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The author(s) have made the following declarations about their contributions: Conceived and designed the experiments: RMP. Performed the experiments: RMP. Analyzed the data: RMP DFD. Wrote the paper: RMP DFD. Contributed data, technical advice, and reviews of the manuscript: AKB RJ TMP.

The authors have declared that no competing interests exist.

Termites indirectly enhance plant and animal productivity near their mounds, and the uniform spatial patterning of these mounds enhances the overall productivity of the entire landscape.

The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity). Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity): insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced). This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.

Local interactions between organisms in nature can scale up to produce strikingly regular patterns across entire landscapes. With improvements in satellite imagery, such patterns are increasingly reported in the ecological literature. It remains unclear, however, whether the existence of such patterns actually matters for key ecosystem processes such as productivity. In semi-arid East Africa, below-ground mounds built by

A succession of spatially explicit ecological models in the early 1990s indicated that large-scale regular spatial patterns could arise within homogeneous landscapes from local biotic interactions alone

Over the past decade, however, multiple studies have shown that regular patterns are both common and persistent across a range of ecosystems

Our study site in central Kenya (0°20′ N, 36°53′ E) is a wooded grassland on level vertisol soils. The high clay concentration (40%–60%) of these soils reduces water infiltration and causes shrink-swell dynamics that can shear plant roots

In this ecosystem, fungus-cultivating termites (Macrotermitinae:

(A) Multispectral Quickbird satellite image (2.4 m resolution, here in false-color infrared) showing even spacing of termite mounds (small circular regions with red color indicative of high primary productivity; large red regions are abandoned cattle corrals). White rectangle encompasses the 0.36 km^{2} area mapped for analyses (see _{1,33} = 9.5, _{1,33} = 49.0, _{1,33} = 10.9, _{1,61} = 22.6, _{1,62} = 4.9, _{1,62} = 49.3, _{1,62} = 42.8, _{1,62} = 15.0, _{1,62} = 0.7, _{1,62} = 26.5, _{1,61} = 16.1,

We used field observations and manipulative experiments to show that, by enhancing primary productivity on and around their mounds, termites exert positive indirect effects upon multiple trophic levels of arboreal animals, from herbivorous insects to spiders and geckos. We further show that these indirect effects create spatial patterns in the abundance and reproductive output of these taxa that parallel the patterning of termite mounds. We then extrapolated these patterns to the landscape scale, showing that uniform spacing of termite mounds (over-dispersion) increases secondary and tertiary productivity relative to simulated landscapes in which mounds were randomly distributed.

We quantified the spatial pattern of termite mounds using Ripley's

To determine whether the gecko _{c}

Using the parameters of this model, we determined the mean probability of occupancy (≥ 1 gecko) as a function of mound proximity for five percentiles of tree size (

(A) Probability of gecko occupancy (≥1 individual) as a function of mound proximity and five percentiles of observed tree surface area. (B) Spatial probability distribution of number of geckos per tree in a 0.36 km^{2} portion of the study site, assuming trees with median surface area. Expected values for each grid cell are drawn from the best-fitting ordinal-regression model of number of geckos per tree (

Two questions remain about the mechanisms causing this pattern. First, mean tree size decreased with distance from the nearest mound (_{1,475} = 19.3,

We addressed these issues experimentally using artificial “trees” consisting of wooden posts of two sizes (“large” and “small”). These posts differed only in their size. At each of 12 mounds, we placed one post of each size at both 10 m (“close”) and 30 m (“far”) from the mound center, controlling for nearby tree density. From October 2006 to June 2007, we surveyed all posts 12 times. Occupation frequency was greater on large and close posts than small and far ones (_{1,32} = 7.8, _{1,32} = 4.5,

(A) Gecko habitat-selection experiment (repeated-measures MANOVA main effects: post size _{1,33} = 95.9, _{1,33} = 11.0, _{1,33} = 7.5, _{1,99} = 21.9, _{1,88} = 5.1,

Thus, tree size and mound proximity have independent effects on gecko occurrence. To test whether the effect of mound proximity indeed arose from variation in prey availability, we repeated the artificial-tree experiment with one modification: we affixed plastic cups to the base of every post and, each morning from August–December 2007, we added 3–9 non-flying insects to cups at all far posts only. Consistent with the prey-availability hypothesis, prey supplementation almost equalized the overall mean occupation frequencies at 10 m (0.799±0.064 geckos/post) and 30 m (0.771±0.046 geckos/post) from termite mounds (

