Eric Harvey
email: eric.harvey@eawag.ch

Isabelle Gounand

Pravin Ganesanandamoorthy

Florian Altermatt

Spatially cascading effect of perturbations in experimental meta-ecosystems

Keywords: meta-ecosystems, disturbance regime, allochthonous subsidy, spatial flows, global change

Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighboring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross-ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to highest level of subsidy flows, however the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over-time. Both theoretical and experimental results

show that perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for an integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows.

Introduction

The importance of allochthonous subsidies for biological community persistence and functioning in recipient ecosystems has been long recognized [START_REF] Fisher | Energy flow in bear brook, New Hampshire: an integrative approach to stream ecosystem metabolism[END_REF][START_REF] Polis | Extraordinarily high spider densities on islands: flow of energy from the marine to terrestrial food webs and the absence of predation[END_REF][START_REF] Polis | Toward an integration of landscape and food web ecology: The Dynamics of Spatially Subsidized Food Webs[END_REF]. Ecosystems are linked to neighbouring ecosystems through their shared boundaries by the spatial movement of resources, despite wide variations in magnitude and type of inputs (e.g., movement of prey, detritus, nutrient). Allochthonous inputs to the recipient ecosystem subsidize primary producer biomass, consumer biomass [START_REF] Murakami | Indirect effect of aquatic insect emergence on a terrestrial insect population through by birds predation[END_REF][START_REF] Gratton | Ecosystem linkages between lakes and the surrounding terrestrial landscape in Northeast Iceland[END_REF][START_REF] Krell | Aquatic prey subsidies to riparian spiders in a stream with different land use types[END_REF], and strongly modulate the dynamics and structure of food webs [START_REF] Bartels | Reciprocal subsidies between freshwater and terrestrial ecosystems structure consumer resource dynamics[END_REF][START_REF] Turschak | Nearshore energy subsidies support Lake Michigan fishes and invertebrates following major changes in food web structure[END_REF]. These spatial flows may even trigger complex dynamical feedbacks between ecosystems (meta-ecosystem dynamics), acting at different trophic levels. Over the last decade, extensive conceptual and theoretical work has suggested that meta-ecosystem dynamics, by integrating spatial flows of energy, material and organisms, may have important implications for the stability of biological communities [START_REF] Marleau | Nutrient flows between ecosystems can destabilize simple food chains[END_REF][START_REF] Gounand | The paradox of enrichment in metaecosystems[END_REF] and the unfolding of ecosystem processes [START_REF] Marleau | Nutrient flows between ecosystems can destabilize simple food chains[END_REF][START_REF] Gravel | Source and sink dynamics in meta-ecosystems[END_REF][START_REF] Gravel | Patch dynamics, persistence, and species coexistence in metaecosystems[END_REF][START_REF] Marleau | Meta-ecosystem dynamics and functioning on finite spatial networks[END_REF][START_REF] Richardson | Resource subsidy flows across freshwaterterrestrial boundaries and influence on processes linking adjacent ecosystems[END_REF]. As a direct consequence of such a coupling of energy/resource release and spatial transport between ecosystems, perturbations in one ecosystem will likely affect community structure and functioning in neighbouring ecosystems via increased or decreased subsidies. Such a scenario is expected to be common in natural systems under recurrent perturbation dynamics [START_REF] Greenwood | Flooding impacts on responses of a riparian consumer to cross-ecosystem subsidies[END_REF]. For instance, spatial flows of nutrients and detritus from a forest to a lake or a river are greatly affected following a fire due to increased erosion and nutrient runoff [START_REF] Minshall | Responses of stream benthic macroinvertebrates to fire[END_REF][START_REF] Spencer | Wildfire effects on stream food webs and nutrient dynamics in Glacier National Park, USA[END_REF][START_REF] Neary | Wildland fire in ecosystems: effects of fire on soils and water[END_REF]. Because perturbation pressure is usually intensified in humanmanaged regions, the dependence of spatial flows on perturbations is expected to be even stronger. This is well exemplified by the effect of biomass harvesting and fertilization in agricultural systems leading to higher resource runoffs in streams, which in turn leads to higher primary production in downstream lakes and potentially to eutrophication issues [START_REF] Tilman | Forecasting agriculturally driven global environmental change[END_REF]. Such changes in ecosystem budgets (carbon and nutrient) following fire, overgrazing or intensive agricultural practices have been widely studied by ecosystem and forest ecologists for their direct impacts on neighbouring ecosystems [START_REF] Neary | Wildland fire in ecosystems: effects of fire on soils and water[END_REF][START_REF] Tilman | Forecasting agriculturally driven global environmental change[END_REF][START_REF] Caraco | When terrestrial organic matter is sent down the river: Importance of allochthonous C inputs to the metabolism in lakes and rivers[END_REF][START_REF] Chen | Climatic warming and overgrazing induced the high concentration of organic matter in Lake Hulun, a large shallow eutrophic steppe lake in northern China[END_REF].

However, rather than directly impacting subsidies (e.g. by leaching of agricultural fertilizers), perturbations can also trigger indirect effects between communities by modifying local community dynamics such that outflowing subsidies are increased or decreased. This can occur if some specific traits of the local community or population interact with perturbation frequency or intensity to increase or decrease local detritus production, generating variations in spatial subsidies to connected ecosystems. The historical divide between community and ecosystem ecology impeded a unification of these perspectives despite its potential significance for understanding connectedecosystem dynamics and the cascading effect of perturbations across the landscape [START_REF] Loreau | From Populations to Ecosystems: Theoretical Foundations for a New Ecological Synthesis (MPB-46)[END_REF].

In the context of global changes, many perturbations are likely to affect resource exchanges between ecosystems, either directly (e.g., agricultural nutrient loads) or indirectly with impacts on communities triggering modifications of outflowing subsidies (e.g., habitat fragmentation, resource exploitation). This suggests that spatial variations in ecosystem processes and services in human-altered landscapes will be at least partly determined by meta-ecosystem dynamics [START_REF] Altermatt | Diversity in riverine metacommunities: a network perspective[END_REF], and their alteration following community response to perturbations.

In this study we propose a demonstration of meta-ecosystem dynamics under perturbations by studying the effects of perturbation-induced cross-ecosystem subsidy exchanges on each ecosystem's biological community and function over time. First, we used a mathematical model inspired from general harvesting theory that couples population demographics to recurrent perturbations, from which we extracted the analytical prediction that detritus levels closely depend on the interaction between local species dynamics and perturbation regime, and that they follow a hump-shaped relationship with perturbation intensity. We then experimentally tested this prediction and analysed its spatial consequences on neighbouring community dynamics using two-patch meta-ecosystems containing contrasting protist communities: one heterotrophic, and one autotrophic community. Such a configuration is commonly seen in many natural ecosystems such as the coupling found between lake benthic (or stream) and forest (or cropland) ecosystems. We simulated a perturbation gradient affecting both ecosystems simultaneously and altering cross-ecosystem subsidy exchanges. The perturbation consisted in the sampling of a certain volume corresponding to the perturbation intensity/subsidy diffusion level (0%, 5%, 30% and 80% of total volume) from each ecosystem. Living protists were subsequently turned into dead biomass and the sample transferred to the recipient ecosystem. Perturbations and subsidy diffusion events occurred repeatedly at controlled intervals, over a three-week period. In parallel, we monitored changes in protist and bacteria density, and percentage oxygen availability as a proxy for ecosystem functioning in each ecosystem.

Methods

Model description

Resource subsidies are often linked to perturbations. Mortality triggered by perturbations fuels the detritus pool that can serve as new resources for organisms, which can be transferred to other ecosystems as subsidies. For instance, during a storm there may be increased leaf litter input from the riparian vegetation into rivers, or in marine fisheries discarded by-catch may feed benthic marine ecosystems [START_REF] Groenewold | Effects on benthic scavengers of discards and damaged benthos produced by the beam-trawl fishery in the southern North Sea[END_REF]. We analysed a simple population model, derived from classic harvesting theory, to understand how subsidies depend on population growth rate (r) and carrying capacity (K), as well as on the frequency (f) and intensity (I) of perturbations. We describe the dynamics of a population density N with a simple logistic model:

𝑑𝑁 𝑑𝑡 = 𝑟𝑁 &1 - 𝑁 𝐾 * [1]
The population, initially at carrying capacity, is subjected to recurrent perturbations.

