Ecosystem properties self organize in response to a directional fog vegetation interaction
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(2) 1204. DANIEL E. STANTON ET AL.. the atmosphere (by plant harvesting), this combination of essential mechanisms may create the feedback needed for the emergence of self-organization and vegetation bands. We here evaluate the ability of a delivery–consumption–harvest model to resolve spatial patterns of plant growth in response to directional resource distribution caused by wind flow. Borthagaray et al. (2010) showed that a hyper-arid, fog-based ecosystem can form foginduced banding consistent with theoretical predictions. Unlike their elegantly simple ecosystem, most terrestrial ecosystems include additional feedbacks between vegetation and soil. Nutrient pools and fluxes are thought to build up over the course of ecosystem development (e.g., Walker and Syers 1976, Menge and Hedin 2009) through internal feedbacks. The clarity of such a conceptual model may lead it to seem self-evident, yet it is difficult to test, with most evidence provided by long chronosequences. Banded forests arising through selforganization in response to fog may provide an empirical example of forest ecosystem development on a much smaller spatial and temporal scale, with local replication. At Fray Jorge National Park, in the semiarid region of Chile, isolated patches and bands of temperate rainforest in the midst of arid scrubland are maintained by considerable fog-water inputs supplementing low rainfall (Squeo et al. 2004, del Val et al. 2006, Gutiérrez et al. 2008). This is an inversion of the northern temperate spruce blowdowns (Sprugel and Bormann 1981, Satō and Iwasa 1993), in that vegetation presence is enhanced by fog availability, making it a creative rather than destructive process. Prior work by del Val et al. (2006) has shown strong demographic differences between windward and leeward edges of the patches, leading them to suggest that these patches may be dynamic, and move towards the fog. We built a simple model based on basic ecological and biophysical concepts, as well as on previously published studies on this particular ecosystem (del Val et al. 2006, Barbosa et al. 2010, Stanton et al. 2013) to illustrate the spatial and vegetation characteristics of such self-organizing feedbacks. Self-organizing systems will characteristically generate dynamic and spatially complex patterning (Solé and Bascompte 2006), expanding upon the asymmetries created by a laterally delivered input. In a fog-dependent ecosystem, some to all water inputs will be provided by fog or ground-level clouds (Dawson 1998, Weathers 1999). Fog does not wet the soil directly, and therefore must be intercepted by vegetation or man-made structures if is to enter the ecosystem. A contrast can therefore be drawn between rainfall inputs, which are largely independent of vegetation on a local scale, and fog inputs, which will correlate to vegetation presence and size. These inputs to the soil can then be lost to evaporation, diffuse into neighboring soil, or be taken up by the vegetation. Water inputs enable the further growth of vegetation.. Ecology, Vol. 95, No. 5. Fog and other wind-entrained particles do not penetrate deeply into a closed forest (Weathers 1999), and so fog interception will create a downwind ‘‘fog shadow’’ (del Val et al. 2006, Borthagaray et al. 2010) and spatial asymmetries in resource availability (Stanton et al. 2013). Rainfall inputs will not be constrained to the presence of plants. Patterns of self-organization can extend far beyond the generating feedbacks. In addition to affecting water dynamics, vegetation presence will also influence nutrient cycling by providing inputs (leaf and root litter). We document the development, maintenance, and decay of an ecosystem (temperate wet forest) under conditions not predicted by local climate (arid Mediterranean), topography, or underlying soil characteristics (low nutrient mineral soils). Recent work at Fray Jorge (Stanton et al. 2013) suggests that soil water and carbon peaks may occur in different parts of patches, with greatest water availability at the windward edge (associated with fog-water inputs, see del Val et al. 2006) and greatest carbon and nitrogen availability at or beyond the leeward edge (associated with greater mortality, see del Val et al. [2006]). We explore a range of models based on known water supply conditions at the site (rainfall, fog) and use them to predict patterns in the relative spatial distribution of woody plants, soil water, and soil nutrients. Field data from transects across a forest–scrubland matrix at Fray Jorge National Park are used to test the model predictions and discriminate between probable mechanisms. We predict that when rainfall is the primary source of water, the areas of highest soil water availability, soil carbon, and plant biomass will coincide, most likely at the center of patches. In contrast, if the resource delivery is horizontally directional, we predict an offset between the location of peak soil water (at the windward edge with greatest fog interception) and the peaks of plant biomass (in the center of the patch) and soil carbon (at the leeward edge where litter inputs are high but decomposition low). We similarly predict the relative locations of peaks of soil water, soil carbon, and plant biomass to be offset across windward to leeward transects across forest patches in Fray Jorge National Park. METHODS Model We used the NetLogo open source software environment (Wilensky 1999); analytical models of comparable (if simpler) systems exist elsewhere (Satō and Iwasa 1993, Klausmeier 1999, Saco et al. 2007, Borthagaray et al. 2010). Our goals were to (1) evaluate whether banding patterns in forests can self-organize through fog harvesting; (2) to predict the quantitative impact of such organizing processes on easily quantifiable measures, such as the relative distributions of bands; and (3) compare these predictions against observed patterns of vegetation and soil factors in the Fray Jorge ecosystem..
