The sensitivity of breeding songbirds to change in seasonal timing is linked to population change but cannot be directly attributed to the effects of trophic asynchrony on productivity. 

The time that birds decide to breed has a strong impact upon the likely success of raising their young to independence. Pairs of birds will generally time egg laying to maximise the availability of food for their chicks. However, one of the strongest impacts of climate change so far has been to alter the timing of spring. In response to milder temperatures, flowers and insects are all appearing earlier than they used to. Songbirds struggling to match their timing to the changing climate could be facing population declines.

Large-scale citizen science improves assessment of risk posed by wind farms to bats in southern Scotland

Research commissioned by Scottish Natural Heritage (SNH) and led by the British Trust for Ornithology (BTO) demonstrates the power of volunteers in helping to better understand the distribution of rare and vulnerable bat species.

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Projected reductions in climatic suitability for vulnerable British Birds

Researchers have long investigated the effects that climate change might have on species’ future ranges. However, for the first time, scientists at BTO have used abundance data to project the future distribution and abundance of more than one hundred breeding birds in Great Britain in order to assess how the whole bird community might change as a consequence of climate change.

Addressing Uncertainty in Marine Resource Management; Combining Community Engagement and Tracking Technology to Characterize Human Behavior

Small-scale fisheries provide an essential source of food and employment for coastal communities, yet the availability of detailed information on the spatiotemporal distribution of fishing effort to support resource management at a country level is scarce. Here, using a national-scale study in the Republic of Congo, we engaged with fishers from 23 of 28 small-scale fisheries landing sites along the coast to demonstrate how combining community engagement and relatively low cost Global Positioning System (GPS) trackers can rapidly provide fine-scale information on: (1) the behavioral dynamics of the fishers and fleets that operate within this sector; and (2) the location, size and attributes of important fishing grounds upon which communities are dependent. This multidisciplinary approach should be considered within a global context where uncertainty over the behavior of marine and terrestrial resource-users can lead to management decisions that potentially compromise local livelihoods, conservation, and resource sustainability goals.

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Implicit assumptions underlying simple harvest models of marine bird populations can mislead environmental management decisions

Assessing the potential impact of additional mortality from anthropogenic causes on animal populations requires detailed demographic information. However, these data are frequently lacking, making simple algorithms, which require little data, appealing. Because of their simplicity, these algorithms often rely on implicit assumptions, some of which may be quite restrictive. Potential Biological Removal (PBR) is a simple harvest model that estimates the number of additional mortalities that a population can theoretically sustain without causing population extinction. However, PBR relies on a number of implicit assumptions, particularly around density dependence and population trajectory that limit its applicability in many situations. Among several uses, it has been widely employed in Europe in Environmental Impact Assessments (EIA), to examine the acceptability of potential effects of offshore wind farms on marine bird populations. As a case study, we use PBR to estimate the number of additional mortalities that a population with characteristics typical of a seabird population can theoretically sustain. We incorporated this level of additional mortality within Leslie matrix models to test assumptions within the PBR algorithm about density dependence and current population trajectory. Our analyses suggest that the PBR algorithm identifies levels of mortality which cause population declines for most population trajectories and forms of population regulation. Consequently, we recommend that practitioners do not use PBR in an EIA context for offshore wind energy developments. Rather than using simple algorithms that rely on potentially invalid implicit assumptions, we recommend use of Leslie matrix models for assessing the impact of additional mortality on a population, enabling the user to explicitly define assumptions and test their importance.

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