Biology subjects

Mace, G. M.

Publications and source records attributed to Mace, G. M..

5 recordsLinked to original sources

bioRxiv2022

EDGE2: advancing the prioritisation of threatened evolutionary history for conservation action

The global biodiversity crisis threatens the natural world and its capacity to provide benefits to humans into the future. The conservation of evolutionary history, captured by the measure phylogenetic diversity (PD), is linked to the maintenance of these benefits and future options. The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to identify species for conservation action that embody large amounts of threatened evolutionary history. In 2017, we convened a workshop to update the EDGE metric to incorporate advances in the field of phylogenetically-informed conservation. Building on that workshop, we devised the metric EDGE2, which we present here. EDGE2 uses a modular, tiered approach to provide priority rankings--and associated measures of uncertainty in both phylogenetic and extinction risk data--for all species in a clade. EDGE2 takes into account the extinction risk of closely-related species to better reflect the contribution a species is expected to make to overall PD in the future. We applied EDGE2 to the worlds mammals to identify an updated list of priority EDGE species and compare the results with the original EDGE approach. Despite similarity in the priority lists produced between EDGE and EDGE2, EDGE2 places greater priority on species with fewer close relatives on the Tree of Life. As we approach a crossroads for global biodiversity policy, EDGE2 exemplifies how academic and applied conservation biologists can collaborate to guide effective priority-setting to conserve the most irreplaceable components of biodiversity upon which humanity depends.

zoology↗

bioRxiv2020

Ecological theory predicts ecosystem stressor interactions in freshwater ecosystems, but highlights the strengths and weaknesses of the additive null model

Understanding and predicting how multiple co-occurring environmental stressors combine to affect biodiversity and ecosystem services is an on-going grand challenge for ecology. So far progress has been made through accumulating large numbers of smaller-scale individual studies that are then investigated by meta-analyses to look for general patterns. In particular there has been an interest in checking for so-called ecological surprises where stressors interact in a synergistic manner. Recent reviews suggest that such synergisms do not dominate, but few other generalities have emerged. This lack of general prediction and understanding may be due in part to a dearth of ecological theory that can generate clear hypotheses and predictions to tested against empirical data. Here we close this gap by analysing food web models based upon classical ecological theory and comparing their predictions to a large (546 interactions) dataset for the effects of pairs of stressors on freshwater communities, using trophic- and population-level metrics of abundance, density, and biomass as responses. We find excellent overall agreement between the stochastic version of our models and the experimental data, and both conclude additive stressor interactions are the most frequent, but that meta-analyses report antagonistic summary interaction classes. Additionally, we show that the statistical tests used to classify the interactions are very sensitive to sampling variation. It is therefore likely that current weak sampling and low sample sizes are masking many non-additive stressor interactions, which our theory predicts to dominate when sampling variation is removed. This leads us to suspect ecological surprises may be more common than currently reported. Our results highlight the value of developing theory in tandem with empirical tests, and the need to examine the robustness of statistical machinery, especially the widely-used null models, before we can draw strong conclusions about how environmental drivers combine.

ecology↗

bioRxiv2020

Modelling parameter uncertainty reveals bushmeat yield versus survival trade-offs in heavily-hunted duiker Cephalophus spp.

Reliably predicting sustainable exploitation levels for many tropical species subject to hunting remains a difficult task, largely because of the inherent uncertainty associated with estimating parameters related to both population dynamics and hunting pressure. Here, we investigate a modelling approach to support decisions in bushmeat management which explicitly considers parameter uncertainty. We apply the approach to duiker Cephalophus spp., assuming either a constant quota-based, or a constant proportional harvesting, strategy. Within each strategy, we evaluate different hunting levels in terms of both average yield and survival probability, over different time horizons. Under quota-based harvesting, considering uncertainty revealed a trade-off between yield and extinction probability that was not evident when ignoring uncertainty. The highest yield was returned by a quota that implied a 40% extinction risk, whereas limiting extinction risk to 10% reduced yield by 50%-70%. By contrast, under proportional harvesting, there was no trade-off between yield and extinction probability. The maximum proportion returned a yield comparable with the maximum possible under quota-based harvesting, but with extinction risk below 10%. However, proportional harvesting can be harder to implement in practice because it depends on an estimate of population size. In both harvesting approaches, predicted yields were highly right-skewed with median yields differing from mean yields, implying that decision outcomes depend on attitude to risk. The analysis shows how an explicit consideration of all available information, including uncertainty, can, as part of a wider process involving multiple stakeholders, help inform harvesting policies.

