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climate change and Competition

31/7/2018

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Fig. 1. The Apennine chamois, the focus of a recent research paper by Francesco Ferretti, Sandro Lovari and Phil Stephens. Photo (C) F. Ferretti.
In the face of rapid anthropogenic climate change, species interactions add an unwelcome element of uncertainty and complexity. Many authors have emphasised the particular perils faced by species with specialist interactions, such as mutualists, or highly specialised consumers. If the temporal or spatial responses to climate change of interacting species are different, interactions could be disrupted - with grave implications for one or both species.

Despite the interest in species interactions, competition has seen less focus in this regard. An exception is Tom's work on competition between domestic and wild ungulates in the alps, in which he showed that Alpine chamois retreat to higher altitudes in the face of both high temperatures and grazing sheep - but that the effect of the presence of competitors is far more pronounced than the predicted effect of climate change. Thus, managing competition might be one way to mitigate for the consequences of climate change.

Last year, Francesco Ferretti visited the CEG from the University of Siena, Italy, on a Senior Fellowship sponsored by the Institute of Advanced Studies. One purpose of his visit was to work on analysing data on climate change and interactions between Apennine chamois (Fig. 1, above) and red deer. Red deer are currently expanding into the Apennines, where they compete with Apennine chamois (a subspecies of Pyrenean chamois recognised to be vulnerable to extinction). Francesco wanted to know if the impact of climate change would exacerbate the effect of competition (because the reduction in resources owing to climate change might make competition more intense), ameliorate the impact of competition (perhaps by leading to greater niche divergence between the species), or if the two would act independently. He brought with him data on foraging behaviour of chamois in an area that red deer have already expanded into, as well as data from an area that red deer have yet to reach. The results of his analyses have recently been published in the journal Current Zoology.

Francesco showed that climatic factors (temperature and rainfall) exerted a strong effect on chamois feeding behaviour. However, the presence or absence of red deer also impacted on the bite rate of chamois (a good indicator of the rate at which they take in food):
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Fig. 2. Feeding rate of Apennine chamois in relation to temperature (upper panels) and rainfall (lower panels) over the past 6 weeks. Hotter, drier weather leads to lower feeding rates. Notice that feeding rates are lower in the presence of red deer (Site A) than in their absence (Site B).

Importantly, in the context of Francesco's original question, there was no evidence of an interaction between the weather conditions and the presence of red deer. Thus, the two challenges appear to operate independently.

Francesco also showed that kid survival (indexed by the ratio of females to kids versus the ratio of females to yearlings in the different sites) was lower in the site with red deer than in the site without. Based on what is known about adult survival, we estimated that populations would only be stable (population growth rate, λ = 1) when kid survival was approximately 36%. In fact, the best estimate for kid survival was 49% in the site with no red deer but 27% in the site with red deer. Even given the uncertainty in that survival rate, there is a 95% chance that the survival rate in the site with red deer is too low for the chamois population to be self-sustaining (see Fig. 3). In general, increasing frequencies of drought conditions are likely to imperil Apennine chamois and related species - but that threat will be more pronounced in the presence of competitors, such as red deer, which are increasingly numerous throughout Europe.
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Fig. 3. Estimates of chamois kid survival (accounting for uncertainty) in the deer-free area (orange) and the deer-present area (red). Accounting for that uncertainty leads to estimates of the likely population growth rate, λ, in the deer-free area (purple) and the deer-present area (blue). Best estimates for both parameters are shown by the open (deer-free) and filled (deer-present) circles. The solid line shows the relationship between λ and kid survival, all else being equal; the broken lines show where those are sufficient for population stability.
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First paper published by the MammalWeb project

19/7/2018

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The MammalWeb project keeps many of us (including Phil, Pen and Sammy) pretty busy. Happily, the first paper from the project has just been published in the journal Remote Sensing in Ecology and Conservation! Here, we talk about the motivation for the project and the findings of the paper.

To conserve biodiversity effectively, we need to know where and in what abundance it occurs. Breeding bird surveys, which happen in many countries every year, are a great example of how high-quality biodiversity data can underpin science and policy. In contrast to birds, however, many mammal species are elusive and surprisingly poorly documented. Motion-sensing camera traps can change this, owing to the relative ease with which they can be set up across a wide area to observe and document mammals in a non-intrusive way. As a result, camera trapping is a highly active focus of research in ecology and conservation.

A major challenge for camera trapping is dealing with the sheer volume of data that can be produced. Even modest studies can rapidly generate data sets numbering tens or hundreds of thousands of images. Someone must look at each photo and record the animals captured in it. This classification process can be a huge drain on a researcher’s time and can significantly delay the ecological insights that camera trapping can provide.
In recent years, many researchers have turned to online crowdsourcing platforms where anyone who is interested can help with data processing, which includes classifying camera trap photos. For example, the highly successful Snapshot Serengeti project attracted tens of thousands of participants to classify more than a million camera trap photos. An important trick of the trade is to ask multiple participants to classify each photo. This way, researchers can aggregate those “votes” to calculate a consensus classification. Once a consensus is achieved for a photo, it can be “retired” (i.e., no longer shown to visitors) so that users can look at other images in the dataset.