At a frequency f, a perturbation provokes the death of a fraction I of the population, which characterizes the intensity of the perturbation. This fraction is removed from N, and is considered as a subsidy. This leads to the following equation to characterize subsidy dynamics:

𝑆(𝑛𝑇) = 𝑁 !" (𝑛𝑇) * 𝐼 [START_REF] Polis | Extraordinarily high spider densities on islands: flow of energy from the marine to terrestrial food webs and the absence of predation[END_REF] with 𝑇 = 1 𝑓 ⁄ the time between two perturbations (period), n the number of the perturbation, and 𝑁 !" the biomass of the population at the time 𝑛𝑇 just before the perturbation. We analytically derived the solution of 𝑆(𝑛𝑇), the level of subsidy at equilibrium, and the conditions under which the system is not crashing.

Experimental design

Our general model showed that the amount of perturbation-induced subsidy produced locally is strongly dependent on the interaction between demography parameters (e.g., growth rate) and perturbation regime (e.g., intensity, see 'results' section below). We propose to test these predictions and their consequences at the landscape level. To do so, we built a factorial protist microcosm experiment composed of two-patch metaecosystems linked by different intensity of perturbation-induced subsidy pulse (0, 5%, 30%, 80%, thereafter referred to as diffusion treatment) and by species dispersal (with/without dispersal; see Fig. 1). We had four replicates of each treatment combination at the meta-ecosystem level, resulting in a total of 24 meta-ecosystems, each composed of two connected patches, and 4 unconnected controls (56 microcosms, see Fig. 1). The experiment lasted 21 days and took place in a controlled culture room at 20 °C and constant light. The position of replicate groups was randomized across the shelves in the culture room to control for possible micro-condition differences.

In order to study effects of subsidy exchanges between contrasting ecosystem types in a representative way, we built two-patch meta-ecosystems consisting of one heterotrophic protist community (ecosystem 1) and one autotrophic protist community (ecosystem 2).

The heterotrophic community was composed of four bacteriophagous ciliate protist species: Colpidium sp., Paramecium aurelia, Spirostomum sp., and Tetrahymena pyriformis. The autotrophic community was composed of the photosynthetic flagellate Euglena gracilis. This autotrophic species has a slow growth rate relative to most species in the heterotrophic community (except for Spirostomum sp.). These contrasting growth rates between the two ecosystems are essential to test the spatial consequences of our model predictions on the interaction between demography and perturbation intensity (see above). For details on culture conditions and experimental procedures, see [START_REF] Altermatt | Big answers from small worlds: a user's guide for protist microcosms as a model system in ecology and evolution[END_REF] and [START_REF] Carrara | Inferring species interactions in ecological communities: a comparison of methods at different levels of complexity[END_REF] .

Each microcosm consisted of a 250 mL Schott bottle filled to 100 mL. Microcosms were assembled by first filling each Schott bottle with 75 mL of pre-autoclaved standard protist medium (Carolina Biological Supply, Burlington NC, USA), and 5 mL of a bacteria solution composed of three species (Serratia fonticola, Bacillus subtilis and Brevibacillus brevis). After 24 hours, to allow time for bacteria growth, we added 20 mL of protist solution with each protist species at carrying capacity (5 mL per species for heterotrophic communities, and 20 mL of Euglena gracilis for autotrophic communities).

Thus, protist communities were added at 20% of their carrying capacity and were allowed to grow 24 hours before the first diffusion event.

Diffusion and dispersal procedures

For each diffusion level (0, 5%, 30%, and 80%), a corresponding volume (0, 5, 30, and 80 mL) was sampled from each microcosm and microwaved to turn living cells into detritus. After a 3 hours cooling period at ambient temperature (20 °C), the microwaved samples were poured into the respective neighbouring recipient ecosystems. Dispersal was unidirectional, from the autotrophic to the heterotrophic community, to test whether the introduction of an autotroph species could interact synergistically with subsidy diffusion and enhance microbial activity and ecosystem functioning. Dispersal was performed simultaneously with the diffusion procedure. It was done by sampling 5 mL (corresponds to an average of 1450 Euglena cells) from the autotrophic microcosm that was then poured directly into the heterotrophic microcosm of the corresponding metaecosystem. Because detritus and nutrient were also dispersed at the same time via the medium, the 5 mL was subtracted from the volume taken for subsidy diffusion from the autotrophic community. The logistical difficulty to disperse species without also diffusing medium (i.e., nutrient and detritus) did not permit having a 'no-diffusion with dispersal' treatment (see below for statistical implications and Fig. 1). The herein used dispersal rate (i.e., 5%) corresponds to levels of dispersal rates that have been successfully applied in related experiments (e.g., [START_REF] Altermatt | Interactive effects of disturbance and dispersal directionality on species richness and composition in metacommunities[END_REF][START_REF] Warren | Dispersal and destruction in a multiple habitat system: an experimental approach using protist communities[END_REF]), and is arguably an intermediate to high value even for many natural systems (e.g., [START_REF] Nichols | Dispersal. 1 edition[END_REF]). Experimentally, much lower dispersal rates (<0.01%) have been shown to significantly affect metacommunity dynamics (e.g., [START_REF] Declerck | Effects of patch connectivity and heterogeneity on metacommunity structure of planktonic bacteria and viruses[END_REF]).

Measurements

Measurements were synchronized with diffusion/dispersion procedures, with the measurements occurring every Tuesday (experimental days 0, 7, 14, 21) and Friday (experimental days 3, 10, 17), and diffusion/dispersion occurring every Wednesday and Saturday (see experimental calendar on Figure S1 in Online Supplementary Information).

The last diffusion event was performed on day 15 to allow ecosystems to reach near equilibrium by day 21 (last measurement), and thus to evaluate the long-term impacts of our different diffusion treatments without its mortality effect.

On each measurement day we quantified oxygen concentration, protist and bacteria densities in each microcosm. Oxygen concentration was measured using sensors that were mounted in the microcosm bottles at a medium depth of 2 cm. The information from the sensors was collected through an optical fiber cable connected to an oxygen meter device (PreSens Fibox 4 Optical Oxygen Meters, Germany) controlling for water pressure and temperature. On each measurement day, two 0.5 mL samples were taken:

one for protist and one for bacteria density analysis. Protist density was measured by using a standardized video procedure [START_REF] Altermatt | Big answers from small worlds: a user's guide for protist microcosms as a model system in ecology and evolution[END_REF][START_REF] Pennekamp | Implementing image analysis in laboratorybased experimental systems for ecology and evolution: a hands-on guide[END_REF]. In brief, a constant volume (17.6 µL) of each sample was placed under a dissecting microscope connected to a camera and a computer for the recording of videos (5 seconds per video). Then, using an image processing software (ImageJ, National Institute of Health, USA) we extracted the number of moving organisms per video frame along with a suit of different traits for each occurrence (e.g., speed, shape, size) that were used to filter out background movement noise (e.g., particles from the medium, [START_REF] Pennekamp | Implementing image analysis in laboratorybased experimental systems for ecology and evolution: a hands-on guide[END_REF][START_REF] Pennekamp | BEMOVI, software for extracting behavior and morphology from videos, illustrated with analyses of microbes[END_REF]). Finally, bacteria density was measured using standard flow cytometry on fresh SYBR green fixated cells using a BD Accuri TM C6 cell counter (1/1000 dilution, following [START_REF] Altermatt | Big answers from small worlds: a user's guide for protist microcosms as a model system in ecology and evolution[END_REF]).

Since detritus spatial flows were varying through time with species densities, we estimated the effective amount of detritus transferred from the autotroph ecosystem by simulating the logistic growth of Euglena from measured densities at each sampling day (~48 hours before each diffusion treatment). Parameters for the growth curve were extracted from control time series. We used the predicted numbers of Euglena individuals multiplied by the diffusion intensity as a proxy for realized subsidy (see also model description above, results section below, and the analysis of the general model).

Statistical analyses

To test for the reciprocal effects of cross-ecosystem subsidy exchanges on protist and bacteria densities, and ecosystem oxygen level, we first ran one generalized linear model (GLM) for each variable, testing for the main and interacting effects among all treatments and time. We used standardized residuals versus fitted values plots, residuals distribution, variance over-dispersion, and log-likelihood information to select the most appropriate variance and link functions for each GLM model (i.e., Gamma for oxygen concentration, and Gaussian on log-transformed data for bacteria and protist densities). The level of significance and the effect size of each factor and their interactions were then assessed using a standard F test (Type II analysis of deviance) on each GLM model. Finally, we used post-hoc pairwise comparisons (with Tukey adjusted p-values) on sub-models to extract the different contrasts of interest from significant terms in the main model. We used sub-models to avoid inflations of type II error [START_REF] Nakagawa | A farewell to Bonferroni: the problems of low statistical power and publication bias[END_REF] given the high number of potential pairwise comparisons in each main model. Because there was by definition no direct control for the dispersal effect (no dispersal only treatment, see Fig. 1), this treatment was removed from the main GLM models to avoid contrast imbalance. Instead, we tested for dispersal effects using log-response ratios for each diffusion level with 95% confidence intervals (see Fig. S2).