(3) May 2014. ECOSYSTEM SELF-ORGANIZATION AND FOG. 1205. TABLE 1. Model parameters. Variable name. Values. Units. Description. xcor ycor PBi, j g PBmax p(ld) p(lw) FWi, j FWmax R p(Rain) Wi, j Wc Wmax eo ep u diff a hr Ci, j i p(dd) p(dw). 130 40 0–PBmax 0.01 15 0.005 0.001 0–FWmax 25 0–40 0–0.1 0–Wmax 0.05 30 0.01 0.005 0.01 0.001 0.1 4 0–‘ 0.005 0.004 0.001. grid cells grid cells unit height unit height/t unit height unitless unitless unit water unit water percentage of Fmax unitless unit water unit water unit water unit waterunit water1t1 unit waterunit water1t1 unit waterunit height1t1 t1 unit water/unit height unit height unit C unit Cunit height1t1 unit Cunit C1t1 unit Cunit C1t1. grid length grid width plant height growth rate maximum plant height mortality probability in dry soil mortality probability in wet soil water content of air maximum water content of air recharge rate of water content of air probability of saturating rainfall event soil water content critical soil moisture threshold soil field capacity rate of evaporation from open soil rate of evaporation from plant-covered soil plant uptake rate rate of diffusion to neighboring grid cells fog harvesting efficiency minimum plant height for fog interception soil carbon content soil carbon input rate decomposition rate constant in dry soil decomposition rate constant in wet soil. Note: The variable t represents the time step used in the simulations.. The annotated code to the model can be found in Supplement. Table 1 lists the model parameters and values. In our model, a grid (40 3 100 cells) was initially covered with a homogenous plant cover representing the temperate rainforest that historically covered the entire region (Villagrán et al. 2004). We then iterated forward the amount of aboveground plant biomass (PB) in each cell as PBi; j ðt þ 1Þ PBi; j ðtÞð1 pðld ÞÞ ¼ PBi; j ðtÞð1 þ gPB pðlw ÞÞ. if Wi; j ðtÞ , Wc ð1Þ if Wi; j ðtÞ . Wc. where plant growth is a first-order function of biomass (gPB) and mortality is a stochastic process with a probability of death p(l) as a binary function of the soil water (W ) available in each grid cell. When soil water exceeded a critical threshold (Wc), plants grew incrementally and suffered stochastic mortality lw Below the critical soil water threshold, plants did not grow, and suffered stochastic mortality ld, where typically ld . lw Plant growth was constrained to a maximum height (PBmax). Rainfall was assumed to be a stochastic processes by which the soil water of every grid cell was recharged to field capacity (Wmax) with probability ( p[Rain]) at each time step. The harvesting of fog water is primarily an impaction process (Villegas et al. 2008), not unlike filterfeeding, by which inputs will be determined by the. Wi; j ðt þ 1Þ ¼. . surface area available to intercept liquid fog-droplets entrained in air. Fog-water inputs were therefore modeled as a linear function of plant height, limited by the total amount of water contained in the fog above the grid cell. Although the surface area of a plant is unlikely to be a linear function of its height, the shape of the harvesting function does not qualitatively impact the overall dynamics of the model, and the linear approximation was retained for simplicity. Vegetation in fast flowing wind forms a thick boundary layer, below which height very little fog interception will be possible; therefore, fog-water inputs were allowed to occur only when plant size (assumed to scale with biomass) exceeded a pre-determined ‘‘boundary layer’’ height (h). Soil water losses were modeled as the result of evaporation and plant uptake and transpiration. Plants provide shading, and therefore the losses due to evaporation in grid cells with plants (fixed rate ep) were assumed to be lower than in those without (fixed rate eo). Relaxation of this assumption had little qualitative effect on the dynamics observed, and its inclusion served primarily to sharpen the contours of forest patches. Water uptake (and ultimately transpiration, as a firstorder function of plant biomass, uPB) occurred only in the presence of growing plants, and was assumed to be smaller than evaporative losses. Soil water availability in each grid cell was thus modeled in Eq. 2 as a balance of inputs (from rain and fog) and losses from soil (evaporation and plant uptake and transpiration).. Wi; j ðtÞ þ pðRainÞWmax e0 Wi; j ðtÞ þ pðRainÞWmax þ f ðPBi; j ; FWi; j Þ ep uPB. i; j ðtÞ. if PBi1; j ðtÞ , h : if PBi1; j ðtÞ . h. ð2Þ.
