The ecological consequences of biodiversity loss have aroused considerable interest and controversy during the past decade. Major advances have been made in describing the relationship between species diversity and ecosystem processes, in identifying functionally important species, and in revealing underlying mechanisms. There is, however, uncertainty as to how results obtained in recent experiments scale up to landscape and regional levels and generalize across ecosystem types and processes. Larger numbers of species are probably needed to reduce temporal variability in ecosystem processes in changing environments. A major future challenge is to determine how biodiversity dynamics, ecosystem processes, and abiotic factors interact.

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Interactions between biotic and abiotic processes complicate the design and interpretation of ecological experiments. Separating causality from simple correlation requires distinguishing among experimental treatments, experimental responses, and the many processes and properties that are correlated with either the treatments or the responses, or both. When an experimental manipulation has multiple components, but only one of them is identified as the experimental treatment, erroneous conclusions about cause and effect relationships are likely because the actual cause of any observed response may be ignored in the interpretation of the experimental results. This unrecognized cause of an observed response can be considered a "hidden treatment." Three types of hidden treatments are potential problems in biodiversity experiments: (1) abiotic conditions, such as resource levels, or biotic conditions, such as predation, which are intentionally or unintentionally altered in order to create differences in species numbers for "diversity" treatments; (2) non-random selection of species with particular attributes that produce treatment differences that exceed those due to "diversity" alone; and (3) the increased statistical probability of including a species with a dominant negative or positive effect (e.g., dense shade, or nitrogen fixation) in randomly selected groups of species of increasing number or "diversity." In each of these cases, treatment responses that are actually the result of the "hidden treatment" may be inadvertently attributed to variation in species diversity. Case studies re-evaluating three different types of biodiversity experiments demonstrate that the increases found in such ecosystem properties as productivity, nutrient use efficiency, and stability (all of which were attributed to higher levels of species diversity) were actually caused by "hidden treatments" that altered plant biomass and productivity.

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If plants cannot simultaneously acclimate to shade and drought because of physiological trade‐offs, then plants are expected to be less tolerant to shading under drier conditions. One observation that, at first sight, seems incompatible with this idea is the fact that the establishment of new plants in dry areas is often restricted to shady sites under the canopy of other plants, called “nurse plants.” We use a graphical model to resolve this paradox. The model visualizes how facilitative patterns can be understood from the simultaneous effects of plant canopies on microsite light and moisture, and the growth responses of establishing seedlings to those factors. The approach emphasizes the fact that positive and negative effects of plant canopies always occur simultaneously. In the presented light–water model, facilitation only occurs when the improvement of plant water relations under the canopy exceeds the costs caused by lower light levels. This may be true under dry conditions, whereas in less dry situations, competition rather than facilitation is observed. The model shows how changes in water availability may shift interactions from competitive to facilitative and vice versa, as observed in some field patterns. It is argued that other environmental factors explaining facilitative patterns can be understood in the same context.

In plant-pollinator communities many pollinators are potential generalists and their preferences for certain plants can change quickly in response to changes in plant and pollinator densities. These changes in preferences affect coexistence within pollinator guilds as well as within plant guilds. Using a mathematical model, we study how adaptations of pollinator preferences influence population dynamics of a two-plant-two-pollinator community interaction module. Adaptation leads to coexistence between generalist and specialist pollinators, and produces complex plant population dynamics, involving alternative stable states and discrete transitions in the plant community. Pollinator adaptation also leads to plant-plant apparent facilitation that is mediated by changes in pollinator preferences. We show that adaptive pollinator behavior reduces niche overlap and leads to coexistence by specialization on different plants. Thus, this article documents how adaptive pollinator preferences for plants change the structure and coexistence of plant-pollinator communities.

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