Archetypes of Climate Vulnerability: a Mixed-method Approach Applied in the Peruvian Andes

<p>Farm household systems (FHSs) in the Andes handle climate-related hazards such as frost and droughts with risk-coping and risk-management strategies based on the adaptive capital available to them. Nevertheless, a higher frequency of climatic stressors observed during the last few decades is challenging their capacity to adapt at a pace fast enough to keep up with the changes in external conditions. This increases the demand on the scientific community from policy and decision makers to investigate climate impacts and propose viable adaptation pathways at the local and regional scales. Better understanding heterogeneity in climate vulnerability is an important step towards addressing this demand. We present here a mixed-method approach to assessing archetypes or patterns of climate vulnerability that combines qualitative tools from participatory rural assessment approaches and quantitative techniques including cluster analysis. We illustrate this by looking at a case study of the Central Andes of Peru. The operationalization of the methods revealed differential factors for climate vulnerability, allowing us to categorize FHS archetypes according to the differences in those underlying factors. The archetypes differed mainly according to farm area, agro-ecological zones, irrigation, off-farm employment and climate-related damages. The results suggest that the approach is useful for explaining vulnerability as a function of recurrent internal and external determinants of vulnerability and developing related adaptive strategies.</p

Plant Interactions Alter the Predictions of Metabolic Scaling Theory

<div><p>Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of −4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms’ internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than −4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.</p></div

Relationship between relative interaction intensity (RII) and density of surviving plants at different levels of resource limitation and modes of competition.

<p><i>RL</i> indicates the level of resource limitation (from 0 to 1 indicating no limitation to extreme limitation), <i>p</i> indicates the modes of competition (0: completely symmetric; 1: perfectly size-symmetric; 10: highly size-asymmetric; ∞: completely asymmetric). Values of RII indicate the intensity of interactions as competition (from −1 to 0), neutral interaction (equal to 0) and facilitation (from 0 to 1).</p

Slopes and intercepts of self-thinning trajectories of mean individual biomass versus survivor density under different levels of resource limitation and modes of competition.

<p><i>RL</i> indicates the level of resource limitation (from 0 to 1 indicating no limitation to extreme limitation), <i>p</i> indicates the modes of competition (∞: completely asymmetric; 10: highly size-asymmetric; 1: perfectly size-symmetric; 0: completely symmetric). Bars indicate 95% confidence intervals.</p

Data_Sheet_2_Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans—An agent-based modeling approach.PDF

Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity).</p

Data_Sheet_1_Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans—An agent-based modeling approach.pdf

Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity).</p

Schematic representation of a PCQM sample point with trees represented as circles, squares or triangles.

<p>In this example squares are always the nearest to the sample point and represent trees measured for PCQM, followed by circles for PCQM2 and triangles for PCQM3.</p

The relative root mean square error (RRMSE) and relative bias (RBIAS) with “aggregated” spatial pattern, varying aggregation radius (AR), varying aggregation intensity (AI) and a fixed true density of 3000 ha^-1.

<p>The relative root mean square error (RRMSE) and relative bias (RBIAS) with “aggregated” spatial pattern, varying aggregation radius (AR), varying aggregation intensity (AI) and a fixed true density of 3000 ha^-1.</p

Box plot of the density (individuals ha^–1) distribution of 1,000 simulations estimated with different methods using varying sample points (N = 15 to 100) comparing the differences between the two estimators in three natural populations (site 1, site 2 and site 3).

<p>In each sample size, boxes with white background represent <i>corrected</i> estimators and those with grey background represent <i>published</i> estimators (PCQM1, PCQM2 and PCQM3 from left to right in each scenario). The dotted horizontal line in each plot indicates the true density.</p

The relative root mean square error (RRMSE) and relative bias (RBIAS) with varying true density and “random” spatial pattern.

<p>The relative root mean square error (RRMSE) and relative bias (RBIAS) with varying true density and “random” spatial pattern.</p