(4) 1206. DANIEL E. STANTON ET AL.. At each time step, a small amount of soil water (1%) was redistributed from cells with nonzero soil water to neighboring grid cells to simulate soil water diffusion and drip from overhanging canopies. Available fog water was modeled as a moving cloud. For each row of grid cells, an air parcel moved across the grid along the x-axis (left to right), advancing by one grid cell per time step and looping back to the start when it reached the edge of the grid. The available fog water (FW) in a given parcel of air was a balance of the amount removed by plants (a first-order function of plant biomass, aPB, representing the water contained in fog-water droplets intercepted by the branches of the plant and subsequently dripped to the ground) and recharge (constant rate R, representing the refilling of moisture in the air parcel from the wetter air above it): FWi; j ðt þ 1Þ FWi1; j ðtÞ þ R ¼ FWi1; j ðtÞ aPB. i1; j ðtÞ. if PBi1; j ðtÞ , h : ð3Þ if PBi1; j ðtÞ . h. The recharge of fog water in an air parcel is driven by intermixing between the air at the height of the vegetation and the surrounding air. Increasing turbulence or steeper slopes will contribute to greater recharge rates (see Borthagaray et al. 2010), by increasing the potential for mixing between with overlying air. Within this model framework, slope and fog recharge rate can therefore be seen as equivalent. A very simple carbon cycle was also included in the model. Soil carbon in each grid cell was again a function of inputs from plants (a first-order function of plant biomass, iPB, litter carbon as a proportion of living plant biomass) and losses to soil respiration and photodegradation (a first-order decay constant d): Ci; j ðt þ 1Þ ¼ Ci; j ðtÞ 3ð1 dÞ þ iPB. i; j :. ð4Þ. The sensitivity of the model to essential mechanisms was tested by repeated simulations (10 replicates of 150 000 time steps each, sufficient to reach stable dynamics). Fog recharge rates R and probability of a saturating rainfall event p(Rain) were varied separately to determine the parameter space in which different types of patterning is formed. Sensitivity of the model to other parameters is described more fully in the Appendix. Fieldwork Research was conducted in Parque National Fray Jorge, in the semiarid region of Chile (30840 0 S, 71830 0 W). A large number (370) of small patches of forest form a mosaic embedded in a xerophytic matorral scrubland (Squeo et al. 2004, del Val et al. 2006, Gutiérrez et al. 2008, Barbosa et al. 2010). The persistence of these forest patches, whose species composition closely resembles Valdivian temperate rainforest 1000 km to the south (Villagrán et al. 2004), despite very low rainfall (147 mm annually) at Fray Jorge has been attributed to fog-water inputs of marine origin (del Val et al. 2006, Gutiérrez et. Ecology, Vol. 95, No. 5. al. 2008). Forest patches span a wide range of sizes, from 0.1 to 36 ha (Barbosa et al. 2010) and in some areas form bands perpendicular to the predominant wind direction (Fig. 1). Nine transects were established across forest patches. The patches chosen included those previously studied by Barbosa et al. (2010). To ensure consistency in sampling, each transect was started in the middle of the windward edge of the patch, and extended perpendicular to the edge (in the direction of prevailing winds). The length of each transect depended on the width of the forest patch crossed, and was chosen to extend to at least three sampling points beyond both leeward and windward edges. The ‘‘borders’’ of the patch were determined to be the first and last point along each transect at which at least one woody plant exceeded 3 m in height. These transects were conducted as part of a study documenting within-patch asymmetries (Stanton et al. 2013) for vegetation structure, composition, light availability, aerial root and leaf litter depth, soil moisture, and soil characteristics (total C, total N, density). To avoid any micro-topographic effects, for the present study we focused patches on two moderately sloped plateaus, where very small patches and matorral scrubland alternate with no change in slope. Three of the forest transects originally described in Stanton et al. (2013) were extended by 130–200 m beyond the forest patch edge, sampled at 5-m