In a few microcosms we observed protist contaminations (e.g., Euglena individuals in heterotrophic communities without dispersal), though mostly occurring at low densities.

To account for these contaminations, and to ensure that they did not bias our results, we evaluated their impact on our analyses. We ran all of our GLM models with and without the contaminated microcosms (see Tables S1,S2, and S3). We show that retaining the replicates with contamination in the analysis did not affect the qualitative outputs of our models, and that in all cases they made our interpretations overall more conservative by increasing each model's residual variation. Therefore, we decided to retain all replicates in the main analyses.

All analyses were conducted with R 3.1.2 (R Development Core team, 2014), using the 'bemovi' package [START_REF] Pennekamp | BEMOVI, software for extracting behavior and morphology from videos, illustrated with analyses of microbes[END_REF] for video analyses, the 'car' package [START_REF] Fox | An R companion to applied regression[END_REF] for type II analysis of deviance, and the 'lsmeans' package for post hoc pairwise comparisons [START_REF] Lenth | lsmeans: Least-Squares Means[END_REF]. All data and the R code to reproduce our main results and figures are available on Dryad [START_REF] Harvey | Data from: Spatially cascading effect of perturbations in experimental meta-ecosystems[END_REF].

Results

Model

We examined how changes in perturbation intensity, frequency and specific demographic parameters (here intrinsic growth rate) can affect available subsidy levels.

We found that when a population has enough time to reach its carrying capacity between perturbations, the level of subsidy remains almost constant (e.g. top dynamics in Fig. 2b).

However, when the perturbations are too frequent, too intense, or the population too slow to recover, the population and subsidies decrease over time (Fig. 2b, dynamics "r-", "I+", "r-/I+"). We can demonstrate (see Appendix S1 in Supplementary Information) that, assuming initial density at carrying capacity (𝑁(0) = 𝐾), if the growth rate and perturbation regime satisfy the inequality:

𝑟𝑇 + 𝑙𝑛(1 -𝐼) > 0 [3],
the level of subsidies stabilizes to the following finite positive value:

𝐾𝐼 1 + 𝐼 > 1 1 -𝑎 -1@ [4], with 𝑎 = # !"#
$"% . The amount of subsidy at equilibrium (equation [START_REF] Murakami | Indirect effect of aquatic insect emergence on a terrestrial insect population through by birds predation[END_REF]) decreases with decreasing r and increasing f, and follows a hump-shaped relationship with I (Fig. 2c). If inequality [START_REF] Polis | Toward an integration of landscape and food web ecology: The Dynamics of Spatially Subsidized Food Webs[END_REF] is not satisfied, for instance with a combination of high perturbation intensity and low species growth rate, then both population and subsidies even tend to crash over time (Figs 2b "r-/I+" and 2c).

Experiment

We found contrasting effects of the diffusion treatment in heterotroph versus autotroph ecosystems on protist density (F(3,333) = 61.24, p<0.001, see Table S1 for full GLM table), and bacteria density (F(3,333) = 3.65, p<0.01, see Table S2 for full GLM table). In the autotroph ecosystems, Euglena gracilis, which is characterized by a slower growth rate than the bacteriophagous species in the heterotroph ecosystems, was slow to recover from each diffusion-induced mortality event, especially at high levels of diffusion (Fig. 3d).

The slow recovery at 80% diffusion level eventually resulted in a significant decline in population densities from the beginning to the end of the experiment (adjusted p-value <0.0001, Fig. 3d). As predicted by the model, this decline fed back along time on subsidies coming from autotroph ecosystems (Fig. 4c-f): At the beginning of the experiment (Fig. 4: Day 3), the 80% diffusion level generated a high amount of available subsidy (estimated dead Euglena cells) to the heterotroph ecosystems (Fig. 4c). In the heterotroph ecosystems, these subsidies sustained higher bacteriophagous protist densities (F(18,333) = 3.00, p<0.001, Fig. 4a, and see Table S4 for all post-hoc multiple comparison results), paralleled by a decrease in bacteria density (F(18,333) = 1.74, p<0.05, Fig. 4a, and Table S4). As a consequence of this increase in bacteria consumption, and potentially bacteria turnover rates, oxygen concentration declined along the diffusion gradient (F(18,333) = 1.69 p<0.05, Fig. 4b, and Table S4). Over time, however, Euglena's difficulty to recover from the repeated 80% mortality (Fig. 3d) led to a drop in detritus production that disrupted the amount of subsidies available to the heterotrophic ecosystems (Fig. 4f). As a consequence, by the end of the experiment (Fig. 4: Day 21), the intermediate 30% diffusion level provided more subsidies to the heterotrophic ecosystems than the 80% diffusion (Fig. 4f, adjusted p-values < 0.05) thus mirroring the model prediction of a hump-shaped relationship between perturbation intensity and detritus production. This resulted into a significant peak of bacteria densities at 30% (adjusted p-values<0.05, Fig. 4d, and Table S4) followed by a decline at 80% diffusion (adjusted p-value<0.05, Fig. 4d, and Table S4).

In contrast to initial dynamics (Fig. 4a), protist and bacteria densities were positively rather than negatively associated by the end of the experiment (Fig. 4d). This temporal change probably occurred because of an overall enrichment of the heterotroph communities at 30% compared to 80% diffusion, owing to Euglena photosynthesis over the course of the experiment. By the end of the experiment, and in the absence of recent diffusion-induced perturbations (we stopped the diffusion treatment 6 days before the last measurement -see "Methods" section), all heterotrophic and autotrophic ecosystems converged to similar oxygen concentrations (Fig. 4e). This convergence in oxygen level, in the absence of perturbations, likely developed because of similar overall biological rate averaging between Euglena producing oxygen, but sustaining high density of oxygenconsuming bacteria in autotroph ecosystems, and low level of bacteria but likely with high turnover due to higher level of protist density in heterotroph ecosystems.

The negative effect of diffusion-induced mortality on Euglena densities also meant that in treatments where it dispersed to heterotrophic ecosystems its density was systematically too low to have significant contributions on oxygen concentration or protist density at 80% diffusion level (see Fig. S2), however it did significantly contribute to increase protist density in heterotrophic ecosystems at low and intermediate diffusion levels (day 21 only, Fig. S2b).

Discussion

We experimentally showed how perturbation-induced cross-ecosystem subsidy exchanges affect the local biological communities of two connected ecosystems with contrasting demographic and natural history parameters. Our experimental results that perturbations can lead to a decline of subsidy over-time also matched the outcome of our theoretical model, which indicates that high levels of perturbations lead to collapsing subsidies after initial positive effects. Thus, we found first experimental evidences of meta-ecosystem effects on biological communities and ecosystem function (Figs. 3 and4), and of spatially cascading effect of perturbations via a disruption of spatial flows (Figs. 2,4).

