<p class="first" id="d5663264e297">Knowledge of species composition and their interactions,
in the form of interaction
networks, is required to understand processes shaping their distribution over time
and space. As such, comparing ecological networks along environmental gradients represents
a promising new research avenue to understand the organization of life. Variation
in the position and intensity of links within networks along environmental gradients
may be driven by turnover in species composition, by variation in species abundances
and by abiotic influences on species interactions. While investigating changes in
species composition has a long tradition, so far only a limited number of studies
have examined changes in species interactions between networks, often with differing
approaches. Here, we review studies investigating variation in network structures
along environmental gradients, highlighting how methodological decisions about standardization
can influence their conclusions. Due to their complexity, variation among ecological
networks is frequently studied using properties that summarize the distribution or
topology of interactions such as number of links, connectance, or modularity. These
properties can either be compared directly or using a procedure of standardization.
While measures of network structure can be directly related to changes along environmental
gradients, standardization is frequently used to facilitate interpretation of variation
in network properties by controlling for some co-variables, or via null models. Null
models allow comparing the deviation of empirical networks from random expectations
and are expected to provide a more mechanistic understanding of the factors shaping
ecological networks when they are coupled with functional traits. As an illustration,
we compare approaches to quantify the role of trait matching in driving the structure
of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized
by null models and hypothesis-based metaweb. Overall, our analysis warns against a
comparison of studies that rely on distinct forms of standardization, as they are
likely to highlight different signals. Fostering a better understanding of the analytical
tools available and the signal they detect will help produce deeper insights into
how and why ecological networks vary along environmental gradients.
</p>