intervals, encompassed much of the surrounding matorral scrubland, and crossed additional, neighboring patches. In total, 12 forest patches were sampled. Vegetation structure was assessed at 2-m intervals along each transect. The area surrounding the sampling point was divided into four equal quadrats. The height and species of the canopy overlying the sampling point, as well as the height and identity of the nearest woody plant species in each quadrat, were recorded. Volumetric soil moisture at 2-m intervals was recorded in situ using a handheld TDR probe (Fieldscout TDR 100; Spectrum Technologies, Plainfield, Illinois, USA). Five measurements were recorded for each sampling point, after clearing away leaf litter and subaerial roots. Soil samples for soil nutrient content were collected at 2-m intervals. Approximately 20 g of soil were collected, homogenized, and oven dried at 608C to constant mass in the Biogeochemistry lab of the Pontificia Universidad Católica de Chile, Santiago, Chile. Subsamples (;3 g) were sieved through 1-mm mesh and sent to the Hedin Lab, Princeton University, Princeton, New Jersey, USA for analysis. Samples were ground by mortar and pestle and oven dried at 608C for 3 d prior to carbon and nitrogen analysis using a Carlo Erba 4500 Elemental Analyser (Costech, Valencia, California, USA). Comparison of model and field data All statistical analyses were performed in R (R Development Core Team 2010). Simulated landscapes.
(5) May 2014. ECOSYSTEM SELF-ORGANIZATION AND FOG. 1207. FIG. 1. Small forest patches in Fray Jorge National Park, northern Chile, with low-shrubby matorral in the foreground. Prevailing winds carry clouds from the coast from right to left across the area shown, and the greater prevalence of dead trees in the leeward edges is discernible. Trees within the patches are 3–5 m tall and the horizontal width of each patch is ;30 m. Photo credit: D. Stanton.. were ‘‘sampled’’ in the same way as the field data, by conducting virtual transects from windward to leeward across the middle of the grid. Within each transect, the individual patches were identified and measured according to criteria similar to those for the field (first and last plant above the threshold for fog collection). Many of the parameters in the model are not easily assigned values from existing literature on the system (del Val et al. 2006, Gutiérrez et al. 2008, Barbosa et al. 2010, Stanton et al. 2013) or measured in the field (e.g., fog recharge rates). Although the parameters of the simulated data are not directly equivalent to real-world measures, the patterns generated have nondimensional properties that allow for easy comparison of patterns. The relative widths of patches and inter-patch spaces can be used as a nondimensional descriptor of banding patterns. Differences in the underlying mechanism of pattern generation can produce different relative locations of the peak values of measured variables. To quantitatively compare model and field patterns, we compared the relative locations of the peak values of the three variables generated by both model and field data: plant height, soil water content, and total soil carbon. The distances between peaks were normalized by the patch width to provide nondimensional metrics of landscape patterning. The mean relative difference between peaks was compared using paired Wilcox tests.. RESULTS We evaluated the ability of our model to reproduce the observed banded vegetation patterns as a function of rainfall rates (defined as the probability of saturating rainfall event) and fog delivery (defined as rate of recovery of fog water to a parcel of air following plant interception). The model was able to reproduce banded vegetation patterns at low rainfall levels in the presence of fog (Fig. 2). Rainwater inputs alone, regardless of frequency of saturating rainfall events, were unable to generate banding patterns. High rainfall frequency could maintain continuous forest patches, while low rainfall excluded trees entirely. Intermediate levels of rainfall, however, were sometimes able to maintain patchy distributions of trees, but not the directional vegetation bands observed in the field. Changing the rainfall distribution from the flat random distribution used in the primary simulations to a Poisson distribution did not qualitatively affect pattern formation. Directional fog, however, could generate banding patterns at all but the highest levels of rainfall. Very high rainfall supplied sufficient water for closed canopy forest, which obscured any banding. Band width correlated positively with fog delivery in the absence of rain (r 2 ¼ 0.355, F1, 377 ¼ 39.03, P ¼ 3.13 3 108) and weakly with rainfall frequency (r 2 ¼ 0.09557, F1, 130 ¼ 37.88, P ¼ 2.1 3 109). Differential mortality between wet and dry soil was not required for the formation of bands, but in constant mortality scenarios, bands tended.