Exploring theoretical scenarios, we first derived the general conditions under which local perturbations lead to the collapse of local detritus pool (Methods, eq. 4), disrupting regional dynamics through the flow of detritus. Similar dynamics have been studied in harvesting theory with a general focus on determining the optimal harvest effort (i.e., perturbation intensity and frequency) for a maximal profit [START_REF] Getz | Population harvesting: demographic models of fish, forest, and animal resources[END_REF]. Here we stress the indirect consequences of recurrent perturbations on connected ecosystems. In the particular context of global changes, perturbations that kill a part of populations (e.g., insect outbreaks, fires, storms) may occur in a more frequent or intense way [START_REF] Cai | Increasing frequency of extreme El Nino events due to greenhouse warming[END_REF]. Our model shows that this may decrease subsidies to other systems (e.g., litter inputs into rivers), the more severely as the intensity and frequency of the focal perturbations are increasing if populations are slow to recover. This change in subsidy levels may affect deeply the structure and functioning of the recipient community [START_REF] Verkaik | Fire as a disturbance in mediterranean climate streams[END_REF]. Previous empirical work had shown the importance of directional resource spatial flows between ecosystems for the maintenance of community structure and stability [START_REF] Polis | Extraordinarily high spider densities on islands: flow of energy from the marine to terrestrial food webs and the absence of predation[END_REF][START_REF] Bartels | Reciprocal subsidies between freshwater and terrestrial ecosystems structure consumer resource dynamics[END_REF][START_REF] Ward | HSS revisited: multi-channel processes mediate trophic control across a productivity gradient[END_REF]. However, the temporal feedbacks that can occur over time had only been investigated in theoretical terms, using the meta-ecosystem framework [START_REF] Marleau | Nutrient flows between ecosystems can destabilize simple food chains[END_REF][START_REF] Gounand | The paradox of enrichment in metaecosystems[END_REF][START_REF] Loreau | Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology[END_REF]. Thus, in a second step we experimentally demonstrated that meta-ecosystem dynamics have implications for natural ecosystems under perturbation pressure because the way neighbouring ecosystems respond can directly affect community dynamics and functioning in connected ecosystems. The link between subsidy flow and perturbations, however, was not trivial because the direction of the effect was completely reversed over time. Initially, the high level of diffusion-induced mortality in the autotrophic ecosystem generated a peak in available subsidy for the heterotrophic neighbour. By the end of the experiment, this high mortality level fed back to generate an overall impoverishment in subsidy exchange, which significantly impacted community composition and ecosystem dynamics in both ecosystems.

The analysis of the demographic mathematical model revealed the circumstances that can lead (or not lead) to the observed temporal feedback in detritus exchanges (Fig. 2). Slow species growth rates in a neighbouring ecosystem in combination with high perturbation frequency and intensity generated the conditions for a collapse of the amount of detritus exchanged over time (Fig. 2c bottom panel). For instance, slow-growing woody plants of riparian forests exposed to recurrent fires are progressively replaced by alien annuals of higher growth rates in Mediterranean areas [START_REF] Verkaik | Fire as a disturbance in mediterranean climate streams[END_REF][START_REF] Keeley | Alien plant dynamics following fire in mediterranean-climate california shrublands[END_REF]. Such high perturbation regimes will both deforest and re-structure the autotrophic riparian community towards a lower biomass system, and decline macro-invertebrate densities in streams by reducing leaf litter inputs [START_REF] Sweeney | Riparian deforestation, stream narrowing, and loss of stream ecosystem services[END_REF]. Here we show that, more generally, a habitat-or ecosystem-specific response to any kind of perturbations can strongly impact neighbouring ecosystems through the disruption of detritus flows.

Subsidy quality can also have important impacts on recipient ecosystems [START_REF] Greig | Warming, eutrophication, and predator loss amplify subsidies between aquatic and terrestrial ecosystems[END_REF][START_REF] Marleau | Emergence of nutrient co-limitation through movement in stoichiometric meta-ecosystems[END_REF][START_REF] Sitters | Spatial stoichiometry: cross-ecosystem material flows and their impact on recipient ecosystems and organisms[END_REF]. In our experiment, the autotrophic protist species was not only a key species because of its inability to recover from perturbation over time, but also because it could increase the total level of resource in each ecosystem through photosynthetic activities. Thus, spatial flows from autotroph ecosystems would have contained higher levels of resources than flows from heterotrophic ecosystems. Over time such a local enrichment would have increased the overall level of energy in the meta-ecosystems where autotrophs remained abundant (e.g., 30% as opposed to 80% diffusion). Therefore, the feedback between perturbation intensity and the slow recovery rate of autotrophs impoverished the metaecosystem under high perturbation pressure. This led to the observed change in the relationship between heterotrophic bacteria and protist density from initially negative to positive at the end. This interpretation also lead to the important, but yet untested hypothesis, that local species identity might play an essential role in mediating the quantity and quality of among-ecosystems spatial flows.

Our results have important implications for the management of human-altered landscapes because conservation targets, such as in forest or grasslands, are usually localized in their actions, focussing on the most sensitive habitats or ecosystems. Our findings show that these management-induced disturbances (or preventions thereof) can directly affect dynamics in spatially coupled ecosystems, such as rivers or lakes, which are fed by resources from these "green" ecosystems [START_REF] Bartels | Reciprocal subsidies between freshwater and terrestrial ecosystems structure consumer resource dynamics[END_REF][START_REF] Sitters | Spatial stoichiometry: cross-ecosystem material flows and their impact on recipient ecosystems and organisms[END_REF][START_REF] Richardson | Resource subsidies across the land-freshwater interface and responses in recipient communities[END_REF][START_REF] Collins | The importance of terrestrial subsidies in stream food webs varies along a stream size gradient[END_REF][START_REF] Soininen | Toward More Integrated Ecosystem Research in Aquatic and Terrestrial Environments[END_REF]. We experimentally demonstrated, and showed also in a mathematical model, that the direction of the effects depend on the temporal unfolding, the magnitude of disturbance and the type of connected ecosystems (autotrophic vs. heterotrophic dominated). Increasing dispersal rate by maintaining habitat connections can mitigate the deleterious effects of perturbation on local communities [START_REF] Tewksbury | Corridors affect plants, animals, and their interactions in fragmented landscapes[END_REF], however our results suggest that high perturbation pressure can hinder rescue effects when the dispersing populations are too slow to recover. Our study calls for a more integrative management that takes into account regional dynamics related to species and resource flows [START_REF] Haegeman | General relationships between consumer dispersal, resource dispersal and metacommunity diversity[END_REF], and spatial variations in ecosystem functions [START_REF] Staddon | Connectivity, non-random extinction and ecosystem function in experimental metacommunities[END_REF][START_REF] Allan | Using cultural ecosystem services to inform restoration priorities in the Laurentian Great Lakes[END_REF].

For instance, watershed conservation approaches could help to better integrate spatial flows within river networks [START_REF] Altermatt | Diversity in riverine metacommunities: a network perspective[END_REF], and a better understanding of spatial flows between forest and agricultural habitats would greatly improve agroforestry landscape management, maximizing the delivery of ecosystem services.

We have demonstrated that cross-ecosystem subsidy exchanges can have far-reaching implications for community dynamics and ecosystem processes beyond the generally well recognized one-way allochthonous input of detritus [START_REF] Polis | Extraordinarily high spider densities on islands: flow of energy from the marine to terrestrial food webs and the absence of predation[END_REF][START_REF] Polis | Toward an integration of landscape and food web ecology: The Dynamics of Spatially Subsidized Food Webs[END_REF]. The actual prevalence of meta-ecosystems in natural landscapes is currently unknown but evidences suggest that they might be ubiquitous to certain ecosystem boundaries [START_REF] Bartels | Reciprocal subsidies between freshwater and terrestrial ecosystems structure consumer resource dynamics[END_REF][START_REF] Altermatt | Diversity in riverine metacommunities: a network perspective[END_REF]. The feedback between demography, perturbations and changes in cross-ecosystem subsidy exchanges that we demonstrated here suggests that meta-ecosystem dynamics might be even more significant within fragmented and altered landscapes [START_REF] Largaespada | Meta-ecosystem engineering: Nutrient fluxes reveal intraspecific and interspecific feedbacks in fragmented mussel beds[END_REF]. Yet our empirical understanding of meta-ecosystems is strikingly insufficient, and more experiments are needed to fully understand the potentially complex feedbacks triggered by spatial flows that theory predicts [START_REF] Gounand | The paradox of enrichment in metaecosystems[END_REF][START_REF] Gravel | Source and sink dynamics in meta-ecosystems[END_REF][START_REF] Gravel | Patch dynamics, persistence, and species coexistence in metaecosystems[END_REF][START_REF] Marleau | Meta-ecosystem dynamics and functioning on finite spatial networks[END_REF], and to forecast how local perturbations can spread across space in spatially structured landscapes [START_REF] Harvey | Habitat loss and herbivore attack in recruiting oaks[END_REF][START_REF] Harvey | Spatially heterogeneous perturbations homogenize the regulation of insect herbivores[END_REF]. Figure 1. Each meta-ecosystem was composed of two ecosystems with contrasting protist communities: one heterotrophic (white background), and one autotrophic community (green background). The two microcosms within each meta-ecosystem were either linked by diffusion alone (movement of the brown compartment; brown line), or diffusion and dispersal (movement of the blue compartment; blue line). The diffusion of detritus was generated by a gradient of perturbation intensity (0, 5, 30, 80%) and occurred by reciprocal transfer of medium without living organisms. With four replicates per treatment combination, the experiment was composed of 24 meta-ecosystems and 4 unconnected pairs as controls for a total of 56 microcosms. P: protist community, B: bacteria community, D: detritus, R: resource.

