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Evaluating the conservation effectiveness of alternative land management scenarios using a state-of-the-art eco-evolutionary modelling platform

Periodic Reporting for period 1 - ConservaTEAM (Evaluating the conservation effectiveness of alternative land management scenarios using a state-of-the-art eco-evolutionary modelling platform)

Reporting period: 2015-09-01 to 2017-08-31

Human population growth is placing ever increasing demands on using land for housing and for food and fuel production. This demand is driving rapid land use change across much of the globe, in particular in developing countries, which poses a major threat to biodiversity and the ecosystem services it provisions. Simultaneously, climate is changing rapidly, and thus biodiversity faces the joint threat of land use and climate change; not only will species need to be able to persist in heavily degraded landscapes, but they are likely to have to shift their ranges through highly fragmented habitat patches embedded within a hostile matrix. A key role for applied ecology over the coming years will be to provide clear recommendations on how conservation activities can optimise the landscape structure such that as much biodiversity as possible is likely to be retained. This in turn benefits local populations through crucial ecosystem services provided by intact ecosystems. In ConservaTEAM I will make use of a novel modelling platform, RangeShifter, to test the likely effectiveness of alternative land management scenarios in terms of their ability to protect forest bird species. RangeShifter is unique in that it allows to model animal dispersal realistically in function of the landscape which likely is crucial for evaluating management scenarios that seek to increase the persistence of populations in fragmented landscapes. As a case study, the project will focus on the Eastern Arc Mountain Range (EAM) in East Africa.
The first step was selecting a set of forest bird species occurring in the Eastern Arc Mountains that could be used as model species within the designed modelling framework. A first requirement was availability of population demographic data. A second requirement for species selection was their dependency on montane evergreen forest. Seven bird species fulfilled these conditions: Arizelocichla masukuensis, A. milanjensis, Chamaetylas fuelleborni, Illadopsis rufipennis, Modulatrix stictigula, Phyllastrepus placidus, Sheppardia sharpei. These species differ in their dependence on intact forest, climate associations and dispersal capacity.
We modeled bird population dynamics using a sex specific stage-structured model as this would allow to restrict dispersal to the juveniles and to account for sex-biased dispersal. Survival rates were available to ConservaTEAM from a long-term population monitoring study in Tanzania. Fecundity had to estimated as no reliable data were available.
To model dispersal mechanistically in function of the landscape, RS requires a cost surface with each cell reflecting the relative preference of forest birds to select it. I created a set of cost surfaces that either reflected a relatively permeable or impermeable matrix.
Current climate and future predictions were generated based on remotely sensed climate data (MODIS for temperature and CHIRPS for rainfall). Data from 2006-2015 were used to calculate a set of 14 relevant climatic variables centered around 2010. Subsequently, projections for the future were calculated at decadal intervals for the period 2020-2090 according to two alternative emission pathways (RCP4.5 and RCP8.5) using a regional downscaled model (AFRICLIM).
Environmental suitability for each species was modeled using Maxent. This model is recognized to represent the best option when using presence-only-data. Species occurrences were compiled in close collaboration with ornithological experts in the EAM region and environmental suitability subsequently estimated using a set of relevant and uncorrelated climate variables across a range of model settings.
RangeShifter was used to evaluate the ecological effectiveness of a set of management scenarios on the persistence of P. cabanisi. In this study, recommendations from a stakeholder workshop in the Taita Hills (SE Kenya) were used to develop scenarios aimed at increasing species persistence in this mountain bloc. The study made use of a version of RS that did not yet incorporate effects of climate change. We found that the largest population increase was predicted to occur under scenarios increasing habitat area. However, the effectiveness was sensitive to spatial planning. Compared to adding one large patch to the habitat network, adding several small patches yielded mixed benefits: although overall population sizes increased, specific newly created patches acted as dispersal sinks, which compromised population persistence in some existing patches. The study nicely demonstrated that the effectiveness of spatial management is strongly driven by patterns of individual dispersal across landscapes.
One of the main objectives of the project was to develop conservation management scenarios together with stakeholders. However, due to limitations of RangeShifter in representing climate change encountered in the process, we had to change our plans regarding stakeholder engagement in formulating and designing management scenarios that could mitigate the impacts of climate change. However, I found it important to communicate with stakeholders involved in conservation planning in the EAM about the possible effects of climate change on biodiversity. For this workshop, I analysed further the climate change projections and calculated measures of climate loss for the different EAM mountain blocs. This workshop sparked a number of very interesting ideas and we are now in the process to incorporate these in ongoing work.

Aben, J., Bocedi,
An important advantage of RangeShifter is that it incorporates realistic dispersal rules. Of particular value when it comes to modelling functional connectivity is the option to model the transfer phase of dispersal mechanistically in function of information on the landscape. In its current form, dispersal simulations are influenced by information within a predefined perceptual range. However, the model does not take into account how much of this information is actually available to the animal form a particular location. Rugged topography and vegetation are likely to influence this availability, which makes it difficult to interpret movement decisions or to model them in function of the landscape. By coincidence I learned about ‘viewshed analysis’, a GIS tool designed to model the visibility taken into account three dimensional properties of the environment. Although heavily used in non-ecological disciplines, viewshed analysis has been rarely used in ecology. I started to develop ideas to use this analysis in conjunction 3D environmental information to analyse location data of forest birds. These ideas were further developed culminating in the opinion article “A call for viewshed ecology”.
Engaging with stakeholders in Tanzania.