreational fishing. Comprehensive stock and impact assessments are unavailable for most species in most regions due to limited information on life history and catch and abundance time series. When hexanchiform species have been commercially harvested, however, they have been unable to sustain targeted fisheries for long periods. The potentially high vulnerability to intense fishing pressure warrants a conservative exploitation of this order until thorough quantitative assessments are conducted. At least some species have been shown to be significant apex predators in the systems they inhabit. Should Hexanchiformes be removed from coastal and deep-water systems, the lack of sympatric shark species that share the same resources suggests no other species would be capable of fulfilling their apex predator role in the short term. This has potential ecosystem consequences such as meso-predator release or trophic cascades. This review proposes some hypotheses on the ecology of Hexanchiformes and their role in ecosystem dynamics, highlighting the areas where critical information is required to stimulate research directions.     

Modelling the distribution of short-toed eagle (<Emphasis Type=BoldItalic>Circaetus gallicus</Emphasis>) in semi-arid Mediterranean landscapes: identifying important explanatory variables and their implications for its conservation

Mediterranean semi-arid landscapes are currently experiencing accelerated land use changes which are affecting species distributions. An important fraction of the European short-toed eagle (Circaetus gallicus) population, a specialised snake predator, breeds in this kind of landscapes. Information on the habitat characteristics that may affect the occurrence of this species is of paramount importance to try to evaluate how this species could be affected by ongoing territory changes. In this study, we use hierarchical partitioning analysis to identify environmental variables (natural vegetation, agricultural uses, hydrological web, topography, human pressure and climate) at two resolution scales (1 and 4 km²) that may influence the presence of the short-toed eagle in a populated Mediterranean region in southeastern Spain. Results were highly consistent between scales. Forest was the most important variable determining the presence of the short-toed eagle in the study area, showing a positive effect, particularly those inland forests with nearby presence of sunny open scrublands where the species may find its prey. On the contrary, herbaceous crops and all variables related to human pressure, including urbanisations, dispersed houses and roads, are negatively affecting the occurrence of the species. These variables are strongly related to the main driving forces that change landscapes in our study area, including the abandonment of traditional territory uses and the expansion of urbanised areas. These results indicate that the increasing number of housing developments projected in inland areas would have a detrimental effect on the short-toed eagle, especially if they are located close to pine forests and rivers.     

Predictive models in ecology: Comparison of performances and assessment of applicability

Ecological systems are governed by complex interactions which are mainly nonlinear. In order to capture the inherent complexity and nonlinearity of ecological, and in general biological systems, empirical models recently gained popularity. However, although these models, particularly connectionist approaches such as multilayered backpropagation networks, are commonly applied as predictive models in ecology to a wide variety of ecosystems and questions, there are no studies to date aiming to assess the performance, both in terms of data fitting and generalizability, and applicability of empirical models in ecology. Our aim is hence to provide an overview for nature of the wide range of the data sets and predictive variables, from both aquatic and terrestrial ecosystems with different scales of time-dependent dynamics, and the applicability and robustness of predictive modeling methods on such data sets by comparing different empirical modeling approaches. The models used in this study range from predicting the occurrence of submerged plants in shallow lakes to predicting nest occurrence of bird species from environmental variables and satellite images. The methods considered include k-nearest neighbor (k-NN), linear and quadratic discriminant analysis (LDA and QDA), generalized linear models (GLM) feedforward multilayer backpropagation networks and pseudo-supervised network ARTMAP.Our results show that the predictive performances of the models on training data could be misleading, and one should consider the predictive performance of a given model on an independent test set for assessing its predictive power. Moreover, our results suggest that for ecosystems involving time-dependent dynamics and periodicities whose frequency are possibly less than the time scale of the data considered, GLM and connectionist neural network models appear to be most suitable and robust, provided that a predictive variable reflecting these time-dependent dynamics included in the model either implicitly or explicitly. For spatial data, which does not include any time-dependence comparable to the time scale covered by the data, on the other hand, neighborhood based methods such as k-NN and ARTMAP proved to be more robust than other methods considered in this study. In addition, for predictive modeling purposes, first a suitable, computationally inexpensive method should be applied to the problem at hand a good predictive performance of which would render the computational cost and efforts associated with complex variants unnecessary.     