ecology↗

bioRxiv2020

The Madingley General Ecosystem Model predicts bushmeat yields, species extinction rates and ecosystem-level impacts of bushmeat harvesting

Traditional approaches to guiding decisions about harvesting bushmeat often employ single-species population dynamic models, which require species- and location-specific data, are missing ecological processes such as multi-trophic interactions, cannot represent multi-species harvesting, and cannot predict the broader ecosystem impacts of harvesting. In order to explore an alternative approach to devising sustainable harvesting strategies, we employ the Madingley General Ecosystem Model, which can simulate ecosystem dynamics in response to multi-species harvesting given nothing other than location-specific climate data. We used the model to examine yield, extinctions, and broader ecosystem impacts, for a range of harvesting intensities of duiker-sized ectothermic herbivores. Duiker antelope (such as Cephalophus callipygus and Cephalophus dorsalis) are the most heavily hunted species in sub-Saharan Africa, contributing 34%-95% of all bushmeat in the Congo Basin. Across a range of harvesting rates, the Madingley model gave estimates for optimal harvesting rate, and extinction rate, that were qualitatively and quantitatively similar to the estimates from single-species Beverton-Holt model. Predicted yields were somewhat greater (around 5 times, on average) for the Madingley model, which would be expected given that the Madingley simulates multi-species harvesting from an initially pristine ecosystem. This match increased the degree of confidence with which we could examine other predictions from the ecosystem model, as follows. At medium and high levels of harvesting of duiker-sized herbivores, there were statistically significant, but moderate, reductions in the densities of the targeted functional group; increases in small-bodied herbivores; decreases in large-bodied carnivores; and minimal ecosystem-level impacts overall. The results suggest that general ecosystem models such as the Madingley model could be used more widely to help estimate sustainable harvesting rates, bushmeat yields and broader ecosystem impacts across different locations and target species.

ecology↗

bioRxiv2019

Modelling variation in bushmeat harvesting among seven African ecosystems using the Madingley Model: yield, survival and ecosystem impacts

In principle, both the maximum sustainable yields of bushmeat, and the ecosystem impacts of extracting those yields, are likely to vary among ecosystems due to differences in the structure and function of ecosystems, but the data necessary to estimate this variation is lacking. Here, we compare seven different ecosystems on a North-South latitudinal gradient in Central Africa in terms of their trophic structure and capacity to support yields from bushmeat harvesting, using the Madingley General Ecosystem Model. The only factor that varies across simulations of these ecosystems is the climate which drives differences in vegetation structure and function, leading in turn to differences in the structure of the ecological community that emerge from the model. In a series of experiments (n=30), we simulate constant proportional harvesting of small and medium-sized warm-bloodied heterotrophs (1-23kg) over 30 years, recording expected bushmeat yields, and impacts on ecosystem structure, including trophic structure. Predictions for animal densities and trophic structures in the pristine (no harvesting) case varied among the ecosystems, with implications for bushmeat harvesting. For example, wooded savannah ecosystems stood out as having the greatest pristine densities in the target groups (11000-12000 animals per kilometre squared), greatest yields (100% higher than the tropical forest and 1000% higher than the desert ecosystem), and were the most resilient to harvesting. By contrast, small and medium-sized endothermic heterotrophs contributed only a small proportion of heterotrophs in the desert ecosystem, and thus the potential for bushmeat harvesting here was low. In all ecosystems, harvesting at the rate that maximised yield (55-65% population per year, except for the southern desert ecosystem) had strong impacts, causing drastic reductions in target functional groups, coupled with increases in smaller- and larger-bodied animals. Forest and desert ecosystems were particularly sensitive. Overall, the results suggest that, even for similar functional groups, bushmeat harvesting policies will need to vary substantially among ecosystems - and show that general ecosystem models could be a useful tool in helping to guide these policies.

ecology↗