(6) 1208. DANIEL E. STANTON ET AL.. to be broader and less clearly defined. Bands moved towards the oncoming fog whenever they formed, except in the complete absence of any soil water diffusion to neighboring grid cells (Appendix). Directionality of fog delivery was critical to the formation of regular patterning; random wind movement impeded the formation of clear patches or bands (Appendix: Fig. A3). Simulated patches moved across the landscape in the windward direction. This movement was remarkably constant across a wide range of parameters, and movement rate was unaffected by rainfall or fog availability. Movement rates were most strongly determined by plant growth rates and water inputs at the windward edge, since the expansion of the leading edge is what determines the conditions within the rest of the patch. Patches formed first as individual ‘‘islands’’ that eventually joined together into bands spanning the breadth of the simulation field. The bands were partially reset by each major rainfall event, since growth outside the already established patches was then possible for a short window. The natural landscape is therefore made up of elongated islands rather than long bands. We next evaluated whether the simulated banding patterns were similar to those observed in the field (Fig. 1). To do this semiquantitatively, we considered the spatial distributions of plants, soil water, and soil carbon. A distinct characteristic of the field observations was that locations of the peak values of plant height (Appendix: Fig. 3A), soil water (Appendix: Fig. 3B), and soil carbon (Appendix: Fig. 3C) differed considerably. Although the spatial distribution of the vegetation bands in the model can be viewed as an implicit result of the choice of model parameters, the relative location of soil properties was not predetermined, and therefore may be considered diagnostic of the mechanisms involved. Soil water peaks were consistently found significantly upwind of the peaks for plant height in both field observations (P ¼ 0.00454, two-sided paired Wilcox test, n ¼ 12 forest patches; Fig 4A, left panel) and in model simulations excluding rainfall but including fog (Fig. 4A, middle panel). Rainfall in the absence of fog eliminated any spatial separation between water and vegetation peaks (Fig. 4A, right panel). The formation of bands was not a consequence of the grid dimensions or sensitive to other model parameters (Appendix). The separation of peaks was quantitatively but not qualitatively sensitive to the choice of parameter values in the simulations, such that the choice of boundary layer height, fog density, fog collection ability, mortality (in wet and dry conditions), and decomposition rates used were representative rather than exceptional cases (Appendix). In the field data, soil C and soil N peaks were consistently downwind of peak plant height (P ¼ 0.106 and 0.027, respectively, n ¼ 10 forest patches; Fig 4B, left panel), and not significantly different from each other.. Ecology, Vol. 95, No. 5. The model did not simulate soil N, but did reproduce the same significant offset between plants and soil C at high fog delivery rates in the absence of rainfall (Fig. 4B, middle panel). Limited fog delivery or rainfall alone did not produce any significant spatial separation between plants and soil nutrients (Fig. 4B, right panel). As might be expected from the relative positions of soil water and plants, in the field, soil C (P ¼ 0.0107, n ¼ 10) and soil N (P ¼ 0.00025, n ¼ 10) were both consistently downwind of soil water peaks (Fig. 4C, left panel). In the simulations, fog alone generated a similar significant offset between soil water and soil carbon peaks (Fig. 4C, middle panel). Such a peak separation was not, however, produced by rainfall (Fig. 4C, right panel) DISCUSSION Most broadly, our findings support the idea that positive feedbacks between plant and