Synthesis
7.3 Population viability as an explicit function of anthropogenic pressures
Quantifying the effects of anthropogenic factors on populations in a changing environ- ment is highly important to design more targeted and effective conservation actions (Purvis et al. 2000). In general, anthropogenic pressures affect populations by decreas- ing the population growth rate, population size, population distribution and/or carrying capacity. In this thesis, the influence of two human pressures on population viability was investigated: chemical pollution (affecting the growth rate and carrying capacity) and water scarcity (affecting the distribution).
The effect of chemical pollution was quantified based on pressure-response relationships between the toxicant exposure levels and the growth rate (survival and reproduction) and carrying capacity of a population (Hakoyama, Iwasa & Nakanishi 2000; Nakamaru, Iwasa & Nakanishi 2003; Hendriks et al. 2005; Korsman et al. 2012). This approach was applied in two case studies: to quantify the impact of DDE on the white-tailed eagle, bald eagle and osprey (chapter 4) and to calculate the reintroduction efforts required to mit- igate the impact of DDE on the peregrine falcon population in California (chapter 5). It was found that the exposure concentrations were high enough to increase population extinction vulnerabilities of all studied bird species in the second half of the 20th century. The results further indicated that the reintroduction efforts required to mitigate these
toxicant impacts were substantial (chapter 5), which highlights the need to timely quan- tify and counteract the effects of chemical exposure on populations. Pressure-response relationships were retrieved with regression analyses from either laboratory (chapter 4) or field monitoring data (chapter 5). Although the use of field data obviates the need to extrapolate lab-based effect measures to field responses (Hill et al. 1994; Traas, Lut- tik & Jongbloed 1996; Bednarska, Jevtić & Laskowski 2013; Forbes & Calow 2013), it requires approaches to correct for the confounding influences of other environmental factors on the responses observed. In this thesis quantile regression was applied for this purpose, similar to e.g., Van Goethem et al. (2015), Hoondert et al. (2018) and Muller, Cade and Schwarzkopf (2018). However, it was found that quantile regression requires a large amount of field monitoring data evenly spread over the pressure-response plane to obtain significant relationships for the upper boundaries of the response variable dis- tribution (such as the 95th percentile). Therefore, population viability assessments based on laboratory data might be preferred. Nevertheless, laboratory experimentation is lim- ited to due to practical, financial and ethical constraints (Hendriks 2013; Hoondert et al. 2018), and, as shown in chapter 4, population-level laboratory data of toxicant impacts are therefore lacking for many mammals and birds, including threatened or endangered species (Forbes et al. 2016). Thus, in absence of laboratory data, the quantile regression method based on field data may be applied to obtain an increasing number of (first) esti- mates of population extinction vulnerabilities due to chemical exposure.
The effect of water scarcity on the spatial distribution of populations was quantified using pressure-response relationships between water availability and habitat suita- bility. Habitat suitability was determined by forage biomass, slope, elevation, vegeta- tion cover and distance to water in combination with species-specific information on environmental requirements. It was found that water scarcity becomes a problem in savanna landscapes when drought periods occur, leading in general to decreased pop- ulation distributions. Additionally, the results indicated that the proposed management strategy of decreasing the water availability in the landscape to facilitate a return to previous animal distribution patterns would not result into the expected effects and that additional measures might be necessary, highlighting the value of using modelling approaches to predict system-wide impacts of conservation actions (Nichols & Williams 2006; McGowan et al. 2017). However, as in the model the effects of water scarcity on population densities were not included, additional data on these impacts may help to better assess the anticipated effects of the proposed management actions in the future. Furthermore, as complex models, such as the one used in chapter 6, are invariably employed for the on-site prediction of dynamics and thus primarily suitable to answer specific conservation questions for specific areas and species populations, the impacts of other anthropogenic factors that influence the spatial distributions of herbivore pop- ulations in savanna landscapes may be investigated, such as climate change, fencing and fire management (Christensen et al. 2004; Bunting et al. 2016; Fullman et al. 2017). This would require site-specific parameters to produce meaningful results (Van Langevelde et al. 2011).
Future research may also focus on quantifying the influence of particular pressures on population extinction vulnerabilities for a large number of species by using similar allometric approaches based on body size as developed in chapters 1 and 2, including
pressures that influence the population size, the population growth rate or the carry- ing capacity, such as climate change, diseases, habitat alteration, hunting, culling and the introduction of predators (e.g., Nacci et al. 2005; Munns Jr 2006; Carrete et al. 2009; Benítez-López et al. 2017; Greenville, Wardle & Dickman 2017; Martay et al. 2017). To this end, the effects of these pressures on the demographic parameters should be related to body size. Thus, pressure-response relationships should be quantified for many spe- cies so that relationships between body size and effect measures (such as half of the maximal effective concentration [e.g. EC50 or LC50] and the Hill slope coefficient) could be derived. These relationships can then be combined with equations that relate the pop- ulation growth rate, population size, population distribution and/or carrying capacity with body size, as used for the population growth rate and carrying capacity in chap- ter 4. Data requirements to quantify pressure-response relationships for many species, including interactive (and cumulative) effects, might, however, limit this type of study at the moment (Munns Jr 2006; Crain, Kroeker & Halpern 2008). Methods that help to use the available data more effectively, such as interspecies extrapolation (e.g., Raimondo, Mineau & Barron 2007) and the quantile regression approach presented in chapter 4, may provide a means to increase the number of species for which pressure-response rela- tionships and hence population extinction vulnerabilities due to anthropogenic stress- ors can be quantified. Ultimately, by including both the relevant intrinsic and external factors, we should be able to even more accurately predict extinction vulnerabilities.