Motivated by the need to find better ways to monitor mammals in the United Kingdom, CEG staff collaborated with staff at Durham Wildlife Trust, plus many volunteers from around the country, to start MammalWeb, a citizen science project for monitoring wild mammals in north-east England. The project is unusual, in that MammalWeb citizen scientists can participate in one or both of two ways: by being a “Trapper” who sets up camera traps and uploads photos and associated data to our web platform; and by being a “Spotter” who logs in to help classify those photos (Fig. 1). One challenge for MammalWeb is that we have a much smaller group of Spotters (hundreds of users) than big, international projects like Snapshot Serengeti (tens of thousands of users). Therefore, we wanted to see if there is a way to arrive at those consensus classifications in an even more economical way, so that user effort can be focused on examining photos requiring more scrutiny. If we can do this, crowd-sourced camera trapping projects big and small can all benefit.
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The MammalWeb “Spotter” interface, where users can help to classify camera trap photos.
We started by looking at a “gold standard” subset of images for which we already know the species pictured. By comparing our user-submitted classifications to this gold standard, we can get an idea of how accurate our Spotters are. According to this, MammalWeb Spotters have over a 90% chance of correctly identifying the presence of an animal (if it is indeed present) for 10 out of 16 frequently-seen species. Where user classifications are not correct, the reasons seem to depend on the type of species. For example, classification accuracy for small rodents is lower because, often, they are simply missed by a Spotter. Other species are more frequently mis-identified rather than missed altogether. An example of this is the brown hare (Fig. 2), which is often confused with the European rabbit.
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Camera trap photo of a brown hare, which is often confused with the European rabbit.
We also calculated the confidence we can have in a consensus classification, given the number and types of user classifications that underlie it. We found, for example, that very few classifications saying a badger is present are needed for us to be confident that it really is there; this is because badgers are fairly easy to identify. However, for more “ambiguous” species, such as the brown hare, we need to have more people look at the photos before we can be certain about whether or not it is there. Users are extremely unlikely to provide “false positive” classifications, suggesting that a species is pictured when the image sequence actually contains no wildlife.  Hence, even when many classifications suggest that an image sequence is devoid of wildlife, a single dissenter is more likely to be correct.

What all this means is that, when crowdsourcing the classification of camera trap photos and calculating consensus classifications, it may be helpful to factor in (1) differences in detectability between species, and (2) the relative influence of different types of incorrect classifications (where species have been missed versus where they have been misclassified). Together, these solutions can better focus user classification efforts on those photos requiring more scrutiny.

As projects like MammalWeb, Snapshot Serengeti and eMammal gather a large body of classified camera trap photos, they can be used as training data to aid machine learning algorithms to automatically classify wildlife photos. The first steps look very promising, emphasising how critical it is for researchers to share their data and results so that we can build on each other’s progress to address the need for large scale monitoring in this time of rapid ecological change.

More generally, the MammalWeb project has also demonstrated that citizen science is not limited to scientists crowdsourcing, or “outsourcing”, their work to volunteers. MammalWeb citizen scientists have not only been instrumental in setting up camera traps to observe wild mammals, but have also taken the initiative and started their own wildlife surveys. Some use the data they collect to inform public planning and engage policy makers, while others develop and deliver camera trapping workshops to other wildlife groups. Can citizen science camera trapping be as successful as other citizen-initiated remote sensing projects such as aerial mapping?

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Pen wins 'Science Postgraduate Excellence in Outreach award'

4/7/2018

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Pen has been honoured for his science outreach work, winning the 'Science Postgraduate Excellence in Outreach Award'. The award recognises outstanding contributions to public engagement with science.​ Pen has been involved in many outreach activities for the project MammalWeb, a joint project between the University and the Durham Wildlife Trust where members of the public help with mammal monitoring by deploying camera traps. Pen has worked with students from Belmont Community School in Durham, teaching them about camera trapping, and allowing them to do their own field work and research with the camera traps. Together, they made a video to explain more about MammalWeb and their experiences with it. You can watch the full video by clicking here, or a shorter version of the video here.
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Pen giving a demonstration at a public Science Day.
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New paper in Conservation Letters!