• r I + • • ref • • I + 0 3 6 9 • • • • • • • ref. 0 3 6 9 • • • • • • • r 0 3 6 9 • • • • • • • I+ 0 50

Figure 2 .

 2 Figure2. Interaction between species dynamics, perturbations and subsidies. Results from a simple population model (defined in "Methods" section) showing (a) the changes in density (green solid lines) through time of a species having a logistic growth rate r, submitted to recurrent perturbations of intensity I at a frequency f. The intensity of the perturbation is defined as the proportion of species dying suddenly and turned into subsidies. Panel (b) shows examples of species (green solid lines) and subsidy (grey points) dynamics for different parameter sets. In the top dynamics ("ref.") the species can reach its carrying capacity between two perturbations and subsidies are constant. Other dynamics illustrate, from top to bottom, cases with a lower growth rate (r-), a greater perturbation intensity (I+), or both (r-/I+), compared to the top dynamics. Panel (c) show

  subsidies at equilibrium according to perturbation intensity I and for different growth rates r (blue colour refers to low growth rate while red to high ones). Points show the parameter couples used in panel (b). Values of parameters are: 𝐾 = 9; 𝑓 = 1/30; in panel (b) 𝑟 = {0.13,0.02,0.13,0.02} and 𝐼 = {0.3,0.3,0.7,0.7} from top to bottom; in panel (c) 𝐼 ∈ [0,0.99] and 𝑟 ∈ {0.01,0.02,0.05,0.07,0.09,0.11,0.13}.

Figure 3 .Figure 4 .

 34 Figure 3. Temporal dynamics for each diffusion level of protist densities in (a) heterotroph and (d) autotroph ecosystems, bacteria densities in (b) heterotroph and (e) autotroph ecosystems, oxygen concentration in (c) heterotroph and (f) autotroph ecosystems. Panels a, b, d and e are presented on a log-scale. Bars represent ± standard error for each experimental day. Dispersal and no dispersal treatments were lumped together to produce the figure

Acknowledgements

We thank the E.M.E.R.Ge research group for discussions and Stéphane Gounand for advices on mathematical demonstration. We thank two anonymous reviewers for comments on the manuscript. Funding is from the Swiss National Science Foundation Grant PP00P3_150698, University of Zurich and Eawag.

amount of detritus moved from the autotrophic to the heterotrophic ecosystem at the last diffusion procedure before sampling day 3 (c) and 21 (f). Panels (a) and (d) are presented on a log-scale. Bars represent ± standard error for each diffusion level.


Eric Harvey
email: eric.harvey@eawag.ch

Isabelle Gounand

Colette Ward

Florian Altermatt

Bridging ecology and conservation: from ecological networks to ecosystem function Running Head: From ecological networks to ecosystem function

Keywords: Ecological network, conservation biology, ecosystem functioning, global environmental change, meta-community, meta-ecosystem, spatial ecology, species interactions

1. Current approaches to conservation may be inadequate to maintain ecosystem integrity because they are mostly based on rarity status of organisms rather than functional significance. Alternatively, approaches focusing on the protection of ecological networks lead to more appropriate conservation targets to maintain ecosystem integrity.

2. We propose that a shift in focus from species to interaction networks is necessary to achieve pressing conservation management and restoration ecology goals of conserving biodiversity, ecosystem processes and ultimately landscape-scale delivery of ecosystem services.

3.

Using topical examples from the literature, we discuss historical and conceptual advances, current challenges, and ways to move forward. We also propose a road map to ecological network conservation, providing a novel ready to use approach to identify clear conservation targets with flexible data requirements.

Synthesis and applications.

Integration of how environmental and spatial constraints affect the nature and strength of local interaction networks will improve our ability to predict their response to change. This will better protect species, ecosystem processes, and the resulting ecosystem services we depend on.

Introduction -linking conservation science with 21 st century ecology

Conservation biology and restoration ecology are two modern research areas fostered by national park movements, wildlife conservation, and the broad international recognition of human impact on the planet that developed during the 20 th century (e.g.,

1987 Montreal protocol, and 1992 Rio De Janeiro convention on biodiversity). At the intersection between ecology and social sciences, conservation biology evolved as an independent science with its own body of scientific journals and communities. As an unintended consequence, there is now a significant divide between current concepts and knowledge in the field of ecology and the prescription of conservation measures and development of new policies. This schism has been noted [START_REF] Pulliam | Conservation ecology: bridging the gap between ecology and resource management[END_REF], and the gap is widening as the field of ecology has experienced significant conceptual and methodological paradigm shifts at the onset of the 21 st century which have yet to be integrated into conservation and restoration perspectives.

The objective of our forum article is to identify major conceptual advances from ecological science that could enhance our capacity to efficiently protect and predict diversity and ecosystem integrity in the face of global change. In light of recent developments in ecology we argue that addressing the gap between conservation management and ecology requires (i) a better integration of ecological networks as conservation target, which would, in turn, allow for better conceptual bridging toward (ii) the prediction of ecosystem-level supporting processes and emerging services (Fig. 1).

For each of these two points we identify challenges, illustrated by current examples, and suggest productive ways to move forward. Finally, we propose a step-by-step road map to ecological network conservation using a novel and ready-to-use tool to identify clear conservation targets.

From species to interaction networks

Current state of knowledge

In the context of increasing human population, reduction in habitable land owing to climate change, and increasing demand for food and goods production, the 'glass bell' approach to conservation, involving complete landscape protection through the creation of national parks, poses important spatial and societal challenges (Millenium Ecosystem Assessment, 2005). The often-perceived alternative to the more holistic park perspective is a species-level focus (Fig. 1). Protective legislation for rare or endangered species can be successful, however 'Noah's Ark' approaches are often costly and ineffective [START_REF] Laycock | Evaluating the costeffectiveness of conservation: The UK Biodiversity Action Plan[END_REF]. Moreover, this approach tends to be reactive and targets species based on rarity rather than functional significance, which can lead to significant resource allocation to a specific group of species or even a single species with limited return in terms of ecosystem integrity and functioning (e.g., Gotelli et al. 2012, discussing this in the context of resource-allocations to the presumably extinct ivory-billed woodpecker).

Frequent lack of resources for conservation management has led to the development of cost-effective trade-offs in conservation efforts [START_REF] Weitzman | The Noah's Ark problem[END_REF]. However, ranking conservation priorities among species or habitats is a complicated matter because such an assessment cannot be achieved without considering inter-dependencies among species owing to complex direct and indirect interactions [START_REF] Courtois | Conservation priorities when species interact: the noah's ark metaphor revisited[END_REF].

The integration of interdependent survival probabilities within conservation projects prioritization models has shown that taking species interactions into account can completely reverse conservation priorities [START_REF] Simianer | Accounting for non-independence of extinction probabilities in the derivation of conservation priorities based on Weitzman's diversity concept[END_REF]. However, to accurately rank conservation priorities, one would need predictions about which species or functional groups are most likely to respond to future changes, and how these changes would spread across the interaction network and affect other species (for an example see "a road map to ecological network conservation" section further below). The net effect of perturbations is not always intuitive, owing to different types of interactions (e.g., trophic, mutualistic)

and indirect links between species [START_REF] Tylianakis | Conservation of species interaction networks[END_REF]. For instance, the extinction of the butterfly Phengaris (Maculinea) arion in the UK resulted indirectly from the biocontrol of European rabbits (Oryctolagus cuniculus): the butterfly depended on the nest of the ant Myrmica sabuleti for the development of its larvae; Myrmica, in turn, depended on open areas supplied by rabbit grazing to establish their nests [START_REF] Thomas | Successful conservation of a threatened Maculinea butterfly[END_REF].

