4. Discussion
This study first revealed the new knowledge about the development mode
of ecosystem-level productivity over the NH in the first decade of this
century, e.g., the productivity of the LEP- and HEP-kind ecosystems
behaving with weaker tendencies of increasing than that of the whole NH
ecosystem. Actually, it is hard to acquire such properties of the LEP
and HEP ecosystems in the traditional ecology. In addition to such brief
rules of EP trends, more EP characteristics were also derived in
details. For the NA, its middle-latitudes performed with comparable EP
development modes between its LEP (0.15 year-1), AEP
(0.15 year-1), and HEP (0.14 year-1)
ecosystems, but its high-latitudes exhibited a distinctive mode – LEP
(0.05 year-1) weaker than AEP (0.16
year-1), far weaker than HEP (0.20
year-1). This meant that the components of the
middle-latitude ecosystems in the NA had relatively similar modes in
productivity increasing, but the ecosystem components at the
high-latitudes behaved in a different mode –in productivity increasing
the LEP ecosystems were weak whereas the HEP ecosystems were strong. For
the NE, its middle- and high-latitudes demonstrated the comparative EP
development modes but slightly weaker and stronger amplitudes between
the LEP, AEP, and HEP ecosystems (0.28 vs. 0.36
year-1; 0.30 vs. 0.39 year-1; 0.27
vs. 0.35 year-1, respectively). North Europe and North
Asia performed with discrepant development modes for the EP of the LEP,
AEP, and HEP ecosystems (0.25 vs. 0.34 year-1; 0.26
vs. 0.37 year-1; 0.25 vs. 0.34
year-1), a little like the opposites of the middle-
and high-latitudes of NE. In a whole sense, in EP development the NE
region was not only more intense but also more consistent than the NA.
We found that the development of the Arctic circumpolar EP can be
statistically attributed to the inter-annual variations of SP, and this
gave a confirming answer to the first question. Our results pointed that
the INDVI-characterized EP was more closely associated to snow-onset
than -end SP. Three potential mechanisms, in terms of light
(temperature), nutrient, and water as the three kinds of fundamental
resources required by all plants, might account for these results.
First, compared to snow-end SP, snow-onset SP is more indicative to its
insulation capacity, which may decide the temperatures experienced by
soils and plants during winter (Sturm et al., 1997) and further
influences ecosystem productivity in the growing season (Billings &
Bliss 1959), as evidenced by that altered snow density may affect plant
growths (Rixen et al., 2008). Second, compared to snow-end SP,
snow-onset SP is more related with its thickness and cover. In some
cases, increased snow covers can be anticipated to add plant nitrogen
concentrations (Aerts et al., 2009), which proved to be able to
determine vegetation productivity eventually (Walsh et al.,1997). Third, in contrast to snow-end SP, snow-onset SP tends to be able
to better project the variable of snow water equivalent, which serves as
an essentially dependent factor of supporting ecosystem growth and
productivity (Mark et al., 2015). The underlying hydrological
process can also refer to the disentangled mechanisms of winter SP
shifting plant activity in northern ecosystems (Wang et al.,2018). The finding as reviewed above can help to establish the
theoretical basis for developing the EP-SP ecology.
We answered the second question that the Arctic circumpolar EP, indeed,
was more sensitive to the SP around, and further, we noticed that this
sensitivity occurred more to north for the NA but more to south for the
NE. In effect, the findings have basically validated our proposed
conceptual framework – periconnection – for revealing more special
traits in ecology. But in contrast to its initial proposal based on a
simple analogy just from one scheme-similar case, the discussion of
periconnection here needed to cover the potential causes as many as
possible for its theoretical establishment eventually in the future
studies. Substantially, as a derivative from “teleconnection”,
“periconnection” shall feature the same theoretical bases, involving
solar radiative transfers, land surface-atmosphere interactions, and
atmospheric circulations (Mikolajewicz et al., 1997; Allen &
Luptowitz 2017; Mamalakis et al., 2018). The principles in
macroecology can somehow explain the “heterogeneous-response”-causing
eco-effects such as the spatial-heterogeneity effect (Chuine 2000) and
the force-accumulation effect (Walsh et al., 1997). Further, the
possible principles in specific reasoning here may involve the common
drivers making simultaneous effects to EP and SP, e.g., temperature
decreasing driven by wind reaches the thresholds of triggering the
chilling effect (He et al., 2018), and the characterized
directional eco-effect can just verify this hypothesis to some extent.
Totally, the scientific essence of the neighborhood eco-effect is
characterization of the time-lagging eco-effect (Walsh et al.,1997; Chuine 2000; Wu et al., 2015; Lin & Jiang 2017),
alternatively in a spatial way here. As regard to the directional
eco-effect, the phenomena that the NE and NA had contrasting ecosystem
responses to recent climate changes and fire disturbances at the
northern high latitudes were observed, based on remote sensing data and
atmospheric transport model simulations (Goetz et al., 2007). In
other words, atmospheric transports may be a key kind of external
triggers of such directional eco-effects, and hence, taking atmospheric
circulations into account may somehow explain why the EP-SP
sensitivities occurred more to north for the NA but more to south for
the NE. In addition, earlier experiments showed that the circulation
response to maximum Eurasian snowfall is focused downstream in early
winter, whereas upstream response is more evident from the North
American experiments (Henderson et al., 2013). Such mechanisms
may lay a more solid theoretical foundation for periconnection. However,
all of these explanations are still hypothetical inferences, and more
following endeavors shall be made for determining the real causes.
In summary, compared to the endeavors in attempting to attribute the
interannual EP anomalies to the interannual SP variations based on
direct correlations between the same geo-grids (Vaganov et al.,1999; Peng et al., 2013; Wang et al., 2018), this study
taking the SP around into account as well is relatively rare. The new
findings can help people to make a novel step toward more
comprehensively understanding how climate changes affect the
developments of ecosystems. Our inferences can increase some new
macroecological information for improving the performance of
ecosystem-climate-interaction modules in various dynamic global
vegetation models (McCarthy et al., 2012; Murray 2014; Yanget al., 2015; IPCC 2007). However, a lot of endeavors further
need to be conducted to truly set up the new methodological system of
“periconnection”. The statistical analyses operated in this study need
more explorations for reliably exposing the mechanisms of their
performance, and more exploratory analyses (Brown & Robinson 2011) need
to be carried out to explore other kinds of eco-effects for enriching
the theoretical framework of the proposed concept. Moreover, whether the
SP in some particular surrounding geo-grids really alludes the EP
anomalies is still an open question. After all, the impacts of
snow-onset and -end SP on EP have been observed to be nonlinear (Piaoet al., 2016), which further adds the difficulty in just using a
pursuit of statistical relations between the current SP and EP indices
to predict the EP in future climate scenarios. Therefore, well-designed
manipulation experiments are also needed to improve our understanding of
the ecological interactions between EP and SP, and, in a broader sense,
of global carbon balance and ecosystem feedbacks to the ongoing climate
changes.