That adding prey increased occupation of far posts is consistent with a behavioral response to food availability but does not rule out a simultaneous numerical (i.e., reproductive) response. It is difficult to measure variation in reproductive output for _{c}

These results are a unique demonstration that subterranean termites indirectly enhance abundance and create spatial pattern across multiple trophic levels of tree-dwelling animals. We next tested the theoretical prediction ^{2} mapped portion of the study site (see _{c}

For every variable, the real (over-dispersed) landscape was far more productive than were simulated landscapes with randomly distributed mounds. The estimated means for all response variables in the over-dispersed landscape were >99.9th percentile of the means obtained from the 1,000 randomly generated landscapes (

Vertical bars show the mean landscape value for each variable obtained using the evenly spaced distribution of termite mounds in the mapped 0.36 km^{2} area of the landscape (

This analysis assumes that multiple mounds would not have additive effects on the density or productivity of trees and tree fauna, which might lead to greater production under clumped scenarios than our models (which were based only on nearest-mound distance) predict. We tested this assumption. When we collected data on gecko abundances in 2009 to test the predictive power of our best-fitting ordinal regression model, we recorded the locations of the two mounds closest to each tree (hereafter, nearest and second-nearest). Adding second-nearest mound distance as a predictor to our best model did not improve the model whatsoever (−2×log-likelihood = 666.265641 for both models). Because nearest and second-nearest mound distances were very weakly correlated (

Collectively, our data show (a) that a regularly patterned array of termite mounds induces parallel patterning in the abundance and reproductive output of tree-dwelling fauna, (b) that these patterns arise via both consumptive (i.e., trophic) and non-consumptive (i.e., engineering) indirect interactions, and (c) that the uniformity of the pattern increases the total biomass of prey and predators in the landscape. This emergent effect of spatial pattern upon a fundamental ecosystem function (productivity across trophic levels) confirms theory predicting linkages between patterning and production. Our results further imply that the landscape-level effects of any set of features that induce local gradients in ecological processes are likely to hinge on the spatial patterning of these features, with highly uniform spacing often producing the strongest net outcomes. Future work should address how the landscape-level effects of different spatial patterns vary with the shape and slope of biotic distance-response functions, as well as with possible interactive effects among patterned features.

Our study highlights the importance of conserving pattern-inducing taxa and processes—in this case, termites and their mound-building activities. In Africa's fields and pastures, termites are sometimes eradicated to protect crops and forage, and mounds are sometimes destroyed to redistribute the nutrients within them

We conducted this study between June 2006 and August 2009 at the Mpala Research Centre (0°20′ N, 36°53′ E) in central Kenya. Total rainfall during this period was 1,810 mm. The annual pattern was variable and tri-modal, with peaks in August (70 mm) and November (93 mm) of 2006; April (86 mm), June (152 mm), and September (98 mm) of 2007; and May (99.6 mm), July (58.7 mm), and October (143.8 mm) of 2008, followed by drought. The study area is underlain by flat, heavy-clay vertisol (“black cotton”) soils of recent volcanic origin, which are characterized by impeded drainage, pronounced shrink-swell dynamics

Each

Nests built by subterranean termites (Macrotermitinae:

Macrotermitinae mounds have long been known to occur with apparently even spacing in upland Kenya and other semi-arid regions throughout Africa (^{2} extent, we visually identified circular areas of high productivity, corresponding to termite mounds. To verify accuracy of our visual photo-interpretation, we field-recorded the geographic coordinates of 50 mounds using a CMT March II GPS (1–5 m accuracy), which we overlaid as a shape file upon the satellite image, confirming that these ground-truthed points did indeed appear as mounds on the image. We then applied Ripley's

We identified all arthropods to order and some spiders and beetles to family. For tree-dwelling arthropods, we analyzed predators and prey both separately and together. Because the ecology and taxonomy of the invertebrate fauna of this region is poorly characterized, we treated mantids and spiders as predators and assumed that all other insects represented “prey.” Although this categorization slightly undercounts predators by excluding some predators from trophically mixed orders such as Coleoptera, a previously published stable-isotope analysis of these same samples