Drivers of extinction risk in African mammals: the interplay of distribution state,human pressure,conservation response and species biology

Although conservation intervention has reversed the decline of some species, our success is outweighed by a much larger number of species moving towards extinction. Extinction risk modelling can identify correlates of risk and species not yet recognized to be threatened. Here, we use machine learning models to identify correlates of extinction risk in African terrestrial mammals using a set of variables belonging to four classes: species distribution state, human pressures, conservation response and species biology. We derived information on distribution state and human pressure from satellite-borne imagery. Variables in all four classes were identified as important predictors of extinction risk, and interactions were observed among variables in different classes (e.g. level of protection, human threats, species distribution ranges). Species biology had a key role in mediating the effect of external variables. The model was 90% accurate in classifying extinction risk status of species, but in a few cases the observed and modelled extinction risk mismatched. Species in this condition might suffer from an incorrect classification of extinction risk (hence require reassessment). An increased availability of satellite imagery combined with improved resolution and classification accuracy of the resulting maps will play a progressively greater role in conservation monitoring.     

Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference

Reconstruction of ancestral DNA and amino acid sequences is an important means of inferring information about past evolutionary events. Such reconstructions suggest changes in molecular function and evolutionary processes over the course of evolution and are used to infer adaptation and convergence. Maximum likelihood (ML) is generally thought to provide relatively accurate reconstructed sequences compared to parsimony, but both methods lead to the inference of multiple directional changes in nucleotide frequencies in primate mitochondrial DNA (mtDNA). To better understand this surprising result, as well as to better understand how parsimony and ML differ, we constructed a series of computationally simple "conditional pathway" methods that differed in the number of substitutions allowed per site along each branch, and we also evaluated the entire Bayesian posterior frequency distribution of reconstructed ancestral states. We analyzed primate mitochondrial cytochrome b (Cyt-b) and cytochrome oxidase subunit I (COI) genes and found that ML reconstructs ancestral frequencies that are often more different from tip sequences than are parsimony reconstructions. In contrast, frequency reconstructions based on the posterior ensemble more closely resemble extant nucleotide frequencies. Simulations indicate that these differences in ancestral sequence inference are probably due to deterministic bias caused by high uncertainty in the optimization-based ancestral reconstruction methods (parsimony, ML, Bayesian maximum a posteriori). In contrast, ancestral nucleotide frequencies based on an average of the Bayesian set of credible ancestral sequences are much less biased. The methods involving simpler conditional pathway calculations have slightly reduced likelihood values compared to full likelihood calculations, but they can provide fairly unbiased nucleotide reconstructions and may be useful in more complex phylogenetic analyses than considered here due to their speed and flexibility. To determine whether biased reconstructions using optimization methods might affect inferences of functional properties, ancestral primate mitochondrial tRNA sequences were inferred and helix-forming propensities for conserved pairs were evaluated in silico. For ambiguously reconstructed nucleotides at sites with high base composition variability, ancestral tRNA sequences from Bayesian analyses were more compatible with canonical base pairing than were those inferred by other methods. Thus, nucleotide bias in reconstructed sequences apparently can lead to serious bias and inaccuracies in functional predictions.     

Primates in northern Viet Nam: A review of the ecology and conservation status of extant species,with notes on pleistocene localities

We discuss the distribution of living and fossil primates in northern Viet Nam, integrate new localities into the known ranges, and address the ecological parameters and status of extant primate species. In addition, we interpolate fossil specimens from Pleistocene cave sites into the discussion of current ranges. This approach provides a unique glimpse into the past ranges of extant species in a tropical setting, which is unavailable for most regions of the world. Finally, we review the effects of ecocide and other anthropogenic threats to nonhuman primates in Viet Nam.