The answer to this question depends on a reef’s location, given that shark abundances can vary with primary productivity and other oceanographic features. It also depends on which time period you chose as your reference point. Shark abundances can fluctuate over the course of a few hours – as well as over days to years to decades and beyond. Even if you chose the same time and place as the person before you, you might have come up with a slightly different answer. This variation in how we determine baselines – overlaid on a backdrop of natural variation in shark communities over space and time – can contribute to differing perceptions about what’s natural or what a depleted population can possibly be restored to.
There are an estimated 830,000 species on coral reefs worldwide. At some stage in their lives, nearly all of these species are consumed as prey items. In this super diverse buffet of fishes, corals, crabs, worms, and other critters, the number of possible interactions between predators and prey is nearly inexhaustible.
The extreme diversity of coral reefs has fascinated naturalists for centuries. Pinpointing predator-prey dynamics is essential to fully understand coral reef ecosystem dynamics, and visual analysis of gut contents has been a staple technique of coral reef ecologists. While the joy of spending copious hours looking through a microscope at half-digested marine mush is undeniable, this type of visual inspection has limitations. Even so, visual gut content analysis (along with stable isotope analysis and behavioural observations) has showcased a highly complex dietary network.
To digest this extreme complexity and surmount the hurdle of dietary unknowns, researchers frequently lump fishes into broad trophic categories, such as ‘mobile herbivores’. Broad generalisations are pragmatic and may be help us detect broad ecological trends, but they oversimplify species’ actual dietary preferences. As coral reefs are changing due to anthropogenic disturbances, it’s critical to thoroughly examine how well trophic groupings capture dietary linkages among reef organisms. Continue reading →
To me, the ‘citizen scientist’ label feels a little patronising – conveying an image of people co-opted en masse for top-down, scientist-led, large-scale biological surveys. That said, scientist-led surveys can offer valid contributions to conservation and the documentation of the effects of climate change (among other objectives). They also engage the public (not least children) in science, although volunteers usually have an interest in natural history and science already. For me though, the real excitement comes in following a bottom-up path: making my own discoveries and approaching scientists for assistance with my projects.
Robert Colwell at the Boreas Pass in Colorado, USA
ROB: I grew up on a working ranch in the Colorado mountains, surrounded on three sides by National Forest and a National Wilderness Area. My mother, an ardent amateur naturalist, taught me and my sister the local native flora and fauna and our father instilled a respect for the land in us. For my doctoral research at the University of Michigan, I studied insect biodiversity in Colorado and Costa Rica at several elevations. The challenges of estimating the number of species (species richness) and understanding why some places are species-rich and others species-poor has fascinated me ever since. Continue reading →
BACIPS (Before-After Control-Impact Paired Series) is probably the best-known and most powerful approach to detect and quantify human interventions on ecosystems. In BACIPS designs, Impact and Control sites are sampled simultaneously (or nearly so) multiple times Before and After an intervention. For each sampling survey conducted Before or After, the difference in the sampled response variable (e.g. density) is calculated. Before and After differences are then compared to provide a measure of the effect of the intervention, assuming that the magnitude of the induced change is constant through time. However, many interventions may not cause immediate, constant changes to a system.
We developed a new statistical approach – called Progressive-Change BACIPS (Before-After Control-Impact Paired-Series) – that extends and generalises the scope of BACIPS analyses to time-dependent effects. After quantifying the statistical power and accuracy of the method with simulated data sets, we used marine and terrestrial case studies to illustrate and validate their approach. We found that the Progressive-Change BACIPS works pretty well to estimate the effects of environmental impacts and the time-scales over which they operate.
The following images show the diversity of contexts in which this approach can be undertaken.
Moorea is an island located in French Polynesia. It’s known for its extraordinary marine biodiversity, but also for the great, natural spatial and temporal variability due to recurrent external forces. This place, and the statistical challenges it represents, has provided us with a wealth of inspiration in formulating our Progressive-Change BACIPS approach to environmental impact assessment.
Unlike classic experimental studies like this one, environmental impacts are not (and often should not) be replicated.
Recurrent disturbances such as Crown-of-Thorns Starfish (Acanthaster planci) outbreaks are important drivers of declines and recoveries in coral reef ecosystems. How can we reliably estimate the effect of local human interventions (for example marine protected areas, MPAs) amid such noise?
Here, a scientist is counting fish where a MPA will be implemented using a Diver-Operated Video system. Repeated assessments before enforcement provide an estimate of the spatial variability between the Control and Impact sites in the absence of an effect of the MPA.
A change in the difference in density between the Control and Impact sites after the establishment of the MPA provides an estimate of the local effect of the MPA. This is the BACIPS design.
Progressive-Change BACIPS uses these data to inform the form of the final model. Many models can be tested such as step-change, linear, asymptotic or logistic models – whatever that seems appropriate. This coral reef application was just one of the many possibilities to measure environmental impacts that our tool can reveal when applied to BACIPS data.
We have also applied it to other study contexts – such as the effect of highway construction on the abundance of birds. Here is an Andean condor (Vultur gryphus) flying away after the passage of a car.
This method is also well suited to forest ecosystems, for example to study the effect of increasing tourist visitation on this ancient Araucaria (Araucaria araucana) forest in Chile.
As long as data collected before and after, inside and outside the impacted area, exist Progressive-Change BACIPS is an excellent statistical approach to estimate the effects of environmental impacts.