fog-water inputs can promote the formation of banded vegetation patterns, as well as partially offset banded patterns in distributions of soil C and N (downwind of vegetation peak) and water (upwind of vegetation peak). We infer that in the Fray Jorge ecosystem, the relative absence of rainfall, but presence of directional fog, is the dominant factor that creates both the structure and the functional feedbacks that permit the persistence of these unique, banded plant communities. Furthermore, this feedback is disrupted as one moves from the forest edge into the plant community. In turn, this disruption of feedbacks initiates a decay of the same ecosystem through increased mortality and reduced recruitment. The fogforest patches described in this study thus replicate both the growth and self-induced decay of a temperate forest over a much reduced spatial scale (,50 m). A simple model that did not impose an underlying spatial pattern or explicit competition for soil water was sufficient to generate patterns closely analogous to those in the field and to generate the spatial differences between three key variables observed in the field. More striking was the impact of this emergent banding on belowground resources. The simple assumption that carbon losses from soil are greater in wet than dry soil (due to the dependence of microbial respiration on water) is sufficient for the generation of telltale wakes of increased soil carbon downwind from the forest patches. The sole external drivers (intermittent rainfall and directional fog-water inputs) did not a priori impose these complex spatial patterns, which instead arose through internal feedbacks. The appearance of these complex spatial patterns (repeated banding, spatial separation of resource peaks) is consistent with selforganization of the ecosystem, above and beyond the asymmetries generated by lateral resource delivery (Stanton et al. 2013). These ‘‘footprints’’ (markers of forest patch movement), are clearly identifiable in transects across both natural and simulated landscapes (Fig. 3). Their existence lends further support to recent.
(7) May 2014. ECOSYSTEM SELF-ORGANIZATION AND FOG. 1209. FIG. 2. Steady-state simulated vegetation patterns (150 000 steps) as a function of fog recharge rates (percentage of maximum water content recovered by passing over a grid cell) and probability of a saturating rainfall event at each time step, p(rain). Colors show percentage of vegetation cover, from bare (red) to continuous (green). Plots on the left are contour maps of vegetation height, with x and y dimensions outlining the grid space. These plots show representative simulated landscapes for continuous cover, sparse trees, and banded vegetation, respectively.. notions that these forest patches are not simply products of anthropogenic forest fragmentation but are instead natural units in this landscape (del Val et al. 2006). These features are generated by differential water availability and its impacts on demography. Competition for water will favor windward growth, both of individual plants and of the forest patch as a whole. Gutiérrez et al. (2008) reported a skewed distribution in tree ages, and del Val et al. (2006) found recruitment to be highest windward and mortality to increase leeward. That soil water is limited beyond the windward edge of patches (Fig. 3), means that the high leeward mortality may be driven by drought. Indeed, leeward edges of the forest patches are characterized by the presence of aridadapted shrubs from the surrounding matorral (del Val et al. 2006, Salgado-Negret et al. 2013, Stanton et al. 2013; Vidiella and Dawson, unpublished data). Seemingly cyclical patterns in vegetation dynamics have long been known (e.g., Watt 1947), and well studied within the context of community succession. This discussion has, however, been dominated by a focus on species identity and interspecific competition. Nevertheless, our findings suggest that these patterns also can be generated through the process of asymmetric collection and depletion of resources and its influence on demography. Although it can be argued that the upwind interception of fog is indeed marked by competition, the situation differs from the usual concepts in that the mortality at the leeward edge is not caused by the forest trees being outcompeted by the surrounding shrubs, so much as by more distant conspecifics. This