The study of species interactions has greatly improved our appreciation of the importance of network structure for ecological community stability, sensitivity to invasion, and extinction. For example, Pearse & Altermatt (2013a) analyzed regional extinctions in a trophic network of 900 Lepidoptera and 2403 potential host plant species in Central Europe. They reported that 8 of the 59 observed regional extinctions of Lepidoptera were associated with host-plant loss. Importantly, all 8 observed regional extinctions of Lepidoptera associated with host-plant loss occurred before the actual extinction of the host-plant. Thus, strong declines of host-plants can have cascading extinction effects on higher trophic levels before the plants actually go extinct, illustrating that interactions can be lost before any actual decline in species richness (plants persisted at low abundance). This illustrates that preserving keystone interactions, rather than species, can be a pro-active way to maintain ecosystem integrity in the face of global change instead of allocating resources to already endangered species. In a conservation biology context, the network structure, and more specifically the connectance (number of interactions per node), is also important with respect to which species are likely to be threatened: monophagous or strictly oligophagous Lepidoptera are significantly more often listed as "regionally extinct" or "critically endangered" than as "least concern", indicating that interaction networks may give a direct causal explanation for species' threat status (Pearse & Altermatt 2013a).

A possible further contribution of studies of pairwise species interactions for conservation management is a better understanding of biocontrol failure or potential indirect effects of novel trophic interactions on community structure, species invasions, and response to perturbations [START_REF] Russo | Patterns of introduced species interactions affect multiple aspects of network structure in plant-pollinator communities[END_REF][START_REF] Wood | Novel interactions between non-native mammals and fungi facilitate establishment of invasive pines[END_REF][START_REF] Alexander | Novel competitors shape species' responses to climate change[END_REF]. Among-species interactions can also be a powerful tool for predicting potential novel trophic interactions based on existing interactions in a straightforward manner (Pearse & Altermatt 2013b). For instance, the integration of 459 non-native plants into the diet of 900 native, Central European lepidoptera could be accurately predicted by a simple model based only on the interactions of lepidoptera with their native hosts as well as a plant phylogeny (Pearse & Altermatt 2013b). Some of the observed, and accurately predicted, novel trophic interactions between native plant hosts and lepidopteran herbivores also included species of agricultural or forestry significance, such as extensions of the Tussock moth (Calliteara pudibunda) larval diet to the non-native red oak (Quercus rubra) or sesiid moth Synanthedon tipuliformis larval diet to a non-native, introduced gooseberry species (e.g., Ribes aureum). If such among-species interactions are ignored, natural enemies could potentially fail to control important agricultural pests, for instance the green peach aphid (Myzus persicae) has devastated potato fields [START_REF] Straub | Species identity dominates the relationship between predator biodiversity and herbivore suppression[END_REF], despite efforts to increase natural enemies abundance and diversity.

Moreover, introduced non-native biocontrol agents can have non-target indirect effects despite high host-specificity. For instance gall flies (Urophora affinis and U.

quadrifasciata), introduced in North America to control the expansion of knapweeds (Centaurea maculosa and C. diffusa), failed in their biocontrol role but became superabundant and subsidized populations of the generalist deer mouse (Peromyscus maniculatus), which in turn triggered several declines of native plants, insects and small mammals [START_REF] Pearson | Indirect effects of host-specific biological control agents[END_REF].

Caveats and future perspective

Unfortunately, despite these important contributions, early ecological network studies did not produce general principles for the organization and dynamics of natural communities, largely because they did not consider the environmental context in which these interactions occur [START_REF] Mcgill | Rebuilding community ecology from functional traits[END_REF]. However, recent conceptual developments in community ecology have successfully integrated biotic interactions within both their local environment and their spatial context [START_REF] Leibold | The metacommunity concept: a framework for multi-scale community ecology[END_REF]). During the same period, the field of biogeography began to question the use of species-specific climatic envelopes for predicting species range-shifts following climate change, acknowledging that species do not migrate into empty vacuums but rather into established, complex and diverse biotic communities [START_REF] Pearson | Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?[END_REF]. Thus, there is now compelling evidence from both biogeography [START_REF] Araújo | The importance of biotic interactions for modelling species distributions under climate change[END_REF] and meta-community research that local biodiversity strongly depends on interactions occurring at local and regional scales. For instance Pillai and colleagues (2011) demonstrated that complex food webs can persist in a structured landscape on a single basal resource, even though local coexistence would be impossible.

One of the greatest impediments to a broader development of ecological network research in conservation sciences is the challenge to construct accurate and meaningful interaction networks [START_REF] Morales-Castilla | Inferring biotic interactions from proxies[END_REF]. Complete species networks are rare and prone to resolution issues because they are often built over many years and integrate information from many contrasting sources (e.g. expert knowledge, gut contents, cooccurrence data). The problem with these time-and resource-consuming methods is that they can lead to false negatives (missing links that are important), overestimation of the importance of some links, or even -and most importantly -to false positives (hypothesized links that are not realized) when assuming interactions based on simple cooccurrences [START_REF] Morales-Castilla | Inferring biotic interactions from proxies[END_REF]. This is problematic because it means that most species network knowledge has been produced from a small subset of nonreproducible networks. Moreover, these traditional methods are not amenable to construction of interaction networks beyond food webs, resulting in historical bias towards the study of antagonistic interactions (Morales-Castilla et al. 2015), despite increasing awareness of the importance of mutualistic and facilitation interactions for the maintenance of diversity and ecosystem processes [START_REF] Bascompte | Mutualistic networks[END_REF].

There is also a need for development of new and more accurate process-based experimental and empirical knowledge. Recent breakthroughs have shown that the qualitative nature (competitive, predator-prey, mutualistic) and quantitative strength of species interactions can change in space as a function of local conditions [START_REF] Poisot | The dissimilarity of species interaction networks[END_REF]. For instance, stress gradients can modify the net balance between competition and facilitation, with competition dominating in low stress habitats and facilitation dominating in high stress habitats [START_REF] Lortie | Re-analysis of meta-analysis: support for the stressgradient hypothesis[END_REF]. This has obvious implications for the study of species range shifts along environmental degradation gradients (e.g., climatic, drought) because increasing positive interactions at each end of the gradient could support better persistence rates than previously predicted. However our mechanistic understanding of how the nature and strength of these interactions change as a function of environmental context remains shockingly anemic [START_REF] Poisot | The dissimilarity of species interaction networks[END_REF]). In the context of increased frequency of perturbations and landscape alterations, we also need to understand mechanistically how multiple perturbations spread through local networks [START_REF] Tylianakis | Conservation of species interaction networks[END_REF]. In a recent study, [START_REF] Harvey | Spatially heterogeneous perturbations homogenize the regulation of insect herbivores[END_REF] showed how regional landscape fragmentation and local fertilization in grasslands interact to homogenize insect herbivore regulation. This unfolded because fragmentation reduced predator abundance, while both fragmentation and fertilization altered host plant diversity. These effects led to a significant increase in bottom-up constraints, facilitating a reduction in insect diversity and regional dominance by a few Hemipteran herbivore generalists (mainly Miridae family). Most importantly, the study demonstrated that these perturbation effects on insect herbivores were entirely mediated by bottom-up and topdown trophic interactions, suggesting that herbivores themselves would be the wrong target to mitigate effects of landscape alteration. For these purposes, accessible methods have been recently proposed to measure interaction strengths within controlled laboratory experiments [START_REF] Carrara | Inferring species interactions in ecological communities: a comparison of methods at different levels of complexity[END_REF], and the use of molecular toolkits (e.g., stable isotopes, eDNA) promise an exciting future for the generation of in situ new empirical data beyond species level information [START_REF] Smith | Barcoding a quantified food web: crypsis, concepts, ecology and hypotheses[END_REF].

From ecological network conservation to ecosystem functioning

Recent evidence that interactions can be lost at a quicker pace than species following environmental degradation, for instance through the local extinction of host plants (Pearse & Altermatt 2013a) or through the desynchronization of species activity periods [START_REF] Visser | Shifts in phenology due to global climate change: the need for a yardstick[END_REF], is concerning because it demonstrates that essential functions performed by species (e.g., pollination, herbivore regulation) can be lost despite species remaining present in a system [START_REF] Valiente-Banuet | Beyond species loss: the extinction of ecological interactions in a changing world[END_REF]. For instance, many insectivorous birds, such as the great tit (Parus major), hatch in synchrony with the emergence of high-protein insect prey necessary to sustain youngling development (Fig. 2b). Earlier springs and longer growing seasons due to climate change generate a mismatch between hatching time of the great tit and its prey emergence, leading to a decrease of the number and fitness of fledged chicks [START_REF] Visser | Shifts in caterpillar biomass phenology due to climate change and its impact on the breeding biology of an insectivorous bird[END_REF]. Despite the presence of both prey and predator, the interaction can be weakened, and even disappear, with phenological mismatches. This may have cascading negative effects on ecosystem functions, such as herbivory control, and services, for instance if the resource of herbivores is of agricultural interest (Figs. 2a,2c). It also means that the common practice of monitoring species richness as a surrogate for ecosystem integrity or functioning is not always relevant, especially under a high level of extinction debt.