We sampled aerial arthropods (

We sampled arboreal arthropods (_{c}

In 2006, as part of a concurrent study, Doak, Brody, and Palmer used a laser rangefinder (accurate to within 10 cm) to map and individually number all trees within ∼35-m-radius semicircles centered on each of six mounds. For this study, we selected three of these mounds and used a random-number generator to choose 60 trees (>1 m tall) for search. The mounds were several hundred meters apart. From July–August 2007, Pringle and two assistants exhaustively searched all trees for geckos, using ladders to reach high branches and probing within any hollows. For all 180 trees, we recorded the number of geckos, mound proximity (nearest 0.1 m), nearest-neighbor distance (nearest 0.1 m), height (nearest 0.1 m), basal diameter (nearest 0.1 cm), and resident

Female spiders guarding egg masses were selected opportunistically and haphazardly. Upon collection, we preserved female spiders in ethanol, placed the egg masses in ventilated plastic cups in a common laboratory environment, and checked them periodically. When we were confident that all spiderlings had emerged from the egg sacs (∼14 d after first emergence), we froze the spiderlings and counted them using a dissecting microscope. It is extremely unlikely that cannibalism among spiderlings during this interval influenced our results; we are not aware of any reports of cannibalism among newly hatched juveniles in the Araneidae, and a bias would require that cannibalism was much more frequent among offspring of females far from termite mounds, which is improbable. Of 110 egg cases, 106 (96%) hatched in the laboratory. We calculated two measures of reproductive output for each female: total number of spiderlings and mean number of spiderlings per egg sac per female (each female's egg mass consisted of 1–12 individual egg sacs).

Jocqué confirmed the genus identification for this as-yet-undescribed species and measured the width of the carapace and the combined length of the tibia and patella of leg I for each adult female. Measurements were made with an ocular graticule in a Leica M10 stereo microscope (measurement unit = 0.0164 mm). We could not obtain reliable carapace-width measurements for four females, giving us a final sample size of 102. Both measures of reproductive output were positively correlated with female carapace width (_{1,100} = 6.1, _{1,100} = 4.3, _{1,100} = 1.3,

To determine the mechanisms (especially the role of termite-mound proximity) influencing tree-dwelling-arthropod abundance, gecko occurrence, and spider fecundity, we constructed sets of candidate regression models and ranked them using the AIC_{c}. Prior to constructing candidate sets, we visually examined the shape of the relationship between each response variable and mound proximity. In all candidate sets, we included both a raw mound-proximity term and one-or-more nonlinear transformations (log_{e} for gecko abundance; square-root for spider abundance; log_{e}, square, and square-root for arthropod abundance/biomass and _{c} results are available from Pringle on request.

To explain variation in the number of geckos on trees, we employed ordinal logistic regression using the “Ordinal” routine in the Statbox 4.2 Toolbox for MATLAB (_{c} (

We conducted multiple-regression analyses of the abundance of adult arboreal spiders (based on our sample of 70 trees that we sprayed with insecticide) that largely paralleled our ordinal-regression analyses of gecko abundance. Independent variables included combinations of mound proximity, estimated tree surface area, square-root transformations of these variables, their first-order interactions, and mound identity. We constructed 26 candidate models and ranked them using AIC_{c} (

We analyzed arthropod abundance and biomass data (log-transformed to meet parametric assumptions) using multiple regression. Response variables included total arthropod abundance and biomass, prey-arthropod abundance and biomass, and predatory-arthropod abundance and biomass. We constructed 24 candidate models for each variable. Unlike for geckos and spiders alone, all models for arthropod abundance/biomass contained a mound-proximity term (either raw or transformed, as described above), but none contained interactions. The other predictors included raw and log-transformed tree size (estimated surface area, as described above) and mound identity. The best models (

For each response variable, we used the single best model for all spatial analyses (see below) and all tests of statistical significance for individual predictors. The log-transformed mound-proximity term was a better predictor of gecko abundance than the linear form. Square-transformed mound-proximity terms best approximated the responses of all arthropod variables except predator abundance, which was best approximated by a linear term, and prey biomass, which was best approximated (albeit non-significantly) by a log-transformed term.