may seem. like definitional fussing, but the mechanisms of these dynamics are significantly different. Although topography does not directly determine the location of forest patches, it nonetheless indirectly affects the banding pattern. The effects of slope on banding patterns have been explored in considerable detail in the models of fog-fed Tillandsia fields (Borthagaray et al. 2010) and semiarid tiger-bush (Klausmeier 1999, Saco et al. 2007). In our model, as in that of Borthagaray et al. (2010), this effect is equivalent to changes in fog recharge rates, such that increased fog recharge is equivalent to steeper slopes (and thus reduced separation of bands). This effect is separate from the total amount of moisture in fog reaching the ecosystem, such that reduced fog inputs on a steeper slope could, but not necessarily, lead to banding. In the field, larger patches are often found on steeper slopes (Barbosa et al. 2010), and many spatial asymmetries found in small patches are reduced or absent in large patches (Stanton et al. 2013), which is consistent with our finding of greater patch size and reduced patch separation at high fog recharge rates. Interestingly, in the presence of the feedbacks between plants and soil nutrients identified in the present study, slope would increasingly reduce the space/time for decay of forest soil characteristics, minimizing any belowground patterns. On sufficiently steep slopes, continuous canopy cover might never be lost, and indeed patch size appears to be correlated with slope. Internal breaks in the forest or localized ones of higher mortality would pass unnoticed in a large, seemingly continuous patch..
(8) 1210. DANIEL E. STANTON ET AL.. Ecology, Vol. 95, No. 5. FIG. 3. Attributes of small forest patches in Fray Jorge National Park: (A) plant height, (B) soil moisture, and (C) total soil carbon. Gray vertical dashed lines mark the forest patch edges. Box plots show median (middle line), interquartile range (box edges), maxima and minima within 1.5 times the interquartile range (whiskers), and outliers (open circles). Distance is measured in meters in the leeward direction from the windward direction of the patch (i.e., negative distances are windward of the patch). Data represent the averages of three transects through small forest patches in the flattest area of Fray Jorge.. The directional dynamics of this model predict progressive windward movement of patches, as suggested by del Val et al. (2006). Since growth and decomposition rates in arid environments such as Fray Jorge are low, the rate of movement of these patches is likely to be slow and only perceptible on a centuries scale. The total soil carbon content drops from around 22% mass to the matorral average of 6% within 20–30 m of the leeward edge (Fig. 3C). This translates into a rate of approximately 0.04–0.05% C/m, assuming first-order decomposition processes. If we apply the decomposition rates found for perennial grass litter in the Argentinian steppe (0.4% C/yr; Austin and Vivanco 2006), this would suggest a movement rate of 8–10 yr/m. Since the rate estimates are from a slightly wetter (150 mm annual precipitation) site and possibly less recalcitrant litter, they serve as a lower bound for patch movement rates. Such movement would be difficult to detect from aerial photography, but becomes quite significant over the course of centuries, an entire cycle from windward edge. to open matorral to new windward edge taking ;1000 yr for the distantly spaced small patches considered in this study. Such slow movement may account for the fact that the patches form elongated islands rather than long bands, since the landscape may still be in transition after wetter glacial conditions. The sensitivity of the model to parameterization provides some insights into the responses of selforganized systems to climatic changes. Changes in climate impacting the rate of growth of plants at the leading edge could lead to changes in the rate of movement, whereas changes in fog availability are more likely to influence the width of the patches. Increased rainfall would favor growth of plants outside of the facilitating environment of the windward edge, and lead to less marked patches. Generation of new patches outside of existing ones may be the only process obviously dependent on occasional rainfall pulses, such as El Niño events (Holmgren and Scheffer 2001)..