Interactions can be lost, but novel interactions can also emerge with equally important consequences for the maintenance of diversity and ecosystem processes (Pearse & Altermatt 2013b).

There is now good evidence that species interactions vary in space independently of species composition because the same co-occurring species do not always interact, while different species can all share the same type of interactions [START_REF] Poisot | The dissimilarity of species interaction networks[END_REF]. This suggests that interactions themselves can trump species identity, and that eventually the main driver of community structure and ecosystem processes is the spatial build up and arrangement of interaction diversity, identity, and strength [START_REF] Pillai | Metacommunity theory explains the emergence of food web complexity[END_REF]). Therefore at the ecosystem process level, what matters are the interactions, rather than the species, we lose from the system.

The main logical implication of spatial variation in biotic interactions is that ecosystem processes likely vary across the landscape, resulting in spatial variation in the provision of ecosystem functions and services [START_REF] Nelson | Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales[END_REF][START_REF] Steffen | Planetary boundaries: Guiding human development on a changing planet[END_REF].

The causes of these variations in ecosystem functions are not yet well understood, however spatial connections between ecosystems through consumer coupling of habitats and the exchange of living (dispersal) and dead organisms (detritus, resources) certainly affect local interactions [START_REF] Loreau | Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology[END_REF]. Indeed, theoretical work using the meta-ecosystem framework recently demonstrated that structural attributes of a species interaction network in one ecosystem can have important effects on diversity and functioning of neighbouring ecosystems through direct dispersal or indirect energy and material flux [START_REF] Loreau | Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology[END_REF]. For example, in the Palmyra Atoll, the translocation of pelagic nutrients to otherwise oligotrophic coastal waters is facilitated by native trees Pisonia grandis and Tournefortia argentea, which are preferred nesting and roosting habitat for pelagic-foraging marine birds. This nutrient conveyer belt is thus disrupted by the replacement of native trees with cultivated coconut palm Cocos nucifera [START_REF] Mccauley | Long ecological interaction chains in less-disturbed ecosystems[END_REF]. Relative to Cocos stands, forest patches dominated by Pisonia and Tournefortia have greater marine bird abundance, greater soil and foliar nitrogen (attributed to bird guano), which are associated with greater nitrogen runoff into coastal waters, which is in turn associated with enhanced phytoplankton, zooplankton, and finally planktivorous manta ray (Manta birostris) abundance. Taking into account the potential impacts of reciprocal effects between ecosystems due to spatial flux may help predict how species interactions change with local environmental variation, possibly induced by anthropogenic perturbations. This should explain, at least in part, the wide spatial variation in ecosystem processes observed among naturally connected ecosystems [START_REF] Altermatt | Diversity in riverine metacommunities: a network perspective[END_REF], or heterogeneous landscapes such as agricultural mosaics. For instance, in the deciduous boreal forest organic matter is exported to otherwise nutrient-poor, lowproductivity lakes [START_REF] Tanentzap | Forests fuel fish growth in freshwater deltas[END_REF]. This subsidy enhances biomass in a food chain leading from bacteria to zooplankton and ultimately yellow perch (Perca flavescens), a species of commercial and recreational value. The subsidy is disrupted by timber harvesting as the resultant reduced vegetation and poorly developed soils supply less organic matter to downstream lakes. Such effect of forest harvesting on riverine zooplankton may have spatially cascading effects on biotic interactions downstream (see Fig. 3), which ultimately may cause nutrient loadings and boosts of algal growth, resulting in loss of important ecosystem services (see Fig. 3).

Moving from a species to an interaction network perspective is necessary to understand how global change will affect biodiversity [START_REF] Mccann | Protecting biostructure[END_REF] and will also offer a pro-active alternative targeting keystone interactions based on functional significance rather than the current, necessary, but more reactive approach to conservation. Targeting keystone interactions will therefore provide a much better proxy and predictor of ecosystem processes [START_REF] Tomczak | Ecological network indicators of ecosystem status and change in the baltic sea[END_REF][START_REF] Schleuning | Predicting ecosystem functions from biodiversity and mutualistic networks: an extension of trait-based concepts to plant-animal interactions[END_REF][START_REF] Creamer | Ecological network analysis reveals the inter-connection between soil biodiversity and ecosystem function as affected by land use across Europe[END_REF].

A road map to ecological network conservation

Despite the above-discussed conceptual and logistical advances, it remains unclear how network conservation should take form in practice: which specific metrics should be measured, and which current management tools could help to restore or protect ecological networks [START_REF] Tylianakis | Conservation of species interaction networks[END_REF][START_REF] Hagen | 2 -Biodiversity, species interactions and ecological networks in a fragmented world[END_REF])? The use of interaction networks in management remains in its infancy, hindered by the technical and scientific caveats highlighted above, frequent lack of localized abundance and interaction data, and gaps in mechanistic understanding of how interactions change across local contexts.

Here, given the state of current knowledge, we demonstrate a novel approach to ecological network conservation allowing for a direct stability assessment of the community and the identification of clear conservation targets to maintain it. We address questions related to the minimum amount of information needed, how to build the network, which metrics to measure and how, and then briefly discuss possible management tools. In its simplest implementation the technique is suitable for data-poor systems; as localized data become available and as mechanistic underpinnings of context dependencies become better understood, it will become possible to use interaction networks (or this technique) in management within spatially explicit contexts, integrating ecological network data that can be used to gain essential information to build similar ecological networks [START_REF] Poisot | mangal -making ecological network analysis simple[END_REF]. For conservation purposes, these new developments allow access to the "gold mine" that represents the vast collection of currently available empirical datasets previously considered ill-suited or insufficiently complete for network studies. The construction of interaction networks using time series or spatially explicit large datasets will allow direct testing of how interaction networks are qualitatively and quantitatively affected by land use changes, perturbations, and which network attributes hold the most important predictive value; all essential and previously unavailable keys for the implementation of network approaches in conservation science.

Identifying conservation targets

Many network metrics are known to be important for ecological community stability, however it remains unclear how these are affected by sampling effort and perturbations; furthermore, measuring these metrics often requires extensive knowledge of species interactions [START_REF] Martinez | Artifacts or Attributes ? Effects of resolution on the Little Rock lake food web[END_REF][START_REF] Tylianakis | Conservation of species interaction networks[END_REF]. Instead, and until more information is available, we propose to extend the already well proven and extensively used keystone species concept [START_REF] Paine | A conversation on refining the concept of keystone species[END_REF][START_REF] Jordán | Keystone species and food webs[END_REF]) by defining it here as the interactions between two species with the strongest impacts on community stability following their removal.

The advantage of using keystone interactions is that it provides clear conservation targets, in contrast to other holistic but more diffused metrics (e.g. protecting network connectance). Moreover, identifying keystone interactions can be achieved easily with a directed network without prior knowledge of interaction strengths (see proof of concept in Fig. 4). Starting with a simple adjacency matrix composed of 1 (interaction) and 0 (no interaction, see Fig. 4b) we use a recently developed bootstrapping method to evaluate changes in network structural stability after removing each interaction sequentially (with replacement, based on [START_REF] Tang | Correlation between interaction strengths drives stability in large ecological networks[END_REF][START_REF] Tang | Correlation between interaction strengths drives stability in large ecological networks[END_REF][START_REF] Sauve | How plants connect pollination and herbivory networks and their contribution to community stability[END_REF], see Appendix 1 in Supporting Information for a detailed description and a ready-to-use annotated R code to perform the analysis). We propose a two-step approach to identify conservation targets in ecological networks: (i) each pairwise interaction is ranked based on its effect on network structural stability. This step provides information on which pairwise interactions need specific attentions from managers (see Fig. 4c). (ii) Sensitive species that are likely to go extinct following the removal of their prey (e.g. specialist consumers), potentially leading to cascading extinctions, are identified (Fig. 4c). This step provides managers with the identity of especially sensitive network nodes.

Therefore, together these two steps lead to clear conservation targets for the holistic protection of both network structure and stability (Fig. 4d). Importantly, in Fig. 4 we document an example for consumptive interactions, however the technique is readily applicable to other types of interactions (e.g. mutualisms, see Appendix 1 for more details on how to proceed).

