Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for these relationships and the implications for landscape planning in agricultural areas.

1. 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.2. 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.3. 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.4. 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.5. 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.

Translocation experiments showed that a woodcreeper bird species is able to move between isolated forest fragments, but this ability is limited by increasing interpatch distances. Larger distances (> 100 m) were overcome by using small stepping‐stones (isolated trees), which enhance connectivity and are useful for the species conservation in fragmented landscapes.

a b s t r a c tLandscape changes can lead to bee species loss, what impairs proper landscape level pollination processes, impacting both nature conservation and human welfare. Although landscape heterogeneity can rescue bee communities from collapsing, these insects seem sensitive to reduced functional connectivity, hindering pollen transfer among plants. Our objective was to verify which of these two factors, landscape heterogeneity or functional connectivity, can better explain variations of bee abundance and richness in a fragmented Atlantic Forest region. We sampled flower-visiting bees in 12 landscapes with varying heterogeneity and functional connectivity measured using a Functional Ecological Corridors framework. Both richness and abundance were affected by landscape factors, reaching its highest levels at intermediate levels of functional connectivity in highly heterogeneous landscapes, indicating the existence of strong regime shifts in the system. In low-forested landscapes, conservation actions for pollinating bees should focus on implementing diversified environments with high quality which are interspersed among each other and with native vegetation.

No abstract

Context Loss of natural habitat can isolate pollinator populations and negatively affect sexual reproduction of animal-pollinated plants.Objective We evaluated how the loss of natural forest affects pollinator diversity in the understory of the Atlantic Rainforest in Northeastern Brazil. Methods We focused on bees, the main group of pollinators for angiosperms. We assessed how changes in forest cover at regional (36 km 2 ) and local (0.36 km 2 ) scales affect bee richness and abundance. Results We sampled 492 bees from 59 species, of which 58 % were above ground nesting species and 73 % exhibited some level of sociality. Our results show that the loss of forest had negative effects on understory bee abundance, which was particularly accentuated for species that nest above ground. However, for social bees the effect of changes in forest cover at a local scale depended on regional forest cover, negative effects being only detected when landscapes had at least 35 % of forest. For bee richness, the null model was among the best models bringing considerable uncertainty about landscape effects on bee richness. Conclusions These findings suggest that management strategies and conservation practices must integrate proper actions that consider both local and regional scales. For existing fragmented landscapes, it is important to increase forest availability at the regional scale, while also maintaining high environmental heterogeneity at the local scale. We believe that with proper landscape planning this multiscalar approach can be not only more effective, but also easier to implement.Electronic supplementary material The online version of this article (

No abstract

No abstract