(9) May 2014. ECOSYSTEM SELF-ORGANIZATION AND FOG. 1211. FIG. 4. Separation between locations of peak values of (A) soil water and plant height, (B) plant height and soil carbon, and (C) soil water and soil carbon. A significant departure from zero (see footnote for P values) indicates that the locations of greatest soil water, tallest vegetation, and/or greatest soil carbon stocks are spatially separate across the landscape. Field data (left panels) are shown compared to the results of simulations with varying fog recharge rates (equivalent to slope) but no rainfall (middle panels) and simulations with increasing rainfall probability but no fog (right panels). Box plots show median (middle line), interquartile range (box edges), maxima and minima within 1.5 times the interquartile range (whiskers), and outliers (open circles). Distances between patches are normalized by patch width to allow non-dimensional comparison of simulated data and field measurements. *** P , 0.0005; ** P , 0.005; * P , 0.05; n.s., not significant. Positive feedbacks are often conceptually associated with rapid changes. The dependence of many biogeochemical processes on water means that loss of a waterbased positive feedback induces a slow rather than abrupt decrease of soil characteristics associated with broken feedback. The reliance on water makes this ecosystem an accelerated analog to models of ecosystem development (e.g., Walker and Syers 1976): a given location would see a forest develop and decay aboveground over the course of a few centuries. The forest patches presented in this particular study may represent an extreme reliance on positive feedbacks than that found in many ecosystems. This very fact may. make Fray Jorge illustrative of developmental processes often obscured by time or opposing variables in other ecosystems. Resources are often not predominantly horizontally distributed, but positive feedbacks remain significant in their development. The fog-forest patches of Fray Jorge are a reminder that even in the absence of external changes, the internal structure and dynamics of ecosystems need not be static in time or space. ACKNOWLEDGMENTS This research was funded by NSF DDIG award # 0909984 to L. Hedin and D. Stanton; Princeton Latin American Studies Travel Grants and a Princeton President’s Award to D. Stanton. Research in Chile was conducted under CONAF.
(10) 1212. DANIEL E. STANTON ET AL.. research permit 06/08. We extend special thanks to Beatriz Salgado-Negret for her help with fieldwork and discussion of ideas; Patricio Valenzuela, Marı́a Fernanda Pérez, and the CONAF staff at Fray Jorge for support in the field; and Aurora Gaxiola, Luke Robinson, Pablo Marquet, Allison Shaw, and members of the Hedin lab for their support and discussion of ideas. We also thank D. Doak and two anonymous reviewers for helpful editorial comments. LITERATURE CITED. Austin, A., and L. Vivanco. 2006. Plant litter decomposition in a semi-arid ecosystem controlled by photodegradation. Nature 442:555–558. Barbosa, O., P. A. Marquet, L. D. Bacigalupe, D. A. Christie, E. Del-Val, A. G. Gutiérrez, C. G. Jones, K. C. Weathers, and J. J. Armesto. 2010. Interactions among patch area, forest structure and water fluxes in a fog-inundated forest ecosystem in semi-arid Chile. Functional Ecology 24:1–9. Borthagaray, A. I., M. A. Fuentes, and P. A. Marquet. 2010. 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Squeo, A. Gutiérrez, and I. Hernández, editors. Historia natural del Parque National Bosque Fray Jorge, Ediciones Universidad de La Serena, La Serena, Chile. Villegas, J. C., C. Tobón, and D. D. Breshears. 2008. Fog interception by non-vascular epiphytes in tropical montane cloud forests: dependencies on gauge type and meteorological conditions. Hydrological Processes 22:2484–2492. Walker, T., and J. Syers. 1976. Fate of phosphorus during pedogenesis. Geoderma 15:1–19. Watt, A. 1947. Pattern and process in the plant community. Journal of Ecology 35:1–22. Weathers, K. 1999. The importance of cloud and fog in the maintenance of ecosystems. Trends in Ecology and Evolution 14:214–215. Wilensky, U. 1999. NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, Illinois, USA.. SUPPLEMENTAL MATERIAL Appendix Additional figures showing sensitivity of model to key parameters (Ecological Archives E095-103-A1). Supplement Netlogo code for simulating forest dynamics in response to directional fog and rain (Ecological Archives E095-103-S1)..
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