Management tools

Once keystone interactions and sensitive nodes are identified, the main issue is to efficiently achieve their protection. Based on current knowledge, we suggest that the main lever to restore or conserve ecological network structure and stability is the management of spatial configuration. Extensive research on effects of habitat loss and fragmentation on ecological networks [START_REF] Hagen | 2 -Biodiversity, species interactions and ecological networks in a fragmented world[END_REF] suggests that re-thinking the spatial configuration of reserve networks is paramount to ecological network conservation [START_REF] Hamilton | Incorporating biogeography into evaluations of the Channel Islands marine reserve network[END_REF][START_REF] Spiecker | Reciprocal feedbacks between spatial subsidies and reserve networks in coral reef meta-ecosystems[END_REF]. Specific recommendations on spatial management for ecological network conservation are beyond the scope of this work, but we believe that despite a growing interest there is still a great need for research on the subject (for an extensive review see [START_REF] Hagen | 2 -Biodiversity, species interactions and ecological networks in a fragmented world[END_REF].

Back to conservation

Protecting ecosystem integrity and species diversity is at the core of all conservation or restoration management actions. However, current rates of biodiversity loss speak volumes to the current failures and future challenges in targeting appropriate conservation priorities. In this context, it is important to question some of our basic assumptions about classical conservation approaches. Here we argue that the maintenance of biodiversity and ecosystem integrity are hypothesized rather than realized by species-specific and integral land conservation approaches (Fig. 1a). Instead, evidence suggests that changes in the nature and diversity of biotic interactions directly explain patterns of diversity and ecosystem function. In this context, we propose that a shift in focus from species to interaction networks is necessary to achieve pressing conservation management and restoration ecology goals of conserving biodiversity and the delivery of ecosystem services (Fig. 1b).

Ecosystems provide benefits to humans via a myriad of provisioning, cultural, and regulating services, which are all maintained by supporting ecosystem processes. Recent global indicators suggest that we have likely crossed the 'safe operating space' for many biogeochemical cycles directly related to these services. In light of current knowledge, global biodiversity loss and associated erosion of ecosystem processes are likely to lead to sudden collapses in the provision of several essential services. Here, we focus on current challenges to advance ecological sciences. Future research should also focus on fostering a better integration of social, economic, and ecological sciences, which constitutes the only way toward a unified framework to maintain ecosystem service provision [START_REF] Consortium | Networking our way to better ecosystem service provision[END_REF]. The Millennium Ecosystem Assessment (2005) called for a change of perspective that yet needs to be fully implemented; now is the time to do so.

Figures

Figure 1. (a) Interaction networks drive ecosystem processes, which in turn determine the provision of ecosystem services. For instance, (b) some bird species feed on insects, while caterpillars supply protein-rich food for their offspring; this regulation of herbivores ensures good fruit production. However, (c) global warming may shift species phenology and caterpillar abundances may peak before eggs hatch. Although all species would remain present (no change in species richness), birds would no longer regulate caterpillars. This interaction loss may impact fruit production. For instance, (a) litter inputs from riverine forest supply food for bacteria, supporting high zooplankton abundance. This, in turn, enables zooplankton to regulate fast-growing algae (in green), whose abundance is boosted by agricultural fertilizer leachate. In this scenario, ecosystem services are maintained via spatial feedbacks of resource flows on species interactions. However, (b) if the forest is cut, algae escape zooplankton regulation owing to low bacterial density (attributable to disruption of litter input), potentially leading to eutrophication and ecosystem service loss. Figure 4. Identifying conservation targets in networks. Based on a hypothetical food web we describe how the loss of interactions affects stability of communities, and give a workflow of how conservation can identify and target such key interactions. Panel (a) illustrates a hypothetical food web composed of species A to Q, with arrows representing consumption links going from the resource to the consumer species. Panel (b) shows the corresponding adjacency matrix, with black squares representing interactions with species in rows consuming species in columns. Panel (c) shows the change in structural community stability (resilience to perturbation) which occurs when each interaction is set to 0. Interactions are ranked on the X-axis from those having the largest positive effect (green colours) to those having the largest negative effect (red colours) on structural stability when removed. The blue arrows indicate ultra specialist species, which would go extinct following the loss of their prey (i.e., cascading extinctions). The number below each arrow represents the number of species expected to go extinct. In panel (d) we illustrate the interaction ranking from panel (c) with each arrow's colour giving the expected change in network stability following a loss of an interaction.

A B C D E F G H I J K L M N O P Q A B C D E F G H I J K L M N O P Q Resources Consumers • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Link removed % Change in structural stability L D O I G B P M Q J L G M J O K P I N J Q H H B Q K F D N K H D K G I E K F Q N F B O L Q L E A J F Q M Q O Q G N F L H E B G D J E K E F C A B C D H G F E K L J I O N M Q P A B C D H G F E K L J I O N M Q P (a) (b) (c) (d)

  Figure1. A New focus in conservation biology. (a) Current conservation approaches focus on protecting lands (national parks) or individual species of iconic value or hypothesized key role (umbrella species). These approaches assume implicit protection of ecosystem processes or biological communities, which may or may not be realized. (b) We propose that future conservation efforts focus on protecting ecosystem processes and interaction networks per se, with explicit positive effects on habitats and biodiversity. Thereby, both ecosystem services (ultimate value) and the diversity of habitats and species (proximate values) are maintained.

Figure 2 .

 2 Figure2. From interactions to ecosystem services. (a) Interaction networks drive ecosystem processes, which in turn determine the provision of ecosystem services. For instance, (b) some bird species feed on insects, while caterpillars supply protein-rich food for their offspring; this regulation of herbivores ensures good fruit production. However, (c) global warming may shift species phenology and caterpillar abundances may peak before eggs hatch. Although all species would remain present (no change in species richness), birds would no longer regulate caterpillars. This interaction loss may impact fruit production.

  Figure3. Resource flows and spatial feedbacks. Interaction networks (circles and black arrows) are influenced by spatial flows of resources (brown arrows). For instance, (a) litter inputs from riverine forest supply food for bacteria, supporting high zooplankton abundance. This, in turn, enables zooplankton to regulate fast-growing algae (in green), whose abundance is boosted by agricultural fertilizer leachate. In this scenario, ecosystem services are maintained via spatial feedbacks of resource flows on species interactions. However, (b) if the forest is cut, algae escape zooplankton regulation owing to low bacterial density (attributable to disruption of litter input), potentially leading to eutrophication and ecosystem service loss.

Acknowledgements

We would like to thank C. Lortie, A. Sauve, E. Thébault and the E.M.E.R.Ge research group for enlightening discussions, and D. Bohan and one anonymous reviewer for comments that improved our manuscript. EH, IG, and FA acknowledge funding from the Swiss National Science Foundation Grant PP00P3_150698, University of Zurich and Eawag.

local context dependencies and quantitative interactions to accurately predict and prevent the consequences of perturbations such as species invasion, habitat fragmentation or climate change.

Building ecological networks

Quantifying interaction strength between each pair of species in an ecological network is too laborious and costly for most managers. Thus, the general ecology motto "the more the better" does not agree well with time and resource constraints associated with conservation management. It is, however, reasonable to assume that most conservation plans already include some kind of biodiversity survey. Therefore, a species list associated with qualitative or quantitative functional trait information as well as information on each species' overall occurrence, is often readily available at low cost, and constitutes the minimum information necessary to build an ecological network.

Simplifying the process of building ecological networks remains a work in progress.

Fortunately, the recent resurgence of interest in interaction networks has triggered new methodological developments toward this goal. Perhaps most promising and exciting is the use of inferential methods based on likelihood estimators (i.e. maximum likelihood or Bayesian) which allow for the flexible integration of prior knowledge and measurement error estimation [START_REF] Grace | Guidelines for a graph-theoretic implementation of structural equation modeling[END_REF][START_REF] Hooten | A guide to Bayesian model selection for ecologists[END_REF], and machine learning, which facilitates the construction and validation of food webs using algorithms [START_REF] Bohan | Automated discovery of food webs from ecological data using logic-based machine learning[END_REF][START_REF] Tamaddoni-Nezhad | Chapter Four -Construction and validation of food webs using logic-based machine learning and text mining[END_REF]. These approaches, mixed with available functional traits, phylogenetic, and co-occurrence data, can generate accurate, standardized, and highly reproducible networks (for a promising example see [START_REF] Morales-Castilla | Inferring biotic interactions from proxies[END_REF]. Furthermore, publically available platforms already compile