We extrapolated to the landscape scale for six response variables (predatory-arthropod abundance/biomass, total arthropod abundance/biomass, gecko occurrence, and spider fecundity) using a 600×600 m section of our study area, which included 62 termite mounds (

We then compared the estimated mean landscape value of each response variable from the actual, over-dispersed mound landscape with the corresponding distributions of values from simulated random landscapes that lacked the uniform spacing of real mounds (

As mentioned above, the most likely real-world complication that could influence the results of the randomization tests just described is variation in tree densities at different distances from mounds. For one mound in our study area, we mapped the positions of all trees out to ∼35 m in all directions; for five other mounds, we did the same for a ∼35 m radius semicircle. We used these data to determine whether and how the densities of trees >1 m tall vary with distance from mound centers. We used the following procedure to determine densities. First, for each mound, we used a MATLAB routine to construct Voronoi or Thiessen polygons

Using these estimates, we applied general linear models with distance and mound identity as independent variables and density as the dependent variable. For 5 m bins, mound ID is highly significant (^{−7}) and distance is also significant (^{−7}; distance:

These highly variable results make it unlikely that any consistent patterns in tree density would bias the conclusions of our simulations. However, to test for such effects, we used the results from the 5 m binned data to estimate changes in densities for the average mound effect (density = 0.071+0.0011×distance). We used this relationship to estimate a weighted average of all sampled points in the real and simulated landscapes that accounted for the relative tree density at different distances. These results (

Our experiments were designed to (a) isolate the effects of tree size and mound proximity on gecko occupation rates and (b) determine whether mound proximity truly represented a trophic effect. We created artificial gecko habitat using wooden posts of two different sizes. “Large” posts were 2.6±0.06 m tall and 10.3±0.58 cm in diameter (means ± SD) (^{2} for both real and artificial trees; mean occupancy = 0.6±0.2 and 0.7±0.1 geckos/tree, respectively, means±95% CI). At each of 12 termite mounds, we placed one post of each size at both 10 m (“close”) and 30 m (“far”) from the mound center. We placed the large and small posts 5 m from one another at each distance. To control for any confounding influence of neighboring tree density, we situated each post 3 m from the nearest tree ≥2 m tall and ensured that the density of trees in the 20×20 m area surrounding the posts at each distance did not differ (close density = 23.8±6.6, far density = 24.2±6.0, means ± SD).

We completed the experimental setup on September 30, 2006 and waited 1 mo prior to beginning surveys to allow geckos to adjust to the habitat perturbation and colonize the posts. Between October 28, 2006 and June 20, 2007, we conducted 12 surveys of all posts. Because of the simplified architecture of the posts, we suspect that detection probability approached 100%. During five of these surveys, we captured geckos (

To ascertain whether the effect of mound proximity on gecko occupation arose from variation in prey availability, we repeated this experiment in conjunction with daily food supplementation. Insects, which included mealworms, termite workers found in dried dung, and sweep-net contents (all collected off site), were always added to the cups between 7:30 and 8:30 a.m., immediately prior to the onset of peak gecko activity. We did not attempt to capture any geckos during this phase of the experiment (_{1,12} = 0.2,

We analyzed the data from both runs of this experiment using a single repeated-measures MANOVA design (in JMP 8.01). The dependent variables were the mean occupation frequencies of each post during the 12 surveys prior to prey addition and the same mean frequencies for the 12 surveys conducted during daily prey addition to the far posts. The between-subject factors were post size (large versus small), mound proximity (close versus far), their interaction, and mound identity. The within-subject factor was time (pre- versus post-prey addition). In this design, the significant time × mound proximity interaction (

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_{i}_{c}), along with a model (for comparison) that contained only a constant. The best-fitting model, which we used for simulations, appears in bold. _{i}_{c} value and that of the model with the lowest AIC_{c}; the Akaike weight _{i}

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_{i}_{c}), along with a model (for comparison) that contained only a constant. The best-fitting model, which we used for simulations, appears in bold. Symbols correspond to those in _{i}_{i}

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_{c}, as described in the

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We thank Paul Ehrlich, Gretchen Daily, Truman Young, Lauren McGeoch, Glen Weyl, Ted Hart, Os Schmitz, Michel Loreau, and three anonymous reviewers for their insights about this study, the Government of Kenya for permission to conduct it (NCST/5/002/R/656), and Siobhan Phillips for writing a poem about it.