1/5/2018

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Tom Mason has recently published a policy perspective in Conservation Letters exploring whether current management of conservation conflicts is suitable for tackling their wicked complexity (spoiler: it isn't!). Co-lead author Chris Pollard has written a great blog on the paper, re-posted below from the Stirling Conservation Science (STICS) page:

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Wicked Complex Conservation Conflict

​Conservation conflict in which people disagree about how to manage biodiversity and parties are perceived to assert their point of view to the detriment of others is an example of a Wicked Problem. Actually, to be honest there are loads of issues in conservation science that can be dropped into the complex, bubbling bucket of wicked problems. Are you dealing with lots of uncertainty? Finding the boundaries of the problem difficult to define? Lacking clear solutions that don’t cause problems elsewhere? Experiencing multiple feedback loops which interact with non-linear dynamics? Yep, you’ve got yourself a wicked problem there, pal.

In 2014, Game et al., described conservation challenges as operating under wicked problem conditions, providing a starter list as to where the common, conventional, “tame” approaches to conservation science were falling short (see also DeFries & Nagendra, 2017). Game et al., also helpfully, provided some wicked alternatives,  pointing researchers towards the complexity-type thinking required.
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Conventional and wicked problem inspired management approaches, adapted from Game et al. 2014

So far, so abstract. But in 2016, the first Interdisciplinary Conservation Network workshop was hosted by ICCS at the University of Oxford, in conjunction with STICS and CBCS at the University of Queensland. This workshop for early career researchers (the second incarnation of ICN is happening later in 2018) included wicked problem thinking for conservation conflict as one of three topics discussed at the event. Eight researchers, each with knowledge of a specific conservation conflict, were joined by mentors to discuss how the conventional and wicked processes were being implemented in the real world. And if they weren’t currently being used, are wicked thinking approaches even appropriate or feasible for these conservation conflicts?

Our output from the workshop has now been published in Conservation Letters.

We found that for each conflict case study, wicked problem thinking was not applied even though over three-quarters were deemed both appropriate and feasible. For half of the case studies not one wicked approach had been tried.
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The appropriateness, feasibility and implementation of wicked approaches, for each of eight conflict case-studies

Having used our case studies to assess the current state of play as regards wicked problem thinking for conservation conflict management, we moved onto thinking how could we fill out those wicked approaches a little more. We came up with five emerging themes worthy of further study.

1. Distributed decision-making
Wicked problem thinking aims to achieve a greater devolution of decision-making to suit the uniqueness and dynamism of different conflicts. This may not always be straight-forward if governance structures or existing policy will not allow transfer of powers.
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In Scotland, a national goose management review group sets the overall agreed national strategy, but local goose management groups have the freedom to find local solutions. This has allowed sport hunting to be used as a population reduction tool on Orkney, but government-led culling used on Islay. Image: Gordon Langsbury

2. Diverse opinions
Embracing diverse voices can form an important route to foster creativity. Research into the links between knowledge co-production, creativity and conflict are required to fully understand the potential value of diverse voices.
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In western Cameroon managers combined data on key fishing zones identified by fishers with ecological data from manatee activity surveys. By uniting these diverse knowledge types, strategies were put in place to restrict damaging fishing techniques in important areas for manatees but not from the most profitable fishing zones. Image: Creative commons

3. Pattern-based predictions
Recognising patterns in ecological dynamics, human behaviour and links between the two can reveal processes acting as conflict triggers, such as the alienation of certain groups. Pattern-recognition analyses can make use of widely available sources of data.
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A typical pattern of events resulting in bat roost damage in the UK might be for a homeowner to ignore a request for a bat survey, the local planning authority to inadequately screen their planning application, the homeowner to destroy any roost prior to the visit of the planning authority, and an application to be subsequently approved. Pattern analysis could reveal how and when these events are most likely to happen, allowing institutional interventions. Image: (c) Hugh Clark/www.bats.org.uk

4. Trade-off based objectives
Objectives guided by trade-offs between the interests of different stakeholders are likely to produce fairer outcomes than those based on a single group’s interests.
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The example of ecological restoration in Queensland, Australia, focussed on flexibility in how objectives are achieved and variation in stakeholder objectives. The emphasis on fundamental objectives such as maximising persistence of threatened species, allows a range of management options to be considered during each iteration of adaptive management. Image: City of Gold Coast

​5. Reporting of failures
No case-studies shared failures transparently even though failures are inevitable, due to the complexities of socio-ecological systems. Communicating these openly can optimise management. It may be possible to encourage open communication by requiring different parties to formally commit to sharing risk and viewing failures as transient features of a wicked problem. While it is tough to develop ‘safe-fail’ cultures in conservation, honest discussions between managers and stakeholders about failures – and the potential to learn from them – provide an important step forward.
 
A thread which runs through all five themes is one of admission of complexity. Conservation scientists cannot solve these problems with conventional methods and to tame them we must share power with and get help from others whilst admitting that we don’t always have the solutions and will sometimes fall short. Wicked problems are a nightmare to manage, but by thinking and working holistically, we can be optimistic about their taming.
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